An Analysis of eHealth Adoption and Utilisation in Kerala 

An Analysis of eHealth Adoption and Utilisation in Kerala | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An Analysis of eHealth Adoption and Utilisation in Kerala Mohammed Asharu Jaman, Bhavya Fernandez, Mahesh N, Veetilakath Jithesh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6427125/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Jul, 2025 Read the published version in Discover Public Health → Version 1 posted 14 You are reading this latest preprint version Abstract Background: Digital transformation in healthcare is gaining momentum globally, with eHealth systems playing a key role in improving service delivery and data integration. Kerala’s eHealth initiative aims to digitalize the state’s public healthcare system by introducing a centralized digital platform to streamline services. Objective: This study aims to determine the extent of eHealth adoption across public healthcare facilities in Kerala and examine its utilisation in service delivery. Methods: A descriptive analysis was conducted using secondary data from the eHealth dashboard and the Directorate of Health Services (DHS). Adoption data from the launch of the program in 2016 to April 2024 were used to assess implementation across districts and facility types. utilisation data, covering May 2023 to April 2024, included outpatient (OPD) visits, inpatient (IP) admissions, laboratory investigations, UHID coverage, and online appointment bookings. Results: As of April 2024, 43.87% of public healthcare facilities in Kerala had adopted the eHealth system. Adoption was highest in Medical Colleges (85.71%) and General Hospitals (70.59%), and lowest in Community Health Centres (11.51%) and Taluk Hospitals (26.14%). During this period, 36.42% of OPD visits and 35.85% of IP admissions were recorded via eHealth. Only 6.7% of lab investigations and 0.87% of OPD visits were processed through online booking. UHID coverage reached 14.89%. Conclusion: While eHealth adoption in Kerala shows promise, key features remain underutilized. Expanding UHID coverage, promoting online services, and strengthening digital infrastructure are essential for realizing the full benefits of healthcare digitalization. eHealth Public Health Digitalisation UHID Digital Health 1. Introduction In the current era of global digital transformation, the healthcare sector is experiencing significant changes with the integration of digital technologies into healthcare systems fundamentally revolutionizing the delivery, management, and accessibility of medical services. This transformation generates momentum toward enhancing efficiency, improving accessibility, and prioritizing patient-centred care as healthcare systems worldwide adapt to evolving demands and complex challenges [ 1 ]. eHealth systems have emerged in many countries as key tools for achieving these goals [ 2 ]. The World Health Organization (WHO) defines eHealth as “the use of information and communications technology in support of health and health-related fields, including services for public health, clinical care, patient education, and health systems management” [ 3 ]. This shift encompasses a broad array of innovations, including electronic health records, telemedicine, artificial intelligence, wearable health technologies, and more [ 4 ]. By leveraging digital infrastructure, healthcare systems can optimize health outcomes and advance the goals of Universal Health Coverage (UHC) [ 5 ]. India’s healthcare system is organised through a decentralised structure, comprising primary care centres (Sub-Health Centres, Primary Health Centres), secondary care centres (Community Health Centres, Sub-District Hospitals, District Hospitals), and tertiary care centres (Medical Colleges, Specialty Hospitals) [ 6 ]. This decentralised framework allows services to be delivered efficiently at different levels of care, depending on the complexity of health needs and helps cater to diverse local populations. The push towards digitalising healthcare has gained momentum in India in recent years. The National Health Policy (NHP) 2017 emphasised the creation of a Digital Health Technology Ecosystem to improve healthcare access, quality, and data integration [ 7 ]. To further these goals, the National Digital Health Blueprint (NDHB) was developed, leading to the launch of the National Digital Health Mission (NDHM) in 2020 [ 8 ]. This initiative was later renamed the Ayushman Bharat Digital Mission (ABDM) in 2021, aiming to create a secure, interoperable digital health ecosystem across India [ 9 ]. As part of the broader global shift toward digital transformation in healthcare, Kerala took a pioneering step ahead of the national initiative by launching its eHealth Project in 2017, to modernize its public health infrastructure. The project was first implemented as a pilot in Trivandrum district in mid-2016 before its official launch. This World Bank-aided project was developed with the support of the Ministry of Electronics and Information Technology (MeitY), Government of India, and the Department of Health and Family Welfare, Government of Kerala [ 10 ]. The project seeks to transform the state's healthcare system by establishing Electronic Health Records (EHR) for all citizens, effectively digitalising and centralizing health-related data. Its primary objective is to streamline hospital operations and develop a centralized state health information system, which facilitates improved continuity of care across government hospitals [ 11 ]. The project was initially piloted in eight healthcare institutions within the Thiruvananthapuram district and has since been proposed for broader implementation across hospitals and clinics under the Department of Medical Education (DME) and the Directorate of Health Services (DHS). This proposed expansion encompasses various modern medicine facilities, including Sub-Health Centres (SHCs), Family Health Centres/Primary Health Centres (FHCs/PHCs), Community Health Centres (CHCs), Taluk Hospitals (THs), District Hospitals (DHs), speciality hospitals, and government medical colleges [ 12 ]. A Centralized data system streamlines patient management, reduces redundancy, facilitates coordinated care and aids in health research [ 13 ]. By creating a centralized state health information system, Kerala’s eHealth initiative aims to enhance the efficiency of healthcare delivery across all levels of care. This digital platform is designed to streamline hospital operations, from patient registration and appointment scheduling to the management of laboratory tests and prescriptions. The introduction of Aadhaar-based Unique Health Identification (UHID) numbers for citizens enables the creation of lifelong health records, which can be accessed by healthcare providers across the state using a secure, OTP-based authentication system [ 11 ]. This interoperability between facilities ensures continuity of care, reduces waiting times, and minimizes the risk of medical errors due to incomplete or inaccessible patient records [ 14 ]. In addition to streamlining administrative processes, the eHealth Project is expected to significantly reduce the burden on healthcare staff, allowing them to focus more on direct patient care rather than administrative tasks. The integration of digital tools also supports better decision-making, enabling healthcare providers to access real-time data and make informed clinical decisions [ 15 ]. The eHealth Project in Kerala was launched in 2017 as a pivotal step towards digitalizing the state's healthcare infrastructure, with the ultimate goal of improving the quality, efficiency, and accessibility of public health services. As of 2024, the project has been in progress for nearly seven years, making it timely and necessary to evaluate how well eHealth has been adopted across the state's public healthcare facilities. This assessment will provide a clearer picture of how digital health systems have evolved in the state over time. The objectives are to determine the extent of eHealth system adoption across public healthcare facilities in the state and to examine how eHealth is utilized in service delivery within these facilities. 2. Methods This study is a descriptive secondary data analysis, asfsessing the utilisation and adoption of the eHealth system in public healthcare facilities across Kerala. The study evaluates data available from May 1, 2023, to April 30, 2024, and provides a district-wise and facility-type-wise breakdown of eHealth adoption and usage trends. Key areas of analysis include UHID coverage, advance bookings through eHealth and online consultations, Outpatient Department (OPD) visits, Inpatient (IP) admissions, and lab investigations. 2.1 Data Sources and Collection Process The data for this study were collected from two primary sources: the eHealth Dashboard and the Directorate of Health Services (DHS). From the eHealth Dashboard, the following datasets were collected for the period from May 1, 2023, to April 30, 2024: eHealth adoption: Data on the number of healthcare facilities adopting eHealth from 2016 to May 2024, disaggregated by district and facility type. eHealth utilisation: Total OPD visits, IP admissions, and lab investigations recorded through the eHealth system for the specified period. Advance bookings and online consultations: Number of UHID cards issued, categorized by district, and the number of advance bookings and online consultations facilitated through the eHealth Portal during the same period. From the Directorate of Health Services (DHS), data was provided on: Healthcare facilities: The total number of public healthcare facilities across Kerala, categorized by district and facility type, which serves as a baseline for calculating eHealth adoption rates. Service utilisation: Total OPD visits, IP admissions, and lab investigations across all public health facilities, both eHealth and non-eHealth utilizing, for the period from May 1, 2023, to April 30, 2024. 2.2 Data Processing and Analysis Once collected, the data was processed and analysed to derive meaningful insights into the adoption and utilisation of the eHealth system; which includes the following domains: eHealth Adoption Rate: Adoption rates were calculated by comparing the number of facilities that implemented eHealth as per data collected from the eHealth dashboard, to the total number of healthcare facilities (from DHS data) based on district and facility-types. Service utilisation: OPD, IP, and Lab utilisation Rates: Calculated as the percentage of services (OPD visits, IP admissions, and lab investigations) recorded through the eHealth system versus the total number of services provided (from DHS data). UHID Coverage: The percentage of the population with UHID cards was calculated by dividing the number of UHIDs issued (from the eHealth dashboard) by the total population of each district (from DHS population data). Advance Bookings and Online Consultations: The number and percentage of OPD visits booked in advance through the eHealth portal and online consultations facilitated were compared with the total OPD visits recorded through the eHealth system. 2.3 Ethical Considerations The study used secondary, aggregated data from publicly available dashboards and government reports. No personal or identifiable patient data were accessed, ensuring full compliance with ethical standards for data privacy and confidentiality. 3. Results The following section presents the findings from the analysis of eHealth uptake and utilisation across public health facilities in Kerala. We focused on various aspects of eHealth integration in the health system, including its use for recording Outpatient Department (OPD) visits, Inpatient (IP) admissions, laboratory investigations, and prescription issuance. Additionally, we also explored the UHID coverage, rates of advance bookings, and online consultations facilitated through the eHealth system. The results will provide insights into the distribution of eHealth utilisation across districts and facility types, highlighting areas with high adoption as well as regions where the system is underutilised. 3.1 eHealth Adoption Status in Kerala 3.1.1 Trend Analysis of eHealth Adoption As seen in Fig. 1 , the adoption of eHealth in public health facilities across Kerala has steadily increased over the years, with fluctuations in growth rates. In 2016, 10 facilities adopted the eHealth system, marking the initial phase of the program. The adoption rate remained low in 2017, with only 3 new facilities coming on board. Starting in 2018, the pace picked up, with the total number of facilities having adopted eHealth increasing to 19 in that year. This upward trend continued into 2019, with a total of 89 facilities adopting the system and in 2020, the number more than doubled to 174 facilities. By 2021, eHealth adoption surged further, reaching a total of 324 facilities, which further increased to 486 facilities by the end of 2022. In 2023, 116 new adoptions were recorded, raising the cumulative total to 602. The 2024 data, representing figures from the initial months of the year, shows 2 additional new adoptions, making a total of 604 institutions. 3.1.2 District-wise eHealth Adoption Status The adoption of the eHealth project in Kerala has been uneven across the 14 districts, with an overall average adoption rate of 43.86%. Thiruvananthapuram, which was one of the first districts to implement the eHealth project, beginning with eight institutions in the first phase when the project started in 2016, stands out as the leader in this effort, with 76.47% of its facilities having adopted eHealth. Thrissur follows with an adoption rate of 56%. Notably, 8 districts, such as Kollam, Pathanamthitta, Alappuzha, Kottayam, Idukki, Palakkad, Kannur, and Kasaragod, have eHealth adoption rates below 40%. A detailed overview of the district-wise eHealth adoption rates is provided in Table 1 . Table 1 District-wise eHealth adoption status District Total number of facilities No. of facilities implemented eHealth Percentage Thiruvananthapuram 136 104 76.47 Kollam 94 31 32.98 Pathanamthitta 67 20 29.85 Alappuzha 97 32 32.99 Kottayam 90 32 35.56 Idukki 63 20 31.75 Ernakulam 131 57 43.51 Thrissur 125 70 56.00 Palakkad 118 45 38.14 Malappuram 135 55 40.74 Kozhikode 105 56 53.33 Wayanad 39 18 46.15 Kannur 116 41 35.34 Kasaragod 61 23 37.70 Kerala 1377 604 43.86 Other districts with adoption rates higher than 40% include Ernakulam, Malappuram, Kozhikode, and Wayanad. 56.14% of the state's healthcare facilities have not yet adopted the eHealth system. 3.1.3 Facility-type-wise eHealth Adoption Status Kerala’s Public healthcare system comprises various types of facilities, each playing a distinct role in providing care at different levels. The adoption rate of eHealth across these facilities varies. As seen in Table 2 , Family Health Centres* 1 and Primary Health Centres (PHC) exhibit a notable eHealth adoption rate of 53.95%. Table 2 Facility -type-wise eHealth Adoption status Type of Facility Total No. of Facilities No. of facilities implemented eHealth Percentage FHC and PHC 849 458 53.95 UPHC 102 50 49.02 CHC 226 26 11.51 TH 88 23 26.14 GH 17 12 70.59 DH 18 7 38.89 Medical College Hospital 14 12 85.72 Specialty Hospital 34 10 29.42 Other 29 6 20.69 Total 1377 604 43.87 Urban Primary Health Centres (UPHC) follow closely with a 49.02% eHealth adoption rate. However, Community Health Centres (CHC) lag with a relatively low adoption rate of 11.51%. Taluk Hospitals and District Hospitals have moderate adoption rates of 26.14% and 38.89%, respectively. In contrast, General Hospitals and Medical College Hospitals have high adoption rates of 70.59% and 85.71%, respectively, setting a benchmark for digital excellence in secondary and tertiary-level healthcare. Specialty Hospitals such as Women and Child Hospital, Coastal Specialty Hospital, Cochin Cancer Centre, and other centres such as Public Health Laboratories and Mental Health Centres have relatively low adoption rates of 29.42% and 20.69%, respectively. 3.1.4 Distribution of Permanent UHID Coverage Across Kerala Districts The Kerala eHealth Project’s introduction of the Permanent Unique Health Identification (UHID) card has been a pivotal step toward streamlining healthcare across the state. The UHID serves as an Aadhar-based unique identifier for every individual and allows access to medical records via OTP-based authentication, viewing prescriptions and lab results, thus providing citizens with a lifelong, Aadhaar-linked health record. This allows seamless access to medical history across all public healthcare facilities, reducing redundant tests and paperwork. It enhances continuity of care, improves data accessibility for providers, streamlines treatment and ensures more efficient and patient-centric healthcare across the state. As of May 2024, 4973912 individuals across Kerala have received their UHID, representing 14.89% of the total population. District-wise UHID distribution data reveals significant variance in coverage across Kerala. Table 3 presents the detailed distribution of UHID cards by district. Table 3 Distribution of Permanent UHID Coverage Across Kerala Districts Districts Total Population (C.2011) Permanent UHID Percentage Thiruvananthapuram 3301427 1211899 36.71 Kollam 2635375 210546 7.99 Pathanamthitta 1197412 184227 15.39 Alappuzha 2127789 284167 13.36 Kottayam 1974551 129836 6.58 Idukki 1108974 175781 15.86 Ernakulam 3282388 219865 6.70 Thrissur 3121200 370991 11.89 Palakkad 2809934 468721 16.69 Malappuram 4112920 807870 19.65 Kozhikode 3086293 337816 10.95 Wayanad 817420 271345 33.20 Kannur 2523003 173605 6.89 Kasaragod 1307375 127243 9.74 Kerala 33406061 4973912 14.89 Thiruvananthapuram stands out with the highest UHID coverage, with 1,211,899 cards issued, representing 36.71% of its population. Wayanad has achieved a high coverage rate of 33.20%, with 271,345 cards issued. Malappuram also shows notable coverage as well, with 807,870 UHID cards distributed, accounting for 19.64% of its total population. Several districts have adoption rates that fall below the state average, such as Kollam, Kottayam, Ernakulam, Kannur, Kasaragod, Thrissur, and Alappuzha. Among these, Kottayam stands out with the lowest rate of 6.58%. 3.2 Service Delivery through eHealth in Kerala 3.2.1 Utilisation of Online advance Booking Services through eHealth District-wise Advance booking is a key feature of the eHealth system, designed to enhance patients’ convenience by allowing them to schedule their appointments online. By logging into their UHID profile, patients can select their preferred doctor and healthcare facility and book available time slots. This system aims to reduce waiting times and streamline the appointment process. Despite the potential benefits of advance booking, its actual utilisation remains minimal. Over the past year, from May 1, 2023, to April 30, 2024, the statewide average for advance bookings through eHealth stands at only 0.87%. During this period, a total of 43,951,175 OPD visits were recorded via the eHealth system, out of which only 381,111 visits were booked in advance. As shown in Table 4 , the utilisation of advance booking through the eHealth system varies significantly across districts in Kerala. Table 4 District-wise utilisation of Online Visits/Advance Booking Through eHealth in Kerala Districts Total OPD Visits through eHealth Online Visits/advance booking through eHealth Percentage Thiruvananthapuram 11759533 244497 2.07 Kollam 2460788 33925 1.38 Pathanamthitta 930884 670 0.07 Alappuzha 2613040 1079 0.04 Kottayam 2172849 8506 0.39 Idukki 740601 1674 0.23 Ernakulam 3512876 42464 1.21 Thrissur 4601645 27014 0.59 Palakkad 1950086 1461 0.07 Malappuram 4475285 1768 0.04 Kozhikode 4543792 13547 0.30 Wayanad 1344823 269 0.02 Kannur 1696110 3841 0.23 Kasaragod 868863 396 0.05 Kerala 43671175 381111 0.87 Thiruvananthapuram led with the highest percentage of advance bookings, approximately 2.07%, with 244,497 out of 11,939,533 OPD visits scheduled online. Conversely, Wayanad has the lowest utilisation, with only 0.02% of OPD visits booked in advance, only 269 out of 1,344,823 visits. Most districts recorded a low utilisation of advance booking through eHealth, with the majority having percentages below 1%. Facility type-wise As shown in Table 5 , only 3.19% of OPD visits in General Hospitals (GH) were booked in advance through the eHealth system, which is the highest percentage among different facility types. Similarly, Medical Colleges (MCH) had 2.06% of their visits scheduled in advance, while Specialty Hospitals (SpH) recorded 1.44% of advance bookings. In the last year, advance bookings in facilities like Family Health Centres (FHC), Urban Primary Health Centres (UPHC), and Community Health Centres (CHC) were all below 1%. Table 5 Facility-wise utilisation of Online Visits/Advance Booking Through eHealth in Kerala. Facility Total OPD Visits through eHealth Online Visits/advance booking through eHealth Percentage FHC 21054097 27255 0.13 UPHC 1183227 480 0.04 CHC 2329069 1646 0.07 TH 4745915 39955 0.84 GH 3641805 116197 3.19 DH 1976762 22572 1.14 MC 7611523 157362 2.07 SpH 895439 12885 1.44 Other 233338 2759 1.18 Total 43671175 381111 0.87 3.2.2 Utilisation of eHealth for Recording OPD Visits District-wise OPD Visits eHealth allows citizens with a permanent UHID to easily manage their health records and book OPD appointments online or directly at facilities. For those without a permanent UHID, a temporary HID is issued to ensure their visit is recorded in the eHealth system. As shown in Table 6 the percentage of OPD visits recorded through eHealth varies significantly across the state, The overall percentage of OPD visits recorded through eHealth in the state stands at 36.42%. Thiruvananthapuram has the highest percentage, with 77.65% of its OPD visits recorded through eHealth. Kozhikode, Thrissur, and Wayanad show adoption rates close to the state average, at 43.36%, 40.25%, and 36.72%, respectively. In contrast, districts such as Kannur and Kasaragod have lower adoption rates, with 17.82% and 19.34% of their OPD visits recorded through eHealth, respectively. Table 6 District-wise utilisation of eHealth for Recording OPD Visits Districts Total OPD Visits OPD Visits recorded through eHealth Percentage Thiruvananthapuram 15143757 11759533 77.65 Kollam 8935286 2460788 27.54 Pathanamthitta 4558508 930884 20.42 Alappuzha 8189852 2613040 31.91 Kottayam 6900445 2172849 31.49 Idukki 3600847 740601 20.57 Ernakulam 10465098 3512876 33.57 Thrissur 11431568 4601645 40.25 Palakkad 8353302 1950086 23.35 Malappuram 14161164 4475285 31.6 Kozhikode 10479459 4543792 43.36 Wayanad 3662194 1344823 36.72 Kannur 9519952 1696110 17.82 Kasaragod 4492610 868863 19.34 Kerala 119894042 43671175 36.42 Facility type-wise OPD Visits The utilisation of eHealth for outpatient department (OPD) visits across different types of healthcare facilities is detailed in Table 8 . The table provides a comprehensive breakdown of how eHealth is employed in recording OPD visits across various facility types. Medical college hospitals (MCH) demonstrated the highest utilisation of eHealth systems, with 94.91% of their total OPD visits recorded digitally, followed by Family Health Centres, at 56.85%, Urban Primary Health Centres (UPHC) at 42.3%, and Speciality Hospitals (SpH) at 37.57%. Table 7 Facility-wise utilisation of eHealth for Recording OPD Visits Facility Total OPD visits Visits recorded through eHealth Percentage FHC 37034358 21054097 56.85 UPHC 2797351 1183227 42.3 CHC 23041626 2329069 10.11 TH 26872179 4745915 17.66 GH 9924817 3641805 36.69 DH 9810571 1976762 20.15 MC 8019789 7611523 94.91 Sph 2383351 895439 37.57 Other Facilities -* 2 233338 - Total 119894042 43671175 36.42 In contrast, Community Health Centres (CHC) have the lowest rate of eHealth utilisation, with only 10.11% of OPD visits recorded through eHealth. Taluk Hospitals and District Hospitals have eHealth recording rates that are lower than the state average of 36.42, while General Hospitals show rates that are almost similar to the state average. 3.2.3 Utilisation of eHealth for Recording IP Admissions A District-wise Analysis of IP Admissions through eHealth in Kerala The utilisation of eHealth systems for recording In-Patient (IP) admissions across districts in Kerala showed significant variation, as detailed in Table 9 . In the last year, Thiruvananthapuram led with 82.09% of IP admissions recorded through eHealth. Alappuzha follows with 63.02% of IP admissions digitally recorded, showcasing significant eHealth adoption in IP admission. Conversely, several districts reported very low, or no IP admissions recorded through eHealth. Districts such as Pathanamthitta, Idukki, Palakkad, Malappuram, Kozhikode, Wayanad, Kannur, and Kasaragod have either minimal or zero recorded admissions via eHealth. The statewide average for IP admissions recorded through eHealth stands at 35.85%. Table 8 District-wise utilisation of eHealth for recording IP admission Districts No. of Total IP admission No. of IP admission recorded through eHealth Percentage Thiruvananthapuram 223181 183220 82.09 Kollam 74980 21035 28.05 Pathanamthitta 33547 0 0.00 Alappuzha 96699 60944 63.02 Kottayam 56158 29549 52.62 Idukki 25056 0 0.00 Ernakulam 88019 27190 30.89 Thrissur 127712 69597 54.50 Palakkad 92605 0 0.00 Malappuram 91654 1 0.00 Kozhikode 69502 2676 3.85 Wayanad 31929 0 0.00 Kannur 54905 0 0.00 Kasaragod 38782 1804 4.65 Kerala 1104729 396016 35.85 Facility type-wise utilisation of eHealth for IP Admission Table 10 summarizes the utilisation of eHealth systems for recording IP admissions across various types of healthcare facilities in Kerala. Since Family Health Centres (FHC) and Urban Primary Health Centres (UPHC) do not typically handle IP admissions, they are not considered in this section. Medical Colleges (MC) demonstrate the highest level of eHealth utilisation for IP admissions, with 83.47% of admissions recorded through eHealth. Table 9 Facility-wise utilisation of eHealth for recording IP admission Facility No. of IP admission No. of IP admission recorded through eHealth Percentage CHC 45590 1083 2.38 TH 233417 2519 1.08 GH 189729 44107 23.25 DH 189263 13334 7.05 MCH 382610 319361 83.47 Sph 61429 15612 25.41 Total 1102038 396016 35.93 General Hospitals (GH) and Speciality Hospitals (SpH) show notable adoption rates at 23.25% and 25.41%, respectively. District Hospital (DH), Community Health Centres (CHC), and Taluk Hospital (TH) have a lower utilisation rate. Most facilities have eHealth utilisation rates for IP admissions below the state average of 35.93%. 3.2.4 Utilisation of eHealth for recording Lab investigations District-wise Lab investigations through eHealth in Kerala As shown in Table 11 , the overall utilisation of eHealth systems for ordering lab investigations across Kerala remains extremely low, with an average of 6.7% of lab investigations recorded through eHealth. Thiruvananthapuram has the highest adoption rate with 19.84% of lab investigations being recorded digitally. Thrissur follows with a utilisation rate of 10.62%. However, several districts report significantly low usage of eHealth for lab investigations. Pathanamthitta shows the lowest rate, with just 2.24% of lab investigations recorded in eHealth. Table 10 District-wise utilisation of eHealth for recording lab investigation Districts No.of total lab investigations No.of lab investigations recorded through eHealth Percentage Thiruvananthapuram 10553545 2093386 19.84 Kollam 7674281 487637 6.35 Pathanamthitta 3520816 78868 2.24 Alappuzha 8631486 261825 3.03 Kottayam 3748532 90167 2.41 Idukki 2704516 73601 2.72 Ernakulam 7758866 335623 4.33 Thrissur 8305773 881805 10.62 Palakkad 6664578 202312 3.04 Malappuram 6180990 233067 3.77 Kozhikode 4759925 329061 6.91 Wayanad 2957063 148933 5.04 Kannur 4093508 125792 3.07 Kasaragod 3367792 75952 2.26 Kerala 80921671 5418029 6.70 Several districts, such as Kozhikode and Kollam, show utilisation rates that are almost similar to the state average of 6.7%. All other districts show utilisation rates below the state average of 6.7%. Facility type-wise utilisation of eHealth for Lab investigations The utilisation of eHealth for lab investigations varies across different healthcare facilities. As seen in Table 12, Family Health Centres (FHC) show the highest adoption, with 16.47% of lab investigations recorded through eHealth. Medical Colleges also display a significant level of utilisation of eHealth, with 12.73% of their lab investigations. Urban Primary Health Centres (UPHC) similarly demonstrate a notable utilisation rate of 7.92%, which is higher than the state average. Table 11 Facility-wise utilisation of eHealth for recording lab investigation Facility No.of total lab investigations No.of lab investigations recorded through eHealth Percentage FHC 12026612 1981353 16.47 UPHC 1557969 123338 7.92 CHC 11589907 231322 2.00 TH 19701479 505965 2.57 GH 11800492 598386 5.07 DH 9551163 146067 1.53 MC 11461760 1459310 12.73 SpH 3232289 95203 2.95 Other -* 3 277085 - Total 80921671 5418029 6.70 Several facilities report lower adoption of eHealth for lab investigations. District Hospitals (DH), Community Health Centres (CHC), Taluk Hospitals (TH), and General Hospitals (GH) all fall below the state average of 6.70%. Although Urban Primary Health Centres (UPHC) report a utilisation rate of 7.92%, which is above the state average. 4. Discussion This study assessed the adoption of eHealth and its utilisation in public health facilities across Kerala between May 2023 and April 2024. The analysis revealed significant progress, as well as considerable disproportionalities in eHealth adoption and usage across districts and facility types. Aligning with the broader vision of digital transformation in healthcare, the state has made significant progress, with 604 of 1,377 healthcare facilities adopting the eHealth system (43.87%). However, the findings reveal substantial disparities across districts and types of healthcare facilities. Family Health Centers (FHCs) and Primary Health Centers (PHCs) demonstrated a higher adoption rate of eHealth (53.95%), which is a positive indicator of digital healthcare reaching grassroots-level facilities. The relatively high adoption in Medical College Hospitals (85.71%) and General Hospitals (70.59%) reinforces the idea that larger, better-resourced institutions tend to lead in the implementation of digital systems. Community Health Centers (CHCs) and Taluk Hospitals (TH) lagged significantly, with adoption rates of 11.51% and 26.14%, respectively. This disparity was anticipated based on previous literature suggesting that smaller and rural facilities often face challenges in adopting digital health technologies due to limited resources and infrastructure [ 17 ]. Moreover, the Aardram scheme primarily focuses on strengthening Family Health Centers (FHCs), which explains the higher adoption rates in FHCs compared to CHCs. At the district level, Thiruvananthapuram (76.47%) led in eHealth adoption, consistent with it being the site of the state's initial pilot rollout, followed by Thrissur (56%), which also demonstrated a high adoption rate. On the other hand, several districts exhibited low adoption, reflecting regional disparities. The lower percentages suggest ongoing challenges in the adoption of eHealth systems, which may include limited digital infrastructure, insufficient staff training, and other barriers to fully implementing a paperless record-keeping system in the state. The incomplete adoption of eHealth across Kerala's public health facilities has hindered the achievement of full interoperability, limiting seamless data exchange and continuity of care [ 17 , 18 ]. The goal of the eHealth initiative is to implement the eHealth system across all 1,377 public health facilities in Kerala and achieving this target is crucial for the comprehensive digital transformation of the healthcare system. Only 36.94% of OPD visits, 35.85% of IP admissions, and 6.7% of lab investigations were recorded through the eHealth system during the study period. These figures suggest that while facilities may have adopted the system, the full potential of digital health services remains untapped. One of the main features of eHealth is the provision for advance bookings to improve patient convenience and reduce waiting times [ 19 ]. However, the findings indicate that these features are severely underutilised, with only 0.87% of OPD visits being booked in advance statewide. This aligns with previous observations, that advance digital healthcare features often see low adoption unless patients and healthcare providers are actively encouraged and educated about their benefits [ 4 , 20 ]. The introduction of Permanent Unique Health Identification (UHID) cards was a key part of the eHealth initiative, aimed at streamlining patient records and improving continuity of care. However, the findings reveal a low UHID coverage, with only 14.89% of Kerala’s population registered by April 2024. This is a significant limitation in the digital health ecosystem, as the UHID system is central to achieving the goal of integrated and seamless healthcare records across facilities. Previous literature has also emphasized the importance of digital identifiers like UHID for the successful implementation of eHealth systems [ 21 ]. Low UHID coverage can limit the full functionality of eHealth, as patients without UHIDs cannot fully leverage the benefits of a unified health record. Addressing this gap requires stronger efforts in public outreach and administrative streamlining to ensure more widespread issuance of UHIDs. 4.1 Implications for Policy and Practice The findings of this study have important implications for healthcare policy and practice in Kerala. To achieve the full potential of the eHealth system, the following areas should be addressed: Strengthening Infrastructure in Underperforming Districts: Districts with low adoption and utilisation rates require targeted interventions, including upgrading technical infrastructure and providing additional support for healthcare staff. Increasing UHID Coverage: Since the UHID system is critical for the integration of health records, accelerating the registration process is essential. Public awareness campaigns and integration of UHID registration into routine healthcare visits could increase coverage. Promoting the Use of Advance Booking and Online Consultations: to promote underutilised advanced features of eHealth, such as online bookings, public education campaigns and incentivizing healthcare workers to encourage patients to use these services can be considered. 4.2 Limitations of the study This study relies on secondary data from the eHealth Dashboard and the Directorate of Health Services, which may contain reporting inconsistencies or gaps, particularly in the completeness of service utilisation data. Additionally, the analysis covers a limited period from May 2023 to April 2024, potentially overlooking longer-term trends or fluctuations in eHealth adoption and utilisation. Another limitation is the lack of qualitative insights into barriers to adoption and utilisation, such as staff readiness, patient awareness, or technical challenges, which could provide a deeper understanding of the underlying factors. These limitations highlight the need for further research to validate findings and explore the perspectives of stakeholders involved in the eHealth system. 5. Conclusion This study highlights significant progress in the adoption and utilisation of the eHealth system in Kerala, with 43.87% of public health facilities having implemented the system as of April 2024. However, this progress in adoption is not reflected uniformly in all facilities under the eHealth framework. While the infrastructure and implementation have expanded across many institutions, significant gaps remain in how effectively these facilities are leveraging the system's features. The considerable disparities persist across districts and facility types, with higher adoption in larger institutions like Medical Colleges and General Hospitals, and lower uptake in Community Health Centers and Taluk Hospitals. The utilisation of key eHealth features, including advance bookings and UHID-based digital records, remains limited, indicating untapped potential in improving healthcare efficiency and continuity of care. Low UHID coverage (14.89%) and minimal usage of advance booking services (0.87%) underscore the need for stronger public outreach, enhanced digital literacy, and improved infrastructure to ensure broader engagement with the system. Achieving full adoption and interoperability of eHealth across all facilities is critical for the comprehensive digital transformation of Kerala's healthcare system, enabling seamless data exchange, equitable access, and enhanced patient outcome. Abbreviations WHO World Health Organization NDHB National Digital Health Blueprint NDHM National Digital Health Mission ABDM Ayushman Bharat Digital Mission EHR Electronic Health Records DME Department of Medical Education DHS Directorate of Health Services FHC Family Health Centre PHC Primary Health Centre CHC Community Health Centre UPHC Urban Primary Health Centre TH Taluk Hospital DH District Hospital GH General Hospital MCH Medical College Hospital SpH Speciality Hospital UHID Unique Health Identification Declarations Funding: Funding was not required as the study used publicly available aggregated data. Clinical Trial Number: Not Applicable. Availability of Data and Materials: This study used two datasets. The first dataset was extracted from the publicly available Kerala eHealth Dashboard, accessible at https://dashboard.health.kerala.gov.in. The second dataset was obtained from the Directorate of Health Services (DHS), Government of Kerala. This dataset is not publicly available due to administrative restrictions but can be obtained from the corresponding author on reasonable request and with permission from DHS. All datasets analysed during this study are with the corresponding author and can be shared upon reasonable request. Corresponding Author: Bhavya Fernandez, email: [email protected] Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare that they have no competing interests. Author Contribution M.A.J., B.F., and V.J. conceptualized and designed the study. M.A.J. collected the data and performed the data analysis.M.A.J. wrote the manuscript and prepared the figures and tables. B.F. and V.J. reviewed and edited the manuscript for intellectual content. M.N. provided a critical review of the final version for accuracy and clarity.All authors read and approved the final version of the manuscript. Acknowledgement The authors would like to thank Ujjwal Shalikrao Kadu, Research Intern at State Health Systems Resource Centre Kerala , for his valuable assistance in data extraction. We also sincerely acknowledge the support and cooperation of our colleagues, Shilpa Sara Abraham and Shwetha Ashok, whose insights and encouragement greatly contributed to the completion of this study. References Xiaoyan G, De Leon JM. Enhancing Patient Experience through Digital Transformation: A Case Study of Outpatient Department Services in Hospitals. Available from: https://ijsea.com/archive/volume13/issue8/IJSEA13081004.pdf Riahi S, Fischler I, Stuckey MI, Klassen PE, Chen J. The value of electronic medical record implementation in mental health care: a case study. JMIR Med Inf. 2017;5(1). 10.2196/medinform.6512 . World Health Organization. - Regional Office for the Eastern Mediterranean [Internet]. [cited 2024 Sep 21]. WHO EMRO | eHealth | Health topics. Available from: http://www.emro.who.int/health-topics/ehealth/ Mumtaz H, Riaz MH, Wajid H, Saqib M, Zeeshan MH, Khan SE, et al. Current challenges and potential solutions to the use of digital health technologies in evidence generation: a narrative review. Front Digit Health. 2023;5:1203945. 10.3389/fdgth.2023.1203945 . Ibeneme S, Karamagi H, Muneene D, Goswami K, Chisaka N, Okeibunor J. Strengthening health systems using innovative digital health technologies in Africa. Front Digit Health. 2022;4:854339. 10.3389/fdgth.2022.854339 . Chokshi M, Patil B, Khanna R, Neogi SB, Sharma J, Paul VK, et al. Health systems in India. J Perinatol. 2016;36(Suppl 3). 10.1038/jp.2016.184 . National Health Policy. 2017. Ministry of Health and Family Welfare, Government of India, 2017.Available from: https://mohfw.gov.in/sites/default/files/9147562941489753121.pdf National Digital Health Mission.Ministry of Health and Family Welfare. Ministry of Electronics and Information Technology, National Health Authority, July 2020.Available from: https://mohfw.gov.in/sites/default/files/9147562941489753121.pdf A Brief Guide on Ayushman Bharat Digital Mission (ABDM) and Its Various Building Blocks . National Health Authority, 21 Dec. 2021.Available from: https://abdm.gov.in:8081/uploads/ABDM_Building_Blocks_v8_3_External_Version_eabbc5c0f3_4_a96f40c645_5716a684de_b344369144.pdf e-health project launch. The Hindu [Internet]. 2017 Jan 23 [cited 2024 Sep 25]; Available from: https://www.thehindu.com/news/national/kerala/e-health-project launch/article17079444.ece About e Health PORTAL. ehealth.kerala.gov.in , State Digital Health Mission,[cited 2024 Sep 25]. Available form: ehealth.kerala.gov.in/ Directorate of Health Services, Kerala. Expression of interest for eHealth initiatives. Thiruvananthapuram: Directorate of Health Services, Kerala. 2013. Available from: https://dhs.kerala.gov.in/wp-content/uploads/2024/04/ehealth.pdf Tariq S, Tariq S, Shoukat AA. Centralized healthcare database for ensuring better healthcare: Are we lagging behind? Pak J Med Sci [Internet]. 2024 [cited 2024 Dec 2];40(3Part-II):257–8. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10862436/ Srivastava SK. Adoption of electronic health records: a roadmap for india. Healthc Inform Res [Internet]. 2016 Oct [cited 2024 Dec 4];22(4):261–9. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116537/ Gopal G, Suter-Crazzolara C, Toldo L, Eberhardt W. Digital transformation in healthcare – architectures of present and future information technologies. Clinical Chemistry and Laboratory Medicine. 2019 Mar 1 [cited 2024 Dec 4];57(3):328–35. Available from: https://www.degruyter.com/document/doi/ 10.1515/cclm-2018-0658/html Kapoor S. Digital Health Ecosystem in India: Present Status, Challenges, and Way Forward. DY Patil Journal of Health Sciences 10(4):p 202–205, Oct–Dec 2022.Available from: https://journals.lww.com/dypj/fulltext/2022/10040/digital_health_ecosystem_in_india__present_status,.10.aspx Powell KR, PhD RN, Alexander CGL, PhD RN et al. Mitigating barriers to interoperability in health care | HIMSS [Internet]. 2019 [cited 2024 Dec 4]. Available from: https://gkc.himss.org/resources/mitigating-barriers-interoperability-health-care Barigela R, Kodali PB, Hense. Sibasis. What is Stopping Primary Health Centers to Go Digital? Findings of a Mixed-method Study at a District Level Health System in Southern India. Indian Journal of Community Medicine 46(1):p 97–101, Jan–Mar 2021. 10.4103/ijcm.IJCM_304_20 Mardiah FP, Basri MH. The analysis of appointment system to reduce outpatient waiting time at Indonesia’s public hospital. Human Resource Management Research [Internet]. 2013 [cited 2024 Dec 4];3(1):27–33. Available from: http://article.sapub.org /10.5923.j.hrmr.20130301.06.html Samadbeik M, Saremian M, Garavand A, Hasanvandi N, Sanaeinasab S, Tahmasebi H. Assessing the online outpatient booking system. Shiraz E-Medical Journal. 2018;19(4).Avaialble from: https://brieflands.com/articles/semj-60249.pdf John S, Hussain I, Aqueel U, Aadhaar. Another milestone for Indian public healthcare information system integration. International Journal of Research and Analytical Reviews. 2019;6(2).Available from: https://www.researchgate.net/profile/Imran-Hussain-11/publication/335920640 ACRONYMS. /ABBREVIATIONS. Footnotes Family Health Centres (FHCs) are expanded forms of Primary Health Centres (PHCs) under the Aardram Mission. These centers typically employ more than one doctor and have a higher number of nursing staff compared to standard PHCs, enhancing their capacity to deliver comprehensive primary healthcare services. * Data for total OPD visits in "Other facilities” is not available. Data for total lab investigations in Other facilities is not available. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6427125","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":455043509,"identity":"db5741cd-3b0f-46da-ad0a-769d44bf2ce9","order_by":0,"name":"Mohammed Asharu Jaman","email":"","orcid":"","institution":"State Health Systems Resource Centre-Kerala","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"Asharu","lastName":"Jaman","suffix":""},{"id":455043510,"identity":"10da0e7a-4d9e-48b8-abde-4450b2708ef5","order_by":1,"name":"Bhavya Fernandez","email":"data:image/png;base64,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","orcid":"","institution":"State Health Systems Resource Centre-Kerala","correspondingAuthor":true,"prefix":"","firstName":"Bhavya","middleName":"","lastName":"Fernandez","suffix":""},{"id":455043511,"identity":"e93dddeb-6321-4a32-9e2b-d0334f774a3c","order_by":2,"name":"Mahesh N","email":"","orcid":"","institution":"Directorate of Health Service- Kerala","correspondingAuthor":false,"prefix":"","firstName":"Mahesh","middleName":"","lastName":"N","suffix":""},{"id":455043512,"identity":"37be67e1-08f7-4b06-8af2-6206ff679a24","order_by":3,"name":"Veetilakath Jithesh","email":"","orcid":"","institution":"State Health Systems Resource Centre-Kerala","correspondingAuthor":false,"prefix":"","firstName":"Veetilakath","middleName":"","lastName":"Jithesh","suffix":""}],"badges":[],"createdAt":"2025-04-11 09:53:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6427125/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6427125/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12982-025-00829-7","type":"published","date":"2025-07-28T16:29:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88268467,"identity":"0794188b-1dcd-44fb-9b0d-29d2ad2df017","added_by":"auto","created_at":"2025-08-04 16:51:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1718024,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6427125/v1/3d674bc7-7bd5-4beb-9600-3851841184fc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An Analysis of eHealth Adoption and Utilisation in Kerala ","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn the current era of global digital transformation, the healthcare sector is experiencing significant changes with the integration of digital technologies into healthcare systems fundamentally revolutionizing the delivery, management, and accessibility of medical services. This transformation generates momentum toward enhancing efficiency, improving accessibility, and prioritizing patient-centred care as healthcare systems worldwide adapt to evolving demands and complex challenges [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. eHealth systems have emerged in many countries as key tools for achieving these goals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The World Health Organization (WHO) defines eHealth as \u0026ldquo;the use of information and communications technology in support of health and health-related fields, including services for public health, clinical care, patient education, and health systems management\u0026rdquo; [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This shift encompasses a broad array of innovations, including electronic health records, telemedicine, artificial intelligence, wearable health technologies, and more [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. By leveraging digital infrastructure, healthcare systems can optimize health outcomes and advance the goals of Universal Health Coverage (UHC) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIndia\u0026rsquo;s healthcare system is organised through a decentralised structure, comprising primary care centres (Sub-Health Centres, Primary Health Centres), secondary care centres (Community Health Centres, Sub-District Hospitals, District Hospitals), and tertiary care centres (Medical Colleges, Specialty Hospitals) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This decentralised framework allows services to be delivered efficiently at different levels of care, depending on the complexity of health needs and helps cater to diverse local populations. The push towards digitalising healthcare has gained momentum in India in recent years. The National Health Policy (NHP) 2017 emphasised the creation of a Digital Health Technology Ecosystem to improve healthcare access, quality, and data integration [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. To further these goals, the National Digital Health Blueprint (NDHB) was developed, leading to the launch of the National Digital Health Mission (NDHM) in 2020 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This initiative was later renamed the Ayushman Bharat Digital Mission (ABDM) in 2021, aiming to create a secure, interoperable digital health ecosystem across India [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs part of the broader global shift toward digital transformation in healthcare, Kerala took a pioneering step ahead of the national initiative by launching its eHealth Project in 2017, to modernize its public health infrastructure. The project was first implemented as a pilot in Trivandrum district in mid-2016 before its official launch. This World Bank-aided project was developed with the support of the Ministry of Electronics and Information Technology (MeitY), Government of India, and the Department of Health and Family Welfare, Government of Kerala [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The project seeks to transform the state's healthcare system by establishing Electronic Health Records (EHR) for all citizens, effectively digitalising and centralizing health-related data. Its primary objective is to streamline hospital operations and develop a centralized state health information system, which facilitates improved continuity of care across government hospitals [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe project was initially piloted in eight healthcare institutions within the Thiruvananthapuram district and has since been proposed for broader implementation across hospitals and clinics under the Department of Medical Education (DME) and the Directorate of Health Services (DHS). This proposed expansion encompasses various modern medicine facilities, including Sub-Health Centres (SHCs), Family Health Centres/Primary Health Centres (FHCs/PHCs), Community Health Centres (CHCs), Taluk Hospitals (THs), District Hospitals (DHs), speciality hospitals, and government medical colleges [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA Centralized data system streamlines patient management, reduces redundancy, facilitates coordinated care and aids in health research [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. By creating a centralized state health information system, Kerala\u0026rsquo;s eHealth initiative aims to enhance the efficiency of healthcare delivery across all levels of care. This digital platform is designed to streamline hospital operations, from patient registration and appointment scheduling to the management of laboratory tests and prescriptions. The introduction of Aadhaar-based Unique Health Identification (UHID) numbers for citizens enables the creation of lifelong health records, which can be accessed by healthcare providers across the state using a secure, OTP-based authentication system [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This interoperability between facilities ensures continuity of care, reduces waiting times, and minimizes the risk of medical errors due to incomplete or inaccessible patient records [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In addition to streamlining administrative processes, the eHealth Project is expected to significantly reduce the burden on healthcare staff, allowing them to focus more on direct patient care rather than administrative tasks. The integration of digital tools also supports better decision-making, enabling healthcare providers to access real-time data and make informed clinical decisions [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe eHealth Project in Kerala was launched in 2017 as a pivotal step towards digitalizing the state's healthcare infrastructure, with the ultimate goal of improving the quality, efficiency, and accessibility of public health services. As of 2024, the project has been in progress for nearly seven years, making it timely and necessary to evaluate how well eHealth has been adopted across the state's public healthcare facilities. This assessment will provide a clearer picture of how digital health systems have evolved in the state over time. The objectives are to determine the extent of eHealth system adoption across public healthcare facilities in the state and to examine how eHealth is utilized in service delivery within these facilities.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eThis study is a descriptive secondary data analysis, asfsessing the utilisation and adoption of the eHealth system in public healthcare facilities across Kerala. The study evaluates data available from May 1, 2023, to April 30, 2024, and provides a district-wise and facility-type-wise breakdown of eHealth adoption and usage trends. Key areas of analysis include UHID coverage, advance bookings through eHealth and online consultations, Outpatient Department (OPD) visits, Inpatient (IP) admissions, and lab investigations.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data Sources and Collection Process\u003c/h2\u003e \u003cp\u003eThe data for this study were collected from two primary sources: the eHealth Dashboard and the Directorate of Health Services (DHS).\u003c/p\u003e \u003cp\u003eFrom the eHealth Dashboard, the following datasets were collected for the period from May 1, 2023, to April 30, 2024:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eeHealth adoption: Data on the number of healthcare facilities adopting eHealth from 2016 to May 2024, disaggregated by district and facility type.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eeHealth utilisation: Total OPD visits, IP admissions, and lab investigations recorded through the eHealth system for the specified period.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAdvance bookings and online consultations: Number of UHID cards issued, categorized by district, and the number of advance bookings and online consultations facilitated through the eHealth Portal during the same period.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eFrom the Directorate of Health Services (DHS), data was provided on:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eHealthcare facilities: The total number of public healthcare facilities across Kerala, categorized by district and facility type, which serves as a baseline for calculating eHealth adoption rates.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eService utilisation: Total OPD visits, IP admissions, and lab investigations across all public health facilities, both eHealth and non-eHealth utilizing, for the period from May 1, 2023, to April 30, 2024.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data Processing and Analysis\u003c/h2\u003e \u003cp\u003eOnce collected, the data was processed and analysed to derive meaningful insights into the adoption and utilisation of the eHealth system; which includes the following domains:\u003c/p\u003e \u003cp\u003eeHealth Adoption Rate: Adoption rates were calculated by comparing the number of facilities that implemented eHealth as per data collected from the eHealth dashboard, to the total number of healthcare facilities (from DHS data) based on district and facility-types.\u003c/p\u003e \u003cp\u003eService utilisation: OPD, IP, and Lab utilisation Rates: Calculated as the percentage of services (OPD visits, IP admissions, and lab investigations) recorded through the eHealth system versus the total number of services provided (from DHS data).\u003c/p\u003e \u003cp\u003eUHID Coverage: The percentage of the population with UHID cards was calculated by dividing the number of UHIDs issued (from the eHealth dashboard) by the total population of each district (from DHS population data).\u003c/p\u003e \u003cp\u003eAdvance Bookings and Online Consultations: The number and percentage of OPD visits booked in advance through the eHealth portal and online consultations facilitated were compared with the total OPD visits recorded through the eHealth system.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Ethical Considerations\u003c/h2\u003e \u003cp\u003eThe study used secondary, aggregated data from publicly available dashboards and government reports. No personal or identifiable patient data were accessed, ensuring full compliance with ethical standards for data privacy and confidentiality.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe following section presents the findings from the analysis of eHealth uptake and utilisation across public health facilities in Kerala.\u003c/p\u003e \u003cp\u003eWe focused on various aspects of eHealth integration in the health system, including its use for recording Outpatient Department (OPD) visits, Inpatient (IP) admissions, laboratory investigations, and prescription issuance. Additionally, we also explored the UHID coverage, rates of advance bookings, and online consultations facilitated through the eHealth system. The results will provide insights into the distribution of eHealth utilisation across districts and facility types, highlighting areas with high adoption as well as regions where the system is underutilised.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 eHealth Adoption Status in Kerala\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1 Trend Analysis of eHealth Adoption\u003c/h2\u003e \u003cp\u003eAs seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the adoption of eHealth in public health facilities across Kerala has steadily increased over the years, with fluctuations in growth rates. In 2016, 10 facilities adopted the eHealth system, marking the initial phase of the program. The adoption rate remained low in 2017, with only 3 new facilities coming on board. Starting in 2018, the pace picked up, with the total number of facilities having adopted eHealth increasing to 19 in that year.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis upward trend continued into 2019, with a total of 89 facilities adopting the system and in 2020, the number more than doubled to 174 facilities. By 2021, eHealth adoption surged further, reaching a total of 324 facilities, which further increased to 486 facilities by the end of 2022. In 2023, 116 new adoptions were recorded, raising the cumulative total to 602. The 2024 data, representing figures from the initial months of the year, shows 2 additional new adoptions, making a total of 604 institutions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 District-wise eHealth Adoption Status\u003c/h2\u003e \u003cp\u003eThe adoption of the eHealth project in Kerala has been uneven across the 14 districts, with an overall average adoption rate of 43.86%. Thiruvananthapuram, which was one of the first districts to implement the eHealth project, beginning with eight institutions in the first phase when the project started in 2016, stands out as the leader in this effort, with 76.47% of its facilities having adopted eHealth. Thrissur follows with an adoption rate of 56%. Notably, 8 districts, such as Kollam, Pathanamthitta, Alappuzha, Kottayam, Idukki, Palakkad, Kannur, and Kasaragod, have eHealth adoption rates below 40%. A detailed overview of the district-wise eHealth adoption rates is provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistrict-wise eHealth adoption status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistrict\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal number of facilities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of facilities implemented eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiruvananthapuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKollam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathanamthitta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlappuzha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKottayam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIdukki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErnakulam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrissur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalakkad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalappuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKozhikode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWayanad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKannur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKasaragod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKerala\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1377\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e604\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e43.86\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOther districts with adoption rates higher than 40% include Ernakulam, Malappuram, Kozhikode, and Wayanad. 56.14% of the state's healthcare facilities have not yet adopted the eHealth system.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 Facility-type-wise eHealth Adoption Status\u003c/h2\u003e \u003cp\u003eKerala\u0026rsquo;s Public healthcare system comprises various types of facilities, each playing a distinct role in providing care at different levels. The adoption rate of eHealth across these facilities varies. As seen in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Family Health Centres*\u003csup\u003e1\u003c/sup\u003e and Primary Health Centres (PHC) exhibit a notable eHealth adoption rate of 53.95%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFacility -type-wise eHealth Adoption status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of Facility\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal No. of Facilities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of facilities implemented eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFHC and PHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUPHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical College Hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecialty Hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1377\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e604\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e43.87\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eUrban Primary Health Centres (UPHC) follow closely with a 49.02% eHealth adoption rate. However, Community Health Centres (CHC) lag with a relatively low adoption rate of 11.51%. Taluk Hospitals and District Hospitals have moderate adoption rates of 26.14% and 38.89%, respectively. In contrast, General Hospitals and Medical College Hospitals have high adoption rates of 70.59% and 85.71%, respectively, setting a benchmark for digital excellence in secondary and tertiary-level healthcare. Specialty Hospitals such as Women and Child Hospital, Coastal Specialty Hospital, Cochin Cancer Centre, and other centres such as Public Health Laboratories and Mental Health Centres have relatively low adoption rates of 29.42% and 20.69%, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.1.4 Distribution of Permanent UHID Coverage Across Kerala Districts\u003c/h2\u003e \u003cp\u003eThe Kerala eHealth Project\u0026rsquo;s introduction of the Permanent Unique Health Identification (UHID) card has been a pivotal step toward streamlining healthcare across the state. The UHID serves as an Aadhar-based unique identifier for every individual and allows access to medical records via OTP-based authentication, viewing prescriptions and lab results, thus providing citizens with a lifelong, Aadhaar-linked health record. This allows seamless access to medical history across all public healthcare facilities, reducing redundant tests and paperwork. It enhances continuity of care, improves data accessibility for providers, streamlines treatment and ensures more efficient and patient-centric healthcare across the state. As of May 2024, 4973912 individuals across Kerala have received their UHID, representing 14.89% of the total population. District-wise UHID distribution data reveals significant variance in coverage across Kerala. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the detailed distribution of UHID cards by district.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Permanent UHID Coverage Across Kerala Districts\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistricts\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Population (C.2011)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePermanent UHID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiruvananthapuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3301427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1211899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKollam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2635375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e210546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathanamthitta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1197412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e184227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlappuzha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2127789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e284167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKottayam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1974551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e129836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIdukki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1108974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErnakulam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3282388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e219865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrissur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3121200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e370991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalakkad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2809934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e468721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalappuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4112920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e807870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKozhikode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3086293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e337816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWayanad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e817420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e271345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKannur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2523003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e173605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKasaragod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1307375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e127243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKerala\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e33406061\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4973912\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e14.89\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThiruvananthapuram stands out with the highest UHID coverage, with 1,211,899 cards issued, representing 36.71% of its population. Wayanad has achieved a high coverage rate of 33.20%, with 271,345 cards issued. Malappuram also shows notable coverage as well, with 807,870 UHID cards distributed, accounting for 19.64% of its total population. Several districts have adoption rates that fall below the state average, such as Kollam, Kottayam, Ernakulam, Kannur, Kasaragod, Thrissur, and Alappuzha. Among these, Kottayam stands out with the lowest rate of 6.58%.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Service Delivery through eHealth in Kerala\u003c/h2\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 Utilisation of Online advance Booking Services through eHealth\u003c/h2\u003e \u003cp\u003e \u003cb\u003eDistrict-wise\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAdvance booking is a key feature of the eHealth system, designed to enhance patients\u0026rsquo; convenience by allowing them to schedule their appointments online. By logging into their UHID profile, patients can select their preferred doctor and healthcare facility and book available time slots. This system aims to reduce waiting times and streamline the appointment process. Despite the potential benefits of advance booking, its actual utilisation remains minimal. Over the past year, from May 1, 2023, to April 30, 2024, the statewide average for advance bookings through eHealth stands at only 0.87%. During this period, a total of 43,951,175 OPD visits were recorded via the eHealth system, out of which only 381,111 visits were booked in advance. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the utilisation of advance booking through the eHealth system varies significantly across districts in Kerala.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistrict-wise utilisation of Online Visits/Advance Booking Through eHealth in Kerala\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistricts\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal OPD Visits through eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnline Visits/advance booking through eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiruvananthapuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11759533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e244497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKollam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2460788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathanamthitta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e930884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlappuzha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2613040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKottayam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2172849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIdukki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e740601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErnakulam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3512876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrissur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4601645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalakkad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1950086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalappuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4475285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKozhikode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4543792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWayanad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1344823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKannur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1696110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKasaragod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e868863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKerala\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e43671175\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e381111\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.87\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThiruvananthapuram led with the highest percentage of advance bookings, approximately 2.07%, with 244,497 out of 11,939,533 OPD visits scheduled online. Conversely, Wayanad has the lowest utilisation, with only 0.02% of OPD visits booked in advance, only 269 out of 1,344,823 visits. Most districts recorded a low utilisation of advance booking through eHealth, with the majority having percentages below 1%.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFacility type-wise\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, only 3.19% of OPD visits in General Hospitals (GH) were booked in advance through the eHealth system, which is the highest percentage among different facility types. Similarly, Medical Colleges (MCH) had 2.06% of their visits scheduled in advance, while Specialty Hospitals (SpH) recorded 1.44% of advance bookings. In the last year, advance bookings in facilities like Family Health Centres (FHC), Urban Primary Health Centres (UPHC), and Community Health Centres (CHC) were all below 1%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFacility-wise utilisation of Online Visits/Advance Booking Through eHealth in Kerala.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal OPD Visits through eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnline Visits/advance booking through eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21054097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUPHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1183227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2329069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4745915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3641805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1976762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7611523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e157362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e895439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e233338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e43671175\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e381111\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.87\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 Utilisation of eHealth for Recording OPD Visits\u003c/h2\u003e \u003cp\u003e \u003cb\u003eDistrict-wise OPD Visits\u003c/b\u003e \u003c/p\u003e \u003cp\u003eeHealth allows citizens with a permanent UHID to easily manage their health records and book OPD appointments online or directly at facilities. For those without a permanent UHID, a temporary HID is issued to ensure their visit is recorded in the eHealth system. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e the percentage of OPD visits recorded through eHealth varies significantly across the state, The overall percentage of OPD visits recorded through eHealth in the state stands at 36.42%. Thiruvananthapuram has the highest percentage, with 77.65% of its OPD visits recorded through eHealth. Kozhikode, Thrissur, and Wayanad show adoption rates close to the state average, at 43.36%, 40.25%, and 36.72%, respectively. In contrast, districts such as Kannur and Kasaragod have lower adoption rates, with 17.82% and 19.34% of their OPD visits recorded through eHealth, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistrict-wise utilisation of eHealth for Recording OPD Visits\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistricts\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal OPD Visits\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOPD Visits recorded through eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiruvananthapuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15143757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11759533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKollam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8935286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2460788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathanamthitta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4558508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e930884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlappuzha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8189852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2613040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKottayam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6900445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2172849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIdukki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3600847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e740601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErnakulam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10465098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3512876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrissur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11431568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4601645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalakkad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8353302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1950086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalappuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14161164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4475285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKozhikode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10479459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4543792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWayanad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3662194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1344823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKannur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9519952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1696110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKasaragod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4492610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e868863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKerala\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e119894042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e43671175\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e36.42\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFacility type-wise OPD Visits\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe utilisation of eHealth for outpatient department (OPD) visits across different types of healthcare facilities is detailed in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. The table provides a comprehensive breakdown of how eHealth is employed in recording OPD visits across various facility types. Medical college hospitals (MCH) demonstrated the highest utilisation of eHealth systems, with 94.91% of their total OPD visits recorded digitally, followed by Family Health Centres, at 56.85%, Urban Primary Health Centres (UPHC) at 42.3%, and Speciality Hospitals (SpH) at 37.57%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFacility-wise utilisation of eHealth for Recording OPD Visits\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal OPD visits\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVisits recorded through eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37034358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21054097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUPHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2797351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1183227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23041626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2329069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26872179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4745915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9924817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3641805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9810571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1976762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8019789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7611523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSph\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2383351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e895439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-*\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e233338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e119894042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e43671175\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e36.42\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn contrast, Community Health Centres (CHC) have the lowest rate of eHealth utilisation, with only 10.11% of OPD visits recorded through eHealth. Taluk Hospitals and District Hospitals have eHealth recording rates that are lower than the state average of 36.42, while General Hospitals show rates that are almost similar to the state average.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3 Utilisation of eHealth for Recording IP Admissions\u003c/h2\u003e \u003cp\u003e \u003cb\u003eA District-wise Analysis of IP Admissions through eHealth in Kerala\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe utilisation of eHealth systems for recording In-Patient (IP) admissions across districts in Kerala showed significant variation, as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. In the last year, Thiruvananthapuram led with 82.09% of IP admissions recorded through eHealth. Alappuzha follows with 63.02% of IP admissions digitally recorded, showcasing significant eHealth adoption in IP admission. Conversely, several districts reported very low, or no IP admissions recorded through eHealth. Districts such as Pathanamthitta, Idukki, Palakkad, Malappuram, Kozhikode, Wayanad, Kannur, and Kasaragod have either minimal or zero recorded admissions via eHealth. The statewide average for IP admissions recorded through eHealth stands at 35.85%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistrict-wise utilisation of eHealth for recording IP admission\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistricts\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo. of Total IP admission\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of IP admission recorded through eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiruvananthapuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e223181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e183220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKollam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathanamthitta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlappuzha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKottayam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29549\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIdukki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErnakulam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrissur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e127712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalakkad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalappuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKozhikode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWayanad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKannur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKasaragod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKerala\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1104729\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e396016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e35.85\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFacility type-wise utilisation of eHealth for IP Admission\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e summarizes the utilisation of eHealth systems for recording IP admissions across various types of healthcare facilities in Kerala. Since Family Health Centres (FHC) and Urban Primary Health Centres (UPHC) do not typically handle IP admissions, they are not considered in this section. Medical Colleges (MC) demonstrate the highest level of eHealth utilisation for IP admissions, with 83.47% of admissions recorded through eHealth.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFacility-wise utilisation of eHealth for recording IP admission\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo. of IP admission\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of IP admission recorded through eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e233417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e189729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e189263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e382610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e319361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSph\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1102038\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e396016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e35.93\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eGeneral Hospitals (GH) and Speciality Hospitals (SpH) show notable adoption rates at 23.25% and 25.41%, respectively. District Hospital (DH), Community Health Centres (CHC), and Taluk Hospital (TH) have a lower utilisation rate. Most facilities have eHealth utilisation rates for IP admissions below the state average of 35.93%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.2.4 Utilisation of eHealth for recording Lab investigations\u003c/h2\u003e \u003cp\u003e \u003cb\u003eDistrict-wise Lab investigations through eHealth in Kerala\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e, the overall utilisation of eHealth systems for ordering lab investigations across Kerala remains extremely low, with an average of 6.7% of lab investigations recorded through eHealth. Thiruvananthapuram has the highest adoption rate with 19.84% of lab investigations being recorded digitally. Thrissur follows with a utilisation rate of 10.62%. However, several districts report significantly low usage of eHealth for lab investigations. Pathanamthitta shows the lowest rate, with just 2.24% of lab investigations recorded in eHealth.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistrict-wise utilisation of eHealth for recording lab investigation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistricts\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.of total lab investigations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.of lab investigations recorded through eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThiruvananthapuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10553545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2093386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKollam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7674281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e487637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathanamthitta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3520816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlappuzha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8631486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e261825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKottayam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3748532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIdukki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2704516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErnakulam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7758866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e335623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrissur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8305773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e881805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalakkad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6664578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e202312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalappuram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6180990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e233067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKozhikode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4759925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e329061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWayanad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2957063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e148933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKannur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4093508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKasaragod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3367792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKerala\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e80921671\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5418029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSeveral districts, such as Kozhikode and Kollam, show utilisation rates that are almost similar to the state average of 6.7%. All other districts show utilisation rates below the state average of 6.7%.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFacility type-wise utilisation of eHealth for Lab investigations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe utilisation of eHealth for lab investigations varies across different healthcare facilities. As seen in Table\u0026nbsp;12, Family Health Centres (FHC) show the highest adoption, with 16.47% of lab investigations recorded through eHealth. Medical Colleges also display a significant level of utilisation of eHealth, with 12.73% of their lab investigations. Urban Primary Health Centres (UPHC) similarly demonstrate a notable utilisation rate of 7.92%, which is higher than the state average.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFacility-wise utilisation of eHealth for recording lab investigation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.of total lab investigations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.of lab investigations recorded through eHealth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12026612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1981353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUPHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1557969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11589907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e231322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19701479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e505965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11800492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e598386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9551163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e146067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11461760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1459310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3232289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-*\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e277085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e80921671\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5418029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSeveral facilities report lower adoption of eHealth for lab investigations. District Hospitals (DH), Community Health Centres (CHC), Taluk Hospitals (TH), and General Hospitals (GH) all fall below the state average of 6.70%. Although Urban Primary Health Centres (UPHC) report a utilisation rate of 7.92%, which is above the state average.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study assessed the adoption of eHealth and its utilisation in public health facilities across Kerala between May 2023 and April 2024. The analysis revealed significant progress, as well as considerable disproportionalities in eHealth adoption and usage across districts and facility types. Aligning with the broader vision of digital transformation in healthcare, the state has made significant progress, with 604 of 1,377 healthcare facilities adopting the eHealth system (43.87%). However, the findings reveal substantial disparities across districts and types of healthcare facilities.\u003c/p\u003e \u003cp\u003eFamily Health Centers (FHCs) and Primary Health Centers (PHCs) demonstrated a higher adoption rate of eHealth (53.95%), which is a positive indicator of digital healthcare reaching grassroots-level facilities. The relatively high adoption in Medical College Hospitals (85.71%) and General Hospitals (70.59%) reinforces the idea that larger, better-resourced institutions tend to lead in the implementation of digital systems. Community Health Centers (CHCs) and Taluk Hospitals (TH) lagged significantly, with adoption rates of 11.51% and 26.14%, respectively. This disparity was anticipated based on previous literature suggesting that smaller and rural facilities often face challenges in adopting digital health technologies due to limited resources and infrastructure [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Moreover, the Aardram scheme primarily focuses on strengthening Family Health Centers (FHCs), which explains the higher adoption rates in FHCs compared to CHCs. At the district level, Thiruvananthapuram (76.47%) led in eHealth adoption, consistent with it being the site of the state's initial pilot rollout, followed by Thrissur (56%), which also demonstrated a high adoption rate. On the other hand, several districts exhibited low adoption, reflecting regional disparities. The lower percentages suggest ongoing challenges in the adoption of eHealth systems, which may include limited digital infrastructure, insufficient staff training, and other barriers to fully implementing a paperless record-keeping system in the state. The incomplete adoption of eHealth across Kerala's public health facilities has hindered the achievement of full interoperability, limiting seamless data exchange and continuity of care [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The goal of the eHealth initiative is to implement the eHealth system across all 1,377 public health facilities in Kerala and achieving this target is crucial for the comprehensive digital transformation of the healthcare system.\u003c/p\u003e \u003cp\u003eOnly 36.94% of OPD visits, 35.85% of IP admissions, and 6.7% of lab investigations were recorded through the eHealth system during the study period. These figures suggest that while facilities may have adopted the system, the full potential of digital health services remains untapped. One of the main features of eHealth is the provision for advance bookings to improve patient convenience and reduce waiting times [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, the findings indicate that these features are severely underutilised, with only 0.87% of OPD visits being booked in advance statewide. This aligns with previous observations, that advance digital healthcare features often see low adoption unless patients and healthcare providers are actively encouraged and educated about their benefits [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe introduction of Permanent Unique Health Identification (UHID) cards was a key part of the eHealth initiative, aimed at streamlining patient records and improving continuity of care. However, the findings reveal a low UHID coverage, with only 14.89% of Kerala\u0026rsquo;s population registered by April 2024. This is a significant limitation in the digital health ecosystem, as the UHID system is central to achieving the goal of integrated and seamless healthcare records across facilities. Previous literature has also emphasized the importance of digital identifiers like UHID for the successful implementation of eHealth systems [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Low UHID coverage can limit the full functionality of eHealth, as patients without UHIDs cannot fully leverage the benefits of a unified health record. Addressing this gap requires stronger efforts in public outreach and administrative streamlining to ensure more widespread issuance of UHIDs.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Implications for Policy and Practice\u003c/h2\u003e \u003cp\u003eThe findings of this study have important implications for healthcare policy and practice in Kerala. To achieve the full potential of the eHealth system, the following areas should be addressed:\u003c/p\u003e \u003cp\u003eStrengthening Infrastructure in Underperforming Districts: Districts with low adoption and utilisation rates require targeted interventions, including upgrading technical infrastructure and providing additional support for healthcare staff.\u003c/p\u003e \u003cp\u003eIncreasing UHID Coverage: Since the UHID system is critical for the integration of health records, accelerating the registration process is essential. Public awareness campaigns and integration of UHID registration into routine healthcare visits could increase coverage.\u003c/p\u003e \u003cp\u003ePromoting the Use of Advance Booking and Online Consultations: to promote underutilised advanced features of eHealth, such as online bookings, public education campaigns and incentivizing healthcare workers to encourage patients to use these services can be considered.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Limitations of the study\u003c/h2\u003e \u003cp\u003eThis study relies on secondary data from the eHealth Dashboard and the Directorate of Health Services, which may contain reporting inconsistencies or gaps, particularly in the completeness of service utilisation data. Additionally, the analysis covers a limited period from May 2023 to April 2024, potentially overlooking longer-term trends or fluctuations in eHealth adoption and utilisation. Another limitation is the lack of qualitative insights into barriers to adoption and utilisation, such as staff readiness, patient awareness, or technical challenges, which could provide a deeper understanding of the underlying factors. These limitations highlight the need for further research to validate findings and explore the perspectives of stakeholders involved in the eHealth system.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study highlights significant progress in the adoption and utilisation of the eHealth system in Kerala, with 43.87% of public health facilities having implemented the system as of April 2024. However, this progress in adoption is not reflected uniformly in all facilities under the eHealth framework. While the infrastructure and implementation have expanded across many institutions, significant gaps remain in how effectively these facilities are leveraging the system's features. The considerable disparities persist across districts and facility types, with higher adoption in larger institutions like Medical Colleges and General Hospitals, and lower uptake in Community Health Centers and Taluk Hospitals. The utilisation of key eHealth features, including advance bookings and UHID-based digital records, remains limited, indicating untapped potential in improving healthcare efficiency and continuity of care. Low UHID coverage (14.89%) and minimal usage of advance booking services (0.87%) underscore the need for stronger public outreach, enhanced digital literacy, and improved infrastructure to ensure broader engagement with the system. Achieving full adoption and interoperability of eHealth across all facilities is critical for the comprehensive digital transformation of Kerala's healthcare system, enabling seamless data exchange, equitable access, and enhanced patient outcome.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eWHO\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eWorld Health Organization\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNDHB\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eNational Digital Health Blueprint\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNDHM\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eNational Digital Health Mission\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eABDM\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eAyushman Bharat Digital Mission\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eEHR\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eElectronic Health Records\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eDME\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eDepartment of Medical Education\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eDHS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eDirectorate of Health Services\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eFHC\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eFamily Health Centre\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ePHC\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003ePrimary Health Centre\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCHC\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eCommunity Health Centre\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eUPHC\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eUrban Primary Health Centre\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eTH\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eTaluk Hospital\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eDH\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eDistrict Hospital\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eGH\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eGeneral Hospital\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eMCH\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eMedical College Hospital\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eSpH\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eSpeciality Hospital\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eUHID\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eUnique Health Identification\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003cbr/\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eFunding was not required as the study used publicly available aggregated data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:\u0026nbsp;\u003c/strong\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials:\u0026nbsp;\u003c/strong\u003eThis study used two datasets. The first dataset was extracted from the publicly available Kerala eHealth Dashboard, accessible at https://dashboard.health.kerala.gov.in. The second dataset was obtained from the Directorate of Health Services (DHS), Government of Kerala. This dataset is not publicly available due to administrative restrictions but can be obtained from the corresponding author on reasonable request and with permission from DHS. All datasets analysed during this study are with the corresponding author and can be shared upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding Author:\u0026nbsp;\u003c/strong\u003eBhavya Fernandez, email: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM.A.J., B.F., and V.J. conceptualized and designed the study. M.A.J. collected the data and performed the data analysis.M.A.J. wrote the manuscript and prepared the figures and tables. B.F. and V.J. reviewed and edited the manuscript for intellectual content. M.N. provided a critical review of the final version for accuracy and clarity.All authors read and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank Ujjwal Shalikrao Kadu, Research Intern at State Health Systems Resource Centre Kerala , for his valuable assistance in data extraction. We also sincerely acknowledge the support and cooperation of our colleagues, Shilpa Sara Abraham and Shwetha Ashok, whose insights and encouragement greatly contributed to the completion of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eXiaoyan G, De Leon JM. Enhancing Patient Experience through Digital Transformation: A Case Study of Outpatient Department Services in Hospitals. 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Digital transformation in healthcare \u0026ndash; architectures of present and future information technologies. Clinical Chemistry and Laboratory Medicine. 2019 Mar 1 [cited 2024 Dec 4];57(3):328\u0026ndash;35. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.degruyter.com/document/doi/\u003c/span\u003e\u003cspan address=\"https://www.degruyter.com/document/doi/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1515/cclm-2018-0658/html\u003c/span\u003e\u003cspan address=\"10.1515/cclm-2018-0658/html\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKapoor S. Digital Health Ecosystem in India: Present Status, Challenges, and Way Forward. DY Patil Journal of Health Sciences 10(4):p 202\u0026ndash;205, Oct\u0026ndash;Dec 2022.Available from:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://journals.lww.com/dypj/fulltext/2022/10040/digital_health_ecosystem_in_india__present_status,.10.aspx\u003c/span\u003e\u003cspan address=\"https://journals.lww.com/dypj/fulltext/2022/10040/digital_health_ecosystem_in_india__present_status,.10.aspx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePowell KR, PhD RN, Alexander CGL, PhD RN et al. Mitigating barriers to interoperability in health care | HIMSS [Internet]. 2019 [cited 2024 Dec 4]. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://article.sapub.org\u003c/span\u003e\u003cspan address=\"http://article.sapub.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e/10.5923.j.hrmr.20130301.06.html\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSamadbeik M, Saremian M, Garavand A, Hasanvandi N, Sanaeinasab S, Tahmasebi H. Assessing the online outpatient booking system. Shiraz E-Medical Journal. 2018;19(4).Avaialble from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://brieflands.com/articles/semj-60249.pdf\u003c/span\u003e\u003cspan address=\"https://brieflands.com/articles/semj-60249.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohn S, Hussain I, Aqueel U, Aadhaar. Another milestone for Indian public healthcare information system integration. International Journal of Research and Analytical Reviews. 2019;6(2).Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.researchgate.net/profile/Imran-Hussain-11/publication/335920640\u003c/span\u003e\u003cspan address=\"https://www.researchgate.net/profile/Imran-Hussain-11/publication/335920640\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eACRONYMS. /ABBREVIATIONS.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e \u003cb\u003eFamily Health Centres (FHCs)\u003c/b\u003e are expanded forms of Primary Health Centres (PHCs) under the Aardram Mission. These centers typically employ more than one doctor and have a higher number of nursing staff compared to standard PHCs, enhancing their capacity to deliver comprehensive primary healthcare services.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e* Data for total OPD visits in \"Other facilities\u0026rdquo; is not available.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Data for total lab investigations in Other facilities is not available.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"eHealth, Public Health Digitalisation, UHID, Digital Health","lastPublishedDoi":"10.21203/rs.3.rs-6427125/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6427125/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Digital transformation in healthcare is gaining momentum globally, with eHealth systems playing a key role in improving service delivery and data integration. Kerala’s eHealth initiative aims to digitalize the state’s public healthcare system by introducing a centralized digital platform to streamline services.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThis study aims to determine the extent of eHealth adoption across public healthcare facilities in Kerala and examine its utilisation in service delivery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA descriptive analysis was conducted using secondary data from the eHealth dashboard and the Directorate of Health Services (DHS). Adoption data from the launch of the program in 2016 to April 2024 were used to assess implementation across districts and facility types. utilisation data, covering May 2023 to April 2024, included outpatient (OPD) visits, inpatient (IP) admissions, laboratory investigations, UHID coverage, and online appointment bookings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAs of April 2024, 43.87% of public healthcare facilities in Kerala had adopted the eHealth system. Adoption was highest in Medical Colleges (85.71%) and General Hospitals (70.59%), and lowest in Community Health Centres (11.51%) and Taluk Hospitals (26.14%). During this period, 36.42% of OPD visits and 35.85% of IP admissions were recorded via eHealth. Only 6.7% of lab investigations and 0.87% of OPD visits were processed through online booking. UHID coverage reached 14.89%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eWhile eHealth adoption in Kerala shows promise, key features remain underutilized. Expanding UHID coverage, promoting online services, and strengthening digital infrastructure are essential for realizing the full benefits of healthcare digitalization.\u003c/p\u003e","manuscriptTitle":"An Analysis of eHealth Adoption and Utilisation in Kerala ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 10:10:42","doi":"10.21203/rs.3.rs-6427125/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-27T16:59:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-19T11:07:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"185623957749687405365956047345306185026","date":"2025-05-14T06:13:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37283119760790231758746310440568267973","date":"2025-05-14T00:31:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-12T03:11:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-10T11:55:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"328966953523400875938873077342941554101","date":"2025-05-09T04:20:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272378793605271522157737257953438103767","date":"2025-05-08T13:28:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"340036693134630551800087662776699278406","date":"2025-05-08T12:24:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"103934520896133763079136377789783576218","date":"2025-05-08T09:56:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-08T09:13:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-05T08:28:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-05T05:43:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2025-05-05T05:42:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d0aa1dc3-d14d-4667-8325-9278e5793a64","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-04T16:47:27+00:00","versionOfRecord":{"articleIdentity":"rs-6427125","link":"https://doi.org/10.1186/s12982-025-00829-7","journal":{"identity":"discover-public-health","isVorOnly":false,"title":"Discover Public Health"},"publishedOn":"2025-07-28 16:29:10","publishedOnDateReadable":"July 28th, 2025"},"versionCreatedAt":"2025-05-13 10:10:42","video":"","vorDoi":"10.1186/s12982-025-00829-7","vorDoiUrl":"https://doi.org/10.1186/s12982-025-00829-7","workflowStages":[]},"version":"v1","identity":"rs-6427125","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6427125","identity":"rs-6427125","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}