The Readiness of Primary Healthcare Facilities to Address Noncommunicable Diseases in Rural Bangladesh

The Readiness of Primary Healthcare Facilities to Address Noncommunicable Diseases in Rural Bangladesh | 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 The Readiness of Primary Healthcare Facilities to Address Noncommunicable Diseases in Rural Bangladesh Tanmoy Sarker, Wubin Xie, Ali Ahsan, Fahmida Atker, Md Mokbul Hossain, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7977902/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Introduction Strengthening the capacity of primary healthcare (PHC) systems is essential to address the rising burden of non-communicable diseases (NCDs) in Bangladesh. The study assessed the readiness of rural PHC facilities in addressing the five World Health Organization (WHO) priority NCDs: diabetes, cardiovascular diseases, chronic respiratory diseases, cervical cancer, and mental health disorders. Methods Between March and April 2024, a cross-sectional survey was conducted in three subdistricts of Dinajpur District, Bangladesh, as a part of a type-2 hybrid effectiveness-implementation trial aimed at evaluating implementation fidelity and examining the process of intervention delivery pertinent to NCD care. All healthcare facilities (government, non-government, and private,) within the study areas were included. Two existing tools, the WHO Service Availability and Readiness Assessment (SARA) and the Harmonized Health Facility Assessment (HHFA), were adapted to evaluate NCD-specific readiness across four domains: clinical services, staff and guidelines; equipment; diagnostic capacity; and essential medicines. Readiness scores were calculated for each domain, with scores ≥ 70% indicating sufficient preparedness for NCD management. Results Union-level public health facilities (ULPHFs) had slightly better overall service readiness (39.6%) than community clinics (CC) (38.7%), while upazila (subdistrict) health complexes (UHCs) had the highest overall readiness (82.1%). UHCs had the highest readiness for diabetes care (68.2%), particularly in clinical services, staffing, and guidelines (88.9%). The availability of medicines was critically low in CC (0.2%). Equipment for the management of cardio-vascular diseases was most available (80.0%), whereas cervical cancer equipment was totally unavailable (0.0%) in ULPHFs, CCs, and private/NGO facilities. Chronic respiratory disease and cervical cancer diagnostic capacity were totally absent (0.0%) in ULPHFs and CCs. In mental health service provision, UHCs were the most prepared (32.5%), whereas ULPHFs were the least prepared (3.3%). None of the facilities achieved the 70% threshold of overall readiness for all five NCDs. Conclusion Findings reveal serious gaps in the readiness of PHC facilities in Bangladesh to respond to NCDs in the four areas. Shortages of trained personnel, absence of standard treatment guidelines, limited diagnostic services, and irregular availability of essential medicines highlight important areas requiring urgent strengthening to enhance PHC readiness and ensure equitable NCD-care provision. Non-communicable diseases Bangladesh service availability readiness primary healthcare Figures Figure 1 Figure 2 Introduction NCDs are currently the leading causes of death and disability worldwide, and accounted for 43 million deaths in 2021 (75% of non-pandemic related deaths) 1 . In Bangladesh, mortality due to NCDs has increased phenomenally from 8% in 1986 to 63.1% in 2021 2,3 . The growing burden of NCD-related disability and death in Bangladesh seriously strains the country's health system, which is traditionally geared towards managing communicable diseases, and maternal and child health 4 , 5 . NCDs impose enormous economic burdens on individuals, families, and healthcare systems, contributing to poverty, inequality, and social unrest 6 , 7 . In response to the growing burden of NCDs, the government of Bangladesh has implemented various interventions in recent years 5 , 8 . In light of the successful achievement of under-five mortality targets through primary health care interventions, the Ministry of Health and Family Welfare prioritized strengthening primary health care in its 2017–2022 Health, Population, Nutrition Sector Program (HPNSP) to expand NCD prevention and management services 9 , 10 . The screening and management of NCDs has been incorporated into the Essential Service Package in the fourth HPNSP 9 . This strategic plan prioritized the equitable, effective, and cost-effective delivery of healthcare, particularly among marginalized and hard-to-reach populations 9 . The establishment of NCD corners at the Upazila Health Complexes (UHCs) in 2012 was a crucial step in delivering NCD services at the doorstep of the community 4 . Thus, the NCD corner of the UHC became the prime focus for implementing the Operational Plan of the Non-communicable Disease Control Program (NCDC), which provides hypertension and diabetes care following national protocols 11 . Approximately 70 of the UHCs now follow the NCD management model of the 4th HPNSP and provide services such as identification and registration at the household level, screening at the community clinic level, diagnosis and management at the UHC level, and an upward and backward referral system 9 , 12 . NCD-related services require continuous care within health facilities, skilled and trained medical staff, and a reliable supply of equipment, medications, and other essential resources 13 . Despite the introduction of NCD corners and related initiatives, the primary healthcare system of Bangladesh faces significant challenges with the efficient management of NCDs 5 . Some of the major challenges in delivering NCD services include inadequate laboratory facilities, insufficiently trained medical personnel, irregular availability of drugs, and lack of documentation and reporting systems 14 . Several studies have assessed the readiness of health facilities at different levels in Bangladesh, with varying geographic coverage. A common finding from these studies was that the majority of health facilities lack readiness to provide NCD care in nearly every domain (diagnostic facilities, equipment, medicine, trained staff and guideline), 16–19 with the exception of some tertiary-level hospitals. 15 – 17 Two studies that included the most peripheral primary care facilities (i.e., community clinics) reported particularly low readiness for these facilities compared with higher subdistrict-level health facilities. 16 , 19 The majority (68%) of Bangladeshi people live in rural areas and depend on the public primary care system for healthcare. 18 However, few existing studies have stratified their analysis by rural versus urban samples; most of these studies used data collected before 2018 (with the exception of the Kabir et al study conducted in 2021); and no studies have assessed readiness to provide mental health services. 16 Timely and accurate knowledge of the capabilities and constraints of primary healthcare facilities in providing NCD services is crucial for an effective response to NCD care delivery. Using data collected in 2024, the present study assessed the availability and readiness of primary healthcare systems in a rural region in Bangladesh for all five WHO-prioritized NCDs (i.e., cardiovascular disease (CVD), diabetes mellitus (DM), chronic respiratory disease, cervical cancer, and mental disorders), addressing critical information gaps to guide comprehensive NCD management efforts in Bangladesh. Methodology Study design This cross-sectional study was conducted between March and April 2024 as a part of the evaluation component of a type-2 hybrid study (NCT06258473) aimed at evaluating the process and assessing implementation fidelity of interventions for the prevention and control of NCDs 19 . Study settings and sample The study took place in three subdistricts of Dinajpur district, namely Chirirbandar, Parbatipur and Biral. Dinajpur is a border-based district located in the northern part of Bangladesh. The areas of Chirirbandar, Parbatipur, and Biral subdistricts are 312.69, 395.04, and 353.98 square kilometers, respectively, with literacy rates of 78.98%, 79.46%, and 78.52% 20,18 . Their respective populations are 323,880 for Chirirbandar, 400,630 for Parbatipur, and 281,549 for Biral 18 (Fig. 1 ). In rural Bangladesh, the government primary healthcare system in a subdistrict operates at three levels. CCs stand in the lowest tier of the health system, serving approximately 6,000 people each, ULPHFs cater to approximately 25,000 people per facility, and UHCs, equipped with outpatient and emergency services and indoor services with surgical facilities, each serving a population of about 250,000. Accordingly, we divided healthcare facilities into four categories: UHC, ULPHF, CC, and private/NGO health facility. Our study explored 179 healthcare facilities across the government, private, and NGO sectors in these areas. Facility selection was undertaken using the Directorate General of Health Services (DGHS) health facility registry as the primary sampling frame, with supplementary inclusion of private and NGO-operated clinics identified during field data collection that were not listed in the official registry. Data were collected from all the identified government, non-government and relevant private facilities in each of the study subdistricts. Data collection tool The data collection instrument was adapted from the WHO Service Availability and Readiness Assessment (SARA) tool and the WHO Harmonized Health Facility Assessment (HHFA) tool (Supplementary material: service availability and readiness assessment tool) 21 , 22 . Basic information concerning the health facility, staffing, infrastructure, and major NCD management including training of the staff, counseling and management guidelines, equipment and supplies, and pharmaceutical commodities, was collected. The HHFA tool does not include any reference to equipment or diagnostic services for mental healthcare. Therefore, our data on mental health services focused solely on staff training, availability of management guidelines, and pharmaceutical resources. Before data collection, the study tool was translated into the local language Bengali and was subsequently pretested at 10 healthcare facilities located in the Birganj subdistrict, which was not part of the main study area. Data collection The data collection field team comprised 14 staff members, a physician, a data collection supervisor, and 12 data collectors. To effectively cover the three subdistricts, the data collectors were divided into three groups of four. The supervisor prepared the field plan and tackled on-site challenges, with the physician always providing technical support. Data collectors received five days of training (field and in-house) on the data collection tool. Data collection was carried out using electronic technology (tablet computers), and KoboToolbox software was used to create forms to enable real-time data entry. Data collection interviews were conducted with the facility manager and the relevant officials of different sections (laboratory and pharmacy) of the facility after obtaining written informed consent. Observations were made according to the instructions provided on the study instrument. The data collectors uploaded the data into the KoboToolbox server daily at data collection close. The data was downloaded, and quality check was performed by the investigators for ensuring data quality. Data analysis For analysis, we followed the HHFA indicator inventory and Service Availability and Readiness Assessment manual of the WHO 22 , 23 . Density of the health facilities was reported against the WHO standard of 2 per 10,000 population, and density of core health workforce was compared with the WHO standard of 23 per 10,000 individuals and reported as percentages. Proportion was determined by dividing the actual number of existing health facilities in the subdistrict by the number required corresponding to the population size outlined in the SARA manual. Service readiness was evaluated in four domains for general as well as NCD care. General service readiness included (i) basic amenities, (ii) basic equipment, (iii) basic diagnostics, and (iv) essential medicines. Conversely, service readiness for NCDs tapped into this platform and explored more specialist components required for managing NCDs. These included the availability of (i) clinical services (at least one of the services: diagnosis, follow-up or referral) specific to NCDs, the presence of trained staff and clinical guidelines, (ii) specialized equipment, (iii) diagnostic capacity for NCD conditions, and (iv) essential NCD medicines. Comprehensive descriptions of the items corresponding to each domain are available in the supplementary materials. The score for each domain was calculated using the mean availability of tracer items expressed as a percentage within that domain. Subsequently, the means (± standard deviation) of all domain scores were calculated to generate the overall service readiness index as well as indices specific to NCD-related services. These measures were assessed using a 70% cutoff point, meaning that any facility scoring below this level was considered inadequate for managing NCDs 22 . Results Characteristics of healthcare facilities A total of 179 primary healthcare facilities were assessed, of which 68 were from Chirirbandar, 63 from Parbatipur and 48 from Biral. The public healthcare facilities included 108 community clinics, 42 ULPHFs, and 3 UHCs (Table-1). Table 1 Characteristics of health facilities Indicators Chirirbandar Parbatipur Biral Overall Area * (square kilometers) 312.69 395.04 353.98 1061.71 Population $ Male 162,563 200,598 141,447 504,608 Female 161,317 200,032 140,102 501,451 Total 323,880 400,630 281,549 1,006,059 Literacy rate $ 78.98 79.46 78.52 78.98 Facility type $ Upazila Health Complex 1 1 1 3 Union-level public facilities 15 16 11 42 Community Clinic 36 38 34 108 Private/NGO facility 16 8 2 26 Total 68 63 48 179 * Data source: Bangladesh population and housing census 2011. Zila report Zila: Dinajpur $ Data source: Population and housing census 2022: National report (Volume 1) The facility density score was 100% for the Chirirbandar subdistrict, whereas the facility density was 78.6% for Parbatipur and 85.2% for Biral. The core health workforce density score was highest in Chirirbandar (28.1%) among the three subdistricts, followed by Biral (23.9%), and Parbatipur (21.9%) (Table 2 ). Table 2 Health facility density and core health workforce density domain score Domain score % Upazila Health Complex (n = 3) Union-level public facilities (n = 42) Community Clinic (n = 108) Private/NGO facility (n = 26) Total (n = 179) Health facility density Chirirbandar 1.5 23.2 55.6 24.7 100.0 Parbatipur 1.2 20.0 47.4 10.0 78.6 Biral 1.8 19.5 60.4 3.6 85.2 Overall 1.5 20.9 54.5 12.8 87.9 Core health workforce density Chirirbandar 6.8 1.6 9.0 10.6 28.1 Parbatipur 7.4 0.7 8.0 5.9 21.9 Biral 9.4 1.7 10.5 2.3 23.9 Overall 7.9 1.3 9.2 6.3 24.6 General NCD service readiness Table 3 and supplementary table 1 presents domain-specific general service readiness for four domains: basic amenities, basic equipment, diagnostic capacity, and basic medicines. Among the 179 healthcare facilities, the mean readiness index for general service delivery for NCD was highest for UHC (82.1%), followed by private/NGO facilities (56.6%), ULPHF (39.6%), and CC (38.6%) (Fig. 2 a). All the individual items for basic amenities were available in UHCs; therefore, they had the highest mean domain score for basic amenities (100.0%), and for other facilities (private/NGO, ULPHF, and CC), it ranged between 48.7% and 72.6%. The mean domain score for the availability of basic equipment was 85.7%, the highest among the facilities, followed by CC (65.7%), ULPHF (64.3%), and private/NGO facilities (61.0%). Private/NGO facilities had the highest mean domain score for the availability of diagnostic services (64.5%), followed by UHC (59.3%), ULPHF (9.3%), and CC (6.2%). The availability of basic medicines for treating NCDs was the highest in UHCs (83.3%), followed by ULPHF (34.4%), CC (34.0%), and private/NGO (28.3%). Table 3 General NCD and NCD specific service readiness index score by facility type Domain score, % (SD) Upazila Health Complex (n = 3) Union-level public facilities (n = 42) Community Clinic (n = 108) Private/NGO facility (n = 26) Total (n = 179) General NCD services Basic amenities 100.0 (0.0) 50.5 (33.6) 48.7 (36.2) 72.6 (35.8) 53.4 (30.5) Basic equipment 85.7 (26.2) 64.3 (21.0) 65.7 (17.1) 61.0 (30.2) 65.0 (18.8) Basic diagnostics 59.3 (43.4) 9.3 (16.0) 6.2 (15.9) 64.5 (33.8) 16.3 (16.2) Basic medicines 83.3 (36.4) 34.4 (30.0) 34.0 (46.8) 28.3 (9.6) 34.1 (34.7) Overall readiness index for general NCD services [Mean (± SD)] 82.1 (16.9) 39.6 (23.6) 38.7 (25.2) 56.6 (19.5) 42.2 (21.5) Diabetes Clinical service, staff and guidelines 88.9 (19.2) 13.5 (17.2) 22.8 (19.9) 25.6 (41.1) 22.2 (20.1) Equipment 57.1 (46.0) 36.4 (29.0) 33.3 (32.2) 44.0 (33.3) 36.0 (29.2) Diagnostic capacity 51.9 (41.2) 9.3 (16.0) 6.2 (15.9) 59.0 (36.2) 15.3 (16.6) Medicines 75.0 (50.0) 7.7 (11.2) 0.2 (0.5) 10.6 (9.1) 4.7 (4.5) Overall readiness index for services specific to diabetes [Mean (± SD)] 68.2 (39.1) 16.7 (18.4) 15.6 (17.1) 34.8 (29.9) 19.6 (17.6) Cardiovascular diseases Clinical service, staff and guidelines 88.9 (19.2) 21.4 (33.1) 35.5 (35.6) 30.8 (50.0) 32.4 (35.8) Equipment 80.0 (29.8) 71.4 (21.0) 73.9 (11.8) 66.9 (34.8) 72.4 (17.1) Diagnostic capacity 26.7 (43.5) 0 (0.0) 0 (0.0) 50.8 (31.6) 7.8 (5.1) Medicines 72.2 (39.0) 8.3 (10.3) 0.5 (1.1) 14.7 (14.9) 5.6 (5.3) Overall readiness index for services specific to cardiovascular disease [Mean (± SD)] 66.9 (32.9) 25.3 (16.1) 27.5 (12.1) 40.8 (32.8) 29.6 (15.8) Chronic respiratory disease (CRD) Clinical service, staff and guidelines 91.7 (16.7) 20.2 (22.9) 30.8 (32.4) 30.8 (34.3) 29.3 (28.7) Equipment 61.1 (44.3) 30.6 (31.6) 26.7 (34.5) 32.1 (31.8) 29.0 (31.7) Diagnostic capacity 44.4 (50.9) 0 (0.0) 0 (0.0) 44.9 (38.9) 7.3 (6.3) Medicines 57.1 (53.5) 8.2 (13.5) 20.5 (37.6) 12.6 (10.3) 17.1 (26.7) Overall readiness index for services specific to CRD [Mean (± SD)] 63.6 (41.3) 14.7 (17.0) 19.5 (26.1) 30.1 (28.8) 20.7 (23.4) Cervical cancer Clinical service, staff and guidelines 66.7 (57.7) 0.8 (1.4) 15.1 (26.2) 1.3 (2.2) 10.6 (17.0) Equipment 72.2 (32.8) 0 (0.0) 0 (0.0) 0 (0.0) 1.2 (0.5) Diagnostic capacity 33.3 (57.7) 0 (0.0) 0 (0.0) 0 (0.0) 0.6 (1.0) Medicines 66.7 (57.7) 35.7 (39.8) 31.8 (55.1) 14.1 (13.5) 30.7 (44.3) Overall readiness index for services specific to cervical cancer [Mean (± SD)] 59.7 (51.5) 9.1 (10.3) 11.7 (20.3) 3.8 (3.9) 10.8 (15.7) Mental health disorder Clinical service, staff and guidelines 55.6 (19.2) 6.3 (11.0) 7.7 (9.6) 6.4 (11.1) 8.0 (10.1) Medicines 9.5 (25.2) 0.3 (0.9) 0 (0.0) 6.6 (6.2) 1.2 (0.9) Overall readiness index for services specific to mental health disorder [Mean (± SD)] 32.5 (22.2) 3.3 (5.9) 3.9 (4.8) 6.5 (8.6) 4.6 (5.5) Readiness index specific to the service for diabetes The readiness index scores of healthcare facilities for diabetes related service are displayed in Table 3 and Supplementary table 2 . All the UHCs (100%) provided clinical services (diagnosis, treatment, or follow-up) for diabetes, whereas approximately three-quarters (73.1%) of the private/NGO facilities and approximately one-third of the ULPHFs (33.3%) and CCs (36.1%) provided the services. CCs and private/NGO facilities reported having no guidelines for the diagnosis and treatment of diabetes; only 2.4% of the ULPHFs and 66.7% of the UHCs had guidelines. All UHCs and 32.4% of CCs had at least one trained staff member for the management of diabetes. All UHCs (100%) were equipped with a glucometer, glucometer strips, and an adult weighing scale. Urine ketone test strips and ophthalmoscopes were not available in any health facility, except in a small proportion of private/NGO facilities − 3.8% had urine ketone test strips, and 11.5% had ophthalmoscopes. Both random and fasting blood sugar tests were available in all UHCs (100.0%). Among private/NGO facilities, 92.3% offered random blood glucose testing, whereas 88.5% provided fasting blood glucose testing. The mean domain score for diagnostic capacity was the highest in private/NGO facilities (59.0%), followed by UHCs (51.9%), ULPHFs (9.3%), and CCs (6.2%). Regarding diabetes, the mean domain score for UHC was 75.0%, whereas the other facilities had very low scores; private/NGO facilities had 10.6%, ULPHFs had 7.7%, and CCs had only a 0.2% score for medicine availability. Overall, the diabetes service-related mean readiness score varied across healthcare facilities (ranging from 15.6% for CCs to 68.2% for UHCs) (Fig. 2 b). Readiness index specific to the service for cardiovascular disease (CVD) Table 3 and Supplementary table 3 presents the facility readiness index for cardiovascular service delivery. The availability of clinical services, guidelines and trained staff for CVD varied greatly among healthcare facilities (ranging from 89.9% in UHCs to 21.4% in ULPHFs). Almost all facilities had a functional blood pressure apparatus (UHCs and private/NGO facilities 100.0%, CCs 92.4%, and ULPHFs 88.1%), an adult weighing machine (UHCs and private/NGO facilities 100%), and a stethoscope (UHCs and private/NGO facilities 100%, ULPHFs 90.5%, and CCs 89.6%). The availability of diagnostic facilities for CVD was low among healthcare facilities. The mean domain scores were 50.8% for private/NGO facilities, 26.7% for UHCs, and 0.0% for ULPHFs and CCs. Calcium channel blockers, angiotensin receptor blockers, and thiazide diuretics were available in all UHCs (100%), but their availability varied among other health facilities (from 0.0% to 53.8%). The overall mean readiness index score was highest for UHCs (66.9%) and lowest for ULPHFs (25.3%) (Fig. 2 c). Readiness index specific to the service for chronic respiratory diseases (CRD) The items related to service for CRD are presented in Table 3 and Supplementary table 4. Clinical services for asthma and chronic obstructive pulmonary disease (COPD) were available for all UHCs (100.0%). Services for both asthma and COPD were less commonly available at ULPHFs (50.0% and 26.2%, respectively), CCs (75.9% and 18.5%), and private/NGO facilities (69.2% and 50.0%). The mean domain score for equipment varied among healthcare facilities, from 61.1% for UHCs to 26.7% for CCs. Only UHCs and private/NGO facilities had diagnostic facilities available, with mean domain scores of 44.4% and 44.9%, respectively. For medicines, the mean domain score ranged from 8.2% for the ULPHFs to 57.1% for the UHCs. The overall readiness index was the highest for UHCs (63.6%), followed by private/NGO facilities (30.1%), CCs (19.5%), and ULPHFs (14.7%) (Fig. 2 d). Readiness index specific to the service for cervical cancer The readiness index scores of healthcare facilities for services related to cervical cancer are shown in Table 3 and Supplementary table 5. Although 45.4% of the CCs had at least one trained staff member regarding cervical cancer, along with ULPHFs and private/NGO facilities, they did not provide any clinical services. All the UHCs (100.0%) provided clinical services and had at least one staff member; however, guidelines for cervical cancer management were unavailable in all facilities. Only UHCs had equipment for cervical cancer management with a mean domain score of 72.2%. All (100.0%) the UHCs provided visual inspection with the acetic acid (VIA) test, but the other diagnostic facilities were unavailable. The mean domain score for the availability of medicines was highest for UHCs (66.7%) and lowest for private and NGO facilities (14.1%). The readiness index for the overall services for cervical cancer was highest in UHCs (59.7%) and lowest in private and NGO facilities (3.8%) (Fig. 2 e). Readiness index specific to the service for mental health Tracer items related to mental health services are listed in Table 3 and Supplementary table 6. Sixty seven percent of the UHCs, 18.5% of the CCs and approximately 19.0% of the ULPHFs and private/NGO facilities provided clinical services for mental health. Guidelines were only available in UHCs (33.3%), and 4.6% of the CCs and 66.7% of the UHCs had at least one trained staff member. For the availability of medicines, the mean domain score was 9.5% for UHCs, which was the highest, followed by 6.6% for private/NGO facilities. The general readiness index for mental healthcare was highest in UHCs (32.5%) and lowest in ULPHFs (3.3%) (Fig. 2 f). Discussion To the best of our knowledge, our study is the first to explore the readiness of both government and private primary healthcare facilities regarding the five NCDs recommended by the WHO in rural Bangladesh. We found that the density of health facilities for Chirirbandar met the WHO SARA guidelines (2 per 10,000 population), but the Parbatipur and Biral subdistricts fell short of this standard. All three subdistricts had critical shortages of core health workers achieving only 21.9–28.1% of the WHO SARA standard (23 per 10,000 people). The UHCs demonstrated service readiness exceeding the 70% benchmark for basic amenities, medical equipment/supplies, and medicine stocks, though diagnostic capabilities fell below this threshold. None of the primary healthcare facilities at any level met the WHO SARA-recognized minimum standards for the management of all five NCDs. For disease-specific NCDs, CVD, CRD, and diabetes showed higher readiness than cervical cancer and mental health diseases. UHCs had the highest readiness index for all five major NCDs compared with the other facilities (ULPHF, CC, and private/NGO). The availability of clinical services, guidelines, and at least one trained staff member was highest for CRD (91.7%), with diabetes and cardiovascular disease services being slightly lower (both 88.9%) at UHC. However, for cervical cancer, the availability of these three components was the lowest in ULPHF (0.8%) and private/NGO facilities (1.3%). A study in Bangladesh reported comparable results, where the guidelines and at least one trained staff member lacked for cervical cancer services at ULPHFs compared with CRD, CVD, and DM 24 . These findings were consistent with a recent systematic review, which revealed that primary healthcare facilities are better equipped in terms of guidelines and at least one trained staff member for DM management compared with cancer care in Bangladesh 13 . Cancer-related services have historically been limited in Bangladesh, with the primary healthcare system being particularly affected 25 . It is evident from various studies across the countries that primary healthcare facilities often lack properly trained frontline workers to manage NCDs 13 , 26 – 29 . Studies have also suggested that a shortage of trained health personnel is a common phenomenon in low-and middle-income countries 30 – 34 . Similarly, for NCD-related service delivery, Bangladesh is experiencing a deficit in skilled health workers 16 , 17 . The unequal distribution of the health workforce with rapid turnover heavily affects health service delivery in Bangladesh 35 , 36 . In these circumstances, periodic training of frontline health workers would be more effective than deploying a disease-specific health workforce. Studies have also shown that adequate training and supervision by non-physicians, clinicians, and staff in nurse-led clinics can deliver effective primary care for NCDs 37 – 39 . The equipment and diagnostic capacity of a healthcare facility play a vital role in the diagnosis, management, and follow-up of NCDs. In our study, we found that UHC had sufficient equipment for CVD and cervical cancer services (readiness scores were 80.0% and 72.2%, respectively) but lacked DM and CRD care (readiness scores were 57.1% and 61.1%, respectively). In addition to CVD care, other health facilities were critically underequipped for DM, CRD, and cervical cancer services. The result is concordant with other studies conducted in Bangladesh, which also reported better availability of CVD care equipment compared to the inadequate resources for DM care 15 , 17 , 24 . Primary healthcare facilities with available glucometers frequently face operational challenges, as the devices are often non-functional or lack essential supplies such as test strips and batteries 14 . A blood pressure apparatus and stethoscope are required and are used for routine clinical examinations for diseases other than CVD at healthcare facilities. Moreover, the NCDC provides a digital blood pressure apparatus at the NCD corners of the UHCs. This might explain the better availability of CVD-care-related equipment in healthcare facilities. Although private or NGO facilities had higher readiness scores for diagnostic services related to diabetes, CVD, and CRD, none of the healthcare facilities met the WHO SARA benchmark for service readiness. This finding is consistent with previous research in Bangladesh, which highlighted the limited diagnostic readiness for NCD management in general 24 . Other studies conducted in Bangladesh have also reported higher diagnostic readiness scores for NCD services in private and NGO healthcare facilities 15 – 17 . Laboratory tests in primary healthcare facilities may enhance diagnostic accuracy and patient outcomes 40 . Inadequate necessary supplies (reagents and equipment), improper maintenance, and lack of trained and regular human resources to operate available equipment are barriers to laboratory diagnostic services at public healthcare facilities at the PHC level 41 . Moreover, the deceitful behavior of some healthcare staff at public healthcare facilities has led patients to private facilities or higher-level facilities for basic laboratory tests 41 . This may incentivize private facilities to further strengthen their laboratory diagnostic services, which are often a key source of revenue for these institutions. All these factors subsequently increase the out-of-pocket expenditure of patients, resulting in a drop out of treatment. NCDs require uninterrupted access to medicines for effective disease management. Our study revealed that only medicines for DM and CVD were available at the UHC, according to the WHO SARA standard, which is consistent with the findings of a study conducted in northeastern Bangladesh 42 . The availability of medicine was the highest for CRD and the lowest for mental health disorders. Comparable results were observed in another study conducted in similar settings 24 . Mental healthcare provision is disproportionately concentrated in urban areas, leaving rural primary and secondary health facilities severely underserved 43 . The absence of NCD-related medication supplies or substandard drug quality in public healthcare institutions has emerged as a primary source of patient discontent, ultimately driving individuals toward private sector purchases that significantly increase out-of-pocket health expenditures 44 – 46 . Collectively, these factors disproportionately impact socioeconomically disadvantaged populations, contributing to medication non-adherence and consequently resulting in poor control of hypertension, diabetes and other NCDs 24 . The 4th HPNSP model explicitly mentioned potential roles for ULPHFs and CCs in a team-based NCD care model, including screening, routine follow-up, and drug refill, through an upward and backward referral system with NCD corners 9 , 12 . By shifting stable patients from doctor-run facilities (UHCs) to non-physician-led centers (ULPHFs and CCs) with the support of digital technology and task redistribution, subdistrict-level NCD corners could focus on managing more complicated cases, and the primary care system as a whole may cater to a much larger patient population. 47 , 48 Moreover, this approach reduces travel-related costs and increase the accessibility of NCD services, especially in those hard-to-reach rural areas. 47 The rapid development of digital tools for care coordination and clinical decision support provides important opportunities to support decentralized primary care. 49 – 52 Studies have provided early evidence that utilizing lower-level primary healthcare facilities may enhance treatment outcomes for hypertension and diabetes. 48 Within this model of care, requirements of guidelines, healthcare staff training, medications, diagnostic facilities, and equipment would be less stringent for these peripheral primary care facilities, and thus the commonly used 70% cutoff may not apply to these grassroot-level primary care facilities. Consistent with previous studies, 16, 19 we found that the domain scores for the availability of NCD medicines across all five major NCDs were critically low in the ULPHF and CC. Majority of these facilities are not prepared to take responsibility for providing NCD care in a team-based decentralized model. More investment in peripheral primary care facilities is urgently needed to improve the availability and accessibility of much needed NCD care in rural Bangladesh. Strengths and limitations of the study A key strength of this study is that it examined a thorough scenario for all five NCDs prioritized by the WHO in primary healthcare settings. The study included all the registered healthcare facilities across the three subdistricts, providing a comprehensive overview of NCD service delivery in these areas. We also acknowledge several limitations. First, the assessment of readiness indicators following the WHO-SARA manual considers only supply-side determinants, such as infrastructure, medical equipment, and human resources. This approach does not fully capture complex interactions and contextual determinants influencing broader health system dynamics. Second, part of the data relied on subjective responses of the respondents that could not be independently verified. Because of restricted availability of facility records, data provided by facility managers could not be verified through cross-checking, and this could have resulted in some bias. Third, the study was focused on rural primary healthcare centers in three subdistricts, which may limit the generalizability of the findings because urban healthcare centers were not included. Additionally, the cross-sectional design of the study only reflected the state of healthcare facilities on specific days of data collection, limiting insight into long-term trends or variability. Conclusion The study findings reveal that while certain domains of NCD service delivery readiness at UHCs showed adequate scores, overall preparedness for NCD management remains critically low across public and private/NGO primary healthcare facilities. The most important obstacles to delivering quality NCD services include insufficient clinical services, lack of adequately trained staff, no guidelines, inadequate diagnostic capacity, and stockout of priority medicines. Although the government of Bangladesh has initiated several important programs, universal health coverage is to be achieved by an integrated multisectoral strategy offering ensured access to skilled health professionals, essential medicines, and functional diagnostic equipment at the primary care level. Abbreviations PHC: Primary healthcare; NCDs: Non-communicable diseases; WHO: World Health Organization; SARA: Service Availability and Readiness Assessment; HHFA: Harmonized Health Facility Assessment; ULPHFs: Union-level public health facilities; CC: Community clinic; UHC: Upazila (sub-district) Health Complex; HPNSP: Health, Population, Nutrition Sector Program; NCDC: Non-communicable Disease Control Program; CVD: Cardiovascular disease; DM: Diabetes mellitus; COPD: Chronic obstructive pulmonary disease; CRD: Chronic respiratory disease; DGHS: Directorate General of Health Services Declarations Acknowledgements The authors would like to express their sincere appreciation to all the participants in this study for their valuable time and contributions. We also extend our gratitude to the Line Director of the Non-Communicable Disease Control Program, Directorate General of Health Services, Ministry of Health and Family Welfare, for granting permission to conduct this research and collect data from healthcare facilities. Special thanks are due to the Civil Surgeon of Dinajpur and the Upazila Health and Family Planning Officers of the three sub-districts for their generous support and coordination during data collection. Funding This research was funded by the National Institute for Health and Care Research (NIHR) (16/136/68) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care. Data availability statement The data are available to researchers upon reasonable request to the study data access committee. Contact forms and emails are provided on the GHRU website (www.ghru-southasia.org). Authors’ contributions WX, MKM, BO and JC conceptualized the study, while WX and MKM were responsible for its design. Data collection was carried out by TS and AA. TS performed the data analysis and the interpretation of findings. TS drafted the initial version of the manuscript. TS, FA, MKM and WX were involved in the critical revision and contributed to enhancing the intellectual content of the manuscript. All authors reviewed and approved the final version for submission. The authors bear sole responsibility for the accuracy of the data analysis and the integrity of the manuscript’s content. Ethical approval and consent to participant This study was approved by the Institutional Review Board of James P Grant School of Public Health, BRAC University (reference number: IRB-16-November-23-041). The ethical approval was done in accordance with the Declaration of Helsinki. Informed written consent was obtained from all participants and their participation was voluntary. Confidentiality and anonymity of the information provided were assured to the participants. Consent for publication Not Applicable. Competing interests The authors have no conflicts of interest to disclose. Author details 1 BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh; 2 Nanyang Technological University, Singapore; 3 Baker Heart and Diabetes Institute, Melbourne, Australia; 4 Tyree Foundation Institute of Health Engineering, UNSW Sydney, NSW 2052, Australia; 5 Sprightly Pte Ltd, Singapore; 6 Google Health, Palo Alto, CA, USA; 7 School of Psychology and Public Health, La Trobe University, Melbourne, Australia; 8 Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK References World Health Organization. Noncommunicable diseases. 2024. 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11:47:56","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":163752,"visible":true,"origin":"","legend":"","description":"","filename":"eb737e30eb194e5aaf9cf1d673fc893a1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7977902/v1/53dcb5244f3b0dcdea38759c.xml"},{"id":95800974,"identity":"63a551e9-8c4a-49b3-beba-19371b30f4e5","added_by":"auto","created_at":"2025-11-13 08:24:04","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":176982,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7977902/v1/d4c95e50572915e28c6d179f.html"},{"id":95800777,"identity":"e0ce50b7-15d7-4db8-aa72-287f1771a63b","added_by":"auto","created_at":"2025-11-13 08:23:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":198351,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLocation of primary healthcare facilities at Chirirbandar, Parbatipur and Biral subdistrict\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7977902/v1/2f33c7532106799a0995ca75.png"},{"id":95731400,"identity":"e41e3a7c-7e22-4d94-83fa-9a9878b36a88","added_by":"auto","created_at":"2025-11-12 11:47:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":165809,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDomain stratified general and disease specific NCD service readiness score by healthcare facility (a: General NCD service; b: Diabetes; Fig 2c: Cardiovascular disease; d: Chronic respiratory disease, e: Cervical cancer; f: Mental health disorder)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7977902/v1/a4deea6be0f1f7d8ea9799b5.png"},{"id":95805536,"identity":"f924b6ab-bd66-4778-baa2-95dfbbbe6a72","added_by":"auto","created_at":"2025-11-13 08:41:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1891266,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7977902/v1/ec495430-d57e-40df-9282-678c6e4eab88.pdf"},{"id":95731403,"identity":"f2b5d94d-ec92-4d29-9fdd-1ed8775b6a4f","added_by":"auto","created_at":"2025-11-12 11:47:56","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":58260,"visible":true,"origin":"","legend":"","description":"","filename":"BMCTheme3SupplementarytablesTS.docx","url":"https://assets-eu.researchsquare.com/files/rs-7977902/v1/710cdfdfa19ae3d8ff6b4cd6.docx"},{"id":95801204,"identity":"de6d6bed-307a-4947-be02-e0e5809ca364","added_by":"auto","created_at":"2025-11-13 08:24:42","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":196838,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarymaterialServiceavailabilityandreadinessassessmenttoolEnglish.docx","url":"https://assets-eu.researchsquare.com/files/rs-7977902/v1/a58dc5a2ac627c63a9e48f8a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Readiness of Primary Healthcare Facilities to Address Noncommunicable Diseases in Rural Bangladesh","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNCDs are currently the leading causes of death and disability worldwide, and accounted for 43\u0026nbsp;million deaths in 2021 (75% of non-pandemic related deaths)\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In Bangladesh, mortality due to NCDs has increased phenomenally from 8% in 1986 to 63.1% in 2021\u003csup\u003e2,3\u003c/sup\u003e. The growing burden of NCD-related disability and death in Bangladesh seriously strains the country's health system, which is traditionally geared towards managing communicable diseases, and maternal and child health\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. NCDs impose enormous economic burdens on individuals, families, and healthcare systems, contributing to poverty, inequality, and social unrest\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn response to the growing burden of NCDs, the government of Bangladesh has implemented various interventions in recent years \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In light of the successful achievement of under-five mortality targets through primary health care interventions, the Ministry of Health and Family Welfare prioritized strengthening primary health care in its 2017\u0026ndash;2022 Health, Population, Nutrition Sector Program (HPNSP) to expand NCD prevention and management services \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The screening and management of NCDs has been incorporated into the Essential Service Package in the fourth HPNSP \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. This strategic plan prioritized the equitable, effective, and cost-effective delivery of healthcare, particularly among marginalized and hard-to-reach populations \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. The establishment of NCD corners at the Upazila Health Complexes (UHCs) in 2012 was a crucial step in delivering NCD services at the doorstep of the community \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Thus, the NCD corner of the UHC became the prime focus for implementing the Operational Plan of the Non-communicable Disease Control Program (NCDC), which provides hypertension and diabetes care following national protocols \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Approximately 70 of the UHCs now follow the NCD management model of the 4th HPNSP and provide services such as identification and registration at the household level, screening at the community clinic level, diagnosis and management at the UHC level, and an upward and backward referral system \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNCD-related services require continuous care within health facilities, skilled and trained medical staff, and a reliable supply of equipment, medications, and other essential resources\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Despite the introduction of NCD corners and related initiatives, the primary healthcare system of Bangladesh faces significant challenges with the efficient management of NCDs \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Some of the major challenges in delivering NCD services include inadequate laboratory facilities, insufficiently trained medical personnel, irregular availability of drugs, and lack of documentation and reporting systems \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Several studies have assessed the readiness of health facilities at different levels in Bangladesh, with varying geographic coverage. A common finding from these studies was that the majority of health facilities lack readiness to provide NCD care in nearly every domain (diagnostic facilities, equipment, medicine, trained staff and guideline),\u003csup\u003e16\u0026ndash;19\u003c/sup\u003e with the exception of some tertiary-level hospitals.\u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Two studies that included the most peripheral primary care facilities (i.e., community clinics) reported particularly low readiness for these facilities compared with higher subdistrict-level health facilities.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe majority (68%) of Bangladeshi people live in rural areas and depend on the public primary care system for healthcare.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e However, few existing studies have stratified their analysis by rural versus urban samples; most of these studies used data collected before 2018 (with the exception of the Kabir et al study conducted in 2021); and no studies have assessed readiness to provide mental health services.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Timely and accurate knowledge of the capabilities and constraints of primary healthcare facilities in providing NCD services is crucial for an effective response to NCD care delivery. Using data collected in 2024, the present study assessed the availability and readiness of primary healthcare systems in a rural region in Bangladesh for all five WHO-prioritized NCDs (i.e., cardiovascular disease (CVD), diabetes mellitus (DM), chronic respiratory disease, cervical cancer, and mental disorders), addressing critical information gaps to guide comprehensive NCD management efforts in Bangladesh.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design\u003c/h2\u003e\u003cp\u003eThis cross-sectional study was conducted between March and April 2024 as a part of the evaluation component of a type-2 hybrid study (NCT06258473) aimed at evaluating the process and assessing implementation fidelity of interventions for the prevention and control of NCDs \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy settings and sample\u003c/h3\u003e\n\u003cp\u003eThe study took place in three subdistricts of Dinajpur district, namely Chirirbandar, Parbatipur and Biral. Dinajpur is a border-based district located in the northern part of Bangladesh. The areas of Chirirbandar, Parbatipur, and Biral subdistricts are 312.69, 395.04, and 353.98 square kilometers, respectively, with literacy rates of 78.98%, 79.46%, and 78.52% \u003csup\u003e20,18\u003c/sup\u003e. Their respective populations are 323,880 for Chirirbandar, 400,630 for Parbatipur, and 281,549 for Biral \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn rural Bangladesh, the government primary healthcare system in a subdistrict operates at three levels. CCs stand in the lowest tier of the health system, serving approximately 6,000 people each, ULPHFs cater to approximately 25,000 people per facility, and UHCs, equipped with outpatient and emergency services and indoor services with surgical facilities, each serving a population of about 250,000. Accordingly, we divided healthcare facilities into four categories: UHC, ULPHF, CC, and private/NGO health facility. Our study explored 179 healthcare facilities across the government, private, and NGO sectors in these areas.\u003c/p\u003e\u003cp\u003eFacility selection was undertaken using the Directorate General of Health Services (DGHS) health facility registry as the primary sampling frame, with supplementary inclusion of private and NGO-operated clinics identified during field data collection that were not listed in the official registry. Data were collected from all the identified government, non-government and relevant private facilities in each of the study subdistricts.\u003c/p\u003e\n\u003ch3\u003eData collection tool\u003c/h3\u003e\n\u003cp\u003eThe data collection instrument was adapted from the WHO Service Availability and Readiness Assessment (SARA) tool and the WHO Harmonized Health Facility Assessment (HHFA) tool (Supplementary material: service availability and readiness assessment tool) \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Basic information concerning the health facility, staffing, infrastructure, and major NCD management including training of the staff, counseling and management guidelines, equipment and supplies, and pharmaceutical commodities, was collected. The HHFA tool does not include any reference to equipment or diagnostic services for mental healthcare. Therefore, our data on mental health services focused solely on staff training, availability of management guidelines, and pharmaceutical resources. Before data collection, the study tool was translated into the local language Bengali and was subsequently pretested at 10 healthcare facilities located in the Birganj subdistrict, which was not part of the main study area.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eThe data collection field team comprised 14 staff members, a physician, a data collection supervisor, and 12 data collectors. To effectively cover the three subdistricts, the data collectors were divided into three groups of four. The supervisor prepared the field plan and tackled on-site challenges, with the physician always providing technical support. Data collectors received five days of training (field and in-house) on the data collection tool. Data collection was carried out using electronic technology (tablet computers), and KoboToolbox software was used to create forms to enable real-time data entry. Data collection interviews were conducted with the facility manager and the relevant officials of different sections (laboratory and pharmacy) of the facility after obtaining written informed consent. Observations were made according to the instructions provided on the study instrument. The data collectors uploaded the data into the KoboToolbox server daily at data collection close. The data was downloaded, and quality check was performed by the investigators for ensuring data quality.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eFor analysis, we followed the HHFA indicator inventory and Service Availability and Readiness Assessment manual of the WHO \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Density of the health facilities was reported against the WHO standard of 2 per 10,000 population, and density of core health workforce was compared with the WHO standard of 23 per 10,000 individuals and reported as percentages. Proportion was determined by dividing the actual number of existing health facilities in the subdistrict by the number required corresponding to the population size outlined in the SARA manual. Service readiness was evaluated in four domains for general as well as NCD care. General service readiness included (i) basic amenities, (ii) basic equipment, (iii) basic diagnostics, and (iv) essential medicines. Conversely, service readiness for NCDs tapped into this platform and explored more specialist components required for managing NCDs. These included the availability of (i) clinical services (at least one of the services: diagnosis, follow-up or referral) specific to NCDs, the presence of trained staff and clinical guidelines, (ii) specialized equipment, (iii) diagnostic capacity for NCD conditions, and (iv) essential NCD medicines. Comprehensive descriptions of the items corresponding to each domain are available in the supplementary materials. The score for each domain was calculated using the mean availability of tracer items expressed as a percentage within that domain. Subsequently, the means (\u0026plusmn;\u0026thinsp;standard deviation) of all domain scores were calculated to generate the overall service readiness index as well as indices specific to NCD-related services. These measures were assessed using a 70% cutoff point, meaning that any facility scoring below this level was considered inadequate for managing NCDs \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eCharacteristics of healthcare facilities\u003c/h2\u003e\u003cp\u003eA total of 179 primary healthcare facilities were assessed, of which 68 were from Chirirbandar, 63 from Parbatipur and 48 from Biral. The public healthcare facilities included 108 community clinics, 42 ULPHFs, and 3 UHCs (Table-1).\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\u003eCharacteristics of health facilities\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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\u003eIndicators\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChirirbandar\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eParbatipur\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiral\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eArea\u003c/b\u003e\u003csup\u003e*\u003c/sup\u003e (square kilometers)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e312.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e395.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e353.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1061.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePopulation\u003c/b\u003e\u003csup\u003e$\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e162,563\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e200,598\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e141,447\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e504,608\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e161,317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e200,032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e140,102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e501,451\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e323,880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e400,630\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e281,549\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1,006,059\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLiteracy rate\u003c/b\u003e\u003csup\u003e$\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e78.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFacility type\u003c/b\u003e\u003csup\u003e$\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUpazila Health Complex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnion-level public facilities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCommunity Clinic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e108\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrivate/NGO facility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e179\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e*\u003c/sup\u003e Data source: Bangladesh population and housing census 2011. Zila report Zila: Dinajpur\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e$\u003c/sup\u003e Data source: Population and housing census 2022: National report (Volume 1)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe facility density score was 100% for the Chirirbandar subdistrict, whereas the facility density was 78.6% for Parbatipur and 85.2% for Biral. The core health workforce density score was highest in Chirirbandar (28.1%) among the three subdistricts, followed by Biral (23.9%), and Parbatipur (21.9%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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\u003eHealth facility density and core health workforce density domain score\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDomain score %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUpazila Health Complex\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnion-level public facilities\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCommunity Clinic\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;108)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePrivate/NGO facility\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eHealth facility density\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChirirbandar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParbatipur\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e78.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e85.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e87.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCore health workforce density\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChirirbandar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e28.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParbatipur\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24.6\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\n\u003ch3\u003eGeneral NCD service readiness\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents domain-specific general service readiness for four domains: basic amenities, basic equipment, diagnostic capacity, and basic medicines. Among the 179 healthcare facilities, the mean readiness index for general service delivery for NCD was highest for UHC (82.1%), followed by private/NGO facilities (56.6%), ULPHF (39.6%), and CC (38.6%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). All the individual items for basic amenities were available in UHCs; therefore, they had the highest mean domain score for basic amenities (100.0%), and for other facilities (private/NGO, ULPHF, and CC), it ranged between 48.7% and 72.6%. The mean domain score for the availability of basic equipment was 85.7%, the highest among the facilities, followed by CC (65.7%), ULPHF (64.3%), and private/NGO facilities (61.0%). Private/NGO facilities had the highest mean domain score for the availability of diagnostic services (64.5%), followed by UHC (59.3%), ULPHF (9.3%), and CC (6.2%). The availability of basic medicines for treating NCDs was the highest in UHCs (83.3%), followed by ULPHF (34.4%), CC (34.0%), and private/NGO (28.3%).\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\u003eGeneral NCD and NCD specific service readiness index score by facility type\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDomain score, % (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUpazila Health Complex\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnion-level public facilities\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCommunity Clinic\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;108)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePrivate/NGO facility\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral NCD services\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBasic amenities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100.0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.5\u003c/p\u003e\u003cp\u003e(33.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48.7\u003c/p\u003e\u003cp\u003e(36.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e72.6\u003c/p\u003e\u003cp\u003e(35.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e53.4 (30.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBasic equipment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85.7\u003c/p\u003e\u003cp\u003e(26.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64.3\u003c/p\u003e\u003cp\u003e(21.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65.7\u003c/p\u003e\u003cp\u003e(17.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61.0\u003c/p\u003e\u003cp\u003e(30.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e65.0 (18.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBasic diagnostics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59.3\u003c/p\u003e\u003cp\u003e(43.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.3\u003c/p\u003e\u003cp\u003e(16.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.2\u003c/p\u003e\u003cp\u003e(15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e64.5\u003c/p\u003e\u003cp\u003e(33.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16.3 (16.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBasic medicines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e83.3\u003c/p\u003e\u003cp\u003e(36.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.4\u003c/p\u003e\u003cp\u003e(30.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.0\u003c/p\u003e\u003cp\u003e(46.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28.3\u003c/p\u003e\u003cp\u003e(9.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e34.1 (34.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOverall readiness index for general NCD services [Mean (\u0026plusmn;\u0026thinsp;SD)]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82.1\u003c/p\u003e\u003cp\u003e(16.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39.6\u003c/p\u003e\u003cp\u003e(23.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38.7\u003c/p\u003e\u003cp\u003e(25.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56.6\u003c/p\u003e\u003cp\u003e(19.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e42.2\u003c/p\u003e\u003cp\u003e(21.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical service, staff and guidelines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88.9\u003c/p\u003e\u003cp\u003e(19.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003cp\u003e(17.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.8 (19.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.6\u003c/p\u003e\u003cp\u003e(41.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.2\u003c/p\u003e\u003cp\u003e(20.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEquipment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57.1\u003c/p\u003e\u003cp\u003e(46.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.4\u003c/p\u003e\u003cp\u003e(29.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.3\u003c/p\u003e\u003cp\u003e(32.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44.0\u003c/p\u003e\u003cp\u003e(33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e36.0\u003c/p\u003e\u003cp\u003e(29.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiagnostic capacity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51.9\u003c/p\u003e\u003cp\u003e(41.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.3\u003c/p\u003e\u003cp\u003e(16.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.2\u003c/p\u003e\u003cp\u003e(15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e59.0\u003c/p\u003e\u003cp\u003e(36.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15.3\u003c/p\u003e\u003cp\u003e(16.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedicines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75.0\u003c/p\u003e\u003cp\u003e(50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.7\u003c/p\u003e\u003cp\u003e(11.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003cp\u003e(0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.6\u003c/p\u003e\u003cp\u003e(9.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.7\u003c/p\u003e\u003cp\u003e(4.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOverall readiness index for services specific to diabetes [Mean (\u0026plusmn;\u0026thinsp;SD)]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68.2\u003c/p\u003e\u003cp\u003e(39.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.7\u003c/p\u003e\u003cp\u003e(18.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.6\u003c/p\u003e\u003cp\u003e(17.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34.8\u003c/p\u003e\u003cp\u003e(29.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.6\u003c/p\u003e\u003cp\u003e(17.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCardiovascular diseases\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical service, staff and guidelines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88.9\u003c/p\u003e\u003cp\u003e(19.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.4\u003c/p\u003e\u003cp\u003e(33.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.5\u003c/p\u003e\u003cp\u003e(35.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30.8\u003c/p\u003e\u003cp\u003e(50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32.4\u003c/p\u003e\u003cp\u003e(35.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEquipment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.0\u003c/p\u003e\u003cp\u003e(29.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e71.4\u003c/p\u003e\u003cp\u003e(21.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73.9\u003c/p\u003e\u003cp\u003e(11.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e66.9\u003c/p\u003e\u003cp\u003e(34.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e72.4\u003c/p\u003e\u003cp\u003e(17.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiagnostic capacity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.7\u003c/p\u003e\u003cp\u003e(43.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50.8\u003c/p\u003e\u003cp\u003e(31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.8\u003c/p\u003e\u003cp\u003e(5.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedicines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72.2\u003c/p\u003e\u003cp\u003e(39.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.3\u003c/p\u003e\u003cp\u003e(10.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003cp\u003e(1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.7\u003c/p\u003e\u003cp\u003e(14.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.6\u003c/p\u003e\u003cp\u003e(5.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOverall readiness index for services specific to cardiovascular disease [Mean (\u0026plusmn;\u0026thinsp;SD)]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66.9\u003c/p\u003e\u003cp\u003e(32.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.3\u003c/p\u003e\u003cp\u003e(16.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.5\u003c/p\u003e\u003cp\u003e(12.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40.8\u003c/p\u003e\u003cp\u003e(32.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e29.6\u003c/p\u003e\u003cp\u003e(15.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eChronic respiratory disease (CRD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical service, staff and guidelines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e91.7\u003c/p\u003e\u003cp\u003e(16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.2\u003c/p\u003e\u003cp\u003e(22.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.8\u003c/p\u003e\u003cp\u003e(32.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30.8\u003c/p\u003e\u003cp\u003e(34.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e29.3\u003c/p\u003e\u003cp\u003e(28.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEquipment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61.1\u003c/p\u003e\u003cp\u003e(44.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.6\u003c/p\u003e\u003cp\u003e(31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.7\u003c/p\u003e\u003cp\u003e(34.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32.1\u003c/p\u003e\u003cp\u003e(31.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e29.0 (31.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiagnostic capacity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44.4\u003c/p\u003e\u003cp\u003e(50.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44.9\u003c/p\u003e\u003cp\u003e(38.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003cp\u003e(6.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedicines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57.1\u003c/p\u003e\u003cp\u003e(53.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.2\u003c/p\u003e\u003cp\u003e(13.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.5\u003c/p\u003e\u003cp\u003e(37.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.6\u003c/p\u003e\u003cp\u003e(10.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.1 (26.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOverall readiness index for services specific to CRD [Mean (\u0026plusmn;\u0026thinsp;SD)]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63.6\u003c/p\u003e\u003cp\u003e(41.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.7\u003c/p\u003e\u003cp\u003e(17.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.5\u003c/p\u003e\u003cp\u003e(26.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30.1\u003c/p\u003e\u003cp\u003e(28.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.7\u003c/p\u003e\u003cp\u003e(23.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCervical cancer\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical service, staff and guidelines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66.7\u003c/p\u003e\u003cp\u003e(57.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003cp\u003e(1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.1\u003c/p\u003e\u003cp\u003e(26.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003cp\u003e(2.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.6\u003c/p\u003e\u003cp\u003e(17.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEquipment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72.2\u003c/p\u003e\u003cp\u003e(32.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003cp\u003e(0.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiagnostic capacity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.3\u003c/p\u003e\u003cp\u003e(57.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003cp\u003e(1.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedicines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66.7\u003c/p\u003e\u003cp\u003e(57.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.7\u003c/p\u003e\u003cp\u003e(39.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.8\u003c/p\u003e\u003cp\u003e(55.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.1\u003c/p\u003e\u003cp\u003e(13.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30.7\u003c/p\u003e\u003cp\u003e(44.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOverall readiness index for services specific to cervical cancer [Mean (\u0026plusmn;\u0026thinsp;SD)]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59.7\u003c/p\u003e\u003cp\u003e(51.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.1\u003c/p\u003e\u003cp\u003e(10.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.7\u003c/p\u003e\u003cp\u003e(20.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.8\u003c/p\u003e\u003cp\u003e(3.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.8\u003c/p\u003e\u003cp\u003e(15.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMental health disorder\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical service, staff and guidelines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55.6\u003c/p\u003e\u003cp\u003e(19.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.3\u003c/p\u003e\u003cp\u003e(11.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.7\u003c/p\u003e\u003cp\u003e(9.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.4\u003c/p\u003e\u003cp\u003e(11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.0\u003c/p\u003e\u003cp\u003e(10.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedicines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.5\u003c/p\u003e\u003cp\u003e(25.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003cp\u003e(0.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003cp\u003e(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.6\u003c/p\u003e\u003cp\u003e(6.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003cp\u003e(0.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOverall readiness index for services specific to mental health disorder [Mean (\u0026plusmn;\u0026thinsp;SD)]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.5\u003c/p\u003e\u003cp\u003e(22.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.3\u003c/p\u003e\u003cp\u003e(5.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.9\u003c/p\u003e\u003cp\u003e(4.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.5\u003c/p\u003e\u003cp\u003e(8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.6\u003c/p\u003e\u003cp\u003e(5.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eReadiness index specific to the service for diabetes\u003c/h2\u003e\u003cp\u003eThe readiness index scores of healthcare facilities for diabetes related service are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. All the UHCs (100%) provided clinical services (diagnosis, treatment, or follow-up) for diabetes, whereas approximately three-quarters (73.1%) of the private/NGO facilities and approximately one-third of the ULPHFs (33.3%) and CCs (36.1%) provided the services. CCs and private/NGO facilities reported having no guidelines for the diagnosis and treatment of diabetes; only 2.4% of the ULPHFs and 66.7% of the UHCs had guidelines. All UHCs and 32.4% of CCs had at least one trained staff member for the management of diabetes. All UHCs (100%) were equipped with a glucometer, glucometer strips, and an adult weighing scale. Urine ketone test strips and ophthalmoscopes were not available in any health facility, except in a small proportion of private/NGO facilities \u0026minus;\u0026thinsp;3.8% had urine ketone test strips, and 11.5% had ophthalmoscopes. Both random and fasting blood sugar tests were available in all UHCs (100.0%). Among private/NGO facilities, 92.3% offered random blood glucose testing, whereas 88.5% provided fasting blood glucose testing. The mean domain score for diagnostic capacity was the highest in private/NGO facilities (59.0%), followed by UHCs (51.9%), ULPHFs (9.3%), and CCs (6.2%).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eRegarding diabetes, the mean domain score for UHC was 75.0%, whereas the other facilities had very low scores; private/NGO facilities had 10.6%, ULPHFs had 7.7%, and CCs had only a 0.2% score for medicine availability. Overall, the diabetes service-related mean readiness score varied across healthcare facilities (ranging from 15.6% for CCs to 68.2% for UHCs) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eReadiness index specific to the service for cardiovascular disease (CVD)\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary table 3 presents the facility readiness index for cardiovascular service delivery. The availability of clinical services, guidelines and trained staff for CVD varied greatly among healthcare facilities (ranging from 89.9% in UHCs to 21.4% in ULPHFs). Almost all facilities had a functional blood pressure apparatus (UHCs and private/NGO facilities 100.0%, CCs 92.4%, and ULPHFs 88.1%), an adult weighing machine (UHCs and private/NGO facilities 100%), and a stethoscope (UHCs and private/NGO facilities 100%, ULPHFs 90.5%, and CCs 89.6%). The availability of diagnostic facilities for CVD was low among healthcare facilities. The mean domain scores were 50.8% for private/NGO facilities, 26.7% for UHCs, and 0.0% for ULPHFs and CCs. Calcium channel blockers, angiotensin receptor blockers, and thiazide diuretics were available in all UHCs (100%), but their availability varied among other health facilities (from 0.0% to 53.8%). The overall mean readiness index score was highest for UHCs (66.9%) and lowest for ULPHFs (25.3%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eReadiness index specific to the service for chronic respiratory diseases (CRD)\u003c/h2\u003e\u003cp\u003eThe items related to service for CRD are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary table 4. Clinical services for asthma and chronic obstructive pulmonary disease (COPD) were available for all UHCs (100.0%). Services for both asthma and COPD were less commonly available at ULPHFs (50.0% and 26.2%, respectively), CCs (75.9% and 18.5%), and private/NGO facilities (69.2% and 50.0%). The mean domain score for equipment varied among healthcare facilities, from 61.1% for UHCs to 26.7% for CCs. Only UHCs and private/NGO facilities had diagnostic facilities available, with mean domain scores of 44.4% and 44.9%, respectively. For medicines, the mean domain score ranged from 8.2% for the ULPHFs to 57.1% for the UHCs. The overall readiness index was the highest for UHCs (63.6%), followed by private/NGO facilities (30.1%), CCs (19.5%), and ULPHFs (14.7%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eReadiness index specific to the service for cervical cancer\u003c/h2\u003e\u003cp\u003eThe readiness index scores of healthcare facilities for services related to cervical cancer are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary table 5. Although 45.4% of the CCs had at least one trained staff member regarding cervical cancer, along with ULPHFs and private/NGO facilities, they did not provide any clinical services. All the UHCs (100.0%) provided clinical services and had at least one staff member; however, guidelines for cervical cancer management were unavailable in all facilities. Only UHCs had equipment for cervical cancer management with a mean domain score of 72.2%. All (100.0%) the UHCs provided visual inspection with the acetic acid (VIA) test, but the other diagnostic facilities were unavailable. The mean domain score for the availability of medicines was highest for UHCs (66.7%) and lowest for private and NGO facilities (14.1%). The readiness index for the overall services for cervical cancer was highest in UHCs (59.7%) and lowest in private and NGO facilities (3.8%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eReadiness index specific to the service for mental health\u003c/h2\u003e\u003cp\u003eTracer items related to mental health services are listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary table 6. Sixty seven percent of the UHCs, 18.5% of the CCs and approximately 19.0% of the ULPHFs and private/NGO facilities provided clinical services for mental health. Guidelines were only available in UHCs (33.3%), and 4.6% of the CCs and 66.7% of the UHCs had at least one trained staff member. For the availability of medicines, the mean domain score was 9.5% for UHCs, which was the highest, followed by 6.6% for private/NGO facilities. The general readiness index for mental healthcare was highest in UHCs (32.5%) and lowest in ULPHFs (3.3%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge, our study is the first to explore the readiness of both government and private primary healthcare facilities regarding the five NCDs recommended by the WHO in rural Bangladesh. We found that the density of health facilities for Chirirbandar met the WHO SARA guidelines (2 per 10,000 population), but the Parbatipur and Biral subdistricts fell short of this standard. All three subdistricts had critical shortages of core health workers achieving only 21.9\u0026ndash;28.1% of the WHO SARA standard (23 per 10,000 people). The UHCs demonstrated service readiness exceeding the 70% benchmark for basic amenities, medical equipment/supplies, and medicine stocks, though diagnostic capabilities fell below this threshold. None of the primary healthcare facilities at any level met the WHO SARA-recognized minimum standards for the management of all five NCDs. For disease-specific NCDs, CVD, CRD, and diabetes showed higher readiness than cervical cancer and mental health diseases. UHCs had the highest readiness index for all five major NCDs compared with the other facilities (ULPHF, CC, and private/NGO).\u003c/p\u003e\u003cp\u003eThe availability of clinical services, guidelines, and at least one trained staff member was highest for CRD (91.7%), with diabetes and cardiovascular disease services being slightly lower (both 88.9%) at UHC. However, for cervical cancer, the availability of these three components was the lowest in ULPHF (0.8%) and private/NGO facilities (1.3%). A study in Bangladesh reported comparable results, where the guidelines and at least one trained staff member lacked for cervical cancer services at ULPHFs compared with CRD, CVD, and DM \u003csup\u003e24\u003c/sup\u003e. These findings were consistent with a recent systematic review, which revealed that primary healthcare facilities are better equipped in terms of guidelines and at least one trained staff member for DM management compared with cancer care in Bangladesh \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Cancer-related services have historically been limited in Bangladesh, with the primary healthcare system being particularly affected \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. It is evident from various studies across the countries that primary healthcare facilities often lack properly trained frontline workers to manage NCDs\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Studies have also suggested that a shortage of trained health personnel is a common phenomenon in low-and middle-income countries \u003csup\u003e\u003cspan additionalcitationids=\"CR31 CR32 CR33\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Similarly, for NCD-related service delivery, Bangladesh is experiencing a deficit in skilled health workers \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The unequal distribution of the health workforce with rapid turnover heavily affects health service delivery in Bangladesh \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. In these circumstances, periodic training of frontline health workers would be more effective than deploying a disease-specific health workforce. Studies have also shown that adequate training and supervision by non-physicians, clinicians, and staff in nurse-led clinics can deliver effective primary care for NCDs \u003csup\u003e\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe equipment and diagnostic capacity of a healthcare facility play a vital role in the diagnosis, management, and follow-up of NCDs. In our study, we found that UHC had sufficient equipment for CVD and cervical cancer services (readiness scores were 80.0% and 72.2%, respectively) but lacked DM and CRD care (readiness scores were 57.1% and 61.1%, respectively). In addition to CVD care, other health facilities were critically underequipped for DM, CRD, and cervical cancer services. The result is concordant with other studies conducted in Bangladesh, which also reported better availability of CVD care equipment compared to the inadequate resources for DM care \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Primary healthcare facilities with available glucometers frequently face operational challenges, as the devices are often non-functional or lack essential supplies such as test strips and batteries \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. A blood pressure apparatus and stethoscope are required and are used for routine clinical examinations for diseases other than CVD at healthcare facilities. Moreover, the NCDC provides a digital blood pressure apparatus at the NCD corners of the UHCs. This might explain the better availability of CVD-care-related equipment in healthcare facilities.\u003c/p\u003e\u003cp\u003eAlthough private or NGO facilities had higher readiness scores for diagnostic services related to diabetes, CVD, and CRD, none of the healthcare facilities met the WHO SARA benchmark for service readiness. This finding is consistent with previous research in Bangladesh, which highlighted the limited diagnostic readiness for NCD management in general \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Other studies conducted in Bangladesh have also reported higher diagnostic readiness scores for NCD services in private and NGO healthcare facilities \u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Laboratory tests in primary healthcare facilities may enhance diagnostic accuracy and patient outcomes \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Inadequate necessary supplies (reagents and equipment), improper maintenance, and lack of trained and regular human resources to operate available equipment are barriers to laboratory diagnostic services at public healthcare facilities at the PHC level \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Moreover, the deceitful behavior of some healthcare staff at public healthcare facilities has led patients to private facilities or higher-level facilities for basic laboratory tests \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. This may incentivize private facilities to further strengthen their laboratory diagnostic services, which are often a key source of revenue for these institutions. All these factors subsequently increase the out-of-pocket expenditure of patients, resulting in a drop out of treatment.\u003c/p\u003e\u003cp\u003eNCDs require uninterrupted access to medicines for effective disease management. Our study revealed that only medicines for DM and CVD were available at the UHC, according to the WHO SARA standard, which is consistent with the findings of a study conducted in northeastern Bangladesh\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The availability of medicine was the highest for CRD and the lowest for mental health disorders. Comparable results were observed in another study conducted in similar settings \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Mental healthcare provision is disproportionately concentrated in urban areas, leaving rural primary and secondary health facilities severely underserved \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. The absence of NCD-related medication supplies or substandard drug quality in public healthcare institutions has emerged as a primary source of patient discontent, ultimately driving individuals toward private sector purchases that significantly increase out-of-pocket health expenditures \u003csup\u003e\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Collectively, these factors disproportionately impact socioeconomically disadvantaged populations, contributing to medication non-adherence and consequently resulting in poor control of hypertension, diabetes and other NCDs \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe 4th HPNSP model explicitly mentioned potential roles for ULPHFs and CCs in a team-based NCD care model, including screening, routine follow-up, and drug refill, through an upward and backward referral system with NCD corners\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. By shifting stable patients from doctor-run facilities (UHCs) to non-physician-led centers (ULPHFs and CCs) with the support of digital technology and task redistribution, subdistrict-level NCD corners could focus on managing more complicated cases, and the primary care system as a whole may cater to a much larger patient population.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e Moreover, this approach reduces travel-related costs and increase the accessibility of NCD services, especially in those hard-to-reach rural areas.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e The rapid development of digital tools for care coordination and clinical decision support provides important opportunities to support decentralized primary care.\u003csup\u003e\u003cspan additionalcitationids=\"CR50 CR51\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e Studies have provided early evidence that utilizing lower-level primary healthcare facilities may enhance treatment outcomes for hypertension and diabetes.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e Within this model of care, requirements of guidelines, healthcare staff training, medications, diagnostic facilities, and equipment would be less stringent for these peripheral primary care facilities, and thus the commonly used 70% cutoff may not apply to these grassroot-level primary care facilities. Consistent with previous studies,\u003csup\u003e16, 19\u003c/sup\u003e we found that the domain scores for the availability of NCD medicines across all five major NCDs were critically low in the ULPHF and CC. Majority of these facilities are not prepared to take responsibility for providing NCD care in a team-based decentralized model. More investment in peripheral primary care facilities is urgently needed to improve the availability and accessibility of much needed NCD care in rural Bangladesh.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and limitations of the study\u003c/h2\u003e\u003cp\u003eA key strength of this study is that it examined a thorough scenario for all five NCDs prioritized by the WHO in primary healthcare settings. The study included all the registered healthcare facilities across the three subdistricts, providing a comprehensive overview of NCD service delivery in these areas. We also acknowledge several limitations. First, the assessment of readiness indicators following the WHO-SARA manual considers only supply-side determinants, such as infrastructure, medical equipment, and human resources. This approach does not fully capture complex interactions and contextual determinants influencing broader health system dynamics. Second, part of the data relied on subjective responses of the respondents that could not be independently verified. Because of restricted availability of facility records, data provided by facility managers could not be verified through cross-checking, and this could have resulted in some bias. Third, the study was focused on rural primary healthcare centers in three subdistricts, which may limit the generalizability of the findings because urban healthcare centers were not included. Additionally, the cross-sectional design of the study only reflected the state of healthcare facilities on specific days of data collection, limiting insight into long-term trends or variability.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study findings reveal that while certain domains of NCD service delivery readiness at UHCs showed adequate scores, overall preparedness for NCD management remains critically low across public and private/NGO primary healthcare facilities. The most important obstacles to delivering quality NCD services include insufficient clinical services, lack of adequately trained staff, no guidelines, inadequate diagnostic capacity, and stockout of priority medicines. Although the government of Bangladesh has initiated several important programs, universal health coverage is to be achieved by an integrated multisectoral strategy offering ensured access to skilled health professionals, essential medicines, and functional diagnostic equipment at the primary care level.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePHC: Primary healthcare; NCDs: Non-communicable diseases; WHO: World Health Organization; SARA: Service Availability and Readiness Assessment; HHFA: Harmonized Health Facility Assessment; ULPHFs: Union-level public health facilities; CC: Community clinic; UHC: Upazila (sub-district) Health Complex; HPNSP: Health, Population, Nutrition Sector Program; NCDC: Non-communicable Disease Control Program; CVD: Cardiovascular disease; DM: Diabetes mellitus; COPD: Chronic obstructive pulmonary disease; CRD: Chronic respiratory disease; DGHS: Directorate General of Health Services\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere appreciation to all the participants in this study for their valuable time and contributions. We also extend our gratitude to the Line Director of the Non-Communicable Disease Control Program, Directorate General of Health Services, Ministry of Health and Family Welfare, for granting permission to conduct this research and collect data from healthcare facilities. Special thanks are due to the Civil Surgeon of Dinajpur and the Upazila Health and Family Planning Officers of the three sub-districts for their generous support and coordination during data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the National Institute for Health and Care Research (NIHR) (16/136/68) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data are available to researchers upon reasonable request to the study data access committee. Contact forms and emails are provided on the GHRU website (www.ghru-southasia.org).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWX, MKM, BO and JC conceptualized the study, while WX and MKM were responsible for its design. Data collection was carried out by TS and AA. TS performed the data analysis and the interpretation of findings. TS drafted the initial version of the manuscript. TS, FA, MKM and WX were involved in the critical revision and contributed to enhancing the intellectual content of the manuscript. All authors reviewed and approved the final version for submission. The authors bear sole responsibility for the accuracy of the data analysis and the integrity of the manuscript\u0026rsquo;s content.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participant\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of James P Grant School of Public Health, BRAC University (reference number: IRB-16-November-23-041). The ethical approval was done in accordance with the Declaration of Helsinki. Informed written consent was obtained from all participants and their participation was voluntary. Confidentiality and anonymity of the information provided were assured to the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eBRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh; \u003csup\u003e2\u003c/sup\u003eNanyang Technological University, Singapore; \u003csup\u003e3\u003c/sup\u003eBaker Heart and Diabetes Institute, Melbourne, Australia; \u003csup\u003e4\u003c/sup\u003eTyree Foundation Institute of Health Engineering, UNSW Sydney, NSW 2052, Australia; \u003csup\u003e5\u003c/sup\u003eSprightly Pte Ltd, Singapore; \u003csup\u003e6\u003c/sup\u003eGoogle Health, Palo Alto, CA, USA; \u003csup\u003e7\u003c/sup\u003eSchool of Psychology and Public Health, La Trobe University, Melbourne, Australia; \u003csup\u003e8\u003c/sup\u003eDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK\u003cstrong\u003e\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. 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Designing and implementing an integrated non-communicable disease primary care intervention in rural Nepal. \u003cem\u003eBMJ Glob Health\u003c/em\u003e. 2019;4(2):e001343. doi:10.1136/bmjgh-2018-001343\u003c/li\u003e\n\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":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Non-communicable diseases, Bangladesh, service availability, readiness, primary healthcare","lastPublishedDoi":"10.21203/rs.3.rs-7977902/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7977902/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStrengthening the capacity of primary healthcare (PHC) systems is essential to address the rising burden of non-communicable diseases (NCDs) in Bangladesh. The study assessed the readiness of rural PHC facilities in addressing the five World Health Organization (WHO) priority NCDs: diabetes, cardiovascular diseases, chronic respiratory diseases, cervical cancer, and mental health disorders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween March and April 2024, a cross-sectional survey was conducted in three subdistricts of Dinajpur District, Bangladesh, as a part of a type-2 hybrid effectiveness-implementation trial aimed at evaluating implementation fidelity and examining the process of intervention delivery pertinent to NCD care. All healthcare facilities (government, non-government, and private,) within the study areas were included. Two existing tools, the WHO Service Availability and Readiness Assessment (SARA) and the Harmonized Health Facility Assessment (HHFA), were adapted to evaluate NCD-specific readiness across four domains: clinical services, staff and guidelines; equipment; diagnostic capacity; and essential medicines. Readiness scores were calculated for each domain, with scores ≥ 70% indicating sufficient preparedness for NCD management.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnion-level public health facilities (ULPHFs) had slightly better overall service readiness (39.6%) than community clinics (CC) (38.7%), while upazila (subdistrict) health complexes (UHCs) had the highest overall readiness (82.1%). UHCs had the highest readiness for diabetes care (68.2%), particularly in clinical services, staffing, and guidelines (88.9%). The availability of medicines was critically low in CC (0.2%). Equipment for the management of cardio-vascular diseases was most available (80.0%), whereas cervical cancer equipment was totally unavailable (0.0%) in ULPHFs, CCs, and private/NGO facilities. Chronic respiratory disease and cervical cancer diagnostic capacity were totally absent (0.0%) in ULPHFs and CCs. In mental health service provision, UHCs were the most prepared (32.5%), whereas ULPHFs were the least prepared (3.3%). None of the facilities achieved the 70% threshold of overall readiness for all five NCDs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFindings reveal serious gaps in the readiness of PHC facilities in Bangladesh to respond to NCDs in the four areas. Shortages of trained personnel, absence of standard treatment guidelines, limited diagnostic services, and irregular availability of essential medicines highlight important areas requiring urgent strengthening to enhance PHC readiness and ensure equitable NCD-care provision.\u003c/p\u003e","manuscriptTitle":"The Readiness of Primary Healthcare Facilities to Address Noncommunicable Diseases in Rural Bangladesh","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-12 11:47:51","doi":"10.21203/rs.3.rs-7977902/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-14T10:02:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-13T23:29:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-31T08:51:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"96165228151115788455346098407656110255","date":"2025-12-29T13:57:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-26T05:43:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"183138056769170025985335664609313108143","date":"2025-12-19T08:33:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"14878979512432295534926812935025446558","date":"2025-12-19T08:29:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-15T08:19:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"245022543688653771861361102246368217524","date":"2025-11-05T08:14:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-03T06:10:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-03T05:45:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-02T04:25:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-01T14:11:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2025-11-01T13:42:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5ad97e9c-88c0-432e-818a-d0ef62221fcf","owner":[],"postedDate":"November 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T10:56:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-12 11:47:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7977902","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7977902","identity":"rs-7977902","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}