Digital Transformation of Maternal Health data through secure mobile applications: A Pilot Study

Digital Transformation of Maternal Health data through secure mobile applications: A Pilot Study | 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 Digital Transformation of Maternal Health data through secure mobile applications: A Pilot Study Dhanalakshmi P, Lakshmi K, Sreeja PA, Naga Rithesh N, Harikrishnan N, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9124324/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background mHealth is crucial in maternal health. They directly improve access to care & information, which reduces adverse maternal-perinatal outcomes, ultimately playing a vital role in improving overall maternal health. Hypertensive disorders of pregnancy, like gestational hypertension, pre-eclampsia, eclampsia, are a major global health concern, contributing 10–15% of maternal and neonatal complications worldwide, resulting in elevated blood pressure, proteinuria, increased cardiovascular disease, preterm, organ failure, and so on. Objectives The primary aim of this research is to validate a mobile application intervention in improving maternal and fetal outcomes for healthcare data management that enables clinical pharmacists to decentralize the medical history of pregnant women, thereby assisting healthcare providers in diagnosing and planning treatment. Methods The app was designed to be user-friendly for both pregnant women and healthcare providers, with a comprehensive data storage system that aims to prevent the loss of health records. IT professionals developed it, and input was sought from obstetricians. A clinical pharmacist was responsible for entering and monitoring these data. Women diagnosed with HDP and diabetes, participating in a maternal health intervention, were enrolled in the study. After enrolment, the study participants were randomized into an intervention and a non-intervention group, where the intervention group was advised to answer the CPMHA questionnaire to access their maternal health metrics. Then, the intervention group received the maternal health intervention through the maternal health guide, and the non-intervention group received the standard care. Results The primary objective was achieved in the intervention group through the incorporation of an mHealth application. The mobile application significantly reduced the occurrence of missing data for antenatal visits and follow-up. The validity and reliability of the structured questionnaire showed an excellent Cronbach’s alpha of 0.9 for assessing maternal health metrics for intervention. The primary outcome was predominant in the intervention group, aged between 21 and 28, primigravid, employed, literate, and from joint families. Gestational hypertension was seen in most of the maternal mothers. Vaginal deliveries, improved maternal and neonatal outcomes, with higher rates were seen in the intervention than the control group. Conclusion The m-health application for storing and retrieving maternal health data with the help of clinical pharmacist intervention was validated as highly effective, with a positive outcome. From a health perspective, our study promotes collaborative research with app developers, distributors, and health care professionals in order to ensure scalability and impact on maternal delivery outcomes, which follows a standard, safe, validated m-health application. mHealth decentralized record healthcare providers data management digital tools Pregnancy Figures Figure 1 Figure 2 Figure 3 1. Introduction The healthcare industry is undergoing a significant digital transformation, notably the shift from paper to electronic health records. Mobile health (mHealth), which uses mobile phones, is a core part of this change 1 . mHealth improves health outcomes, quality of life, storage of patient information, and communication between patients and healthcare providers. Despite progress, challenges remain across India, especially in maternal and neonatal care, even as the government advances efforts like Ayushman Bharat Digital Mission by creating ABHA ID. mHealth can address these gaps through technology-driven care and optimized health record use 2 . Rural regions seem to have considerable maternal complications owing to restricted access to healthcare. Nearly 28,700 died because of pregnancy complications, mostly averted 3 . The emerging field of digital health applications presents an opportunity to alleviate the pressure being experienced. Particularly, m-Health incorporates and utilizes mobile technology to deliver health care services. Antenatal care plays a vital role in improving pregnancy outcomes. Numerous physiological changes occur during the pregnancy lifecycle, and various diseases can exacerbate these changes. It requires continuous monitoring, early identification, and appropriate intervention to improve their pregnancy outcomes. Nowadays, maternal health is more significant due to the rising incidence of hypertensive disorders during pregnancy 4 . The relevance of the rising prevalence of Hypertensive disorders of pregnancy is a challenge faced by our healthcare providers. Many pregnant women with age, a sedentary lifestyle, and obesity are more prone to high-risk pregnancy. The history of hypertensive disorders leads to future risk of cardiovascular disease, even in older mothers. Effective management of hypertensive disorders not only concerns the immediate outcome but also arrests the further risk and alleviates it 5 . Therapeutic approaches are limited due to their impact on the fetus. A regular clinical visit is necessary for the management of hypertension during pregnancy, with monitoring of blood pressure 6 . In order to achieve blood pressure control and identify potential causes related to HDP, active monitoring of maternal parameters is essential. Educating pregnant women who are complicated by hypertension to prevent cardiovascular disease and to adopt a healthy lifestyle in improving blood pressure control throughout their pregnancy 7 . A mHealth application for managing HDP is already well recognized since most mothers are comfortable using mobile apps, which enables them to be active in managing blood pressure 8 . mHealth enables maternal mothers and healthcare providers in monitoring health metrics, clinical health recording, sending reminders, and giving lifestyle modification information, which enables remote monitoring and enhances communication 9 . Several m-health applications, such as Amma Pregnancy Tracker, Mobile for Mothers, and Baby Bundle are available which help in menstrual cycle monitoring, health education, ovulation prediction, weekly updates, and so on. This research mainly focuses on recording their health records and metrics through a structured procedure and delivering personalized interventions to improve their outcomes. Patients with hypertensive disorders of pregnancy can benefit from improved care and reduction in associated mortality through improved quality services, which are systematic approaches in bringing quality healthcare. Clinical pharmacists plays an important role in delivering pharmaceutical care in personalized therapy management to achieve specific outcomes by improving their quality of life. They optimize the anti-hypertensive therapy based on blood pressure management, improving the drug-related problems, and ensuring safe use 10 . Through clinical pharmacist intervention via Mumma’s track m-health application, our research aims to actively improve outcomes for hypertensive disorders of pregnancy with better blood pressure control. This study focuses on pregnancy monitoring by ruling out complications and comparing it between the intervention and control groups throughout the pregnancy period. Primary Objective : To evaluate the efficacy of clinical pharmacist interventions in improving maternal and neonatal outcomes in pregnant women with hypertensive disorders of pregnancy. Secondary Objectives : To develop an electronic data preservation system for patient profiles. To develop and evaluate a CPMHA questionnaire-based tool to obtain better assessment of pregnant mothers. To compare the maternal and neonatal outcomes in women with hypertensive disorders of pregnancy receiving clinical pharmacist care versus standard care. 2. Study setting It is an open-label, pragmatic trial with parallel randomized 1:1 allocation groups, intended to evaluate the app-assisted care for hypertensive disorders in pregnancy. The study aims to enroll 50 participants with HDP diagnosis, where two intervention groups, in which the comparison of HDP with clinical pharmacist intervention and a control group with standard care alone, will be followed by a one-week post-delivery. 2.1 Eligibility criteria: The pilot study enrolled study participants who met the inclusion and exclusion criteria. The study includes maternal mothers aged from 21 to 40 years, with Hypertensive disorders, were included in the study, Participant with CM/NCM and mixed diet, between 20 and 34 weeks of pregnancy (confirmed by USG or UPT), receiving or prescribed antihypertensive therapy or supportive medication related to HDP management. This study excludes participants younger than 21 years or older than 40 years, participants with chronic diseases, twin babies, and those who consume alcohol and smokes; the study participants are currently enrolled in another clinical or interventional study. Patients having haematological tumours or other blood system diseases, insufficient clinical data, or withdrawal, with severe injuries to the liver, kidney, and other organs 11 . 2.2 Methodology The study was planned in three phases: Phase 1 is the development and validation of a mobile application (Mumma’s track), Phase 2 is assessing the maternal health metrics through validated structured questionnaire with the help of trained clinical pharmacist, Phase 3 involves experimental study by randomizing the study participant and validating their outcomes and optimizing their health data through the developed mobile application. 2.3 Study Procedure: The study participants, based on inclusion and exclusion criteria, were recruited and randomized from the 20th week of gestation. Followed by enrolment, the encrypted application will be installed with the consent of the study participant on their respective mobile device. Then the Clinical Pharmacist Maternal Health Assessment Scale (CPMHA) will be circulated through a mobile application for assessing their perceptions through a structured and validated questionnaire. After validation, their intervention period starts based on their recruitment, from the 28th to 32nd week of the gestational period. Every week, a trained clinical pharmacist will start the intervention using the Clinical Pharmacist Maternal Mothers Guide for about 40–60 minutes. 2.4 Proposed model: The proposed conceptual model illustrates a pathway linking maternal mothers with healthcare providers using a mobile health application to improve the quality of life of maternal and neonatal outcomes. Digital health technology has become an essential advancement in healthcare delivery. The increasing use of mobile applications paves the path for efficient access to share and manage health records with health care professionals to improve the maternal and neonatal outcomes 12 , 13 . The framework includes the development of an encryption m-health application by IT experts with the help of a clinical pharmacist (CP). The randomized study participant was enrolled, and the data were uploaded securely. The application was secured and accessed only with the study participant’s help. Then, during each Antenatal visit, the CP will upload all the necessary data, like medical history, lab investigations, and therapy management. The application itself monitors BP and sends reminders tailored to the participant's needs. 2.5 Phase 1: Application development and validation: A mobile application was developed for pregnant women diagnosed with HDP with other comorbid conditions. Pregnant women with hypertension and diabetes were the main focus group during the design and development phase to ensure the version of the device meets the requirements. The main focus of the app is to serve as a repository for patient medical records. The app stores a wide range of data, including medical history, follow-up of periods and cycles, laboratory investigations, antenatal visits, treatment plans, discharge summaries, and follow-ups, which will be maintained securely throughout their lifetime. To protect patient information, encryption and access controls are provided to secure it. The mobile application features are linked to a hospital-based portal that gathers real-time medical records, which are stored in a mobile application, and enables the timely recording of blood pressure, hospital visits, and their medical records with laboratory investigations, helping the obstetric team to monitor and review patient data. (Fig. 1 ) 2.6 Phase 2: CPMHA scale The structured questionnaire tool was generated to assess the maternal health metrics of pregnant mothers. The item was generated through a literature review with the help of OBG experts. Around 30 questions were initially developed for content validity; items were generated using a five-point Likert scale. The developed questionnaire was converted into Google Forms and shared electronically through email to twelve experts who served as validators for the study. There are 12 validators who were from 2 OBG experts, 2 academic experts, 2 nursing experts, 2 pharmacology professionals, 2 clinical pharmacists, 1 dietician, and 1 Psychologist. The validators were requested to validate the structured questionnaire for clarity, relevance, appropriateness with respect to research objectives, and provide quantitative suggestions, recommendations, and improvements to enhance the overall quality of the study. 2.6.1 Expert Recommendations: After validation, the expert quantitative and qualitative suggestions were carefully reviewed and summarized. It primarily focused on improving the clarity and relevance of the content, and duplications were removed. The overall content was improved with a logical sequence, and the final 24 structured CPMHA scale was developed. The revised tool was subjected to internal consistency and reliability. The content and construct validity certificate was received from the experts. Cronbach’s alpha was calculated for its effectiveness, which was around 0.98, indicating excellent consistency of the developed questionnaire. 2.7 Phase 3: Real-time pilot study data The intervention group received clinical pharmacist intervention with standard care, and the control group received standard care alone. Based on maternal health metrics, the structured questionnaires were sent to the study participants and assessed for intervention. The clinical pharmacist's maternal health intervention program was developed to enhance the maternal and neonatal outcomes through a structured maternal guide, which was prepared by a clinical pharmacist. The study participants received target guidance on three sections for four weeks from the 28th to 32nd weeks of gestation. The intervention mainly focuses on physiological changes during pregnancy, obesity during pregnancy, managing complications during pregnancy, hypertensive disorders in pregnancy with possible comorbidities, symptoms, causes, and risk factors, Medication management, mental health, nutritional management, the benefit of physical activity, birth preparedness, intrapartum and post-partum care 14 . The intervention was delivered through live virtual care during their ANC visit and queries and counselling through the m-health application. Each session contains 4 to 5 mothers, who were guided by a trained clinical pharmacist using interventional techniques. The antenatal monitoring was performed throughout their pregnancy period, and outcomes were compared with the control group. (Fig. 2 ) 2.7.1 Intervention: Mumma’s Track The intervention group consists of pregnant mothers who were diagnosed with hypertensive disorders in pregnancy, who were allowed to access the m-health application, an overarching digital tool framed by a clinical pharmacist to support study participants with blood pressure management through intervention techniques. After recruitment, the study participant will be assessed by a clinical pharmacist through a structured questionnaire. The m-health application bridges communication with the patient, clinical pharmacist, and physician for continuous monitoring during their pregnancy life period as well as post-delivery throughout their lifetime. This digital application, with the help of a CP, will upload all your medical records, previous medical conditions, after every ANC visit, and the application regularly monitors your day-to-day BP levels. In addition to this, from the 28th to 32nd week of gestation, a virtual training session will be conducted per week to educate the maternal mothers using the clinical pharmacist maternal mothers guide. This platform gives an online queries section, counselling facilities, along with other healthcare providers. The app has been featured with monitoring parameters, meditation service, a guide to improve their maternal health, and encourages self-monitoring with reminders to improve adherence and enhance well-being. 2.7.2 Control group It consisted of pregnant mothers with hypertensive disorders of pregnancy complications who did not receive access to Mumma’s track m-health application. The participants were given the standard care by the obstetrics team without clinical pharmacist support to compare with the intervention group. 2.7.3 Data Collection: The maternal and neonatal outcomes were collected through a validated data collection form developed by a trained clinical pharmacist. The maternal health metrics will be sought from the CPMHA scale. Comprehensive information was taken from study participants, such as demographic details, menstrual history, previous medical and surgical history, obstetric history, and relevant antenatal, intranatal, and post-partum details 15 . The data will be prospectively collected during ANC visits and further follow-up visits. The validated data collection form is used to collect maternal and neonatal outcomes across study participants and compare them between the intervention and control groups. 3. Ethical consideration Ethical clearance for the study was obtained from ACS Medical College and Hospital, Institutional Ethics Committee, granted No.07 /2025/IEC/ACSMCH Dated.26.02.2025. The trial was registered in the CTRI portal for approval, and the registered trial no is CTRI/2025/04/084088. Prior to enrollment, consent was obtained from pregnant mothers along with their husband’s approval for conducting the study. The declaration of Helsinki’s ethical principles was followed throughout the study period. 4. Data analysis Statistical analysis was performed by SPSS version 31.0. Sociodemographic data were analysed by descriptive statistics. To compare the categorical outcomes between the intervention and control groups, a Chi-square test was done. Statistical significance was confirmed using a threshold of p < 0.05. 5. Results 5.1 Demographic characteristics A total of 24 items were included in the structured CPMHA questionnaires to assess the maternal health metrics; responses were collected and subjected to validity and reliability. Exploratory Factor Analysis was conducted to evaluate the sample adequacy and factorability of CPMHA questionnaires. The Kaiser-Mayer-Olkin (KMO) measures the sampling adequacy of an overall value of 0.576, suggesting an acceptable level of adequacy in performing the analysis. The measure of Sampling Adequacy values ranges from 0.274 to 0.818. The suitability of the data set was further confirmed by Bartlett’s test, which showed statistically significant values of χ² = 436.812, df = 231, p < 0.001. The Chi-Square fit test was demonstrated by the values of 86.000 with 98 degrees of freedom and a p value of 0.801, suggesting the model fits the observed data set, and the hypothesized factor adequately represents the data set. In this study, Table 1 suggests the demographic characteristics comparing both intervention and control groups to interpret the interventional outcomes. The participants were enrolled between 21 and 40 years of age for both the intervention and control groups. The age group of 21–28 (72% in the experimental group and 56% for control group) showed superior performance to other subcategories. Most of the deliveries were primigravida at the age of 21, with educational level on Diploma/UG/PG showing a significant association with other categories. The pregnant women were satisfied with the advanced, easy application usage and communication. The application stores and retrieves medical information, facilitates easy follow-up and reminders, and creates a stress-free environment for users 16 , 17 . In accordance with occupation, most of the study participants are employed; the remaining were homemakers, who are identical in both intervention and control groups. Regarding gender preference, neutral preference was most predominant in the intervention group 72% and the control group, 40%, compared to the girl/boy preference. Joint family structure was more prevalent in both the intervention 88% and the control group 84%, which shows a significant difference from nuclear families. Significant differences were observed in the husband's workplace in both the intervention and control groups. 60% in the experiment group study were more likely to have their husband in the same locality than the control group, 40%. A physically available spouse will improve their day-to-day betterment of life with constant maternal support. A higher proportion was observed in the control group 72% than in the intervention group, 40% of spouses who lived abroad or outstation. Table 1 Socio-demographic variables Variables Sub Categories Experimental Group % Control Group % p-value The age group of the respondents 21–28 18 72 14 56 0.010 29–34 6 24 7 28 35–40 1 4 4 16 Education Level Up to 10/12th 5 20 15 60 0.007 Diploma/UG/PG 20 80 10 40 Occupation Home-Maker 8 32 14 56 0.009 Employed 17 68 11 44 Parity Primigravida 20 80 10 40 0.005 Multigravida 5 20 15 60 Gender Preference during Pregnancy Neutral 18 72 10 40 0.030 Boy/Girl Baby 7 28 15 60 Family Structure Joint Family 22 88 21 84 0.027 Nuclear Family 3 12 4 16 Husband’s place of work Same Locality 15 60 7 28 0.022 Abroad or Outstation 10 40 18 72 The study compares the types of HDP, symptoms, and outcomes between the intervention and control groups. Most of the study participants had gestational hypertension, 11 in the experimental group and 13 in the control group, followed by chronic hypertension, pre-eclampsia, and one case of eclampsia in the intervention group. No cases of Preeclampsia superimposed in any of the groups. (Table 2 ) Table 2 Types of HDP during the trial Types Experimental group Control group Gestational Hypertension 11 13 Chronic hypertension 7 5 Preeclampsia 6 7 Preeclampsia superimposed 0 0 Eclampsia 1 0 With respect to clinical symptoms, headache was most predominant and occurred in both groups (11 in the experimental group and 14 in the control group). Followed by abdominal pain in 9 in the control group and 2 in the experimental group. Then, there was swelling in the face and feet, which was 6 in the control and 2 in the experimental arm. No blurred vision was observed in either arm, and one case of breathing difficulty was observed in the control group. (Fig. 3 ) In the experimental study, suitable participants will be assessed for eligibility and randomized into an experimental and a control group. The recruited participants in the experimental group from the 2nd trimester will be given four interventional sessions between the 28th and 32nd week of gestation. Supportive call and peer support session by trained professional will be continued till the postnatal phase, the control group will be given the standard care by obstetric experts. Risk assessment will be continued during the antenatal and postnatal period for the intervention group. The maternal and neonatal outcomes from both arms will be compared. Table 3 Assessment Timeline PHASE TIMELINE FOR ASSESSMENT ANTENATAL PHASE POSTNATAL PHASE II TRIMESTER III TRIMESTER WEEK 2 WEEK 4 Enrolment Eligibility Assessment * Randomization * Experimental Group Clinical Pharmacist Maternal Mothers Guide 4 sessions (28 weeks − 32 weeks) Guided Peer Support Session * * * * Supportive Phone Call * * * * Control Group Routine Obstetric Care Assessments during Antenatal Phase Risk assessment * Medication related assessment * * * * Clinical Assessment * * Assessments during Postnatal Phase Post-natal mother assessment * Newborn Assessment * Final Follow up assessment * * The primary outcome was achieved by the experimental group (88%) more than the control group (48%). In the experimental group, 80% delivery was achieved by vaginal and 20% LSCS, and in the control group, 48% through vaginal and 52% LSCS. Indications for LSCS in the experimental group were breech presentation and FHR abnormalities, and in the control group, the indications were the same as those in the experimental group, along with uncontrolled BP and previous LSCS. Oliguria and placental abruption were the most common adverse effects in the experimental arm, and oliguria, placental abruption, PPH, and pulmonary edema were found in the control group. Maternal outcomes with 84% gave term delivery in the experimental group, and 66% in the control group, and 80% gave at an appropriate gestation age in the intervention arm, and 60% in the control arm. Neonatal outcomes have been improved compared to the control group; respiratory distress, jaundice, hypoglycaemia, and growth restriction occurred. Table 4 Maternal and Neonatal Outcomes Variables Sub categories Experimental Group % Control Group % P value Achieved primary Outcome 22 88 12 48 0.005* Delivery Outcomes Vaginal 20 80 12 48 0.039* LSCS 5 20 13 52 Indications for LSCS Breech Presentation 1 4 4 16 0.160 FHR abnormalities 1 4 2 8 0.550 Uncontrolled BP 0 0 5 20 0.050 Failed Induction of Labor 0 0 0 0 - Prev LSCS 2 0 5 20 0.417 Adverse outcomes Oliguria 1 4 5 20 0.080 Pulmonary Edema 0 0 2 8 0.150 Placental abruption 1 4 4 16 0.160 PPH 0 0 5 20 0.050 Maternal death 0 0 0 0 - Maternal outcomes Term 21 84 14 66 0.062 Pre term 4 16 11 44 Post term 0 0 0 0 SGA 3 12 9 36 0.217 AGA 20 80 15 60 LGA 2 8 1 4 Neonatal outcomes Birth asphyxia 0 0 4 16 0.004* Growth restriction 1 4 5 20 Hypoglycemia 1 4 6 24 Meconium liquor/aspiration 0 0 0 0 Neonatal jaundice 2 8 6 12 Sepsis 0 0 4 16 Respiratory distress 1 4 6 24 Neonatal death 0 0 0 0 *p < 0.05 considered statistically significant 6. Discussion HDP is considered major reason for adverse pregnancy outcomes. According to this study, safe and effective management of the medical records of study participants was incorporated in m-health application in intervention group, which was created by a trained clinical pharmacist and developed by an IT professional 18 . Initially the study participant was randomized based on eligibility criteria and analysed their health metrics through CPMHA scale. After analysing the maternal health metrics of such as previous medical history, obstetric history, social support, medication adherence, psychological & antenatal health, Physical health and sleep pattern, subjected to intervention. Based on maternal health metrics, personalised clinical pharmacist maternal health intervention (CPMHI) was delivered to the intervention group throughout their antenatal phase and one month follow up during their postnatal period. The present study compares the hypertensive disorders of pregnancy complications between the intervention and control group through their pregnancy period, which was improved by the involvement of a clinical pharmacist maternal education program, which was conducted during the antenatal and postnatal period 19 , 20 . The age group was between 21 and 40 years; most of the study participants were literate and employed in a private organization. Most of the mothers involved in the study were primigravid with neutral preference on gender preference who are living with their spouse in a joint family. Gestational hypertension was mostly found in hypertensive disorders in pregnancy, followed by chronic hypertension and pre-eclampsia. Clinical status of study participants with symptoms such as headache, followed by abdominal pain and swelling in the face and feet, in both the experimental and control groups 21 – 25 . The complications, along with gestational hypertension, gestational diabetes mellitus, chronic hypertension with gestational diabetes, chronic hypertension with thyroid disorders, and eclampsia with anemia, were observed in both groups 26 – 30 . The primary outcome was to improve the efficacy of clinical pharmacist intervention in improving the maternal and neonatal outcomes. The secondary outcome, such as electronic application, CPMHA scale development and validation, will assess the maternal health metrics and improve with maternal health intervention programs. The primary outcome was achieved in the experimental group compared to the control group, with vaginal delivery outcomes in the experimental arm being higher than in the control arm. Breech presentation, FHR abnormalities, uncontrolled blood pressure, and previous LSCS were the indications for LSCS in both arms. The maternal outcome in the intervention group was achieved with a maximum term and appropriate gestational age in the experiment than in the control group. The neonatal outcomes were also achieved in the experimental group. The clinical pharmacist intervention includes physiological changes during pregnancy, obesity, maternal complications, hypertensive disorders in pregnancy care, managing pregnancy related complications, medication management, maternal mental health, nutritional status, selfcare, breast care, lifestyle modifications, infection control, pregnancy danger signals, fetal movement monitoring, birth preparedness, intranatal care, pain management, post-natal care, importance of newborn care, immunization, cleaning, and post-partum contraception. The importance of medical record keeping is necessary for every individual because missed medical records will not be useful in future therapy management 31 – 34 . 6. Satisfaction Index and Service Expectations The implementation of mobile applications in the healthcare sector enhances societal intelligence. It nurtures the ability to overcome issues such as missing data and the timely handling of medical records during emergencies, providing quick access to medical information for prompt decision-making depending on the situation. The health applications enhance and improve abilities to meet health needs by better allocating and communicating available resources 35 – 37 . 7. Conclusion In a transformative advancement in the prevention and management of hypertensive disorders in pregnancy, through the integration of a mobile application has been developed that addresses the critical gap between the patient and other health care providers. The study was conducted with two parallel groups, an intervention and a control group, by involving a clinical pharmacist as one of the health care providers to improve the maternal and neonatal outcomes. This study achieves the primary and secondary objectives by incorporating m-health involvement, the CPMHA scale to analyse maternal health metrics, and personalised CPMHI using the maternal guide to improve blood pressure management and quality of life of pregnant women. The maternal and neonatal outcomes were improved in the experimental group compared to the control group with maximum effectiveness. It is crucial in the healthcare sector, as it delivers high-quality patient care services and enhances overall monitoring. Despite a consistent approach to data storage, pregnant mothers were included in app-assisted care for HDP by timely recording of BP parameters, which is easily accessible for the obstetric team review. It promoted the betterment of healthcare facilities in maternal and neonatal outcomes. Abbreviations HDP Hypertensive Disorders of Pregnancy HELLP Hemolysis (red blood cell breakdown), Elevated Liver enzymes (indicating liver damage), and Low Platelet count (affecting clotting) BP Blood Pressure LSCS Lower Segment Cesarean Section SGA Small for gestational age LGA Large for gestational age AGA Appropriate for gestational age PPH Post Partum hemorrhage LBW Low birth weight VLBW Very Low Birth Weight CM consanguineous marriage NCM non–consanguineous marriage ANC Antenatal Care CPMHA Clinical Pharmacist Maternal Health Assessment Declarations Author contribution: All authors contributed to the manuscript preparation. The authors would like to thank ACS Medical College and Hospital for providing the sources to conduct the study. Ethical approval - (No.07 /2025/IEC/ACSMCH Dt.26.02.2025) Trial registration number - CTRI/2025/04/084088. Funding Declaration: No funding was received for conducting the study. 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Lunde P, Nilsson BB, Bergland A, Bye A. Feasibility of a mobile phone app to promote adherence to a heart-healthy lifestyle: single-arm study. JMIR formative Res. 2019;3(2):e12679. Al-Arkee S, Mason J, Lane DA, Fabritz L, Chua W, Haque MS, Jalal Z. Mobile apps to improve medication adherence in cardiovascular disease: systematic review and meta-analysis. J Med Internet Res. 2021;23(5):e24190. Denu MK, Shao C, Tak K, Iyengar S, Do K, Nagy NY, Singh G, Sadaniantz KA, Shankara S, Kovell LC. Home blood pressure monitoring and mobile health application practices among pregnant persons with and at risk of hypertensive disorders of pregnancy. Pregnancy Hypertens. 2025;39:101197. Epub 2025 Jan 31. PMID: 39892162; PMCID: PMC12431275. Kwun JS, Choi J, Yoon YE, Choi HM, Park JY, Kim HJ, Lee MJ, Choi BY, Yoo S, Suh JW. Prospective validation of a mobile health application for blood pressure management in patients with hypertensive disorders of pregnancy: study protocol for a randomized controlled trial. Trials. 2024;25(1):435. 10.1186/s13063-024-08200-y . PMID: 38956675; PMCID: PMC11218072. Burgess A, Deannuntis T, Wheeling J. Postpartum Remote Blood Pressure Monitoring Using a Mobile App in Women with a Hypertensive Disorder of Pregnancy. MCN Am J Matern Child Nurs. Jul-Aug. 2024;01(4):194–203. Epub 2024 Jun 27. PMID: 38512155. Kókai LL, Ó, Ceallaigh D, Wijtzes AI, van Roeters JE, Duvekot JJ, Hagger MS, Cawley J, Burdorf A, Rohde KIM, van Kippersluis H. App-Based Physical Activity Intervention Among Women With Prior Hypertensive Pregnancy Disorder: A Randomized Clinical Trial. JAMA Netw Open. 2025;8(4):e252656. 10.1001/jamanetworkopen.2025.2656 . PMID: 40172889; PMCID: PMC11966332. Kitt J, Fox R, Tucker KL, McManus RJ. New Approaches in Hypertension Management: a Review of Current and Developing Technologies and Their Potential Impact on Hypertension Care. Curr Hypertens Rep. 2019;21(6):44. 10.1007/s11906-019-0949-4 . PMID: 31025117; PMCID: PMC6483962. Alshammari HM, Almutairi RI, Ghazwani AY, Aditya RS. Evaluating user satisfaction and engagement in mHealth: Insights from the Integrated Digital Health Engagement Model (IDHEM). Digit Health. 2025;11:20552076251346698. PMID: 40718399; PMCID: PMC12290358. Molla A, Hayelom M, Adamu K, Mihiretu MM, Adem YF. Health data management practice and associated factors among health professionals working in public health facilities in Oromia Special Zone, Amhara, Ethiopia: a cross-sectional study. BMJ Public Health. 2024;2(1). Ngusie HS, Shiferaw AM, Bogale AD, Ahmed MH. Health data management practice and associated factors among health professionals working at public health facilities in resource limited settings. Adv Med Educ Pract. 2021;12:855–62. https://doi.org/10.2147/AMEP.S320769 . Melaku MS, Yohannes L. Data management practice of health extension workers and associated factors in central gondar zone, northwest ethiopia. Front Digit Health. 2024;6:1479184. https://doi.org/10.3389/fdgth.2024.1479184 . Miiro C, Ndawula JC, Musudo E, Nabuuma OP, Mpaata CN, Nabukenya S, Sanya D. Achieving optimal heath data impact in rural african healthcare settings: Measures to barriers in bukomansimbi district, central uganda. Int J Equity Health. 2022;21(1):187. https://doi.org/10.1186/s12939-022-01814-1 . Prakash GH, Kumar DS, Arun V, Yadav D, Gopi A, Garg R. Development and validation of android mobile application in the management of mental health. Clin Epidemiol Global Health. 2025;31:101894. Huda FA, Mahmud MU, Islam TT, Akter S, Kabir SF, Hossain MS, Owolabi OO. Assessing the quality of data for selected reproductive health indicators in designated public health facilities in bangladesh. J Global Health. 2024;14:04259. https://doi.org/10.7189/jogh.14.04259 . Adane A, Adege TM, Ahmed MM, Anteneh HA, Ayalew ES, Berhanu D, Janson A. Routine health management information system data in ethiopia: Consistency, trends, and challenges. Global Health Action. 2021;14(1):12. https://doi.org/10.1080/16549716.2020.1868961 . Boateng GO, Neilands TB, Frongillo EA, Melgar-Quiñonez HR, Young SL. Best Practices for Developing and Validating Scales for Health, Social, and Behavioral Research: A Primer. Front Public Health. 2018;6:149. 10.3389/fpubh.2018.00149 . PMID: 29942800; PMCID: PMC6004510. Ahmad N, Alias FA, Hamat M, Mohamed SA. Reliability analysis: application of cronbach's alpha in research instruments. Pioneering the Future: Delving Into E-Learning's Landscape. 2024 Sep 18:114–9. Kabongo EM, Mukumbang FC, Delobelle P, Nicol E. Explaining the impact of mHealth on maternal and child health care in low- and middle-income countries: a realist synthesis. BMC Pregnancy Childbirth. 2021;21(1):196. 10.1186/s12884-021-03684-x . PMID: 33750340; PMCID: PMC7941738. P D, K, L., PA S. Navigating hypertensive disorders in pregnancy: a systematic review. Discov Public Health. 2026;23:70. https://doi.org/10.1186/s12982-025-01304-z . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 09 May, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviews received at journal 22 Apr, 2026 Reviewers agreed at journal 13 Apr, 2026 Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 30 Mar, 2026 Submission checks completed at journal 30 Mar, 2026 First submitted to journal 30 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9124324","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622922661,"identity":"60891e83-cc31-4c48-8ccb-92fa96412bcc","order_by":0,"name":"Dhanalakshmi P","email":"","orcid":"","institution":"Chettinad Academy of Research and Education","correspondingAuthor":false,"prefix":"","firstName":"Dhanalakshmi","middleName":"","lastName":"P","suffix":""},{"id":622922663,"identity":"ee4c794a-0ef0-47f2-a3cd-235e8ccd6786","order_by":1,"name":"Lakshmi K","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYBACPgY2BmYGBgkQm/EBkODhI6SFDUkLswFICxuRWiBsCYgIIS3sx5I/F+ZYyMvPbn9W+TXHTgZoxMNHN/Bp4Uk7Jj1zm4ThhjtnzG7LbksGOozN2DgHr8PS25h5t0kkGEjksN2W3MYM1MLDJo1XC//z5s8gLfIz0p8VS26rJ0KLRNoBaZAWhhsJZowftx0mRsuzNJAWkF+MpRm3HedhYybgF37+NGOgw+pAIfbw489t1fb87M0PH+PTggDASGHmATGYCalE1sL4g2jVo2AUjIJRMJIAAJt9PUqB8pzrAAAAAElFTkSuQmCC","orcid":"","institution":"Chettinad Academy of Research and Education","correspondingAuthor":true,"prefix":"","firstName":"Lakshmi","middleName":"","lastName":"K","suffix":""},{"id":622922669,"identity":"d74aba8c-fa2a-42e7-ab9c-2a9df453a8ef","order_by":2,"name":"Sreeja PA","email":"","orcid":"","institution":"Dr. M.G.R. Educational and Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Sreeja","middleName":"","lastName":"PA","suffix":""},{"id":622922670,"identity":"628acdcf-31ae-4e81-91a9-152e1f601f07","order_by":3,"name":"Naga Rithesh N","email":"","orcid":"","institution":"Vellore Institute of Technology University","correspondingAuthor":false,"prefix":"","firstName":"Naga","middleName":"Rithesh","lastName":"N","suffix":""},{"id":622922673,"identity":"c1334fcb-73b1-4d66-90e0-d3218b39a587","order_by":4,"name":"Harikrishnan N","email":"","orcid":"","institution":"Dr. M.G.R. Educational and Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Harikrishnan","middleName":"","lastName":"N","suffix":""},{"id":622922674,"identity":"0b3d715a-3d35-4238-8e44-5690bc788892","order_by":5,"name":"Aman Suresh Tharayil","email":"","orcid":"","institution":"Dr. M.G.R. Educational and Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Aman","middleName":"Suresh","lastName":"Tharayil","suffix":""},{"id":622922675,"identity":"d54f988b-e121-427c-b889-51ae3fc3cdae","order_by":6,"name":"Chathreian SR","email":"","orcid":"","institution":"Icon (India)","correspondingAuthor":false,"prefix":"","firstName":"","middleName":"","lastName":"Chathreian","suffix":"SR"}],"badges":[],"createdAt":"2026-03-14 17:53:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9124324/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9124324/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107485280,"identity":"9c82415a-78c0-4f06-a019-1c04016ae358","added_by":"auto","created_at":"2026-04-22 02:34:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":260564,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConceptual framework of Application development\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9124324/v1/67dd2f7747ddf14a23fff98f.png"},{"id":107363236,"identity":"f4ce9161-d6ae-4a2d-a482-aed719de329b","added_by":"auto","created_at":"2026-04-20 18:56:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53238,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConsort flowchart of the study\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9124324/v1/2e3c70b4656a55feb52c92f3.png"},{"id":107487750,"identity":"23156bcb-1d62-439a-86b3-3c008ab34e86","added_by":"auto","created_at":"2026-04-22 02:42:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":36196,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSymptoms during Pregnancy period\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9124324/v1/6089d7547038b2be964bb2d1.png"},{"id":107489371,"identity":"60031b9c-605e-48d3-89d7-3ed719780663","added_by":"auto","created_at":"2026-04-22 02:47:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1021254,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9124324/v1/e231f607-a87b-4342-8e7b-38a7bc2eb6ed.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Digital Transformation of Maternal Health data through secure mobile applications: A Pilot Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe healthcare industry is undergoing a significant digital transformation, notably the shift from paper to electronic health records. Mobile health (mHealth), which uses mobile phones, is a core part of this change\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. mHealth improves health outcomes, quality of life, storage of patient information, and communication between patients and healthcare providers. Despite progress, challenges remain across India, especially in maternal and neonatal care, even as the government advances efforts like Ayushman Bharat Digital Mission by creating ABHA ID. mHealth can address these gaps through technology-driven care and optimized health record use\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Rural regions seem to have considerable maternal complications owing to restricted access to healthcare. Nearly 28,700 died because of pregnancy complications, mostly averted\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The emerging field of digital health applications presents an opportunity to alleviate the pressure being experienced. Particularly, m-Health incorporates and utilizes mobile technology to deliver health care services.\u003c/p\u003e \u003cp\u003eAntenatal care plays a vital role in improving pregnancy outcomes. Numerous physiological changes occur during the pregnancy lifecycle, and various diseases can exacerbate these changes. It requires continuous monitoring, early identification, and appropriate intervention to improve their pregnancy outcomes. Nowadays, maternal health is more significant due to the rising incidence of hypertensive disorders during pregnancy\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The relevance of the rising prevalence of Hypertensive disorders of pregnancy is a challenge faced by our healthcare providers. Many pregnant women with age, a sedentary lifestyle, and obesity are more prone to high-risk pregnancy. The history of hypertensive disorders leads to future risk of cardiovascular disease, even in older mothers. Effective management of hypertensive disorders not only concerns the immediate outcome but also arrests the further risk and alleviates it\u003csup\u003e5\u003c/sup\u003e. Therapeutic approaches are limited due to their impact on the fetus. A regular clinical visit is necessary for the management of hypertension during pregnancy, with monitoring of blood pressure\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. In order to achieve blood pressure control and identify potential causes related to HDP, active monitoring of maternal parameters is essential. Educating pregnant women who are complicated by hypertension to prevent cardiovascular disease and to adopt a healthy lifestyle in improving blood pressure control throughout their pregnancy\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. A mHealth application for managing HDP is already well recognized since most mothers are comfortable using mobile apps, which enables them to be active in managing blood pressure\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. mHealth enables maternal mothers and healthcare providers in monitoring health metrics, clinical health recording, sending reminders, and giving lifestyle modification information, which enables remote monitoring and enhances communication\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Several m-health applications, such as Amma Pregnancy Tracker, Mobile for Mothers, and Baby Bundle are available which help in menstrual cycle monitoring, health education, ovulation prediction, weekly updates, and so on. This research mainly focuses on recording their health records and metrics through a structured procedure and delivering personalized interventions to improve their outcomes.\u003c/p\u003e \u003cp\u003ePatients with hypertensive disorders of pregnancy can benefit from improved care and reduction in associated mortality through improved quality services, which are systematic approaches in bringing quality healthcare. Clinical pharmacists plays an important role in delivering pharmaceutical care in personalized therapy management to achieve specific outcomes by improving their quality of life. They optimize the anti-hypertensive therapy based on blood pressure management, improving the drug-related problems, and ensuring safe use\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Through clinical pharmacist intervention via Mumma\u0026rsquo;s track m-health application, our research aims to actively improve outcomes for hypertensive disorders of pregnancy with better blood pressure control. This study focuses on pregnancy monitoring by ruling out complications and comparing it between the intervention and control groups throughout the pregnancy period.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePrimary Objective\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eTo evaluate the efficacy of clinical pharmacist interventions in improving maternal and neonatal outcomes in pregnant women with hypertensive disorders of pregnancy.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSecondary Objectives\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eTo develop an electronic data preservation system for patient profiles.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo develop and evaluate a CPMHA questionnaire-based tool to obtain better assessment of pregnant mothers.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo compare the maternal and neonatal outcomes in women with hypertensive disorders of pregnancy receiving clinical pharmacist care versus standard care.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"2. Study setting","content":"\u003cp\u003eIt is an open-label, pragmatic trial with parallel randomized 1:1 allocation groups, intended to evaluate the app-assisted care for hypertensive disorders in pregnancy. The study aims to enroll 50 participants with HDP diagnosis, where two intervention groups, in which the comparison of HDP with clinical pharmacist intervention and a control group with standard care alone, will be followed by a one-week post-delivery.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Eligibility criteria:\u003c/h2\u003e \u003cp\u003eThe pilot study enrolled study participants who met the inclusion and exclusion criteria. The study includes maternal mothers aged from 21 to 40 years, with Hypertensive disorders, were included in the study, Participant with CM/NCM and mixed diet, between 20 and 34 weeks of pregnancy (confirmed by USG or UPT), receiving or prescribed antihypertensive therapy or supportive medication related to HDP management. This study excludes participants younger than 21 years or older than 40 years, participants with chronic diseases, twin babies, and those who consume alcohol and smokes; the study participants are currently enrolled in another clinical or interventional study. Patients having haematological tumours or other blood system diseases, insufficient clinical data, or withdrawal, with severe injuries to the liver, kidney, and other organs\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Methodology\u003c/h2\u003e \u003cp\u003eThe study was planned in three phases: Phase 1 is the development and validation of a mobile application (Mumma\u0026rsquo;s track), Phase 2 is assessing the maternal health metrics through validated structured questionnaire with the help of trained clinical pharmacist, Phase 3 involves experimental study by randomizing the study participant and validating their outcomes and optimizing their health data through the developed mobile application.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Study Procedure:\u003c/h2\u003e \u003cp\u003eThe study participants, based on inclusion and exclusion criteria, were recruited and randomized from the 20th week of gestation. Followed by enrolment, the encrypted application will be installed with the consent of the study participant on their respective mobile device. Then the Clinical Pharmacist Maternal Health Assessment Scale (CPMHA) will be circulated through a mobile application for assessing their perceptions through a structured and validated questionnaire. After validation, their intervention period starts based on their recruitment, from the 28th to 32nd week of the gestational period. Every week, a trained clinical pharmacist will start the intervention using the Clinical Pharmacist Maternal Mothers Guide for about 40\u0026ndash;60 minutes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Proposed model:\u003c/h2\u003e \u003cp\u003eThe proposed conceptual model illustrates a pathway linking maternal mothers with healthcare providers using a mobile health application to improve the quality of life of maternal and neonatal outcomes. Digital health technology has become an essential advancement in healthcare delivery. The increasing use of mobile applications paves the path for efficient access to share and manage health records with health care professionals to improve the maternal and neonatal outcomes\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The framework includes the development of an encryption m-health application by IT experts with the help of a clinical pharmacist (CP). The randomized study participant was enrolled, and the data were uploaded securely. The application was secured and accessed only with the study participant\u0026rsquo;s help. Then, during each Antenatal visit, the CP will upload all the necessary data, like medical history, lab investigations, and therapy management. The application itself monitors BP and sends reminders tailored to the participant's needs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Phase 1: Application development and validation:\u003c/h2\u003e \u003cp\u003eA mobile application was developed for pregnant women diagnosed with HDP with other comorbid conditions. Pregnant women with hypertension and diabetes were the main focus group during the design and development phase to ensure the version of the device meets the requirements. The main focus of the app is to serve as a repository for patient medical records. The app stores a wide range of data, including medical history, follow-up of periods and cycles, laboratory investigations, antenatal visits, treatment plans, discharge summaries, and follow-ups, which will be maintained securely throughout their lifetime. To protect patient information, encryption and access controls are provided to secure it. The mobile application features are linked to a hospital-based portal that gathers real-time medical records, which are stored in a mobile application, and enables the timely recording of blood pressure, hospital visits, and their medical records with laboratory investigations, helping the obstetric team to monitor and review patient data. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Phase 2: CPMHA scale\u003c/h2\u003e \u003cp\u003eThe structured questionnaire tool was generated to assess the maternal health metrics of pregnant mothers. The item was generated through a literature review with the help of OBG experts. Around 30 questions were initially developed for content validity; items were generated using a five-point Likert scale. The developed questionnaire was converted into Google Forms and shared electronically through email to twelve experts who served as validators for the study. There are 12 validators who were from 2 OBG experts, 2 academic experts, 2 nursing experts, 2 pharmacology professionals, 2 clinical pharmacists, 1 dietician, and 1 Psychologist. The validators were requested to validate the structured questionnaire for clarity, relevance, appropriateness with respect to research objectives, and provide quantitative suggestions, recommendations, and improvements to enhance the overall quality of the study.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.6.1 Expert Recommendations:\u003c/h2\u003e \u003cp\u003eAfter validation, the expert quantitative and qualitative suggestions were carefully reviewed and summarized. It primarily focused on improving the clarity and relevance of the content, and duplications were removed. The overall content was improved with a logical sequence, and the final 24 structured CPMHA scale was developed. The revised tool was subjected to internal consistency and reliability. The content and construct validity certificate was received from the experts. Cronbach\u0026rsquo;s alpha was calculated for its effectiveness, which was around 0.98, indicating excellent consistency of the developed questionnaire.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Phase 3: Real-time pilot study data\u003c/h2\u003e \u003cp\u003eThe intervention group received clinical pharmacist intervention with standard care, and the control group received standard care alone. Based on maternal health metrics, the structured questionnaires were sent to the study participants and assessed for intervention. The clinical pharmacist's maternal health intervention program was developed to enhance the maternal and neonatal outcomes through a structured maternal guide, which was prepared by a clinical pharmacist. The study participants received target guidance on three sections for four weeks from the 28th to 32nd weeks of gestation. The intervention mainly focuses on physiological changes during pregnancy, obesity during pregnancy, managing complications during pregnancy, hypertensive disorders in pregnancy with possible comorbidities, symptoms, causes, and risk factors, Medication management, mental health, nutritional management, the benefit of physical activity, birth preparedness, intrapartum and post-partum care\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The intervention was delivered through live virtual care during their ANC visit and queries and counselling through the m-health application. Each session contains 4 to 5 mothers, who were guided by a trained clinical pharmacist using interventional techniques. The antenatal monitoring was performed throughout their pregnancy period, and outcomes were compared with the control group. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.7.1 Intervention: Mumma\u0026rsquo;s Track\u003c/h2\u003e \u003cp\u003eThe intervention group consists of pregnant mothers who were diagnosed with hypertensive disorders in pregnancy, who were allowed to access the m-health application, an overarching digital tool framed by a clinical pharmacist to support study participants with blood pressure management through intervention techniques. After recruitment, the study participant will be assessed by a clinical pharmacist through a structured questionnaire. The m-health application bridges communication with the patient, clinical pharmacist, and physician for continuous monitoring during their pregnancy life period as well as post-delivery throughout their lifetime. This digital application, with the help of a CP, will upload all your medical records, previous medical conditions, after every ANC visit, and the application regularly monitors your day-to-day BP levels. In addition to this, from the 28th to 32nd week of gestation, a virtual training session will be conducted per week to educate the maternal mothers using the clinical pharmacist maternal mothers guide. This platform gives an online queries section, counselling facilities, along with other healthcare providers. The app has been featured with monitoring parameters, meditation service, a guide to improve their maternal health, and encourages self-monitoring with reminders to improve adherence and enhance well-being.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.7.2 Control group\u003c/h2\u003e \u003cp\u003eIt consisted of pregnant mothers with hypertensive disorders of pregnancy complications who did not receive access to Mumma\u0026rsquo;s track m-health application. The participants were given the standard care by the obstetrics team without clinical pharmacist support to compare with the intervention group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.7.3 Data Collection:\u003c/h2\u003e \u003cp\u003eThe maternal and neonatal outcomes were collected through a validated data collection form developed by a trained clinical pharmacist. The maternal health metrics will be sought from the CPMHA scale. Comprehensive information was taken from study participants, such as demographic details, menstrual history, previous medical and surgical history, obstetric history, and relevant antenatal, intranatal, and post-partum details\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The data will be prospectively collected during ANC visits and further follow-up visits. The validated data collection form is used to collect maternal and neonatal outcomes across study participants and compare them between the intervention and control groups.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Ethical consideration","content":"\u003cp\u003e Ethical clearance for the study was obtained from ACS Medical College and Hospital, Institutional Ethics Committee, granted No.07 /2025/IEC/ACSMCH Dated.26.02.2025. The trial was registered in the CTRI portal for approval, and the registered trial no is CTRI/2025/04/084088. Prior to enrollment, consent was obtained from pregnant mothers along with their husband\u0026rsquo;s approval for conducting the study. The declaration of Helsinki\u0026rsquo;s ethical principles was followed throughout the study period.\u003c/p\u003e"},{"header":"4. Data analysis","content":"\u003cp\u003eStatistical analysis was performed by SPSS version 31.0. Sociodemographic data were analysed by descriptive statistics. To compare the categorical outcomes between the intervention and control groups, a Chi-square test was done. Statistical significance was confirmed using a threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"5. Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e5.1 Demographic characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 24 items were included in the structured CPMHA questionnaires to assess the maternal health metrics; responses were collected and subjected to validity and reliability. Exploratory Factor Analysis was conducted to evaluate the sample adequacy and factorability of CPMHA questionnaires. The Kaiser-Mayer-Olkin (KMO) measures the sampling adequacy of an overall value of 0.576, suggesting an acceptable level of adequacy in performing the analysis. The measure of Sampling Adequacy values ranges from 0.274 to 0.818. The suitability of the data set was further confirmed by Bartlett\u0026rsquo;s test, which showed statistically significant values of \u0026chi;\u0026sup2; = 436.812, df\u0026thinsp;=\u0026thinsp;231, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. The Chi-Square fit test was demonstrated by the values of 86.000 with 98 degrees of freedom and a p value of 0.801, suggesting the model fits the observed data set, and the hypothesized factor adequately represents the data set.\u003c/p\u003e\n \u003cp\u003eIn this study, Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e suggests the demographic characteristics comparing both intervention and control groups to interpret the interventional outcomes. The participants were enrolled between 21 and 40 years of age for both the intervention and control groups. The age group of 21\u0026ndash;28 (72% in the experimental group and 56% for control group) showed superior performance to other subcategories. Most of the deliveries were primigravida at the age of 21, with educational level on Diploma/UG/PG showing a significant association with other categories. The pregnant women were satisfied with the advanced, easy application usage and communication. The application stores and retrieves medical information, facilitates easy follow-up and reminders, and creates a stress-free environment for users\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eIn accordance with occupation, most of the study participants are employed; the remaining were homemakers, who are identical in both intervention and control groups. Regarding gender preference, neutral preference was most predominant in the intervention group 72% and the control group, 40%, compared to the girl/boy preference. Joint family structure was more prevalent in both the intervention 88% and the control group 84%, which shows a significant difference from nuclear families. Significant differences were observed in the husband\u0026apos;s workplace in both the intervention and control groups. 60% in the experiment group study were more likely to have their husband in the same locality than the control group, 40%. A physically available spouse will improve their day-to-day betterment of life with constant maternal support. A higher proportion was observed in the control group 72% than in the intervention group, 40% of spouses who lived abroad or outstation.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSocio-demographic variables\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSub Categories\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExperimental Group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl Group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eThe age group of the respondents\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u0026ndash;28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u0026ndash;34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u0026ndash;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUp to 10/12th\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiploma/UG/PG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHome-Maker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimigravida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultigravida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender Preference during Pregnancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoy/Girl Baby\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily Structure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJoint Family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNuclear Family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHusband\u0026rsquo;s place of work\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSame Locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbroad or Outstation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe study compares the types of HDP, symptoms, and outcomes between the intervention and control groups. Most of the study participants had gestational hypertension, 11 in the experimental group and 13 in the control group, followed by chronic hypertension, pre-eclampsia, and one case of eclampsia in the intervention group. No cases of Preeclampsia superimposed in any of the groups. (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTypes of HDP during the trial\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTypes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExperimental group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl group\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia superimposed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eWith respect to clinical symptoms, headache was most predominant and occurred in both groups (11 in the experimental group and 14 in the control group). Followed by abdominal pain in 9 in the control group and 2 in the experimental group. Then, there was swelling in the face and feet, which was 6 in the control and 2 in the experimental arm. No blurred vision was observed in either arm, and one case of breathing difficulty was observed in the control group. (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003eIn the experimental study, suitable participants will be assessed for eligibility and randomized into an experimental and a control group. The recruited participants in the experimental group from the 2nd trimester will be given four interventional sessions between the 28th and 32nd week of gestation. Supportive call and peer support session by trained professional will be continued till the postnatal phase, the control group will be given the standard care by obstetric experts. Risk assessment will be continued during the antenatal and postnatal period for the intervention group. The maternal and neonatal outcomes from both arms will be compared.\u0026nbsp;\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAssessment Timeline\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" align=\"left\"\u003e\n \u003cp\u003ePHASE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" align=\"left\"\u003e\n \u003cp\u003eTIMELINE FOR ASSESSMENT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eANTENATAL PHASE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003ePOSTNATAL PHASE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003cp\u003eTRIMESTER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003cp\u003eTRIMESTER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWEEK 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWEEK 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnrolment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEligibility Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRandomization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eExperimental Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical Pharmacist Maternal Mothers Guide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e4 sessions\u003c/p\u003e\n \u003cp\u003e(28 weeks\u0026thinsp;\u0026minus;\u0026thinsp;32 weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGuided Peer Support Session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupportive Phone Call\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRoutine Obstetric Care\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAssessments during Antenatal Phase\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRisk assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedication related assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAssessments during\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePostnatal Phase\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePost-natal mother assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNewborn Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFinal Follow up assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe primary outcome was achieved by the experimental group (88%) more than the control group (48%). In the experimental group, 80% delivery was achieved by vaginal and 20% LSCS, and in the control group, 48% through vaginal and 52% LSCS. Indications for LSCS in the experimental group were breech presentation and FHR abnormalities, and in the control group, the indications were the same as those in the experimental group, along with uncontrolled BP and previous LSCS. Oliguria and placental abruption were the most common adverse effects in the experimental arm, and oliguria, placental abruption, PPH, and pulmonary edema were found in the control group. Maternal outcomes with 84% gave term delivery in the experimental group, and 66% in the control group, and 80% gave at an appropriate gestation age in the intervention arm, and 60% in the control arm. Neonatal outcomes have been improved compared to the control group; respiratory distress, jaundice, hypoglycaemia, and growth restriction occurred.\u0026nbsp;\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMaternal and Neonatal Outcomes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSub categories\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExperimental Group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl Group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eAchieved primary Outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eDelivery Outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVaginal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.039*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLSCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" align=\"left\"\u003e\n \u003cp\u003eIndications for LSCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreech Presentation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.160\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFHR abnormalities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.550\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncontrolled BP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFailed Induction of Labor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrev LSCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.417\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" align=\"left\"\u003e\n \u003cp\u003eAdverse outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOliguria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePulmonary Edema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlacental abruption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.160\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePPH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" align=\"left\"\u003e\n \u003cp\u003eMaternal outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTerm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre term\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePost term\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"8\" align=\"left\"\u003e\n \u003cp\u003eNeonatal outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBirth asphyxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrowth restriction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypoglycemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMeconium liquor/aspiration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeonatal jaundice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSepsis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory distress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeonatal death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"6. Discussion","content":"\u003cp\u003eHDP is considered major reason for adverse pregnancy outcomes. According to this study, safe and effective management of the medical records of study participants was incorporated in m-health application in intervention group, which was created by a trained clinical pharmacist and developed by an IT professional\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Initially the study participant was randomized based on eligibility criteria and analysed their health metrics through CPMHA scale. After analysing the maternal health metrics of such as previous medical history, obstetric history, social support, medication adherence, psychological \u0026amp; antenatal health, Physical health and sleep pattern, subjected to intervention. Based on maternal health metrics, personalised clinical pharmacist maternal health intervention (CPMHI) was delivered to the intervention group throughout their antenatal phase and one month follow up during their postnatal period.\u003c/p\u003e \u003cp\u003eThe present study compares the hypertensive disorders of pregnancy complications between the intervention and control group through their pregnancy period, which was improved by the involvement of a clinical pharmacist maternal education program, which was conducted during the antenatal and postnatal period\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The age group was between 21 and 40 years; most of the study participants were literate and employed in a private organization. Most of the mothers involved in the study were primigravid with neutral preference on gender preference who are living with their spouse in a joint family. Gestational hypertension was mostly found in hypertensive disorders in pregnancy, followed by chronic hypertension and pre-eclampsia. Clinical status of study participants with symptoms such as headache, followed by abdominal pain and swelling in the face and feet, in both the experimental and control groups\u003csup\u003e\u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The complications, along with gestational hypertension, gestational diabetes mellitus, chronic hypertension with gestational diabetes, chronic hypertension with thyroid disorders, and eclampsia with anemia, were observed in both groups\u003csup\u003e\u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe primary outcome was to improve the efficacy of clinical pharmacist intervention in improving the maternal and neonatal outcomes. The secondary outcome, such as electronic application, CPMHA scale development and validation, will assess the maternal health metrics and improve with maternal health intervention programs. The primary outcome was achieved in the experimental group compared to the control group, with vaginal delivery outcomes in the experimental arm being higher than in the control arm. Breech presentation, FHR abnormalities, uncontrolled blood pressure, and previous LSCS were the indications for LSCS in both arms. The maternal outcome in the intervention group was achieved with a maximum term and appropriate gestational age in the experiment than in the control group. The neonatal outcomes were also achieved in the experimental group. The clinical pharmacist intervention includes physiological changes during pregnancy, obesity, maternal complications, hypertensive disorders in pregnancy care, managing pregnancy related complications, medication management, maternal mental health, nutritional status, selfcare, breast care, lifestyle modifications, infection control, pregnancy danger signals, fetal movement monitoring, birth preparedness, intranatal care, pain management, post-natal care, importance of newborn care, immunization, cleaning, and post-partum contraception. The importance of medical record keeping is necessary for every individual because missed medical records will not be useful in future therapy management\u003csup\u003e\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"6. Satisfaction Index and Service Expectations","content":"\u003cp\u003eThe implementation of mobile applications in the healthcare sector enhances societal intelligence. It nurtures the ability to overcome issues such as missing data and the timely handling of medical records during emergencies, providing quick access to medical information for prompt decision-making depending on the situation. The health applications enhance and improve abilities to meet health needs by better allocating and communicating available resources\u003csup\u003e\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"7.\tConclusion","content":"\u003cp\u003eIn a transformative advancement in the prevention and management of hypertensive disorders in pregnancy, through the integration of a mobile application has been developed that addresses the critical gap between the patient and other health care providers. The study was conducted with two parallel groups, an intervention and a control group, by involving a clinical pharmacist as one of the health care providers to improve the maternal and neonatal outcomes. This study achieves the primary and secondary objectives by incorporating m-health involvement, the CPMHA scale to analyse maternal health metrics, and personalised CPMHI using the maternal guide to improve blood pressure management and quality of life of pregnant women. The maternal and neonatal outcomes were improved in the experimental group compared to the control group with maximum effectiveness. It is crucial in the healthcare sector, as it delivers high-quality patient care services and enhances overall monitoring. Despite a consistent approach to data storage, pregnant mothers were included in app-assisted care for HDP by timely recording of BP parameters, which is easily accessible for the obstetric team review. It promoted the betterment of healthcare facilities in maternal and neonatal outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHDP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHypertensive Disorders of Pregnancy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHELLP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHemolysis (red blood cell breakdown), Elevated Liver enzymes (indicating liver damage), and Low Platelet count (affecting clotting)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBlood Pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLSCS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLower Segment Cesarean Section\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSmall for gestational age\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLarge for gestational age\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAppropriate for gestational age\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePost Partum hemorrhage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLBW\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLow birth weight\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVLBW\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVery Low Birth Weight\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econsanguineous marriage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNCM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon\u0026ndash;consanguineous marriage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAntenatal Care\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCPMHA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eClinical Pharmacist Maternal Health Assessment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution:\u0026nbsp;\u003c/strong\u003eAll authors contributed to the manuscript preparation. The authors would like to thank ACS Medical College and Hospital for providing the sources to conduct the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e - (No.07 /2025/IEC/ACSMCH Dt.26.02.2025)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration number\u003c/strong\u003e - CTRI/2025/04/084088.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration:\u003c/strong\u003e No funding was received for conducting the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate:\u003c/strong\u003e The informed consent was obtained from the study participant before conducting the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish Declaration\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e: Nil\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e The datasets generated during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSmyth S, Molphy Z, Tully E, et al. 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Discov Public Health. 2026;23:70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12982-025-01304-z\u003c/span\u003e\u003cspan address=\"10.1186/s12982-025-01304-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"mHealth, decentralized record, healthcare providers, data management, digital tools, Pregnancy","lastPublishedDoi":"10.21203/rs.3.rs-9124324/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9124324/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003emHealth is crucial in maternal health. They directly improve access to care \u0026amp; information, which reduces adverse maternal-perinatal outcomes, ultimately playing a vital role in improving overall maternal health. Hypertensive disorders of pregnancy, like gestational hypertension, pre-eclampsia, eclampsia, are a major global health concern, contributing 10\u0026ndash;15% of maternal and neonatal complications worldwide, resulting in elevated blood pressure, proteinuria, increased cardiovascular disease, preterm, organ failure, and so on.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eThe primary aim of this research is to validate a mobile application intervention in improving maternal and fetal outcomes for healthcare data management that enables clinical pharmacists to decentralize the medical history of pregnant women, thereby assisting healthcare providers in diagnosing and planning treatment.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe app was designed to be user-friendly for both pregnant women and healthcare providers, with a comprehensive data storage system that aims to prevent the loss of health records. IT professionals developed it, and input was sought from obstetricians. A clinical pharmacist was responsible for entering and monitoring these data. Women diagnosed with HDP and diabetes, participating in a maternal health intervention, were enrolled in the study. After enrolment, the study participants were randomized into an intervention and a non-intervention group, where the intervention group was advised to answer the CPMHA questionnaire to access their maternal health metrics. Then, the intervention group received the maternal health intervention through the maternal health guide, and the non-intervention group received the standard care.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe primary objective was achieved in the intervention group through the incorporation of an mHealth application. The mobile application significantly reduced the occurrence of missing data for antenatal visits and follow-up. The validity and reliability of the structured questionnaire showed an excellent Cronbach\u0026rsquo;s alpha of 0.9 for assessing maternal health metrics for intervention. The primary outcome was predominant in the intervention group, aged between 21 and 28, primigravid, employed, literate, and from joint families. Gestational hypertension was seen in most of the maternal mothers. Vaginal deliveries, improved maternal and neonatal outcomes, with higher rates were seen in the intervention than the control group.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe m-health application for storing and retrieving maternal health data with the help of clinical pharmacist intervention was validated as highly effective, with a positive outcome. From a health perspective, our study promotes collaborative research with app developers, distributors, and health care professionals in order to ensure scalability and impact on maternal delivery outcomes, which follows a standard, safe, validated m-health application.\u003c/p\u003e","manuscriptTitle":"Digital Transformation of Maternal Health data through secure mobile applications: A Pilot Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-20 18:56:02","doi":"10.21203/rs.3.rs-9124324/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-09T20:10:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"91533850946737493596995019703346708731","date":"2026-04-29T18:59:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-22T14:29:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"276603464489091851596662297235738077178","date":"2026-04-13T10:01:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-08T05:40:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-30T07:06:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-30T04:15:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2026-03-30T04:10:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"415f0bb1-342e-4792-af89-eb9285fa08a2","owner":[],"postedDate":"April 20th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-09T20:10:00+00:00","index":89,"fulltext":""},{"type":"reviewerAgreed","content":"91533850946737493596995019703346708731","date":"2026-04-29T18:59:50+00:00","index":88,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-20T18:56:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-20 18:56:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9124324","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9124324","identity":"rs-9124324","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}