EHR Systems Research Articles

Implementing and Adopting EHR Systems in Developing Countries

Implementing and Adopting EHR Systems in Developing Countries

Practices and systems employed by health professionals toward protection and confidentiality of patient health records in Ghana

ObjectivesHealth information relies on a patient's sensory perceptions as well as objective assessments, diagnoses, and test findings. Ghana's current laws governing the confidentiality of patient health data seems a little pertinent in spite of ongoing conversations on the significance of patient health information and the necessity to protect patient information from improper disclosure. The study therefore investigated the extent of patient confidentiality in Ghana by looking into the guidelines, regulations, and rules that govern patient records. MethodsThe interpretive, phenomenological, and narrative methodologies used in qualitative research were employed to study the phenomenon. Twenty (20) participants were interviewed in a semi-structured manner to gather the data needed for the analysis comprising of Doctors, Nurses, Administrative staff, Record Officers, and Information Communication Technology (ICT0 Technicians of five Departments in La General Hospital. The Activity Theory was used as a theoretical foundation for the study ConclusionsThe study revealed that healthcare professionals uphold the moral standards relating to patient confidentiality and trust. Again, the findings of the study showed that medical records are safely stored through the use of Electronic Health Record system in the hospital in a manner that wouldn't compromise patient confidentiality. However, the results establishes that health care workers can potentially serve as a conduit for the leak or breach of patient information through negligence and unprofessional practices. Public interest statementThe study investigated systems and practices that are employed by health workers in Ghana to ensure that patient health records are safeguarded in order to build patients confidence in how their health records are protected. Health workers were interviewed in this study and the findings of the study show that there are practices and systems put in place to safeguard patient health records in the hospitals. Although, it was established that EHR systems help in safeguarding patient health records, the study recommends the need for users of the Health Electronic Records to be fully involved in the implementation process and strict enforcement of policies regarding the use of the EHR system to help prevent negligence and unprofessional application of the system.

Unlocking success: Multidisciplinary rounds for effective discharge planning.

341 Background: Multidisciplinary rounds (MDR) streamline collaboration among healthcare professionals across various disciplines to devise patient progress and post-hospitalization transition plans. In our gynecology oncology inpatient unit, coordinating patient care involves multiple teams aiming for discharge objectives. While nurses oversee the care plan, physicians, advanced practice providers, case managers, and other key stakeholders possess essential insights to effective discharge planning. The aim of our study was to evaluate the impact of structured MDR implementation on discharge accuracy, effectiveness, and hospital throughput. Methods: In April 2022, our gynecologic oncology inpatient team implemented structured MDRs to enhance discharge processes, focusing on patient outcomes and hospital throughput. The initiative aimed to identify discharge barriers early, set goals, and address challenges collaboratively through: 1) Interdisciplinary Assessment: Using standardized tools to evaluate patient status and care needs; 2) Review of Clinical Data: Analyzing medical records via EHR systems; 3) Collaborative Decision-Making: Using decision-support tools to set the Estimated Discharge Date (EDD); 4) Patient Engagement: Involving patients and families in shared decision-making; 5) Documentation and Communication: Ensuring clear EDD documentation and effective communication through team huddles, bedside rounds, and discharge planning meetings. EDD reporting, discharge order timing, and patient discharge time were tracked using our Care Team Transformation Dashboard. Results: The implementation of structured MDR led to significant improvements in discharge processes. We observed enhanced accuracy in EDD, with a 2.9% increase, and a notable rise in the completion of discharge orders before 9 am, showing a 60.5% increase (Table). The percentage of patients leaving the hospital before noon increased by 20.4%, highlighting MDRs effectiveness in facilitating timely discharge, enhancing intradisciplinary collaboration, and streamlining discharge efficiency. Conclusions: MDRs play a pivotal role in improving teamwork, quality of care, and patient outcomes. Setting EDDs through structured MDR processes enhances proactive discharge planning, thereby reducing delays and optimizing patient flow, ultimately contributing to the delivery of high-quality, patient-centered healthcare. Measure Preintervention: 1/2023-1/2024 Postintervention02-05/2024 Percentage Increase EDD accuracy 1 day prior 46.9 48.3 2.9% Discharge orders before 9am 33.4 53.6 60.5% Discharges prior to noon 19.1 23.0 20.4%

Virtual addressing reality: Development of a virtual social work program to address health-related social needs.

405 Background: Assessment of Health-Related Social Needs (HRSNs) has become an integral part of understanding barriers to care and improving patients’ lives and experiences as they receive cancer care. Increased assessment, however, can result in a raised awareness of unmet needs in oncology patient populations. This tends to highlight gaps in services and necessitate additional staff to attend to these needs. Addressing HRSNs can be facilitated with lay navigators (non-licensed staff), licensed staff, clinical staff, and other members of a multi-disciplinary team. Actions can include, but are not limited to, identification of practical concerns, referrals to community-based organizations (CBOs), referral to the clinical team, or further escalation to a licensed clinical social worker (LCSW). Methods: The National Comprehensive Cancer Network (NCCN) Distress Thermometer screening tool was implemented in July 2023 where patients are screened every 3 months in a community oncology setting. A workflow was established where a clinic staff would administer the screening tool and enter the details of the screening into the EHR system. Based on established criteria, the patient would be referred to the social work team via electronic referral. Due to an increase in screening and subsequent referrals, a virtual team of (5) social workers called Patient Resource Coordinators (PRCs) was established in December 2023 to address the practical concerns and facilitate the coordination of resources based on identified needs. After the team was established, non-urgent referrals were then assigned to a PRC. The PRC could refer to an on-site LMSW/LCSW for higher level of acuity assessment, like crisis support or positive PHQ-9 scores. Results: See Table. Conclusions: The virtual PRC team is able to manage ~55% of referrals made to a social worker based on results from an HRSN screening tool. This has allowed the onsite LMSWs/LCSWs to work at the top of their license and enabled patients to receive support with care coordination and connection to resources. Over time, the referrals managed by the virtual team has increased and their connections to patients have grown. In the future, the PRC team aims to add additional LCSW services to assist patients with higher acuity needs. This will broaden the scope of services available to the patients to address their health-related social needs in a timely manner. PRC Activity Dec ’23 Jan ‘24 Feb ‘24 Mar ’24 Apr ‘24 May ’24 (*May to date at time of submission) # of Referrals Received via EHR 110 542 610 586 1216 570 # of Referrals Assigned to PRC 45 245 299 315 660 312 % of Referrals Assigned to PRC 41% 45% 49% 54% 54% 55% *Secondary Referral to SW 8 9 20 4 # of calls attempted 102 479 536 577 959 448 # of patients reached 38 180 217 270 413 277 % of patients reached 37% 38% 40% 47% 43% 62% # of practical concerns identified 31 131 426 430 742 349 Total Visit Duration (in hrs.) 36hrs 181hrs 348hrs 450hrs 836hrs 485hrs

Exploring home healthcare clinicians' needs for using clinical decision support systems for early risk warning.

To explore home healthcare (HHC) clinicians' needs for Clinical Decision Support Systems (CDSS) information delivery for early risk warning within HHC workflows. Guided by the CDS "Five-Rights" framework, we conducted semi-structured interviews with multidisciplinary HHC clinicians from April 2023 to August 2023. We used deductive and inductive content analysis to investigate informants' responses regarding CDSS information delivery. Interviews with thirteen HHC clinicians yielded 16 codes mapping to the CDS "Five-Rights" framework (right information, right person, right format, right channel, right time) and 11 codes for unintended consequences and training needs. Clinicians favored risk levels displayed in color-coded horizontal bars, concrete risk indicators in bullet points, and actionable instructions in the existing EHR system. They preferred non-intrusive risk alerts requiring mandatory confirmation. Clinicians anticipated risk information updates aligned with patient's condition severity and their visit pace. Additionally, they requested training to understand the CDSS's underlying logic, and raised concerns about information accuracy and data privacy. While recognizing CDSS's value in enhancing early risk warning, clinicians highlighted concerns about increased workload, alert fatigue, and CDSS misuse. The top risk factors identified by machine learning algorithms, especially text features, can be ambiguous due to a lack of context. Future research should ensure that CDSS outputs align with clinical evidence and are explainable. This study identified HHC clinicians' expectations, preferences, adaptations, and unintended uses of CDSS for early risk warning. Our findings endorse operationalizing the CDS "Five-Rights" framework to optimize CDSS information delivery and integration into HHC workflows.

Health professionals’ perceptions of electronic health records system: a mixed method study in Ghana

BackgroundElectronic Health Record systems (EHRs) offer significant benefits and have transformed healthcare in developed countries. However, their implementation and adoption in low- and middle-income countries (LMICs) remains low due to challenges and competing interests. Health professionals’ perception of EHRs can influence their adoption and continued use. The objectives of this study are to explore the perception of health professionals regarding implemented EHR systems in three hospitals in Ghana and identify factors influencing their perception and satisfaction.MethodsIn this study, we employed a concurrent mixed method design to collect data from study participants from May to June 2023. The quantitative part employed a descriptive-survey and the qualitative (in-depth interview) techniques was applied. After obtaining written informed consent from each respondent, a structured survey questionnaire was filled out by the health professionals from three hospitals. An a priori power calculation was used to determine the sample size for the quantitative component. Two hundred and sixty-three (263) health professionals completed the questionnaire from the three facilities. A purposive sampling technique was used to select fifteen [1] participants for the interviews. A semi-structured interview guide was used for the in-depth interviews. The interviews were audio recorded, transcribed, and coded into themes using QSR Nvivo 12 software before thematic content analysis.ResultsOur findings revealed that 213 (80.99%) health professionals perceived the EHRs as beneficial to patients and were generally satisfied. An overwhelming majority, 197 (74.90%) of the health professionals, were satisfied with its use and expressed interest in continuing to use the system. The majority of health professionals viewed the EHRs to have improved their work and workflow processes and provided the desired results. However, few other health professionals were dissatisfied with the system because they viewed the EHRs as frustrating due to unstable internet connectivity and power supply. Other concerns were related to the privacy and confidentiality of patient information. They believe access to patient information should be on a need-to-know basis, and patient information should not be accessible to all other clinicians except those involved directly in their care processes.ConclusionThe study revealed that health professionals have a positive perception of the implemented EHRs, are highly satisfied with them, and are interested in continuing to use them. However, health professionals’ concerns about the unstable power supply, poor internet connectivity, security, and confidentiality of patient’s information need attention, to mitigate their frustrations and boost their confidence in the system.

Impact and Implications of Quantum Computing on Blockchain-based Electronic Health Record Systems

Aims This study will investigate the integration of quantum computing and blockchain technology of EHR systems, evaluating the potential and major vulnerabilities of the developed blockchain platforms. In addition, through this evaluation, in this paper, transaction capabilities, energy consumption, and quantum susceptibilities of Ethereum, Bitcoin, and Ripple are being evaluated. Further, research gaps on quantum implications and transition strategies to quantum-resistant systems for achieving secure, efficient, and patient-centric Healthcare 4.0 are identified. Background The embedding of quantum computing and blockchain technology within EHR systems represents the next wave of scientific development within the healthcare sector. However, at the same time, emerging quantum capabilities have raised serious vulnerabilities for major blockchain platforms. If Ethereum and Bitcoin display quantum threats regarding their high transaction capacities, then Ripple, with its high rate of transactions, truly presents a high stake in terms of quantum threats. Further, the energy consumption discrepancies pose some environmental impacts and point to the need for research on energy-efficient quantum-resistant systems. Objective This research investigates the potential and vulnerabilities of major blockchain platforms with electronic health record systems in a new quantum computing environment. In that context, this work evaluates transaction capacities, quantum threats, and energy use for platforms like Ethereum, Bitcoin, and Ripple. Additionally, it seeks to identify research gaps and propose transition strategies toward a quantum-resistant system in support of the development of a secure and efficient Healthcare 4.0. Methods This work focused on assessing the potential and vulnerabilities of blockchain platforms under quantum computing threats in EHR systems. We analyzed transaction processing rates, quantum susceptibilities, and energy consumption metrics for the Ethereum, Bitcoin, and Ripple platforms. A complete literature review is presented with respect to realistic quantum implications and practical transition strategies toward quantum-resistant systems oriented to support the development of secure and efficient Healthcare 4.0. Results The evaluations revealed that Ethereum processed 30 transactions per second and Bitcoin processed 7, with each having low quantum vulnerability. Ripple, at 1500 transactions per second, also had significant quantum vulnerabilities. In addition to energy use, Bitcoin consumes 707 kWh per single transaction compared with Ripple's 0.0078 kWh. Other gaps in research existed in real-world quantum consequences and considerations for transitioning to quantum-resistant systems, all of which are vital for making Healthcare 4.0 secure and efficient. Conclusion This has underscored the transformative potential as well as the weaknesses involved in integrating quantum computing and blockchain technologies into EHR. However, Ethereum, Bitcoin, and Ripple vary in their transaction rates; all three face a similar quantum threat while having large differences in energy consumption. These are problems that would call for more research into quantum-resistant systems and strategic implementation. Actualization of a secure, efficient, and patient-centered Healthcare 4.0 will call for proactive research collaboration and strategic efforts towards ensuring technological and environmental sustainability.

PheMIME: an interactive web app and knowledge base for phenome-wide, multi-institutional multimorbidity analysis.

To address the need for interactive visualization tools and databases in characterizing multimorbidity patterns across different populations, we developed the Phenome-wide Multi-Institutional Multimorbidity Explorer (PheMIME). This tool leverages three large-scale EHR systems to facilitate efficient analysis and visualization of disease multimorbidity, aiming to reveal both robust and novel disease associations that are consistent across different systems and to provide insight for enhancing personalized healthcare strategies. PheMIME integrates summary statistics from phenome-wide analyses of disease multimorbidities, utilizing data from Vanderbilt University Medical Center, Mass General Brigham, and the UK Biobank. It offers interactive and multifaceted visualizations for exploring multimorbidity. Incorporating an enhanced version of associationSubgraphs, PheMIME also enables dynamic analysis and inference of disease clusters, promoting the discovery of complex multimorbidity patterns. A case study on schizophrenia demonstrates its capability for generating interactive visualizations of multimorbidity networks within and across multiple systems. Additionally, PheMIME supports diverse multimorbidity-based discoveries, detailed further in online case studies. The PheMIME is accessible at https://prod.tbilab.org/PheMIME/. A comprehensive tutorial and multiple case studies for demonstration are available at https://prod.tbilab.org/PheMIME_supplementary_materials/. The source code can be downloaded from https://github.com/tbilab/PheMIME. PheMIME represents a significant advancement in medical informatics, offering an efficient solution for accessing, analyzing, and interpreting the complex and noisy real-world patient data in electronic health records. PheMIME provides an extensive multimorbidity knowledge base that consolidates data from three EHR systems, and it is a novel interactive tool designed to analyze and visualize multimorbidities across multiple EHR datasets. It stands out as the first of its kind to offer extensive multimorbidity knowledge integration with substantial support for efficient online analysis and interactive visualization.

The Proposed Model for Pharmacy Led Med-to-bed Discharge Service in Tertiary Care Hospital

Introduction: The pharmacy-led discharge medication delivery to bedside (Med-to-bed) service in a tertiary care Johns Hopkins Aramco Healthcare (JHAH) hospital aims to optimize medication management during patient transitions from admission to discharge, especially for those with chronic conditions. The service entails the direct delivery of discharge medications to patients at the pharmacy following their discharge from inpatient wards, accompanied by comprehensive medication counseling. The pharmacy-led Med-to-Bed service aims to reduce patient wait times and improve overall clinical outcomes. Methods: This article highlights common challenges in medication reconciliation and post-discharge prescription fulfillment, highlighting the need for standardized protocols and improved hospital adherence to ensure seamless care transitions. It also discusses future considerations for optimizing the Med-to-Bed service, including proposed pharmacy renovations, installing a dedicated robotic dispensing system, and providing private spaces for patient counseling during medication pickup. Additionally, the proposal suggests deploying more pharmacy staff to address delayed discharge orders and making systemic enhancements to the EHR system to streamline prescription pickup. Result: The successful implementation of the proposed pharmacy-led Med-to-Bed service demonstrates the efficacy of interdisciplinary collaboration among nurses, physicians, and pharmacists. Through this collaborative approach, the Med-to-Bed service has shown tangible improvements in operational efficiency and patient outcomes, underscoring its potential to transform healthcare delivery models. Conclusion: Overall, this proposed model provides valuable insights into the transformative impact of integrated care initiatives like the Med-to-bed service in tackling complex medication management and enhancing quality patient care in hospitals.

Machine learning-based prediction of vancomycin concentration after abdominal administration in patients with peritoneal dialysis-related peritonitis.

Peritonitis is a serious complication of peritoneal dialysis (PD), in which insufficient control of antibacterial drug concentrations poses a significant risk for poor outcomes. Predicting antibacterial drug concentrations is crucial in clinical practice. The limitations imposed by compartment models have presented a considerable challenge. In this study, we employed machine learning as model-free methods to circumvent the constraints of compartment models. We collected data from 68 observations from 38 patients with peritoneal dialysis-related peritonitis who were treated with vancomycin from the EHR system. This data included information about drug administration, demographic details, and experimental indicators as predictors. We constructed models using Genetic Adaptive Supporting Vector Regression (GA-SVR), KNN-regression, GBM, XGBoost, and a stacking ensemble model. Additionally, we used RMSE loss and partial-dependence profiles to elucidate the effects of these predictors. GA-SVAR outperformed other large-scale models. In 10-fold cross-validation, the RMSE ratio and R-squared values for direct concentration prediction were 23.5% and 0.633, respectively. The ROC AUC for predicting concentrations below 15 and exceeding 20 μg/mL were 0.890 and 0.948, respectively. Notably, the most influential predictors included times of drug administration and weight. These predictors were also influenced by residual kidney function. To assist in controlling vancomycin concentrations for patients with PD-related peritonitis in clinical practice, we developed GA-SVR and a corresponding explainer model. Our study improves the controlling of vancomycin in clinical settings by enhancing our understanding of vancomycin concentration in patients with PD-related peritonitis.

Evaluation of an electronic health record Drug Interaction Customization Editor (DICE).

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Due to the low specificity of drug-drug interaction (DDI) warnings, hospitals and healthcare systems would benefit from the ability to customize alerts, thereby reducing the burden of alerts while simultaneously preventing harm. We developed a tool, called the Drug Interaction Customization Editor (DICE), as a prototype to identify features and functionality that could assist healthcare organizations in customizing DDI alerts. A team of pharmacists, physicians, and DDI experts identified attributes expected to be useful for filtering DDI warnings. A survey was sent to pharmacists with informatics responsibilities and other medication safety committee members to obtain their opinions about the tool. The survey asked participants to evaluate the 4 sections of the DICE tool (General, Medication, Patient, and Visit) on a scale ranging from 0 (not useful) to 100 (very useful). The survey provided an opportunity for participants to express their opinions on the overall usefulness of the DICE tool and to provide other comments. The 50 survey respondents were mainly pharmacists (n = 47, 94%) with almost half (n = 23, 47%) having health information technology/informatics training. Most respondents (n = 33, 80%) were employed by organizations with over 350 beds. Respondents indicated the most useful features of the DICE tool were the ability to filter DDI warnings based on routes of administrations (mean [SD] rating scale score, 86.5 [21.6]), primary drug properties (85.7 [20.5]) patient attributes (85.6 [16.7]) and laboratory attributes (88.8 [18.0]). The overall impression of the DICE tool was rated at 82.8 (19.0), and when asked about the potential to reduce DDI alerts, respondents rated the tool at 83.7 (21.8). The ability to customize DDI alerts using data elements currently within the EHR has the potential to decrease alert fatigue and override rates. This prototype DICE tool could be used by end users and vendors as a template for developing a more advanced DDI filtering tool within EHR systems.

Generalizability of PGS313 for breast cancer risk in a Los Angeles biobank

Polygenic scores (PGS) summarize the combined effect of common risk variants and are associated with breast cancer risk in patients without identifiable monogenic risk factors. One of the most well-validated PGSs in breast cancer to date is PGS313, which was developed from a Northern European biobank but has shown attenuated performance in non-European ancestries. We further investigate the generalizability of the PGS313 for American women of European (EA), African (AFR), Asian (EAA), and Latinx (HL) ancestry within one institution with a singular EHR system, genotyping platform, and quality control process. We found that the PGS313 achieved overlapping Areas under the ROC Curve (AUCs) in females of Lantix (AUC, 0.68; 95 CI, 0.65-0.71) and European ancestry (AUC, 0.70; 95 CI, 0.69-0.71) but lower AUCs for the AFR and EAA populations (AFR: AUC, 0.61; 95 CI, 0.56-0.65; EAA: AUC, 0.64; 95 CI, 0.60-0.680). While PGS313 is associated with Hormone Positive (HR+) disease in European Americans (OR, 1.42; 95 CI, 1.16-1.64), this association is lost in African, Latinx, and Asian Americans. In summary, we found that PGS313 was significantly associated with breast cancer but with attenuated accuracy in women of African and Asian descent within a singular health system in Los Angeles. Our work further highlights the need for additional validation in diverse cohorts prior to clinical implementation of polygenic scores.

Reducing No-Show Appointments in Preanesthesia Screening

PurposePreanesthesia screening is critical to evaluate the patient’s medical and surgical history prior to any procedure or surgery to assess for risks and to optimize outcomes during the perioperative period. Missed appointments impede the ability to identify comorbidities, perform cardiac testing, review laboratory results and current medications. No-shows also result in a waste of clinical resources and impacts the schedules of Advance Practice Providers (APPs). The purpose of this quality improvement project was to decrease the number of missed appointments in the outpatient preanesthesia and surgical screening clinic and the impact on provider satisfaction. DesignThe design of this quality improvement project was pre and post design. Automated and live phone calls reminders were provided for patients scheduled in the outpatient preanesthesia. Data was collected to compare missed appointment rates from a 3-month period prior to the project implementation and a 3-month period afterwards. MethodsPre-data collection included the number of no-shows in the EHR system from the previous 3 months. Participants included all adult patients who are scheduled for a pre-anesthesia surgical screening appointment. Provider satisfaction was assessed using a 5-question survey, pre and post innovation. FindingsReminder systems had a statistically significant impact on reducing the number of no-shows in the preanesthesia and surgical screening clinic (PASS). No significant impact was shown in provider satisfaction. ConclusionImplementation of a reminder system can help to reduce no show rates in clinics. Patient no-shows overload the health system by reducing the productivity of providers and waste resources including use of clinic staff, longer wait times for other patients, and the timing providers put into chart preparation.

EHR Systems and Blockchain: Potentials, Challenges and the Road Ahead

EHR Systems and Blockchain: Potentials, Challenges and the Road Ahead

Nurse and Physician Perceptions and Decision Making During Interdisciplinary Communication

Errors in decision making and communication play a key role in poor patient outcomes. Safe patient care requires effective decision making during interdisciplinary communication through communication channels. Research on factors that influence nurse and physician decision making during interdisciplinary communication is limited. Understanding influences on nurse and physician decision making during communication channel selection is needed to support effective communication and improved patient outcomes. The purpose of the study was to explore nurse and physician perceptions of and decision-making processes for selecting interruptive or noninterruptive interdisciplinary communication channels in medical-surgical and intermediate acute care settings. Twenty-six participants (10 RNs, 10 resident physicians, and six attending physicians) participated in semistructured interviews in two acute care metropolitan hospitals for this qualitative descriptive study. The Practice Primed Decision Model guided interview question development and early data analysis. Findings include a core category, Development of Trust in the Communication Process, supported by three main themes: (1) Understanding of Patient Status Drives Communication Decision Making; (2) Previous Interdisciplinary Communication Experience Guides Channel Selection; and (3) Perceived Usefulness Influences Communication Channel Selection. Findings from this study provide support for future design and research of communication channels within the EHR and clinical decision support systems.

Transforming Healthcare Data Management: A Blockchain-Based Cloud EHR System for Enhanced Security and Interoperability

The adoption of cloud-based electronic health record (EHR) systems and blockchain technology in healthcare is gaining attention for enhancing data security and interoperability. This research focuses on designing and implementing a blockchain-based cloud EHR system. It explores selecting suitable blockchain technology, cloud infrastructure, and data management methods to ensure patient data confidentiality, integrity, and availability. The architecture and components of the system, including the blockchain network, cloud storage layer, and user interface, are thoroughly discussed. A pilot study evaluates the system’s feasibility and performance, showcasing improved data protection, sharing, and management compared to traditional EHR systems. The potential benefits, drawbacks, and barriers to adoption of a blockchain-based cloud EHR system are examined. This research provides valuable insights and recommendations for healthcare institutions considering the implementation of such systems, addressing the challenges, and offering guidance for successful adoption.

Doctor App- Manipal Health Enterprise

Abstract: The "Doctor App - Manipal Health Enterprise" is a comprehensive healthcare solution designed to enhance the efficiency, accessibility, and quality of healthcare services provided by Manipal Health, a leading healthcare enterprise. This innovative mobile application aims to bridge the gap between healthcare providers and patients, offering a seamless and userfriendly platform for medical consultations, appointments, and health management. The app facilitates remote medical consultations, allowing patients to connect with experienced healthcare professionals from Manipal Health Enterprise. This feature promotes timely access to medical advice and reduces the need for in-person visits. Users can conveniently schedule appointments with healthcare practitioners through the app. This feature streamlines the booking process, reducing waiting times and optimizing the overall patient experience. The app integrates a secure EHR system, enabling patients and healthcare providers to access and manage medical records digitally. This enhances coordination between different healthcare services and ensures comprehensive patient care. The application prioritizes data security and ensures encrypted communication between patients and healthcare professionals. This commitment to privacy instills confidence in users to share sensitive health information. The "Doctor App - Manipal Health Enterprise" not only simplifies healthcare access but also fosters a patient-centric approach by leveraging technology to enhance communication and collaboration between healthcare providers and patients. By embracing the digital transformation of healthcare services, Manipal Health Enterprise aims to deliver a more efficient, patientfriendly, and comprehensive healthcare experience.

An Ontology-Based Architecture to Support Language Variants of Model-Driven Electronic Health Records.

This paper describes the implementation of tools to support multiple language variants of the clinical information models that are used to define a model-driven EHR system. Beyond that, it describes how a complete EHR system can be created with multiple language variants, using the example of an EHR for clinical management of patients in a Fracture Liaison Service. A clinical information model, represented as ontology, was developed in the English language. This model was translated into Spanish and Mandarin, and the modeling tools were refined, on the basis of the experience gained. A workshop was then held, where participants used the EHR tools to create additional language variants in German, French, Portuguese, Arabic, Farsi, Urdu and Somali. The results from the workshop are presented here, with a brief summary of the lessons learned; further work will focus on improving the tools in response to those lessons.

Nurse-centered co-design of an electronic health record nursing summary

BackgroundElectronic health record (EHR) nursing summaries have the potential to support nurses in locating and synthesizing patient information. However, nurses’ role-specific perspectives are often excluded in the design of the EHR system. The purpose of this study was to describe nurses’ current use of nursing summaries and vital sign information within them and glean their ideas for design improvements. MethodsThis research followed Nielsen and Norman's 4-phased design cycle and focused on the discovery and exploration phases to identify the context of nurses' use of the nursing summary (discovery) and to create prototype design layout using physical materials (exploration). ResultsTen clinical inpatient nurses participated in interviews and co-design activities. Nurses hardly use the nursing summary to overview a comprehensive patient's health status. The current design of a nursing summary lacks comprehensive patient information and contains much irrelevant data. Nurses prefer vital signs to be prominently displayed on the summary screen for easy visibility. ConclusionInvolving nurses in the design process can lead to a nursing summary that better meets their needs.

Patient-Reported Outcome Measures (PROMs) in Neurology for Web 3.0 and mHealth: A Conceptual Framework

According to 2019 WHO data, neurological conditions contribute to 1503.39 disability-adjusted life years (DALYs) per 100,000 population. Approximately 57% of office-based physicians use EHR systems and the natural place to incorporate standardized ePRO is into EHR. However, implementing patient-reported outcomes (PROs) for neurological conditions is challenging because many patients are elderly, have comorbidities, and experience cognitive impairment. As healthcare digitization increases, we propose a framework for easily customizable electronic PROs (ePROMs) in neurology. The framework requires implementation of technological standards, including governance plans, integration, and reporting workflows. It consists of four steps: developing an ePRO questionnaire, making ePRO mobile-compatible and user-friendly, building consensus around ePRO, and validating ePRO. It is important to involve all stakeholders in the ePRO development process and continuously monitor and evaluate progress in real-time to sustain ePRO tools over time.