Health Information Technology Research Articles

Patient-Engagement Health Information Technology and Quality Process Outcomes in Federally Qualified Health Centers.

Health information technology (HIT) for patient-engagement can positively influence the quality and efficiency of health care delivery. Although this topic is of significant importance, it has not been fully addressed in the federally qualified health center (FQHC) context. This research investigates the relationship between the level of patient-engagement HIT and FQHC preventive health care quality outcomes. Based on the Uniform Data System (UDS), this study employed multivariable regression analysis to investigate the association between the level of patient-engagement HIT and FQHC preventive health care quality outcomes. FQHCs were placed in 4 mutually exclusive groups based on the level of FQHC use of patient-engagement HIT. The results indicate that compared with the most comprehensive patient-engagement HIT at FQHCs, less comprehensive patient-engagement HIT was associated with lower rates of preventive care provision. Comprehensive patient-engagement HIT across FQHCs may improve preventive health care quality outcomes. The results support policy incentives for FQHCs with less comprehensive levels of patient-engagement HIT to foster improved preventive care for their patients.

Plugging Public Health Data into the Health IT Ecosystem to Protect National Health

The Covid-19 pandemic exposed many challenges in the United States’ public health systems, and in particular the antiquated data ecosystem that hinders the nation’s ability to use timely data to detect and respond to emerging public health threats. One key challenge of the public health data ecosystem is the limited use of electronic, standardized, and interoperable ways for data to be readily shared between health care delivery and public health systems. At the start of the Covid-19 pandemic, most data exchange between health care and public health, and across public health, was manual, relying on faxes, labor-intensive data entry, and other outdated technology. Although significant progress has been made over the last several years to introduce more standardization and connectivity between public health and health care IT systems, more work is needed. This commentary describes the benefits and potential of robust, modern interoperability between health care and public health systems, defines key policies and technology activities that will drive toward a future state of a highly connected public health and health care data ecosystem, and summarizes potential challenges that must be overcome.

Data Lake, Data Warehouse, Datamart, and Feature Store: Their Contributions to the Complete Data Reuse Pipeline.

The growing adoption and use of health information technology has generated a wealth of clinical data in electronic format, offering opportunities for data reuse beyond direct patient care. However, as data are distributed across multiple software, it becomes challenging to cross-reference information between sources due to differences in formats, vocabularies, and technologies and the absence of common identifiers among software. To address these challenges, hospitals have adopted data warehouses to consolidate and standardize these data for research. Additionally, as a complement or alternative, data lakes store both source data and metadata in a detailed and unprocessed format, empowering exploration, manipulation, and adaptation of the data to meet specific analytical needs. Subsequently, datamarts are used to further refine data into usable information tailored to specific research questions. However, for efficient analysis, a feature store is essential to pivot and denormalize the data, simplifying queries. In conclusion, while data warehouses are crucial, data lakes, datamarts, and feature stores play essential and complementary roles in facilitating data reuse for research and analysis in health care.

Global Perspective on EMR and eHealth

A goal of this exploratory study was to uncover the attitudes of the public towards health information technology (HIT) during a health crisis (COVID-19 pandemic). A socio-technical network formed by EMR/eHealth, COVID-19, and the tweeters was investigated using the Actor-Network-Theory (ANT) to understand global perspectives on healthcare technology, taking into account the human dimension and social reality in technology. Social Media (SM) analytics was used to mine HIT-related tweets from the early phases of the COVID-19 pandemic. Results show that positivity, trust, and anticipation are the three most significant emotions associated with electronic medical records (EMR) and eHealth from the tweets. Our analysis found an acceptance of HIT by the global public and optimism for its role in information dissemination, control and containment, and public health improvement. The ANT analysis reveals a virtual coalition building that occurred through discussions among notable network actors, and the role of crowdsourcing in disseminating digital health information.

Usability Evaluation Ecological Validity: Is More Always Better?

The ecological validity associated with usability testing of health information technologies (HITs) can affect test results and the predictability of real-world performance. It is, therefore, necessary to identify conditions with the greatest effect on validity. We conducted a comparative analysis of two usability testing conditions. We tested a HIT designed for anesthesiologists to detect pain signals and compared two fidelity levels of ecological validity. We measured the difference in the number and type of use errors identified between high and low-fidelity experimental conditions. We identified the same error types in both test conditions, although the number of errors varied as a function of the condition. The difference in total error counts was relatively modest and not consistent across levels of severity. Increasing ecological validity does not invariably increase the ability to detect use errors. Our findings suggest that low-fidelity tests are an efficient way to identify and mitigate usability issues affecting ease of use, effectiveness, and safety. We believe early low-fidelity testing is an efficient but underused way to maximize the value of usability testing.

Unveiling the Adoption and Barriers of Telemedicine in US Hospitals: A Comprehensive Analysis (2017-2022).

Telemedicine has emerged as a vital healthcare delivery model, especially pronounced during the COVID-19 pandemic. Our study uniquely focuses on an institutional lens, examining US hospitals to offer targeted policy implications. To investigate the trend in telemedicine adoption across US hospitals from 2017 to 2022 and analyze the institutional challenges they encounter, particularly in the realm of electronic health information exchange. Cross-sectional study leveraging data from the American Hospital Association's (AHA) annual surveys for the years 2017 to 2021 and the 2022 AHA IT Supplement Survey. The study includes a national sample of US hospitals, covering a diverse range of hospital types including large, nonprofit, teaching, and system-affiliated institutions. US hospitals form the study's participants, with a substantial response rate to the surveys. Key metrics include the number of telemedicine patient encounters, percentage of hospitals offering telemedicine services, and institutional challenges to electronic health information exchange. Telemedicine encounters saw a 75% increase, growing from approximately 111.4 million in 2020 to nearly 194.4 million in 2021. The percentage of hospitals offering at least one form of telemedicine service went from 46% in 2017 to 72% in 2021. Larger, nonprofit, and teaching hospitals were more prone to telehealth adoption, without notable urban-rural disparities. While over 90% of hospitals allow patients to view and download medical records, only 41% permit online data submission. Importantly, 25% of hospitals identified Certified Health IT Developers such as EHR vendor as frequent culprits in information blocking, with cost being the primary obstacle. The findings underscore the rapid yet uneven adoption of telemedicine services in U.S. hospitals. The results point to the need for comprehensive policy interventions to address the challenges identified and realize telemedicine's full potential in healthcare delivery and resilience.

Impact of monitoring and evaluation practices on the performance of Health IT projects coordinated from Nairobi, Kenya

This study investigated the impact of Monitoring and Evaluation (M&E) practices on the performance of Health IT projects coordinated from Nairobi, Kenya. The research problem focused on assessing how M&E planning processes, technical expertise, and stakeholder involvement influence project outcomes. A descriptive cross-sectional survey design was employed, collecting quantitative data through structured questionnaires and qualitative insights via semi-structured interviews with project beneficiaries, health IT staff, and key stakeholders. Results revealed that 82 per cent of respondents agreed that comprehensive M&E planning enhances project execution and outcomes. Additionally, 77 per cent emphasised the importance of technical expertise, while only 42 per cent confirmed adequate stakeholder analysis and 46 per cent agreed on the collection of stakeholder feedback. The findings highlighted the necessity of integrating detailed M&E plans into project designs for systematic tracking of progress and timely corrective actions. Technical expertise is crucial for effective M&E, underscoring the need for continuous training and the selection of competent personnel. Recommendations include developing comprehensive M&E plans at the project's inception, investing in continuous skill development through regular training programs, and enhancing stakeholder engagement strategies by conducting comprehensive stakeholder analyses, collecting regular feedback, and involving stakeholders in key decision-making processes.

Leadership style, change management and job performance of health information management practitioners in tertiary hospitals in South-East, Nigeria

PurposeManaging patients’ health information is one of the building blocks of the health system and the adoption of health information technologies like electronic health records (EHRs) is expected to reduce the various challenges in keeping and accessing quality health-care data that aid decision-making among medical practitioners. This study aims to investigate how leadership styles and change management affected the job performance of health information management practitioners on their adoption of EHRs in tertiary hospitals in Nigeria.Design/methodology/approachThe study used primary data collected using a Likert scale questionnaire from 117 health information management officers and health information technicians in selected tertiary hospitals in South-Eastern Nigeria. The data were analysed using bivariate correlation and multiple regression techniques of inferential statistics.FindingsThe analyses revealed that transformational leadership style, transactional leadership style and change management had significant positive influence on the job performance of health information management practitioners. However, laissez-faire leadership style did not show any significant positive influence. A further analysis showed that the combined effects of leadership styles and change management were also affirmed to significantly influence the adoption of EHRs for quality health-care delivery in Nigerian tertiary hospitals.Originality/valueThe study contributes to health information management and the need to understand how leadership styles and change management can influence the adoption of EHRs. However, there is no adequate research that examined the role of leadership style and change management in influencing the job performance of Nigerian HIM practitioners regarding their usage of EHRs in tertiary hospitals in Nigeria.

Data quality and timeliness analysis for post-vaccination adverse event cases reported through healthcare data exchange to FDA BEST pilot platform.

This study is part of the U.S. Food and Drug Administration (FDA)'s Biologics Effectiveness and Safety (BEST) initiative, which aims to improve the FDA's postmarket surveillance capabilities by using real-world data (RWD). In the United States, using RWD for postmarket surveillance has been hindered by the inability to exchange clinical data between healthcare providers and public health organizations in an interoperable format. However, the Office of the National Coordinator for Health Information Technology (ONC) has recently enacted regulation requiring all healthcare providers to support seamless access, exchange, and use of electronic health information through the interoperable HL7 Fast Healthcare Interoperability Resources (FHIR) standard. To leverage the recent ONC changes, BEST designed a pilot platform to query and receive the clinical information necessary to analyze suspected AEs. This study assessed the feasibility of using the RWD received through the data exchange of FHIR resources to study post-vaccination AE cases by evaluating the data volume, query response time, and data quality. The study used RWD from 283 post-vaccination AE cases, which were received through the platform. We used descriptive statistics to report results and apply 322 data quality tests based on a data quality framework for EHR. The volume analysis indicated the average clinical resources for a post-vaccination AE case was 983.9 for the median partner. The query response time analysis indicated that cases could be received by the platform at a median of 3 min and 30 s. The quality analysis indicated that most of the data elements and conformance requirements useful for postmarket surveillance were met. This study describes the platform's data volume, data query response time, and data quality results from the queried postvaccination adverse event cases and identified updates to current standards to close data quality gaps.

Health Information Technology Use among Foreign-Born Adults of Middle Eastern and North African Descent in the United States.

Health information technology (HIT) use among foreign-born adults of Middle Eastern and North African (MENA) descent is understudied. MENA Americans are currently categorized as "White" in the United States (US) on federal forms. Our purpose was to uncover the prevalence of HIT use among MENA immigrants compared to US- and foreign-born White adults before and after adjusting for covariates. The 2011-2018 National Health Interview Survey data (n = 161,613; ages 18 + years) were analyzed. HIT uses evaluated were searching for health information, filling prescriptions, scheduling appointments, and communicating with healthcare providers via email (last 12months). Crude and multivariable logistic regression models were used to estimate the odds of each HIT use (searching for health information, filling prescriptions, scheduling appointments, and/or communicating with healthcare providers via email), and overall use of any HIT before and after adjustment. The most common HIT use was looking up health information (46.4% foreign-born MENA, 47.8% foreign-born White, 51.2% US-born White; p = .0079). Foreign-born adults of MENA descent had lower odds (OR = 0.64; 95% CI = 0.56-0.74) of reporting any HIT use, but no difference in reporting all HIT uses compared to US-born White adults. This is the first study to explore HIT use among MENA Americans. Results contribute to growing body of literature showing the health of MENA Americans differs from White Americans. A separate racial/ethnic identifier is needed to better capture HIT uses among populations of MENA descent.

Harnessing health information technology to promote equitable care for patients with limited English proficiency and complex care needs

BackgroundPatients with language barriers encounter healthcare disparities, which may be alleviated by leveraging interpreter skills to reduce cultural, language, and literacy barriers through improved bidirectional communication. Evidence supports the use of in-person interpreters, especially for interactions involving patients with complex care needs. Unfortunately, due to interpreter shortages and clinician underuse of interpreters, patients with language barriers frequently do not get the language services they need or are entitled to. Health information technologies (HIT), including artificial intelligence (AI), have the potential to streamline processes, prompt clinicians to utilize in-person interpreters, and support prioritization.MethodsFrom May 1, 2023, to June 21, 2024, a single-center stepped wedge cluster randomized trial will be conducted within 35 units of Saint Marys Hospital & Methodist Hospital at Mayo Clinic in Rochester, Minnesota. The units include medical, surgical, trauma, and mixed ICUs and hospital floors that admit acute medical and surgical care patients as well as the emergency department (ED). The transitions between study phases will be initiated at 60-day intervals resulting in a 12-month study period. Units in the control group will receive standard care and rely on clinician initiative to request interpreter services. In the intervention group, the study team will generate a daily list of adult inpatients with language barriers, order the list based on their complexity scores (from highest to lowest), and share it with interpreter services, who will send a secure chat message to the bedside nurse. This engagement will be triggered by a predictive machine-learning algorithm based on a palliative care score, supplemented by other predictors of complexity including length of stay and level of care as well as procedures, events, and clinical notes.DiscussionThis pragmatic clinical trial approach will integrate a predictive machine-learning algorithm into a workflow process and evaluate the effectiveness of the intervention. We will compare the use of in-person interpreters and time to first interpreter use between the control and intervention groups.Trial registrationNCT05860777. May 16, 2023.

User acceptance of health information technologies (HIT): an application of the theory of planned behavior

Health Information Technologies (HIT) has a significant chance of enhancing the standard of medical treatment, but their acceptance faces major obstacles including low adoption rates and professional hesitancy. Limited research on HIT adoption, especially in poor nations, adds to this problem and clearly challenges health care managers and researchers. It emphasizes the need of knowing the elements influencing acceptance, choice, and usage of healthcare technology to improve user adoption willingness. Using past studies from several nations, this paper investigates the elements driving HIT adoption within the prism of the Theory of Planned Behavior (TPB). Using a Systematic Literature Review (SLR) under direction from the PRISMA framework guaranteed an open and exhaustive study. With eight publications compared to six from wealthy countries, the results expose a notable trend: emerging countries help more to promote HIT adoption research. Furthermore, the combination of TPB with other theories like the Technology Acceptance Model (TAM) provides a whole framework for grasp the elements influencing HIT uptake. Core TPB components include subjective norms, attitude, and perceived behavioral control are well known in industrialized nations and supported by TAM's perceived utility and simplicity of use, along with demographic elements, therefore stressing a user-centric approach. Research on emerging nations, particularly China, shows, on the other hand, a wide spectrum of variables on HIT adoption including personal, technical, social, and institutional ones. The results greatly improve our knowledge of HIT adoption seen from the TPB perspective and provide insightful analysis for legislators developing sensible plans for HIT implementation

Implementation of an EHR-integrated web-based depression assessment in primary care: PORTAL-Depression.

To integrate a computerized adaptive test for depression into the electronic health record (EHR) and establish systems for administering assessments in-clinic and via a patient portal to improve depression care. This article reports the adoption, implementation, and maintenance of a health information technology (IT) quality improvement (QI) project, Patient Outcomes Reporting for Timely Assessment of Life with Depression (PORTAL-Depression). The project was conducted in a hospital-based primary care clinic that serves a medically underserved metropolitan community. A 30-month (July 2017-March 2021) QI project was designed to create an EHR-embedded system to administer adaptive depression assessments in-clinic and via a patient portal. A multi-disciplinary team integrated 5 major health IT innovations into the EHR: (1) use of a computerized adaptive test for depression assessment, (2) 2-way secure communication between cloud-based software and the EHR, (3) improved accessibility of depression assessment results, (4) enhanced awareness and documentation of positive depression results, and (5) sending assessments via the portal. Throughout the 30-month observational period, we collected administrative, survey, and outcome data. Attending and resident physicians who participated in the project were trained in depression assessment workflows through presentations at clinic meetings, self-guided online materials, and individual support. Developing stakeholder relationships, using an evaluative and iterative process, and ongoing training were key implementation strategies. The PORTAL-Depression project was a complex and labor-intensive intervention. Despite quick adoption by the clinic, only certain aspects of the intervention were sustained in the long term due to financial and personnel constraints.

Integrated Application of Health Information Technology in Chronic Disease Management

The prevalence of chronic diseases is a critical challenge for healthcare systems worldwide. This study evaluates the integration of Health Information Technology (HIT) in managing chronic conditions, focusing on Electronic Health Records (EHRs), Mobile Health Monitoring, and Personalized Interventions. We aim to assess the impact of HIT on patient self-management, clinical effectiveness, and quality of life, offering insights for healthcare providers and policymakers.

Evaluation of the Ghanaian Healthcare Environment and Patient Safety context using the SEIPS model of Work System

Objective: This paper aimed to evaluate hazards contributing to patient safety incidents within Ghana’s healthcare system using a human factors engineering model to trace risks across interacting domains. Methods: The Systems Engineering Initiative for Patient Safety (SEIPS) model framed analysis of challenges within the dimensions of healthcare Personnel, Tasks, Tools/Technology, Environment, Organization and Processes. Over 25 studies provided multi-dimensional empirical evidence, with insights synthesized across domains to depict risk pathways enabling patient harm events. Conclusions: The analysis reveals a severely overburdened and constrained healthcare ecosystem unable to reliably deliver safe care processes – with risks stemming from financing limitations, infrastructure deficits, equipment failures, health worker shortages and skills gaps, supply variability, leadership prioritization, and information systems. Solutions require coordinated commitment across these interdependent aspects. Recommendations: Six priority actions are proposed spanning governance, culture, staffing, health IT, quality programs and financing – grounded in concrete evidence-based initiatives but connected through systems thinking. Significance: This systems analysis substantially advances understanding of patient safety threats in Ghana to motivate action. The model approach further demonstrates application of human factors engineering methods to diagnose healthcare quality challenges in limited-resource settings.

Exploring the Trend of Technology Use and Innovation in Health Care Service in Hospitals through a Bibliometric Analysis

Background: Information technology innovation is needed in various fields, including health. In the health sector, technological innovations can be applied to patient care, hospital management and research. Technological innovation can be applied to various hospital activities, from patient data collection to cleaning staff activities. Various innovations are needed to simplify health service activities to make services more effective and efficient. The purpose of the study was to explore the trend of technology use and innovation in health care services in hospitals by analyzing network visualization, overlay visualization, and density visualization on the topic through bibliometric analysis. Main body: In this research, bibliometric analysis was used. Records were identified through a database search at https://app.dimensions.ai/. The data obtained was then selected further by the PRISMA flow diagram. Papers were limited to publication years 2020-2023. The publication type is the article only, on the other hand, book chapters, thesis and proceeding publications are excluded. Data were analyzed using VOSviewer, and then reviewed by co-occurrence and co-authors. From the network visualization, it was identified that there were 199 items divided into 8 clusters with 9,504 links with a total link strength of 54,785. After identifying the clusters, the trends of technology use and innovation in health care services in hospitals were artificial intelligence, digital health technology, electronic health records, health information technology, smart health, telemedicine, virtual care, communication technology, electronic medical records and health care delivery. From the overlay visualization, it was indicated that the newest topics that were widely researched related to this theme were digital health service, digital transformation, digital health technology, digital tools, and telehealth service. From density visualization, it was indicated that topics that were rarely researched related to trends of technology use and innovation in healthcare services in hospitals were communication technology, healthcare organizations, and digital solutions. Conclusion: Technological developments have had a major impact on improving the quality of services in hospitals. Health professionals need to develop and improve their competencies so that they can continue to keep up with current technological developments and innovations.

Patient-Reported Outcome Measures Within a National Multispecialty Surgical Quality Improvement Program

Patient-reported outcome measures (PROMs) are increasingly recognized for their ability to promote patient-centered care, but concerted health information technology (HIT)-enabled PROM implementations have yet to be achieved for national surgical quality improvement. To evaluate the feasibility of collecting PROMs within a national surgical quality improvement program. This was a pragmatic implementation cohort study conducted from February 2020 to March 2023. Hospitals in the US participating in the American College of Surgeons National Surgical Quality Improvement Program and their patients were included in this analysis. Strategies to increase PROM collection rates were identified using the Institute for Healthcare Improvement (IHI) Framework for Spread and the Consolidated Framework for Implementation Research and operationalized with the IHI Model for Improvement's Plan-Do-Study-Act (PDSA) cycles. The primary goal was to accrue more than 30 hospitals and achieve collection rates of 30% or greater in the first 3 years. Logistic regression was used to identify hospital-level factors associated with achieving collection rates of 30% or greater and to identify patient-level factors associated with response to PROMs. At project close, 65 hospitals administered PROMs to 130 365 patients (median [IQR] age, 60.1 [46.2-70.0] years; 77 369 female [59.4%]). Fifteen PDSA cycles were conducted to facilitate implementation, primarily targeting the Consolidated Framework for Implementation Research domains of Inner Setting (ie, HIT platform) and Individuals (ie, patients). The target collection rate was exceeded in quarter 3 (2022). Fifty-eight hospitals (89.2%) achieved collection rates of 30% or greater, and 9 (13.8%) achieved collection rates of 50% or greater. The median (IQR) maximum hospital-level collection rate was 40.7% (34.6%-46.7%). The greatest increases in collection rates occurred when both email and short-message service text messaging were used, communications to patients were personalized with their surgeon's and hospital's information, and the number of reminders increased from 2 to 5. No identifiable hospital characteristic was associated with achieving the target collection rate. Patient age and insurance status contributed to nonresponse. Results of this cohort study suggest that the large-scale electronic collection of PROMs into a national multispecialty surgical registry was feasible. Findings suggest that HIT platform functionality and earning patient trust were the keys to success; although, iterative opportunities to increase collection rates and address nonresponse remain. Future work to drive continuous surgical quality improvement with PROMs are ongoing.

Making Science Computable Using Evidence-Based Medicine on Fast Healthcare Interoperability Resources: Standards Development Project.

Evidence-based medicine (EBM) has the potential to improve health outcomes, but EBM has not been widely integrated into the systems used for research or clinical decision-making. There has not been a scalable and reusable computer-readable standard for distributing research results and synthesized evidence among creators, implementers, and the ultimate users of that evidence. Evidence that is more rapidly updated, synthesized, disseminated, and implemented would improve both the delivery of EBM and evidence-based health care policy. This study aimed to introduce the EBM on Fast Healthcare Interoperability Resources (FHIR) project (EBMonFHIR), which is extending the methods and infrastructure of Health Level Seven (HL7) FHIR to provide an interoperability standard for the electronic exchange of health-related scientific knowledge. As an ongoing process, the project creates and refines FHIR resources to represent evidence from clinical studies and syntheses of those studies and develops tools to assist with the creation and visualization of FHIR resources. The EBMonFHIR project created FHIR resources (ie, ArtifactAssessment, Citation, Evidence, EvidenceReport, and EvidenceVariable) for representing evidence. The COVID-19 Knowledge Accelerator (COKA) project, now Health Evidence Knowledge Accelerator (HEvKA), took this work further and created FHIR resources that express EvidenceReport, Citation, and ArtifactAssessment concepts. The group is (1) continually refining FHIR resources to support the representation of EBM; (2) developing controlled terminology related to EBM (ie, study design, statistic type, statistical model, and risk of bias); and (3) developing tools to facilitate the visualization and data entry of EBM information into FHIR resources, including human-readable interfaces and JSON viewers. EBMonFHIR resources in conjunction with other FHIR resources can support relaying EBM components in a manner that is interoperable and consumable by downstream tools and health information technology systems to support the users of evidence.

The Effect of Health Information Technology Assets on the Sustainability of Health Management Information Systems Usage Moderated by Strategy in Kendari City

Background:Health policies in Indonesia facilitate public access to healthcare information in efforts to improve public health. These policies rely on the support of electronic healthcare information systems to provide health data and information. However, the usage of these systems faces various challenges that affect their sustainability. Objective:To determine the effect of healthcare information technology assets on the sustainability of healthcare management information systems and the role of healthcare information technology strategies as a moderating variable. Methods:This is a quantitative and explanatory research study. The sample consisted of 350 respondents, with a significance level of 0.05. Latent variables included the sustainability of healthcare management information system usage, healthcare information technology assets, and information system strategies, which also served as an intervening variable. Results:The direct effect test yielded a p-value of 0.000 (<0.05), leading to the rejection of the null hypothesis. Thus, healthcare information technology assets and healthcare information technology strategies have a positive and significant effect on the sustainability of healthcare management information system usage. The indirect effect test yielded a p-value of 0.003 (<0.05), also leading to the rejection of the null hypothesis. These results indicate that the healthcare information technology strategies variable moderates the effect of healthcare information technology assets on the sustainability of healthcare management information system usage. Conclusion:Healthcare information technology strategies strengthen the effect of healthcare information technology assets on the sustainability of healthcare management information system usage. Keywords:Health Policy; Health Information Systems; Information Technology; Indonesia

Educational Information Technologies for Fostering Pedagogical Activity and Strengthening Public Health in the Context of Implementing State Policy on the Education of Humanistic-Legal Values

Educational Information Technologies for Fostering Pedagogical Activity and Strengthening Public Health in the Context of Implementing State Policy on the Education of Humanistic-Legal Values