Status of MyHealthWay and Suggestions for Widespread Implementation, Emphasizing the Utilization and Practical Use of Personal Medical Data

OBJECTIVES

In the Fourth Industrial Revolution, there is a focus on managing diverse medical data to improve healthcare and prevent disease. The challenges include tracking detailed medical records across multiple institutions and the necessity of linking domestic public medical entities for efficient data sharing. This study explores MyHealthWay, a Korean healthcare platform designed to facilitate the integration and transfer of medical data from various sources, examining its development, importance, and legal implications.

METHODS

To evaluate the management status and utilization of MyHealthWay, we analyzed data types, security, legal issues, domestic versus international issues, and infrastructure. Additionally, we discussed challenges such as resource and infrastructure constraints, regulatory hurdles, and future considerations for data management.

RESULTS

The secure sharing of medical information via MyHealthWay can reduce the distance between patients and healthcare facilities, fostering personalized care and self-management of health. However, this approach faces legal challenges, particularly relating to data standardization and access to personal health information. Legal challenges in data standardization and access, particularly for secondary uses such as research, necessitate improved regulations. There is a crucial need for detailed governmental guidelines and clear data ownership standards at institutional levels.

CONCLUSIONS

This report highlights the role of Korea's MyHealthWay, which was launched in 2023, in transforming healthcare through systematic data integration. Challenges include data privacy and legal complexities, and there is a need for data standardization and individual empowerment in health data management within a systematic medical big data framework.

Adoption of Electronic Medical Records in Healthcare Facilities in the Emirate of Dubai

OBJECTIVES

This paper aimed to assess the adoption of electronic medical records (EMRs) in healthcare facilities in Dubai, the largest city in the United Arab Emirates (UAE) and a location where extensive healthcare services are provided. It explored the challenges, milestones, and accomplishments associated with this process.

METHODS

A situation analysis was conducted by contacting 2,089 healthcare facilities in Dubai to determine whether they had implemented EMR in their medical practices and to identify the challenges they faced during this process. Additionally, the Electronic Medical Record Adoption Model (EMRAM) was utilized to measure the maturity level of hospitals in terms of EMR adoption. The EMRAM stages were rated on a scale from 0 to 7, with 0 representing the least mature stage and 7 the most mature.

RESULTS

By September 2023, all hospitals (100%, n = 54) and 75% of private clinics (n = 1,460) in Dubai had implemented EMRs. Several challenges were identified, including the absence of EMRs within the healthcare facility, having an EMR with a low EMRAM score, or the lack of a unified interoperability standard. Additionally, the absence of a clear licensing program for EMR vendors, whether standalone or cloud-based, was among the other challenges noted.

CONCLUSIONS

EMR implementation in healthcare facilities in Dubai is at a mature stage. However, further efforts are required at both the decision-making and technical levels. We believe that our experience can benefit other countries in the region in implementing EMRs and using EMRAM to assess their health information systems.

Codesign of health technology interventions to support best-practice perioperative care and surgical waitlist management

OBJECTIVES

This project aimed to determine where health technology can support best-practice perioperative care for patients waiting for surgery.

METHODS

An exploratory codesign process used personas and journey mapping in three interprofessional workshops to identify key challenges in perioperative care across four health districts in Sydney, Australia. Through participatory methodology, the research inquiry directly involved perioperative clinicians. In three facilitated workshops, clinician and patient participants codesigned potential digital interventions to support perioperative pathways. Workshop output was coded and thematically analysed, using design principles.

RESULTS

Codesign workshops, involving 51 participants, were conducted October to November 2022. Participants designed seven patient personas, with consumer representatives confirming acceptability and diversity. Interprofessional team members and consumers mapped key clinical moments, feelings and barriers for each persona during a hypothetical perioperative journey. Six key themes were identified: 'preventative care', 'personalised care', 'integrated communication', 'shared decision-making', 'care transitions' and 'partnership'. Twenty potential solutions were proposed, with top priorities a digital dashboard and virtual care coordination.

DISCUSSION

Our findings emphasise the importance of interprofessional collaboration, patient and family engagement and supporting health technology infrastructure. Through user-based codesign, participants identified potential opportunities where health technology could improve system efficiencies and enhance care quality for patients waiting for surgical procedures. The codesign approach embedded users in the development of locally-driven, contextually oriented policies to address current perioperative service challenges, such as prolonged waiting times and care fragmentation.

CONCLUSION

Health technology innovation provides opportunities to improve perioperative care and integrate clinical information. Future research will prototype priority solutions for further implementation and evaluation.

Challenges in surveillance of all cancer cases: The Chilean National Cancer Registry

Cancer causes millions of deaths worldwide, making its registration essential. There are clinical, hospital, and population-based registries in place. The latter is the gold standard for information on cancer incidence and survival in a defined region. Chile has five population-based registries located in specific areas of the country. The Chilean National Cancer Registry emerged with the challenge of creating a tool encompassing all three types of registries to identify the number of cancer cases by type. Its design involved a series of actions to achieve consensus among various actors regarding information, validation, and events to be registered. Four stages were identified in the care and registration process: suspected diagnosis, morphological confirmation (biopsy), clinical resolution (oncology committee, including treatment recommendations), treatment, and oncological follow-up. The platform's development (from 2018 to 2021) involved gathering information and agreements on the requirements for co-designing the registry, including a successful pilot program with over 20 public and private healthcare facilities that recorded nearly 7500 cancer cases. The deployment and use of the National Cancer Registry at a national level depends on the healthcare authority. It is an information system that continuously and systematically collects, stores, processes, and analyzes data on all cancer cases and types occurring in the country. This work presents the design and development of the tool, the challenges addressed, as well as its strengths and weaknesses.

Review of Qualitative Research Methods in Health Information System Studies

OBJECTIVES

The aim of this study was to review hospital-based health information system (HIS) studies that used qualitative research methods and evaluate their methodological contexts and implications. In addition, we propose practical guidelines for HIS researchers who plan to use qualitative research methods.

METHODS

We collected papers published from 2012 to 2022 by searching the PubMed and CINAHL databases. As search keywords, we used specific system terms related to HISs, such as "electronic medical records" and "clinical decision support systems," linked with their operational terms, such as "implementation" and "adaptation," and qualitative methodological terms such as "observation" and "in-depth interview." We finally selected 74 studies that met this review's inclusion criteria and conducted an analytical review of the selected studies.

RESULTS

We analyzed the selected articles according to the following four points: the general characteristics of the selected articles; research design; participant sampling, identification, and recruitment; and data collection, processing, and analysis. This review found methodologically problematic issues regarding researchers' reflections, participant sampling methods and research accessibility, and data management.

CONCLUSIONS

Reports on the qualitative research process should include descriptions of researchers' reflections and ethical considerations, which are meaningful for strengthening the rigor and credibility of qualitative research. Based on these discussions, we suggest guidance for conducting ethical, feasible, and reliable qualitative research on HISs in hospital settings.

Call to digital health leaders: test and leverage this guideline to support health information technology implementation in practice

BACKGROUND

Health information technology (HIT) is increasingly used to enable health service/system transformation. Most HIT implementations fail to some degree; very few demonstrate sustainable success. No guidelines exist for health service leaders to leverage factors associated with success. The purpose of this paper is to present an evidence-based guideline for leaders to test and leverage in practice.

METHODS

This guideline was developed from a literature review and refined by a set of eight interviews with people in senior HIT roles, which were thematically analysed. It was refined in the consultancy work of the first author and confirmed after minor refinements.

RESULTS

Five key actions were identified: relationships, vision, HIT system attributes, constant evaluation and learning culture.

CONCLUSIONS

This guideline presents a significant opportunity for health system leaders to systematically check relevant success factors during the implementation process of single projects and regional/national programmes.

Implementer report: ICD-10 code F44.5 review for functional seizure disorder

OBJECTIVE

The study aimed to measure the validity of International Classification of Diseases, 10th Edition (ICD-10) code F44.5 for functional seizure disorder (FSD) in the Veterans Affairs Connecticut Healthcare System electronic health record (VA EHR).

METHODS

The study used an informatics search tool, a natural language processing algorithm and a chart review to validate FSD coding.

RESULTS

The positive predictive value (PPV) for code F44.5 was calculated to be 44%.

DISCUSSION

ICD-10 introduced a specific code for FSD to improve coding validity. However, results revealed a meager (44%) PPV for code F44.5. Evaluation of the low diagnostic precision of FSD identified inconsistencies in the ICD-10 and VA EHR systems.

CONCLUSION

Information system improvements may increase the precision of diagnostic coding by clinicians. Specifically, the EHR problem list should include commonly used diagnostic codes and an appropriately curated ICD-10 term list for 'seizure disorder,' and a single ICD code for FSD should be classified under neurology and psychiatry.

Current Status and Key Issues of Data Management in Tertiary Hospitals: A Case Study of Seoul National University Hospital

OBJECTIVES

In the era of the Fourth Industrial Revolution, where an ecosystem is being developed to enhance the quality of healthcare services by applying information and communication technologies, systematic and sustainable data management is essential for medical institutions. In this study, we assessed the data management status and emerging concerns of three medical institutions, while also examining future directions for seamless data management.

METHODS

To evaluate the data management status, we examined data types, capacities, infrastructure, backup methods, and related organizations. We also discussed challenges, such as resource and infrastructure issues, problems related to government regulations, and considerations for future data management.

RESULTS

Hospitals are grappling with the increasing data storage space and a shortage of management personnel due to costs and project termination, which necessitates countermeasures and support. Data management regulations on the destruction or maintenance of medical records are needed, and institutional consideration for secondary utilization such as long-term treatment or research is required. Government-level guidelines for facilitating hospital data sharing and mobile patient services should be developed. Additionally, hospital executives at the organizational level need to make efforts to facilitate the clinical validation of artificial intelligence software.

CONCLUSIONS

This analysis of the current status and emerging issues of data management reveals potential solutions and sets the stage for future organizational and policy directions. If medical big data is systematically managed, accumulated over time, and strategically monetized, it has the potential to create new value.

ELGA Terminology Server for Clinical Decision Support: A Case-Study Using an Existing Knowledge Base, CDS Hooks and FHIR

BACKGROUND

There are many medical knowledge bases with potential for supporting medical professionals in their decision-making during routine care, yet usage of these sources remains low. Standardized linking of Clinical Decision Support (CDS) applications and existing medical knowledge bases is not a common practice.

OBJECTIVES

Using existing eHealth standards to increase the utilization of knowledge bases and implement a prototype.

METHODS

Linking an existing online knowledge base via a FHIR CodeSystem supplement to the Austrian national EHR (ELGA) terminology server and accessing these data using CDS Hooks and FHIR.

RESULTS

We tested the approach by incorporating photosensitivity data of medications into a local copy of the Austrian terminology server. These data are directly used by a CDS Hooks compliant CDS service.

CONCLUSION

The Austrian Terminology Server could be an important interface to access existing knowledge bases from within EHR systems. FHIR and CDS Hooks could lead the way for a simple and open integration of CDS services into EHR systems.

Primary health care coverage in Brazil: a dataset from 1998 to 2020

OBJECTIVES

Primary health care builds the backbone of an effective healthcare system and can improve population health, reduce cost growth, and lessen inequality. We offer a machine-readable and open-access dataset on primary health care coverage in Brazil from 1998 to 2020. This dataset is interoperable with epidemiological data from two major studies and reusable by the research community worldwide for other purposes, such as monitoring progress toward universal health coverage and studying the association between primary health care and health outcomes.

DATA DESCRIPTION

The dataset gathers official and public information from the "e-Gestor AB" platform of the Ministry of Health of Brazil and restricted data obtained by the Brazilian Access to Information Law. It includes 1,509,870 observations and 35 attributes aggregated by months/years and policy-relevant geographic units (country, macroregions, states, municipalities, and capitals) on primary health care team count and their absolute and relative population coverage estimates, information on the More Doctors Program implementation and physician counts, and spatial, demographic, and socioeconomic characteristics. We automated all data processing and curation in the free and open software R. The codes can be audited, replicated, and reused to produce alternative analyses.

Exploring the feasibility of establishing a core set of sexual, reproductive, maternal, newborn, child, and adolescent health indicators in humanitarian settings: results from a multi-methods assessment in Jordan

BACKGROUND

Reliable and rigorously collected sexual, reproductive, maternal, newborn, child, and adolescent health (SRMNCAH) data in humanitarian settings is often sparse and variable in quality across different humanitarian settings. To address this gap in data quality, the World Health Organization (WHO) developed a core set of indicators for monitoring and evaluating SRMNCAH services and outcomes in humanitarian settings, and assessed their feasibility in the field in Jordan, in addition to three other countries; with the goal of aggregating information from global consultations and field-level assessments to reach consensus on a set of core SRMNCAH indicators for services and outcome evaluation in humanitarian settings among WHO global partners.

METHODS

The feasibility assessment in Jordan focused on the following constructs: relevance/usefulness, feasibility of measurement, systems and resources, and ethical issues. The multi-methods assessment included five components; a desk review, key informant interviews, focus group discussions, facility assessments, and observational sessions.

RESULTS

Findings suggest that there is widespread support among regional, national, as well as global stakeholders for developing a core list of SRMNCAH indicators for monitoring and evaluation of services and outcomes in humanitarian settings in Jordan. There are numerous resources and data collection systems that could be leveraged, built upon, and improved to ensure the feasibility of collecting this proposed set of indicators. However, the data collection load requested from donors, the national government, international and UN agencies, coordination/cluster systems must be better harmonized, standardized, and less burdensome.

CONCLUSIONS

Despite stakeholder support in developing a core set of indicators, this would only be useful if it has the buy-in from the international community. Greater harmonization and coordination, alongside increased resource allocation, would improve data collection efforts and allow stakeholders to meet indicators' reporting requirements.

Routine health information use among healthcare providers in Ethiopia: a systematic review and meta-analysis

INTRODUCTION

Healthcare policy formulation, programme planning, monitoring and evaluation, and healthcare service delivery as a whole are dependent on routinely generated health information in a healthcare setting. Several individual research articles on the utilisation of routine health information exist in Ethiopia; however, each of them revealed inconsistent findings.

OBJECTIVE

The main aim of this review was to combine the magnitude of routine health information use and its determinants among healthcare providers in Ethiopia.

METHODS

Databases and repositories such as PubMed, Global Health, Scopus, Embase, African journal online, Advanced Google Search and Google Scholar were searched from 20 to 26 August 2022.

RESULT

A total of 890 articles were searched but only 23 articles were included. A total of 8662 (96.3%) participants were included in the studies. The pooled prevalence of routine health information use was found to be 53.7% with 95% CI (47.45% to 59.95%). Training (adjusted OR (AOR)=1.56, 95% CI (1.12 to 2.18)), competency related to data management (AOR=1.94, 95% CI (1.35 to 2.8)), availability of standard guideline (AOR=1.66, 95% CI (1.38 to 1.99)), supportive supervision (AOR=2.07, 95% CI (1.55 to 2.76)) and feedback (AOR=2.20, 95% CI (1.30 to 3.71)) were significantly associated with routine health information use among healthcare providers at p value≤0.05 with 95% CI.

CONCLUSION

The use of routinely generated health information for evidence-based decision-making remains one of the most difficult problems in the health information system. The study's reviewers suggested that the appropriate health authorities in Ethiopia invest in enhancing the skills in using routinely generated health information.

PROSPERO REGISTRATION NUMBER

CRD42022352647.

Organizational and health professional readiness for the implementation of electronic medical record system: an implication for the current EMR implementation in northwest Ethiopia

OBJECTIVE

The WHO developed a manual outlining the preliminary organizational and health professionals' readiness to implement electronic medical records (EMR). On the other hand, the readiness assessment in Ethiopia only includes the evaluation of health professionals, leaving out organisational readiness components. As a result, this research aimed to determine health professionals' and organizational readiness to implement EMR at a specialized teaching hospital.

METHODS

An institutional-based cross-sectional study design was conducted among 423 health professionals and 54 managers. Self-administered and pretested questionnaires were used to collect data. Binary logistic regression analysis was used to identify factors associated with health professionals' readiness for EMR implementation. An OR with a 95% CI and p<0.05 was used to determine the strength of the association and the statistical significance, respectively.

RESULTS

In this study, 53.7% management capacity, 33.3% finance and budget capacity, 42.6% operational capacity, 37.0% technology capability and 53.7% organisational alignment among the five dimensions evaluated to assess an organisation's readiness to implement an EMR system. Of 411 health professionals in this study, 173 (42.1%) with (95 CI 37.3% to 46.8%) were ready to implement an EMR system at the hospital. Sex (AOR 2.69, 95% CI 1.73 to 4.18), basic computer training (AOR 1.59, 95% CI 1.02 to 2.46), knowledge of EMR (AOR 1.88, 95% CI 1.19 to 2.97) and attitudes towards EMR (AOR 1.65, 95% CI 1.05 to 2.59) were significantly associated with health professionals' readiness towards EMR system implementation.

CONCLUSIONS

Findings showed that most dimensions of organizational readiness for EMR implementation were below 50%. This study also revealed a lower level of EMR implementation readiness among health professionals compared with previous research studies' results. To improve organisational readiness to implement an electronic medical record system, a focus on management capability, financial and budget capability, operational capability, technical capability and organisational alignment was crucial. Likewise, having basic computer training, giving special attention to female health professionals and improving health professionals' knowledge of and attitudes towards EMR could help improve the readiness level of health professionals for implementing an EMR system.

Keep it simple: designing a user-centred digital information system to support chronic disease management in low/middle-income countries

OBJECTIVE

Implement a user-centred digital health information system to facilitate rapidly and substantially increasing the number of patients treated for hypertension in low/middle-income countries.

METHODS

User-centred design of Simple, an offline-first app for mobile devices to record patient clinical visits and a web-based dashboard to monitor programme performance.

RESULTS

The Simple mobile application scaled rapidly over the past 4 years to reach more than 11 400 primary care facilities in four countries with over 3 million patients enrolled. Simple achieved median duration for new patient registration of 76 s (IQR 2 s) and follow-up visit entry of 13 s (IQR 1 s).

CONCLUSIONS

A fast, easy-to-use digital information system for hypertension programmes that accommodates healthcare worker time constraints by minimising data entry and focusing on key performance indicators can successfully reach scale in low-resource settings.

Small area population denominators for improved disease surveillance and response

The Covid-19 pandemic has highlighted the value of strong surveillance systems in supporting our abilities to respond rapidly and effectively in mitigating the impacts of infectious diseases. A cornerstone of such systems is basic subnational scale data on populations and their demographics, which enable the scale of outbreaks to be assessed, risk to specific groups to be determined and appropriate interventions to be designed. Ongoing weaknesses and gaps in such data have however been highlighted by the pandemic. These can include outdated or inaccurate census data and a lack of administrative and registry systems to update numbers, particularly in low and middle income settings. Efforts to design and implement globally consistent geospatial modelling methods for the production of small area demographic data that can be flexibly integrated into health-focussed surveillance and information systems have been made, but these often remain based on outdated population data or uncertain projections. In recent years, efforts have been made to capitalise on advances in computing power, satellite imagery and new forms of digital data to construct methods for estimating small area population distributions across national and regional scales in the absence of full enumeration. These are starting to be used to complement more traditional data collection approaches, especially in the delivery of health interventions, but barriers remain to their widespread adoption and use in disease surveillance and response. Here an overview of these approaches is presented, together with discussion of future directions and needs.

Production and Provision of Context-Based Patient-Specific Educational Resources

BACKGROUND

Patient education is generally accompanied by instructive materials. The Korean government has recommended the provision of patient-specific educational materials (PEMs) via an electronic medical record (EMR) certification system. However, there are currently no clear standards or guidelines for including PEMs in current domestic educational materials. We investigated the benefits of integrating PEMs with the EMR certification system and the methods by which this integration can be achieved.

METHODS

We developed and administered three structured Delphi surveys to 26 healthcare providers in clinical settings based on data collected from separate semi-structured advisory interviews with five experts. The surveys included the following topics: 1) expected effects of patient-specific education and health-related notifications/alarms, 2) desirable methods for providing PEMs, and 3) appropriate fee-setting and government support. We distributed the Delphi surveys via e-mail and calculated the average and standard deviation of the survey responses.

RESULTS

PEMs are expected to have significant educational effects, such as the provision of surgery/intervention-related information, and will improve the understanding of various treatment processes/procedures. The preferred method for providing PEMs was via automatic request after receiving confirmation from healthcare providers. The provision of these materials was based on set fees and government support. The average fee per session was set at approximately USD 23 (as of October 2021, USD 1 = KRW 1,196).

CONCLUSION

In this study, we investigated the prerequisites, contents, methods, and fees related to the provision of effective and efficient PEMs. The study findings can facilitate the production and provision of PEMs.

Health Information System in Developing Countries: A Review on the Challenges and Causes of Success and Failure

Background: A review on the health information systems (HISs) of each country should not be limited only to data collected and reported normally by the service providers. In this regard, the first step for the development in any national project is exploring the experiences of other countries worldwide, especially those with economic, political, cultural, and regional partnerships, and then using their resources and documents to have a broader attitude and a better profitability in planning the development strategy. This study was conducted to review the studies conducted on the causes of HIS success and failure, and the challenges faced by developing countries in using these systems. Methods: The present study was a narrative review to meet the aim of the study, and those studies published in English language in PubMed, Web of science, and Science Direct databases and Scopus between 2000 and 2020 were investigated. Primary keywords used to extract content in these databases were as follows: "health information system", "challenges", "success", "failure", "developing country", and "low and middle income country". Results: After searching the above-mentioned databases, 455 studies were retrieved. Finally, 24 articles were used. The causes of success and failure of HISs were finally divided into 4 categories: human, organizational, financial and technical factors. A total of 30 subfactors were extracted for different factors. Moreover, the findings indicated that many of the challenges that developing countries face in using HISs are influenced by the social, cultural, economic, geographical, and political conditions of these countries. The results represented that organizational and human elements play a critical role in the advancement or falling of the health HIS in growing countries. Conclusion: There is a demand to come up with flexible standards for designing and deploying HISs to address these complexities. Several solutions can be found to address the obstacles and problems facing HISs in developing countries, including formulating strategic plans and policies necessary for the development of national HISs.

A Formal Model for the FAIR4Health Information Architecture

In the EU project FAIR4Health, a ETL pipeline for the FAIRification of structured health data as well as an agent-based, distributed query platform for the analysis of research hypotheses and the training of machine learning models were developed. The system has been successfully tested in two clinical use cases with patient data from five university hospitals. Currently, the solution is also being considered for use in other hospitals. However, configuring the system and deploying it in the local IT architecture is non-trivial and meets with understandable concerns about security. This paper presents a model for describing the information architecture based on a formal approach, the 3LGM metamodel. The model was evaluated by the developers. As a result, the clear separation of tasks and the software components that implement them as well as the rich description of interactions via interfaces were positively emphasized.

Improving Findability of Digital Assets in Research Data Repositories Using the W3C DCAT Vocabulary

Research data management requires stable, trustworthy repositories to safeguard scientific research results. In this context, rich markup with metadata is crucial for the discoverability and interpretability of the relevant resources. SEEK is a web-based software to manage all important artifacts of a research project, including project structures, involved actors, documents and datasets. SEEK is organized along the ISA model (Investigation - Study - Assay). It offers several machine-readable serializations, including JSON and RDF. In this paper, we extend the power of RDF serialization by leveraging the W3C Data Catalog Vocabulary (DCAT). DCAT was specifically designed to improve interoperability between digital assets on the Web and enables cross-domain markup. By using community-consented gold standard vocabularies and a formal knowledge description language, findability and interoperability according to the FAIR principles are significantly improved.

Health Information Systems Adaptation and Flexibility in Extreme Situations: The COVID Effect

In 2020, a pandemic forced the entire world to adapt to a new scenario. The objective of this study was to know how Health Information Systems were adapted driven by the pandemic of COVID. 12 CIOS of healthcare organizations were interviewed and the interviews were classified according to the dimensions of a sociotechnical model: Infrastructure, Clinical Content, Human Computer Interface, People, Workflow and Communication, Organizational Characteristics and Internal Policies, Regulations, and Measurement and Monitoring. Adaptation to the Pandemic involved social, organizational and cultural rather than merely technical aspects in private organizations with mature and stable Health Information Systems.

Establishing a Data Quality Baseline in the AKTIN Emergency Department Data Registry - A Secondary Use Perspective

Secondary use of clinical data is an increasing application that is affected by the data quality (DQ) of its source systems. Techniques such as audits and risk-based monitoring for controlling DQ often rely on source data verification (SDV). SDV requires access to data generating systems. We present an approach to a targeted SDV based on manual input and synthetic data that is applicable in low resource settings with restricted system access. We deployed the protocol in the DQ management of the AKTIN Emergency Department Data Registry. Our targeted approach has shown to be feasible to form a DQ baseline that can be used for different DQ monitoring processes such as the identification of different error sources.

Feasibility of establishing a core set of sexual, reproductive, maternal, newborn, child, and adolescent health indicators in humanitarian settings: results from a multi-methods assessment in Bangladesh

BACKGROUND

Reliable and rigorously collected sexual, reproductive, maternal, newborn, child, and adolescent health (SRMNCAH) data in humanitarian settings is often sparse and varies in quality across different humanitarian settings. To address this gap in quality data, the World Health Organization (WHO) developed a core set of indicators for monitoring and evaluating SRMNCAH services and outcomes, and assessed their feasibility in Bangladesh, Afghanistan, Jordan, and the Democratic Republic of Congo.

METHODS

The feasibility assessments aggregated information from global consultations and field-level assessments to reach a consensus on a set of core SRMNCAH indicators among WHO partners. The feasibility assessment in Bangladesh focused on the following constructs: relevance/usefulness of the core set of indicators, the feasibility of measurement, availability of systems and resources, and ethical issues during data collection and management. The field-level multi-methods assessment included five components; a desk review, key informant interviews, focus group discussions, and facility assessments including observations of facility-level data management.

RESULTS

The findings suggest that there is widespread support among stakeholders for developing a standardized core set of SRMNCAH indicators to be collected among all humanitarian actors in Bangladesh. There are numerous resources and data collection systems that could be leveraged, built upon, and improved to ensure the feasibility of collecting this proposed set of indicators. However, the data collection load requested from donors, the national government, international and UN agencies, coordination/cluster systems must be better harmonized, standardized, and less burdensome.

CONCLUSION

This core set of indicators would only be useful if it has the buy-in from the international community that results in harmonizing and coordinating data collection efforts and relevant indicators' reporting requirements.

The InfAct proposal for a sustainable European health information infrastructure on population health: the Distributed Infrastructure on Population Health (DIPoH)

Background

In Europe, data on population health is fragmented, difficult to access, project-based and prone to health information inequalities in terms of availability, accessibility and especially in quality between and within countries. This situation is further exacerbated and exposed by the recent COVID-19 pandemic. The Joint Action on Health Information (InfAct) that builds on previous works of the BRIDGE Health project, carried out collaborative action to set up a sustainable infrastructure for health information in the European Union (EU). The aim of this paper is to present InfAct’s proposal for a sustainable research infrastructure, the Distributed Infrastructure on Population Health (DIPoH), which includes the setup of a Health Information Portal on population health to be maintained beyond InfAct’s time span.

Methods

The strategy for the proposal was based on three components: scientific initiatives and proposals to improve Health Information Systems (HIS), exploration of technical acceptability and feasibility, and finally obtaining high-level political support.. The technical exploration (Technical Dialogues—TD) was assumed by technical experts proposed by the countries, and political guidance was provided by the Assembly of Members (AoM), which gathered representatives from Ministries of Health and Science of EU/EEA countries. The results from the AoM and the TD were integrated in the sustainability plan compiling all the major outputs of InfAct.

Results

The InfAct sustainability plan was organized in three main sections: a proposal of a new research infrastructure on population health (the DIPoH), new health information tools and innovative proposals for HIS, and a comprehensive capacity building programme. These activities were carried out in InfAct and are being further developed in the Population Health Information Research Infrastructure (PHIRI). PHIRI is a practical rollout of DIPoH facilitating and generating the best available evidence for research on health and wellbeing of populations as impacted by COVID-19.

Conclusions

The sustainability plan received wide support from Member States and was recognized to have an added value at EU level. Nevertheless, there were several aspects which still need to be considered for the near future such as: (i) a commitment of stable financial and political support by Member States (MSs), (ii) the availability of resources at regional, national and European level to deal with innovations, and (iii) a more direct involvement from EU and international institutions such as the European Centre for Disease Prevention and Control (ECDC), the World Health Organization (WHO) and the Organisation for Economic Cooperation and Development OECD for providing support and sustainable contributions.

Database on the coverage of the "Bolsa-Família" conditioning cash-transfer program: Brazil, 2005 to 2021

Objectives

The “Bolsa-Família” Program (PBF) is a Brazilian conditional cash-transfer program in which families should comply with health, education, and social assistance conditionalities. The program aims to fight poverty and hunger, promoting nutrition and health services for low-income populations. This paper presents a database on the coverage of monitoring and compliance with the PBF health conditionalities in Brazil from January 2005 to July 2021.

Data description

Database on the PBF conditioning cash-transfer program coverage in Brazil from 2005 to 2021. It comprises information on the number of families benefited, health conditionalities, and the follow-up on vaccination and nutrition of children under seven years old. The cities and semesters are the minimal aggregation units.

Research Development Using REDCap Software

OBJECTIVES

High-quality clinical research is dependent on adequate design, methodology, and data collection. The utilization of electronic data capture (EDC) systems is recommended to optimize research data through proper management. This paper's objective is to present the procedures of REDCap (Research Electronic Data Capture), which supports research development, and to promote the utilization of this software among the scientific community.

METHODS

REDCap's web application version 10.4.1 released on 2021 (Vanderbilt University) is an EDC system suitable for clinical research development. This paper describes how to join the REDCap consortium and presents how to develop survey instruments and use them to collect and analyze data.

RESULTS

Since REDCap is a web application that stimulates knowledge-sharing among the scientific community, its development is not finished and it is constantly receiving updates to improve the system. REDCap's tools provide access control, audit trails, and data security to the research team.

CONCLUSIONS

REDCap is a web application that can facilitate clinical research development, mainly in health fields, and reduce the costs of conducting research. Its tools allow researchers to make the best use of EDC components, such as data storage.

Developing A General Framework for National Health Information Network for Developing Countries

Background

The National Health Information Network (NHIN) is one of the key issues in health information systems in any country. However, the development of this network should be based on an appropriate framework. Unfortunately, the conducted projects of health information systems in the Ministry of Health of Iran do not fully comply with the concept of NHIN. The present study was aimed to develop a general framework for NHIN in Iran.

Materials and Methods

In this study, in the first stage, the required information about the concept of the NHIN framework and related NHIN documents in the USA and the UK were collected based on a literature review. Then, according to the results of the first stage and with regards to the structure of the Iranian health system, a general framework for Iranian NHIN was proposed. The Delphi technique was conducted to verify the framework.

Results

The proposed framework for Iranian NHIN includes three dimensions; components, principles, and architecture. Over 80% of experts have evaluated all three aspects of the framework at an acceptable scale. In total, the proposed framework has been evaluated by 83.8% of the experts at an acceptable scale.

Conclusion

The proposed framework was expected to serve as the starting point for moving towards the design and creation of Iranian NHIN. At any rate, the framework could be criticized, and it could only be used for the countries whose health system is similar to the structure of the health system in Iran.

Comparison of Knowledge Databases to Be Used in Automated Monitoring of Orthopedic Medical Devices

Surveillance and traceability of medical devices (MD) is a challenge in health care systems. In the perspective of reusing EHR data to automate the monitoring of medical devices, we carried out a comparison of the main MD knowledge bases (MD-KDB) currently available in France. Four MD-KDBs (ANSM, Gudid, Exhausmed and CIOdm) were compared quantitatively and through an example of a shoulder prosthesis. The number of MDs registered differs from one MD-KDB to another. Domain terminologies used in MD-KDBs differ in terms of granularity and in the ease of querying. Waiting EUDAMED, the European MD-KDB, it seems necessary so far to use and combine information coming from several MD-KDBs to address MD monitoring.

The Process of Modeling Information System Architectures with IHE

IHE has defined more than 200 integration profiles in order to improve the interoperability of application systems in healthcare. These profiles describe how standards should be used in particular use cases. These profiles are very helpful but their correct use is challenging, if the user is not familiar to the specifications. Therefore, inexperienced modelers of information systems quickly lose track of existing IHE profiles. In addition, the users of these profiles are often not aware of rules that are defined within these profiles and of dependencies that exist between the profiles. There are also modelers that do not notice the differences between the implemented actors, because they do not know the optional capabilities of some actors. The aim of this paper is therefore to describe a concept how modelers of information systems can be supported in the selection and use of IHE profiles and how this concept was prototypically implemented in the "Three-layer Graph-based meta model" modeling tool (3LGM2 Tool). The described modeling process consists of the following steps that can be looped: defining the use case, choosing suitable integration profiles, choosing actors and their options and assigning them to application systems, checking for required actor groupings and modeling transactions. Most of these steps were implemented in the 3LGM2 Tool. Further implementation effort and evaluation of our approach by inexperienced users is needed. But after that our tool should be a valuable tool for modelers planning healthcare information system architectures, in particular those based on IHE.

Health Data Privacy in the COVID-19 Pandemic Context: Discourses on HIPAA

BACKGROUND

Considering the impacts of the COVID-19 pandemic on health service delivery, the US Office for Civil Rights (OCR) updated the policies on health data processing, and Health Insurance Portability and Accountability Act (HIPAA).

OBJECTIVES

In this study, we investigated discourses on HIPAA in relation to COVID-19.

METHODS

Through a search of media sources in the Factiva database, relevant texts were identified. We applied a text mining approach to identify concepts and themes in these texts.

RESULTS

Our analysis revealed six central themes, namely, Health, HIPAA, Privacy, Security, Patients, and Need, as well as their associated concepts. Among these, Health was the most frequently discussed theme. It comprised concepts such as public, care, emergency, providers, telehealth, entity, use, discretion, OCR, Health and Human Services (HHS), enforcement, business, and services.

CONCLUSION

Our discourse analysis of media outlets highlights the role of health data privacy law in the response to global public health emergencies and demonstrates how discourse analysis and computational methods can inform health data protection policymaking in the digital health era.

Barriers in Health Information Systems and Technologies to Support Maternal and Neonatal Referrals at Primary Health Centers

Objectives

This study explored health workers’ perceptions and experiences regarding the maternal and neonatal referral system, focusing on barriers of health information systems and technologies (IS/IT) at primary health centers (PHCs) in South Tangerang, Indonesia.

Methods

This qualitative study was conducted using semi-structured interviews, which were conducted at the South Tangerang District Health Office and three PHCs. Interviews were conducted with nine participants responsible for maternal and neonatal referrals in their organizations. The data were analyzed using qualitative content analysis.

Results

In South Tangerang, the Primary Health Care Information System (SIMPUS) is used to register patients and record data on medical treatment. To facilitate referrals, the PHCs currently use the Integrated Referral Information System (SISRUTE), P-Care, and the Integrated Emergency Management System (SPGDT). The following four IS/IT barriers to support maternal and neonatal referrals were found: technology, human resources, organizational support, and the referral process and implementation.

Conclusions

The barriers in technology, human resources, and organizational support cause problems in the maternal and neonatal referral process and in the implementation of referrals. Barriers to referrals can influence patients’ ability to receive appropriate care in a timely fashion and lead to inefficiency in maternal and neonatal referrals. This study contributes knowledge about IS/IT implementation in maternal and neonatal referral systems and provides recommendations to health regulators and application developers for the implementation of IS/IT in Indonesia.

Future and Development Direction of Digital Healthcare

OBJECTIVES

Digital healthcare is expected to play a pivotal role in patient-centered healthcare. It empowers patients by informing, communicating, and motivating them. However, a pragmatic evaluation of the present status of digital healthcare has not been presented; therefore, we aimed to examine the status of digital healthcare in Korea.

METHODS

This article discusses digital healthcare, examples of assessment in Korea and other countries, the implications of past examples, and future directions for development.

RESULTS

Over the years, various clinical studies have used clinical evidence to assess the feasibility of digital healthcare. If feasible, it is actually clinically effective. If it is effective, can it be commercialized at an acceptable cost? These questions have been investigated in various evidence-based studies. In addition, great efforts are being made to secure ample evidence to assess various aspects of digital healthcare, such as safety, quality, end-user experience, and equity.

CONCLUSIONS

Digital healthcare requires a deep understanding of both the technical and medical aspects. To strengthen the competence of the medical aspect, medical staff, patients, and the government must work together with continuous interest in this goal.

Maternal and neonatal data collection systems in low- and middle-income countries for maternal vaccines active safety surveillance systems: A scoping review

BACKGROUND

Most post-licensure vaccine pharmacovigilance in low- and middle-income countries (LMICs) are passive reporting systems. These have limited utility for maternal immunization pharmacovigilance in LMIC settings and need to be supplemented with active surveillance. Our study's main objective was to identify existing perinatal data collection systems in LMICs that collect individual information on maternal and neonatal health outcomes and could be developed to inform active safety surveillance of novel vaccines for use during pregnancy.

METHODS

A scoping review was performed following the Arksey and O'Malley six-stage approach. We included studies describing electronic or mixed paper-electronic data collection systems in LMICs, including research networks, electronic medical records, and custom software platforms for health information systems. Medline PubMed, EMBASE, Global Health, Cochrane Library, LILACS, Bibliography of Asian Studies (BAS), and CINAHL were searched through August 2019. We also searched grey literature including through Google and websites of existing relevant perinatal data collection systems, as well as contacted authors of key studies and experts in the field to validate the information and identify additional sources of relevant unpublished information.

RESULTS

A total of 11,817 records were identified. The full texts of 264 records describing 96 data collection systems were assessed for eligibility. Eight perinatal data collection systems met our inclusion criteria: Global Network's Maternal Newborn Health Registry, International Network for the Demographic Evaluation of Populations and their Health; Perinatal Informatic System; Pregnancy Exposure Registry & Birth Defects Surveillance; SmartCare; Open Medical Record System; Open Smart Register Platform and District Health Information Software 2. These selected systems were qualitatively characterized according to seven different domains: governance; system design; system management; data management; data sources, outcomes and data quality.

CONCLUSION

This review provides a list of active maternal and neonatal data collection systems in LMICs and their characteristics as well as their outreach, strengths, and limitations. Findings could potentially help further understand where to obtain population-based high-quality information on outcomes to inform the conduct of maternal immunization active vaccine safety surveillance activities and research in LMICs.

Assessing the potential use of blockchain technology to improve the sharing of public health data in a western Canadian province

This exploratory, qualitative study set out to identify the encountered and perceived barriers to public health (PH) data sharing in a Canadian province with a view to assessing blockchain technology as a potential solution. A topic guide was developed, based on previous research in the area. This was then utilised for ten in-depth, semi-structured interviews with PH professionals between 27 May and 18 June 2019. Each stage of research was congruent with the philosophical underpinning of Gadamerian hermeneutic phenomenology. The major themes that emerged from the data collected were related to the information systems in use, data quality and ownership, as well as client identity management. The recurring core theme throughout all interviews was related to ineffective leadership and management, contributing to each major theme. Overwhelmingly the results show that the majority of barriers faced in this province are human-related. It is concluded that while blockchain technology shows promise for enhancing data sharing in healthcare, it is still many years away from being implemented in this Canadian province. As the results of this study indicate, there are human related barriers that could be addressed in the meantime, which are outside the scope of a technical solution. Future work should explore the perspectives of other stakeholders, such as the provincial government to fully understand the potential for using blockchain to share PH data in this province.

[A New Paradigm in Health Research: FAIR Data (Findable, Accessible, Interoperable, Reusable)]

The digital era, that we are living nowadays, is transforming health, health care models and services, and the role of society in this new reality. We currently have a large amount of stored health data, including clinical, biometric, and scientific research data. Nonetheless, its potential is not being fully exploited. It is essential to foster the sharing and reuse of this data not only in research but also towards the development of health technologies in order to improve health care efficiency, as well as products, services or digital health apps, to promote preventive and individualized medicine and to empower citizens in health literacy and self-management. In this sense, the FAIR concept has emerged, which implies that health data is findable, accessible, shared and reusable, facilitating interoperability between systems, ensuring the protection of personal and sensitive data. In this paper we review the FAIR concept, 'FAIRification' process, FAIR data versus open access data, ethical issues and the general data protection regulation, and digital health and citizen science.

Effects of User Participation in the Development of Health Information Systems on Their Evaluation Within Occupational Health Services

Information management and the usability of health information systems (HIS) are important for the development of HIS in occupational health services. User participation in the HIS development process has been shown to contribute to the success of an HIS. The purpose of this study was to analyze how user participation in HIS development affected evaluation of the success of HIS. The success was assessed on the basis of the DeLone and McLean Information Systems (IS) Success Model. The study was conducted within occupational health services and the data (n=210) was analyzed with quantitative methods. The results showed that users participating in the HIS development process assessed the success of the HIS as better than those that had not taken part in the development. This difference could be seen in all seven dimensions of the DeLone and McLean IS success model but was statistically significant only for System Quality and Intention to Use. The results also showed that the users that had participated in the HIS development process also used the HIS more often and more extensively than those that had not participated in the development. The results indicate that user participation in the development process positively influences their assessment of the HIS and increases their active use of the IS. However, more research is needed to determine the long-term effects of using participatory design in HIS development.

Real-Time Monitoring System to Manage Mental Healthcare Emergency Unit

Objectives

Real-time relevant information helps guide the healthcare decision-making process in daily clinical practice as well as the management and optimization of healthcare processes. However, proprietary business intelligence suite solutions supporting the production of decision-making information requires investment that is out of reach of small and medium-sized healthcare facilities or those with limited resources, particularly in developing countries. This paper describes our experience in designing and implementing a real-time healthcare monitoring system solution to manage healthcare emergency units.

Methods

Through the use of free Business Intelligence tools and Python data science language we designed a real-time monitoring system, which was implemented to explore the Electronic Medical Records system of a university mental health emergency unit and render an electronic dashboard to support health professional daily practice.

Results

Three main dashboards were created to monitor patient waiting time, to access the clinical notes summary for the next waiting patient, and to obtain insights into activity during the last 24 hours.

Conclusions

The designed system could serve as a monitoring support model using free and user-friendly data science tools, which are good alternatives to proprietary business intelligence solutions and drastically reduce cost. Still, the key to success in decision-making systems is based on investment in human resources, business intelligence skills training, the organizational aspect of the decision-making process, and data production quality insurance.

Coping with Information Technology Downtime in Hospitals: A Scoping Study

Downtime of information systems is a universal challenge faced by health care institutions. Regardless of whether downtime is planned or unplanned, the unavailability of essential information requires alternative solutions. In this paper, we conduct a scoping review of how hospitals deal with downtime. A total of 13 papers were included in the final analysis, and we found that coping can be grouped into three strategies; 1) Increasing communication, 2) Analog fallback, and 3) Restricted redundant systems. As the majority of coping mechanisms are related to increasing communication and analog fall back, our findings point to the importance of customizing coping mechanisms for individual healthcare institutions.

Monitoring Mental Healthcare Services Using Business Analytics

Objectives

Monitoring healthcare activities is the first step for health stakeholders and health professionals to improve the quality and performance of healthcare services. However, monitoring remains a challenge for healthcare facilities, especially in developing countries. Fortunately, advances in business analytics address this need. This paper aims to describe the experience of a low-income healthcare facility in a developing country in using business analytics descriptive techniques and to discuss business analytics implementation challenges and opportunities in such an environment.

Methods

Business analytics descriptive techniques were applied on 3 years’ electronic medical records of outpatient consultation of the University Psychiatric Centre (CPU) of Casablanca. Statistical analysis was conducted to compare results over years.

Results

Over the 3 monitored years, the monthly number of computerized physician order entries increased significantly (p < 0.001). Physicians improved their personal recording over years. Schizophrenia as well as depressive and bipolar disorders were noted at the top of outpatient mental disorders. Antipsychotics are the most prescribed drugs, and a significant annual decrease in outpatient care wait time was noted (p < 0.001).

Conclusions

Business analytics allowed CPU to monitor mental healthcare outpatient activity and to adopt its business processes according to outcomes. However, challenges mainly in the organizational dimension of the decision-making process and the definition of strategic key metrics, data structuration, and the quality of data entry had to be considered for the optimal use of business analytics.

Coping with IT Downtime in Hospitals

Downtime of information systems is a universal challenge faced by health care institutions. In this poster, we present the findings of a scoping review of how hospital organizations and their staff deal with downtime, and how coping can be grouped into three strategies; 1) Increasing communication, 2) Analog fallback, and 3) Restricted redundant systems. Our findings point to the importance of customizing coping mechanisms for individual healthcare institutions, and designing systems that empower users to deal with downtime.

Towards Precise Descriptions of Medical Free/Libre and Open Source Software

The web portal Medfloss.org lists over 360 medical free/libre and open source software (MEDFLOSS) projects. These projects are described with the help of a self-developed nomenclature. Due to inconsistencies, the nomenclature shall be replaced by HITO, the Health IT Ontology. HITO is developed iteratively based on different use cases. This paper aims to describe methods and results of the second HITO use case in which HITO is extended to improve the description, retrieval and comparisons of MEDFLOSS projects on Medfloss.org. We use a mixed-methods approach to add concepts and relationships to describe MEDFLOSS precisely. The resulting HITO version stresses functional descriptions based on features and supported enterprise functions, rather than just describing technical characteristics. However, describing a larger number of MEDFLOSS projects requires the commitment of the community.

Qualitative and Quantitative Analysis of Definitions of e-Health and m-Health

Objectives

Skills to employ nursing informatics to promote the health of individuals is of such importance that it is considered a core competence. Although investments are made to increase the use of e-health, there is no full understanding of the usability of e-health for healthcare. This paper presents a current picture of how e-health and m-health are defined and used as well as the effects their usage may have on the intended target group.

Methods

Peer-reviewed open-access papers and grey literature that define e-health and m-health from PubMed, SpringerLink, and Google.com were randomized. A mixed method design with an inductive approach was employed. Open-source software were used for analysis.

Results

The overview includes 30 definitions of e-health and m-health, respectively. The definitions were thematised into 14 narrative themes. The results of the study, and primarily a three-level model, provide an understanding of how different types of e-health and m-health can be put into practice, and the effects or consequences of using them, which may be either positive or negative.

Conclusions

Mobility and flexibility is important for both m-health and e-health. Five keywords that characterize the definitions of e-health and m-health are "health", "mobile", "use", "information", and "technology". E-health or m-health cannot replace human actors because e-health and m-health consist of social and material interactions. Using e-health and m-health is, thus, about developing healthcare without compromising native relics.

Web-Based Spine Segmentation Using Deep Learning in Computed Tomography Images

Objectives

Back pain, especially lower back pain, is experienced in 60% to 80% of adults at some points during their lives. Various studies have found that lower back pain is a very common problem among adolescents, and the highest incidence rates are for adults in their 30s. There has been a remarkable increase in using computer-aided diagnosis to assist doctors in the interpretation of medical images. Spine segmentation in computed tomography (CT) scans using algorithmic methods allows improved diagnosis of back pain.

Methods

In this study, we developed a web-based automatic spine segmentation method using deep learning and obtained the dice coefficient by comparison with the predicted image. Our method is based on convolutional neural networks for segmentation. More specifically, we train a hierarchical data format file using U-Net architecture and then insert the test data label to perform segmentation. Thus, we obtained more specific and detailed results. A total of 344 CT images were used in the experiment. Of these, 330 were used for learning, and the remaining 14 for testing.

Results

Our method achieved an average dice coefficient of 90.4%, a precision of 96.81%, and an F1-score of 91.64%.

Conclusions

The proposed web-based deep learning approach can be very practical and accurate for spine segmentation as a diagnostic method.

Evaluation of the Integrated Health Information System (IHIS) in Public Hospitals in Cyprus Utilizing the DIPSA Framework

INTRODUCTION

The Ministry of Health of the Republic of Cyprus has implemented an Integrated Health Information System (IHIS) in two hospitals. However, no evaluation of IHIS has been conducted to assess its safety, efficiency and effectiveness. The proper utilization of IHIS is essential for the provision of quality healthcare services.

AIM

The purpose of this study was to evaluate the current IHIS in public hospitals in Cyprus utilizing the DIPSA evaluation framework.

METHODS

A total of 309 subjects, including doctors, nurses and other healthcare professionals, participated in the study. The DIPSA evaluation framework assessed the users' perception in five categories namely, satisfaction, collaboration, system quality, safety and procedures, using Likert scale and 3 open questions. Correlation between the categories was assessed using the Pearson correlation coefficient, and multiple regression analysis was used to examine the relationship between the demographic characteristics and categories. Data analysis was done using SPSS v24.

RESULTS

All five categories were rated moderately, between 2.5 and 3, by the participants. All categories were correlated (P < 0.01). Multiple regression analysis indicated the need for improvement between the professionals (mainly doctors and nurses) and the categories. The open questions pointed out the need for improvement in all 3 factors examined (Technology, Human Factor, Organization).

DISCUSSION

The moderately rated categories, in the Cyprus IHIS, suggest that there is a lot of room for improvement. Some interventions are suggested that could positively and simultaneously affect one or more categories.

Accountable Care Organizations Serving Deprived Communities Are Less Likely to Share in Savings

PURPOSE

Primary care physicians are increasingly participating in accountable care organizations (ACOs). While prior studies have identified ACO and patient characteristics associated with savings, none have examined characteristics of the communities served by ACOs. Our objective was to assess the relationship between an ACO's service area characteristics and its savings rate.

METHODS

In this cross-sectional study, we used the Centers for Medicare and Medicaid Services 2014 Medicare Shared Savings Program ACO Provider and Beneficiary, and Public Use Files to identify ACO and beneficiary characteristics. We used the American Community Survey to measure community deprivation at the ACO service area-level by using the social deprivation index. The outcome of interest was the ACO savings rate. We conducted bivariate analyses and regressions, adjusting for ACO organization and beneficiary characteristics.

RESULTS

Our sample consisted of 320 ACOs participating in the Shared Savings Plan. The savings rate for ACOs serving the most deprived communities was 1.19% compared with 1.14% for those serving the least deprived. Adjusting for ACO and beneficiary characteristics, however, ACOs serving the most deprived had a savings rate that was 2.3 percentage points lower than those serving the least deprived.

CONCLUSIONS

ACOs serving deprived communities generate less savings. These findings are important to primary care practices, payers, and policy makers anticipating continued ACO expansion, if population health is to be achieved equitably.

Mental Workload Relating Health Information System - A Literature Review

BACKGROUND

Assessing Mental Workload related to Health Information Systems can help to analyze weak points of the use of Health Information Systems and in health care work processes. Our objectives were to give an overview of current research and applied measurement methods as well as gaining insights into influencing factors of mental workload on the use of health information systems and vice versa.

METHODS

We applied a structured literature research by searching for "mental workload" on PubMed. Studies were included into our review if they assessed related to Health Information Systems.

RESULTS

The research in PubMed led to 124 articles, resulting in 17 papers taken into in-depth analyses. We identified three categories referring to different study design types. Additionally, articles showed that mental workload was influenced by using health information systems and vice versa.

DISCUSSION

The review was limited to only one database but revealed that future research with sociotechnical focus including mental workload is necessary.

CONCLUSION

In contrast to the high relevance only a few articles address mental workload in Health Information systems. The quality of the studies in terms of evidence and external validity appears to be largely in need of development and should be improved in ongoing research.

A Privacy-Preserving Infrastructure for Analyzing Personal Health Data in a Vertically Partitioned Scenario

It is widely anticipated that the use and analysis of health-related big data will enable further understanding and improvements in human health and wellbeing. Here, we propose an innovative infrastructure, which supports secure and privacy-preserving analysis of personal health data from multiple providers with different governance policies. Our objective is to use this infrastructure to explore the relation between Type 2 Diabetes Mellitus status and healthcare costs. Our approach involves the use of distributed machine learning to analyze vertically partitioned data from the Maastricht Study, a prospective population-based cohort study, and data from the official statistics agency of the Netherlands, Statistics Netherlands (Centraal Bureau voor de Statistiek; CBS). This project seeks an optimal solution accounting for scientific, technical, and ethical/legal challenges. We describe these challenges, our progress towards addressing them in a practical use case, and a simulation experiment.

A Framework for Applied AI in Healthcare

Significant efforts are being made to develop artificial intelligence technologies for health settings. In a health system that has been notoriously slow to adopt innovative technologies, it is important to consider the implementation of a new technology early in the development stage, especially one that will have added challenges of trust and transparency. To facilitate this process, an implementation framework for artificial intelligence technologies in clinical settings has been created.

Generalizability of Readability Models for Medical Terms

Detection of difficult for understanding words is a crucial task for ensuring the proper understanding of medical texts such as diagnoses and drug instructions. We propose to combine supervised machine learning algorithms using various features with word embeddings which contain context information of words. Data in French are manually cross-annotated by seven annotators. On the basis of these data, we propose cross-validation scenarios in order to test the generalization ability of models to detect the difficulty of medical words. On data provided by seven annotators, we show that the models are generalizable from one annotator to another.