Identifying Opportunities to Strengthen the Public Health Informatics Infrastructure: Exploring Hospitals' Challenges with Data Exchange.

Policy Points Even though most hospitals have the technological ability to exchange data with public health agencies, the majority continue to experience challenges. Most challenges are attributable to the general resources of public health agencies, although workforce limitations, technology issues such as a lack of data standards, and policy uncertainty around reporting requirements also remain prominent issues. Ongoing funding to support the adoption of technology and strengthen the development of the health informatics workforce, combined with revising the promotion of the interoperability scoring approach, will likely help improve the exchange of electronic data between hospitals and public health agencies. CONTEXT: The novel coronavirus 2019 (COVID-19) pandemic has highlighted significant barriers in the exchange of essential information between hospitals and local public health agencies. Thus it remains important to clarify the specific issues that hospitals may face in reporting to public health agencies to inform focused approaches to improve the information exchange for the current pandemic as well as ongoing public health activities and population health management. METHODS: This study uses cross-sectional data of acute-care, nonfederal hospitals from the 2017 American Hospital Association Annual Survey and Information Technology supplement. Guided by the technology-organization-environment framework, we coded the responses to a question regarding the challenges that hospitals face in submitting data to public health agencies by using content analysis according to the type of challenge (i.e., technology, organization, or environment), responsible entity (i.e., hospital, public health agency, vendor, multiple), and the specific issue described. We used multivariable logistic and multinomial regression to identify characteristics of hospitals associated with experiencing the types of challenges. FINDINGS: Our findings show that of the 2,794 hospitals in our analysis, 1,696 (61%) reported experiencing at least one challenge in reporting health data to a public health agency. Organizational issues were the most frequently reported type of challenge, noted by 1,455 hospitals. The most common specific issue, reported by 1,117 hospitals, was the general resources of public health agencies. An advanced EHR system and participation in a health information exchange both decreased the likelihood of not reporting experiencing a challenge and increased the likelihood of reporting an organizational challenge. CONCLUSIONS: Our findings inform policy recommendations such as improving data standards, increasing funding for public health agencies to improve their technological capabilities, offering workforce training programs, and increasing clarity of policy specifications and reporting. These approaches can improve the exchange of information between hospitals and public health agencies.

Distributed Data Networks That Support Public Health Information Needs.

INTRODUCTION: Data networks, consisting of pooled electronic health data assets from health care providers serving different patient populations, promote data sharing, population and disease monitoring, and methods to assess interventions. Better understanding of data networks, and their capacity to support public health objectives, will help foster partnerships, expand resources, and grow learning health systems. METHODS: We conducted semistructured interviews with 16 key informants across the United States, identified as network stakeholders based on their respective experience in advancing health information technology and network functionality. Key informants were asked about their experience with and infrastructure used to develop data networks, including each network's utility to identify and characterize populations, usage, and sustainability. RESULTS: Among 11 identified data networks representing hundreds of thousands of patients, key informants described aggregated health care clinical data contributing to population health measures. Key informant interview responses were thematically grouped to illustrate how networks support public health, including (1) infrastructure and information sharing; (2) population health measures; and (3) network sustainability. CONCLUSION: Collaboration between clinical data networks and public health entities presents an opportunity to leverage infrastructure investments to support public health. Data networks can provide resources to enhance population health information and infrastructure.

Better health intelligence: a new era for civil registration and vital statistics?

The impetus and opportunities for improving birth, death, and cause of death data have never been more propitious. Renewed country commitment to strengthen vital registration systems is clearly evident, supported by nascent regional coalitions of technical and development organisations. The announcement of a major new investment by Bloomberg Philanthropies to strengthen data systems and capacity in selected countries has the potential to catalyse and realise significant improvements in the availability and quality of data for health. This will require technical leadership, strategic intervention choices, strong country partnerships, and efficient delivery and management of multiple technical interventions across participating countries.

Cross-sectional survey on public health informatics workforce in China: issues, developments and the future.

OBJECTIVE: To explore the current situation and issues related to the development of the public health informatics (PHI) workforce in provincial and prefectural centers for disease control and prevention (CDCs) in China, and to describe the corresponding strategies to address these issues for the future. STUDY DESIGN: National cross-sectional study. METHODS: One thousand two hundred and eighty-one respondents were selected at random from provincial and prefectural CDCs. The survey used a self-administered, structured questionnaire with an online data collection tool that integrated data quality control and user management. The questionnaire was divided into seven main categories. Score percentage of satisfaction and proportion in each part were calculated. Descriptive statistics were used to analyse the data, stratifying by country region, CDC level, job role and educational level. RESULTS: One hundred and sixty staff from provincial CDCs and 1121 staff from prefectural CDCs were selected. Only 7.4% (33/445) of prefectural CDCs were not involved in this survey, due to lack of PHI practitioners. CDC staff in the eastern region were predominantly aged 30-39 years (39.5%), which was much younger compared with the other regions (P = 0.0012). Only 34 respondents (2.7%) had academic majors in both health and information technology. More staff had Master's degrees and a higher level of education (18.7%) in the eastern region compared with the other regions (P < 0.0001). Staff in the eastern region in high-level positions and with a higher level of education were more knowledgeable about PHI strategy. Prefectural CDC staff were more satisfied with their work and training than provincial CDC staff. In the eastern region, 34.9% of staff were hired through competitive recruitment, and 57.8% of staff had received a job description with detailed information about their responsibilities, which was higher than in the other regions. Staff in the western region were more likely to leave if a better job became available (37.7%) compared with staff in the other regions (P = 0.0116). CONCLUSION: This study found regional disparities in PHI workforce development, possibly related to disparities in overall regional development. Findings showed a severe shortage of staff with a background in PHI, and occupational development paths were clearly lacking. Based on this study of current workforce issues, a comprehensive strategy for PHI workforce development in China has been described.

Accelerating the development of an information ecosystem in health care, by stimulating the growth of safe intermediate processing of health information (IPHI).

Health care, in common with many other industries, is generating large amounts of routine data, data that are challenging to process, analyse or curate, so-called 'big data'. A challenge for health informatics is to make sense of these data. Part of the answer will come from the development of ontologies that support the use of heterogeneous data sources and the development of intermediate processors of health information (IPHI). IPHI will sit between the generators of health data and information, often the providers of health care, and the managers, commissioners, policy makers, researchers, and the pharmaceutical and other healthcare industries. They will create a health ecosystem by processing data in a way that stimulates improved data quality and potentially healthcare delivery by providers of health care, and by providing greater insights to legitimate users of data. Exemplars are provided of how a health ecosystem might be encouraged and developed to promote patient safety and more efficient health care. These are in the areas of how to integrate data around the unsafe use of alcohol and to explore vaccine safety. A challenge for IPHI is how to ensure that their processing of data is valid, safe and maintains privacy. Development of the healthcare ecosystem and IPHI should be actively encouraged internationally. Governments, regulators and providers of health care should facilitate access to health data and the use of national and international comparisons to monitor standards. However, most importantly, they should pilot new methods of improving quality and safety through the intermediate processing of health data.

Public Health and Epidemiology Informatics: Recent Research Trends.

OBJECTIVES: To introduce and analyse current trends in Public Health and Epidemiology Informatics. METHODS: PubMed search of 2020 literature on public health and epidemiology informatics was conducted and all retrieved references were reviewed by the two section editors. Then, 15 candidate best papers were selected among the 920 references. These papers were then peer-reviewed by the two section editors, two chief editors, and external reviewers, including at least two senior faculty, to allow the Editorial Committee of the 2021 International Medical Informatics Association (IMIA) Yearbook to make an informed decision regarding the selection of the best papers. RESULTS: Among the 920 references retrieved from PubMed, four were suggested as best papers and the first three were finally selected. The fourth paper was excluded because of reproducibility issues. The first best paper is a very public health focused paper with health informatics and biostatistics methods applied to stratify patients within a cohort in order to identify those at risk of suicide; the second paper describes the use of a randomized design to test the likely impact of fear-based messages, with and without empowering self-management elements, on patient consultations or antibiotic requests for influenza-like illnesses. The third selected paper evaluates the perception among communities of routine use of Whole Genome Sequencing and Big Data technologies to capture more detailed and specific personal information. CONCLUSIONS: The findings from the three studies suggest that using Public Health and Epidemiology Informatics methods could leverage, when combined with Deep Learning, early interventions and appropriate treatments to mitigate suicide risk. Further, they also demonstrate that well informing and empowering patients could help them to be involved more in their care process.

The future of health intelligence: challenges and opportunities.

Over the last 10 years, the discipline of health intelligence has come into being. This combines analysis, informatics, public health methodology, skills and interpretation. We have come a long way but there remains a long way to go. In particular, a number of challenges for the next 10 years are articulated, namely: the right information at the right time; real-time data; barriers to information access; and knowledge transfer.

Data-driven. HHS unleashes wave of public health data so software developers can create tools to raise awareness, spur action.

Guided by how weather data from the National Oceanic and Atmospheric Administration fuels all kinds of weather reports, maps and forecasts, HHS officials saw parallels on how to distribute health data so software developers could create tools to be used by patients and providers. "We thought that was inspiring," said Todd Park, left, HHS' chief technology officer.

COVID-19 prevention and treatment information on the internet: a systematic analysis and quality assessment.

OBJECTIVE: To evaluate the quality of information regarding the prevention and treatment of COVID-19 available to the general public from all countries. DESIGN: Systematic analysis using the 'Ensuring Quality Information for Patients' (EQIP) Tool (score 0-36), Journal of American Medical Association (JAMA) benchmark (score 0-4) and the DISCERN Tool (score 16-80) to analyse websites containing information targeted at the general public. DATA SOURCES: Twelve popular search terms, including 'Coronavirus', 'COVID-19 19', 'Wuhan virus', 'How to treat coronavirus' and 'COVID-19 19 Prevention' were identified by 'Google AdWords' and 'Google Trends'. Unique links from the first 10 pages for each search term were identified and evaluated on its quality of information. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: All websites written in the English language, and provides information on prevention or treatment of COVID-19 intended for the general public were considered eligible. Any websites intended for professionals, or specific isolated populations, such as students from one particular school, were excluded, as well as websites with only video content, marketing content, daily caseload update or news dashboard pages with no health information. RESULTS: Of the 1275 identified websites, 321 (25%) were eligible for analysis. The overall EQIP, JAMA and DISCERN scores were 17.8, 2.7 and 38.0, respectively. Websites originated from 34 countries, with the majority from the USA (55%). News Services (50%) and Government/Health Departments (27%) were the most common sources of information and their information quality varied significantly. Majority of websites discuss prevention alone despite popular search trends of COVID-19 treatment. Websites discussing both prevention and treatment (n=73, 23%) score significantly higher across all tools (p<0.001). CONCLUSION: This comprehensive assessment of online COVID-19 information using EQIP, JAMA and DISCERN Tools indicate that most websites were inadequate. This necessitates improvements in online resources to facilitate public health measures during the pandemic.

Characteristics of HIV seroprevalence of visitors to public health centers under the national HIV surveillance system in Korea: cross sectional study.

BACKGROUND: In Korea, the cumulative number of HIV-infected individuals was smaller than those of other countries. Mandatory HIV tests, dominating method until 1990's, have been gradually changed to voluntary HIV tests. We investigated HIV seroprevalence status and its characteristics of visitors to Public Health Centers (PHCs), which conducted both mandatory test and voluntary test under the national HIV/STI surveillance program. METHODS: We used HIV-testing data from 246 PHCs in 2005 through the Health Care Information System. The number of test taker was calculated using the code distinguished by the residential identification number. The subjects were classified into four groups by reason for testing; General group, HIV infection suspected group (HIV ISG), HIV test recommended group (HIV TRG), and sexually transmitted infection (STI) risk group. RESULTS: People living with HIV/AIDS were 149 (124 male and 25 female) among 280,456 individuals tested at PHCs. HIV seroprevalence was 5.3 per 10,000 individuals. Overall, the male revealed significantly higher seroprevalence than the female (adjusted Odds Ratio (adj. OR): 6.2; CI 3.8-10.2). Individuals aged 30-39 years (adj. OR: 2.6; CI 1.7-4.0), and 40-49 years (adj. OR: 3.8; CI 2.4-6.0) had higher seroprevalence than 20-29 years. Seroprevalence of HIV ISG (voluntary test takers and cases referred by doctors) was significantly higher than those of others. Foreigners showed higher seroprevalence than native Koreans (adj. OR: 3.8; CI 2.2-6.4). HIV ISG (adj. OR: 4.9; CI 3.2-7.5), and HIV TRG (adj. OR: 2.6; CI 1.3-5.4) had higher seroprevalence than General group. CONCLUSION: A question on the efficiency of current mandatory test is raised because the seroprevalence of mandatory test takers was low. However, HIV ISG included voluntary test takers was high in our result. Therefore, we suggest that Korea needs to develop a method encouraging more people to take voluntary tests at PHCs, also to expand the anonymous testing centers and Voluntary Counselling and Testing Program (VCT) for general population to easily access to HIV testing.

HCLS 2.0/3.0: health care and life sciences data mashup using Web 2.0/3.0.

We describe the potential of current Web 2.0 technologies to achieve data mashup in the health care and life sciences (HCLS) domains, and compare that potential to the nascent trend of performing semantic mashup. After providing an overview of Web 2.0, we demonstrate two scenarios of data mashup, facilitated by the following Web 2.0 tools and sites: Yahoo! Pipes, Dapper, Google Maps and GeoCommons. In the first scenario, we exploited Dapper and Yahoo! Pipes to implement a challenging data integration task in the context of DNA microarray research. In the second scenario, we exploited Yahoo! Pipes, Google Maps, and GeoCommons to create a geographic information system (GIS) interface that allows visualization and integration of diverse categories of public health data, including cancer incidence and pollution prevalence data. Based on these two scenarios, we discuss the strengths and weaknesses of these Web 2.0 mashup technologies. We then describe Semantic Web, the mainstream Web 3.0 technology that enables more powerful data integration over the Web. We discuss the areas of intersection of Web 2.0 and Semantic Web, and describe the potential benefits that can be brought to HCLS research by combining these two sets of technologies.

HealthMap: the development of automated real-time internet surveillance for epidemic intelligence.

With the recent entry into force of the new International Health Regulations (IHR 2005), there is still significant concern as to whether broad compliance will be feasible given the challenges associated with reporting mechanisms and multilateral coordination.

Inventory of electronic health information exchange in Wisconsin, 2006.

CONTEXT: The Governor's Board for eHealth Care Quality and Patient Safety plans for universal adoption of electronic health records and information exchange. OBJECTIVES: The inventory sought to describe characteristics, challenges, and policy recommendations of health information exchange (HIE) projects and create a directory and baseline for periodic reassessment. DESIGN, SETTING, SUBJECTS: A cross-sectional Internet survey of any project where electronic patient information was transmitted by multiple organizations in Wisconsin in 2006. MAIN OUTCOME MEASURES: A description of operational and planned HIE projects, including stage of development, information users, organizational home, funding, governance, geographic scope, data standardization, drivers, internal and external challenges, and recommendations for statewide action. RESULTS: Twenty-one organizations sponsor 16 operational and 11 planned HIE projects. Most are surveillance programs, but a growing proportion serves clinicians and patients. Under half use data standards for interoperability. Leading internal challenges relate to funding, organizational and staff issues, governance, and technology. Leading external challenges are marketing, enlisting participants, regulatory issues, and sustainability. CONCLUSION: Wisconsin enjoys rich experience with HIE, but data remains largely in separate silos. Statewide collaboration, coordination and resource sharing can enhance the future of exchange efforts.

PopHR: a knowledge-based platform to support integration, analysis, and visualization of population health data.

Population health decision makers must consider complex relationships between multiple concepts measured with differential accuracy from heterogeneous data sources. Population health information systems are currently limited in their ability to integrate data and present a coherent portrait of population health. Consequentially, these systems can provide only basic support for decision makers. The Population Health Record (PopHR) is a semantic web application that automates the integration and extraction of massive amounts of heterogeneous data from multiple distributed sources (e.g., administrative data, clinical records, and survey responses) to support the measurement and monitoring of population health and health system performance for a defined population. The design of the PopHR draws on the theories of the determinants of health and evidence-based public health to harmonize and explicitly link information about a population with evidence about the epidemiology and control of chronic diseases. Organizing information in this manner and linking it explicitly to evidence is expected to improve decision making related to the planning, implementation, and evaluation of population health and health system interventions. In this paper, we describe the PopHR platform and discuss the architecture, design, key modules, and its implementation and use.