A population ecology perspective on the functioning and future of health information organizations

Background: Increasingly, health care providers need to exchange information to meet policy expectations and business needs. A variety of health information organizations (HIOs) provide services to facilitate health information exchange (HIE). However, the future of these organizations is unclear. Purpose: The aim of this study was to explore the environmental context, potential futures, and survivability of community HIOs, enterprise HIEs, and electronic health record vendor-mediated exchange using the population ecology theory. Approach: Qualitative interviews with 33 key informants representing each type of HIE organization were analyzed using template analysis. Results: Community HIOs, enterprise HIEs, and electronic health record vendors exhibited a high degree of competition for resources, especially in the area of exchange infrastructure services. Competition resulted in closures in some areas. In response to environmental pressures, each organizational type was endeavoring to differentiate its services and unique use case, as well as pursing symbiotic relationships or attempting resource partitioning. Conclusion: HIOs compete for similar resources and are reacting to environmental pressures to better position themselves for continued survival and success. Our ecological research perspective helps move the discourse away from situation of a single exchange organization type toward a view of the broader dynamics and relationships of all organizations involved in facilitating HIE activities

Differing Strategies to Meet Information‐Sharing Needs: Publicly Supported Community Health Information Exchanges Versus Health Systems’ Enterprise Health Information Exchanges

POLICY POINTS: Community health information exchanges have the characteristics of a public good, and they support population health initiatives at the state and national levels. However, current policy equally incentivizes health systems to create their own information exchanges covering more narrowly defined populations. Noninteroperable electronic health records and vendors' expensive custom interfaces are hindering health information exchanges. Moreover, vendors are imposing the costs of interoperability on health systems and community health information exchanges. Health systems are creating networks of targeted physicians and facilities by funding connections to their own enterprise health information exchanges. These private networks may change referral patterns and foster more integration with outpatient providers. CONTEXT: The United States has invested billions of dollars to encourage the adoption of and implement the information technologies necessary for health information exchange (HIE), enabling providers to efficiently and effectively share patient information with other providers. Health care providers now have multiple options for obtaining and sharing patient information. Community HIEs facilitate information sharing for a broad group of providers within a region. Enterprise HIEs are operated by health systems and share information among affiliated hospitals and providers. We sought to identify why hospitals and health systems choose either to participate in community HIEs or to establish enterprise HIEs. METHODS: We conducted semistructured interviews with 40 policymakers, community and enterprise HIE leaders, and health care executives from 19 different organizations. Our qualitative analysis used a general inductive and comparative approach to identify factors influencing participation in, and the success of, each approach to HIE. FINDINGS: Enterprise HIEs support health systems' strategic goals through the control of an information technology network consisting of desired trading partners. Community HIEs support obtaining patient information from the broadest set of providers, but with more dispersed benefits to all participants, the community, and patients. Although not an either/or decision, community and enterprise HIEs compete for finite organizational resources like time, skilled staff, and money. Both approaches face challenges due to vendor costs and less-than-interoperable technology. CONCLUSIONS: Both community and enterprise HIEs support aggregating clinical data and following patients across settings. Although they can be complementary, community and enterprise HIEs nonetheless compete for providers' attention and organizational resources. Health policymakers might try to encourage the type of widespread information exchange pursued by community HIEs, but the business case for enterprise HIEs clearly is stronger. The sustainability of a community HIE, potentially a public good, may necessitate ongoing public funding and supportive regulation

Applications of health information exchange information to public health practice

Increased information availability, timeliness, and comprehensiveness through health information exchange (HIE) can support public health practice. The potential benefits to disease monitoring, disaster response, and other public health activities served as an important justification for the US’ investments in HIE. After several years of HIE implementation and funding, we sought to determine if any of the anticipated benefits of exchange participation were accruing to state and local public health practitioners participating in five different exchanges. Using qualitative interviews and template analyses, we identified public health efforts and activities that were improved by participation in HIE. HIE supported public health activities consistent with expectations in the literature. However, no single department realized all the potential benefits of HIE identified. These findings suggest ways to improve HIE usage in public health

Using Bibliometric Big Data to Analyze Faculty Research Productivity in Health Policy and Management

Bibliometric big data and social media tools provide new opportunities to aggregate and analyze researchers' scholarly impact. The purpose of the current paper is to describe the process and results we obtained after aggregating a list of public Google Scholar profiles representing researchers in Health Policy and Management or closely-related disciplines. We extracted publication and citation data on 191 researchers affiliated with health administration programs in the U.S. With these data, we created a publicly available listing of faculty that includes each person's name, affiliation, year of first citation, total citations, h-index, and i-10 index. The median of total citations per individual faculty member was 700, while the maximum was 46,363. The median h-index was 13, while the maximum was 91. We plan to update these statistics and add new faculty to our public listing as new Google Scholar profiles are created by faculty members in the field. This listing provides a resource for students and faculty in our discipline to easily compare productivity and publication records of faculty members in their own and other departments. Similarly, this listing provides a resource for faculty, including department chairs and deans, who desire discipline-specific context for promotion and tenure processes

Not only teachers: What do health administration faculty members do?

Researchers have long been interested in how university faculty allocate their time between professional tasks. This study uses multiple years of Health Administration (HA) faculty survey data to examine how work activity has changed over time, and how work activity relates to faculty rank and the type of school in which a faculty member is employed. We report on faculty time allocation to research, teaching, and administration by survey year, faculty rank, and type of school. We also examine factors related to faculty's status as a principal investigator, teaching load, and research funding. On average, HA faculty spent 43% of their time teaching, 31% doing research, 20% in administrative activities, and 5% in other activities. Full professors spent significantly less time teaching, had lighter teaching loads, and spent more time on administration than other faculty. Faculty in schools of health professions, business, and other schools spent more time in teaching and had lower research funding expectations than faculty in schools of public health and medicine. These findings may help faculty identify jobs that best align with their interests and benchmark their work against industry norms. These findings may also help administrators in HA programs set appropriate expectations for their faculty

Using structured and unstructured data to identify patients’ need for services that address the social determinants of health

Introduction Increasingly, health care providers are adopting population health management approaches that address the social determinants of health (SDH). However, effectively identifying patients needing services that address a SDH in primary care settings is challenging. The purpose of the current study is to explore how various data sources can identify adult primary care patients that are in need of services that address SDH. Methods A cross-sectional study described patients in need of SDH services offered by a safety-net hospital’s federally qualified health center clinics. SDH services of social work, behavioral health, nutrition counseling, respiratory therapy, financial planning, medical-legal partnership assistance, patient navigation, and pharmacist consultation were offered on a co-located basis and were identified using structured billing and scheduling data, and unstructured electronic health record data. We report the prevalence of the eight different SDH service needs and the patient characteristics associated with service need. Moreover, characteristics of patients with SDH services need documented in structured data sources were compared with those documented by unstructured data sources. Results More than half (53%) of patients needed SDH services. Those in need of such services tended to be female, older, more medically complex, and higher utilizers of services. Structured and unstructured data sources exhibited poor agreement on patient SDH services need. Patients with SDH services need documented by unstructured data tended to be more complex. Discussion The need for SDH services among a safety-net population is high. Identifying patients in need of such services requires multiple data sources with structured and unstructured data

Factors Related to User Ratings and User Downloads of Mobile Apps for Maternal and Infant Health: Cross-Sectional Study

Background: Mobile health apps related to maternal and infant health (MIH) are prevalent and frequently used. Some of these apps are extremely popular and have been downloaded over 5 million times. However, the understanding of user behavior and user adoption of these apps based on consumer preferences for different app features and categories is limited. Objective: This study aimed to examine the relationship between MIH app characteristics and users’ perceived satisfaction and intent to use. Methods: The associations between app characteristics, ratings, and downloads were assessed in a sample of MIH apps designed to provide health education or decision-making support to pregnant women or parents and caregivers of infants. Multivariable linear regression was used to assess the relationship between app characteristics and user ratings, and ordinal logistic regression was used to assess the relationship between app characteristics and user downloads. Results: The analyses of user ratings and downloads included 421 and 213 apps, respectively. The average user rating was 3.79 out of 5. Compared with the Apple App Store, the Google Play Store was associated with high user ratings (beta=.33; P =.005). Apps with higher standardized user ratings (beta=.80; P <.001), in-app purchases (beta=1.12; P =.002), and in-app advertisements (beta=.64; P =.02) were more frequently downloaded. Having a health care organization developer as part of the development team was neither associated with user ratings (beta=−.20; P =.06) nor downloads (beta=−.14; P =.63). Conclusions: A majority of MIH apps are developed by non–health care organizations, which could raise concern about the accuracy and trustworthiness of in-app information. These findings could benefit app developers in designing better apps and could help inform marketing and development strategies. Further work is needed to evaluate the clinical accuracy of information provided within the apps. [JMIR Mhealth Uhealth 2020;8(1):e15663

Image Sharing Technologies and Reduction of Imaging Utilization: A Systematic Review and Meta-analysis

INTRODUCTION: Image sharing technologies may reduce unneeded imaging by improving provider access to imaging information. A systematic review and meta-analysis were conducted to summarize the impact of image sharing technologies on patient imaging utilization. METHODS: Quantitative evaluations of the effects of PACS, regional image exchange networks, interoperable electronic heath records, tools for importing physical media, and health information exchange systems on utilization were identified through a systematic review of the published and gray English-language literature (2004-2014). Outcomes, standard effect sizes (ESs), settings, technology, populations, and risk of bias were abstracted from each study. The impact of image sharing technologies was summarized with random-effects meta-analysis and meta-regression models. RESULTS: A total of 17 articles were included in the review, with a total of 42 different studies. Image sharing technology was associated with a significant decrease in repeat imaging (pooled effect size [ES] = -0.17; 95% confidence interval [CI] = [-0.25, -0.09]; P < .001). However, image sharing technology was associated with a significant increase in any imaging utilization (pooled ES = 0.20; 95% CI = [0.07, 0.32]; P = .002). For all outcomes combined, image sharing technology was not associated with utilization. Most studies were at risk for bias. CONCLUSIONS: Image sharing technology was associated with reductions in repeat and unnecessary imaging, in both the overall literature and the most-rigorous studies. Stronger evidence is needed to further explore the role of specific technologies and their potential impact on various modalities, patient populations, and settings

Challenges in Translating National and State Reopening Plans Into Local Reopening Policies During the COVID-19 Pandemic

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Pandemic events, such as coronavirus disease 2019 (COVID-19), affect health and economics at national and international scales, but in the United States, health care delivery and public health practice occur at the local level. Transmission control and eventual economic recovery require detailed guidance for communities, cities, metropolitan areas, and states. Our recent experience as consultants on the control and reopening plans for the city of Indianapolis and Marion County, Indiana, illustrated challenges with national plans, highlighted fundamental tensions in identifying the best course for policy, and emphasized gaps in the evidence base and our public health resources