The development and implementation of a new hospital performance measure to assess hospital contributions to community health and equity.

OBJECTIVE: To develop and implement a measure of how US hospitals contribute to community health with a focus on equity. DATA SOURCES: Primary data from public comments and hospital surveys and secondary data from the IBM Watson Top 100 Hospitals program collected in the United States in 2020 and 2021. STUDY DESIGN: A thematic analysis of public comments on the proposed measure was conducted using an iterative grounded approach for theme identification. A cross-sectional survey of 207 hospitals was conducted to assess self-attestation to 28 community health best practice standards in the revised measure. An analysis of hospital rankings before and after inclusion of the new measure was performed. DATA COLLECTION/EXTRACTION METHODS: Public comment on the proposed measure was collected via an online survey, email, and virtual meetings in 2020. The survey of hospitals was conducted online by IBM in 2021. The analysis of hospital ranking compared the 2020 and 2021 IBM Watson Top 100 Hospitals program results. PRINCIPAL FINDINGS: More than 650 discrete comments from 83 stakeholders were received and analyzed during measure development. Key themes identified in thematic analysis included equity, fairness, and community priorities. Hospitals that responded to a cross-sectional survey reported meeting on average 76% of applicable best practice standards. Least met standards included providing emergent buprenorphine treatment for opioid use disorder (53%), supporting an evidence-based home visiting program (53%), and establishing a returning citizens employment program (27%). Thirty-seven hospitals shifted position in the 100 Top Hospital rankings after the inclusion of the new measure. CONCLUSIONS: There is broad interest in measuring hospital contributions to community health with a focus on equity. Many highly ranked hospitals report meeting best practice standards, but significant gaps remain. Improving measurement to incentivize greater hospital contributions to community health and equity is an important priority.

Health Care Equity in the Use of Advanced Analytics and Artificial Intelligence Technologies in Primary Care.

The integration of advanced analytics and artificial intelligence (AI) technologies into the practice of medicine holds much promise. Yet, the opportunity to leverage these tools carries with it an equal responsibility to ensure that principles of equity are incorporated into their implementation and use. Without such efforts, tools will potentially reflect the myriad of ways in which data, algorithmic, and analytic biases can be produced, with the potential to widen inequities by race, ethnicity, gender, and other sociodemographic factors implicated in disparate health outcomes. We propose a set of strategic assertions to examine before, during, and after adoption of these technologies in order to facilitate healthcare equity across all patient population groups. The purpose is to enable generalists to promote engagement with technology companies and co-create, promote, or support innovation and insights that can potentially inform decision-making and health care equity.

Leveraging Informatics and Technology to Support Public Health Response: Framework and Illustrations using COVID-19.

OBJECTIVE: To develop a conceptual model and novel, comprehensive framework that encompass the myriad ways informatics and technology can support public health response to a pandemic. METHOD: The conceptual model and framework categorize informatics solutions that could be used by stakeholders (e.g., government, academic institutions, healthcare providers and payers, life science companies, employers, citizens) to address public health challenges across the prepare, respond, and recover phases of a pandemic, building on existing models for public health operations and response. RESULTS: Mapping existing solutions, technology assets, and ideas to the framework helped identify public health informatics solution requirements and gaps in responding to COVID-19 in areas such as applied science, epidemiology, communications, and business continuity. Two examples of technologies used in COVID-19 illustrate novel applications of informatics encompassed by the framework. First, we examine a hub from The Weather Channel, which provides COVID-19 data via interactive maps, trend graphs, and details on case data to individuals and businesses. Second, we examine IBM Watson Assistant for Citizens, an AI-powered virtual agent implemented by healthcare providers and payers, government agencies, and employers to provide information about COVID-19 via digital and telephone-based interaction. DISCUSSION: Early results from these novel informatics solutions have been positive, showing high levels of engagement and added value across stakeholders. CONCLUSION: The framework supports development, application, and evaluation of informatics approaches and technologies in support of public health preparedness, response, and recovery during a pandemic. Effective solutions are critical to success in recovery from COVID-19 and future pandemics.