Assessing and addressing COVID-19 information needs via a weather application.

We describe implementation and usage of a coronavirus disease 2019 (COVID-19) digital information hub delivered through the widely adopted The Weather Company (TWC) application and explore COVID-19 knowledge, behaviors, and information needs of users. TWC deployed the tool, which displayed local case counts and trends, in March 2020. Unique users, visits, and interactions with tool features were measured. In August 2020, a cross-sectional survey assessed respondent characteristics, COVID-19 knowledge, behaviors, and preferences. TWC COVID-19 hub averaged 1.97 million unique users with over 2.6 million visits daily and an average interaction time of 1.63 min. Respondents reported being knowledgeable about COVID-19 (92.3%) and knowing relevant safety precautions (90.9%). However, an average of 35.3% of respondents reported not increasing preventive practices across behaviors surveyed due to information about COVID-19. In conclusion, we find a free weather application delivered COVID-19 data to millions of Americans. Despite confidence in knowledge and best practices for prevention, over one-third of survey respondents did not increase practice of preventive behaviors due to information about COVID-19.

Risky business: a scoping review for communicating results of predictive models between providers and patients.

OBJECTIVE: Given widespread excitement around predictive analytics and the proliferation of machine learning algorithms that predict outcomes, a key next step is understanding how this information is-or should be-communicated with patients. MATERIALS AND METHODS: We conducted a scoping review informed by PRISMA-ScR guidelines to identify current knowledge and gaps in this domain. RESULTS: Ten studies met inclusion criteria for full text review. The following topics were represented in the studies, some of which involved more than 1 topic: disease prevention (N = 5/10, 50%), treatment decisions (N = 5/10, 50%), medication harms reduction (N = 1/10, 10%), and presentation of cardiovascular risk information (N = 5/10, 50%). A single study included 6- and 12-month clinical outcome metrics. DISCUSSION: As predictive models are increasingly published, marketed by industry, and implemented, this paucity of relevant research poses important gaps. Published studies identified the importance of (1) identifying the most effective source of information for patient communications; (2) contextualizing risk information and associated design elements based on users' needs and problem areas; and (3) understanding potential impacts on risk factor modification and behavior change dependent on risk presentation. CONCLUSION: An opportunity remains for researchers and practitioners to share strategies for effective selection of predictive algorithms for clinical practice, approaches for educating clinicians and patients in effectively using predictive data, and new approaches for framing patient-provider communication in the era of artificial intelligence.

The Perceived Impact and Usability of a Care Management and Coordination System in Delivering Services to Vulnerable Populations: Mixed Methods Study.

BACKGROUND: People with complex needs, such as those experiencing homelessness, require concurrent, seamless support from multiple social service agencies. Sonoma County, California has one of the nation's largest homeless populations among largely suburban communities. To support client-centered care, the county deployed a Care Management and Coordination System (CMCS). This system comprised the Watson Care Manager (WCM), a front-end system, and Connect 360, which is an integrated data hub that aggregates information from various systems into a single client record. OBJECTIVE: The aim of this study is to evaluate the perceived impact and usability of WCM in delivering services to the homeless population in Sonoma County. METHODS: A mixed methods study was conducted to identify ways in which WCM helps to coordinate care. Interviews, observations, and surveys were conducted, and transcripts and field notes were thematically analyzed and directed by a grounded theory approach. Responses to the Technology Acceptance Model survey were analyzed. RESULTS: A total of 16 participants were interviewed, including WCM users (n=8) and department leadership members (n=8). In total, 3 interdisciplinary team meetings were observed, and 8 WCM users were surveyed. WCM provided a central shared platform where client-related, up-to-date, comprehensive, and reliable information from participating agencies was consolidated. Factors that facilitated WCM use were users' enthusiasm regarding the tool functionalities, scalability, and agency collaboration. Constraining factors included the suboptimal awareness of care delivery goals and functionality of the system among the community, sensitivities about data sharing and legal requirements, and constrained funding from government and nongovernment organizations. Overall, users found WCM to be a useful tool that was easy to use and helped to enhance performance. CONCLUSIONS: WCM supports the delivery of care to individuals with complex needs. Integration of data and information in a CMCS can facilitate coordinated care. Future research should examine WCM and similar CMCSs in diverse populations and settings.

U.S. hospital performance methodologies: a scoping review to identify opportunities for crossing the quality chasm.

BACKGROUND: Hospital performance quality assessments inform patients, providers, payers, and purchasers in making healthcare decisions. These assessments have been developed by government, private and non-profit organizations, and academic institutions. Given the number and variability in available assessments, a knowledge gap exists regarding what assessments are available and how each assessment measures quality to identify top performing hospitals. This study aims to: (a) comprehensively identify current hospital performance assessments, (b) compare quality measures from each methodology in the context of the Institute of Medicine's (IOM) six domains of STEEEP (safety, timeliness, effectiveness, efficiency, equitable, and patient-centeredness), and (c) formulate policy recommendations that improve value-based, patient-centered care to address identified gaps. METHODS: A scoping review was conducted using a systematic search of MEDLINE and the grey literature along with handsearching to identify studies that provide assessments of US-based hospital performance whereby the study cohort examined a minimum of 250 hospitals in the last two years (2017-2019). RESULTS: From 3058 unique records screened, 19 hospital performance assessments met inclusion criteria. Methodologies were analyzed across each assessment and measures were mapped to STEEEP. While safety and effectiveness were commonly identified measures across assessments, efficiency, and patient-centeredness were less frequently represented. Equity measures were also limited to risk- and severity-adjustment methods to balance patient characteristics across populations, rather than stand-alone indicators to evaluate health disparities that may contribute to community-level inequities. CONCLUSIONS: To further improve health and healthcare value-based decision-making, there remains a need for methodological transparency across assessments and the standardization of consensus-based measures that reflect the IOM's quality framework. Additionally, a large opportunity exists to improve the assessment of health equity in the communities that hospitals serve.