Outcomes from an Early Adopters Home Hospital Accelerator for Acute Care at Home.

BACKGROUND: Following the Centers for Medicare and Medicaid Services' approval of the Acute Hospital Care at Home waiver, an increasing number of health care organizations launched Home Hospital (HH) programs in the USA. Ongoing barriers include access to HH expertise and a standard, comprehensive set of implementation tools. We created the HH Early Adopters Accelerator to bring together a network of health care organizations to develop tools ("knowledge products") necessary for HH implementation. OBJECTIVE: To demonstrate the feasibility of the Accelerator approach for generating and implementing relevant, high-quality knowledge products. DESIGN: Mixed methods evaluation of the Accelerator. Surveys and qualitative interviews of Accelerator participants were conducted. Surveys elicited feedback on the knowledge products, including time spent on development, perceived utility and quality, and implementation success. The qualitative interviews gathered more in-depth information on topics covered in the surveys. PARTICIPANTS: Eighteen healthcare organizations and 105 individuals participated in the Accelerator. KEY RESULTS: The Accelerator reached its goal and developed 20 knowledge products in 32 working weeks (more efficient than expected). Participants agreed that the knowledge products were useful (developers: 98.1%; stakeholders: 93.8%), of high quality (developers: 96.8%), and would improve patient care if implemented in their HH program (developers: 91.7%; stakeholders: 91.2%). Two thirds (66.7%) of the participating organizations who had implemented knowledge products at 3 months continued utilizing knowledge products in their HH program at 1 year. Agreement that knowledge products improve patient care persisted (92% strongly agreed or agreed) at 1 year. Several programs created new tools, policies, and workflows as a result of implementing the knowledge products. CONCLUSIONS: The Accelerator created high-quality, comprehensive knowledge products that healthcare organizations found useful for safe HH implementation 1 year later. The Accelerator approach can feasibly help healthcare organizations safely bridge the gap between innovation and standard practice.

Characteristics and Attitudes of Wearable Device Users and Nonusers in a Large Health Care System.

BACKGROUND: Consumer wearable devices with health and wellness features are increasingly common and may enhance disease detection and management. Yet studies informing relationships between wearable device use, attitudes toward device data, and comprehensive clinical profiles are lacking. METHODS AND RESULTS: WATCH-IT (Wearable Activity Tracking for Comprehensive Healthcare-Integrated Technology) studied adults receiving longitudinal primary or ambulatory cardiovascular care in the Mass General Brigham health care system from January 2010 to July 2021. Participants completed a 20-question electronic survey about perceptions and use of consumer wearable devices, with responses linked to electronic health records. Multivariable logistic regression was used to identify factors associated with device use. Among 214 992 individuals receiving longitudinal primary or cardiovascular care with an active electronic portal, 11 121 responded (5.2%). Most respondents (55.8%) currently used a wearable device, and most nonusers (95.3%) would use a wearable if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, most believed it would be very (20.4%) or moderately (34.4%) important to share device-related health information with providers. In multivariable models, older age (odds ratio [OR], 0.80 per 10-year increase [95% CI, 0.77-0.82]), male sex (OR, 0.87 [95% CI, 0.80-0.95]), and heart failure (OR, 0.75 [95% CI, 0.63-0.89]) were associated with lower odds of wearable device use, whereas higher median income (OR, 1.08 per 1-quartile increase [95% CI, 1.04-1.12]) and care in a cardiovascular medicine clinic (OR, 1.17 [95% CI, 1.05-1.30]) were associated with greater odds of device use. CONCLUSIONS: Among patients in primary and cardiovascular medicine clinics, consumer wearable device use is common, and most users perceive value in wearable health data.

Building alternative payment models in health care.

Introduction: Global interest is growing in new value-based models of financing, delivering, and paying for health care services that could produce higher-quality and lower cost outcomes for patients and for society. However, research indicates evidence gaps in knowledge related to alternative payment models (APMs) in early experimentation phases or those contracted between private insurers and their health care provider-partners. The aim of this research was to understand and update the literature related to learning how industry experts design and implement APMs, including specific elements of their models and their choice of stakeholders to be involved in the design and contractual details. Methods: A literature review was conducted to guide the research focus and to select themes. The sample was selected using snowball sampling to identify subject matter experts (SMEs). Researchers conducted 16 semi-structured interviews with SMEs in the US, the Netherlands, and Germany in September and October 2021. Interviews were transcribed and using Braun and Clarke's six-phase approach to thematic analysis, researchers independently read, reviewed, and coded participants' responses related to APM design and implementation and subsequently reviewed each other's codes and themes for consistency. Results: Participants represented diverse perspectives of the payer, provider, consulting, and government areas of the health care sector. We found design considerations had five overarching themes: (1) population and scope of care and services, (2) benchmarking, metrics, data, and technology; (3) finance, APM type, risk adjustment, incentives, and influencing provider behavior, (4) provider partnerships and the role of physicians, and (5) leadership and regulatory issues. Discussion: This study confirmed several of the core components of APM model designs and implementations found in the literature and brought insights on additional aspects not previously emphasized, particularly the role of physicians (especially in leadership) and practice transformation/care processes necessary for providers to thrive under APM models. Importantly, researchers found significant concerns relevant for policymakers about regulations relating to health data sharing, rigid price-setting, and inter-organizational data communication that greatly inhibit the ability to experiment with APMs and those models' abilities to succeed long-term.