Wearable technologies promise to redefine assessment of health behaviors, yet their clinical implementation remains a challenge. To address this gap, two of the NIH’s Big Data to Knowledge Centers of Excellence organized a workshop on potential clinical applications of wearables. A workgroup comprised of 14 stakeholders from diverse backgrounds (hospital administration, clinical medicine, academia, insurance, and the commercial device industry) discussed two successful digital health interventions that involve wearables to identify common features responsible for their success. Seven features were identified including: a clearly defined problem, integration into a system of healthcare delivery, technology support, personalized experience, focus on end-user experience, alignment with reimbursement models, and inclusion of clinician champions. Health providers and systems keen to establish new models of care inclusive of wearables may consider these features during program design. A better understanding of these features is necessary to guide future clinical applications of wearable technology.

ImportanceAntibiotic resistance is a global health issue. Up to 50% of antibiotics are inappropriately prescribed, the majority of which are for acute respiratory tract infections (ARTI).ObjectiveTo evaluate the impact of unblinded normative comparison on rates of inappropriate antibiotic prescribing for ARTI.DesignNon-randomised, controlled interventional trial over 1 year followed by an open intervention in the second year.SettingPrimary care providers in a large regional healthcare system.ParticipantsThe test group consisted of 30 primary care providers in one geographical region; controls consisted of 162 primary care providers located in four other geographical regions.InterventionThe intervention consisted of provider and patient education and provider feedback via biweekly, unblinded normative comparison highlighting inappropriate antibiotic prescribing for ARTI. The intervention was applied to both groups during the second year.Main outcomes and measuresRate of inappropriate antibiotic prescription for ARTI.ResultsBaseline inappropriate antibiotic prescribing for ARTI was 60%. After 1 year, the test group rate of inappropriate antibiotic prescribing decreased 40%, from 51.9% to 31.0% (p<0.0001), whereas controls decreased 7% (61.3% to 57.0%, p<0.0001). In year 2, the test group decreased an additional 47% to an overall prescribing rate of 16.3%, and the control group decreased 40% to a prescribing rate of 34.5% after implementation of the same intervention.Conclusions and relevanceProvider and patient education followed by regular feedback to provider via normative comparison to their local peers through unblinded provider reports, lead to reductions in the rate of inappropriate antibiotic prescribing for ARTI and overall antibiotic prescribing rates.

Modest changes in routine hospital care can improve the hospital environment impacting sleep and access to health knowledge, leading to improvements in hospital outcomes. Sleep-wake patterns of hospitalized patients represent a potential avenue for further enhancing hospital quality and safety.

Hypertension (HTN) is the most common chronic disease in the U.S., and the standard model of office-based care delivery has yielded suboptimal outcomes, with approximately 50% of affected patients not achieving blood pressure (BP) control. Poor population-level BP control has been primarily attributed to therapeutic inertia and low patient engagement. New models of care delivery utilizing patient-generated health data, comprehensive assessment of social health determinants, computerized algorithms generating tailored interventions, frequent communication and reporting, and non-physician providers organized as an integrated practice unit, have the potential to transform population-based HTN control. This review will highlight the importance of these elements and construct the rationale for a reengineered model of care delivery for populations with HTN.

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