Detection of Medication Taking Using a Wrist-Worn Commercially Available Wearable Device.

PURPOSE: Medication nonadherence is a persistent and costly problem across health care. Measures of medication adherence are ineffective. Methods such as self-report, prescription claims data, or smart pill bottles have been used to monitor medication adherence, but these are subject to recall bias, lack real-time feedback, and are often expensive. METHODS: We proposed a method for monitoring medication adherence using a commercially available wearable device. Passively collected motion data were analyzed on the basis of the Movelet algorithm, a dictionary learning framework that builds person-specific chapters of movements from short frames of elemental activities within the movements. We adapted and extended the Movelet method to construct a within-patient prediction model that identifies medication-taking behaviors. RESULTS: Using 15 activity features recorded from wrist-worn wearable devices of 10 patients with breast cancer on endocrine therapy, we demonstrated that medication-taking behavior can be predicted in a controlled clinical environment with a median accuracy of 85%. CONCLUSION: These results in a patient-specific population are exemplar of the potential to measure real-time medication adherence using a wrist-worn commercially available wearable device.

A Mobile, Electronic Health Record-Connected Application for Managing Team Workflows in Inpatient Care.

BACKGROUND: Clinical workflows require the ability to synthesize and act on existing and emerging patient information. While offering multiple benefits, in many circumstances electronic health records (EHRs) do not adequately support these needs. OBJECTIVES: We sought to design, build, and implement an EHR-connected rounding and handoff tool with real-time data that supports care plan organization and team-based care. This article first describes our process, from ideation and development through implementation; and second, the research findings of objective use, efficacy, and efficiency, along with qualitative assessments of user experience. METHODS: Guided by user-centered design and Agile development methodologies, our interdisciplinary team designed and built Carelign as a responsive web application, accessible from any mobile or desktop device, that gathers and integrates data from a health care institution's information systems. Implementation and iterative improvements spanned January to July 2016. We assessed acceptance via usage metrics, user observations, time-motion studies, and user surveys. RESULTS: By July 2016, Carelign was implemented on 152 of 169 total inpatient services across three hospitals staffing 1,616 hospital beds. Acceptance was near-immediate: in July 2016, 3,275 average unique weekly users generated 26,981 average weekly access sessions; these metrics remained steady over the following 4 years. In 2016 and 2018 surveys, users positively rated Carelign's workflow integration, support of clinical activities, and overall impact on work life. CONCLUSION: User-focused design, multidisciplinary development teams, and rapid iteration enabled creation, adoption, and sustained use of a patient-centered digital workflow tool that supports diverse users' and teams' evolving care plan organization needs.

Assessing the utility of an IoS application in the perioperative care of spine surgery patients: the NeuroPath Pilot study.

BACKGROUND: In an attempt to improve care while decreasing costs and postoperative pain, we developed a novel IoS mobile health application, NeuroPath. The objective of this innovative app is to integrate enhanced recovery after surgery (ERAS) principles, patient education, and real-time pain and activity monitoring in a home setting with unencumbered two-way communication. METHODS: The NeuroPath application was built over 18 months, with support from Apple, Medable, the Department of Information-Technology and the Department of Neurosurgery. Target areas addressed by NeuroPath include patient prep for surgery, perioperative risk mitigation, activity monitoring, wound care, and opioid use management. These target areas are monitored through a provider app, which is downloaded to the care providers IPad Mini. The provider app permits real time viewing of wound healing (patient incision photographs), activity levels, pain levels, and narcotic usage. Participants are given a daily To-Do list, via the Care Card section of the interface. The To-Do list presents the patient with specific tasks for exercise, instructions to wash incision area, pre-operative instructions, directions for discussing medication with care team, among other patient specific recommendations. RESULTS: Of the 30 patients enrolled in the pilot study, there was a range of activity on the app. Patients with high involvement in the app logged in nearly every day from a week pre-op to >45 days post-op. Data for patients that utilized the app and uploaded regularly show trends of appropriately healing wounds, decreasing levels of pain, increasing step counts, and discontinuation of narcotics. CONCLUSIONS: This pilot study of the NeuroPath app demonstrates its potential utility for improving quality of patient care without increased costs. Participants who regularly used the app showed consistent improvement throughout the post-operative recovery period (increasing ambulation, decreasing pain and guided reduction in narcotic usage).