Despite growing interest in remote patient monitoring, limited evidence exists to substantiate claims of its ability to improve outcomes. Our aim was to evaluate randomized controlled trials (RCTs) that assess the effects of using wearable biosensors (e.g. activity trackers) for remote patient monitoring on clinical outcomes. We expanded upon prior reviews by assessing effectiveness across indications and presenting quantitative summary data. We searched for articles from January 2000 to October 2016 in PubMed, reviewed 4,348 titles, selected 777 for abstract review, and 64 for full text review. A total of 27 RCTs from 13 different countries focused on a range of clinical outcomes and were retained for final analysis; of these, we identified 16 high-quality studies. We estimated a difference-in-differences random effects meta-analysis on select outcomes. We weighted the studies by sample size and used 95% confidence intervals (CI) around point estimates. Difference-in-difference point estimation revealed no statistically significant impact of remote patient monitoring on any of six reported clinical outcomes, including body mass index (−0.73; 95% CI: −1.84, 0.38), weight (−1.29; −3.06, 0.48), waist circumference (−2.41; −5.16, 0.34), body fat percentage (0.11; −1.56, 1.34), systolic blood pressure (−2.62; −5.31, 0.06), and diastolic blood pressure (−0.99; −2.73, 0.74). Studies were highly heterogeneous in their design, device type, and outcomes. Interventions based on health behavior models and personalized coaching were most successful. We found substantial gaps in the evidence base that should be considered before implementation of remote patient monitoring in the clinical setting.

Objective The number of therapies for axial spondyloarthritis (axSpA) is increasing. Thus, it has become more challenging for patients and physicians to navigate the risk‐benefit profiles of the various treatment options. In this study, we used conjoint analysis—a form of trade‐off analysis that elucidates how people make complex decisions by balancing competing factors—to examine patient decision‐making surrounding medication options for axSpA. Methods We conducted an adaptive choice‐based conjoint analysis survey for patients with axSpA to assess the relative importance of medication attributes (eg, chance of symptom improvement, risk of side effects, route of administration, etc) in their decision‐making. We also performed logistic regression to explore whether patient demographics and disease characteristics predicted decision‐making. Results Overall, 397 patients with axSpA completed the conjoint analysis survey. Patients prioritized medication efficacy (importance score 26.8%), cost (26.3%), and route of administration (13.9%) as most important in their decision‐making. These were followed by risk of lymphoma (9.5%), dosing frequency (7.2%), risk of serious infection (6.0%), tolerability of side effects (5.3%), and clinic visit and laboratory test frequency (4.8%). In regression analyses, there were few significant associations between patients’ treatment preferences and sociodemographic and axSpA characteristics. Conclusions Treatment decision‐making in axSpA is highly individualized, and demographics and baseline disease characteristics are poor predictors of individual preferences. This calls for the development of online shared decision‐making tools for patients and providers, with the goal of selecting a treatment that is consistent with patients’ preferences.

Objective Given the changing political and social climate around opioids, we examined how clinicians in the outpatient setting made decisions about managing opioid prescriptions for new patients already on long-term opioid therapy. Methods We conducted in-depth interviews with 32 clinicians in Southern California who prescribed opioid medications in the outpatient setting for chronic pain. The study design, interview guides, and coding for this qualitative study were guided by constructivist grounded theory methodology. Results We identified three approaches to assuming a new patient’s opioid prescriptions. Staunch Opposers, mostly clinicians with specialized training in pain medicine, were averse to continuing opioid prescriptions for new patients and often screened outpatients seeking opioids. Cautious and Conflicted Prescribers were wary about prescribing opioids but were willing to refill prescriptions if they perceived the patient as trustworthy and the medication fell within their comfort zone. Clinicians in the first two groups felt resentful about other clinicians “dumping” patients on opioids on them. Rapport Builders, mostly primary care physicians, were the most willing to assume opioid prescriptions and were strategic in their approach to transitioning patients to safer doses. Conclusions Clinicians with the most training in pain management were the least willing to assume responsibility for opioid prescriptions for patients already on long-term opioid therapy. In contrast, primary care clinicians were the most willing to assume this responsibility. However, primary care clinicians face barriers to providing high-quality care for patients with complex pain conditions, such as short visit times and less specialized training.

BackgroundPatients using opioids to treat chronic non-cancer pain often experience side effects that may affect health-related quality of life (HRQOL). These side effects include opioid-induced constipation (OIC), sedation, dizziness, and nausea. OIC can significantly affect HRQOL for patients on a daily basis. However, it is not well understood whether patients and clinicians view OIC management similarly.AimsIn this study, we sought to elucidate the decision-making process around managing OIC by assessing patient and provider treatment preferences, experiences, and communication regarding this condition.MethodsWe conducted semi-structured interviews with 33 clinicians, and held three focus groups with patients who were currently using or had used opioids for chronic non-cancer pain. We then analyzed transcribed interviews using descriptive qualitative methods based on grounded theory methodology.ResultsClinicians recognized OIC as a concern but prioritized pain management over constipation. They focused on medication-based treatments for OIC, but also recommended lifestyle changes (e.g., diet) and reducing opioids to relieve symptoms. Patients reported using over-the-counter treatments, but the majority focused on diet-related constipation management. Patients reported not receiving adequate information from clinicians about OIC and relevant treatments. Cost of treatment was a major concern for both patients and clinicians.ConclusionsAssessing experiences with and preferences for OIC treatment, including cost, ease of access, and side effects, could improve patient-provider communication and HRQOL. Quality improvement efforts can target uncovered misalignments between patients and clinicians to improve communication about opioid medication adverse effects and relevant treatment options, which may help improve quality of life for patients with chronic pain.

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In decision analysis of a hypothetical cohort of patients who met Rome IV criteria for IBS-D, we identified cost and accuracy thresholds that can guide investigators and payers as they develop, validate, price, and/or reimburse IBS-D biomarker tests for use in everyday clinical practice.

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