Objective: To describe telehealth interventions and determine their effect on medication adherence for patients with type 2 diabetes, hypertension, and/or dyslipidemia. Data Sources: PubMed/MEDLINE, EMBASE, Cochrane, CINAHL Plus, PsycINFO, Academic Search Ultimate, International Pharmaceutical Abstracts, Scopus, Web of Science, WHO Global Index Medicus, association websites, and gray literature were searched from January 1, 1998, to December 31, 2019. Study Selection and Data Extraction: Eligible studies reported eHealth, mobile health, and telehealth interventions for adult patients prescribed medications for chronic condition management (eg, type 2 diabetes, hypertension, and/or dyslipidemia). Studies were required to evaluate medication adherence outcomes (eg, medication possession ratio [MPR], proportion of days covered (PDC)]. Randomized controlled trials, cohort studies, and controlled before-and-after studies were included. Multiple reviewers independently extracted data and evaluated risk of bias. Data Synthesis: Of 8693 studies identified, 13 reported either an MPR or PDC and were included in the systematic review. The systematic review demonstrated that electronic health (eHealth) and telehealth interventions were successful at improving medication adherence, whereas mobile health interventions did not improve medication adherence. Relevance to Patient Care and Clinical Practice: This systematic review highlighted the available research and findings of studies assessing interventions to improve medication nonadherence among patients with type 2 diabetes, hypertension, and/or dyslipidemia. The evaluated findings lend support to the need for targeted medication adherence interventions based on patient population and practice settings. Conclusions: Telehealth modalities include telephonic outreach and specialized tools designed to increase health literacy. eHealth and telehealth medication adherence interventions were associated with improved MPR and/or PDC rates.

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Deprescribing is the intentional dose reduction or discontinuation of a medication. The development of deprescribing interventions should take into consideration important organizational, interprofessional, and patient‐specific barriers that can be further complicated by the presence of multiple prescribers involved in a patient's care. Patients who receive care from an increasing number of prescribers may experience disruptions in the timely transfer of relevant healthcare information, increasing the risk of exposure to drug–drug interactions and other medication‐related problems. Furthermore, the fragmentation of healthcare information across health systems can contribute to the refilling of discontinued medications, reducing the effectiveness of deprescribing interventions. Thus, deprescribing interventions must carefully consider the unique characteristics of patients and their prescribers to ensure interventions are successfully implemented. In this special article, an international working group of physicians, pharmacists, nurses, epidemiologists, and researchers from the United States Deprescribing Research Network (USDeN) developed a socioecological model to understand how multiple prescribers may influence the implementation of a deprescribing intervention at the individual, interpersonal, organizational, and societal level. This manuscript also includes a description of the concept of multiple prescribers and outlines a research agenda for future investigations to consider. The information contained in this manuscript should be used as a framework for future deprescribing interventions to carefully consider how multiple prescribers can influence the successful implementation of the service and ensure the intervention is as effective as possible.

Background: Potentially inappropriately prescribed medications (PIPMs) among patients with chronic kidney disease (CKD) may vary among clinical settings. Rates of PIPM are unknown among Medicare-enrolled Medication Therapy Management (MTM) eligible patients. Objectives: Determine prevalence of PIPM among patients with CKD and evaluate characteristics of patients and providers associated with PIPM. Design: An observational cross-sectional investigation of a Medicare insurance plan for the year 2018. Patients: Medicare-enrolled MTM eligible patients with stage 3–5 CKD. Main Measures: PIPM was identified utilizing a tertiary database. Logistic regression assessed relationship between patient characteristics and PIPM. Key Results: Investigation included 3624 CKD patients: 2856 (79%), 548 (15%), and 220 (6%) patients with stage 3, 4, and 5 CKD, respectively. Among patients with stage 3, stage 4, and stage 5 CKD, 618, 430, and 151 were with at least one PIPM, respectively. Logistic regression revealed patients with stage 4 or 5 CKD had 7–14 times the odds of having a PIPM in comparison to patients with stage 3 disease (p < 0.001). Regression also found PIPM was associated with increasing number of years qualified for MTM (odds ratio (OR) 1.46–1.74, p ≤ 0.005), female gender (OR 1.25, p = 0.008), and increasing polypharmacy (OR 1.30–1.57, p ≤ 0.01). Approximately 14% of all medications (2879/21093) were considered PIPM. Majority of PIPMs (62%) were prescribed by physician primary care providers (PCPs). Medications with the greatest percentage of PIPM were spironolactone, canagliflozin, sitagliptin, levetiracetam, alendronate, pregabalin, pravastatin, fenofibrate, metformin, gabapentin, famotidine, celecoxib, naproxen, meloxicam, rosuvastatin, diclofenac, and ibuprofen. Conclusion: Over one-third of Medicare MTM eligible patients with CKD presented with at least one PIPM. Worsening renal function, length of MTM eligibility, female gender, and polypharmacy were associated with having PIPM. Majority of PIPMs were prescribed by PCPs. Clinical decision support tools may be considered to potentially reduce PIPM among Medicare MTM–enrolled patients with CKD.