Effectiveness of Digital Medicines to Improve Clinical Outcomes in Patients with Uncontrolled Hypertension and Type 2 Diabetes: Prospective, Open-Label, Cluster-Randomized Pilot Clinical Trial

Background Hypertension and type 2 diabetes mellitus are major modifiable risk factors for cardiac, cerebrovascular, and kidney diseases. Reasons for poor disease control include nonadherence, lack of patient engagement, and therapeutic inertia. Objective The aim of this study was to assess the impact on clinic-measured blood pressure (BP) and glycated hemoglobin (HbA1c) using a digital medicine offering (DMO) that measures medication ingestion adherence, physical activity, and rest using digital medicines (medication taken with ingestible sensor), wearable sensor patches, and a mobile device app. Methods Participants with elevated systolic BP (SBP ≥140 mm Hg) and HbA1c (≥7%) failing antihypertensive (≥2 medications) and oral diabetes therapy were enrolled in this three-arm, 12-week, cluster-randomized study. Participants used DMO (includes digital medicines, the wearable sensor patch, and the mobile device app) for 4 or 12 weeks or received usual care based on site randomization. Providers in the DMO arms could review the DMO data via a Web portal. In all three arms, providers were instructed to make medical decisions (medication titration, adherence counseling, education, and lifestyle coaching) on all available clinical information at each visit. Primary outcome was change in SBP at week 4. Other outcomes included change in SBP and HbA1c at week 12, and low-density lipoprotein cholesterol (LDL-C) and diastolic blood pressure (DBP) at weeks 4 and 12, as well as proportion of patients at BP goal (<140/90 mm Hg) at weeks 4 and 12, medical decisions, and medication adherence patterns. Results Final analysis included 109 participants (12 sites; age: mean 58.7, SD years; female: 49.5%, 54/109; Hispanic: 45.9%, 50/109; income ≤ US $20,000: 56.9%, 62/109; and ≤ high school education: 52.3%, 57/109). The DMO groups had 80 participants (7 sites) and usual care had 29 participants (5 sites). At week 4, DMO resulted in a statistically greater SBP reduction than usual care (mean –21.8, SE 1.5 mm Hg vs mean –12.7, SE 2.8 mmHg; mean difference –9.1, 95% CI –14.0 to –3.3 mm Hg) and maintained a greater reduction at week 12. The DMO groups had greater reductions in HbA1c, DBP, and LDL-C, and a greater proportion of participants at BP goal at weeks 4 and 12 compared with usual care. The DMO groups also received more therapeutic interventions than usual care. Medication adherence was ≥80% while using the DMO. The most common adverse event was a self-limited rash at the wearable sensor site (12%, 10/82). Conclusions For patients failing hypertension and diabetes oral therapy, this DMO, which provides dose-by-dose feedback on medication ingestion adherence, can help lower BP, HbA1c, and LDL-C, and promote patient engagement and provider decision making. Trial Registration Clinicaltrials.gov NCT02827630; https://clinicaltrials.gov/show/NCT02827630 (Archived by WebCite at http://www.webcitation.org/6rL8dW2VF)

[1]  B. Scientific Thinking Outside the Pillbox A System-wide Approach to Improving Patient Medication Adherence for Chronic Disease , 2009 .

[2]  Shadi Farsaei,et al.  Adherence to statin therapy in patients with type 2 diabetes: An important dilemma , 2015, Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences.

[3]  Hayden B Bosworth,et al.  Ingredients of successful interventions to improve medication adherence. , 2013, JAMA.

[4]  N. McGlynn Thinking fast and slow. , 2014, Australian veterinary journal.

[5]  R. Reves,et al.  Early clinical experience with networked system for promoting patient self-management. , 2011, The American journal of managed care.

[6]  C. Pashos,et al.  Prevalence and economic consequences of medication adherence in diabetes: a systematic literature review. , 2006, Managed care interface.

[7]  Eric J. Topol,et al.  A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors , 2015, bioRxiv.

[8]  Helen X. Gao,et al.  Prevalence of and trends in diabetes among adults in the United States, 1988-2012. , 2016, Journal of diabetes.

[9]  Judith H Hibbard,et al.  Patients with lower activation associated with higher costs; delivery systems should know their patients' 'scores'. , 2013, Health affairs.

[10]  E. Vermeire,et al.  The concept and definition of therapeutic inertia in hypertension in primary care: a qualitative systematic review , 2014, BMC Family Practice.

[11]  D. Sherr,et al.  Diabetes self-management education for adults with type 2 diabetes mellitus: A systematic review of the effect on glycemic control. , 2016, Patient education and counseling.

[12]  Sidney C. Smith,et al.  2016 ACC Expert Consensus Decision Pathway on the Role of Non-Statin Therapies for LDL-Cholesterol Lowering in the Management of Atherosclerotic Cardiovascular Disease Risk: A Report of the American College of Cardiology Task Force on Clinical Expert Consensus Documents. , 2016, Journal of the American College of Cardiology.

[13]  Andreas Bock,et al.  Medication Adherence Assessment: High Accuracy of the New Ingestible Sensor System in Kidney Transplants , 2013, Transplantation.

[14]  S. De Geest,et al.  Adherence to Long-Term Therapies: Evidence for Action , 2003, European journal of cardiovascular nursing : journal of the Working Group on Cardiovascular Nursing of the European Society of Cardiology.

[15]  R. Collins,et al.  Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies , 2002, The Lancet.

[16]  M. Fornage,et al.  Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association , 2017, Circulation.

[17]  Patrick J O'Connor,et al.  Effect of home blood pressure telemonitoring and pharmacist management on blood pressure control: a cluster randomized clinical trial. , 2013, JAMA.

[18]  J. Hibbard,et al.  Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers. , 2004, Health services research.

[19]  Lawrence J Appel,et al.  Recommendations for blood pressure measurement in humans and experimental animals: Part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. , 2005, Hypertension.

[20]  L. Heinemann,et al.  Insulin Infusion Set: The Achilles Heel of Continuous Subcutaneous Insulin Infusion , 2012, Journal of diabetes science and technology.

[21]  F. Camacho,et al.  Predictors of medication adherence and associated health care costs in an older population with type 2 diabetes mellitus: a longitudinal cohort study. , 2003, Clinical therapeutics.

[22]  S. Taneepanichskul,et al.  A clinical study of transdermal contraceptive patch in Thai women. , 2006, Journal of the Medical Association of Thailand = Chotmaihet thangphaet.

[23]  A. Khera,et al.  Forecasting the Future of Cardiovascular Disease in the United States: A Policy Statement From the American Heart Association , 2011, Circulation.

[24]  L. DiCarlo,et al.  First Use of an Ingestible Sensor to Manage Uncontrolled Blood Pressure in Primary Practice: The UK Hypertension Registry , 2017 .

[25]  R. Hurt,et al.  Nicotine-replacement therapy with use of a transdermal nicotine patch--a randomized double-blind placebo-controlled trial. , 1990, Mayo Clinic proceedings.

[26]  R. Reves,et al.  Feasibility of an Ingestible Sensor-Based System for Monitoring Adherence to Tuberculosis Therapy , 2013, PloS one.

[27]  Emily M. Lindley,et al.  Patient-Controlled Transdermal Fentanyl Versus Intravenous Morphine Pump After Spine Surgery. , 2015, Orthopedics.

[28]  Roy H Perlis,et al.  First experience with a wireless system incorporating physiologic assessments and direct confirmation of digital tablet ingestions in ambulatory patients with schizophrenia or bipolar disorder. , 2013, The Journal of clinical psychiatry.

[29]  J. Coresh,et al.  Trends in Prevalence and Control of Diabetes in the United States, 19881994 and 19992010 , 2014, Annals of Internal Medicine.

[30]  R. E. Hoye,et al.  Is Patient Activation Associated With Future Health Outcomes and Healthcare Utilization Among Patients With Diabetes? , 2009, The Journal of ambulatory care management.

[31]  P. Godbehere,et al.  Hypertension Assessment and Management: Role for Digital Medicine , 2014, Journal of clinical hypertension.

[32]  B. Egan,et al.  Blood Pressure and Cholesterol Control in Hypertensive Hypercholesterolemic Patients: National Health and Nutrition Examination Surveys 1988–2010 , 2013, Circulation.

[33]  C. Clar,et al.  Self-monitoring of blood glucose in type 2 diabetes: systematic review. , 2010, Health technology assessment.