Blood pressure outcomes at 18 months in primary care patients prescribed remote physiological monitoring for hypertension: a prospective cohort study.

This pragmatic matched cohort study using EHR data extended the follow up to 18 months for BP outcomes comparing individuals prescribed remote patient monitoring (n = 288) and temporally-matched controls (n = 1152) from six primary care practices. After 18 months, the RPM-prescribed cohort had greater BP control < 140/90 mm Hg (RPM cohort: 71.5%, control cohort: 51.9%, p < 0.001) and lower systolic BP (131.6 versus 136.0 mm Hg, p = 0.004) using office and home measurements. BP control at 18 months assessed by office measurements only was also higher in the RPM group (62.2% versus 51.9%, p = 0.004).

Effect of Home Blood Pressure Monitoring via a Smartphone Hypertension Coaching Application or Tracking Application on Adults With Uncontrolled Hypertension: A Randomized Clinical Trial.

Importance: Mobile applications (apps) may help improve hypertension self-management. Objective: To investigate the effect of an artificial intelligence smartphone coaching app to promote home monitoring and hypertension-related behaviors on systolic blood pressure level compared with a blood pressure tracking app. Design, Setting, and Participants: This was a 2-group, open, randomized clinical trial. Participants with uncontrolled hypertension were recruited in 2016 and 2017 and were followed up for 6 months. Data analysis was performed from April 2019 to December 2019. Interventions: Intervention group participants received a smartphone coaching app to promote home monitoring and behavioral changes associated with hypertension self-management plus a home blood pressure monitor. Control participants received a blood pressure tracking app plus a home blood pressure monitor. Main Outcomes and Measures: The primary study outcome was systolic blood pressure at 6 months. Secondary outcomes included self-reported antihypertensive medication adherence, home monitoring and self-management practices, measures of self-efficacy associated with blood pressure, weight, and self-reported health behaviors. Results: There were 333 participants randomized, and 297 completed the follow-up assessment. Among the participants who completed the study, the mean (SD) age was 58.9 (12.8) years, 182 (61.3%) were women, and 103 (34.7%) were black. Baseline mean (SD) systolic blood pressure was 140.6 (12.2) mm Hg among intervention participants and 141.8 (13.4) mm Hg among control participants. After 6 months, the corresponding mean (SD) systolic blood pressures were 132.3 (15.0) mm Hg and 135.0 (13.9) mm Hg, with a between-group adjusted difference of -2.0 mm Hg (95% CI, -4.9 mm Hg to 0.8 mm Hg; P = .16). At 6 months, self-confidence in controlling blood pressure was greater in the intervention group (0.36 point on a 5-point scale; 95% CI, 0.18 point to 0.54 point; P < .001). There were no significant differences between the 2 groups in other secondary outcomes. The adjusted difference in self-reported physical activity was 26.7 minutes per week (95% CI, -5.4 minutes per week to 58.8 minutes per week; P = .10). Subgroup analysis raised the possibility that intervention effects differed by age. Conclusions and Relevance: Among individuals with uncontrolled hypertension, those randomized to a smartphone coaching app plus home monitor had similar systolic blood pressure compared with those who received a blood pressure tracking app plus home monitor. Given the direction of the difference in systolic blood pressure between groups and the possibility for differences in treatment effects across subgroups, future studies are warranted. Trial Registration: ClinicalTrials.gov Identifier: NCT03288142.

Outreach to Promote Management of Cardiovascular Risk in Primary Care Among Patients With Rheumatoid Arthritis Seen in Rheumatology Practice.

OBJECTIVE: Rheumatoid arthritis (RA) confers a 1.5- to 2.0-fold increased risk of cardiovascular disease (CVD). A prior multifaceted quality improvement approach to improving CVD preventive care increased CVD risk factor assessments, but there was no significant effect on the management of risk factors. We tested the impact of adding a proactive outreach strategy promoting primary care treatment of CVD risk factors among patients with RA through their rheumatology practice. METHODS: Through electronic health record searches, we identified patients with RA who were potential candidates for hypertension treatment initiation or intensification, statin therapy, or a smoking-cessation intervention. A nonclinician care manager contacted patients by phone and mail on behalf of the rheumatologists, provided information about the identified risk factor(s), recommend follow-up with primary care physicians (PCPs), sent correspondence to PCPs, and followed up with patients to see what actions had been taken. We measured preventive cardiology quality indicators and compared preintervention and intervention time periods using interrupted time series methods. RESULTS: During the 6-month intervention period, the proportion of patients prescribed at least moderate-intensity statin treatment for primary prevention rose from 18.4% to 23.8%. The rate of increase was 1.06% greater per month than during the preceding period (P < 0.001). Rates of increase in hypertension diagnosis and control improved more rapidly during this phase (P < 0.001 for each) and reversed preceding negative trends. CONCLUSION: Implementing proactive nonclinician outreach to encourage primary care-based treatment of CVD risk factors was associated with increases in statin prescribing and in hypertension diagnosis and control. Smoking was not affected.

Using Electronic Health Records to Measure Quality Improvement Efforts: Findings from a Large Practice Facilitation Initiative.

BACKGROUND: Federal incentives for electronic health record (EHR) use typically require quality measure reporting over calendar year or 90-day periods. However, required reporting periods may not align with time frames of real-world quality improvement (QI) efforts. This study described primary care practices' ability to obtain measures with reporting periods aligning with a large QI initiative. METHODS: Researchers conducted a substudy of a randomized trial testing practice facilitation strategies for preventive cardiovascular care. Three quality measures (aspirin for ischemic vascular disease; blood pressure control for hypertension; smoking screening/cessation) were collected quarterly over one year. The primary outcome was a binary indicator of whether a practice facilitator obtained all three measures with "rolling 12-month" reporting periods (that is, the year preceding each study quarter). RESULTS: The study included 107 practices, 63 (58.9%) of which met the primary outcome of obtaining all measures with rolling 12-month reporting periods. Smaller practices were less likely to meet the primary outcome (p < 0.001). Practices used 11 different EHRs, 3 of which were unable to consistently produce rolling 12-month measures; at 33 practices (30.8%) using these 3 EHRs, facilitators met a secondary outcome of obtaining prior calendar year and rolling 3-month measures. Facilitators reported barriers to data collection such as practices lacking optional EHR features, and EHRs' inability to produce reporting periods across two calendar years. CONCLUSION: EHR vendors' compliance with federal reporting requirements is not necessarily sufficient to support real-world QI work. Improvements are needed in the flexibility and usability of EHRs' quality measurement functions, particularly for smaller practices.

Changes in Care After Implementing a Multifaceted Intervention to Improve Preventive Cardiology Practice in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) increases cardiovascular disease (CVD) risk. However, CVD risk factor identification and treatment is often inadequate. The authors implemented a multifaceted rheumatology practice intervention to improve CVD risk factor measurement, assessment, and management. The intervention included clinician education, point-of-care decision support, feedback, and care management. The authors measured quality indicators from electronic health records and assessed impact with interrupted time series. Following the intervention, more RA patients had all major CVD risk factors assessed (53% vs 72.2%), and the rate of increase was greater during the intervention period than baseline (difference of 0.74% per month, P = .0016). Moderate- or high-intensity statin prescribing increased (21.6% to 28.2%), but the rate of change was not different from baseline. Several other quality measures did not increase. Although CVD risk factor assessment improved, the intervention did not affect risk factor management and control. Other strategies are needed to optimize CVD prevention in RA.

Design of a randomized controlled trial comparing a mobile phone-based hypertension health coaching application to home blood pressure monitoring alone: The Smart Hypertension Control Study.

BACKGROUND: Hypertension is a major cause of morbidity and mortality but frequently remains uncontrolled. A smartphone application that provides coaching regarding home blood pressure monitoring and other aspects of hypertension self-care and related behavior change may be a scalable way to help manage hypertension. METHODS/DESIGN: The Smart Hypertension Control Study is a prospective, randomized controlled trial to assess the effects of a hypertension personal control program (HPCP), which consists of an automated artificial intelligence smartphone application that provides individualized support and coaching to promote home monitoring and healthy behavior changes related to hypertension self-management. Enrolled adults with uncontrolled hypertension will be randomized in a 1:1 fashion to the HPCP with home blood pressure monitoring or to home monitoring alone. We plan to enroll 350 participants, with a target of 300 participants with complete six-month follow-up data. The primary study outcome will be systolic blood pressure at six months. Additional outcomes include measures of antihypertensive medication adherence, home blood pressure monitoring practices, self-management practices, weight, and self-reported health behaviors. CONCLUSION: The Smart Hypertension Control Study will evaluate blood pressure and hypertension self-management behavior outcomes in participants with uncontrolled hypertension exposed to a smartphone-based hypertension health coaching application in addition to home blood pressure monitoring compared to those exposed to home blood pressure monitoring alone.