Disparities in Hypertension Control Across and Within Three Health Systems Participating in a Data-Sharing Collaborative.

We aimed to standardize data collection from 3 health systems (HS1, HS2, HS3) participating in the San Francisco Bay Collaborative Research Network, and compare rates and predictors of uncontrolled blood pressure among hypertensive adults to identify opportunities for regional collaboration in quality improvement. Retrospective cohort study using deidentified electronic health record data from all primary care patients with at least 1 visit in a 2-year period, using standard data definitions in a common data repository. Primary outcome was uncontrolled blood pressure at the most recent primary care visit. Of 169,793 adults aged 18 to 85 years, 53,133 (31.3%) had a diagnosis of hypertension. Of these, 18,751 (35%) had uncontrolled blood pressure at their last visit, with the proportion varying by system (29%, HS1; 31%, HS2; and 44%, HS3) and by clinical site within each system. In multivariate analyses, differences between health systems persisted, with HS2 and HS3 patients having a 1.15 times (95% CI, 1.11 to 1.19) and 1.46 times (95% CI, 1.42 to 1.50) greater relative risk of uncontrolled blood pressure compared with HS1. Across health systems, hypertensive patients were more likely to have uncontrolled blood pressure if they were uninsured, African Americans, current smokers, obese, or had fewer than 2 primary care visits during the 2-year measurement period. After controlling for standard individual predictors of hypertension control, significant and substantial differences in hypertension control persisted between health systems, possibly due to local quality improvement programs among other factors. There may be opportunities to share best practices and address common disparities across health systems

Safety-net institutions in the US grapple with new cholesterol treatment guidelines: a qualitative analysis from the PHoENIX Network

Valy Fontil,1,2 Courtney R Lyles,1,2 Dean Schillinger,1,2 Margaret A Handley,1–3 Sara Ackerman,4 Gato Gourley,1,2 Kirsten Bibbins-Domingo,1–3 Urmimala Sarkar1,2 1UCSF Center for Vulnerable Populations at San Francisco General Hospital, University of California San Francisco, San Francisco, CA, USA; 2Division of General Internal Medicine, University of California San Francisco, San Francisco, CA, USA; 3Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA; 4Department of Social and Behavioral Sciences, University of California San Francisco School of Nursing, San Francisco, CA, USA Background: Clinical performance measures, such as for cholesterol control targets, have played an integral role in assessing the value of care and translating evidence into clinical practice. New guidelines often require development of corresponding performance metrics and systems changes that can be especially challenging in safety-net health care institutions. Understanding how public health care institutions respond to changing practice guidelines may be critical to informing how we adopt evolving evidence in clinical settings that care for the most vulnerable populations. Methods: We conducted six focus groups with representatives of California’s 21 public hospital systems to examine their reactions to the recent 2013 cholesterol treatment guideline. Results: Participants reported a sense of confusion and lack of direction in implementing the new guideline. They cited organizational and data infrastructural inadequacies that made implementation of the new guidelines impractical in their clinical settings. Conclusion: Adopting new performance measures to align with evolving cholesterol guidelines is a complex process that may work at odds with existing quality improvement priorities. Current efforts to translate evidence into practice may rely too much on performance measures and not enough on building capacity or support for innovative efforts to meet the goals of guidelines. Keywords: pay-for-performance, value-based payment, quality improvemen

Disruption in Blood Pressure Control With the COVID-19 Pandemic: The PCORnet Blood Pressure Control Laboratory

ObjectiveTo explore trends in blood pressure (BP) control before and during the COVID-19 pandemic.Patients and methodsHealth systems participating in the National Patient-Centered Clinical Research Network (PCORnet) Blood Pressure Control Laboratory Surveillance System responded to data queries, producing 9 BP control metrics. Averages of the BP control metrics (weighted by numbers of observations in each health system) were calculated and compared between two 1-year measurement periods (January 1, 2019, through December 31, 2019, and January 1, 2020, through December 31, 2020).ResultsAmong 1,770,547 hypertensive persons in 2019, BP control to <140/<90 mm Hg varied across 24 health systems (range, 46%-74%). Reduced BP control occurred in most health systems with onset of the COVID-19 pandemic; the weighted average BP control was 60.5% in 2019 and 53.3% in 2020. Reductions were also evident for BP control to <130/<80 mm Hg (29.9% in 2019 and 25.4% in 2020) and improvement in BP (reduction of 10 mm Hg in systolic BP or achievement of systolic BP <140 mm Hg; 29.7% in 2019 and 23.8% in 2020). Two BP control process metrics exhibited pandemic-associated disruption: repeat visit in 4 weeks after a visit with uncontrolled hypertension (36.7% in 2019 and 31.7% in 2020) and prescription of fixed-dose combination medications among those with 2 or more drug classes (24.6% in 2019 and 21.5% in 2020).ConclusionBP control decreased substantially during the COVID-19 pandemic, with a corresponding reduction in follow-up health care visits among persons with uncontrolled hypertension. It is unclear whether the observed decline in BP control during the pandemic will contribute to future cardiovascular events

Simulating Strategies for Improving Control of Hypertension Among Patients with Usual Source of Care in the United States: The Blood Pressure Control Model

BACKGROUND: Only half of hypertensive adults achieve blood pressure (BP) control in the United States, and it is unclear how BP control rates may be improved most effectively and efficiently at the population level. OBJECTIVE: We sought to compare the potential effects of system-wide isolated improvements in medication adherence, visit frequency, and higher physician prescription rate on achieving BP control at 52 weeks. DESIGN: We developed a Markov microsimulation model of patient-level, physician-level, and system-level processes involved in controlling hypertension with medications. The model is informed by data from national surveys, cohort studies and trials, and was validated against two multicenter clinical trials (ALLHAT and VALUE). SUBJECTS: We studied a simulated, nationally representative cohort of patients with diagnosed but uncontrolled hypertension with a usual source of care. INTERVENTIONS: We simulated a base case and improvements of 10 and 50 %, and an ideal scenario for three modifiable parameters: visit frequency, treatment intensification, and medication adherence. Ideal scenarios were defined as 100 % for treatment intensification and adherence, and return visits occurring within 4 weeks of an elevated office systolic BP. MAIN OUTCOME: BP control at 52 weeks of follow-up was examined. RESULTS: Among 25,000 hypothetical adult patients with uncontrolled hypertension (systolic BP ≥ 140 mmHg), only 18 % achieved BP control after 52 weeks using base-case assumptions. With 10/50 %/idealized enhancements in each isolated parameter, enhanced treatment intensification achieved the greatest BP control (19/23/71 %), compared with enhanced visit frequency (19/21/35 %) and medication adherence (19/23/26 %). When all three processes were idealized, the model predicted a BP control rate of 95 % at 52 weeks. CONCLUSION: Substantial improvements in BP control can only be achieved through major improvements in processes of care. Healthcare systems may achieve greater success by increasing the frequency of clinical encounters and improving physicians’ prescribing behavior than by attempting to improve patient adherence to medications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11606-015-3231-8) contains supplementary material, which is available to authorized users