Faculty Bibliography

BACKGROUND:Diagnostic error in ambulatory care, a frequent cause of preventable harm, may be mitigated using the collective intelligence of multiple clinicians. The National Academy of Medicine has identified enhanced clinician collaboration and digital tools as a means to improve the diagnostic process. OBJECTIVE:This study aims to assess the efficacy of a collective intelligence output to improve diagnostic confidence and accuracy in ambulatory care cases (from primary care and urgent care clinic visits) with diagnostic uncertainty. METHODS:This is a pragmatic randomized controlled trial of using collective intelligence in cases with diagnostic uncertainty from clinicians at primary care and urgent care clinics in 2 health care systems in San Francisco. Real-life cases, identified for having an element of diagnostic uncertainty, will be entered into a collective intelligence digital platform to acquire collective intelligence from at least 5 clinician contributors on the platform. Cases will be randomized to an intervention group (where clinicians will view the collective intelligence output) or control (where clinicians will not view the collective intelligence output). Clinicians will complete a postvisit questionnaire that assesses their diagnostic confidence for each case; in the intervention cases, clinicians will complete the questionnaire after reviewing the collective intelligence output for the case. Using logistic regression accounting for clinician clustering, we will compare the primary outcome of diagnostic confidence and the secondary outcome of time with diagnosis (the time it takes for a clinician to reach a diagnosis), for intervention versus control cases. We will also assess the usability and satisfaction with the digital tool using measures adapted from the Technology Acceptance Model and Net Promoter Score. RESULTS:We have recruited 32 out of our recruitment goal of 33 participants. This study is funded until May 2020 and is approved by the University of California San Francisco Institutional Review Board until January 2020. We have completed data collection as of June 2019 and will complete our proposed analysis by December 2019. CONCLUSIONS:This study will determine if the use of a digital platform for collective intelligence is acceptable, useful, and efficacious in improving diagnostic confidence and accuracy in outpatient cases with diagnostic uncertainty. If shown to be valuable in improving clinicians' diagnostic process, this type of digital tool may be one of the first innovations used for reducing diagnostic errors in outpatient care. The findings of this study may provide a path forward for improving the diagnostic process. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:DERR1-10.2196/13151.

BACKGROUND:The Centers for Disease Control and Prevention's Million Hearts initiative includes an ambitious ≥80% blood pressure control goal in US adults with hypertension by 2022. We used the validated Blood Pressure Control Model to quantify changes in clinic-based hypertension management processes needed to attain ≥80% blood pressure control. METHODS AND RESULTS:The Blood Pressure Control Model simulates patient blood pressures weekly using 3 key modifiable hypertension management processes: office visit frequency, clinician treatment intensification given uncontrolled blood pressure, and continued antihypertensive medication use (medication adherence rate). We compared blood pressure control rates (using the Seventh Joint National Committee on hypertension targets) achieved over 4 years between usual care and the best-observed values for management processes identified from the literature (1-week return visit interval, 20%-44% intensification rate, and 76% adherence rate). We determined the management process values needed to achieve ≥80% blood pressure control in US adults. In adults with uncontrolled blood pressure, usual care achieved 45.6% control (95% uncertainty interval, 39.6%-52.5%) and literature-based best-observed values achieved 79.7% control (95% uncertainty interval, 79.3%-80.1%) over 4 years. Increasing treatment intensification rates to 62% of office visits with an uncontrolled blood pressure resulted in ≥80% blood pressure control, even when the return visit interval and adherence remained at usual care values. Improving to best-observed values for all 3 management processes would achieve 78.1% blood pressure control in the overall US population with hypertension, approaching the ≥80% Million Hearts 2022 goal. CONCLUSIONS:Achieving the Million Hearts blood pressure control goal by 2022 will require simultaneously increasing visit frequency, overcoming therapeutic inertia, and improving patient medication adherence. As the relative importance of each of these 3 processes will depend on local characteristics, simulation models like the Blood Pressure Control Model can help local healthcare systems tailor strategies to reach local and national benchmarks.

OBJECTIVES/OBJECTIVE:Usable tools to support individual primary care clinicians in their diagnostic processes could help to reduce preventable harm from diagnostic errors. We conducted a formative study with primary care providers to identify key requisites to optimize the acceptability of 1 online collective intelligence platform (Human Diagnosis Project; Human Dx). MATERIALS AND METHODS/METHODS:We conducted semistructured interviews with practicing primary care clinicians in a sample of the US community-based clinics to examine the acceptability and early usability of the collective intelligence online platform using standardized clinical cases and real-world clinical cases from the participants' own practice. We used an integrated inductive-deductive qualitative analysis approach to analyze the interview transcripts. RESULTS AND DISCUSSION/CONCLUSIONS:Perceived usefulness, perceived accuracy, quality assurance, trust, and ease of use emerged as essential domains of acceptability required for providers to use a collective intelligence tool in clinical practice. Participants conveyed that the collective opinion should: (1) contribute to their clinical reasoning, (2) boost their confidence, (3) be generated in a timely manner, and (4) be relevant to their clinical settings and use cases. Trust in the technology platform and the clinical accuracy of its collective intelligence output emerged as an incontrovertible requirement for user acceptance and engagement. CONCLUSION/CONCLUSIONS:We documented key requisites to building a collective intelligence technology platform that is trustworthy, useful, and acceptable to target end users for assistance in the diagnostic process. These key lessons may be applicable to other provider-facing decision support platforms.

BACKGROUND:Detection of chronic kidney disease (CKD) with urine albumin-to-creatinine ratio (UACR) among patients with hypertension (HTN) provides an opportunity for early treatment, potentially mitigating risk of CKD progression and cardiovascular complications. Differences in UACR testing patterns among racial/ethnic populations at risk for CKD could contribute to known disparities in CKD complications. METHODS:We examined the prevalence of UACR testing among low-income adult primary care patients with HTN, defined by a new administrative code for HTN or 2 clinic blood pressures >140/90 mm Hg between January 1, 2014, and January 1, 2017, in one public health-care delivery system with a high prevalence of end-stage kidney disease among race/ethnic minorities. Logistic regression was used to identify odds of UACR testing within 1 year of a HTN diagnosis, overall, and by racial/ethnic subgroup, adjusted for demographic factors, estimated glomerular filtration rate, and HTN severity. Models were also stratified by diabetes status. RESULTS:The cohort (n = 16,414) was racially/ethnically diverse (16% White, 21% Black, 34% Asian, 19% Hispanic, and 10% other) and 51% female. Only 35% of patients had UACR testing within 1 year of a HTN diagnosis. Among individuals without diabetes, odds of UACR testing were higher among Asians, Blacks, and Other subgroups compared to Whites (adjusted OR [aOR] 1.19; 95% CI 1.00-1.42 for Blacks; aOR 1.33; 1.13-1.56 for Asians; aOR 1.30; 1.04-1.60 for Other) but were not significantly different between Hispanics and Whites (aOR 1.17; 0.97-1.39). Among individuals with diabetes, only Asians had higher odds of UACR testing compared to Whites (aOR 1.35; 1.12-1.63). CONCLUSIONS:Prevalence of UACR testing among low-income patients with HTN is low in one public health-care delivery system, with higher odds of UACR testing among racial/ethnic minority subgroups compared to Whites without diabetes and similar odds among those with diabetes. If generalizable, less albuminuria testing may not explain higher prevalence of kidney failure in racial/ethnic minorities.

INTRODUCTION: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. METHODS: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. RESULTS: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. CONCLUSIONS: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.

BACKGROUND:Nearly half of Americans with diagnosed hypertension have uncontrolled blood pressure (BP) while some integrated healthcare systems, such as Kaiser Permanente Northern California, have achieved control rates upwards 90%. METHODS AND RESULTS:<0.01). CONCLUSIONS:Evidence-based system approaches to improving BP control can be implemented in safety-net settings and could play a pivotal role in achieving improved population BP control and reducing hypertension disparities.

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/CONCLUSIONS: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.

OBJECTIVE:To examine adherence to guideline-concordant hypertension treatment practices at community health centers (CHCs) compared with private physicians' offices. DATA SOURCES/STUDY SETTING/METHODS:National Ambulatory Medical Care Survey from 2006 to 2010. STUDY DESIGN/METHODS:We examined four guideline-concordant treatment practices: initiation of a new medication for uncontrolled hypertension, use of fixed-dose combination drugs for patients on multiple antihypertensive medications, use of thiazide diuretics among patients with uncontrolled hypertension on ≥3 antihypertensive medications, and use of aldosterone antagonist for resistant hypertension, comparing use at CHC with private physicians' offices overall and by payer group. DATA COLLECTION/EXTRACTION METHODS/METHODS:We identified visits of nonpregnant adults with hypertension at CHCs and private physicians' offices. PRINCIPAL FINDINGS/RESULTS:Medicaid patients at CHCs were as likely as privately insured individuals to receive a new medication for uncontrolled hypertension (AOR 1.0, 95 percent CI: 0.6-1.9), whereas Medicaid patients at private physicians' offices were less likely to receive a new medication (AOR 0.3, 95 percent CI: 0.1-0.6). Use of fixed-dose combination drugs was lower at CHCs (AOR 0.6, 95 percent CI: 0.4-0.9). Thiazide use for patients was similar in both settings (AOR 0.8, 95 percent CI: 0.4-1.7). Use of aldosterone antagonists was too rare (2.1 percent at CHCs and 1.5 percent at private clinics) to allow for statistically reliable comparisons. CONCLUSIONS:Increasing physician use of fixed-dose combination drugs may be particularly helpful in improving hypertension control at CHCs where there are higher rates of uncontrolled hypertension.

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/METHODS: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/METHODS:We studied a simulated, nationally representative cohort of patients with diagnosed but uncontrolled hypertension with a usual source of care. INTERVENTIONS/METHODS: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/RESULTS: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/CONCLUSIONS: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.