Application of a Tool to Identify Undiagnosed Hypertension - United States, 2016

Current Practices and Attitudes of Community Health Centers Toward the Use of Algorithmic Logic to Identify Patients with Undiagnosed Hypertension

Treating patients with uncontrolled hypertension is a powerful intervention for reducing the risk of heart attack and stroke. Leveraging health information technology to identify patients with undiagnosed hypertension using algorithmic logic can be an effective approach for reaching hypertensive patients who may otherwise be overlooked. Despite evidence that this strategy can support favorable cardiovascular health outcomes in the safety-net healthcare setting, little is known about its implementation outside of targeted practice and research environments. In 2021-2022, Community Clinic Association of Los Angeles County and the Los Angeles County Department of Public Health collaborated on a mixed methods, organizational assessment of community health centers to better understand their practices and attitudes toward the use of algorithmic logic to identify patients with undiagnosed hypertension. Results from the assessment suggest that awareness and use of this approach are limited; numerous challenges are associated with its adoption and implementation.

Contactless and Calibration-Free Blood Pressure and Pulse Rate Monitor for Screening and Monitoring of Hypertension: Cross-Sectional Validation Study

BACKGROUND

The key to reducing the immense morbidity and mortality burdens of cardiovascular diseases is to help people keep their blood pressure (BP) at safe levels. This requires that more people with hypertension be identified, diagnosed, and given tools to lower their BP. BP monitors are critical to hypertension diagnosis and management. However, there are characteristics of conventional BP monitors (oscillometric cuff sphygmomanometers) that hinder rapid and effective hypertension diagnosis and management. Calibration-free, software-only BP monitors that operate on ubiquitous mobile devices can enable on-demand BP monitoring, overcoming the hardware barriers of conventional BP monitors.

OBJECTIVE

This study aims to investigate the accuracy of a contactless BP monitor software app for classifying the full range of clinically relevant BPs as hypertensive or nonhypertensive and to evaluate its accuracy for measuring the pulse rate (PR) and BP of people with BPs relevant to stage-1 hypertension.

METHODS

The software app, known commercially as Lifelight, was investigated following the data collection and data analysis methodology outlined in International Organization for Standardization (ISO) 81060-2:2018/AMD 1:2020 "Non-invasive Sphygmomanometers-Part 2: Clinical investigation of automated measurement type." This validation study was conducted by the independent laboratory Element Materials Technology Boulder (formerly Clinimark). The study generated data from 85 people aged 18-85 years with a wide-ranging distribution of BPs specified in ISO 81060-2:2018/AMD 1:2020. At least 20% were required to have Fitzpatrick scale skin tones of 5 or 6 (ie, dark skin tones). The accuracy of the app's BP measurements was assessed by comparing its BP measurements with measurements made by dual-observer manual auscultation using the same-arm sequential method specified in ISO 81060-2:2018/AMD 1:2020. The accuracy of the app's PR measurements was assessed by comparing its measurements with concurrent electroencephalography-derived heart rate values.

RESULTS

The app measured PR with an accuracy root-mean-square of 1.3 beats per minute and mean absolute error of 1.1 (SD 0.8) beats per minute. The sensitivity and specificity with which it determined that BPs exceeded the in-clinic systolic threshold for hypertension diagnosis were 70.1% and 71.7%, respectively. These rates are consistent with those reported for conventional BP monitors in a literature review by The National Institute for Health and Care Excellence. The app's mean error for measuring BP in the range of normotension and stage-1 hypertension (ie, 65/85, 76% of participants) was 6.5 (SD 12.9) mm Hg for systolic BP and 0.4 (SD 10.6) mm Hg for diastolic BP. Mean absolute error was 11.3 (SD 10.0) mm Hg and 8.6 (SD 6.8) mm Hg, respectively.

CONCLUSIONS

A calibration-free, software-only medical device was independently tested against ISO 81060-2:2018/AMD 1:2020. The safety and performance demonstrated in this study suggest that this technique could be a potential solution for rapid and scalable screening and management of hypertension.

Real-World Evaluation of an Automated Algorithm to Detect Patients With Potentially Undiagnosed Hypertension Among Patients With Routine Care in Hawai'i

BACKGROUND

This real-world evaluation considers an algorithm designed to detect patients with potentially undiagnosed hypertension, receiving routine care, in a large health system in Hawai'i. It quantifies patients identified as potentially undiagnosed with hypertension; summarizes the individual, clinical, and health system factors associated with undiagnosed hypertension; and examines if the COVID-19 pandemic affected detection.

METHODS AND RESULTS

We analyzed the electronic health records of patients treated across 6 clinics from 2018 to 2021. We calculated total patients with potentially undiagnosed hypertension and compared patients flagged for undiagnosed hypertension to those with diagnosed hypertension and to the full patient panel across individual characteristics, clinical and health system factors (eg, clinic of care), and timing. Modified Poisson regression was used to calculate crude and adjusted risk ratios. Among the eligible patients (N=13 364), 52.6% had been diagnosed with hypertension, 2.7% were flagged as potentially undiagnosed, and 44.6% had no evidence of hypertension. Factors associated with a higher risk of potentially undiagnosed hypertension included individual characteristics (ages 40-84 compared with 18-39 years), clinical (lack of diabetes diagnosis) and health system factors (clinic site and being a Medicaid versus a Medicare beneficiary), and timing (readings obtained after the COVID-19 Stay-At-Home Order in Hawai'i).

CONCLUSIONS

This evaluation provided evidence that a clinical algorithm implemented within a large health system's electronic health records could detect patients in need of follow-up to determine hypertension status, and it identified key individual characteristics, clinical and health system factors, and timing considerations that may contribute to undiagnosed hypertension among patients receiving routine care.

State of current management of the heightened risk for atherosclerotic cardiovascular events in an established cohort of patients with lupus erythematosus

OBJECTIVE

Patients with lupus erythematosus (LE) are at heightened risk for clinical events, chiefly heart attacks and strokes, from atherosclerotic cardiovascular disease (ASCVD). We recently proposed new guidelines to assess and manage ASCVD event risk specifically in LE. Here, we examined current cardiovascular management in light of these new recommendations.

METHODS

We studied our entire UPenn Longitudinal Lupus Cohort of patients with cutaneous LE, without (CLE-only) or with (CLE+SLE) concurrent systemic LE, for whom we had full access to medical records (n=370, LE-ASCVD Study Cohort).

RESULTS

Of our LE-ASCVD Study Cohort, 336 out of 370 (90.8%) had a designated primary-care physician. By the new guidelines, the most recent low-density lipoprotein (LDL) levels were above-goal for 249 out of 370 (67.3%). Two-hundred sixty-six (71.9%) had hypertension, which was undertreated or untreated in 198 out of 266 (74.4%). Of current smokers, 51 out of 63 (81.0%) had no documented smoking cessation counselling or referrals. Diabetes and triglyceridaemia were generally well managed. Of the cohort, 278 qualified for two widely used online estimators of ASCVD event risk in primary prevention: the ACC-ASCVD Risk Estimator Plus and QRisk3. We also stratified these 278 patients into our recently defined categories of ASCVD event risk in LE. These three methods for estimating ASCVD event risk showed clinically meaningful discordance for 169 out of 278 (60.8%). The documented rate of ASCVD events in the first 10 years after enrolment was 13.5% (95% CI 8.9%, 17.9%), similar between CLE-only and CLE+SLE, indicating an at-risk population despite the preponderance of women and an average age at enrolment of only 47 years.

CONCLUSION

Patients with CLE-only or CLE+SLE are undertreated compared with the new guidelines and, accordingly, they experience a significant burden of ASCVD events. Moreover, it is unclear how to accurately assess their future ASCVD event risk, except that it is substantial. Efforts are underway to improve ASCVD event risk estimation and guideline implementation in patients with lupus.

Healthy Sleep Associated With Lower Risk of Hypertension Regardless of Genetic Risk: A Population-Based Cohort Study

Background: Hypertension is a leading contributor to the global burden of disease and to mortality. The combined effects of sleep factors on the risk of hypertension are unclear. We aimed to evaluate the effect of combined sleep factors on the risk of hypertension and to explore whether this association is independent of genetic risk. Methods: This population-based prospective cohort study included 170,378 participants from the UK Biobank study. We conducted a healthy sleep score based on a combination of major five sleep factors and a genetic risk score based on 118 risk variants. Cox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: A total of 170,378 participants were included. Compared to participants with a healthy sleep score of 0-1, those with healthy sleep scores of 2 (HR, 0.90; 95% CI, 0.83-0.98), 3 (HR, 0.81; 95% CI, 0.75-0.88), 4 (HR, 0.74; 95% CI, 0.68-0.81), or 5 (HR, 0.67; 95% CI, 0.59-0.77) had increasingly lower risks of hypertension (P for trend <0.001). Participants with high genetic risk and an unfavorable sleep pattern had a 1.80-fold greater risk of hypertension than participants with low genetic risk and a favorable sleep pattern. The association between sleep patterns and hypertension persisted in subgroup analysis, stratified by the genetic risk. Nearly 18.2% of hypertension events in this cohort could be attributed to unfavorable sleep pattern. Conclusions: Favorable sleep pattern was associated with a low risk of hypertension, regardless of genetic risk. These findings highlight the potential of sleep interventions to reduce risk of hypertension across entire populations.

Rates of Undiagnosed Hypertension and Diagnosed Hypertension Without Anti-hypertensive Medication Following the Affordable Care Act

BACKGROUND

The Affordable Care Act (ACA) Medicaid expansion improved access to health insurance and health care services. This study assessed whether the rate of patients with undiagnosed hypertension and the rate of patients with hypertension without anti-hypertensive medication decreased post-ACA in community health center (CHC).

METHODS

We analyzed electronic health record data from 2012 to 2017 for 126,699 CHC patients aged 19-64 years with ≥1 visit pre-ACA and ≥1 post-ACA in 14 Medicaid expansion states. We estimated the prevalence of patients with undiagnosed hypertension (high blood pressure reading without a diagnosis for ≥1 day) and the prevalence of patients with hypertension without anti-hypertensive medication by year and health insurance type (continuously uninsured, continuously insured, gained insurance, and discontinuously insured). We compared the time to diagnosis or to anti-hypertensive medication pre- vs. post-ACA.

RESULTS

Overall, 37.3% of patients had undiagnosed hypertension and 27.0% of patients with diagnosed hypertension were without a prescribed anti-hypertensive medication for ≥1 day during the study period. The rate of undiagnosed hypertension decreased from 2012 through 2017. Those who gained insurance had the lowest rates of undiagnosed hypertension (2012: 14.8%; 2017: 6.1%). Patients with hypertension were also more likely to receive anti-hypertension medication during this period, especially uninsured patients who experienced the largest decline (from 47.0% to 8.1%). Post-ACA, among patients with undiagnosed hypertension, time to diagnosis was shorter for those who gained insurance than other insurance types.

CONCLUSIONS

Those who gained health insurance were appropriately diagnosed with hypertension faster and more frequently post-ACA than those with other insurance types.

CLINICAL TRIALS REGISTRATION

Trial Number NCT03545763.

Examining elevated blood pressure and the effects of diabetes self-management education on blood pressure among a sample of Marshallese with type 2 diabetes in Arkansas

INTRODUCTION

Hypertension is a leading risk factor for heart attack and stroke. Undiagnosed hypertension increases the risk of heart attack and stroke. The risk of hypertension is increased for those with type 2 diabetes mellitus (T2DM). Diabetes self-management education (DSME) has been shown to be effective at improving clinical outcomes, including reducing blood pressure, but few studies have evaluated the effects of DSME for Native Hawaiians and Pacific Islanders.

METHODS

This study examined the baseline prevalence of diagnosed hypertension and undiagnosed high blood pressure and differences in health care access between those with diagnosed hypertension versus undiagnosed high blood pressure. The sample consisted of 221 Marshallese adults with T2DM participating in a DSME randomized controlled trial in northwest Arkansas. The study also examined the effects of DSME interventions on participants' blood pressure, comparing an Adapted-Family DSME with a Standard DSME.

RESULTS

Nearly two-thirds of participants had blood pressure readings indicative of hypertension, and of those, over one-third were previously undiagnosed. The frequency of doctor visits was significantly lower for those with undiagnosed high blood pressure. There were no differences in health insurance coverage or forgone medical care between those with undiagnosed high blood pressure versus diagnosed hypertension. Across all participants, a significant reduction in systolic blood pressure occurred between baseline and post intervention, and a significant reduction in diastolic blood pressure occurred between baseline and post-intervention, 6 months, and 12 months post-intervention. No differences were observed by study arm.

CONCLUSION

This study is the first to document the prevalence of diagnosed hypertension and undiagnosed high blood pressure, as well as the effects of DSME on blood pressure among a sample of Marshallese adults with T2DM.

Novel Digital Technologies for Blood Pressure Monitoring and Hypertension Management

PURPOSE OF REVIEW

Hypertension is common, impacting an estimated 108 million US adults, and deadly, responsible for the deaths of one in six adults annually. Optimal management includes frequent blood pressure monitoring and antihypertensive medication titration, but in the traditional office-based care delivery model, patients have their blood pressure measured only intermittently and in a way that is subject to misdiagnosis with white coat or masked hypertension. There is a growing opportunity to leverage our expanding repository of digital technology to reimagine hypertension care delivery. This paper reviews existing and emerging digital tools available for hypertension management, as well as behavioral economic insights that could supercharge their impact.

RECENT FINDINGS

Digitally connected blood pressure monitors offer an alternative to office-based blood pressure monitoring. A number of cuffless blood pressure monitors are in development but require further validation before they can be deployed for widespread clinical use. Patient-facing hubs and applications offer a means to transmit blood pressure data to clinicians. Though artificial intelligence could allow for curation of this data, its clinical use for hypertension remains limited to assessing risk factors at this time. Finally, text-based and telemedicine platforms are increasingly being employed to translate hypertension data into clinical outcomes with promising results.

SUMMARY

The digital management of hypertension shows potential as an avenue for increasing patient engagement and improving clinical efficiency and outcomes. It is important for clinicians to understand the benefits, limitations, and future directions of digital health to optimize management of hypertension.

Frontiers of Upstream Stroke Prevention and Reduced Stroke Inequity Through Predicting, Preventing, and Managing Hypertension and Atrial Fibrillation: A Call to Action From the Value in Healthcare Initiative's Predict & Prevent Learning Collaborative

Stroke is one of the leading causes of morbidity and mortality in the United States. While age-adjusted stroke mortality was falling, it has leveled off in recent years due in part to advances in medical technology, health care options, and population health interventions. In addition to adverse trends in stroke-related morbidity and mortality across the broader population, there are sociodemographic inequities in stroke risk. These challenges can be addressed by focusing on predicting and preventing modifiable upstream risk factors associated with stroke, but there is a need to develop a practical framework that health care organizations can use to accomplish this task across diverse settings. Accordingly, this article describes the efforts and vision of the multi-stakeholder Predict & Prevent Learning Collaborative of the Value in Healthcare Initiative, a collaboration of the American Heart Association and the Robert J. Margolis, MD, Center for Health Policy at Duke University. This article presents a framework of a potential upstream stroke prevention program with evidence-based implementation strategies for predicting, preventing, and managing stroke risk factors. It is meant to complement existing primary stroke prevention guidelines by identifying frontier strategies that can address gaps in knowledge or implementation. After considering a variety of upstream medical or behavioral risk factors, the group identified 2 risk factors with substantial direct links to stroke for focusing the framework: hypertension and atrial fibrillation. This article also highlights barriers to implementing program components into clinical practice and presents implementation strategies to overcome those barriers. A particular focus was identifying those strategies that could be implemented across many settings, especially lower-resource practices and community-based enterprises representing broad social, economic, and geographic diversity. The practical framework is designed to provide clinicians and health systems with effective upstream stroke prevention strategies that encourage scalability while allowing customization for their local context.