Improving Identification and Diagnosis of Hypertensive Patients Hiding in Plain Sight (HIPS) in Health Centers

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.

Development of a Hypertension Electronic Phenotype for Chronic Disease Surveillance in Electronic Health Records: Key Analytic Decisions and Their Effects

INTRODUCTION

Modernizing chronic disease surveillance with electronic health record (EHR) data may provide better data to improve hypertension prevention and control, but no consensus exists for an EHR-based surveillance definition for hypertension. The Multi-State EHR-Based Network for Disease Surveillance (MENDS) pilot surveillance system was used to develop and test an electronic phenotype for hypertension.

METHODS

We used MENDS data from 1,671,279 patients in Louisiana to examine the effect of different analytic decisions on estimates of hypertension prevalence. Decisions included 1) whether to restrict surveillance to patients with recent blood pressure measurements, 2) varying the number and recency of encounters to define the population at risk of hypertension, 3) how to define hypertension (diagnosis codes, antihypertensive medication, blood pressure measurements, or combinations of these), and 4) how to handle multiple blood pressure measurements on the same day. Results were compared with independent estimates of hypertension prevalence in Louisiana from the Behavioral Risk Factor Surveillance System (BRFSS).

RESULTS

Applying varying criteria resulted in hypertension prevalence estimates ranging from 19.7% to 59.3%. A hypertension surveillance strategy that includes a population with at least 1 clinical encounter with measured blood pressure in the previous 2 years and identifies hypertension using all available data (≥1 diagnosis code, ≥1 antihypertensive medication, and ≥2 elevated blood pressure values ≥140/90 mm Hg on separate days) generated estimates in line with population-based survey data. This definition estimated the crude 2019 hypertension prevalence in the state of Louisiana as 43.4% (age-adjusted, 41.0%), comparable with the crude BRFSS estimate of 39.7% (age adjusted, 37.1%).

CONCLUSION

Applying different criteria to define hypertension using EHR data has a large effect on hypertension prevalence estimates. The proposed electronic phenotype generates hypertension prevalence estimates that align with independent estimates from BRFSS.

An Opportunity to Better Address Hypertension in Women: Self-Measured Blood Pressure Monitoring

More than 56 million women in the United States have hypertension, including almost one in five women of reproductive age. The prevalence of hypertensive disorders of pregnancy is on the rise, putting more women at risk for adverse pregnancy-related outcomes and atherosclerotic cardiovascular disease later in life. Hypertension can be better detected and controlled in women throughout their life course by supporting self-measured blood pressure monitoring. In this study, we present some potential strategies for strengthening our nation's ability to address hypertension in women focusing on pregnancy-related considerations for self-measured blood pressure monitoring.

Small Practices, Big (QI) Dreams: Customizing QI Efforts for Under-resourced Primary Care Practices to Improve Diabetes Disparities (Preprint)

Electronic health record quality improvement (QI) initiatives hold great promise in improving adoption of clinical practice guidelines, including those related to diabetes. QI initiatives implemented in under-resourced primary care settings that primarily serve racial/ethnic minority populations have potential to improve quality of care and ultimately improve diabetes disparities. The “Screen at 23” campaign was launched in 2011 to increase screening for prediabetes and diabetes at lower BMI thresholds (ie, 23 kg/m2) for Asian Americans, in line with the new guidelines put forth by the American Diabetes Association. Here, we describe the implementation of a customized electronic health record QI initiative in under-resourced practices that primarily serve low-income South Asian populations in New York City, designed to increase diabetes screening using updated BMI guidelines and in alignment with the “Screen at 23” campaign. The customization involved the implementation of an innovative, semi-manual alternate solution to automated clinical decision support system (CDSS) alerts in order to address the restrictions on customizing CDSS alerts in electronic health record platforms used in small practice settings. We also discuss challenges and strategies with this customized QI effort. Our experience suggests that multisector partnership engagement, user-centered approaches, and informal strategies for relationship building are even more critical in under-resourced, small practice settings. Relatively simple technological solutions can be greatly beneficial in enhancing small practice capacity to engage in larger-scale QI initiatives. Tailored, context-driven approaches for implementation of equity-focused QI initiatives such as the one we describe can increase adoption of clinical practice guidelines, improve diabetes-related outcomes, and improve health disparities among underserved populations.

Clinical Decision Support for the Diagnosis and Management of Adult and Pediatric Hypertension

PURPOSE OF REVIEW

To review literature from 2016 to 2019 on clinical decision support (CDS) for diagnosis and management of hypertension in children and adults.

RECENT FINDINGS

Ten studies described hypertension CDS systems. Novel advances included the integration of patient-collected blood pressure data, automated information retrieval and management support, and use of CDS in low-resource/developing-world settings and in pediatrics. Findings suggest that CDS increases hypertension detection/control, yet many children and adults with hypertension remain undetected or undercontrolled. CDS challenges included poor usability (from lack of health record integration, excessive data entry requests, and wireless connectivity challenges) and lack of clinician trust in blood pressure measures. Hypertension CDS has improved but not closed gaps in the detection and control of hypertension in children and adults. The studies reviewed indicate that the usability of CDS and the system where CDS is deployed (e.g., commitment to high-quality blood pressure measurement/infrastructure) may impact CDS's ability to increase hypertension detection and control.