Blood pressure control rates measured in specialty vs primary care practices within a large integrated health system

Leveraging Electronic Health Records to Construct a Phenotype for Hypertension Surveillance in the United States

BACKGROUND

Hypertension is an important risk factor for cardiovascular diseases. Electronic health records (EHRs) may augment chronic disease surveillance. We aimed to develop an electronic phenotype (e-phenotype) for hypertension surveillance.

METHODS

We included 11,031,368 eligible adults from the 2019 IQVIA Ambulatory Electronic Medical Records-US (AEMR-US) dataset. We identified hypertension using three criteria, alone or in combination: diagnosis codes, blood pressure (BP) measurements, and antihypertensive medications. We compared AEMR-US estimates of hypertension prevalence and control against those from the National Health and Nutrition Examination Survey (NHANES) 2017-18, which defined hypertension as BP ≥130/80 mm Hg or ≥1 antihypertensive medication.

RESULTS

The study population had a mean (SD) age of 52.3 (6.7) years, and 56.7% were women. The selected three-criteria e-phenotype (≥1 diagnosis code, ≥2 BP measurements of ≥130/80 mm Hg, or ≥1 antihypertensive medication) yielded similar trends in hypertension prevalence as NHANES: 42.2% (AEMR-US) vs. 44.9% (NHANES) overall, 39.0% vs. 38.7% among women, and 46.5% vs. 50.9% among men. The pattern of age-related increase in hypertension prevalence was similar between AEMR-US and NHANES. The prevalence of hypertension control in AEMR-US was 31.5% using the three-criteria e-phenotype, which was higher than NHANES (14.5%).

CONCLUSIONS

Using an EHR dataset of 11 million adults, we constructed a hypertension e-phenotype using three criteria, which can be used for surveillance of hypertension prevalence and control.

Cardiovascular Disease Preventive Services Among Smaller Primary Care Practices

INTRODUCTION

Cardiovascular disease preventive services (aspirin use, blood pressure control, and smoking-cessation support) are crucial to controlling cardiovascular diseases. This study draws from 1,248 small-to-medium-sized primary care practices participating in the EvidenceNOW Initiative from 2015-2016 across 12 states to provide practice-level aspirin use, blood pressure control, and smoking-cessation support estimates; report the percentage of practices that meet Million Hearts targets; and identify the practice characteristics associated with better performance.

METHODS

This cross-sectional study utilized linear regression modeling (analyzed in 2020-2021) to examine the association of aspirin use, blood pressure control, and smoking-cessation support performance with practice characteristics that included structural attributes (e.g., size, ownership, rurality), practice capacity and contextual characteristics, health information technology, and patient panel demographics.

RESULTS

On average, practice performance on aspirin use, blood pressure control, and smoking-cessation support quality measures was 64% for aspirin, 63% for blood pressure, and 62% for smoking-cessation support. The 2012 Million Hearts goal of achieving the rates of 70% was achieved by 52% (aspirin), 32% (blood pressure), and 54% (smoking) of practices. Practice characteristics associated with aspirin use, blood pressure control, and smoking-cessation support performance included ownership (hospital/health system-owned practices had 11% higher aspirin performance than clinician-owned practices [p=0.001]), rurality (rural practices had lower performance than urban practices in all aspirin use, blood pressure control, and smoking-cessation support quality metrics [difference in aspirin=11.1%, p=0.001; blood pressure=4.2%, p=0.022; smoking=14.4%, p=0.009]), and disruptions (practices that experienced >1 major disruption showed lower aspirin performance [-7.1%, p<0.001]).

CONCLUSIONS

Achieving the Million Hearts targets may be assisted by collecting and reporting practice-level performance, which can promote change at the practice level and identify areas where additional support is needed to achieve initiative goals.

Predictors of Smartphone and Tablet Use Among Patients With Hypertension: Secondary Analysis of Health Information National Trends Survey Data

BACKGROUND

Uncontrolled hypertension leads to significant morbidity and mortality. The use of mobile health technology, such as smartphones, for remote blood pressure (BP) monitoring has improved BP control. An increase in BP control is more significant when patients can remotely communicate with their health care providers through technologies and receive feedback. Little is known about the predictors of remote BP monitoring among hypertensive populations.

OBJECTIVE

The objective of this study is to quantify the predictors of smartphone and tablet use in achieving health goals and communicating with health care providers via SMS text messaging among hypertensive patients in the United States.

METHODS

This study was a cross-sectional, secondary analysis of the 2017 and 2018 Health Information National Trends Survey 5, cycles 1 and 2 data. A total of 3045 respondents answered "Yes" to the question "Has a doctor or other healthcare provider ever told you that you had high blood pressure or hypertension?", which defined the subpopulation used in this study. We applied the Health Information National Trends Survey full sample weight to calculate the population estimates and 50 replicate weights to calculate the SEs of the estimates. We used design-adjusted descriptive statistics to describe the characteristics of respondents who are hypertensive based on relevant survey items. Design-adjusted multivariable logistic regression models were fitted to estimate predictors of achieving health goals with the help of smartphone or tablet and sending or receiving an SMS text message to or from a health care provider in the last 12 months.

RESULTS

An estimated 36.9%, SE 0.9% (183,285,150/497,278,883) of the weighted adult population in the United States had hypertension. The mean age of the hypertensive population was 58.3 (SE 0.48) years. Electronic communication with the doctor or doctor's office through email or internet (odds ratio 2.93, 95% CI 1.85-4.63; P<.001) and having a wellness app (odds ratio 1.82, 95% CI 1.16-2.86; P=.02) were significant predictors of using SMS text message communication with a health care professional, adjusting for other demographic and technology-related variables. The odds of achieving health-related goals with the help of a tablet or smartphone declined significantly with older age (P<.001) and ownership of basic cellphones (P=.04). However, they increased significantly with being a woman (P=.045) or with being married (P=.03), having a wellness app (P<.001), using devices other than smartphones or tablets to monitor health (P=.008), making health treatment decisions (P=.048), and discussing with a provider (P=.02) with the help of a tablet or smartphone.

CONCLUSIONS

Intervention measures accounting for age, gender, marital status, and the patient's technology-related health behaviors are required to increase smartphone and tablet use in self-care and SMS text message communication with health care providers.

Hypertension Control and Guideline-Recommended Target Blood Pressure Goal Achievement at an Early Stage of Hypertension in the UAE

(1) Background: The present study aimed to assess the changes in blood pressure (BP) within the first 6 months of treatment initiation in a newly treated hypertensive cohort and to identify the factors that are associated with achieving the target BP recommended by the American (ACC/AHA, 2017), European (ESC/ESH, 2018), United Kingdom (NICE, 2019), and International Society of Hypertension (ISH, 2020) guidelines. (2) Methods: We analyzed 5308 incident hypertensive outpatients across Abu Dhabi, United Arab Emirates (UAE), in 2017; each patient was followed up for 6 months. Hypertension was defined as a BP of 130/80 mmHg according to the ACC/AHA guidelines and 140/90 mmHg according to the ESC/ESH, NICE, and ISH guidelines. Multiple logistic regression was used to identify factors associated with achieving the guideline-recommended BP targets. (3) Results: At baseline, the mean BP was 133.9 ± 72.9 mmHg and 132.7 ± 72.5 mmHg at 6 months. The guideline-recommended BP targets were 39.5%, 43%, 65.6%, and 40.8%, according to the ACC/AHA, ESC/ESH, NICE, and ISH guidelines, respectively. A BMI of <25 kg/m2 was associated with better BP control according to the ACC/AHA (odds ratio (OR) = 1.26; 95% confidence interval (CI) = 1.07–1.49), ESC/ESH (OR = 1.27; 95% CI = 1.08–1.50), and ISH guidelines (OR = 1.22; 95% CI = 1.03–1.44). Hypertension treated in secondary care settings was more likely to achieve the BP targets recommended by the ACC/AHA (1.31 times), ESC/ESH (1.32 times), NICE (1.41 times), and ISH (1.34 times) guidelines. (4) Conclusions: BP goal achievement was suboptimal. BP control efforts should prioritize improving cardiometabolic goals and lifestyle modifications.