Associations between Blood Pressure Control and Documented Nutrition Care Using Structured Data from Electronic Health Records of Patients with Hypertension

Background Documentation in Electronic Health Records (EHRs) of nutrition care events (overweight or obesity (BMI > 25 or 30, respectively) diagnoses, preventive care visits, or provision of patient education materials (PEM)) for chronic diseases is unclear. Methods Cross-sectional analysis using structured EHR data from primary care visits at a health system in the US from January 2018 - December 2020 of adult patients with hypertension (n = 6,419) tested for associations between last visit blood pressure (BP) control (≤ 140 Systolic BP and ≤ 90 Diastolic BP) and aggregate nutrition care events. Descriptive statistics and multiple logistic regression models were constructed to examine the predictive power of nutrition care events for blood pressure control. Results The median age was 62 years, 32% were male, 48% were Black, 26% were from rural areas and 35.9% had controlled BP at last visit. For the 62% of patients with documented nutrition care, 14.6% had an overweight/obesity diagnosis, 26.2% had a preventive care visit, and 42% received PEM with dietary and hypertension content. The models showed patients who had more preventive care visits (aOR 1.12; CL 1.06, 1.18) had higher odds for BP control. Whereas Black patients compared with white patients (aOR 0.84; CL 0.74, 0.95), those with more hypertension medications (aOR 0.97; CL 0.96, 0.99) and more primary care visits over the study period (aOR 0.98; CL 0.97, 0.99) had lower odds for BP control. Conclusions In this study, documented nutrition care in preventive care visits is significantly associated with BP control, but documentation is infrequent. Additional research should include examining clinical notes for evidence of nutrition care, which may uncover areas that show promise for improving nutrition care for patients with chronic disease.


Abstract
Background Documentation in Electronic Health Records (EHRs) of nutrition care events (overweight or obesity (BMI > 25 or 30, respectively) diagnoses, preventive care visits, or provision of patient education materials (PEM)) for chronic diseases is unclear.

Methods
Cross-sectional analysis using structured EHR data from primary care visits at a health system in the US from January 2018 -December 2020 of adult patients with hypertension (n = 6,419) tested for associations between last visit blood pressure (BP) control (≤ 140 Systolic BP and ≤ 90 Diastolic BP) and aggregate nutrition care events. Descriptive statistics and multiple logistic regression models were constructed to examine the predictive power of nutrition care events for blood pressure control.

Results
The median age was 62 years, 32% were male, 48% were Black, 26% were from rural areas and 35

Conclusions
In this study, documented nutrition care in preventive care visits is signi cantly associated with BP control, but documentation is infrequent. Additional research should include examining clinical notes for evidence of nutrition care, which may uncover areas that show promise for improving nutrition care for patients with chronic disease.
Background High blood pressure, or hypertension, affects nearly 1 in 3 US adults, 1 with approximately half of cases under poor control, increasing the risk of death from a sudden heart attack or stroke. 2 A variety of nutrition care events that occur in primary care settings may have a positive effect on patients' dietary patterns. 3 These could be in the form of the awareness brought to the patient through an obesity or overweight diagnosis, 4 providers or staff spending time counseling a patient about the importance of diet to prevent, treat, or manage a chronic disease, 5,6 or passive education materials (PEMs) containing nutrition information relevant to chronic disease management provided in an after-visit summary. 7 Providing nutrition care may improve patient self-management and hypertension outcomes overall, 8,9 but many primary care clinicians and staff face substantial time barriers to conducting and documenting these activities in electronic health records. 10,11 Rates of nutrition care events are generally low, 5,12 and their documentation in structured EHR data is largely unknown. 13,14 A lack of documentation in the EHR may result in limited communication within the care team about patients' nutrition statuses and challenges in evaluating care quality, which may be a missed opportunity to improve patient outcomes. 15 Little is known about the rates of nutrition care events documented for hypertension management or their relationship with blood pressure control of patients. Given this, the objectives of this study were to assess of rates of nutrition care events identi ed in structured EHR data and to test whether these were associated with blood pressure control for adult patients in an academic health system. The hypothesis tested was that documented nutrition care, controlling for patient demographic and health characteristics, is associated with blood pressure control.

Methods
Study Design and Setting.
A single, safety-net academic medical center with six primary care clinic sites in the Mid-Atlantic US serves a diverse patient population of both rural and urban, and underrepresented racial/ethnic patients. Deidenti ed EHR data were obtained for clinical visits (n = 66,875) between December 2017 and December 2020 for (n = 6,419) adult patients, age 18 to 85 years, who had at least two primary care visits during the study period and had a previous diagnosis of hypertension. Records of patients with chronic kidney disease, pregnancy, or who were in hospice or long-term care were excluded per the clinical quality measure for controlling high blood pressure. 16 Due to interruptions in clinical care resulting from the COVID-19 pandemic, 17 records of patients who had not had at least one visit prior to March 2020 were also excluded. Patient data included demographics: sex, racial/ethnicity categories, rural geography indicated by Rural Urban Continuum codes 4-9, 18 and insured status; and clinical factors relevant to hypertension: BMI, comorbidities, 19 hypertension medications, 20 number of visits, and blood pressure control. 16 Nutrition care events were indicated by three commonly provided services in primary care hypertension management that were used as a proxy for nutrition-related information exchanged with the patient. These nutrition care events were identi ed by diagnosis and billing codes for overweight/obesity diagnoses and preventive visits, and a ag that diet-related education materials were provided to the patient. Clinical guidelines for the treatment of overweight/obesity include dietary behavior management, 21,22 and the diagnosis itself may inherently offer an opportunity as a "teachable moment" behavior change intervention. 4 Preventive visits that include evaluation for and management of chronic diseases like hypertension were chosen for the comprehensive counseling and guidance provided to patients to reduce risk factors that include diet. 23,24 Providing patients with printed education materials is a common and passive method for counseling patients about dietary recommendations.

Analyses
Descriptive statistics (frequencies, proportions, means, SDs, medians, and ranges) were calculated for all patients' and strati ed samples of Black and white patients' demographic characteristics and hypertension-relevant indicators, proportions of patients with controlled blood pressure, and rates of documented nutrition care events.
Three multiple logistic regression models were created with the outcome of patients' blood pressure control (yes/no) at their last visit and the predictors as the total number documented in the EHR over the study period of: A) any nutrition care event, B) overweight or obesity diagnoses; preventive care visits that involve nutrition or dietary counseling; and provision of patient education materials, and C) model B strati ed among data for Black patients and white patients. The models adjusted for covariates that included patient demographic characteristics age, sex, race/ethnicity (Model A only), insured status (Private/Medicaid/Medicare/None-Other), geography (rural/urban); and clinical factors BMI, number of hypertension medications prescribed during the study period, and comorbidities. The models also controlled for the random effects from a dose-response through the number of primary care visits the patient made over the study period, and geography through the inclusion of the clinic site of their last visit. Given the sample distribution and consistent disparities identi ed in Models A and B, Model C was constructed as a way to separately examine 25 the strength of association between controlled blood pressure and nutrition care events among Black patient and white patient groups.
Results are presented as adjusted odds ratios and 95% con dence intervals for each multiple logistic regression model and were considered signi cant for p < 0.05. Comorbidities were calculated with HCUP Elixhauser software 19 program using SAS Enterprise Edition 3.7 (SAS Institute, Cary, North Carolina, USA). All remaining analyses were conducted using R Statistical Software (Version 4.0.3; R Foundation for Statistical Computing, 2020). This study was approved as exempt by an Institutional Review Board.

Results
Descriptive statistics for patients' characteristics and clinical factors are found in Table 1. The overall median age of patients in the EHR data sample (n=6,419) was 62 years (range:18,85), nearly a third (n=2,064; 32.2%) were male, almost half (n=3,076; 47.9%) were Black/African American, 26% (n=1,668) were from rural areas, and 10.1% (n=650) were covered by Medicaid insurance. Most patients in the sample were overweight or obese (n=5,629; 87.7%) for at least one recorded BMI during the study period. The median total number of anti-hypertensive prescriptions per patient over the study period was 4 (range:0,40). About a third (n=2,275; 35.4%) had one or more comorbidities, the median number of months since hypertension diagnosis was 38 (range: 0, 229), and about a third (n=2,307; 36%) had controlled hypertension based on blood pressure recordings from their last primary care visit.

Blood Pressure Control and Nutrition Care Events
The multiple logistic regression model (Model A) that tested for association between blood pressure control and the total number of documented nutrition care events (AUC: 0.585) found no signi cant association (aOR: 1.03; 95% CI: 1.00, 1.06). However, the model (Model B) that tested for associations between blood pressure control and the number of speci c types of nutrition care events (AUC: 0.590) had some signi cant ndings. Associations with demographic and health covariates were consistent for each model, with race/ethnicity and the number of hypertension medications prescribed over the study period signi cantly associated with blood pressure control. Patients with more preventive care visits and more hypertension medications documented across the study period had higher odds for having controlled blood pressure (aOR 1.12; 95% CI:

Discussion
EHR data was used in this study to examine associations between blood pressure control and nutrition care events identi ed through documentation of clinical activities that imply nutrition or diet information was communicated with patients who have hypertension. Visits reported in the EHR data were at primary care clinics part of a health system that serves a diverse population of rural and underrepresented racial/ethnic patients. Among the 6,419 patients with hypertension, rates of nutrition care events were generally low, although documentation was variable across the clinics. Of documented nutrition care events, preventive care visits where counseling about dietary risk factors occured were found to be associated with improved odds for blood pressure control. However, there were disparities in blood pressure control by race, for those who had more prescribed hypertension medications, and those who had more clinical encounters.
Overall low rates of documented nutrition care events found in this study support the wider call to address barriers faced by clinicians and staff such as time pressures and limited provider education in providing nutrition care in primary care settings. 10,11 To understand how these rates might increase, these clinical activities must be measured, and to be measured, they must be documented. Stange and colleagues argued health systems measure what is valued, 26 and this study highlights a few important opportunities where nutrition is addressed with patients: diagnoses of overweight or obesity diagnoses, preventive care visits, and provision of patient education materials.
In this study, an overweight or obesity diagnosis was not associated with controlled blood pressure However, BMI persists as a clinical tool for risk assessment, and the diagnosis, as previously mentioned, could play an important role in patient awareness of a health risk. Mixed ndings about BMI associations with hypertension management is seen in a recent study of blood pressure control rates among adults with hypertension. Foti and colleagues found those with overweight or obesity had higher rates of blood pressure control compared with those who had lower BMI. This, the authors suggested, might be because the lower BMI patients may be less aware of their hypertension and be treated less often or intensely. 27 Interestingly, rates of obesity and overweight diagnoses were not concordant with BMI calculated from patient chart data in the present study. The disconnect between BMI and documented obesity diagnoses has been shown elsewhere; one study of EHR data found that while more than half (52%) of patients in the sample had a BMI ≥ 30.0 qualifying them for an obesity diagnosis, very few (5.6%) had obesity recorded in their health record problem list. 28 One factor contributing to the lack of documenting or addressing overweight or obesity with patients may be clinicians are ill-prepared to discuss the topic. 29 The present study had more than a quarter of patients who had at least one preventive visit documented in their EHR record that included a discussion of nutrition-related risk factors. Clinical guidelines suggest nutrition counseling is included in lifestyle treatment for chronic diseases for which diet is a risk factor. Healthy People 2020 suggested a goal to "increase the proportion of physician o ce visits made by patients with a diagnosis of cardiovascular disease, diabetes, or hyperlipidemia that include counseling or education related to diet or nutrition," 30 from 11.5-12.7% (a 10% increase) by 2020 as measured by the National Ambulatory Medical Care Survey (NAMCS). Overall rates reached over 20% by 2015, which may be why the objective was eliminated altogether for Healthy People 2030. However, rates assessed by the present study and Healthy People remain objectively low for a service that may be universally useful if it were achievable to provide such service to all patients, as preventive visits have long been shown to help improve patient health outcomes.
Of note, preventive care visits were less common for Black patients compared to white patients. Given blood pressure control was less likely among Black patients, and in overall and strati ed analysis for both Black patient and white patient samples, preventive care visits were positively and signi cantly associated with blood pressure control. This suggests a disparity in service uptake that may be a missed opportunity for which further understanding and improvements are needed. Others have researched and found delays and underutilization of health services by Black patients due to a variety of reasons 31 including socioeconomic barriers, 32 medical mistrust 33 and perceived racism. 34 Leveraging data entered into the patient's EHR is a way to support the care team in prioritizing appropriate preventive care depending upon patients' individual needs. Krist, et. al. developed an EHR intervention that incorporated automated, tailored, patient-centered messaging for preventive care. In a summary of the initial six months of its use (November 2010 through May 2011), clinics were successful in using the tool to support clinicians to counsel patients about health behaviors and customize prevention and treatment plans for patients. 35 Such initiatives have been instituted within various health systems and clinics nationally over the past decade to support clinicians through the use of risk calculators, 36 automated prompts for clinicians and patients, 37 and provision of printed or electronic patient education materials. 38 Although patient education materials were not signi cantly associated with blood pressure control in this study, they were the most commonly provided nutrition care event. Timely research is needed to understand the effects of using these tools in primary care and preventive visits on patient outcomes across different populations in order to identify disparities as have been identi ed in this study, and apply their use in appropriate settings and support guidelines to do such. Due to the fast rate at which technology use in health care has advanced, health services researchers face additional challenges in e cient dissemination and evaluation of EHR process implementations. 39 Findings of this study offer new contributions and suggestions for additional work needed within the burgeoning area of health services research that seeks to improve preventive services to support patients with chronic disease. First, due to our limited established structures to measure or examine nutrition-related activities in primary care, this study provides a framework of proxy measures for preventive nutrition care that may be found in the voluminous EHR data.
Next, this study applied analyses in strati ed samples of underrepresented racial and ethnic patients, with signi cant ndings to support conducting further detailed explorations of causes and ways forward for improvement. Although not part of the present study, additional strati cation by comorbidities may be conducted to assess differences in treatment plans and nutrition care for complex patients. To gain more insight into nutrition care services and relevant patient outcomes, future research should use a larger data sample or data from a group of health systems, and additional data sources e.g., clinical notes for preventive counseling; and claims data for clinical referrals to dietitians are other avenues to offer a more robust picture of successful processes for conducting and documenting nutrition care delivery that might reveal targets for improvements.
Our study has important limitations. Using EHR data for research has known challenges due to variability of data entry. 40 As a single healthy system study, ndings may not be generalizable, although the EHR used is widely used, and clinics part of the health system served diverse patient populations that represent higher risk for health disparities. These services are critical to chronic disease management and challenges related to their documentation and delivery to patients remain globally applicable.

Conclusions
The present study utilized EHR data to provide a description of nutrition care delivery and examination of its association with patient blood pressure outcomes within a single health system. Overall, documentation of received nutrition care events was low, and preventive care visits, but not overweight/obesity diagnosis or delivery of patient education materials, was associated with patients' blood pressure control. Additionally, disparities were identi ed in rates of nutrition care events and odds for blood pressure control by race. Further research is needed to explore ways to improve documentation and equity of nutrition care. Enhancing EHR work ows, education for providers and staff about nutrition care, and improving effective communication and collaboration within the clinical team may all be system-level targets for improving nutrition care and hypertension outcomes.  Number of patients who received at least one form of nutrition care across the study period.

Declarations
Number of patients who received at least one patient education material (PEM) across the study period.
Number of patients who were provided with a preventive care visit (CPT: 99381-99387, 99391-99397) that includes counseling about chronic disease risk factors and management strategies across the study period.