Evaluating the Use of Electronic Health Records for Type 2 Diabetes Surveillance in 2 California Counties, 2010-2014

Evaluation of an Emergency Department Visit Data Mental Health Dashboard

CONTEXT

Local health departments (LHDs) need timely county-level and subcounty-level data to monitor health-related trends, identify health disparities, and inform areas of highest need for interventions as part of their ongoing assessment responsibilities; yet, many health departments rely on secondary data that are not timely and cannot provide subcounty insights.

OBJECTIVE

We developed and evaluated a mental health dashboard in Tableau for an LHD audience featuring statewide syndromic surveillance emergency department (ED) data in North Carolina from the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT).

DESIGN

We developed a dashboard that provides counts, crude rates, and ED visit percentages at statewide and county levels, as well as breakdowns by zip code, sex, age group, race, ethnicity, and insurance coverage for 5 mental health conditions. We evaluated the dashboards through semistructured interviews and a Web-based survey that included the standardized usability questions from the System Usability Scale.

PARTICIPANTS

Convenience sample of LHD public health epidemiologists, health educators, evaluators, and public health informaticians.

RESULTS

Six semistructured interview participants successfully navigated the dashboard but identified usability issues when asked to compare county-level trends displayed in different outputs (eg, tables vs graphs). Thirty respondents answered all questions on the System Usability Scale for the dashboard, which received an above average score of 86.

CONCLUSIONS

The dashboards scored well on the System Usability Scale, but more research is needed to identify best practices in disseminating multiyear syndromic surveillance ED visit data on mental health conditions to LHDs.

Utilization of Electronic Health Records for Chronic Disease Surveillance: A Systematic Literature Review

This study reviews the current utilization of electronic health records (EHRs) for chronic disease surveillance, discusses approaches that are used in obtaining EHR-derived disease prevalence estimates, and identifies health indicators that have been studied using EHR-based surveillance methods. PubMed was searched for relevant keywords: (electronic health records [Title/Abstract] AND surveillance [Title/Abstract]) OR (electronic medical records [Title/Abstract] AND surveillance [Title/Abstract]). Articles were assessed based on detailed inclusion and exclusion criteria and organized by common themes, as per the PRISMA review protocol. The study period was limited to 2015-2021 due to the wider adoption of EHR in the U.S. only since 2015. The review included only US studies and only those that focused on chronic disease surveillance. 17 studies were included in the review. The most common approaches the review identified focused on validating EHR-derived estimates against those from traditional national surveys. The most studied conditions were diabetes, obesity, and hypertension. The majority of reviewed studies demonstrated comparable prevalence estimates with traditional population health surveillance surveys. The most common approach for the estimation of chronic disease conditions was to use small-area estimation by geographic patterns, neighborhoods, or census tracts. The use of EHR-based surveillance systems for public health purposes is feasible, and the population health estimates appear comparable to those obtained through traditional surveillance surveys. The application of EHRs for public health surveillance appears promising and could offer a real-time alternative to traditional surveillance methods. A timely assessment of population health at local and regional levels would ensure a more targeted allocation of public health and healthcare resources as well as more effective intervention and prevention initiatives.

Hydroxychloroquine Dose and Risk for Incident Retinopathy : A Cohort Study

BACKGROUND

Hydroxychloroquine is recommended for all patients with systemic lupus erythematosus and is often used for other inflammatory conditions, but a critical long-term adverse effect is vision-threatening retinopathy.

OBJECTIVE

To characterize the long-term risk for incident hydroxychloroquine retinopathy and examine the degree to which average hydroxychloroquine dose within the first 5 years of treatment predicts this risk.

DESIGN

Cohort study.

SETTING

U.S. integrated health network.

PARTICIPANTS

All patients aged 18 years or older who received hydroxychloroquine for 5 or more years between 2004 and 2020 and had guideline-recommended serial retinopathy screening.

MEASUREMENTS

Hydroxychloroquine dose was assessed from pharmacy dispensing records. Incident hydroxychloroquine retinopathy was assessed by central adjudication of spectral domain optical coherence tomography with severity assessment (mild, moderate, or severe). Risk for hydroxychloroquine retinopathy was estimated over 15 years of use according to hydroxychloroquine weight-based dose (>6, 5 to 6, or ≤5 mg/kg per day) using the Kaplan-Meier estimator.

RESULTS

Among 3325 patients in the primary study population, 81 developed hydroxychloroquine retinopathy (56 mild, 17 moderate, and 8 severe), with overall cumulative incidences of 2.5% and 8.6% at 10 and 15 years, respectively. The cumulative incidences of retinopathy at 15 years were 21.6% for higher than 6 mg/kg per day, 11.4% for 5 to 6 mg/kg per day, and 2.7% for 5 mg/kg per day or lower. The corresponding risks for moderate to severe retinopathy at 15 years were 5.9%, 2.4%, and 1.1%, respectively.

LIMITATION

Possible misclassifications of dose due to nonadherence to filled prescriptions.

CONCLUSION

In this large, contemporary cohort with active surveillance retinopathy screening, the overall risk for hydroxychloroquine retinopathy was 8.6% after 15 years, and most cases were mild. Higher hydroxychloroquine dose was associated with progressively greater risk for incident retinopathy.

PRIMARY FUNDING SOURCE

National Institutes of Health.

Neighborhood-Level Chronic Disease Surveillance: Utility of Primary Care Electronic Health Records and Emergency Department Claims Data

CONTEXT

Disease burden may vary substantively across neighborhoods in an urban setting. Yet, data available for monitoring chronic conditions at the neighborhood level are scarce. Large health care data sets have potential to complement population health surveillance. Few studies have examined the utility of health care data for neighborhood-level surveillance.

OBJECTIVE

We examined the use of primary care electronic health records (EHRs) and emergency department (ED) claims for identifying neighborhoods with higher chronic disease burden and neighborhood-level prevalence estimation.

DESIGN

Comparison of hypertension and diabetes estimates from EHRs and ED claims with survey-based estimates.

SETTING

Forty-two United Hospital Fund neighborhoods in New York City.

PARTICIPANTS

The EHR sample comprised 708 452 patients from the Hub Population Health System (the Hub) in 2015, and the ED claim sample comprised 1 567 870 patients from the Statewide Planning and Research Cooperative System in 2015. We derived survey-based estimates from 2012 to 2016 Community Health Survey (n = 44 189).

MAIN OUTCOME MEASURE

We calculated hypertension and diabetes prevalence estimates by neighborhood from each data source. We obtained Pearson correlation and absolute difference between EHR-based or claims-based estimates and survey-based estimates.

RESULTS

Both EHR-based and claims-based estimates correlated strongly with survey-based estimates for hypertension (0.91 and 0.72, respectively) and diabetes (0.83 and 0.82, respectively) and identified similar neighborhoods of higher burden. For hypertension, 10 and 17 neighborhoods from the EHRs and ED claims, respectively, had an absolute difference of more than 5 percentage points from the survey-based estimate. For diabetes, 15 and 4 neighborhoods from the EHRs and ED claims, respectively, differed from the survey-based estimate by more than 5 percentage points.

CONCLUSIONS

Both EHRs and ED claims data are useful for identifying neighborhoods with greater disease burden and have potential for monitoring chronic conditions at the neighborhood level.

Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review

Background

Nonclinical determinants of health are of increasing importance to health care delivery and health policy. Concurrent with growing interest in better addressing patients’ nonmedical issues is the exponential growth in availability of data sources that provide insight into these nonclinical determinants of health.

Objective

This review aimed to characterize the state of the existing literature on the use of nonclinical health indicators in conjunction with clinical data sources.

Methods

We conducted a rapid review of articles and relevant agency publications published in English. Eligible studies described the effect of, the methods for, or the need for combining nonclinical data with clinical data and were published in the United States between January 2010 and April 2018. Additional reports were obtained by manual searching. Records were screened for inclusion in 2 rounds by 4 trained reviewers with interrater reliability checks. From each article, we abstracted the measures, data sources, and level of measurement (individual or aggregate) for each nonclinical determinant of health reported.

Results

A total of 178 articles were included in the review. The articles collectively reported on 744 different nonclinical determinants of health measures. Measures related to socioeconomic status and material conditions were most prevalent (included in 90% of articles), followed by the closely related domain of social circumstances (included in 25% of articles), reflecting the widespread availability and use of standard demographic measures such as household income, marital status, education, race, and ethnicity in public health surveillance. Measures related to health-related behaviors (eg, smoking, diet, tobacco, and substance abuse), the built environment (eg, transportation, sidewalks, and buildings), natural environment (eg, air quality and pollution), and health services and conditions (eg, provider of care supply, utilization, and disease prevalence) were less common, whereas measures related to public policies were rare. When combining nonclinical and clinical data, a majority of studies associated aggregate, area-level nonclinical measures with individual-level clinical data by matching geographical location.

Conclusions

A variety of nonclinical determinants of health measures have been widely but unevenly used in conjunction with clinical data to support population health research.

Performance of a computable phenotype for identification of patients with diabetes within PCORnet: The Patient-Centered Clinical Research Network

PURPOSE

PCORnet, the National Patient-Centered Clinical Research Network, represents an innovative system for the conduct of observational and pragmatic studies. We describe the identification and validation of a retrospective cohort of patients with type 2 diabetes (T2DM) from four PCORnet sites.

METHODS

We adapted existing computable phenotypes (CP) for the identification of patients with T2DM and evaluated their performance across four PCORnet sites (2012-2016). Patients entered the cohort on the earliest date they met one of three CP categories: (CP1) coded T2DM diagnosis (ICD-9/ICD-10) and an antidiabetic prescription, (CP2) diagnosis and glycosylated hemoglobin (HbA1c) ≥6.5%, or (CP3) an antidiabetic prescription and HbA1c ≥6.5%. We required evidence of health care utilization in each of the 2 prior years for each patient, as we also developed an incident T2DM CP to identify the subset of patients without documentation of T2DM in the 365 days before t₀ . Among a systematic sample of patients, we calculated the positive predictive value (PPV) for the T2DM CP and incident-T2DM CP using electronic health record (EHR) review as reference.

RESULTS

The CP identified 50 657 patients with T2DM. The PPV of patients randomly selected for validation was 96.2% (n = 1572; CI:95.1-97.0) and was consistently high across sites. The PPV for the incident-T2DM CP was 5.8% (CI:4.5-7.5).

CONCLUSIONS

The T2DM CP accurately and efficiently identified patients with T2DM across multiple sites that participate in PCORnet, although the incident T2DM CP requires further study. PCORnet is a valuable data source for future epidemiological and comparative effectiveness research among patients with T2DM.

Electronic health record case studies to advance environmental public health tracking

Data from traditional public health surveillance systems can have some limitations, e.g., timeliness, geographic level, and amount of data accessible. Electronic health records (EHRs) could present an opportunity to supplement current sources of routinely collected surveillance data. The National Environmental Public Health Tracking Program (Tracking Program) sought to explore the use of EHRs for advancing environmental public health surveillance practices. The Tracking Program funded four state/local health departments to obtain and pilot the use of EHR data to address several issues including the challenges and technical requirements for accessing EHR data, and the core data elements required to integrate EHR data within their departments' Tracking Programs. The results of these pilot projects highlighted the potential of EHR data for public health surveillance of rare diseases that may lack comprehensive registries, and surveillance of prevalent health conditions or risk factors for health outcomes at a finer geographic level. EHRs therefore, may have potential to supplement traditional sources of public health surveillance data.

Data Visualization Promotes Sound Public Health Practice: The AIDSvu Example

The ability to depict surveillance and other complex health-related data in a visual manner promotes sound public health practice by supporting the three core functions of public health: assessment, policy development, and assurance. Further, such efforts potentiate the use of surveillance data beyond traditional public health audiences and venues, thus fostering a "culture of health." This practice report provides several recent examples of how data from AIDSVu-an interactive map of the U.S. showing the impact of HIV at national, state, and local levels-has been used to: fine tune the assessment of HIV-related disparities at a community level, educate and empower communities about HIV and its consequences, and better target HIV interventions to reach underserved, vulnerable populations.