Data-driven approaches to strengthen hypertension management of priority populations in primary care: A Systematic Review (Preprint)

Abstract

Hypertension management of priority populations (e.g., African American/Black) in primary care is highly relevant. However, evidence on whether or how data-driven approaches can help to improve hypertension management in primary care remains scarce.

This review aims to examine data-driven approaches aiming to improve hypertension management in priority populations, specifically to 1) identify and categorize the different kinds of interventions or approaches that exist and 2) to identify how data inform these approaches.

A search strategy based on the PICO guidelines was utilized to query and identify peer-review articles on the Web of Science and PubMed databases. The search strategy was based on terms related to priority populations, hypertension, primary care, and data-driven interventions. Articles were excluded if the focus was not hypertension management in priority populations or if there was no mention of data utilization.

A total of 26 articles were included in this analysis. In all of these studies, the data-driven approaches were based on the electronic health record (EHR). The EHR was used to identify patients (n=26), drive the intervention (n=19), and monitor results and outcomes (n=14). Most often, data-driven approaches were used for health coaching interventions, disease management programs (DMPs), and clinical decision support systems (CDS) like best practice alerts (BPA). However, out of 8 data-driven health coaching interventions, only 4 have been reporting significant results. In contrast, all included studies related to DMPs and CDS/BPA applications reported some significant results with respect to improving hypertension management.

In primary care, data-driven approaches can meaningfully contribute to improving cardiovascular health conditions, including hypertension in priority populations. However, to date, there is no unified concept of what exactly “data-driven” means and how data-driven approaches can be systematically implemented in healthcare. Instead, data-driven aspects are included in a wide variety of health interventions, including target health coaching, DMPs, or BPAs. Future research should address this gap and, in particular, systematize the application of clinical routine data (EHR data) for data-driven approaches to improve the quality of care.

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