# Physicians’ Use of Electronic Health Record Data Elements and Decision Support Tools in Heart Failure Management: User-Centered Cross-Sectional Survey Study

**Authors:** Mohamed S Ali, Bruna Oewel, Kaitlyn M Greer, Sabah Ganai, Mark W Newman, Kelly Murdoch-Kitt, Scott L Hummel, Michael P Dorsch

PMC · DOI: 10.2196/79239 · 2025-11-14

## TL;DR

This study explores how cardiologists and general medicine physicians use EHR data and decision support tools in managing heart failure, revealing differences in their priorities and underutilization of certain tools.

## Contribution

The study identifies specific EHR elements and tools prioritized by cardiologists and general medicine physicians in heart failure care, offering insights for future EHR design.

## Key findings

- Both physician groups rely heavily on medication lists, lab results, diagnostic tests, and problem lists.
- Cardiologists emphasize diagnostic tests more than general medicine physicians in both inpatient and outpatient settings.
- Use of standardized questionnaires and predictive models is low across both groups.

## Abstract

The management of heart failure (HF) requires complex, data-driven decision-making. Although electronic health record (EHR) systems and clinical decision support (CDS) tools can streamline access to essential clinical information, it remains unclear which EHR elements and tools cardiologists and general medicine physicians prioritize when caring for patients with HF.

This study aims to identify these elements and tools to improve the user interface design of future EHR applications.

This study used a user-centered design research approach to understand physician workflows and decision-making needs in HF care. A cross-sectional online survey was administered to 302 physicians, comprising 150 cardiologists (including 15 HF specialists) and 152 general medicine physicians. Respondents reported their use of EHR variables (eg, medication lists, laboratory results, diagnostic tests, problem lists, clinical notes) for decision-making in HF care, as well as their time spent in the EHR before, during, and after patient visits along with their use of predictive models and patient-reported outcome questionnaire. Descriptive analyses, χ2 tests, and t tests were conducted to compare groups, with statistical significance set at P<.05.

A total of 302 health care providers participated in the survey, nearly evenly split between cardiologists (49.7%, 150/302) and general medicine physicians (50.3%, 152/302). Both groups consistently relied on medication lists, vital signs, laboratory results, diagnostic tests, problem lists, and clinical notes for HF decision-making. Cardiologists placed greater emphasis on diagnostic tests for inpatient HF care (mean [SD] overall frequency, 4.66 [0.50] vs 4.44 [0.64]; P=.012) and outpatient HF care (mean [SD] overall frequency, 4.67 [0.55] vs 4.35 [0.71], P<.001). In contrast, general medicine physicians relied more on problem lists for inpatient HF care (mean [SD] overall frequency, 4.63 [0.58] vs 4.43 [0.72], P=.034), with no significant difference in the outpatient setting (P>.05). Both groups underutilized standardized questionnaires and predictive models, with only 20.1% (29/144) of cardiologists and 4.5% (6/133) of general medicine physicians using standardized questionnaires (P<.001)

Both physician groups depend on medication lists, laboratory results, diagnostic tests, and problem lists. Cardiologists prioritize diagnostic tests, whereas general medicine physicians more often use problem lists. Low use of questionnaires and predictive models highlights the need for better integration of these tools. Future EHR design interface should tailor functionalities to accommodate these differing priorities and optimize HF care.

## Linked entities

- **Diseases:** heart failure (MONDO:0005252)

## Full-text entities

- **Diseases:** HF (MESH:D006333)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12617960/full.md

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Source: https://tomesphere.com/paper/PMC12617960