RPM_National: Evaluating the Availability of Remote Patient Monitoring at U.S. Hospitals

Aline F. Pedroso, Zhenqiu Lin, Joseph S. Ross, Rohan Khera

[Manuscript] [CarDS Lab]

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This repository contains the codebase used in the study titled:

"National Patterns of Remote Patient Monitoring Service Availability at U.S. Hospitals"

The study evaluates the presence and temporal trends in Remote Patient Monitoring (RPM) service availability using U.S. hospital-level data, leveraging claims and public datasets to explore RPM adoption across settings, specialties, and patient groups.

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Overview

The repository includes all analytical code to generate:

1. Cohort Construction: Defines a national hospital cohort using the American Hospital Association annual survey data.
2. Descriptive Tables: Summarizes characteristics of hospitals offering RPM and the communities served by these hospitals based on county-level census data.
3. Publication Figures: Visualizes RPM availability and relative increase in availability across hospital/community characteristics and geography.

The repository is intended to promote transparency, reproducibility, and reuse of methodology for hospital-based health services research using administrative data.

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File Descriptions

cohort_creation.py

This script assembles a cohort of U.S. hospitals reporting use of RPM services. Key tasks include:

• Identifying hospitals with documented RPM availability.
• Merging facility-level characteristics from auxiliary datasets.
• Creating analytic variables for hospital type, region, ownership, and digital infrastructure.
• Outputting a structured analytic dataset for further tabulation and plotting.

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tables_rpm_national.py

Generates descriptive statistics for the manuscript, including:

• Table 1: Characteristics of hospitals with RPM services according to size, region, area of location, teaching status and ownership.
• Table 2: Baseline characteristics of the communities served by these hospitals.

All tables are exported as CSV files, ready for review and integration into the publication.

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figures_plots_rpm_national.py

Produces the visualizations in the manuscript, including:

• Figure 1: Relative increase in RPM availability from 2018 to 2022.
• Figure 2: Geographic map of RPM availability by county.
• Figure 3: Community and hospital characteristics associated with the availability of RPM services.
• Figure 4: Trends in the proportion of hospitalizations for HF and AMI at hospitals with and without RPM.
• Figure 5: Trends in RPM service availability by rural-urban commuting area (RUCA) classification. .

Figures are generated using matplotlib, seaborn, and geopandas, and saved as high-resolution PNGs.

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Requirements & Setup

Environment

The analysis requires Python 3.8+ and the following Python packages:

pandas
matplotlib
seaborn
geopandas

Setup

1. Clone this repository:

   git clone https://github.com/YOUR-USERNAME/rpm_national.git
   cd rpm_national

2. (Optional) Set up a virtual environment:

   python -m venv env
   source env/bin/activate
   pip install -r requirements.txt

3. Adjust input paths and filenames as needed within each script to match your data environment.

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Running the Analysis

Run each script sequentially to reproduce the study outputs:

# Step 1: Generate cohort
python cohort_creation.py

# Step 2: Create summary tables
python tables_rpm_national.py

# Step 3: Generate figures
python figures_plots_rpm_national.py

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Citation

If you use or adapt this code, please cite the accompanying manuscript:

MLA:

Pedroso, A.F., Lin, Z., Ross, J.S., Khera, R. "National Patterns of Remote Patient Monitoring Service Availability at U.S. Hospitals." Medrxiv. 2025.

BibTeX:

@article{pedroso2025rpm,
  title={National Patterns of Remote Patient Monitoring Service Availability at US Hospitals},
  author={Pedroso, Aline F. and Lin, Zhenqiu and Ross, Joseph S. and Khera, Rohan},
  journal={Medrxiv},
  year={2025},
  note={Original Research Manuscript}
}

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Contact

For questions about the dataset or analysis, please contact:

Aline F. Pedroso, PhD
📧 aline.pedroso@yale.edu

Rohan Khera, MD, MS
📧 rohan.khera@yale.edu