# Introducing and Validating a Minimum Data Set and Core Functionalities for Remote Poststroke Home Monitoring: “A Cross‐Sectional Study”

## TL;DR

This study identifies essential data elements for remote monitoring systems to support post-stroke patients at home.

## Contribution

A validated minimum dataset and core functionalities for post-stroke remote monitoring systems are introduced.

## Key findings

- 75 data elements were extracted and refined to 61 essential elements across three categories.
- Expert validation confirmed the content validity of the dataset (CVR 0.89, CVI 0.97).
- The study provides a foundation for developing effective remote monitoring applications for post-stroke patients.

## Abstract

Stroke is recognized as a significant global health concern. The design and implementation of remote patient monitoring systems necessitate the identification of relevant data elements to effectively address the needs of individuals following a stroke. Identification and validation of these data elements can contribute to the successful design and implementation of remote patient monitoring systems. This study aimed to identify the requirements for a remote monitoring system designed for poststroke patients.

This descriptive, cross‐sectional study was conducted in three steps, including a literature review, expert panel discussions, and the Delphi technique. The literature was reviewed on electronic databases including the Cochrane Library, Wiley, Scopus, ProQuest, IEEE, PubMed, and Web of Science, using the keywords “stroke,” “secondary stroke,” “remote care,” “telehealth,” “remote patient monitoring,” and “remote monitoring” from 2000 to 2023. Three expert panel sessions were conducted to review and categorize the extracted data elements, with content validity confirmed (CVR 0.89, CVI 0.97). Finally, the Delphi technique involving 20 neurologists was used to validate the finalized data elements and system functionalities.

Thirty‐six studies were selected based on the inclusion criteria. A total of 75 data elements were extracted from the literature review. Finally, 61 data elements in three main categories (demographic information, clinical information, and system functionality) were classified and validated by experts as essential data elements for the design of a remote patient monitoring system for poststroke patients.

The findings of this study encompass a range of fundamental capabilities of remote monitoring systems for poststroke patients. Consequently, this study can guide researchers interested in this field in identifying and selecting the appropriate path for developing a remote patient monitoring application for this group of patients.