Evidence mapPaperPMID 41503547Full record

ArticleHealth science reports2026

Introducing and Validating a Minimum Data Set and Core Functionalities for Remote Poststroke Home Monitoring: "A Cross-Sectional Study".

Mahbubeh Rezazadeh, Azita Yazdani, Amir Ali Ghahremani, Zahra Mahmoudzadeh-Sagheb

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Article in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mahbubeh RezazadehStudent Research Committee, Department of Health Information Management, School of Health Management and Information Sciences Shiraz University of Medical Sciences Shiraz Iran.
Azita YazdaniDepartment of Health Information Management, School of Health Management and Information Sciences, Health Human Resources Research Center Shiraz University of Medical Sciences Shiraz Iran.
Amir Ali GhahremaniDepartment of Internal Medicine North Khorasan University of Medical Sciences Bojnurd Iran.
Zahra Mahmoudzadeh-SaghebDepartment of Health Information Management, School of Health Management and Information Sciences, Health Human Resources Research Center Shiraz University of Medical Sciences Shiraz Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: 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. Methods: 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. Results: 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. Conclusion: 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.

Indexed as

data elementsremote patient monitoringself‐monitoringstroketelemedicine

Identifiers

PMID41503547
PMCPMC12772508

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.