Minimum Dataset of Lung Cancer Patients: An Initial Step Towards Developing a Web-Based Personal Health Record

Background: Personal Health Records (PHR), which utilize advanced health information technology tools, play a crucial role in patient self-management and improving the control of chronic diseases such as lung cancer. To optimize the design of these systems, it is essential to determine the necessary data elements. Objectives: This study aims to identify the minimum dataset required for designing a web-based PHR for lung cancer patients. Methods: This descriptive, cross-sectional research was conducted in 2023. Initially, a lung cancer dataset was extracted through text analysis. In the next phase, a proposed minimum lung cancer dataset was formulated into a questionnaire containing 18 data groups, including 126 data elements. The dataset underwent expert validation in two phases using the Delphi technique. Data analysis was performed using SPSS version 26, with descriptive statistics employed. Results: The minimum web-based PHR dataset for lung cancer patients, consisting of 18 data groups (112 data elements), includes demographics, insurance information, emergency contact details, patient symptoms, tumor-related data, physician details, treatment information, patient-reported measurements, personal medical history, history of procedures and surgeries, visits, allergies, family history, medication information, test results, imaging data, dietary information, and educational materials. Conclusions: Based on the study findings, it is recommended that lung cancer data management encompass not only routine information but also additional dimensions such as allergies, tumor-related information, and dietary details. Collecting comprehensive and complete data can significantly enhance the treatment process and post-treatment follow-up.

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Publication Details

Journal
Shiraz E-Medical Journal
Published
2024-10-28
DOI
https://doi.org/10.5812/semj-150042
Primary Topic
Electronic Health Records Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Minimum Dataset of Lung Cancer Patients: An Initial Step Towards Developing a Web-Based Personal Health Record

Ali Asghar Kiani, Ali Garavand, Mahnaz Samadbeik, Narges Mahmoodi et al.
Shiraz E-Medical Journal
Electronic Health Records Systems
article

Minimum Dataset of Lung Cancer Patients: An Initial Step Towards Developing a Web-Based Personal Health Record

Ali Asghar Kiani, Ali Garavand, Mahnaz Samadbeik, Narges Mahmoodi, Monireh Tahvildarzadeh
article en

Abstract

Background: Personal Health Records (PHR), which utilize advanced health information technology tools, play a crucial role in patient self-management and improving the control of chronic diseases such as lung cancer. To optimize the design of these systems, it is essential to determine the necessary data elements. Objectives: This study aims to identify the minimum dataset required for designing a web-based PHR for lung cancer patients. Methods: This descriptive, cross-sectional research was conducted in 2023. Initially, a lung cancer dataset was extracted through text analysis. In the next phase, a proposed minimum lung cancer dataset was formulated into a questionnaire containing 18 data groups, including 126 data elements. The dataset underwent expert validation in two phases using the Delphi technique. Data analysis was performed using SPSS version 26, with descriptive statistics employed. Results: The minimum web-based PHR dataset for lung cancer patients, consisting of 18 data groups (112 data elements), includes demographics, insurance information, emergency contact details, patient symptoms, tumor-related data, physician details, treatment information, patient-reported measurements, personal medical history, history of procedures and surgeries, visits, allergies, family history, medication information, test results, imaging data, dietary information, and educational materials. Conclusions: Based on the study findings, it is recommended that lung cancer data management encompass not only routine information but also additional dimensions such as allergies, tumor-related information, and dietary details. Collecting comprehensive and complete data can significantly enhance the treatment process and post-treatment follow-up.

Shiraz E-Medical JournalVol. 25(12)
Tabriz University of Medical Sciences (IR), Lorestan University of Medical Sciences (IR)
Lorestan University of Medical Sciences
Openalex Percentile: Top 74%
Electronic Health Records Systems
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