BACKGROUND Common Data Models (CDMs) are essential tools for data harmonization, which can lead to significant improvements in the health domains. CDMs unite data from disparate sources and ease collaborations across institutions that finally result in the generation of large standardized data repositories across different entities. An overview of existing CDMs and methods used to develop these datasets may assist the development process of future models for the health domain, e.g., for decision support systems. OBJECTIVE This Scoping Review (Sc-R) investigates methods used in the development of CDMs for health data. We aim to provide a broad overview of approaches and guidelines that are used in developing CDMs, i.e., Common Data Elements (CDEs) or Common Data Sets (CDS), for different health domains on an international level. METHODS This Sc-R is following the “Preferred Reporting Items for Systematic Review and Meta-Analysis extension for Scoping Reviews” (PRISMA-ScR) Checklist. We conducted our literature research in prominent databases, namely PubMed, Web of Science, Science Direct, and Scopus for five-year publications, starting from 2017 until March 2022. We identified and screened 801 articles. The included articles are evaluated based on the type of utilized method used in the conception, data collection, implementation, and evaluation phase of CDMs, and whether stakeholders (such as medical experts, patients, and IT Staff) were involved during this process. Moreover, the models are grouped into iterative or linear types based on the imperativeness of the stages during development. RESULTS We finally identified 33 articles that fit our eligibility criteria. Of these articles, 26 specifically focus on common medical conditions, five on rare medical conditions, and the remaining two are fitting to both categories. The development process usually involves stakeholders, but in different ways (e.g., working group meetings, Delphi, interviews, and questionnaires). 10 Models followed an iterative process. CONCLUSIONS The articles included show the diversity of methods used to develop a CDM in different domains of health. We highlight the need for more specialized CDM development methods in the health domains and propose a suggestive development process that might ease the development process of the CDMs in the health domain in the future.

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Background Common data models (CDMs) are essential tools for data harmonization, which can lead to significant improvements in the health domain. CDMs unite data from disparate sources and ease collaborations across institutions, resulting in the generation of large standardized data repositories across different entities. An overview of existing CDMs and methods used to develop these data sets may assist in the development process of future models for the health domain, such as for decision support systems. Objective This scoping review investigates methods used in the development of CDMs for health data. We aim to provide a broad overview of approaches and guidelines that are used in the development of CDMs (ie, common data elements or common data sets) for different health domains on an international level. Methods This scoping review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. We conducted the literature search in prominent databases, namely, PubMed, Web of Science, Science Direct, and Scopus, starting from January 2000 until March 2022. We identified and screened 1309 articles. The included articles were evaluated based on the type of adopted method, which was used in the conception, users’ needs collection, implementation, and evaluation phases of CDMs, and whether stakeholders (such as medical experts, patients’ representatives, and IT staff) were involved during the process. Moreover, the models were grouped into iterative or linear types based on the imperativeness of the stages during development. Results We finally identified 59 articles that fit our eligibility criteria. Of these articles, 45 specifically focused on common medical conditions, 10 focused on rare medical conditions, and the remaining 4 focused on both conditions. The development process usually involved stakeholders but in different ways (eg, working group meetings, Delphi approaches, interviews, and questionnaires). Twenty-two models followed an iterative process. Conclusions The included articles showed the diversity of methods used to develop a CDM in different domains of health. We highlight the need for more specialized CDM development methods in the health domain and propose a suggestive development process that might ease the development of CDMs in the health domain in the future.

The Communication and Tracing App HIV (COMTRAC-HIV) project aims to develop a mobile health application for integrated care of HIV patients due to the low availability of those apps in Germany. This study addressed organizational conditions and necessary app functionalities, especially for the care of late diagnosed individuals (late presenters) and those using pre-exposure prophylaxis. We followed a human-centered design approach and interviewed HIV experts in Germany to describe the context of use of the app. The interviews were paraphrased and analyzed with a qualitative content analysis. To define the context of use, user group profiles were defined and tasks derived, which will represent the functionalities of the app. A total of eight experts were included in the study. The results show that the app should include a symptom diary for entering symptoms, side effects, and their intensity. It offers chat/video call functionality for communication with an HIV expert, appointment organization, and sharing findings. The app should also provide medication overview and reminders for medications and appointments. This qualitative study is a first step towards the development of an app for HIV individuals in Germany. Further research includes involving patients in the initial app design and test design usability.