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Development and pilot implementation of Iranian Hemolytic Uremic Syndrome Registry

BACKGROUND: Patients with Hemolytic Uremic Syndrome (HUS) face late diagnosis and lack of appropriate treatment because of a lack of knowledge and experience in this field. A prerequisite for such knowledge is the development of research infrastructures such as a registry system. Therefore, this stu...

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Detalles Bibliográficos
Autores principales: Lazem, Mina, Hooman, Nakysa, Sheikhtaheri, Abbas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205084/
https://www.ncbi.nlm.nih.gov/pubmed/35710568
http://dx.doi.org/10.1186/s13023-022-02376-9
Descripción
Sumario:BACKGROUND: Patients with Hemolytic Uremic Syndrome (HUS) face late diagnosis and lack of appropriate treatment because of a lack of knowledge and experience in this field. A prerequisite for such knowledge is the development of research infrastructures such as a registry system. Therefore, this study aimed to develop and describe the HUS registry in accordance with the Iranian health system and implement its software system. METHODS: We first interviewed 10 pediatric nephrologists and after analyzing the interviews, we identified the features and requirements and the data related to HUS. Then, during two rounds of the Delphi technique (the first round with 23 participants and the second round with 18 participants), the model of this registry was finalized based on the agreement of at least 75% of specialists. At the next step, based on the agreed requirements, IRI.HUS.Reg (Iranian Hemolytic Uremic Syndrome Registry) software was developed and implemented in a pediatric hospital. RESULTS: We classified 369 meaning units of interviews in 41 codes and 7 final themes including purposes of the registry (10 codes), inclusion criteria (7 codes), data collection method (4 codes), data quality control (6 codes), data sources (4 codes), data analysis (3 codes) and software features (7 codes). These 7 feature groups (67 subgroups) and 12 data classes (138 data elements) include demographic data, referrals, examinations, clinical signs, causes, laboratory tests, medical histories, paraclinical measures, treatments, outcomes, patient’s status at discharge, and follow-up data were reviewed by the Delphi panelists, and finally, 64 features and 131 data elements were accepted by at least 78% agreement. Then, we developed and implemented a registry software system in a hospital. CONCLUSION: We implemented IRI.HUS.Reg based on related features, 12 data classes agreed by specialists, literature review, and comparison with other existing registries. Therefore, the data collected in this registry can be compared with other data from existing registries in other countries. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-022-02376-9.