Clare MacRae, Hannah Whittaker, Mome Mukherjee, Luke Daines, Ann Morgan, Chukwuma Iwundu, Mohammed Alsallakh, Eleftheria Vasileiou, Eimear O'Rourke, Alexander T Williams, Philip W Stone, Aziz Sheikh, Jennifer K Quint
{"title":"为未来研究建立一个标准化的推荐呼吸系统疾病代码库。","authors":"Clare MacRae, Hannah Whittaker, Mome Mukherjee, Luke Daines, Ann Morgan, Chukwuma Iwundu, Mohammed Alsallakh, Eleftheria Vasileiou, Eimear O'Rourke, Alexander T Williams, Philip W Stone, Aziz Sheikh, Jennifer K Quint","doi":"10.2147/POR.S353400","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Electronic health record (EHR) databases provide rich, longitudinal data on interactions with healthcare providers and can be used to advance research into respiratory conditions. However, since these data are primarily collected to support health care delivery, clinical coding can be inconsistent, resulting in inherent challenges in using these data for research purposes.</p><p><strong>Methods: </strong>We systematically searched existing international literature and UK code repositories to find respiratory disease codelists for asthma from January 2018, and chronic obstructive pulmonary disease and respiratory tract infections from January 2020, based on prior searches. Medline searches using key terms provided in article lists. Full-text articles, supplementary files, and reference lists were examined for codelists, and codelists repositories were searched. A reproducible methodology for codelists creation was developed with recommended lists for each disease created based on multidisciplinary expert opinion and previously published literature.</p><p><strong>Results: </strong>Medline searches returned 1126 asthma articles, 70 COPD articles, and 90 respiratory infection articles, with 3%, 22% and 5% including codelists, respectively. Repository searching returned 12 asthma, 23 COPD, and 64 respiratory infection codelists. We have systematically compiled respiratory disease codelists and from these derived recommended lists for use by researchers to find the most up-to-date and relevant respiratory disease codelists that can be tailored to individual research questions.</p><p><strong>Conclusion: </strong>Few published papers include codelists, and where published diverse codelists were used, even when answering similar research questions. Whilst some advances have been made, greater consistency and transparency across studies using routine data to study respiratory diseases are needed.</p>","PeriodicalId":20399,"journal":{"name":"Pragmatic and Observational Research","volume":"13 ","pages":"1-8"},"PeriodicalIF":2.3000,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/c4/03/por-13-1.PMC8859726.pdf","citationCount":"2","resultStr":"{\"title\":\"Deriving a Standardised Recommended Respiratory Disease Codelist Repository for Future Research.\",\"authors\":\"Clare MacRae, Hannah Whittaker, Mome Mukherjee, Luke Daines, Ann Morgan, Chukwuma Iwundu, Mohammed Alsallakh, Eleftheria Vasileiou, Eimear O'Rourke, Alexander T Williams, Philip W Stone, Aziz Sheikh, Jennifer K Quint\",\"doi\":\"10.2147/POR.S353400\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Electronic health record (EHR) databases provide rich, longitudinal data on interactions with healthcare providers and can be used to advance research into respiratory conditions. However, since these data are primarily collected to support health care delivery, clinical coding can be inconsistent, resulting in inherent challenges in using these data for research purposes.</p><p><strong>Methods: </strong>We systematically searched existing international literature and UK code repositories to find respiratory disease codelists for asthma from January 2018, and chronic obstructive pulmonary disease and respiratory tract infections from January 2020, based on prior searches. Medline searches using key terms provided in article lists. Full-text articles, supplementary files, and reference lists were examined for codelists, and codelists repositories were searched. A reproducible methodology for codelists creation was developed with recommended lists for each disease created based on multidisciplinary expert opinion and previously published literature.</p><p><strong>Results: </strong>Medline searches returned 1126 asthma articles, 70 COPD articles, and 90 respiratory infection articles, with 3%, 22% and 5% including codelists, respectively. Repository searching returned 12 asthma, 23 COPD, and 64 respiratory infection codelists. We have systematically compiled respiratory disease codelists and from these derived recommended lists for use by researchers to find the most up-to-date and relevant respiratory disease codelists that can be tailored to individual research questions.</p><p><strong>Conclusion: </strong>Few published papers include codelists, and where published diverse codelists were used, even when answering similar research questions. Whilst some advances have been made, greater consistency and transparency across studies using routine data to study respiratory diseases are needed.</p>\",\"PeriodicalId\":20399,\"journal\":{\"name\":\"Pragmatic and Observational Research\",\"volume\":\"13 \",\"pages\":\"1-8\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2022-02-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/c4/03/por-13-1.PMC8859726.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pragmatic and Observational Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2147/POR.S353400\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pragmatic and Observational Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/POR.S353400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Deriving a Standardised Recommended Respiratory Disease Codelist Repository for Future Research.
Background: Electronic health record (EHR) databases provide rich, longitudinal data on interactions with healthcare providers and can be used to advance research into respiratory conditions. However, since these data are primarily collected to support health care delivery, clinical coding can be inconsistent, resulting in inherent challenges in using these data for research purposes.
Methods: We systematically searched existing international literature and UK code repositories to find respiratory disease codelists for asthma from January 2018, and chronic obstructive pulmonary disease and respiratory tract infections from January 2020, based on prior searches. Medline searches using key terms provided in article lists. Full-text articles, supplementary files, and reference lists were examined for codelists, and codelists repositories were searched. A reproducible methodology for codelists creation was developed with recommended lists for each disease created based on multidisciplinary expert opinion and previously published literature.
Results: Medline searches returned 1126 asthma articles, 70 COPD articles, and 90 respiratory infection articles, with 3%, 22% and 5% including codelists, respectively. Repository searching returned 12 asthma, 23 COPD, and 64 respiratory infection codelists. We have systematically compiled respiratory disease codelists and from these derived recommended lists for use by researchers to find the most up-to-date and relevant respiratory disease codelists that can be tailored to individual research questions.
Conclusion: Few published papers include codelists, and where published diverse codelists were used, even when answering similar research questions. Whilst some advances have been made, greater consistency and transparency across studies using routine data to study respiratory diseases are needed.
期刊介绍:
Pragmatic and Observational Research is an international, peer-reviewed, open-access journal that publishes data from studies designed to closely reflect medical interventions in real-world clinical practice, providing insights beyond classical randomized controlled trials (RCTs). While RCTs maximize internal validity for cause-and-effect relationships, they often represent only specific patient groups. This journal aims to complement such studies by providing data that better mirrors real-world patients and the usage of medicines, thus informing guidelines and enhancing the applicability of research findings across diverse patient populations encountered in everyday clinical practice.