David M Kern, John J Barron, Bingcao Wu, Alex Ganetsky, Vincent J Willey, Ralph A Quimbo, Michael J Fisch, Joseph Singer, Ann Nguyen, Ronac Mamtani
{"title":"从新型癌症护理质量计划中获取的临床数据的验证与行政索赔数据直接集成。","authors":"David M Kern, John J Barron, Bingcao Wu, Alex Ganetsky, Vincent J Willey, Ralph A Quimbo, Michael J Fisch, Joseph Singer, Ann Nguyen, Ronac Mamtani","doi":"10.2147/POR.S140579","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Data from a Cancer Care Quality Program are directly integrated with administrative claims data to provide a level of clinical detail not available in claims-based studies, and referred to as the HealthCore Integrated Research Environment (HIRE)-Oncology data. This study evaluated the validity of the HIRE-Oncology data compared with medical records of breast, lung, and colorectal cancer patients.</p><p><strong>Methods: </strong>Data elements included cancer type, stage, histology (lung only), and biomarkers. A sample of 300 breast, 200 lung, and 200 colorectal cancer patients within the HIRE-Oncology data were identified for medical record review. Statistical measures of validity (agreement, positive predictive value [PPV], negative predictive value [NPV], sensitivity, specificity) were used to compare clinical information between data sources, with medical record data considered the gold standard.</p><p><strong>Results: </strong>All 300 breast cancer records reviewed were confirmed breast cancer, while 197 lung and 197 colorectal records were confirmed (PPV =0.99 for each). The agreement of disease stage was 85% for breast, 90% for lung, and 94% for colorectal cancer. The agreement of lung cancer histology (small cell vs non-small cell) was 97%. Agreement of progesterone receptor, estrogen receptor, and human epidermal growth factor receptor 2 status biomarkers in breast cancer was 92%, 97%, and 92%, respectively; epidermal growth factor receptor and anaplastic lymphoma kinase agreement in lung was 97% and 92%, respectively; and agreement of KRAS status in colorectal cancer was 95%. Measures of PPV, NPV, sensitivity, and specificity showed similarly strong evidence of validity.</p><p><strong>Conclusion: </strong>Good agreement between the HIRE-Oncology data and medical records supports the validity of these data for research.</p>","PeriodicalId":20399,"journal":{"name":"Pragmatic and Observational Research","volume":"8 ","pages":"149-155"},"PeriodicalIF":2.3000,"publicationDate":"2017-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/POR.S140579","citationCount":"8","resultStr":"{\"title\":\"A validation of clinical data captured from a novel Cancer Care Quality Program directly integrated with administrative claims data.\",\"authors\":\"David M Kern, John J Barron, Bingcao Wu, Alex Ganetsky, Vincent J Willey, Ralph A Quimbo, Michael J Fisch, Joseph Singer, Ann Nguyen, Ronac Mamtani\",\"doi\":\"10.2147/POR.S140579\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Data from a Cancer Care Quality Program are directly integrated with administrative claims data to provide a level of clinical detail not available in claims-based studies, and referred to as the HealthCore Integrated Research Environment (HIRE)-Oncology data. This study evaluated the validity of the HIRE-Oncology data compared with medical records of breast, lung, and colorectal cancer patients.</p><p><strong>Methods: </strong>Data elements included cancer type, stage, histology (lung only), and biomarkers. A sample of 300 breast, 200 lung, and 200 colorectal cancer patients within the HIRE-Oncology data were identified for medical record review. Statistical measures of validity (agreement, positive predictive value [PPV], negative predictive value [NPV], sensitivity, specificity) were used to compare clinical information between data sources, with medical record data considered the gold standard.</p><p><strong>Results: </strong>All 300 breast cancer records reviewed were confirmed breast cancer, while 197 lung and 197 colorectal records were confirmed (PPV =0.99 for each). The agreement of disease stage was 85% for breast, 90% for lung, and 94% for colorectal cancer. The agreement of lung cancer histology (small cell vs non-small cell) was 97%. Agreement of progesterone receptor, estrogen receptor, and human epidermal growth factor receptor 2 status biomarkers in breast cancer was 92%, 97%, and 92%, respectively; epidermal growth factor receptor and anaplastic lymphoma kinase agreement in lung was 97% and 92%, respectively; and agreement of KRAS status in colorectal cancer was 95%. Measures of PPV, NPV, sensitivity, and specificity showed similarly strong evidence of validity.</p><p><strong>Conclusion: </strong>Good agreement between the HIRE-Oncology data and medical records supports the validity of these data for research.</p>\",\"PeriodicalId\":20399,\"journal\":{\"name\":\"Pragmatic and Observational Research\",\"volume\":\"8 \",\"pages\":\"149-155\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2017-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.2147/POR.S140579\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pragmatic and Observational Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2147/POR.S140579\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2017/1/1 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.S140579","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2017/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
A validation of clinical data captured from a novel Cancer Care Quality Program directly integrated with administrative claims data.
Background: Data from a Cancer Care Quality Program are directly integrated with administrative claims data to provide a level of clinical detail not available in claims-based studies, and referred to as the HealthCore Integrated Research Environment (HIRE)-Oncology data. This study evaluated the validity of the HIRE-Oncology data compared with medical records of breast, lung, and colorectal cancer patients.
Methods: Data elements included cancer type, stage, histology (lung only), and biomarkers. A sample of 300 breast, 200 lung, and 200 colorectal cancer patients within the HIRE-Oncology data were identified for medical record review. Statistical measures of validity (agreement, positive predictive value [PPV], negative predictive value [NPV], sensitivity, specificity) were used to compare clinical information between data sources, with medical record data considered the gold standard.
Results: All 300 breast cancer records reviewed were confirmed breast cancer, while 197 lung and 197 colorectal records were confirmed (PPV =0.99 for each). The agreement of disease stage was 85% for breast, 90% for lung, and 94% for colorectal cancer. The agreement of lung cancer histology (small cell vs non-small cell) was 97%. Agreement of progesterone receptor, estrogen receptor, and human epidermal growth factor receptor 2 status biomarkers in breast cancer was 92%, 97%, and 92%, respectively; epidermal growth factor receptor and anaplastic lymphoma kinase agreement in lung was 97% and 92%, respectively; and agreement of KRAS status in colorectal cancer was 95%. Measures of PPV, NPV, sensitivity, and specificity showed similarly strong evidence of validity.
Conclusion: Good agreement between the HIRE-Oncology data and medical records supports the validity of these data for research.
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.