Evaluating the impact of alternative phenotype definitions on incidence rates across a global data network. Makadia, R., Shoaibi, A., Rao, G. A., Ostropolets, A., Rijnbeek, P. R., Voss, E. A., Duarte-Salles, T., Ramírez-Anguita, J. M., Mayer, M. A., Maljković, F., Denaxas, S., Nyberg, F., Papez, V., Sena, A. G., Alshammari, T. M., Lai, L. Y. H., Haynes, K., Suchard, M. A., Hripcsak, G., & Ryan, P. B. JAMIA Open, 6(4):ooad096, 2023. 2574-2531 Makadia, Rupa Shoaibi, Azza Rao, Gowtham A Ostropolets, Anna Orcid: 0000-0002-0847-6682 Rijnbeek, Peter R Voss, Erica A Orcid: 0000-0002-0651-0613 Duarte-Salles, Talita Orcid: 0000-0002-8274-0357 Ramírez-Anguita, Juan Manuel Mayer, Miguel A Maljković, Filip Denaxas, Spiros Orcid: 0000-0001-9612-7791 Nyberg, Fredrik Orcid: 0000-0003-0892-5668 Papez, Vaclav Orcid: 0000-0002-2123-7993 Sena, Anthony G Orcid: 0000-0001-8630-5347 Alshammari, Thamir M Lai, Lana Y H Haynes, Kevin Suchard, Marc A Orcid: 0000-0001-9818-479x Hripcsak, George Ryan, Patrick B Journal Article United States 2023/11/29 JAMIA Open. 2023 Nov 21;6(4):ooad096. doi: 10.1093/jamiaopen/ooad096. eCollection 2023 Dec.abstract bibtex OBJECTIVE: Developing accurate phenotype definitions is critical in obtaining reliable and reproducible background rates in safety research. This study aims to illustrate the differences in background incidence rates by comparing definitions for a given outcome. MATERIALS AND METHODS: We used 16 data sources to systematically generate and evaluate outcomes for 13 adverse events and their overall background rates. We examined the effect of different modifications (inpatient setting, standardization of code set, and code set changes) to the computable phenotype on background incidence rates. RESULTS: Rate ratios (RRs) of the incidence rates from each computable phenotype definition varied across outcomes, with inpatient restriction showing the highest variation from 1 to 11.93. Standardization of code set RRs ranges from 1 to 1.64, and code set changes range from 1 to 2.52. DISCUSSION: The modification that has the highest impact is requiring inpatient place of service, leading to at least a 2-fold higher incidence rate in the base definition. Standardization showed almost no change when using source code variations. The strength of the effect in the inpatient restriction is highly dependent on the outcome. Changing definitions from broad to narrow showed the most variability by age/gender/database across phenotypes and less than a 2-fold increase in rate compared to the base definition. CONCLUSION: Characterization of outcomes across a network of databases yields insights into sensitivity and specificity trade-offs when definitions are altered. Outcomes should be thoroughly evaluated prior to use for background rates for their plausibility for use across a global network.
@article{RN357,
author = {Makadia, R. and Shoaibi, A. and Rao, G. A. and Ostropolets, A. and Rijnbeek, P. R. and Voss, E. A. and Duarte-Salles, T. and Ramírez-Anguita, J. M. and Mayer, M. A. and Maljković, F. and Denaxas, S. and Nyberg, F. and Papez, V. and Sena, A. G. and Alshammari, T. M. and Lai, L. Y. H. and Haynes, K. and Suchard, M. A. and Hripcsak, G. and Ryan, P. B.},
title = {Evaluating the impact of alternative phenotype definitions on incidence rates across a global data network},
journal = {JAMIA Open},
volume = {6},
number = {4},
pages = {ooad096},
note = {2574-2531 Makadia, Rupa Shoaibi, Azza Rao, Gowtham A Ostropolets, Anna Orcid: 0000-0002-0847-6682 Rijnbeek, Peter R Voss, Erica A Orcid: 0000-0002-0651-0613 Duarte-Salles, Talita Orcid: 0000-0002-8274-0357 Ramírez-Anguita, Juan Manuel Mayer, Miguel A Maljković, Filip Denaxas, Spiros Orcid: 0000-0001-9612-7791 Nyberg, Fredrik Orcid: 0000-0003-0892-5668 Papez, Vaclav Orcid: 0000-0002-2123-7993 Sena, Anthony G Orcid: 0000-0001-8630-5347 Alshammari, Thamir M Lai, Lana Y H Haynes, Kevin Suchard, Marc A Orcid: 0000-0001-9818-479x Hripcsak, George Ryan, Patrick B Journal Article United States 2023/11/29 JAMIA Open. 2023 Nov 21;6(4):ooad096. doi: 10.1093/jamiaopen/ooad096. eCollection 2023 Dec.},
abstract = {OBJECTIVE: Developing accurate phenotype definitions is critical in obtaining reliable and reproducible background rates in safety research. This study aims to illustrate the differences in background incidence rates by comparing definitions for a given outcome. MATERIALS AND METHODS: We used 16 data sources to systematically generate and evaluate outcomes for 13 adverse events and their overall background rates. We examined the effect of different modifications (inpatient setting, standardization of code set, and code set changes) to the computable phenotype on background incidence rates. RESULTS: Rate ratios (RRs) of the incidence rates from each computable phenotype definition varied across outcomes, with inpatient restriction showing the highest variation from 1 to 11.93. Standardization of code set RRs ranges from 1 to 1.64, and code set changes range from 1 to 2.52. DISCUSSION: The modification that has the highest impact is requiring inpatient place of service, leading to at least a 2-fold higher incidence rate in the base definition. Standardization showed almost no change when using source code variations. The strength of the effect in the inpatient restriction is highly dependent on the outcome. Changing definitions from broad to narrow showed the most variability by age/gender/database across phenotypes and less than a 2-fold increase in rate compared to the base definition. CONCLUSION: Characterization of outcomes across a network of databases yields insights into sensitivity and specificity trade-offs when definitions are altered. Outcomes should be thoroughly evaluated prior to use for background rates for their plausibility for use across a global network.},
keywords = {algorithms
electronic health record
incidence study
phenotype ,
ISSN = 2574-2531 ,
DOI = 10.1093/jamiaopen/ooad096},
year = {2023},
type = {Journal Article}
}
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The strength of the effect in the inpatient restriction is highly dependent on the outcome. Changing definitions from broad to narrow showed the most variability by age/gender/database across phenotypes and less than a 2-fold increase in rate compared to the base definition. CONCLUSION: Characterization of outcomes across a network of databases yields insights into sensitivity and specificity trade-offs when definitions are altered. Outcomes should be thoroughly evaluated prior to use for background rates for their plausibility for use across a global network.","keywords":"algorithms electronic health record incidence study phenotype , ISSN = 2574-2531 , DOI = 10.1093/jamiaopen/ooad096","year":"2023","bibtex":"@article{RN357,\r\n author = {Makadia, R. and Shoaibi, A. and Rao, G. A. and Ostropolets, A. and Rijnbeek, P. R. and Voss, E. A. and Duarte-Salles, T. and Ramírez-Anguita, J. M. and Mayer, M. A. and Maljković, F. and Denaxas, S. and Nyberg, F. and Papez, V. and Sena, A. 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