دورية أكاديمية
A general framework for developing computable clinical phenotype algorithms.
| العنوان: | A general framework for developing computable clinical phenotype algorithms. |
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| المؤلفون: | Carrell DS; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, United States., Floyd JS; Department of Medicine, School of Medicine, University of Washington, Seattle, WA 98195, United States.; Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA 98195, United States., Gruber S; Putnam Data Sciences, LLC, Cambridge, MA 02139, United States., Hazlehurst BL; Center for Health Research, Kaiser Permanente Northwest, Portland, OR 97227, United States., Heagerty PJ; Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA 98195, United States., Nelson JC; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, United States., Williamson BD; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, United States., Ball R; Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD 20993, United States. |
| المصدر: | Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2024 Aug 01; Vol. 31 (8), pp. 1785-1796. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9430800 Publication Model: Print Cited Medium: Internet ISSN: 1527-974X (Electronic) Linking ISSN: 10675027 NLM ISO Abbreviation: J Am Med Inform Assoc Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: 2015- : Oxford : Oxford University Press Original Publication: Philadelphia, PA : Hanley & Belfus, c1993- |
| مواضيع طبية MeSH: | Algorithms* , Electronic Health Records* , Phenotype* , Natural Language Processing*, Humans ; Machine Learning |
| مستخلص: | Objective: To present a general framework providing high-level guidance to developers of computable algorithms for identifying patients with specific clinical conditions (phenotypes) through a variety of approaches, including but not limited to machine learning and natural language processing methods to incorporate rich electronic health record data. Materials and Methods: Drawing on extensive prior phenotyping experiences and insights derived from 3 algorithm development projects conducted specifically for this purpose, our team with expertise in clinical medicine, statistics, informatics, pharmacoepidemiology, and healthcare data science methods conceptualized stages of development and corresponding sets of principles, strategies, and practical guidelines for improving the algorithm development process. Results: We propose 5 stages of algorithm development and corresponding principles, strategies, and guidelines: (1) assessing fitness-for-purpose, (2) creating gold standard data, (3) feature engineering, (4) model development, and (5) model evaluation. Discussion and Conclusion: This framework is intended to provide practical guidance and serve as a basis for future elaboration and extension. (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.) |
| References: | Genet Med. 2013 Oct;15(10):761-71. (PMID: 23743551) Curr Opin Psychiatry. 2017 Sep;30(5):378-388. (PMID: 28700360) PLoS One. 2022 Jul 6;17(7):e0271049. (PMID: 35793324) Eur J Cardiovasc Nurs. 2022 Jan 11;21(1):85-91. (PMID: 34741600) Med Decis Making. 2012 Jan-Feb;32(1):188-97. (PMID: 21393557) Int J Epidemiol. 2023 Aug 2;52(4):1276-1285. (PMID: 36905602) Pharmacoepidemiol Drug Saf. 2018 Oct;27(10):1077-1084. (PMID: 30152575) J Clin Epidemiol. 2011 Jan;64(1):96-106. (PMID: 21130355) Methods Inf Med. 2021 Sep;60(3-04):84-94. (PMID: 34592777) J Biomed Inform. 2009 Apr;42(2):377-81. (PMID: 18929686) J Am Med Inform Assoc. 2015 Sep;22(5):993-1000. (PMID: 25929596) J Am Med Inform Assoc. 2024 Feb 16;31(3):574-582. (PMID: 38109888) J Am Med Inform Assoc. 2020 May 1;27(5):793-797. (PMID: 32279080) J Am Med Inform Assoc. 2013 Jun;20(e1):e147-54. (PMID: 23531748) J Am Med Inform Assoc. 2018 Oct 1;25(10):1359-1365. (PMID: 29788308) Pediatrics. 2011 May;127 Suppl 1:S45-53. (PMID: 21502240) Clin Pharmacol Ther. 2016 Mar;99(3):265-8. (PMID: 26667601) Nat Protoc. 2019 Dec;14(12):3426-3444. (PMID: 31748751) Gut. 2013 Jan;62(1):102-11. (PMID: 23100216) Ann Intern Med. 1999 Mar 16;130(6):515-24. (PMID: 10075620) Drug Saf. 2022 May;45(5):493-510. (PMID: 35579813) J Am Med Inform Assoc. 2012 Mar-Apr;19(2):225-34. (PMID: 22319176) Am J Epidemiol. 2007 Mar 15;165(6):710-8. (PMID: 17182981) J Am Med Inform Assoc. 2019 Nov 1;26(11):1255-1262. (PMID: 31613361) Ann Epidemiol. 1995 Jul;5(4):278-85. (PMID: 8520709) Health Soc Care Community. 2016 May;24(3):260-9. (PMID: 25661202) J Biomed Inform. 2014 Oct;51:280-6. (PMID: 24960203) Nurse Pract. 2021 Feb 1;46(2):44-49. (PMID: 33475330) Gen Hosp Psychiatry. 2004 Sep-Oct;26(5):337-45. (PMID: 15474633) Stat Appl Genet Mol Biol. 2007;6:Article25. (PMID: 17910531) Curr Epidemiol Rep. 2014 Dec;1(4):175-185. (PMID: 26085977) Fed Regist. 1999 May 10;64(89):25049-50. (PMID: 10558535) AIDS Res Hum Retroviruses. 2014 Jul;30(7):626-33. (PMID: 24564256) J Clin Med. 2020 Apr 23;9(4):. (PMID: 32340369) J Am Med Inform Assoc. 2018 Feb 1;25(2):150-157. (PMID: 28645207) BMC Med Inform Decis Mak. 2022 Jan 28;22(1):23. (PMID: 35090449) Epidemiology. 2023 Jan 1;34(1):33-37. (PMID: 36007092) Int J Med Inform. 2008 Apr;77(4):226-34. (PMID: 17556014) AMIA Annu Symp Proc. 2003;:284-8. (PMID: 14728179) Pharmacoepidemiol Drug Saf. 2020 Feb;29(2):182-188. (PMID: 31797475) J Biomed Inform. 2017 Sep;73:14-29. (PMID: 28729030) BMC Health Serv Res. 2018 May 2;18(1):316. (PMID: 29720153) Pharmacoepidemiol Drug Saf. 2013 Nov;22(11):1205-13. (PMID: 24038742) Epidemiology. 2021 May 1;32(3):439-443. (PMID: 33591057) Am J Epidemiol. 2023 Feb 1;192(2):283-295. (PMID: 36331289) BMJ. 2024 Feb 12;384:e076460. (PMID: 38346815) J Am Med Inform Assoc. 2015 Nov;22(6):1251-60. (PMID: 26224336) BMC Med Res Methodol. 2017 Sep 18;17(1):144. (PMID: 28923013) J Allergy Clin Immunol. 2006 Feb;117(2):391-7. (PMID: 16461139) N Engl J Med. 2011 Feb 10;364(6):498-9. (PMID: 21226658) J Biomed Inform. 2012 Aug;45(4):763-71. (PMID: 22326800) Int J Physiol Pathophysiol Pharmacol. 2021 Jun 15;13(3):86-93. (PMID: 34336132) Epidemiology. 2010 Jan;21(1):128-38. (PMID: 20010215) Ment Health Fam Med. 2008 Dec;5(4):229-35. (PMID: 22477874) J Am Med Inform Assoc. 2018 Jan 1;25(1):54-60. (PMID: 29126253) N Engl J Med. 2018 Nov 29;379(22):2091-2093. (PMID: 30485777) Mach Learn Knowl Discov Databases. 2014;8725:225-239. (PMID: 26023687) J Biomed Inform. 2007 Oct;40(5):539-51. (PMID: 17368112) |
| معلومات مُعتمدة: | 75F40119F19002 United States FD FDA HHS |
| فهرسة مساهمة: | Keywords: computable algorithms; health outcomes; modeling methods; recommended practices |
| تواريخ الأحداث: | Date Created: 20240515 Date Completed: 20240719 Latest Revision: 20240721 |
| رمز التحديث: | 20240721 |
| مُعرف محوري في PubMed: | PMC11258420 |
| DOI: | 10.1093/jamia/ocae121 |
| PMID: | 38748991 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 1527-974X |
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| DOI: | 10.1093/jamia/ocae121 |