J Am Med Inform Assoc - Portability of an algorithm to identify rheumatoid arthritis in electronic health records.

Tópicos

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Resumo

JECTIVES: Electronic health records (EHR) can allow for the generation of large cohorts of individuals with given diseases for clinical and genomic research. A rate-limiting step is the development of electronic phenotype selection algorithms to find such cohorts. This study evaluated the portability of a published phenotype algorithm to identify rheumatoid arthritis (RA) patients from EHR records at three institutions with different EHR systems.MATERIALS AND METHODS: Physicians reviewed charts from three institutions to identify patients with RA. Each institution compiled attributes from various sources in the EHR, including codified data and clinical narratives, which were searched using one of two natural language processing (NLP) systems. The performance of the published model was compared with locally retrained models.RESULTS: Applying the previously published model from Partners Healthcare to datasets from Northwestern and Vanderbilt Universities, the area under the receiver operating characteristic curve was found to be 92% for Northwestern and 95% for Vanderbilt, compared with 97% at Partners. Retraining the model improved the average sensitivity at a specificity of 97% to 72% from the original 65%. Both the original logistic regression models and locally retrained models were superior to simple billing code count thresholds.DISCUSSION: These results show that a previously published algorithm for RA is portable to two external hospitals using different EHR systems, different NLP systems, and different target NLP vocabularies. Retraining the algorithm primarily increased the sensitivity at each site.CONCLUSION: Electronic phenotype algorithms allow rapid identification of case populations in multiple sites with little retraining.

Resumo Limpo

jectiv electron health record ehr can allow generat larg cohort individu given diseas clinic genom research ratelimit step develop electron phenotyp select algorithm find cohort studi evalu portabl publish phenotyp algorithm identifi rheumatoid arthriti ra patient ehr record three institut differ ehr systemsmateri method physician review chart three institut identifi patient ra institut compil attribut various sourc ehr includ codifi data clinic narrat search use one two natur languag process nlp system perform publish model compar local retrain modelsresult appli previous publish model partner healthcar dataset northwestern vanderbilt univers area receiv oper characterist curv found northwestern vanderbilt compar partner retrain model improv averag sensit specif origin origin logist regress model local retrain model superior simpl bill code count thresholdsdiscuss result show previous publish algorithm ra portabl two extern hospit use differ ehr system differ nlp system differ target nlp vocabulari retrain algorithm primarili increas sensit siteconclus electron phenotyp algorithm allow rapid identif case popul multipl site littl retrain

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