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Assessing Resident Cataract Surgical Outcomes Using Electronic Health Record Data

OBJECTIVE: To demonstrate that electronic health record (EHR) data can be used in an automated approach to evaluate cataract surgery outcomes. DESIGN: Retrospective analysis. SUBJECTS: Resident and faculty surgeons. METHODS: Electronic health record data were collected from cataract surgeries perfor...

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Autores principales: Xiao, Grace, Srikumaran, Divya, Sikder, Shameema, Woreta, Fasika, Boland, Michael V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9852949/
https://www.ncbi.nlm.nih.gov/pubmed/36685714
http://dx.doi.org/10.1016/j.xops.2022.100260
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author Xiao, Grace
Srikumaran, Divya
Sikder, Shameema
Woreta, Fasika
Boland, Michael V.
author_facet Xiao, Grace
Srikumaran, Divya
Sikder, Shameema
Woreta, Fasika
Boland, Michael V.
author_sort Xiao, Grace
collection PubMed
description OBJECTIVE: To demonstrate that electronic health record (EHR) data can be used in an automated approach to evaluate cataract surgery outcomes. DESIGN: Retrospective analysis. SUBJECTS: Resident and faculty surgeons. METHODS: Electronic health record data were collected from cataract surgeries performed at the Johns Hopkins Wilmer Eye Institute, and cases were categorized into resident or attending as primary surgeon. Preoperative and postoperative visual acuity (VA) and unplanned return to operating room were extracted from the EHR. MAIN OUTCOME MEASURES: Postoperative VA and reoperation rate within 90 days. RESULTS: This study analyzed 14 537 cataract surgery cases over 32 months. Data were extracted from the EHR using an automated approach to assess surgical outcomes for resident and attending surgeons. Of 337 resident surgeries with both preoperative and postoperative VA data, 248 cases (74%) had better postoperative VA, and 170 cases (51%) had more than 2 lines improvement. There was no statistical difference in the proportion of cases with better postoperative VA or more than 2 lines improvement between resident and attending cases. Attending surgeons had a statistically greater proportion of cases with postoperative VA better than 20/40, but this finding has to be considered in the context that, on average, resident cases started out with poorer baseline VA. A multivariable regression model of VA outcomes vs. resident/attending status that controlled for preoperative VA, patient age, American Society of Anesthesiologists (ASA) score, and estimated income found that resident status, preoperative VA, patient age, ASA score, and estimated income were all significant predictors of VA. The rate of unplanned return to the operating room within 90 days of cataract surgery was not statistically different between resident (1.8%) and attending (1.2%) surgeons. CONCLUSIONS: This study demonstrates that EHR data can be used to evaluate and monitor surgical outcomes in an ongoing way. Analysis of EHR-extracted cataract outcome data showed that preoperative VA, ASA classification, and attending/resident status were important in predicting postoperative VA outcomes. These findings suggest that the utilization of EHR data could enable continuous assessment of surgical outcomes and inform interventions to improve resident training.Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.
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spelling pubmed-98529492023-01-21 Assessing Resident Cataract Surgical Outcomes Using Electronic Health Record Data Xiao, Grace Srikumaran, Divya Sikder, Shameema Woreta, Fasika Boland, Michael V. Ophthalmol Sci Original Article OBJECTIVE: To demonstrate that electronic health record (EHR) data can be used in an automated approach to evaluate cataract surgery outcomes. DESIGN: Retrospective analysis. SUBJECTS: Resident and faculty surgeons. METHODS: Electronic health record data were collected from cataract surgeries performed at the Johns Hopkins Wilmer Eye Institute, and cases were categorized into resident or attending as primary surgeon. Preoperative and postoperative visual acuity (VA) and unplanned return to operating room were extracted from the EHR. MAIN OUTCOME MEASURES: Postoperative VA and reoperation rate within 90 days. RESULTS: This study analyzed 14 537 cataract surgery cases over 32 months. Data were extracted from the EHR using an automated approach to assess surgical outcomes for resident and attending surgeons. Of 337 resident surgeries with both preoperative and postoperative VA data, 248 cases (74%) had better postoperative VA, and 170 cases (51%) had more than 2 lines improvement. There was no statistical difference in the proportion of cases with better postoperative VA or more than 2 lines improvement between resident and attending cases. Attending surgeons had a statistically greater proportion of cases with postoperative VA better than 20/40, but this finding has to be considered in the context that, on average, resident cases started out with poorer baseline VA. A multivariable regression model of VA outcomes vs. resident/attending status that controlled for preoperative VA, patient age, American Society of Anesthesiologists (ASA) score, and estimated income found that resident status, preoperative VA, patient age, ASA score, and estimated income were all significant predictors of VA. The rate of unplanned return to the operating room within 90 days of cataract surgery was not statistically different between resident (1.8%) and attending (1.2%) surgeons. CONCLUSIONS: This study demonstrates that EHR data can be used to evaluate and monitor surgical outcomes in an ongoing way. Analysis of EHR-extracted cataract outcome data showed that preoperative VA, ASA classification, and attending/resident status were important in predicting postoperative VA outcomes. These findings suggest that the utilization of EHR data could enable continuous assessment of surgical outcomes and inform interventions to improve resident training.Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references. Elsevier 2022-12-05 /pmc/articles/PMC9852949/ /pubmed/36685714 http://dx.doi.org/10.1016/j.xops.2022.100260 Text en © 2022 Published by Elsevier Inc. on behalf of American Academy of Ophthalmology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Xiao, Grace
Srikumaran, Divya
Sikder, Shameema
Woreta, Fasika
Boland, Michael V.
Assessing Resident Cataract Surgical Outcomes Using Electronic Health Record Data
title Assessing Resident Cataract Surgical Outcomes Using Electronic Health Record Data
title_full Assessing Resident Cataract Surgical Outcomes Using Electronic Health Record Data
title_fullStr Assessing Resident Cataract Surgical Outcomes Using Electronic Health Record Data
title_full_unstemmed Assessing Resident Cataract Surgical Outcomes Using Electronic Health Record Data
title_short Assessing Resident Cataract Surgical Outcomes Using Electronic Health Record Data
title_sort assessing resident cataract surgical outcomes using electronic health record data
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9852949/
https://www.ncbi.nlm.nih.gov/pubmed/36685714
http://dx.doi.org/10.1016/j.xops.2022.100260
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