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Coronavirus (COVID-19)

Application of the Sight Outcomes Research Collaborative Ophthalmology Data Repository for Triaging Patients With Glaucoma and Clinic Appointments During Pandemics Such as COVID-19

Educational Objective
To describe a flexible and scalable scoring algorithm for patients with glaucoma that considers glaucoma severity and progression risk vs the presence of high-risk features for morbidity from coronavirus disease 2019 (COVID-19), using information from a large data repository.

1 Credit CME

JAMA Ophthalmology

Published Online: July 17, 2020

Original Investigation

Article Information and Disclosures

Nikhil K. Bommakanti, MD^1,2;

Yunshu Zhou, MS^1,2;

Joshua R. Ehrlich, MD, MPH^1,2;

Angela R. Elam, MD^1,2;

Denise John, MD¹;

Shivani S. Kamat, MD¹;

Jared Kelstrom, MD¹;

Paula Anne Newman-Casey, MD, MS^1,2;

Manjool M. Shah, MD¹;

Jennifer S. Weizer, MD¹;

Sarah D. Wood, OD¹;

Amy D. Zhang, MD¹;

Jason Zhang, MD¹;

Paul P. Lee, MD, JD^1,2;

Joshua D. Stein, MD, MS^1,2,3;

SOURCE Consortium

Author Affiliations

¹W.K. Kellogg Eye Center, Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor
²Center for Eye Policy and Innovation, University of Michigan, Ann Arbor
³Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor

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Key Points

Question During a pandemic, can researchers use large data sets to help ophthalmology clinics identify upcoming glaucoma appointments to safely postpone and prioritize appointments for rescheduling during ramp-up (reopening) periods?

Findings In this cross-sectional study, an algorithm was developed that considered glaucoma severity and progression risk plus the morbidity risk from potential coronavirus disease 2019 exposure for 1034 upcoming glaucoma patient appointments. It identified patients whose appointments could safely get postponed and facilitated prioritization of appointments for rescheduling.

Meaning These findings suggest that researchers can leverage big data to triage ophthalmic clinic appointments, balancing the glaucoma progression risk against the morbidity risk from coronavirus disease 2019 exposure during ophthalmic care.

Abstract

Importance During the coronavirus disease 2019 (COVID-19) pandemic, eye care professionals caring for patients with sight-threatening diseases, such as glaucoma, have had to determine whether some patient appointments could safely get postponed, weighing the risk that the patient’s glaucoma could worsen during the interim vs the morbidity risk of acquiring COVID-19 while seeking ophthalmic care. They also need to prioritize appointment rescheduling during the ramp-up phase (when pandemic-associated service reductions are eased).

Objective To describe a flexible and scalable scoring algorithm for patients with glaucoma that considers glaucoma severity and progression risk vs the presence of high-risk features for morbidity from COVID-19, using information from a large data repository.

Design, Setting, and Participants In this cross-sectional study, patients with upcoming clinic appointments for glaucoma from March 16, 2020, to April 16, 2020, at an academic institution enrolled in the Sight Outcomes Research Collaborative (SOURCE) Ophthalmology Electronic Health Record Data Repository were identified. A risk stratification tool was developed that calculated a glaucoma severity and progression risk score and a COVID-19 morbidity risk score. These scores were summed to determine a total score for each patient.

Main Outcomes and Measures Total scores and percentages of clinic appointments recommended for rescheduling.

Results Among the 1034 patients with upcoming clinic appointments for glaucoma, the mean (SD) age was 66.7 (14.6) years. There were 575 women (55.6%), 733 White individuals (71%), and 160 Black individuals (15.5%). The mean (SD) glaucoma severity and progression risk score was 4.0 (14.4) points, the mean (SD) COVID-19 morbidity risk score was 27.2 (16.1) points, and the mean (SD) total score was 31.2 (21.4) points. During pandemic-associated reductions in services, using total score thresholds of 0, 25, and 50 points would identify 970 appointments (93.8%), 668 appointments (64.6%), and 275 appointments (26.6%), respectively, for postponement and rescheduling. The algorithm-generated total scores also helped prioritize appointment rescheduling during the ramp-up phase.

Conclusions and Relevance A tool that considers the risk of underlying ophthalmic disease progression from delayed care receipt and the morbidity risk from COVID-19 exposure was developed and implemented, facilitating the triage of upcoming ophthalmic appointments. Comparable approaches for other ophthalmic and nonophthalmic care during the COVID-19 pandemic and similar crises may be created using this methodology.

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Article Information

Accepted for Publication: June 28, 2020.

Corresponding Author: Joshua D. Stein, MD, MS, W.K. Kellogg Eye Center, Department of Ophthalmology and Visual Sciences, University of Michigan, 1000 Wall St, Ann Arbor, MI 48105 (jdstein@med.umich.edu).

Published Online: July 17, 2020. doi:10.1001/jamaophthalmol.2020.2974

Author Contributions: Dr Stein had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Bommakanti, A. Zhang, J. Zhang, Lee, Stein.

Acquisition, analysis, or interpretation of data: Bommakanti, Zhou, Ehrlich, Elam, John, Kamat, Kelstrom, Newman-Casey, Shah, Weizer, Wood, Stein.

Drafting of the manuscript: Bommakanti, Stein.

Critical revision of the manuscript for important intellectual content: Bommakanti, Zhou, Ehrlich, Elam, John, Kamat, Kelstrom, Newman-Casey, Shah, Weizer, Wood, A. Zhang, J. Zhang, Lee.

Statistical analysis: Bommakanti, Zhou.

Administrative, technical, or material support: Zhou, Ehrlich, Kamat, Kelstrom, Weizer, A. Zhang, J. Zhang, Lee.

Supervision: Stein.

Other—tested this approach in my patient scheduling: Weizer.

Conflict of Interest Disclosure: Dr Ehrlich reported grants from National Institutes of Health during the conduct of the study. Dr Newman-Casey reported grants from National Eye Institute, Research to Prevent Blindness, and the Centers for Disease Control and Prevention during the conduct of the study. Dr Shah reported personal fees from Glaukos, Allergan, and Katena outside the submitted work. Dr Lee reported receiving grants from Research to Prevent Blindness; having received consulting fees from the Centers for Disease Control and Prevention; holding stocks in Pfizer, GSK, Merck, and Medco Health Solutions; and having received an honorarium from Alcon Research Institute outside the submitted work. Dr Stein reported grants from National Eye Institute during the conduct of the study. No other disclosures were reported.

Funding/Support: This study was supported by Lighthouse Guild, National Eye Institute (grant R01 EY026641), and the Beverley and Gerson Geltner Fund.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Members of the SOURCE Consortium: Stanford University Byers Eye Institute, Palo Alto, California: Suzann Pershing and Sophia Y. Wang; Henry Ford Health System, Detroit, Michigan: Sejal Amin and Paul A. Edwards; Montefiore Medical Center, Bronx, New York: Jeffrey S. Schultz and Anurag Shrivastava; Medical College of Wisconsin, Milwaukee: Baseer Ahmad; Scheie Eye Institute, University of Pennsylvania, Philadelphia: Brian L. Vanderbeek; Rocky Mountain Lions Eye Institute, University of Colorado, Aurora: Anne M. Lynch and Prem S. Subramanian; University of California, San Francisco, San Francisco: Michael Deiner and Catherine Q. Sun; Moran Eye Center, The University of Utah, Salt Lake City: Brian C. Stagg; West Virginia University Eye Institute, Morgantown: Brian McMillian and Anthony Realini.

References

World Health Organization. WHO Director-General’s opening remarks at the media briefing on COVID-19—11 March 2020. Published March 11, 2020. Accessed March 16, 2020. https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020

Bialek S , Boundy E , Bowen V , et al; CDC COVID-19 Response Team. Severe outcomes among patients with coronavirus disease 2019 (COVID-19)—United States, February 12-March 16, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(12):343-346. doi:10.15585/mmwr.mm6912e2 PubMed Google Scholar Crossref

American Academy of Ophthalmology. New recommendations for urgent and nonurgent patient care. Published March 18, 2020. Accessed March 20, 2020. https://www.aao.org/headline/new-recommendations-urgent-nonurgent-patient-care

Wu Z , McGoogan JM . Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;323(13):1239-1242. doi:10.1001/jama.2020.2648 PubMed Google Scholar Crossref

Bai Y , Yao L , Wei T , et al. Presumed asymptomatic carrier transmission of COVID-19. JAMA. 2020;323(14):1406-1407. doi:10.1001/jama.2020.2565 PubMed Google Scholar Crossref

Rothe C , Schunk M , Sothmann P , et al. Transmission of 2019-nCoV infection from an asymptomatic contact in Germany. N Engl J Med. 2020;382(10):970-971. doi:10.1056/NEJMc2001468 PubMed Google Scholar Crossref

American Academy of Ophthalmology. Returning to ophthalmology practice. Published March 18, 2020. Accessed May 18, 2020. https://www.aao.org/about/governance/academy-blog/post/returning-to-ophthalmology-practice

Stein JD , Rahman M , Andrews C , et al. Evaluation of an algorithm for identifying ocular conditions in electronic health record data. JAMA Ophthalmol. 2019;137(5):491-497. doi:10.1001/jamaophthalmol.2018.7051 PubMed Google Scholar Crossref

Charlson ME , Pompei P , Ales KL , MacKenzie CR . A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383. doi:10.1016/0021-9681(87)90171-8 PubMed Google Scholar Crossref

Hribar MR , Read-Brown S , Reznick L , Chiang MF . Evaluating and improving an outpatient clinic scheduling template using secondary electronic health record data. AMIA Annu Symp Proc. 2018;2017:921-929.PubMed Google Scholar

Hribar MR , Read-Brown S , Goldstein IH , et al. Secondary use of electronic health record data for clinical workflow analysis. J Am Med Inform Assoc. 2018;25(1):40-46. doi:10.1093/jamia/ocx098 PubMed Google Scholar Crossref

AMA CME Accreditation Information

Credit Designation Statement: The American Medical Association designates this Journal-based CME activity activity for a maximum of 1.00  AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to:

1.00 Medical Knowledge MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program;;
1.00 Self-Assessment points in the American Board of Otolaryngology – Head and Neck Surgery’s (ABOHNS) Continuing Certification program;
1.00 MOC points in the American Board of Pediatrics’ (ABP) Maintenance of Certification (MOC) program;
1.00 Lifelong Learning points in the American Board of Pathology’s (ABPath) Continuing Certification program; and
1.00 CME points in the American Board of Surgery’s (ABS) Continuing Certification program

It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting MOC credit.