Literature DB >> 32678424

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

Nikhil K Bommakanti1,2, Yunshu Zhou1,2, Joshua R Ehrlich1,2, Angela R Elam1,2, Denise John1, Shivani S Kamat1, Jared Kelstrom1, Paula Anne Newman-Casey1,2, Manjool M Shah1, Jennifer S Weizer1, Sarah D Wood1, Amy D Zhang1, Jason Zhang1, Paul P Lee1,2, Joshua D Stein1,2,3.   

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.

Entities:  

Mesh:

Year:  2020        PMID: 32678424      PMCID: PMC7368237          DOI: 10.1001/jamaophthalmol.2020.2974

Source DB:  PubMed          Journal:  JAMA Ophthalmol        ISSN: 2168-6165            Impact factor:   7.389


  8 in total

1.  Evaluating and Improving an Outpatient Clinic Scheduling Template Using Secondary Electronic Health Record Data.

Authors:  Michelle R Hribar; Sarah Read-Brown; Leah Reznick; Michael F Chiang
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

2.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.

Authors:  M E Charlson; P Pompei; K L Ales; C R MacKenzie
Journal:  J Chronic Dis       Date:  1987

3.  Presumed Asymptomatic Carrier Transmission of COVID-19.

Authors:  Yan Bai; Lingsheng Yao; Tao Wei; Fei Tian; Dong-Yan Jin; Lijuan Chen; Meiyun Wang
Journal:  JAMA       Date:  2020-04-14       Impact factor: 56.272

4.  Secondary use of electronic health record data for clinical workflow analysis.

Authors:  Michelle R Hribar; Sarah Read-Brown; Isaac H Goldstein; Leah G Reznick; Lorinna Lombardi; Mansi Parikh; Winston Chamberlain; Michael F Chiang
Journal:  J Am Med Inform Assoc       Date:  2018-01-01       Impact factor: 4.497

5.  Evaluation of an Algorithm for Identifying Ocular Conditions in Electronic Health Record Data.

Authors:  Joshua D Stein; Moshiur Rahman; Chris Andrews; Joshua R Ehrlich; Shivani Kamat; Manjool Shah; Erin A Boese; Maria A Woodward; Jeff Cowall; Edward H Trager; Prabha Narayanaswamy; David A Hanauer
Journal:  JAMA Ophthalmol       Date:  2019-05-01       Impact factor: 7.389

6.  Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany.

Authors:  Camilla Rothe; Mirjam Schunk; Peter Sothmann; Gisela Bretzel; Guenter Froeschl; Claudia Wallrauch; Thorbjörn Zimmer; Verena Thiel; Christian Janke; Wolfgang Guggemos; Michael Seilmaier; Christian Drosten; Patrick Vollmar; Katrin Zwirglmaier; Sabine Zange; Roman Wölfel; Michael Hoelscher
Journal:  N Engl J Med       Date:  2020-01-30       Impact factor: 91.245

7.  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.

Authors:  Zunyou Wu; Jennifer M McGoogan
Journal:  JAMA       Date:  2020-04-07       Impact factor: 56.272

8.  Severe Outcomes Among Patients with Coronavirus Disease 2019 (COVID-19) - United States, February 12-March 16, 2020.

Authors: 
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-03-27       Impact factor: 17.586

  8 in total
  11 in total

1.  Data Sources for Evaluating Health Disparities in Ophthalmology: Where We Are and Where We Need to Go.

Authors:  Sally L Baxter; Kristen Nwanyanwu; Gary Legault; Aaron Y Lee
Journal:  Ophthalmology       Date:  2022-09-01       Impact factor: 14.277

2.  Evaluation of the Nallasamy formula: a stacking ensemble machine learning method for refraction prediction in cataract surgery.

Authors:  Tingyang Li; Joshua Stein; Nambi Nallasamy
Journal:  Br J Ophthalmol       Date:  2022-04-04       Impact factor: 5.908

Review 3.  COVID-19 and retinal degenerative diseases: Promising link "Kaempferol".

Authors:  Arman Firoz; Priti Talwar
Journal:  Curr Opin Pharmacol       Date:  2022-04-14       Impact factor: 4.768

Review 4.  Gaps in standards for integrating artificial intelligence technologies into ophthalmic practice.

Authors:  Sally L Baxter; Aaron Y Lee
Journal:  Curr Opin Ophthalmol       Date:  2021-09-01       Impact factor: 4.299

Review 5.  [Diagnostics of diseases of the optic nerve head in times of artificial intelligence and big data].

Authors:  R Diener; M Treder; N Eter
Journal:  Ophthalmologe       Date:  2021-04-22       Impact factor: 1.059

Review 6.  Ocular and Systemic Complications of COVID-19: Impact on Patients and Healthcare.

Authors:  Ella H Leung; Jason Fan; Harry W Flynn; Thomas A Albini
Journal:  Clin Ophthalmol       Date:  2022-01-04

7.  Audit of outcomes following attendance at the City West drive-through IOP glaucoma clinic during the COVID-19 pandemic.

Authors:  Sarah Powell; Emer Doolan; Karen Curtin; Aoife Doyle; Colm O'Brien
Journal:  Ir J Med Sci       Date:  2022-01-16       Impact factor: 2.089

8.  Evaluation of machine learning algorithms for trabeculectomy outcome prediction in patients with glaucoma.

Authors:  Hasan Ul Banna; Ahmed Zanabli; Brian McMillan; Maria Lehmann; Sumeet Gupta; Michael Gerbo; Joel Palko
Journal:  Sci Rep       Date:  2022-02-15       Impact factor: 4.379

9.  Challenges in managing glaucoma-related morbidity due to lockdown in a developing country.

Authors:  Saswati Sen; Matuli Das; Manmath Kumar Das; Snehalata Dash
Journal:  J Family Med Prim Care       Date:  2022-03-18

10.  Impact of COVID-19-Related Lockdown on Glaucoma Patients

Authors:  Mine Esen Barış; Mukaddes Damla Çiftçi; Suzan Güven Yılmaz; Halil Ateş
Journal:  Turk J Ophthalmol       Date:  2022-04-28
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