Evidence map›Paper›PMID 33971832›Full record

ArticleBMC ophthalmology2021

Modeling the impact of COVID-19 on Retina Clinic Performance.

Karan Sethi, Emily S Levine, Shiyoung Roh, Jeffrey L Marx, David J Ramsey

Abstract read
In one paragraph

Article in BMC ophthalmology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Karan SethiTufts University School of Medicine, Boston, Massachusetts, USA.
Emily S LevineTufts University School of Medicine, Boston, Massachusetts, USA.
Shiyoung RohTufts University School of Medicine, Boston, Massachusetts, USA.
Jeffrey L MarxTufts University School of Medicine, Boston, Massachusetts, USA.
David J RamseyTufts University School of Medicine, Boston, Massachusetts, USA. David.J.Ramsey@lahey.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19, a highly contagious respiratory virus, presents unique challenges to ophthalmology practice as a high-volume, office-based specialty. In response to the COVID-19 pandemic, many operational changes were adopted in our ophthalmology clinic to enhance patient and provider safety while maintaining necessary clinical operations. The aim of this study was to evaluate how measures adopted during the pandemic period affected retina clinic performance and patient satisfaction, and to model future clinic flow to predict operational performance under conditions of increasing patient and provider volumes.

methodsClinic event timestamps and demographics were extracted from the electronic medical records of in-person retina encounters from March 15 to May 15, 2020 and compared with the same period in 2019 to assess patient flow through the clinical encounter. Patient satisfaction was evaluated by Press Ganey patient experience surveys obtained from randomly selected outpatient encounters. A discrete-events simulation was designed to model the clinic with COVID-era restrictions to assess operational performance under conditions of increasing patient and provider volumes.

resultsRetina clinic volume declined by 62 % during the COVID-19 health emergency. Average check-in-to-technician time declined 79 %, total visit length declined by 46 %, and time in the provider phase of care declined 53 %. Patient satisfaction regarding access nearly doubled during the COVID-period compared with the prior year (p < 0.0001), while satisfaction with overall care and safety remained high during both periods. A model incorporating COVID-related changes demonstrated that wait time before rooming reached levels similar to the pre-COVID era by 30 patients-per-provider in a 1-provider model and 25 patients-per-provider in a 2-provider model (p < 0.001). Capacity to maintain distancing between patients was exceeded only in the two 2-provider model above 25 patients-per-provider.

conclusionsClinic throughput was optimized in response to the COVID-19 health emergency. Modeling these clinic changes can help plan for eventual volume increases in the setting of limits imposed in the COVID-era.

Indexed as

COVID-19TelemedicineHumansPandemicsPatient SatisfactionRetinaSARS-CoV-2COVID-19Discrete‐event simulationHealth Services ResearchOutpatientPatient flow

Identifiers

PMID33971832
PMCPMC8107774

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.