Evidence map›Paper›PMID 35764976›Full record

ArticleBMC ophthalmology2022

Measuring impact of a quality improvement initiative on glaucoma clinic flow using an automated real-time locating system.

John A Musser, Juno Cho, Amy Cohn, Leslie M Niziol, Dena Ballouz, David T Burke, Paula Anne Newman-Casey

Abstract read
In one paragraph

Article in BMC ophthalmology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

John A Musser *Department of Ophthalmology & Visual Sciences, University of Michigan Medical School, 1000 Wall St, Ann Arbor, MI, 48105, USA.
Juno Cho *Department of Ophthalmology & Visual Sciences, University of Michigan Medical School, 1000 Wall St, Ann Arbor, MI, 48105, USA.
Amy CohnDepartment of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, USA.
Leslie M NiziolDepartment of Ophthalmology & Visual Sciences, University of Michigan Medical School, 1000 Wall St, Ann Arbor, MI, 48105, USA.
Dena BallouzDepartment of Ophthalmology & Visual Sciences, University of Michigan Medical School, 1000 Wall St, Ann Arbor, MI, 48105, USA.
David T BurkeDepartment of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
Paula Anne Newman-CaseyDepartment of Ophthalmology & Visual Sciences, University of Michigan Medical School, 1000 Wall St, Ann Arbor, MI, 48105, USA. panewman@med.umich.edu.

Funding

NRSA Training CoreTL1TR002242 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HOLINSTAT, MICHAEL ALLAN · 2017 to 2021
$2.8M
Improving glaucoma self-management with technology-supported counselorsK23EY025320 · NEI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI NEWMAN-CASEY, PAULA ANNE · 2016 to 2019
$920k
NCATS NIH HHS TL1 TR002242NCATS NIH HHS TL1TR002242NEI NIH HHS K23 EY025320NEI NIH HHS K23EY025320Research to Prevent Blindness Career Development Award
6 · The paper itself

Abstract

backgroundLean methodology helps maximize value by reducing waste, first by defining what value and waste are in a system. In ophthalmology clinics, value is determined by the number of patients flowing through the clinic for a given time. We aimed to increase value using a lean-methodology guided policy change, then assessed its impact on clinic flow using an automated radiofrequency identification (RFID) based real-time locating system (RTLS).

methodsA total of 6813 clinical visits occurred at a single academic institution's outpatient glaucoma clinic between January 5, 2018 to July 3, 2018. Over that period, 1589 patients comprising 1972 (29%) of visits were enrolled, with 1031 clinical visits occurring before and 941 visits after a policy change. The original policy was to refract all patients that improved with pinhole testing. The policy change was not to refract patients with a visual acuity ≥20/30 unless a specific request was made by the patient. Pre-post analysis of an automated time-motion study was conducted for the data collected 3 months before and 3 months after the policy change occurred on March 30, 2018. Changes to process and wait times were summarized using descriptive statistics and fitted to linear mixed regression models adjusting for appointment type, clinic volume, and daily clinic trends.

resultsOne thousand nine hundred twenty-three visits with 1588 patients were included in the analysis. Mean [SD] age was 65.9 [14.7] years and 892 [56.2%] were women. After the policy change, technician process time decreased by 2.9 min (p < 0.0001) while daily clinical patient volume increased from 51.9 ± 16.8 patients to 58.4 ± 17.4 patients (p < 0.038). No significant difference was found in total wait time (p = 0.18) or total visit time (p = 0.83).

conclusionsReal-time locating systems are effective at capturing clinical flow data and assessing clinical practice change initiatives. The refraction policy change was associated with reduced technician process time and overall the clinic was able to care for 7 more patients per day without significantly increasing patient wait time.

Indexed as

GlaucomaQuality ImprovementAdolescentAmbulatory Care FacilitiesFemaleHumansMaleAutomated time and motion studyLean-analysisPre-post analysisProcess time

Identifiers

PMID35764976
PMCPMC9238160

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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.