Evidence map›Paper›PMID 29027078›Full record

ArticleJournal of medical systems2017

Dynamic Scheduling for Veterans Health Administration Patients using Geospatial Dynamic Overbooking.

Stephen Adams, William T Scherer, K Preston White, Jason Payne, Oved Hernandez, Mathew S Gerber, N Peter Whitehead

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Stephen AdamsDepartment of Systems and Information Engineering, University of Virginia, 151 Engineer's Way, Charlottesville, VA, 22904, USA. sca2c@virginia.edu.ORCID http://orcid.org/0000-0002-1207-4504
William T SchererDepartment of Systems and Information Engineering, University of Virginia, 151 Engineer's Way, Charlottesville, VA, 22904, USA.
K Preston WhiteDepartment of Systems and Information Engineering, University of Virginia, 151 Engineer's Way, Charlottesville, VA, 22904, USA.
Jason PayneDepartment of Systems and Information Engineering, University of Virginia, 151 Engineer's Way, Charlottesville, VA, 22904, USA.
Oved HernandezDepartment of Systems and Information Engineering, University of Virginia, 151 Engineer's Way, Charlottesville, VA, 22904, USA.
Mathew S GerberDepartment of Systems and Information Engineering, University of Virginia, 151 Engineer's Way, Charlottesville, VA, 22904, USA.
N Peter WhiteheadSystems Engineering Technical Center, The Mitre Corporation, McClean, VA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Veterans Health Administration (VHA) is plagued by abnormally high no-show and cancellation rates that reduce the productivity and efficiency of its medical outpatient clinics. We address this issue by developing a dynamic scheduling system that utilizes mobile computing via geo-location data to estimate the likelihood of a patient arriving on time for a scheduled appointment. These likelihoods are used to update the clinic's schedule in real time. When a patient's arrival probability falls below a given threshold, the patient's appointment is canceled. This appointment is immediately reassigned to another patient drawn from a pool of patients who are actively seeking an appointment. The replacement patients are prioritized using their arrival probability. Real-world data were not available for this study, so synthetic patient data were generated to test the feasibility of the design. The method for predicting the arrival probability was verified on a real set of taxicab data. This study demonstrates that dynamic scheduling using geo-location data can reduce the number of unused appointments with minimal risk of double booking resulting from incorrect predictions. We acknowledge that there could be privacy concerns with regards to government possession of one's location and offer strategies for alleviating these concerns in our conclusion.

Indexed as

Appointments and SchedulesCell PhoneEfficiency, OrganizationalSpatio-Temporal AnalysisAlgorithmsAmbulatory Care FacilitiesComputer SimulationHumansTime FactorsUnited StatesUnited States Department of Veterans AffairsGeo-location dataPatient trackingSchedule updating

Identifiers

PMID29027078

What OpenQuestion holds

Textmetadata
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.