Evidence map›Paper›PMID 32078081›Full record

ArticleHealth care management science2020

Designing schedule configuration of a hybrid appointment system for a two-stage outpatient clinic with multiple servers.

Sharan Srinivas, A Ravi Ravindran

Abstract read
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Article in Health care management science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
4.4field-weighted citation impact, top 4% of its field
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

7 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Article
  3. Analysis of the Waiting Time in Clinic Registration of Patients with Appointments and Random Walk-Ins.International journal of environmental research and public health · 2023
    Article
  4. Article
  5. Article
  6. A Machine Learning-Based Approach for Predicting Patient Punctuality in Ambulatory Care Centers.International journal of environmental research and public health · 2020
    Article
  7. 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

2 authors at 2 institutions in 1 country.

Sharan SrinivasDepartment of Industrial and Manufacturing Systems Engineering, College of Engineering, University of Missouri, Columbia, MO, 65211, USA. SrinivasSh@missouri.edu.ORCID http://orcid.org/0000-0003-2066-8836
A Ravi RavindranDepartment of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA, 16802, USA.
Missouri College · USPennsylvania State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Even though several clinics serve patients in more than one stage (e.g., visit nurse and then visit doctor) and employ multiple providers in each stage, most of the previous work on appointment system design considers a simplified single-stage single-server clinic. Motivated by a real-life clinic setting, this paper aims to determine the schedule configuration of a hybrid appointment system (i.e., the number of pre-booking and same-day time slots reserved for a physician along with their positions in the schedule) for a two-stage multi-server clinic. A stochastic optimization model is developed to obtain a schedule configuration that minimizes the expected total cost - a weighted sum of excessive patient waiting time, resource idle time, resource overtime, and denied appointment requests. Owing to its computational complexity, we estimate the expected total cost using the sample average approximation method. The proposed model is verified and validated using small test instances and subject matter experts. A case study of a family medicine clinic in Pennsylvania is used to illustrate the proposed approach. The schedule generated by the proposed model results in a significantly lower expected cost compared to the approximated single-stage system's best schedule configuration and clinic's existing configuration. Further, sensitivity analysis is conducted to assess the impacts of no-show rate, service time variation, and cost ratios on the schedule configuration. Our findings demonstrate that the schedule configuration is sensitive to changes in the average no-show rate and cost ratios but is not significantly impacted by service time variation. Several managerial insights are also drawn from our analysis. Finally, we provide directions for future research that also highlights the potential to use the revenue management approach to address the problem under study.

Indexed as

Appointments and SchedulesModels, OrganizationalAmbulatory Care FacilitiesEfficiency, OrganizationalHumansNo-Show PatientsPennsylvaniaStochastic ProcessesTime FactorsWaiting ListsAppointment system designOpen accessOR in health servicesOutpatient clinicSample average approximationSchedulingStochastic optimizationTwo-stage multi-server clinic

Identifiers

PMID32078081
OpenAlexW3008172178

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.