Evidence map›Paper›PMID 32770444›Full record

ArticleHealth care management science2020

Optimal cost adjustment for a selfish routing healthcare network.

Young Hoon Lee, Yong Ho Choi

Abstract read
PubMed Publisher
In one paragraph

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 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 28% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. 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 1 institution in 1 country.

Young Hoon LeeYonsei University, 50 yonsei-ro seodaemun-gu, Seoul, South Korea.
Yong Ho ChoiYonsei University, 50 yonsei-ro seodaemun-gu, Seoul, South Korea. gogho@naver.com.ORCID http://orcid.org/0000-0002-2477-1112
Yonsei University · KR

Funding

National Research Foundation of Korea 2017R1E1A1A03070757
6 · The paper itself

Abstract

South Korea's large hospitals are severely burdened by patient congestion because patients throng to these places expecting to get treated better given their higher-quality healthcare. Effective cost management of the healthcare system is one way to reduce patient congestion in a large hospital. This study proposes methods that can help direct patient flows in a desirable direction and suggests ways to effectively manage the cost of healthcare. The study also discusses how selfish patients act in ways that maximize their benefits by choosing a specific hospital and in turn forcing the hospital and the healthcare network to bear more costs than is necessary. The study proposes a model describing the need for intervention from the government to control the cost escalation resulting from selfish routing. The study proposes two heuristic algorithms to solve the suggested model. The flow-based algorithm addresses the target quantum of flows, and the utility-based algorithm targets the value of cost functions. Performances of heuristics are evaluated through numerical experiments. The utility-based algorithm yields higher values for objectives, while the flow-based algorithm controls the extent of investment. A case study based on data from the Seoul city database is also analyzed. The cost adjustment policy is compared with simple, uniformly improved network policies, and findings show that such policies have the strength needed to improve the cost-effectiveness of the healthcare system if implemented fully and effectively.

Indexed as

Cost-Benefit AnalysisCosts and Cost AnalysisEconomics, HospitalAlgorithmsChoice BehaviorDelivery of Health CareHeuristicsHospitalsHumansOrganizational Case StudiesRepublic of KoreaCost adjustmentHealthcare congestion networkHeuristicOperations researchWardrop equilibrium

Identifiers

PMID32770444
OpenAlexW3047960146

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.