Evidence map›Paper›PMID 24874566›Full record

ArticlePloS one2014

Variability in costs across hospital wards. A study of Chinese hospitals.

Taghreed Adam, David B Evans, Bian Ying, Christopher J L Murray

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Influencing factors of inpatient expenditure pattern for cancer in China, 2015.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2017
    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

4 authors.

Taghreed AdamAlliance for Health Policy and Systems Research, World Health Organization, Geneva, Switzerland.
David B EvansHealth Systems Governance and Financing, World Health Organization, Geneva, Switzerland.
Bian YingInstitute of Chinese Medical Sciences, University of Macau, Macau, China.
Christopher J L MurrayInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.

Funding

World Health Organization 001
6 · The paper itself

Abstract

introductionAnalysts estimating the costs or cost-effectiveness of health interventions requiring hospitalization often cut corners because they lack data and the costs of undertaking full step-down costing studies are high. They sometimes use the costs taken from a single hospital, sometimes use simple rules of thumb for allocating total hospital costs between general inpatient care and the outpatient department, and sometimes use the average cost of an inpatient bed-day instead of a ward-specific cost. PURPOSE: In this paper we explore for the first time the extent and the causes of variation in ward-specific costs across hospitals, using data from China. We then use the resulting model to show how ward-specific costs for hospitals outside the data set could be estimated using information on the determinants identified in the paper. METHODOLOGY: Ward-specific costs estimated using step-down costing methods from 41 hospitals in 12 provinces of China were used. We used seemingly unrelated regressions to identify the determinants of variability in the ratio of the costs of specific wards to that of the outpatient department, and explain how this can be used to generate ward-specific unit costs.

findingsWard-specific unit costs varied considerably across hospitals, ranging from 1 to 24 times the unit cost in the outpatient department--average unit costs are not a good proxy for costs at specialty wards in general. The most important sources of variability were the number of staff and the level of capacity utilization. PRACTICE IMPLICATIONS: More careful hospital costing studies are clearly needed. In the meantime, we have shown that in China it is possible to estimate ward-specific unit costs taking into account key determinants of variability in costs across wards. This might well be a better alternative than using simple rules of thumb or using estimates from a single study.

Indexed as

Cost-Benefit AnalysisHospital CostsChinaHospitalizationHumansModels, Statistical

Identifiers

PMID24874566
PMCPMC4038551

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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.