Evidence map›Paper›PMID 20945101›Full record

ArticleHealth care management science2011

Time for a new budget allocation model for hospital care in Stockholm?

Per-Åke Andersson, Daniel Bruce, Anders Walander, Inga Viberg

Abstract read
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In one paragraph

Article in Health care management science, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Per-Åke AnderssonDepartment of Public Health Sciences, Karolinska institutet, Stockholm, Sweden. panoa@telia.com
Daniel Bruce
Anders Walander
Inga Viberg

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In Stockholm County Council (SLL), budgets for hospital care have been allocated to geographically responsible authorities for a long time. This hospital care includes all publicly financed specialist care, also privately owned hospitals, except private practitioner care. The old needs-index model, a 6D capitation matrix based on demography and socio-economy, was generated on linked individual data for 1994-96. In this paper the power of the old allocation model is evaluated by the use of new data for 2006. The analysis shows that most of the socioeconomic variables have lost their descriptive power in 10 years. Using a methodical search we also find an improved need-based allocation model for hospital care using the new data for 2006. By focusing on costly diagnoses, where the descriptive power has increased between 1996 and 2006, and by using some new socioeconomic variables, and by relying on birth and death prognoses, we are able to generate a matrix model with much higher coefficients-of-determinations in 1 year predictions. In addition, a more careful modelling of multi-morbidity, part-of-the-year inhabitants, episode definition and cost transformation is developed. The area-level cost residuals of registered versus predicted costs show stable signs over the years, indicating unexplained systematics. For the reduction of the residuals, accepting proven inpatient diagnoses but not the full costs, a mixed capitation/fee-for-service strategy is discussed. Once equivalent (e.g. full-year) observations are determined, the link between background and consumption is not on individual-level but on cell-level, as in current resource allocation studies in the United Kingdom.

Indexed as

Computer SimulationAdultAgedAge FactorsBudgetsFemaleHealth Care RationingHospital CostsHumansMaleMiddle AgedModels, EconomicSex FactorsSocioeconomic FactorsState MedicineSweden

Identifiers

What OpenQuestion holds

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Registered trials

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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.