Evidence map›Paper›PMID 34809613›Full record

ArticleBMC health services research2021

Decomposition of outpatient health care spending by disease - a novel approach using insurance claims data.

Michael Stucki, Janina Nemitz, Maria Trottmann, Simon Wieser

Abstract read
In one paragraph

Article in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

6 citing papers in PubMed.

  1. Identifying diseases in claims data using a machine learning approach - a case from Switzerland.Archives of public health = Archives belges de sante publique · 2025
    Article
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  6. [Prevention and cost control in the German healthcare sector].Pravention und Gesundheitsforderung · 2023
    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.

Michael StuckiZHAW Zurich University of Applied Sciences, Winterthur Institute of Health Economics, Gertrudstrasse 15, 8401, Winterthur, Switzerland. stcc@zhaw.ch.ORCID http://orcid.org/0000-0002-2595-1238
Janina NemitzZHAW Zurich University of Applied Sciences, Winterthur Institute of Health Economics, Gertrudstrasse 15, 8401, Winterthur, Switzerland.
Maria TrottmannSWICA Health Insurance, Winterthur, Switzerland.
Simon WieserZHAW Zurich University of Applied Sciences, Winterthur Institute of Health Economics, Gertrudstrasse 15, 8401, Winterthur, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDecomposing health care spending by disease, type of care, age, and sex can lead to a better understanding of the drivers of health care spending. But the lack of diagnostic coding in outpatient care often precludes a decomposition by disease. Yet, health insurance claims data hold a variety of diagnostic clues that may be used to identify diseases.

methodsIn this study, we decompose total outpatient care spending in Switzerland by age, sex, service type, and 42 exhaustive and mutually exclusive diseases according to the Global Burden of Disease classification. Using data of a large health insurance provider, we identify diseases based on diagnostic clues. These clues include type of medication, inpatient treatment, physician specialization, and disease specific outpatient treatments and examinations. We determine disease-specific spending by direct (clues-based) and indirect (regression-based) spending assignment.

resultsOur results suggest a high precision of disease identification for many diseases. Overall, 81% of outpatient spending can be assigned to diseases, mostly based on indirect assignment using regression. Outpatient spending is highest for musculoskeletal disorders (19.2%), followed by mental and substance use disorders (12.0%), sense organ diseases (8.7%) and cardiovascular diseases (8.6%). Neoplasms account for 7.3% of outpatient spending.

conclusionsOur study shows the potential of health insurance claims data in identifying diseases when no diagnostic coding is available. These disease-specific spending estimates may inform Swiss health policies in cost containment and priority setting.

Indexed as

Health ExpendituresOutpatientsAmbulatory CareDelivery of Health CareHealth Care CostsHumansInsurance, HealthUnited StatesCost-of-illnessHealth care costsOutpatient careSpending decompositionSwitzerland

Identifiers

PMID34809613
PMCPMC8609863

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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.