Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-23890
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dc.contributor.authorStucki, Michael-
dc.contributor.authorNemitz, Janina-
dc.contributor.authorTrottmann, Maria-
dc.contributor.authorWieser, Simon-
dc.date.accessioned2022-01-12T14:48:09Z-
dc.date.available2022-01-12T14:48:09Z-
dc.date.issued2021-11-22-
dc.identifier.issn1472-6963de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/23890-
dc.description.abstractBackground: Decomposing 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. Methods: In 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. Results: Our 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. Conclusions: Our 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.de_CH
dc.language.isoende_CH
dc.publisherBioMed Centralde_CH
dc.relation.ispartofBMC Health Services Researchde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectCost-of-illnessde_CH
dc.subjectHealthcare costde_CH
dc.subjectOutpatient carede_CH
dc.subjectSpending decompositionde_CH
dc.subject.ddc360: Soziale Probleme und Sozialversicherungende_CH
dc.subject.ddc362.1041: Gesundheitsökonomiede_CH
dc.titleDecomposition of outpatient health care spending by disease : a novel approach using insurance claims datade_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.organisationalunitWinterthurer Institut für Gesundheitsökonomie (WIG)de_CH
dc.identifier.doi10.1186/s12913-021-07262-xde_CH
dc.identifier.doi10.21256/zhaw-23890-
dc.identifier.pmid34809613de_CH
zhaw.funding.euNode_CH
zhaw.issue1264de_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume21de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
zhaw.monitoring.costperiod2022de_CH
Appears in collections:Publikationen School of Management and Law

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