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Evaluating Hospital Costs in Kaunas Medical University Hospital

The purpose of the study is to evaluate hospital costs in Kaunas Medical University Hospital (KMUH). KMUH is the largest hospital in Lithuania, having 1995 in-patient beds, 26 specialised in-patient departments, 5130 employees, and providing wide range of in-patient services. Methods. Methods, used in the study include assessment of inputs and outputs, evaluation of average cost per case, estimation of cost structure, estimation of case-mix dimensions in in-patient departments and clinical categories and assessment of impact of case-mix dimensions to cost per case, using multiple regressionanalysis. Cross-sectional study designwas used in the study, evaluating mainly cases and expenses of all 26 specialised in-patient departments of KMUH per year 2002. Five cost groups have been used and defined inmonetary terms in each in-patient department: labour costs; medication costs; laboratory, radiology and anaesthesiology costs; running costs of medical equipment supply andother costs (including in-patients’ mealcosts, transportation, laundry, communication, etc. costs). Case was defined as one treatment episode in particular in-patient department. Cases were analysed using following case-mix dimensions: sex, age, absenceor presence of surgical operation, patient separation status and in-patientservice group. Results. Average costs per case vary widely among in-patient departments, ranging from 126.01 Litas (36.52 Euro) to 3451.68 Litas (999.73 Euro) per case.During the study average cost per case were also estimated in clinical profiles – surgery – 1161.0 Litas (336.24 Euro), therapy – 1312.15 Litas (380.02 Euro),obstetrics and gynaecology –685.82 Litas (198.62 Euro), newborn and child care – 893.54 Litas (258.78 Euro) and intensive care – 1292.92 Litas (374.45 Euro). Using multiple regression analysis method, costper case ineach in-patient department and clinical category according case-mix dimensions were predicted. In all in-patient departments predicted values of average costs per case according case-mix dimensions, comparing with actual values, did not differ so much. Positive contributions to predictedvalue of cost per case, shows only one variable – IA in-patient service group. In any predicted case contributions of independent variables have notbeen observedas significant (p&gt;0.05). Conclusions. Inputs (measured in the number of beds) and outputs (measured in the number of in-patientcases and the number of bed-days) are different across in-patient departments, as well as outputs (measured inthe number of treatment episodes according to case-mix dimensions). The average costs per case vary widely across in-patient departments and clinical categories. The analysis of the structure of average costs per case demonstrated striking differences in in-patient departments. In all in-patient departments the predicted values of the average costs per case according to case-mix dimensions, do not differ so much comparing with theactual observed costs per case. Positive contributions to the predicted value of the cost per case, shows only onevariable – IA in-patient service group. The results of the study have proved the evidence that clinical casestreated within the same in-patient department of the hospital are not similar. The results of studyhave showedthe failure of use of “in-patient service groups” as proxy of International Disease Classification due to numberof reasons / <p>ISBN 91-7997-101-6</p>

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:norden-3289
Date January 2005
CreatorsKalibatas, Vytenis
PublisherNordic School of Public Health NHV
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationMaster of Public Health, MPH, 1104-5701 ; MPH 2005:14

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