Literature DB >> 12173495

Predicting the cost of hospital stay for stroke patients: the use of diagnosis related groups.

Silvia Evers1, Gemma Voss, Fred Nieman, André Ament, Tom Groot, Jan Lodder, Anita Boreas, Gerhard Blaauw.   

Abstract

In order to provide tailor-made care, governments are considering the implementation of output-pricing based on hospital case-mix measures, such as diagnosis related groups (DRG). The question is whether the current DRG classification system can provide a satisfactory prediction of the variance of costs in stroke patients and if not, in what way other variables may enhance this prediction. In this study, data from 731 stroke patients hospitalized at University Hospital Maastricht during 1996-1998 are used in the cost analysis. The DRG classification for this group uses information--in addition to the DRG classification operation or no operation--on the patient's age combined with discharge status. The results of regression analysis show that using DRGs, the variance explained in the costs amounts to 34%. Adding other variables to the DRGs, the variance explained increases to about 61%. Additional factors highly correlating with inpatient costs are the level of functioning after stroke, comorbidity, complications, and 'days of stay for non-medical reasons'. Costs decreased for stroke patients discharged during the latter part of the years studied, and if stroke patients happened to die during their hospital stay. The results do suggest that future implementation of output-pricing based on the DRG case-mix measures is feasible for stroke patients only if it is enhanced with information on complications and the level of functioning.

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Year:  2002        PMID: 12173495     DOI: 10.1016/s0168-8510(01)00219-6

Source DB:  PubMed          Journal:  Health Policy        ISSN: 0168-8510            Impact factor:   2.980


  8 in total

Review 1.  Do biomedical models of illness make for good healthcare systems?

Authors:  Derick T Wade; Peter W Halligan
Journal:  BMJ       Date:  2004-12-11

2.  Variations and determinants of hospital costs for acute stroke in China.

Authors:  Jade W Wei; Emma L Heeley; Stephen Jan; Yining Huang; Qifang Huang; Ji-Guang Wang; Yan Cheng; En Xu; Qidong Yang; Craig S Anderson
Journal:  PLoS One       Date:  2010-09-28       Impact factor: 3.240

3.  Costs structure of the inpatient ischemic stroke treatment using an exact costing method.

Authors:  Anne Puumalainen; Outi Elonheimo; Mats Brommels
Journal:  Heliyon       Date:  2020-06-23

4.  Process skill rather than motor skill seems to be a predictor of costs for rehabilitation after a stroke in working age; a longitudinal study with a 1 year follow up post discharge.

Authors:  Ann Björkdahl; Katharina Stibrant Sunnerhagen
Journal:  BMC Health Serv Res       Date:  2007-12-21       Impact factor: 2.655

5.  Determinants of the length of stay in stroke patients.

Authors:  Sang Mi Kim; Sung Wan Hwang; Eun-Hwan Oh; Jung-Kyu Kang
Journal:  Osong Public Health Res Perspect       Date:  2013-11-07

Review 6.  Capturing patients' needs in casemix: a systematic literature review on the value of adding functioning information in reimbursement systems.

Authors:  Maren Hopfe; Gerold Stucki; Ric Marshall; Conal D Twomey; T Bedirhan Üstün; Birgit Prodinger
Journal:  BMC Health Serv Res       Date:  2016-02-03       Impact factor: 2.655

7.  Accounting for What Matters to Patients in the G-DRG System: A Stakeholder's Perspective on Integrating Functioning Information.

Authors:  Maren Hopfe; Gerold Stucki; Jerome E Bickenbach; Birgit Prodinger
Journal:  Health Serv Insights       Date:  2018-09-03

8.  The development of inpatient cost and nursing service weights in a tertiary hospital in Malaysia.

Authors:  Nor Haty Hassan; Syed Mohamed Aljunid; Amrizal Muhammad Nur
Journal:  BMC Health Serv Res       Date:  2020-10-14       Impact factor: 2.655

  8 in total

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