Literature DB >> 2951336

Case-mix differences between teaching and nonteaching hospitals.

M G Goldfarb, R M Coffey.   

Abstract

It has been suggested that teaching hospitals as a group have done well financially under Medicare's prospective payment system. If so, is this because teaching hospitals have reduced inefficiencies or because their case mix is not as severe as presumed? In this study, we used Disease Staging and diagnosis related groups (DRGs) to isolate case mix attributed to given patient populations from that attributed to hospital treatment standards. We also analyzed differences among types of teaching hospitals. We found few case-mix differences between teaching and nonteaching hospitals when the weighting system was independent of resource consumption (i.e., Disease Staging). However, when resources were used to weight case-mix measurement (i.e., DRGs), teaching hospitals were found to have a more serious case mix. We conclude that although teaching hospitals typically do not have a more severe case mix than nonteaching hospitals, they do use more resources to treat their patient mix under DRGs.

Entities:  

Mesh:

Year:  1987        PMID: 2951336

Source DB:  PubMed          Journal:  Inquiry        ISSN: 0046-9580            Impact factor:   1.730


  11 in total

1.  Explaining differences in English hospital death rates using routinely collected data.

Authors:  B Jarman; S Gault; B Alves; A Hider; S Dolan; A Cook; B Hurwitz; L I Iezzoni
Journal:  BMJ       Date:  1999-06-05

2.  Modeling organizational determinants of hospital mortality.

Authors:  A S al-Haider; T T Wan
Journal:  Health Serv Res       Date:  1991-08       Impact factor: 3.402

3.  The cesarean birth rate: influence of hospital teaching status.

Authors:  D M Oleske; G L Glandon; G J Giacomelli; S F Hohmann
Journal:  Health Serv Res       Date:  1991-08       Impact factor: 3.402

4.  Hospital Characteristics Associated With Risk-standardized Readmission Rates.

Authors:  Leora I Horwitz; Susannah M Bernheim; Joseph S Ross; Jeph Herrin; Jacqueline N Grady; Harlan M Krumholz; Elizabeth E Drye; Zhenqiu Lin
Journal:  Med Care       Date:  2017-05       Impact factor: 2.983

5.  Relationship between severity, costs and claims of hospitalized patients using the Severity of Illness Index.

Authors:  M A Asenjo; L Baré; J M Bayas; A Prat; R Lledó; J Grau; L Salleras
Journal:  Eur J Epidemiol       Date:  1994-10       Impact factor: 8.082

Review 6.  Product definition for healthcare contracting: an overview of approaches to measuring hospital output with reference to the UK internal market.

Authors:  N Söderlund
Journal:  J Epidemiol Community Health       Date:  1994-06       Impact factor: 3.710

7.  Hospital Characteristics Associated With Postdischarge Hospital Readmission, Observation, and Emergency Department Utilization.

Authors:  Leora I Horwitz; Yongfei Wang; Faseeha K Altaf; Changqin Wang; Zhenqiu Lin; Shuling Liu; Jacqueline Grady; Susannah M Bernheim; Nihar R Desai; Arjun K Venkatesh; Jeph Herrin
Journal:  Med Care       Date:  2018-04       Impact factor: 2.983

8.  Association of resident coverage with cost, length of stay, and profitability at a community hospital.

Authors:  D Shine; S Beg; J Jaeger; D Pencak; R Panush
Journal:  J Gen Intern Med       Date:  2001-01       Impact factor: 5.128

9.  Teaching status and resource use for patients with acute myocardial infarction: a new look at the indirect costs of graduate medical education.

Authors:  I S Udvarhelyi; T Rosborough; R P Lofgren; N Lurie; A M Epstein
Journal:  Am J Public Health       Date:  1990-09       Impact factor: 9.308

10.  Should episode-based economic profiles be risk adjusted to account for differences in patients' health risks?

Authors:  J William Thomas
Journal:  Health Serv Res       Date:  2006-04       Impact factor: 3.402

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.