Literature DB >> 18480038

A cost-effectiveness framework for profiling the value of hospital care.

Justin W Timbie1, Joseph P Newhouse, Meredith B Rosenthal, Sharon-Lise T Normand.   

Abstract

Provider profiling and performance-based incentive programs have expanded in recent years but need a theoretical framework for measuring and comparing the "value'' of clinical care across medical providers. Cost-effectiveness analysis provides such a framework but has rarely been used outside of the treatment choice context. The authors present a profiling framework based on cost-effectiveness methods and illustrate their approach using data on in-hospital survival and the cost of care for a heart attack from a sample of Massachusetts hospitals during fiscal year 2003. They model each outcome using hierarchical models that allow performance to vary across hospitals as a function of a latent quality effect and an effect of case mix. They also estimate incremental outcomes by conditioning on each hospital's pair of random effects, using indirect standardization to estimate "expected'' outcomes, and then taking their difference. Incremental cost and effectiveness outcomes are combined using incremental net monetary benefits. Using cost-effectiveness methods to profile hospital "value'' permits the comparison of the benefit of a service relative to the cost using existing societal weights.

Mesh:

Year:  2008        PMID: 18480038     DOI: 10.1177/0272989X07312476

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  5 in total

1.  Comparing and ranking hospitals based on outcome: results from The Netherlands Stroke Survey.

Authors:  H F Lingsma; E W Steyerberg; M J C Eijkemans; D W J Dippel; W J M Scholte Op Reimer; H C Van Houwelingen
Journal:  QJM       Date:  2009-12-11

2.  Multidimensional performance assessment of public sector organisations using dominance criteria.

Authors:  Nils Gutacker; Andrew Street
Journal:  Health Econ       Date:  2017-08-18       Impact factor: 3.046

3.  Reference effect measures for quantifying, comparing and visualizing variation from random and fixed effects in non-normal multilevel models, with applications to site variation in medical procedure use and outcomes.

Authors:  Thomas J Glorioso; Gary K Grunwald; P Michael Ho; Thomas M Maddox
Journal:  BMC Med Res Methodol       Date:  2018-07-06       Impact factor: 4.615

4.  Incorporating natural variation into IVF clinic league tables: The Expected Rank.

Authors:  Hester F Lingsma; Marinus J C Eijkemans; Ewout W Steyerberg
Journal:  BMC Med Res Methodol       Date:  2009-07-16       Impact factor: 4.615

5.  Evaluating the effect of healthcare providers on the clinical path of heart failure patients through a semi-Markov, multi-state model.

Authors:  Francesca Gasperoni; Francesca Ieva; Anna Maria Paganoni; Christopher H Jackson; Linda Sharples
Journal:  BMC Health Serv Res       Date:  2020-06-12       Impact factor: 2.655

  5 in total

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