Analysing hospital variation in health outcome at the level of EQ-5D dimensions

Research output: Working paperDiscussion paper

Standard

Analysing hospital variation in health outcome at the level of EQ-5D dimensions. / Gutacker, Nils; Bojke, Chris; Daidone, Silvio; Devlin, Nancy; Street, Andrew.

York, UK : Centre for Health Economics, University of York, 2012. (CHE Research Paper; No. 74).

Research output: Working paperDiscussion paper

Harvard

Gutacker, N, Bojke, C, Daidone, S, Devlin, N & Street, A 2012 'Analysing hospital variation in health outcome at the level of EQ-5D dimensions' CHE Research Paper, no. 74, Centre for Health Economics, University of York, York, UK. <http://www.york.ac.uk/media/che/documents/papers/researchpapers/CHERP74_analysing_hospital_variation_health_outcome_EQ-5D.pdf>

APA

Gutacker, N., Bojke, C., Daidone, S., Devlin, N., & Street, A. (2012). Analysing hospital variation in health outcome at the level of EQ-5D dimensions. (CHE Research Paper; No. 74). Centre for Health Economics, University of York. http://www.york.ac.uk/media/che/documents/papers/researchpapers/CHERP74_analysing_hospital_variation_health_outcome_EQ-5D.pdf

Vancouver

Gutacker N, Bojke C, Daidone S, Devlin N, Street A. Analysing hospital variation in health outcome at the level of EQ-5D dimensions. York, UK: Centre for Health Economics, University of York. 2012 Jan. (CHE Research Paper; 74).

Author

Gutacker, Nils ; Bojke, Chris ; Daidone, Silvio ; Devlin, Nancy ; Street, Andrew. / Analysing hospital variation in health outcome at the level of EQ-5D dimensions. York, UK : Centre for Health Economics, University of York, 2012. (CHE Research Paper; 74).

Bibtex - Download

@techreport{4fe7155e949447f398d7033f789ef7db,
title = "Analysing hospital variation in health outcome at the level of EQ-5D dimensions",
abstract = "The English Department of Health has introduced routine collection of patient-reported health outcome data for selected surgical procedures (hip and knee replacement, hernia repair, varicose vein surgery) to facilitate patient choice and increase provider accountability. The EQ-5D has been chosen as the preferred generic instrument and the current risk-adjustment methodology is based on the EQ-5D index score to measure variation across hospital providers. There are two potential problems with this. First, using a population value set to generate the index score may not be appropriate for purposes of provider performance assessment because it introduces an exogenous source of variation and assumes identical preferences for health dimensions among patients. Second, the multimodal distribution of the index score creates statistical problems that are not yet resolved. Analysing variation for each dimension of the EQ-5D dimensions (mobility, self care, usual activities, pain/discomfort, anxiety/depression) seems therefore more appropriate and promising. For hip replacement surgery, we explore a) the impact of treatment on each EQ-5D dimension b) the extent to which treatment impact varies across providers c) the extent to which treatment impact across EQ-5D dimensions is correlated within providers. We combine information on pre- and post-operative EQ-5D outcomes with Hospital Episode Statistics for the financial year 2009/10. The overall sample consists of 25k patients with complete pre- and post-operative responses. We employ multilevel ordered probit models that recognise the hierarchical nature of the data (measurement points nested in patients, which themselves are nested in hospital providers) and the response distributions. The treatment impact is modelled as a random coefficient that varies at hospital-level. We obtain provider-specific Empirical Bayes (EB) estimates of this coefficient. We estimate separate models for each of the five EQ-5D dimensions and analyse correlations of the EB estimates across dimensions. Our analysis suggests that hospital treatment is indeed associated with improvements in health and that variability in treatment impact is generally more pronounced on the dimensions mobility, usual activity and pain/discomfort than on others. The pairwise correlation between the provider EB estimates is substantial, suggesting a) that certain providers are better in improving health across multiple EQ-5D dimensions than others and b) multivariate models are appropriate and should be further investigated.",
keywords = "hospital care, PATIENT OUTCOMES, PROMs, EQ-5D, performance assessment, provider profiling, hierarchical ordered probit",
author = "Nils Gutacker and Chris Bojke and Silvio Daidone and Nancy Devlin and Andrew Street",
year = "2012",
month = jan,
language = "English",
series = "CHE Research Paper",
publisher = "Centre for Health Economics, University of York",
number = "74",
type = "WorkingPaper",
institution = "Centre for Health Economics, University of York",

}

RIS (suitable for import to EndNote) - Download

TY - UNPB

T1 - Analysing hospital variation in health outcome at the level of EQ-5D dimensions

AU - Gutacker, Nils

AU - Bojke, Chris

AU - Daidone, Silvio

AU - Devlin, Nancy

AU - Street, Andrew

PY - 2012/1

Y1 - 2012/1

N2 - The English Department of Health has introduced routine collection of patient-reported health outcome data for selected surgical procedures (hip and knee replacement, hernia repair, varicose vein surgery) to facilitate patient choice and increase provider accountability. The EQ-5D has been chosen as the preferred generic instrument and the current risk-adjustment methodology is based on the EQ-5D index score to measure variation across hospital providers. There are two potential problems with this. First, using a population value set to generate the index score may not be appropriate for purposes of provider performance assessment because it introduces an exogenous source of variation and assumes identical preferences for health dimensions among patients. Second, the multimodal distribution of the index score creates statistical problems that are not yet resolved. Analysing variation for each dimension of the EQ-5D dimensions (mobility, self care, usual activities, pain/discomfort, anxiety/depression) seems therefore more appropriate and promising. For hip replacement surgery, we explore a) the impact of treatment on each EQ-5D dimension b) the extent to which treatment impact varies across providers c) the extent to which treatment impact across EQ-5D dimensions is correlated within providers. We combine information on pre- and post-operative EQ-5D outcomes with Hospital Episode Statistics for the financial year 2009/10. The overall sample consists of 25k patients with complete pre- and post-operative responses. We employ multilevel ordered probit models that recognise the hierarchical nature of the data (measurement points nested in patients, which themselves are nested in hospital providers) and the response distributions. The treatment impact is modelled as a random coefficient that varies at hospital-level. We obtain provider-specific Empirical Bayes (EB) estimates of this coefficient. We estimate separate models for each of the five EQ-5D dimensions and analyse correlations of the EB estimates across dimensions. Our analysis suggests that hospital treatment is indeed associated with improvements in health and that variability in treatment impact is generally more pronounced on the dimensions mobility, usual activity and pain/discomfort than on others. The pairwise correlation between the provider EB estimates is substantial, suggesting a) that certain providers are better in improving health across multiple EQ-5D dimensions than others and b) multivariate models are appropriate and should be further investigated.

AB - The English Department of Health has introduced routine collection of patient-reported health outcome data for selected surgical procedures (hip and knee replacement, hernia repair, varicose vein surgery) to facilitate patient choice and increase provider accountability. The EQ-5D has been chosen as the preferred generic instrument and the current risk-adjustment methodology is based on the EQ-5D index score to measure variation across hospital providers. There are two potential problems with this. First, using a population value set to generate the index score may not be appropriate for purposes of provider performance assessment because it introduces an exogenous source of variation and assumes identical preferences for health dimensions among patients. Second, the multimodal distribution of the index score creates statistical problems that are not yet resolved. Analysing variation for each dimension of the EQ-5D dimensions (mobility, self care, usual activities, pain/discomfort, anxiety/depression) seems therefore more appropriate and promising. For hip replacement surgery, we explore a) the impact of treatment on each EQ-5D dimension b) the extent to which treatment impact varies across providers c) the extent to which treatment impact across EQ-5D dimensions is correlated within providers. We combine information on pre- and post-operative EQ-5D outcomes with Hospital Episode Statistics for the financial year 2009/10. The overall sample consists of 25k patients with complete pre- and post-operative responses. We employ multilevel ordered probit models that recognise the hierarchical nature of the data (measurement points nested in patients, which themselves are nested in hospital providers) and the response distributions. The treatment impact is modelled as a random coefficient that varies at hospital-level. We obtain provider-specific Empirical Bayes (EB) estimates of this coefficient. We estimate separate models for each of the five EQ-5D dimensions and analyse correlations of the EB estimates across dimensions. Our analysis suggests that hospital treatment is indeed associated with improvements in health and that variability in treatment impact is generally more pronounced on the dimensions mobility, usual activity and pain/discomfort than on others. The pairwise correlation between the provider EB estimates is substantial, suggesting a) that certain providers are better in improving health across multiple EQ-5D dimensions than others and b) multivariate models are appropriate and should be further investigated.

KW - hospital care

KW - PATIENT OUTCOMES

KW - PROMs

KW - EQ-5D

KW - performance assessment

KW - provider profiling

KW - hierarchical ordered probit

M3 - Discussion paper

T3 - CHE Research Paper

BT - Analysing hospital variation in health outcome at the level of EQ-5D dimensions

PB - Centre for Health Economics, University of York

CY - York, UK

ER -