The role of matched controls in building an evidence base for hospital-avoidance schemes: a retrospective evaluation
- PMID: 22224902
- PMCID: PMC3401405
- DOI: 10.1111/j.1475-6773.2011.01367.x
The role of matched controls in building an evidence base for hospital-avoidance schemes: a retrospective evaluation
Abstract
Objective: To test whether two hospital-avoidance interventions altered rates of hospital use: "intermediate care" and "integrated care teams."
Data sources/study setting: Linked administrative data for England covering the period 2004 to 2009.
Study design: This study was commissioned after the interventions had been in place for several years. We developed a method based on retrospective analysis of person-level data comparing health care use of participants with that of prognostically matched controls.
Data collection/extraction methods: Individuals were linked to administrative datasets through a trusted intermediary and a unique patient identifier.
Principal findings: Participants who received the intermediate care intervention showed higher rates of unscheduled hospital admission than matched controls, whereas recipients of the integrated care team intervention showed no difference. Both intervention groups showed higher rates of mortality than did their matched controls.
Conclusions: These are potentially powerful techniques for assessing impacts on hospital activity. Neither intervention reduced admission rates. Although our analysis of hospital utilization controlled for a wide range of observable characteristics, the difference in mortality rates suggests that some residual confounding is likely. Evaluation is constrained when performed retrospectively, and careful interpretation is needed.
© Health Research and Educational Trust.
Figures
References
-
- Abadie A, Imbens G. “Large Sample Properties of Matching Estimators for Average Treatment Effects”. Econometrica. 2006;74:235–67.
-
- Austin PC. “A Critical Appraisal of Propensity-Score Matching in the Medical Literature between 1996 and 2003”. Statistics in Medicine. 2008;27:2037–49. - PubMed
-
- Austin PC, Grootendorst P, Anderson GM. “A Comparison of the Ability of Different Propensity Score Models to Balance Measured Variables between Treated and Untreated Subjects: A Monte Carlo Study”. Statistics in Medicine. 2007;26:734–53. - PubMed
-
- Billings J, Mijanovich T. “Improving the Management of Care for High-Cost Medicaid Patients”. Health Affairs. 2007;26(6):1643–54. - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Molecular Biology Databases
