Indirect Standardization Matching: Assessing Specific Advantage and Risk Synergy

Abstract

Objective. To develop a method to allow a hospital to compare its performance using its entire patient population to the outcomes of very similar patients treated elsewhere. Data Sources/Setting. Medicare claims in orthopedics and common general, gynecologic, and urologic surgery from Illinois, New York, and Texas from 2004 to 2006. Study Design. Using two example "focal" hospitals, each hospital's patients were matched to 10 very similar patients selected from 619 other hospitals. Data Collection/Extraction Methods. All patients were used at each focal hospital, and we found the 10 closest matched patients from control hospitals with exactly the same principal procedure as each focal patient. Principal Findings. We achieved exact matches on all procedures and very close matches for other patient characteristics for both hospitals. There were few to no differences between each hospital's patients and their matched control patients on most patient characteristics, yet large and significant differences were observed for mortality, failure-to-rescue, and cost. Conclusion. Indirect standardization matching can produce fair audits of quality and cost, allowing for a comprehensive, transparent, and relevant assessment of all patients at a focal hospital. With this approach, hospitals will be better able to benchmark their performance and determine where quality improvement is most needed. Key Words. Quality of care, outcomes research, health care research, costThe aim of this paper was to develop a new tool for examining how well hospitals treat their patients and to aid hospitals in identifying subgroups of patients displaying especially good or bad outcomes compared to matched patients treated at other hospitals. We will base this evaluation on a new approach we call indirect standardization matching (ISM).

Discussion on “Time-Dynamic Profiling with Application to Hospital Readmission Among Patients on Dialysis,” by Jason P. Estes, Danh V. Nguyen, Yanjun Chen, Lorien S. Dalrymple, Connie M. Rhee, Kamyar Kalantar-Zadeh, and Damla Senturk

“…If there is limited overlap in patients covariate distributions, then the results can be very sensitive to misspecification of the outcome regression models. As argued by Silber et al (2016), a regression model can say what it has seen, and in hospitals where there are only certain types of patients, it will extrapolate or fabricate results for other types of patients that are absent. While this issue manifests in the time-invariant setting, it is exacerbated by the added time dimension in profiling as the available data are spread more thinly.…”

Auditing Practice Style Variation in Pediatric Inpatient Asthma Care

“…15,16 Medical distance indicates the level of difference between 2 patients in terms of medical covariates such as age, chronic illnesses, and presentation severity (eMethods in the Supplement). 9,10,13,20 To improve the quality of the matches between the template and the specific hospital, we used "near fine balance" [21][22][23][24][25] ; this method ensured that if the template had, for example, a 15% rate of upper respiratory tract infections for its 100 cases, each hospital provided a 15% rate of upper respiratory tract infections for its matched controls whenever possible, without requiring exact matches on that diagnosis for all patients in the hospital with respect to the template patient. A mean constraint was introduced on age at admission and a propensity score for being in the template.…”

“…Specific advantage was defined as observing better patient outcomes in a specific or focal hospital rather than those of matched control patients from other facilities within the same matched set. 13 Risk synergy describes a situation during which, as admission risk increases or decreases, the specific advantage changes in a systematic way. 13,20 For example, as admission risk increases, the focal hospital's patients may have increasingly better outcomes than matched controls from other hospitals.…”

“…13 Risk synergy describes a situation during which, as admission risk increases or decreases, the specific advantage changes in a systematic way. 13,20 For example, as admission risk increases, the focal hospital's patients may have increasingly better outcomes than matched controls from other hospitals. When studying the specific advantage and risk synergy of the focal hospital compared with the matched control population, we tested for an interaction between patientpredicted risk strata and the main effect of the focal hospital.…”

“…Template matching compares hospitals by selecting a reference template of patients and "stamping out copies" of template patients at each hospital through the use of multivariate matching. [9][10][11][12][13] Determining whether resource utilization differs, even when examining similar patients, should help inform individual hospitals as to whether they may need to change their approach to care, and using a matching framework rather than regression modeling allows hospitals to identify specific groups of patients for whom care may be in need of change.…”