Benchmarking Outpatient Rehabilitation Clinics Using Functional Status Outcomes. (6th August 2015)

• Record Type: Journal Article
• Authors: Gozalo, Pedro L.; Resnik, Linda J.; Silver, Benjamin
• Is Part Of: Health services research. Volume 51:Number 2(2016:Apr.)
• Page Start: 768
• Page End: 789
• Publication Date: 2015-08-06
• Subjects: Rehabilitation -- physical therapy -- quality measurement -- bench‐marking -- profiling; Medical care -- Periodicals; Medical care -- Evaluation -- Periodicals; Hospital care -- Periodicals; Health services administration -- Periodicals; 362
• DOI: 10.1111/1475-6773.12344
• Languages: English
• ISSNs: 0017-9124

Abstract

Abstract : Objective: To utilize functional status (FS) outcomes to benchmark outpatient therapy clinics. Data Sources: Outpatient therapy data from clinics using Focus on Therapeutic Outcomes (FOTO) assessments. Study Design: Retrospective analysis of 538 clinics, involving 2, 040 therapists and 90, 392 patients admitted July 2006–June 2008. FS at discharge was modeled using hierarchical regression methods with patients nested within therapists within clinics. Separate models were estimated for all patients, for those with lumbar, and for those with shoulder impairments. All models risk‐adjusted for intake FS, age, gender, onset, surgery count, functional comorbidity index, fear‐avoidance level, and payer type. Inverse probability weighting adjusted for censoring. Data Collection Methods: Functional status was captured using computer adaptive testing at intake and at discharge. Principal Findings: Clinic and therapist effects explained 11.6 percent of variation in FS. Clinics ranked in the lowest quartile had significantly different outcomes than those in the highest quartile ( p < .01). Clinics ranked similarly in lumbar and shoulder impairments (correlation = 0.54), but some clinics ranked in the highest quintile for one condition and in the lowest for the other. Conclusions: Benchmarking models based on validated FS measures clearly separated high‐quality from low‐quality clinics, and they could be used to inform value‐based‐payment policies.