Benchmarking patient improvement in physical therapy with data envelopment analysis

The purpose of this article is to present a case study that documents how management science techniques (in particular data envelopment analysis) can be applied to performance improvement initiatives in an inpatient physical therapy setting.

The data used in this study consist of patients referred for inpatient physical therapy following total knee replacement surgery (at a medium-sized medical facility in the Midwestern USA) during the fiscal year 2002. Data envelopment analysis (DEA) was applied to determine the efficiency of treatment, as well as to identify benchmarks for potential patient improvement. Statistical trends in the benchmarking and efficiency results were subsequently analyzed using non-parametric and parametric methods.

Our analysis indicated that the rehabilitation process was largely effective in terms of providing consistent, quality care, as more than half of the patients in our study achieved the maximum amount of rehabilitation possible given available inputs. Among patients that did not achieve maximum results, most could obtain increases in the degree of flexion gain and reductions in the degree of knee extension.

The study is retrospective in nature, and is not based on clinical trial or experimental data. Additionally, DEA results are inherently sensitive to sampling: adding or subtracting individuals from the sample may change the baseline against which efficiency and rehabilitation potential are measured. As such, therapists using this approach must ensure that the sample is representative of the general population, and must not contain significant measurement error. Third, individuals who choose total knee arthroplasty will incur a transient disability. However, this population does not generally fit the World Health Organization International Classification of Functioning, Disability and Health definition of disability if the surgical procedure is successful. Since the study focuses on the outcomes of physical therapy, range of motion measurements and circumferential measurements were chosen as opposed to the more global measures of functional independence such as mobility, transfers and stair climbing. Applying this technique to data on patients with different disabilities (or the same disability with other outcome variables, such as Functional Independence Measure scores) may give dissimilar results.

This case study provides an example of how one can apply quantitative management science tools in a manner that is both tractable and intuitive to the practising therapist, who may not have an extensive background in quantitative performance improvement or statistics.

DEA has not been applied to rehabilitation, especially in the case where managers have limited data available.