Computerized Adaptive Testing to Direct Delivery of Hospital-Based Rehabilitation

? DESCRIPTION (provided by applicant): Over 60% of frail, elderly, and chronically ill patients lose functional capacity during hospitalization. The result is an unnecessarily increased risk of falls, near-term rehospitalizations, and discharges to institutional rather than home settings. Our current clinical care model systemically engenders these often avoidable losses of function due to its unnecessary and ineffective reliance on busy clinicians to detect functional decline and initiate simple, yet effective, treatment plans. There is a critical need to reconceptualize this situation by: 1) minimizing reliance on overburdened clinicians to detect, address, and monitor patients' rehabilitation needs; and 2) immediately initiating resource-appropriate individualized care plans. A non-burdensome assessment strategy capable of accurately profiling patients' evolving functional capabilities and rehabilitation needs is needed. However, no measure currently offers this capability. We propose to develop and evaluate the needed assessment tool by refining the extant item response theory (IRT)-modeled Activity Measure for Post Acute Care (AM-PAC) item banks to create a disease-independent multidimensional computerized adaptive test (MCAT). In addition to enhanced efficiency and precision, MCAT may definitively address threats to measurement validity that arise when an item's or an IRT model's psychometric properties differ across clinically relevant subgroups (as has been reported for the aged, the intensely symptomatic, and ethnic minorities). The benefits of these achievable efforts will be enormous given that the use of this multidimensional approach will radically enhance assessment scope and efficiency without a commensurate increase in clinician burden in a manner that can be easily integrated into current care practices. More specifically, our approach will be to enrich the current AM-PAC banks and administer them to 1500 hospitalized patients. These data, combined with existing AM-PAC data sets, will be used to evaluate differential item functioning, item density across relevant trait ranges, multidimensional IRT model fit, and cut points for score stratification to match physical therapist (PT)-assigned functional stages. The resultant parameter estimates will be used to create a fixed-length short form (SF) and MCAT specified to assign patients to functional stages that link to validated care plans, as well as to detect meaningful change. We will administer the MCAT and SF to 600 hospitalized patients and 300 proxies, 50% verbally and 50% via tablets, who will concurrently be evaluated by experienced PTs. The resultant data will be used to evaluate the MCAT's and SF's validity relative to the gold standard criterion of PT assessment, association with clinical outcomes, robustness to proxy (i.e., caregiver vs. patient) and mode effects, and responsiveness.