Biologic patterns of disability

We describe the use of a mathematical/statistical method (i.e., Rasch analysis) to elucidate biological patterns of disability present in the functional ability of persons undergoing medical rehabilitation. Two measures chosen for illustration are the FIM Instrument for inpatients and the Body Movement and Control (BMC) measure for outpatients. In order to meet the assumptions necessary for application of linear statistics to clinical measurement studies, Rasch analysis was used to transform ordinal scales into linear measures. Another unique feature of Rasch analysis is that it allows evaluation of the difficulty of items and the abilities of persons being tested, separately, on the same metric. Also, the difficulty represented by each item may be arranged along a hierarchy from easy to hard. The hierarchies of functional ability items are dependent upon the specific patterns of disability related to underlying pathophysiology. For inpatients, initial analyses of the 18 items of the FIM Instrument demonstrated separate hierarchies for the 13 motor items and for the 5 cognition items. Subsequent analyses demonstrated five distinct patterns for the 13 motor items of: brain dysfunction, orthopedic conditions, pain conditions, ambulatory spinal cord dysfunction, and wheelchair users with spinal cord dysfunction. Two patterns were identified for cognition: stroke with right body hemiparesis and all others. For outpatients, the BMC measure of physical functioning is used to demonstrate that pathophysiologic conditions are expected to affect the hierarchial pattern of items differently. This was noted to be the case for persons with lower body dysfunction, low back pain, and neck pain/upper limb dysfunction. Based upon the item responses, sitting, reaching and standing appear to represent items most useful for discriminating between the three conditions in terms of the functional consequences. Rasch analysis, among other advantages, enables investigation of the subtle relationships among items and is a useful method to evaluate underlying biological patterns of disability. A clinician, using a map that shows the expected relationships between item scores, may observe that a particular patient matches or does not match the expected pattern. Such insights may help the clinician in monitoring the responses of the patient to treatment efforts.