Recent research has highlighted the challenges faced by the clinical rehabilitation team in determining if a dysvascular amputee patient is a prosthetic candidate, formulating the most appropriate rehabilitation plan based upon their functional goals, and developing a prosthetic prescription that best matches their probable mobility outcome. The current prescription paradigm involves the estimation of the patient's future mobility outcomes using K-levels. The appropriate prosthetic componentry is then matched to the predicted K-level. This approach is wrought with challenges and clinicians do not have a lot of confidence in the system. There is no evidence to back the clinician's ability to use K-levels to predict future function. Current clinical practice guidelines also do not offer adequate evidence or guidance to shape these decisions. The time of initial prosthetic evaluation is a key time point in the amputee care continuum that can profoundly influence later outcome. Lower extremity amputations are a major health care concern within the VA Health Care System. The VA Amputee System of Care (ASoC), which is a specialized clinical program within Rehabilitation Care Services, has been implemented with the primary goal of enhancing amputee care and improving patient outcomes. This program is concerned with the most appropriate management of amputees to maximizing function and quality of life, as well as reducing health care disparities between regions and improving geographical access to health care resources. To improve the establishment of rehabilitation mobility goals, the provision of the optimum prosthetic device to meet those goals, we must address one of the key perceived needs of amputee rehabilitation providers. We propose to develop a prediction model (AMPREDICT- PROsthetics) that will predict mobility outcome based upon key predictors including demographic, comorbidity, health behavior, cognitive, mental health, access to care, reamputation, stump factors, rehab environment, and prosthetic component sophistication available at the time of prosthetic prescription. It will enhance prosthetic prescription and assist the rehabilitation team in setting realistic goals, as well as manage patient expectations. Ultimately, it should reduce regional variation in care and enhance decision making to all VHA facilities that perform this procedure. Although not a primary aim of the proposed research, the successful development of the proposed prediction model may have additional downstream benefits for this population, reducing trial and error, prosthetic component fitting, with its incumbent dollar costs and patient costs in terms of travel and repeated health care visits. If successful, it could be implemented into VA/DoD Clinical Practice Guidelines and implemented throughout the VA Amputation System of Care.

Public Health Relevance

Our goals for the AMPREDICT PROsthetic prediction model are based on a conceptual model that assumes each patient presents with a composite of risk factors from several important health domains and these factors when considered together with rehab environment, prosthetic componentry, and risk of reamputation have a profound impact on functional mobility. A rigorously developed and validated prediction model (AMPREDICT- PROsthetics) is proposed that will predict functional prosthetic mobility based on an individual's composite of risk factors prior to prosthetic prescription. Rather than relying on subjective estimates of future K-levels not based on evidence, or relying on clinical experience alone, the prediction model will provide the probability of achieving four hierarchical levels of mobility in each individual patient. This predicted probability can then be matched to the most appropriate prosthetic component sophistication.

Agency
National Institute of Health (NIH)
Institute
Veterans Affairs (VA)
Type
Non-HHS Research Projects (I01)
Project #
1I01RX002919-01
Application #
9610048
Study Section
Musculoskeletal Health & Function (RRD2)
Project Start
2018-10-01
Project End
2021-09-30
Budget Start
2018-10-01
Budget End
2019-09-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
VA Puget Sound Healthcare System
Department
Type
DUNS #
020232971
City
Seattle
State
WA
Country
United States
Zip Code
98108