# The VHA AMPREDICT Decision Support Tool:  Translating Success to Point of Care

> **NIH VA I01** · VA PUGET SOUND HEALTHCARE SYSTEM · 2022 · —

## Abstract

Amputation level decision making in patients with chronic limb threatening ischemia (CLTI) is challenging. The
choice of amputation level in this population can profoundly affect risk of operative mortality, re-hospitalization,
reamputation, functional mobility, and ultimately quality of life. One of the most important factors influencing the
amputation level decision is the preservation of mobility because of its association with quality of life. However,
the potential mobility benefits of more distal amputations may not be realized because of the increased risk of
compromised healing, need for ongoing wound care, and ultimately reamputation to a higher level. An additional
factor critical in decision making in this population is a mortality risk which is higher than the majority of cancer
diagnoses. This limited survival creates an imperative for both surgeon and patient to make decisions that will
best ensure the patient’s remaining life years conform to their values and priorities. Veteran Health Administration
data suggest that between 2005-2014, the proportion of incident transmetatarsal (TM) amputations tripled from
10% to 30% of all CLTI amputations with a corresponding decrease in the proportion of transtibial (TT) and
transfemoral (TF) amputations. The increase in TM amputations may be driven by the improvement in
revascularizations, greater teamwork, and the assumption that preserving the ankle joint will enable superior
mobility; however, it is unclear how the risks of not healing are considered in the decision. Balancing these risks
is at the core of a complex shared decision-making (SDM) process between physicians and patients as they
determine the “best” level of amputation. An important resource that enables successful implementation of SDM
are clinical decision support tools (DSTs). They provide clinicians with patient specific risks for key outcomes in
real time. To equip physicians with such a tool, we leveraged our prior prediction models to create the
AMPREDICT DST. It is an online DST that includes a home page, predictor pages, and a result page with patient
specific one-year mortality and reamputation risks and probability of achieving a basic level of independent
mobility, at each of three amputation levels (TM TT, TF). It has undergone successful testing by VHA physicians
nationwide. The successful implementation of the DST in clinical care requires buy in from user groups as well
as the need to overcome potential implementation obstacles. Our evaluation of the DST in physician users has
provided important insights that will be addressed in the current proposal. Many of the providers discussed the
importance of DST integration into the EHR with auto-population of the predictors to minimize the implementation
burden. Further, vascular surgeons recommended considering additional vascular diagnostic and therapeutic
predictors that are viewed as important in the clinical decisional process, in the prediction models. This is
s...

## Key facts

- **NIH application ID:** 10318069
- **Project number:** 1I01RX003690-01A1
- **Recipient organization:** VA PUGET SOUND HEALTHCARE SYSTEM
- **Principal Investigator:** Daniel C Norvell
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2022
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2021-10-01 → 2025-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10318069

## Citation

> US National Institutes of Health, RePORTER application 10318069, The VHA AMPREDICT Decision Support Tool:  Translating Success to Point of Care (1I01RX003690-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10318069. Licensed CC0.

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