Get the latest public health information from CDC: https://www.coronavirus.gov
Get the latest research information from NIH: https://www.nih.gov/coronavirus
Information about ongoing health services research and public health projects
| Individualized Surgical Decision Analysis for Patients with Symptomatic Peripheral Vascular Occlusive Disease
(Archived Project) |
|
|---|---|
| Investigator (PI): | Brothers, Thomas Edward |
| Performing Organization (PO): |
(Current): Medical University of South Carolina |
| Supporting Agency (SA): | American Heart Association (AHA) |
| Initial Year: | 2000 |
| Final Year: | 2003 |
| Award Type: | Grant |
| Abstract: | Peripheral vascular occlusive disease is a form of atherosclerosis that affects the legs and lives of many people, most of whom are in their last decade of life. The symptoms of this disease range from early fatigue of the leg to actual gangrene. Unfortunately, the potential results of treatment for this disease vary widely, ranging from successful improvement of leg circulation to amputation or even death. A number of different treatments are available for this condition, each with its own associated risks and benefits. The standard practice for surgeons treating this disease is for them to decide upon a particular management course that is based on their best estimate of the risks and benefits of treatment. However, the decision to intervene can be very complex due to patient and surgeon misperceptions, unrealistic expectations, and improper interpretation of the available data. The main purpose of this study is to see whether use of a computer model will help make these decisions easier and better for both surgeons and patients. Four principal options of management will be considered for patients who suffer from peripheral vascular occlusive disease: medical therapy only, operation to improve circulation, use of a balloon (angioplasty) to improve circulation, or amputation of the leg. Patients will be asked to complete a questionnaire describing how their disease affects their daily life as well as how they value certain states of health, such as being able to walk without pain or not losing their leg to amputation. At the same time, the surgeons caring for these patients will be asked to estimate what the chances are of success, both short and longterm, for any of these treatments. All of this information will be put into the computer model to predict the best treatment. For half of the patients, this computer analysis will be available for their surgeon before any final decision of treatment is made. For the other half of the patients, the results of the computer prediction will not be available. The impact of the computer model on the following outcomes will be studied. 1) Whether it changes the actual treatment decisions consistent with the best quality of life, 2) Whether it improves the patients' function and quality of life , 3) Whether it reduces the cost of treatment, and, 4) Whether it reduces the surgeon's level of uncertainty regarding what treatment to recommend. |
| MeSH Terms: |
|
| Keywords: |
|
| Country: | United States |
| State: | South Carolina |
| Zip Code: | 29425 |
| UI: | 20010173 |
| Project Status: | Archived |