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Evaluating a Prediction Tool and Decision Aid for Patients with Crohn's Disease

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Use of the Crohn’s Disease Prediction Tool, a validated individualized risk prediction tool plus a web-based decision aid, resulted in improved shared decision making and patients choosing a more effective Crohn’s disease therapy.

Project Details -
Completed

Crohn’s disease is a chronic inflammatory bowel disease that has significant impact on the quality of life of an estimated 500,000 Americans. Treating patients with a combination of immunomodulator and anti-tumor necrosis factor soon after diagnosis but before complications occur leads to better patient outcomes. However, these medications are associated with life-threatening infections and lymphoma. A challenge of treating Crohn’s disease is identifying those patients who will develop severe disease and need medications without over-treating patients who have mild disease. Additionally, patients are often reluctant to begin treatment until the disease becomes more severe with resultant worse outcomes.

This research validated a statistical model that predicts Crohn’s disease severity for an individual patient based on clinical, serologic, and genetic factors. The model was then adapted into a web-based decision aid to help patients weigh the benefits and risks of available treatments for Crohn’s disease. Together, these two tools comprise the Crohn’s Disease Shared Decision-Making Program.

The specific aims of the research were as follows:

  • Validate the Crohn’s disease prediction model. 
  • Optimize the Crohn’s Disease Shared Decision-Making Program.
  • Evaluate the Crohn’s Disease Shared Decision-Making Program. 

A cluster randomized controlled trial of 202 patients found more patients in the intervention group with the shared decision-making program elected to be treated with the combination treatment. Furthermore, the intervention group had fewer patients who remained untreated, more patients who received the treatment they preferred, less decision conflict, an increased understanding of their disease, and increased trust in their physicians. Researchers believe this model could be adapted for use with other chronic disease states where increased information for patients, together with a personalized risk prediction tool, could facilitate shared decision making.

Helping Patients Better Understand Effective Treatment Options for Crohn’s Disease

Helping Patients Better Understand Effective Treatment Options for Crohn’s Disease

Use of the Crohn’s Disease Prediction Tool, a validated individualized risk prediction tool plus a web-based decision aid, resulted in improved shared decision making and patients choosing a more effective Crohn’s disease therapy.

Principal Investigator: Siegel, Corey
Organization: Dartmouth College
Research Profile: Evaluating a Prediction Tool and Decision Aid for Patients with Crohn's Disease
Funded Amount: $2,277,681

Treating Crohn’s disease before it is too late

Crohn’s disease (CD), a chronic inflammatory bowel disease, often begins with mild symptoms resulting in patients delaying care or clinicians questioning whether the patient needs aggressive treatment. Even when care is initiated early in the disease process, patients often do not take the most effective treatments because they are expensive and can result in life-threatening side effects. Unfortunately, delaying treatment with these medications can result in irreversible bowel damage and lead to a decreased quality of life.

Crohn’s Disease usually starts with everyday symptoms like diarrhea and abdominal cramping. By the time you get to the point where you feel sick enough, or the doctor believes you are sick enough for the most effective treatments, much of the damage has already occurred.”
- Dr. Siegel

Helping patients understand the progression of CD and available treatments

Dr. Corey Siegel and his research team at Dartmouth College developed a personalized shared decision making program to help physicians better communicate disease risk and treatment options. The Crohn’s Disease Prediction Tool consists of a previously validated individualized risk prediction tool and a web-based decision aid. The tool shows patients the likelihood they will develop complications over a 3-year period. The decision aid can help patients understand the risks and benefits of treatments.

Beyond Crohn’s disease

Dr. Siegel’s evaluation of the tool found that patients who used it chose more effective treatments earlier in their disease course, participated in choosing a treatment plan they preferred, had greater confidence with their decisions, and had increased trust in their physician than those patients who did not use the tool.

Future analysis of the tool by the researchers will focus on whether patients adhere to the therapy, cost, and clinical outcomes. Dr. Siegel feels this model of using a tool for shared decision making can be translated for use with other chronic diseases and could even be incorporated into telemedicine.