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Tool enables cystic fibrosis patients to actively engage in their care

A computerized decision-making tool has been shown to be effective in helping cystic fibrosis patients engage with clinicians as active participants in their own care.

Developed by researchers at the University of Cincinnati, the shared decision-making tool takes into account patients’ preferences for measures of lung function and health, as well as evidence-based treatment to assist patients in prioritizing home treatments.

Cystic fibrosis patients must undertake time-consuming and sometimes complex home therapies, says Mark Eckman, MD, Posey Professor of Clinical Medicine and director of the UC Division of General Internal Medicine.

However, by factoring personalized data into a computational framework, the tool assigns weights to patient preferences and personal goals for some of these treatments—combined with quantitative data on treatment efficacy, costs and time estimates—resulting in a score for each treatment option, he contends.

“A personalized report is generated based on patient input, but also the model internally is informed by data from clinical trials and medical literature in terms of the efficacy of the different treatments,” says Eckman. “That report then is used in a shared decision-making visit to facilitate a conversation between the patient and the clinician.”

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Eckman and Patricia Joseph, MD, director of the Adult Cystic Fibrosis Program at UC Medical Center, helped conducted a field study of 21 cystic fibrosis patients to determine the tool’s acceptability, understandability and ease of use. They and their co-authors recently published an article in the journal Medical Decision Making Policy & Practice discussing results of the initial evaluation of the tool.

“Our field study of 21 patients with cystic fibrosis found that patients uniformly believed the shared decision-making exercise helped them develop personalized priorities for home therapies and activities,” they concluded.

“Use of the tool helped them clarify their personal values for the relative importance of home treatment goals and helped them feel better prepared to discuss home treatment options with their doctors,” they report. “Perhaps most important, using the (CF-Shared Decision Making Tool) made them feel that they were contributing to making decisions in their care.”

Currently, the system leverages a Microsoft Excel spreadsheet based on a paper pamphlet that patients fill out, and clinicians must manually populate into a computerized model to generate a personalized report. Going forward, Eckman says researchers want to make the tool available via a computer tablet so patients can input their own data and automatically generate results. “This could also be put up on a patient portal,” he adds. “That’s where we want to go. But, right now, the current model and interactions are a bit clunky.”

Drawing from the success of the limited field study, researchers hope to conduct a randomized clinical trial to evaluate whether the tool improves patient adherence to home treatments and clinical outcomes.

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