Considering Spine Surgery: A Web-Based Calculator for Communicating Estimates of Personalized Treatment Outcomes

Prospective evaluation of an informational web-based calculator for communicating estimates of personalized treatment outcomes.

To evaluate the usability, effectiveness in communicating benefits and risks, and impact on decision quality of a calculator tool for patients with intervertebral disc herniations, spinal stenosis, and degenerative spondylolisthesis who are deciding between surgical and nonsurgical treatments.

The decision to have back surgery is preference-sensitive and warrants shared decision making. However, more patient-specific, individualized tools for presenting clinical evidence on treatment outcomes are needed.

Using Spine Patient Outcomes Research Trial data, prediction models were designed and integrated into a web-based calculator tool: http://spinesurgerycalc.dartmouth.edu/calc/. Consumer Reports subscribers with back-related pain were invited to use the calculator via email, and patient participants were recruited to use the calculator in a prospective manner following an initial appointment at participating spine centers. Participants completed questionnaires before and after using the calculator. We randomly assigned previously validated questions that tested knowledge about the treatment options to be asked either before or after viewing the calculator.

A total of 1256 consumer reports subscribers and 68 patient participants completed the calculator and questionnaires. Knowledge scores were higher in the postcalculator group compared to the precalculator group, indicating that calculator usage successfully informed users. Decisional conflict was lower when measured following calculator use, suggesting the calculator was beneficial in the decision-making process. Participants generally found the tool helpful and easy to use.

Although the calculator is not a comprehensive decision aid, it does focus on communicating individualized risks and benefits for treatment options. Moreover, it appears to be helpful in achieving the goals of more traditional shared decision-making tools. It not only improved knowledge scores but also improved other aspects of decision quality.

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