This FAST-TRACK SBIR grant proposes to determine the feasibility of building a computerized decision support system for cancer pain treatment. The investigator's previous NCI research developed and tested a pharmacologic algorithm method, based on the AHCPR Guideline for Cancer Pain Management, in the outpatient setting. The pharmacologic algorithm utilizes an efficacy versus toxicity decision point to funnel comprehensive assessment data into a treatment recommendations flow chart. Re-assessment parameters guide follow-up care dependent upon the severity of pain and side effect indicators. The RO1 algorithm project demonstrated a statistically significant reduction in pain intensity for patients randomized to the algorithm process during a controlled trial. The Phase II project will build on the assessment components of the algorithm imbedded in a workflow application to launch rapid prototyping of a knowledgebase decision support system for pain management. The system will be tested against actual cases treated in the RO1 pen and pencil algorithm format. A panel of clinical experts will rate the treatment recommendations in a blinded fashion. Beta testing in a clinical oncology setting will be performed focusing on adherence to the original algorithm guidelines and user acceptability.
