1C-5 SYSTEMATICALLY-DEVELOPED GUIDANCE FOR THE CONDUCT AND REPORTING OF DECISION AND SIMULATION MODELS

Monday, October 20, 2014: 2:00 PM

Issa J. Dahabreh, MD, MS1, Ethan Balk, MD, MS2, John B. Wong, MD2, Jeffrey Chan, MS2, Amy Earley, BS2 and Thomas Trikalinos, MD, PhD1, (1)Brown University, Providence, RI, (2)Tufts Medical Center, Boston, MA
Purpose: The U.S. Agency for Healthcare Research and Quality (AHRQ) solicited the development of guidance for decision and simulation modeling in the context of systematic reviews.

Method: We updated and expanded existing systematic reviews of recommendations for the conduct and reporting of decision and simulation modeling with input from a multidisciplinary team of clinical, policy, and decision analysis experts. The results of the systematic review were discussed in-person with a panel of 28 stakeholders including patient representatives, providers of care, purchasers of care, payers, policy makers, and principal investigators. Stakeholders commented on existing recommendations from various sources and identified gaps, limitations and areas for elaboration. We subsequently reviewed the websites of 126 international health technology assessment organizations providing guidance on the conduct and reporting of decision and simulation models. We solicited further input from senior researchers with experience in decision and simulation modeling from AHRQ and its Evidence-based Practice Centers. 

Result: We developed a list of principles and good practice recommendations for modeling conducted to enhance and contextualize findings of systematic reviews. The guidance applies to structural mathematical models, including declarative, functional, and spatial models. We categorized recommendations by whether they pertain to the model structure, model data, or consistency, and reporting. We provide the rationale for each recommendation, evidence supporting the recommendation, or best judgment where adequate evidence was lacking.

Conclusion: We used a systematic approach to develop guidance for decision and simulation modeling in the context of systematic reviews. We are optimistic that this work will contribute to increased use of modeling in systematic reviews.