This study will test the quality of opioid-related physician care decisions using a patient-simulation based measurement and feedback approach that combines multiple-choice care decisions with real-time, personalized scoring and feedback. The cases and feedback have been designed to align with the latest CDC opioid guidelines. The study will also measure the impact of gaming-inspired competition and motivation, including a weekly leaderboard, to improve evidence-based care decisions. The quality of care decisions will be measured in the simulations and in a multiple-choice assessment administered before and after the patient simulations.

Primary care providers (PCPs) are often on the front lines of helping patients manage acute and chronic pain. These pain management decisions have become especially important in light of the national opioid crisis that has seen an unsettling rise in opioid dependency, over-doses and fatalities. The Centers for Disease Control has developed specific evidence-based guidelines to help clinicians make more informed decisions about appropriate use of opioids as well as identifying and managing patients at risk for opioid-use disorder and overdose.

The investigators' previous work has shown that patient simulations can rapidly and reliably measure unwarranted practice variation among providers. In addition, published work shows that patient simulations, when administered serially and combined with customized feedback on improvement opportunities can reduce practice variation and improve performance on patient-level quality measures. Given the challenge of the current opioid crisis and the large scope of unwarranted variation in medical practice, there is a need for scalable approaches to measure care decisions, provide feedback on improvement opportunities and benchmark performance to peers.

This study seeks to evaluate the impact of personalized measurement and feedback on evidence-based care decisions made by primary care providers across the country concerning opioid care. The study, a prospective cohort trial, will enroll primary care physicians (PCPs) practicing in the U.S. Upon enrollment, eligible providers will be asked to complete a questionnaire detailing their practice and professional background. They will then be asked to complete the following:

Pretest: Pre-project, participants will take a multiple-choice assessment test. These assessments measure CDC Opioid Guidelines knowledge and adherence. Study administrators will randomize half of providers to take Assessment A pre-intervention, and half to take Assessment B pre-intervention, and have attempted to make these two assessments of equal difficulty.

Intervention: All providers will then care for 1 online CPV QualityIQ patient simulation each week over the course of 6 weeks. The simulated patients will be adults aged 18-75 and present with clinical conditions commonly seen by PCPs, such as chronic or acute pain, for whom opioids are currently in use or may be considered. In the patient simulations, participants will make work-up, diagnostic and treatment decisions relevant to the patient's pain management and will receive real-time feedback on how those decisions align with the CDC recommendations. Each week, participants will receive an email notification with their case score from the previous week, how their care compares to their PCP peers, and a link their new case to be completed.

Posttest: Recruits will take the remaining assessment as described above after completion of the intervention.

Inclusion Criteria:

1. Board-certified in internal medicine or family medicine
2. Minimum patient panel size of 1,000 patients
3. At least 5% of their patients currently or previously using opioid medications
4. English-speaking
5. Access to the internet
6. Informed, signed and voluntarily consented to be in the study

Exclusion Criteria:

1. Not board certified in either internal medicine or family medicine
2. Patient panel size less than 1,000 patients
3. Less than 5% of their patients currently or previously using opioid medications
4. Non-English speaking
5. Unable to access the internet
6. Do not voluntarily consent to be in the study

No individual participant data will be shared with other researchers. Analysis will be conducted at the aggregate group level.