Hypertension Clinical Trial
— Q-IQOfficial title:
Quality IQ Patient Simulation Physician Practice Measurement and Engagement
Verified date | March 2020 |
Source | Qure Healthcare, LLC |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
This study will test the quality of 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 study will also measure the impact of gaming-inspired competition and motivation, including a weekly leaderboard, to improve evidence-based care decisions. In addition, the study the test the impact of CME and MOC credits on participant engagement in the process.
Status | Completed |
Enrollment | 187 |
Est. completion date | April 15, 2019 |
Est. primary completion date | March 11, 2019 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | N/A and older |
Eligibility |
Inclusion Criteria: 1. Board-certified in internal medicine or family medicine 2. Minimum patient panel size of 1,500 patients 3. English-speaking 4. Access to the internet 5. 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 1,500 patients 3. Non-English speaking 4. Unable to access the internet 5. Does not voluntarily consent to be in the study |
Country | Name | City | State |
---|---|---|---|
United States | QURE Healthcare | San Francisco | California |
Lead Sponsor | Collaborator |
---|---|
Qure Healthcare, LLC | CE Outcomes |
United States,
Burgon TB, Cox-Chapman J, Czarnecki C, Kropp R, Guerriere R, Paculdo D, Peabody JW. Engaging Primary Care Providers to Reduce Unwanted Clinical Variation and Support ACO Cost and Quality Goals: A Unique Provider-Payer Collaboration. Popul Health Manag. 2019 Aug;22(4):321-329. doi: 10.1089/pop.2018.0111. Epub 2018 Oct 17. — View Citation
Peabody JW, Luck J, Glassman P, Dresselhaus TR, Lee M. Comparison of vignettes, standardized patients, and chart abstraction: a prospective validation study of 3 methods for measuring quality. JAMA. 2000 Apr 5;283(13):1715-22. — View Citation
Peabody JW, Luck J, Glassman P, Jain S, Hansen J, Spell M, Lee M. Measuring the quality of physician practice by using clinical vignettes: a prospective validation study. Ann Intern Med. 2004 Nov 16;141(10):771-80. — View Citation
Weigel PA, Ullrich F, Shane DM, Mueller KJ. Variation in Primary Care Service Patterns by Rural-Urban Location. J Rural Health. 2016 Spring;32(2):196-203. doi: 10.1111/jrh.12146. Epub 2015 Sep 16. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Change in the percentage of evidence-based diagnostic and treatment decisions made in the simulations. | In each case, participants will answer multiple-choice questions about their preferred course of action to work-up, diagnose and treat patients in the primary care setting. Each question has specific evidence-based scoring criteria identifying necessary and unnecessary care decisions. Each provider will get a score for each case, ranging from 0 to 100 percentage based on the care decisions they make in the case. Over the course of the project, the investigators will track the percentage of correct, evidence-based care decisions made by participants, with the hypothesis that serial measurement and feedback on evidence-based care decisions will lead to increases in appropriate decisions over time. Higher scores represent a better outcome. | 3 months | |
Secondary | Change in MIPS-relevant care decisions made in the patient simulations | As described in the primary outcome measure, the investigators will track the percentage of evidence-based care decisions made by participants in the patient simulations. A subset of these care decisions tie directly to quality measures tracked by Medicare through the Merit-based Incentive Payment System (MIPS). For this outcome measure, the investigators will track changes in the percentage of MIPS-relevant work-up and treatment decisions made in the patient simulations. Higher scores represent a better outcome. | 3 months | |
Secondary | Change in ordering of unneeded work-up tests made in the patient simulations | As described in the primary outcome measure, the investigators will track the percentage of evidence-based care decisions made by participants in the patient simulations. A subset of these care decisions tie to ordering of unneeded laboratory and imaging testing that is not supported by the evidence-based guidelines. For this outcome measure, the investigators will track changes in the frequency with which unneeded tests are ordered in the patient simulations. Higher scores represent a better outcome. | 3 months | |
Secondary | Participant case completion rate | The investigators will track the percentage of enrolled participants who stay engaged in the study and complete at least 75% of their patient simulation cases. | 3 months | |
Secondary | Participant Satisfaction | Investigators will measure participant satisfaction as measured by post-evaluation survey. On a scale of 1 to 5 (with 5 being the highest), participants will be asked about the overall quality of the material, the relevance to their practice and the educational content. Higher scores represent a better outcome. | 3 months | |
Secondary | Impact of available CME and ABIM MOC on recruitment rate | Operating under the hypothesis that physicians offered CME and MOC credits are more likely to participate in a quality improvement program like this, the investigators will track the rate at which a randomized group of primary care physicians enroll in the program when offered CME and MOC credit and compare that to a group that is not offered CME and MOC credit for their participation. | 3 months | |
Secondary | Impact of available CME and ABIM MOC on retention rate | Operating under the hypothesis that physicians offered CME and MOC credits are more likely to continue participating in a quality improvement program, the investigators will track the rate at which a primary care physicians eligible to earn CME and MOC credit complete the full 8 week project and compare that to a group that is not offered CME and MOC credit. | 3 months |
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