DiabetesQ-IQNCT03800901
Quality IQ Patient Simulation Physician Practice Measurement and Engagement
A study testing Continuing Medical Education and Quality IQ Patient Simulations in people with Diabetes and Hypertension, run by Qure Healthcare, LLC at 1 site in United States.
Trial summary
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. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Diabetes, Hypertension, Depression
- What is being tested?
- Continuing Medical Education and Quality IQ Patient Simulations
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 187 participants
- Where
- 1 siteUnited States
- Study dates
- 11 Jan 2019to 15 Apr 2019
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- Board-certified in internal medicine or family medicine
- Minimum patient panel size of 1,500 patients
- English-speaking
- Access to the internet
- Informed, signed and voluntarily consented to be in the study
Who cannot join
- Not board certified in either internal medicine or family medicine
- Patient panel size less than 1,500 patients
- Non-English speaking
- Unable to access the internet
- Does not voluntarily consent to be in the study
Trial locations and contacts
1 site in 1 country.
About this study
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.
Read the detailed description
Primary care providers (PCPs) make many of the most important care decisions, especially for patients with chronic conditions and multiple co-morbidities. Studies have confirmed that unwarranted variation is common among PCPs, with high level of variation in care documented between urban and rural practices, across regions, and even among providers within a single healthcare system.
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 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 measurement, feedback and competition on evidence-based care decisions made by primary care providers across the country. It is a randomized, controlled trial with multiple measurements across key domains of clinical care. All participants are asked to care for simulated patients designed to look like typical patients seen in a primary care practice. In each case, providers will answer multiple-choice questions about their preferred course of action to work-up, diagnose and treat patients in the primary care setting. After each question, providers will receive evidence-based feedback, including references, on the appropriateness of each of their care decisions. Feedback will be supported with relevant reference to evidence-based guidelines, including national MIPS quality measures.
All participants will receive the following interventions:
- Feedback on care decisions made in each Quality IQ case, which will identify correct care, unneeded care, or gaps in care. This feedback will recommend or reinforce evidence-based care decisions and includes references.
- All cases will be scored against evidence-based criteria. For each case, providers will start with 100 base points. Correct care decisions will add to that total, while unnecessary care decisions will subtract from that total. A weekly leaderboard will be posted online, allowing participants to see how they are performing relative to their peers across the country. Participants will have the opportunity to select a unique username or an anonymous user ID to be identified on the leaderboard, to maintain anonymity.
Half of the recruits will be offered Category I CME credit approved by The University of California, San Francisco School of Medicine (UCSF) which has been accredited by the Accreditation Council of Continuing Medical Education to provide CME for physicians and MOC points in the ABIM's MOC program.
- Conditions
- Diabetes, Hypertension, Depression, Osteoarthritis, Asthma, Pain
- Being tested
- Continuing Medical Education, Quality IQ Patient Simulations
- Medical subject headings
- Diabetes Mellitus, Hypertension, Depression, Osteoarthritis, Asthma, Pain, Heart Failure
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Continuing Medical EducationOther
Also called CME
CME or ABIM MOC credits
Quality IQ Patient SimulationsOther
Also called Clinical Performance and Value vignettes, CPVs
Online patient cases designed to simulate typical patients seen in a primary care practice. In each case, providers will answer multiple-choice questions about their preferred course of action to work-up, diagnose and treat patients in the primary care setting. After each question, providers will receive evidence-based feedback, including references, on the appropriateness of each of their care decisions. Feedback will be supported with relevant reference to evidence-based guidelines, including national MIPS quality measures.
Cases will cover clinical conditions aligned with MIPS measures that are commonly seen in the primary care setting including: diabetes, hypertension, depression, osteoarthritis, asthma and pain control.
| Study group | Role | What they receive |
|---|---|---|
| Control | Active comparator | The Control arm will be asked to care for online, Quality IQ patient simulations and will receive feedback based on their care decisions made in each case. The feedback will identify correct care, unneeded care, or gaps in care and recommend or reinforce evidence-based care decisions and includes references. This arm will not be offered Continuing Medical Education (CME) or American Board of Internal Medicine (ABIM) Part II Maintenance of Certification (MOC) credits for their participation. Receives: Other: Quality IQ Patient Simulations |
| CME | Experimental | The CME arm will be asked to care for online, Quality IQ patient simulations and will receive feedback based on their care decisions made in each case. The feedback will identify correct care, unneeded care, or gaps in care and recommend or reinforce evidence-based care decisions and includes references. This arm will be offered Continuing Medical Education (CME) and American Board of Internal Medicine (ABIM) Part II Maintenance of Certification (MOC) credits for their participation. Receives: Other: Continuing Medical Education; Other: Quality IQ Patient Simulations |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 3 months
Secondary outcomes (6)
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.
Measured: 3 months
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.
Measured: 3 months
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.
Measured: 3 months
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.
Measured: 3 months
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.
Measured: 3 months
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.
Measured: 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Jan 2019
- Study start11 Jan 2019
- Primary completion11 Mar 2019
- Study completion15 Apr 2019
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for DiabetesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- The study will enroll practicing PCPs in the US. Once eligibility is determined and providers are enrolled in the study, they will be randomized into one of two arms: * Control: will not be offered CME or ABIM MOC credits for their participation. * CME Arm: will be offered CME or ABIM MOC credits for their participation. Between the two arms, all other aspects of the study will remain constant. All providers will then care for 1 Quality IQ patient simulation each week over the course of 6-8 weeks.
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 187 participants (actual)
Sponsor and investigators
- Lead sponsor
- Qure Healthcare, LLC
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- CE Outcomes
- Responsible party
- Sponsor
- Investigators
- John Peabody, MD, PhD, Principal investigator, QURE Healthcare
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03800901
- Sponsor's protocol ID
- 01-QIQ-K-2018
- Acronym
- Q-IQ
- Status last verified
- Mar 2020
- First submitted
- 4 Jan 2019
- Last updated
- 3 Mar 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: No individual participant data will be shared with other researchers. Analysis will be conducted at the aggregate group level.
Publications
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.
PubMed 30328782Weigel 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.
PubMed 26376210Peabody 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. doi: 10.1001/jama.283.13.1715.
PubMed 10755498Peabody 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. doi: 10.7326/0003-4819-141-10-200411160-00008.
PubMed 15545677Burgon T, Casebeer L, Aasen H, Valdenor C, Tamondong-Lachica D, de Belen E, Paculdo D, Peabody J. Measuring and Improving Evidence-Based Patient Care Using a Web-Based Gamified Approach in Primary Care (QualityIQ): Randomized Controlled Trial. J Med Internet Res. 2021 Dec 23;23(12):e31042. doi: 10.2196/31042.
PubMed 34941547
Study at a glance
From the registry record, last updated by the sponsor on 3 Mar 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Quality IQ Patient Simulation Physician Practice Measurement and Engagement
- ClinicalTrials.gov ID
- NCT03800901
- Acronym / sponsor ID
- Q-IQ / 01-QIQ-K-2018
- Conditions
- Diabetes, Hypertension, Depression, Osteoarthritis, Asthma, Pain
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 187 participants (actual)
- Lead sponsor
- Qure Healthcare, LLCIndustry (pharma, biotech, devices)
- Collaborators
- CE Outcomes
- Study start
- 11 Jan 2019 (actual)
- Primary completion
- 11 Mar 2019 (actual)
- Study completion
- 15 Apr 2019 (actual)
- First posted
- 11 Jan 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Primary care providers (PCPs) make many of the most important care decisions, especially for patients with chronic conditions and multiple co-morbidities. Studies have confirmed that unwarranted variation is common among PCPs, with high level of variation in care documented between urban and rural practices, across regions, and even among providers within a single healthcare system.
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 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 measurement, feedback and competition on evidence-based care decisions made by primary care providers across the country. It is a randomized, controlled trial with multiple measurements across key domains of clinical care. All participants are asked to care for simulated patients designed to look like typical patients seen in a primary care practice. In each case, providers will answer multiple-choice questions about their preferred course of action to work-up, diagnose and treat patients in the primary care setting. After each question, providers will receive evidence-based feedback, including references, on the appropriateness of each of their care decisions. Feedback will be supported with relevant reference to evidence-based guidelines, including national MIPS quality measures.
All participants will receive the following interventions:
- Feedback on care decisions made in each Quality IQ case, which will identify correct care, unneeded care, or gaps in care. This feedback will recommend or reinforce evidence-based care decisions and includes references.
- All cases will be scored against evidence-based criteria. For each case, providers will start with 100 base points. Correct care decisions will add to that total, while unnecessary care decisions will subtract from that total. A weekly leaderboard will be posted online, allowing participants to see how they are performing relative to their peers across the country. Participants will have the opportunity to select a unique username or an anonymous user ID to be identified on the leaderboard, to maintain anonymity.
Half of the recruits will be offered Category I CME credit approved by The University of California, San Francisco School of Medicine (UCSF) which has been accredited by the Accreditation Council of Continuing Medical Education to provide CME for physicians and MOC points in the ABIM's MOC program.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 2
- Model description
- The study will enroll practicing PCPs in the US. Once eligibility is determined and providers are enrolled in the study, they will be randomized into one of two arms: * Control: will not be offered CME or ABIM MOC credits for their participation. * CME Arm: will be offered CME or ABIM MOC credits for their participation. Between the two arms, all other aspects of the study will remain constant. All providers will then care for 1 Quality IQ patient simulation each week over the course of 6-8 weeks.
| Arm | Type | Receives |
|---|---|---|
| Control | Active comparator | Other: Quality IQ Patient SimulationsThe Control arm will be asked to care for online, Quality IQ patient simulations and will receive feedback based on their care decisions made in each case. The feedback will identify correct care, unneeded care, or gaps in care and recommend or reinforce evidence-based care decisions and includes references. This arm will not be offered Continuing Medical Education (CME) or American Board of Internal Medicine (ABIM) Part II Maintenance of Certification (MOC) credits for their participation. |
| CME | Experimental | Other: Continuing Medical Education, Other: Quality IQ Patient SimulationsThe CME arm will be asked to care for online, Quality IQ patient simulations and will receive feedback based on their care decisions made in each case. The feedback will identify correct care, unneeded care, or gaps in care and recommend or reinforce evidence-based care decisions and includes references. This arm will be offered Continuing Medical Education (CME) and American Board of Internal Medicine (ABIM) Part II Maintenance of Certification (MOC) credits for their participation. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (5 listed)
- Board-certified in internal medicine or family medicine
- Minimum patient panel size of 1,500 patients
- English-speaking
- Access to the internet
- Informed, signed and voluntarily consented to be in the study
Key exclusion criteria (5 listed)
- Not board certified in either internal medicine or family medicine
- Patient panel size less than 1,500 patients
- Non-English speaking
- Unable to access the internet
- Does not voluntarily consent to be in the study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Continuing Medical EducationAlso: CMECME or ABIM MOC credits | Other | CME |
| Quality IQ Patient SimulationsAlso: Clinical Performance and Value vignettes, CPVsOnline patient cases designed to simulate typical patients seen in a primary care practice. In each case, providers will answer multiple-choice questions about their preferred course of action to work-up, diagnose and treat patients in the primary care setting. After each question, providers will receive evidence-based feedback, including references, on the appropriateness of each of their care decisions. Feedback will be supported with relevant reference to evidence-based guidelines, including national MIPS quality measures. Cases will cover clinical conditions aligned with MIPS measures that are commonly seen in the primary care setting including: diabetes, hypertension, depression, osteoarthritis, asthma and pain control. | Other | CME, Control |
Primary outcome
Change in the percentage of evidence-based diagnostic and treatment decisions made in the simulations.
Time frame: 3 months
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.
6 secondary outcomes
Change in MIPS-relevant care decisions made in the patient simulations
Time frame: 3 months
Change in ordering of unneeded work-up tests made in the patient simulations
Time frame: 3 months
Participant case completion rate
Time frame: 3 months
Participant Satisfaction
Time frame: 3 months
Impact of available CME and ABIM MOC on recruitment rate
Time frame: 3 months
Impact of available CME and ABIM MOC on retention rate
Time frame: 3 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Mar 2020.
- Background: PubMed 30328782Burgon 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.
- Background: PubMed 26376210Weigel 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.
- Background: PubMed 10755498Peabody 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. doi: 10.1001/jama.283.13.1715.
- Background: PubMed 15545677Peabody 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. doi: 10.7326/0003-4819-141-10-200411160-00008.
- Derived from this study: PubMed 34941547Burgon T, Casebeer L, Aasen H, Valdenor C, Tamondong-Lachica D, de Belen E, Paculdo D, Peabody J. Measuring and Improving Evidence-Based Patient Care Using a Web-Based Gamified Approach in Primary Care (QualityIQ): Randomized Controlled Trial. J Med Internet Res. 2021 Dec 23;23(12):e31042. doi: 10.2196/31042.
- Individual participant dataSharing planned: No. No individual participant data will be shared with other researchers. Analysis will be conducted at the aggregate group level.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
John Peabody, MD, PhD principal investigator
QURE Healthcare
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Continuing Medical Education and Quality IQ Patient Simulations in people with Diabetes and Hypertension, run by Qure Healthcare, LLC at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 3 Mar 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in the percentage of evidence-based diagnostic and treatment decisions made in the simulations. (time frame: 3 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03800901, which also lists 5 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 3 Mar 2020.