- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04870307
Community-engaged Approaches to Testing in Community and Healthcare Settings for Underserved Populations (CATCH-UP)
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
The broad RADx-UP initiative aims to understand the factors associated with COVID-19 morbidity and mortality disparities and to lay the foundation to reduce disparities for underserved and vulnerable populations disproportionately affected by the pandemic through efforts to increase access and effectiveness of diagnostic methods. The approach used in this project will leverage the investigators' experiences in designing and implementing evidence-based interventions in primary care settings, partnerships with Native American and Latino communities, investments in the development of community- driven and responsive organizations developed primarily in rural counties, and the capacity and needs of Oklahoma's government testing and contact tracing infrastructure to develop, test, and evaluate a culturally- responsive SARS-CoV-2 testing intervention, collection of additional data on COVID-19 related health disparities, and identification of additional attitudes, facilitators, and barriers to testing and eventual vaccination.
The investigators have designed an approach that not only allows for collecting essential information about community, provider, and patient-relevant impediments to viral testing but also meeting the critical need to increase testing in testing deserts in Oklahoma as rapidly as possible. The investigators believe that a singular focus on one testing strategy will be ineffective in truly understanding the barriers to testing. No one strategy would be effective in reaching all of the population, due to issues such as lack of access to a primary care provider, lack of insurance, transportation, available time, or individual/community perceptions on testing itself (e.g., safety, necessity, availability, trust). Thus, the investigators have chosen to develop the Community-engaged Approaches to Testing in Community and Healthcare settings for Underserved Populations (CATCH-UP) program with practice-based and community-based approaches to maximize the reach of the RADx-UP consortium, broaden the potential perspectives that could be captured, and compare the effectiveness of strategies. Rather than developing an inflexible practice-based intervention a priori, the investigators believe that the ever-changing barriers, attitudes and conditions in the pandemic, as well as the development and deployment of more effective diagnostic technologies over the next few months, necessitate a pragmatic approach in which increased testing is initiated quickly while simultaneously collaborating with stakeholders and collecting participant survey data in real-time, which will allow the intervention to evolve to changing needs, and provide rapid-cycle evaluation of effectiveness of these activities to provide timely feedback to the partners and other RADx-UP initiatives.
The specific aims of the CATCH-UP Project are as follows:
- Provide technical support to a minimum of 50 Oklahoma primary care practices to implement a person-centered approach to SARS-CoV-2 testing based on best available evidence and current guidelines. The implementation approach will include 1) development of implementation support resources for COVID-19 testing and risk mitigation strategies to meet the needs of vulnerable populations through continuous adaption to changing guidelines, testing protocols and availability, and information learned from the project's provider network and the broader RADx-UP community, 2) support practices to integrate tailored, guideline- based SARS-CoV-2 testing protocols and resources into the workflows through proven methodologies of academic detailing from peer-physician experts, practice change facilitation through quality improvement implementation professionals, and health information technology support. Based on the average number of providers and daily caseload in rural Oklahoma practices the investigators estimate this will result in approximately 60,000 viral tests performed in the first year.
- Rapidly respond to community testing needs by deploying mobile testing units in community settings that will provide operational support to increase the efficiency and the existing capacity for statewide testing by Oklahoma's public health authorities. The model used by the Chickasaw Nation in deploying a high-efficiency community testing system will be combined with ongoing observation and analysis to identify facilitators and barriers to implementing community testing sites to accelerate convergence on effective and replicable methods to increase access and acceptance of testing. The investigators will adapt to ongoing disease outbreaks and community needs, but anticipate that this aim will result in more than 250 testing events at sites throughout the state and 45,000 viral tests performed in the first year.
- Conduct a comprehensive evaluation of the impact of the CATCH-UP program, collaborate closely with other RADx-UP projects in sharing data and adapting processes, and continuously communicate with our community partners to assess effectiveness and disseminate research findings. This evaluation will include measurement and dissemination of data related to 1) Provider-level Outcomes that include knowledge and attitudes of disease prevalence, clinical characteristics including typical and atypical symptoms and disease severity, testing importance and strategies, vaccination, importance and use of personal protective equipment, availability of testing and delays in return of results, and provider observations of patient attitudes and other reported barriers, 2) Care Process Outcomes such as testing, test positivity, and test refusal rates, influenza, pneumococcal, and zoster vaccination rates, 3) Community-level Outcomes that include the number of tests conducted by mobile testing units and the resulting test positivity rate, 4) Patient-level Outcomes such as knowledge and attitudes of disease prevalence, disease characteristics including severity and acute and chronic symptoms, risk perspective and preferences, importance and use of personal protective equipment, patient acceptance of various testing options, and facilitators and barriers to participating in testing and future vaccination programs, 5) Patient Factors such as demographics, social determinants of health, and clinical characteristics that may be associated with COVID-19 morbidity and mortality disparities or reach of each testing modality, and 6) Qualitative Outcomes including perceptions of facilitators and barriers to testing and the utility, effectiveness, and generalizability of the program, explored through key informant interviews, exit interviews, and in-depth program implementation process observations.
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
Oklahoma
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Oklahoma City, Oklahoma, United States, 73104
- Oklahoma Clinical and Translational Science Institute
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
Practices:
- Primary care practices located in Oklahoma.
- Priority to practices serving a majority of patients that are underserved or vulnerable populations (rural, minority, elderly).
- Practices routinely using a certified electronic health record (EHR) will be eligible to participate, as practices that are still using paper records are either planning to close due to clinician retirement or will likely be implementing an EHR during the project, which would compromise their ability to participate.
- Practice-wide participation will be encouraged, but participation of all members within a practice (both clinicians and staff members) will not be required. The minimum acceptable level of participation will be one clinician and nurse/medical assistant dyad plus anyone else who would have to be involved to make changes in the processes of care (e.g. clinic manager) for that unit of care.
- Clinicians and staff members 18 years of age and older at the time of enrollment (consent).
Patients survey participants:
- Patients (or caregivers of patients) who are seen in eligible practices or community testing sites and received a recommendation for the patient to receive a SARS-CoV-2 diagnostic test.
- Patients (or their caregivers) who are 18 or older
Exclusion Criteria:
Practices:
- Practices that are uninterested in reducing missed opportunities for guidelines-based testing for SARS-CoV-2
- Solo practices with a clinician planning to retire within 12 months of enrollment will not be eligible for participation.
- Practices likely to experience ownership change in the next 12 months will not be eligible for participation.
Patient survey participants:
- Patients unable to complete the consent process or survey instruments in English or Spanish.
- Patients or caregivers of patients who are under the age of 18.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Other
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Other: Primary Care Practices
A practice-based implementation study will be conducted with 50 practices, with baseline data collection, and overlapping with interim measurements of care quality and process outcomes, followed by a final data collection at the end of the intervention (including baseline measures plus semi-structured interviews.
The practice based approach to increasing testing will be compared to a community-based approach using mobile-setting to increase testing.
Additional, non-clinical trial components of this study include patient surveys to understand facilitators and barriers to SARS-CoV-2 testing and identification of legal/ethical, socioeconomic, and behavioral implications of increased testing.
Patients are not direct subjects in this part of the study.
Intervention will target practices and practice members.
|
Dissemination and Implementation research involves assisting primary care practices to address SARS-CoV-2 testing using evidence-based practices as well as increased testing in mobile-based community settings.
The D&I model also involves Practice Assessment, Academic Detailing, Practice Facilitation, Health Information Technology Support, Performance Feedback and Benchmarking, and a Virtual Learning Community.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Change in SARS-CoV-2 Testing Rate (Practices)
Time Frame: Baseline to 12 months
|
Change in the proportion of patients eligible for SARS-CoV-2 testing based on screening that receive SARS-CoV-2 test.
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Baseline to 12 months
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Change in SARS-CoV-2 Test Positivity Rate (Community Sites)
Time Frame: Baseline to 12 months
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Change in the proportion of SARS-CoV-2 test results that are positive.
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Baseline to 12 months
|
Barriers to SARS-CoV-2 Testing (Practices)
Time Frame: Baseline
|
Number (and type) of barriers to SARS-CoV-2 testing.
|
Baseline
|
Barriers to SARS-CoV-2 Testing (Practices)
Time Frame: Month 3
|
Number (and type) of barriers to SARS-CoV-2 testing.
|
Month 3
|
Barriers to SARS-CoV-2 Testing (Practices)
Time Frame: Month 6
|
Number (and type) of barriers to SARS-CoV-2 testing.
|
Month 6
|
Barriers to SARS-CoV-2 Testing (Practices)
Time Frame: Month 9
|
Number (and type) of barriers to SARS-CoV-2 testing.
|
Month 9
|
Barriers to SARS-CoV-2 Testing (Practices)
Time Frame: Month 12
|
Number (and type) of barriers to SARS-CoV-2 testing.
|
Month 12
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Change in Influenza Vaccination Rate (NQF #41)
Time Frame: Baseline to 12 months
|
Change in the proportion of patients aged 6 months and older who receive an influenza immunization or report receipt of a influenza immunization.
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Baseline to 12 months
|
Change in Pneumococcal Vaccination Rate (NQF #127)
Time Frame: Baseline to 12 months
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Change in the proportion of patients 65 years of age or older who have ever received a pneumococcal vaccine.
|
Baseline to 12 months
|
Change in Zoster Vaccination Rate
Time Frame: Baseline to 12 months
|
Change in the proportion of patients aged 50 years and older who have had the Shingrix zoster (shingles) vaccination.
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Baseline to 12 months
|
COVID-19 Referrals
Time Frame: Baseline
|
Number (and type) of referrals for COVID-19 treatment.
|
Baseline
|
COVID-19 Referrals
Time Frame: Month 3
|
Number (and type) of referrals for COVID-19 treatment.
|
Month 3
|
COVID-19 Referrals
Time Frame: Month 6
|
Number (and type) of referrals for COVID-19 treatment.
|
Month 6
|
COVID-19 Referrals
Time Frame: Month 9
|
Number (and type) of referrals for COVID-19 treatment.
|
Month 9
|
COVID-19 Referrals
Time Frame: Month 12
|
Number (and type) of referrals for COVID-19 treatment.
|
Month 12
|
Collaborators and Investigators
Sponsor
Collaborators
Investigators
- Principal Investigator: Judith A James, MD, PhD, University of Oklahoma
Publications and helpful links
General Publications
- Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009 Aug 7;4:50. doi: 10.1186/1748-5908-4-50.
- Dwyer JW, Contreras D, Eschbach CL, Tiret H, Newkirk C, Carter E, Cronk L. Cooperative Extension as a Framework for Health Extension: The Michigan State University Model. Acad Med. 2017 Oct;92(10):1416-1420. doi: 10.1097/ACM.0000000000001640.
- Grumbach K, Mold JW. A health care cooperative extension service: transforming primary care and community health. JAMA. 2009 Jun 24;301(24):2589-91. doi: 10.1001/jama.2009.923. No abstract available.
- Kaufman A, Boren J, Koukel S, Ronquillo F, Davies C, Nkouaga C. Agriculture and Health Sectors Collaborate in Addressing Population Health. Ann Fam Med. 2017 Sep;15(5):475-480. doi: 10.1370/afm.2087.
- Phillips RL Jr, Kaufman A, Mold JW, Grumbach K, Vetter-Smith M, Berry A, Burke BT. The primary care extension program: a catalyst for change. Ann Fam Med. 2013 Mar-Apr;11(2):173-8. doi: 10.1370/afm.1495.
- Chou AF, Homco JB, Nagykaldi Z, Mold JW, Daniel Duffy F, Crawford S, Stoner JA. Disseminating, implementing, and evaluating patient-centered outcomes to improve cardiovascular care using a stepped-wedge design: healthy hearts for Oklahoma. BMC Health Serv Res. 2018 Jun 4;18(1):404. doi: 10.1186/s12913-018-3189-4.
- Bodenheimer T, Ghorob A, Willard-Grace R, Grumbach K. The 10 building blocks of high-performing primary care. Ann Fam Med. 2014 Mar-Apr;12(2):166-71. doi: 10.1370/afm.1616.
- Zhang CH, Schwartz GG. Spatial Disparities in Coronavirus Incidence and Mortality in the United States: An Ecological Analysis as of May 2020. J Rural Health. 2020 Jun;36(3):433-445. doi: 10.1111/jrh.12476. Epub 2020 Jun 16.
- Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, Azman AS, Reich NG, Lessler J. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Ann Intern Med. 2020 May 5;172(9):577-582. doi: 10.7326/M20-0504. Epub 2020 Mar 10.
- CDC COVID-19 Response Team. Preliminary Estimates of the Prevalence of Selected Underlying Health Conditions Among Patients with Coronavirus Disease 2019 - United States, February 12-March 28, 2020. MMWR Morb Mortal Wkly Rep. 2020 Apr 3;69(13):382-386. doi: 10.15585/mmwr.mm6913e2.
- CDC COVID-19 Response Team. Geographic Differences in COVID-19 Cases, Deaths, and Incidence - United States, February 12-April 7, 2020. MMWR Morb Mortal Wkly Rep. 2020 Apr 17;69(15):465-471. doi: 10.15585/mmwr.mm6915e4.
- Shahid Z, Kalayanamitra R, McClafferty B, Kepko D, Ramgobin D, Patel R, Aggarwal CS, Vunnam R, Sahu N, Bhatt D, Jones K, Golamari R, Jain R. COVID-19 and Older Adults: What We Know. J Am Geriatr Soc. 2020 May;68(5):926-929. doi: 10.1111/jgs.16472. Epub 2020 Apr 20.
- Iaccarino G, Grassi G, Borghi C, Ferri C, Salvetti M, Volpe M; SARS-RAS Investigators. Age and Multimorbidity Predict Death Among COVID-19 Patients: Results of the SARS-RAS Study of the Italian Society of Hypertension. Hypertension. 2020 Aug;76(2):366-372. doi: 10.1161/HYPERTENSIONAHA.120.15324. Epub 2020 Jun 22.
- Wang X, Fang X, Cai Z, Wu X, Gao X, Min J, Wang F. Comorbid Chronic Diseases and Acute Organ Injuries Are Strongly Correlated with Disease Severity and Mortality among COVID-19 Patients: A Systemic Review and Meta-Analysis. Research (Wash D C). 2020 Apr 19;2020:2402961. doi: 10.34133/2020/2402961. eCollection 2020.
- Turner-Musa J, Ajayi O, Kemp L. Examining Social Determinants of Health, Stigma, and COVID-19 Disparities. Healthcare (Basel). 2020 Jun 12;8(2):168. doi: 10.3390/healthcare8020168.
- Rollston R, Galea S. COVID-19 and the Social Determinants of Health. Am J Health Promot. 2020 Jul;34(6):687-689. doi: 10.1177/0890117120930536b. No abstract available.
- Hawkins D. Differential occupational risk for COVID-19 and other infection exposure according to race and ethnicity. Am J Ind Med. 2020 Sep;63(9):817-820. doi: 10.1002/ajim.23145. Epub 2020 Jun 15.
- Terry DL, Woo MJ. Burnout, job satisfaction, and work-family conflict among rural medical providers. Psychol Health Med. 2021 Feb;26(2):196-203. doi: 10.1080/13548506.2020.1750663. Epub 2020 Apr 13.
- Kaufman BG, Whitaker R, Pink G, Holmes GM. Half of Rural Residents at High Risk of Serious Illness Due to COVID-19, Creating Stress on Rural Hospitals. J Rural Health. 2020 Sep;36(4):584-590. doi: 10.1111/jrh.12481. Epub 2020 Jun 30.
- Davoodi NM, Healy M, Goldberg EM. Rural America's Hospitals are Not Prepared to Protect Older Adults From a Surge in COVID-19 Cases. Gerontol Geriatr Med. 2020 Jul 7;6:2333721420936168. doi: 10.1177/2333721420936168. eCollection 2020 Jan-Dec.
- James CV, Moonesinghe R, Wilson-Frederick SM, Hall JE, Penman-Aguilar A, Bouye K. Racial/Ethnic Health Disparities Among Rural Adults - United States, 2012-2015. MMWR Surveill Summ. 2017 Nov 17;66(23):1-9. doi: 10.15585/mmwr.ss6623a1.
- Henning-Smith C, Tuttle M, Kozhimannil KB. Unequal Distribution of COVID-19 Risk Among Rural Residents by Race and Ethnicity. J Rural Health. 2021 Jan;37(1):224-226. doi: 10.1111/jrh.12463. Epub 2020 Jun 25. No abstract available.
- Bavel JJV, Baicker K, Boggio PS, Capraro V, Cichocka A, Cikara M, Crockett MJ, Crum AJ, Douglas KM, Druckman JN, Drury J, Dube O, Ellemers N, Finkel EJ, Fowler JH, Gelfand M, Han S, Haslam SA, Jetten J, Kitayama S, Mobbs D, Napper LE, Packer DJ, Pennycook G, Peters E, Petty RE, Rand DG, Reicher SD, Schnall S, Shariff A, Skitka LJ, Smith SS, Sunstein CR, Tabri N, Tucker JA, Linden SV, Lange PV, Weeden KA, Wohl MJA, Zaki J, Zion SR, Willer R. Using social and behavioural science to support COVID-19 pandemic response. Nat Hum Behav. 2020 May;4(5):460-471. doi: 10.1038/s41562-020-0884-z. Epub 2020 Apr 30.
- Linton NM, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov AR, Jung SM, Yuan B, Kinoshita R, Nishiura H. Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data. J Clin Med. 2020 Feb 17;9(2):538. doi: 10.3390/jcm9020538.
- Furukawa NW, Brooks JT, Sobel J. Evidence Supporting Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 While Presymptomatic or Asymptomatic. Emerg Infect Dis. 2020 Jul;26(7):e201595. doi: 10.3201/eid2607.201595. Epub 2020 Jun 21.
- Arons MM, Hatfield KM, Reddy SC, Kimball A, James A, Jacobs JR, Taylor J, Spicer K, Bardossy AC, Oakley LP, Tanwar S, Dyal JW, Harney J, Chisty Z, Bell JM, Methner M, Paul P, Carlson CM, McLaughlin HP, Thornburg N, Tong S, Tamin A, Tao Y, Uehara A, Harcourt J, Clark S, Brostrom-Smith C, Page LC, Kay M, Lewis J, Montgomery P, Stone ND, Clark TA, Honein MA, Duchin JS, Jernigan JA; Public Health-Seattle and King County and CDC COVID-19 Investigation Team. Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility. N Engl J Med. 2020 May 28;382(22):2081-2090. doi: 10.1056/NEJMoa2008457. Epub 2020 Apr 24.
- Tromberg BJ, Schwetz TA, Perez-Stable EJ, Hodes RJ, Woychik RP, Bright RA, Fleurence RL, Collins FS. Rapid Scaling Up of Covid-19 Diagnostic Testing in the United States - The NIH RADx Initiative. N Engl J Med. 2020 Sep 10;383(11):1071-1077. doi: 10.1056/NEJMsr2022263. Epub 2020 Jul 22. No abstract available.
- Kenney C. Transforming Health Care. Virginia Mason Medical Center's Pursuit of the Perfect Patient Experience.: Productivity Press.; 2010
- Chao EC. Structured correlation in models for clustered data. Stat Med. 2006 Jul 30;25(14):2450-68. doi: 10.1002/sim.2368.
- van Oest R. A new coefficient of interrater agreement: The challenge of highly unequal category proportions. Psychol Methods. 2019 Aug;24(4):439-451. doi: 10.1037/met0000183. Epub 2018 May 3.
- Cohen DJ, Crabtree BF. Evaluative criteria for qualitative research in health care: controversies and recommendations. Ann Fam Med. 2008 Jul-Aug;6(4):331-9. doi: 10.1370/afm.818.
Helpful Links
- Abrams EM, Szefler SJ. COVID-19 and the impact of social determinants of health. The Lancet Respiratory Medicine. 2020;8(7):659-61. doi: 10.1016/s2213-2600(20)30234-4.
- 2020 Rural Hospital Sustainability Index 2020 [cited 2020]
- United States Department of Agriculture ERS. State Fact Sheet: United States.
- United States Department of Agriculture ERS. State Fact Sheets: Oklahoma
- Kushner Gadarian S, Goodman SW, Pepinsky TB. Partisanship, Health Behavior, and Policy Attitudes in the Early Stages of the COVID-19 Pandemic. SSRN Electronic Journal. 2020. doi: 10.2139/ssrn.3562796
- OPHIC. The Research to Practice to Research Exchange 2018
- Health CNDo. Covid-19 Guidebook 2020 [cited 2020]
- Scoville R, Little K. Comparing Lean and Quality Improvement. IHI White Paper. Cambridge, MA: Institute for Healthcare Improvement; 2014
- Grayson K, R. R. Interrater Reliability. Journal of Consumer Psychology. 2001;10(1):71-3. doi: 10.1207/15327660151043998
- Foundation UH. America's Health Rankings: Summary of Oklahoma
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Estimated)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- 12582
- U54GM104938-08S1 (U.S. NIH Grant/Contract)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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