CATCH-UP Intervention in Increasing Cancer Screening and Prevention Care in Uninsured Patients at Community Health Centers

NCT02355262 | Completed

• 7 other identifiers: IRB00009862NCI-2014-02326CR000245545219MR00042926MR00044877R01CA181452
• Study Type: observational
• Target: 45
• Locations: 1 country
• Sites: 1

Brief Summary

This randomized research trial studies the Community-based Health Information Technology (HIT) Tools for Cancer Screening and Health Insurance Promotion (CATCH-UP) intervention in increasing cancer screening and prevention care in uninsured patients at community health centers. The CATCH-UP intervention may contribute to increased rates of insurance coverage, leading to improved cancer screening and prevention rates in community health care settings, and general recommended preventive care.

Conditions

Breast Carcinoma; Cervical Carcinoma; Colorectal Carcinoma; Health Status Unknown; Human Papillomavirus Infection; Malignant Neoplasm

Keywords

Insurance Coverage; Insurance Continuity

Outcome Measures

Primary Outcomes (3)

• Changes in the proportion of clinic patients who receive age- and gender-appropriate recommended cancer screening and preventive care (clinic-level)

  Pre- and post-implementation differences in proportion of patients with insurance continuity will be calculated between implementation and control community health centers (?difference-in-differences? analysis). Generalized linear/non-linear mixed models will be used, which offer flexible regression modeling to accommodate different sources of correlations (serial and intra-clinic), categorical and continuous covariates, and fixed and time-dependent covariates.

  Baseline to up to 6 years

• Changes in the proportion of clinic patients with insurance continuity

  Pre- and post-implementation differences in proportion of patients with insurance continuity will be calculated between implementation and control community health centers (?difference-in-differences? analysis). Generalized linear/non-linear mixed models will be used, which offer flexible regression modeling to accommodate different sources of correlations (serial and intra-clinic), categorical and continuous covariates, and fixed and time-dependent covariates. Serial and intra-clinic correlations will be modeled as random effects.

  Baseline to up to 6 years

• Total number of months uninsured (total gap months)

  The Community-based Health Information Technology (HIT) Tools for Cancer Screening and Health Insurance Promotion tool?s impact on total number of months uninsured (total gap months) will be evaluated. The distribution of total gap months will be examined before selecting a specific model to use for the analysis. Analytic models will be refined through an iterative process, guided by the hypotheses and preliminary analyses.

  Up to 6 years

Study Arms (2)

Arm I (Independent Tool Implementation)

Participants receive CATCH-UP tools which include a panel management/data aggregator system that identifies patients who may be eligible for public coverage but are not yet insured, or who are nearing coverage expiration, coupled with automated patient outreach and communication at baseline.

Other: Informational Intervention

Arm II (Tool Implementation with Interactive Facilitation)

Participants receive CATCH-UP tools which include a panel management/data aggregator system that identifies patients who may be eligible for public coverage but are not yet insured, or who are nearing coverage expiration, coupled with automated patient outreach and communication. Participants also receive additional implementation support such as trainings, assistance with workflows, and practice facilitation.

Other: Informational Intervention

Interventions

Informational Intervention OTHER

Receive CATCH-UP intervention

Arm I (Independent Tool Implementation); Arm II (Tool Implementation with Interactive Facilitation)

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with at least one encounter at a CHC in the OCHIN network since January 1, 2012

You may qualify if:

• Established patients at CHC sites
• Low-income
• Ethnically diverse populations with lower rates of cancer screening compared to national rates
• Uninsured patients
• Patients 18 to 64 years of age
• Clinics must be primary care sites, with greater than 1,000 adult patients in the past year, be located in a state that expanded Medicaid, and have implemented the OCHIN EHR prior to January 1, 2012

Sponsors & Collaborators

• OHSU Knight Cancer Institute: lead
• Kaiser Permanente: collaborator
• National Cancer Institute (NCI): collaborator
• Oregon Community Health Information Network: collaborator
• Oregon Health and Science University: collaborator

Study Sites (1)

OHSU Knight Cancer Institute

Portland, Oregon, 97239, United States

Location

Related Publications (11)

• Hoopes MJ, Angier H, Gold R, Bailey SR, Huguet N, Marino M, DeVoe JE. Utilization of Community Health Centers in Medicaid Expansion and Nonexpansion States, 2013-2014. J Ambul Care Manage. 2016 Oct-Dec;39(4):290-8. doi: 10.1097/JAC.0000000000000123.

  PMID: 26765808 BACKGROUND

• Hatch B, Tillotson C, Angier H, Marino M, Hoopes M, Huguet N, DeVoe J. Using the electronic health record for assessment of health insurance in community health centers. J Am Med Inform Assoc. 2016 Sep;23(5):984-90. doi: 10.1093/jamia/ocv179. Epub 2016 Jan 23.

  PMID: 26911812 BACKGROUND

• DeVoe JE, Tillotson CJ, Marino M, O'Malley J, Angier H, Wallace LS, Gold R. Trends in Type of Health Insurance Coverage for US Children and Their Parents, 1998-2011. Acad Pediatr. 2016 Mar;16(2):192-9. doi: 10.1016/j.acap.2015.06.009. Epub 2015 Aug 18.

  PMID: 26297668 BACKGROUND

• DeVoe JE, Huguet N, Likumahuwa-Ackman S, Angier H, Nelson C, Marino M, Cohen D, Sumic A, Hoopes M, Harding RL, Dearing M, Gold R. Testing health information technology tools to facilitate health insurance support: a protocol for an effectiveness-implementation hybrid randomized trial. Implement Sci. 2015 Aug 25;10:123. doi: 10.1186/s13012-015-0311-4.

  PMID: 26652866 BACKGROUND

• Angier H, Hoopes M, Gold R, Bailey SR, Cottrell EK, Heintzman J, Marino M, DeVoe JE. An early look at rates of uninsured safety net clinic visits after the Affordable Care Act. Ann Fam Med. 2015 Jan-Feb;13(1):10-6. doi: 10.1370/afm.1741.

  PMID: 25583886 BACKGROUND

• Heintzman J, Marino M, Hoopes M, Bailey SR, Gold R, O'Malley J, Angier H, Nelson C, Cottrell E, Devoe J. Supporting health insurance expansion: do electronic health records have valid insurance verification and enrollment data? J Am Med Inform Assoc. 2015 Jul;22(4):909-13. doi: 10.1093/jamia/ocv033. Epub 2015 Apr 17.

  PMID: 25888586 BACKGROUND

• DeVoe JE, Angier H, Burdick T, Gold R. Health information technology: an untapped resource to help keep patients insured. Ann Fam Med. 2014 Nov-Dec;12(6):568-72. doi: 10.1370/afm.1721.

  PMID: 25384821 BACKGROUND

• Gold R, Burdick T, Angier H, Wallace L, Nelson C, Likumahuwa-Ackman S, Sumic A, DeVoe JE. Improve Synergy Between Health Information Exchange and Electronic Health Records to Increase Rates of Continuously Insured Patients. EGEMS (Wash DC). 2015 Aug 6;3(1):1158. doi: 10.13063/2327-9214.1158. eCollection 2015.

  PMID: 26355818 BACKGROUND

• Huguet N, Hoopes MJ, Angier H, Marino M, Holderness H, DeVoe JE. Medicaid Expansion Produces Long-Term Impact on Insurance Coverage Rates in Community Health Centers. J Prim Care Community Health. 2017 Oct;8(4):206-212. doi: 10.1177/2150131917709403. Epub 2017 May 17.

  PMID: 28513249 BACKGROUND

• Huguet N, Valenzuela S, Marino M, Moreno L, Hatch B, Baron A, Cohen DJ, DeVoe JE. Effectiveness of an insurance enrollment support tool on insurance rates and cancer prevention in community health centers: a quasi-experimental study. BMC Health Serv Res. 2021 Oct 30;21(1):1186. doi: 10.1186/s12913-021-07195-5.

  PMID: 34717616 DERIVED

• Hatch B, Tillotson C, Huguet N, Marino M, Baron A, Nelson J, Sumic A, Cohen D, E DeVoe J. Implementation and adoption of a health insurance support tool in the electronic health record: a mixed methods analysis within a randomized trial. BMC Health Serv Res. 2020 May 15;20(1):428. doi: 10.1186/s12913-020-05317-z.

  PMID: 32414376 DERIVED

MeSH Terms

Conditions

Breast Neoplasms; Uterine Cervical Neoplasms; Colorectal Neoplasms; Papillomavirus Infections; Neoplasms

Condition Hierarchy (Ancestors)

Neoplasms by Site; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases; Uterine Neoplasms; Genital Neoplasms, Female; Urogenital Neoplasms; Uterine Cervical Diseases; Uterine Diseases; Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Diseases; Intestinal Neoplasms; Gastrointestinal Neoplasms; Digestive System Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases; Rectal Diseases; Sexually Transmitted Diseases, Viral; Sexually Transmitted Diseases; Communicable Diseases; Infections; DNA Virus Infections; Virus Diseases; Tumor Virus Infections; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Jennifer DeVoe

  OHSU Knight Cancer Institute

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: ECOLOGIC OR COMMUNITY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: January 23, 2015
• First Posted: February 4, 2015
• Study Start: July 1, 2014
• Primary Completion: June 30, 2020
• Study Completion: June 30, 2020
• Last Updated: August 19, 2020

Record last verified: 2020-08

Locations

US (1)