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Figure 1.  Study Flow Diagram
Study Flow Diagram
Figure 2.  Six-Month Differences in Colorectal Cancer Screening Completion Rates
Six-Month Differences in Colorectal Cancer Screening Completion Rates

aTest for interaction.

Table.  Participant Characteristics
Participant Characteristics
1.
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Rex  DK, Johnson  DA, Anderson  JC, Schoenfeld  PS, Burke  CA, Inadomi  JM; American College of Gastroenterology.  American College of Gastroenterology guidelines for colorectal cancer screening 2009  [corrected].  Am J Gastroenterol. 2009;104(3):739-750.PubMedGoogle ScholarCrossref
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Meester  RG, Doubeni  CA, Zauber  AG,  et al.  Public health impact of achieving 80% colorectal cancer screening rates in the United States by 2018.  Cancer. 2015;121(13):2281-2285.PubMedGoogle ScholarCrossref
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Zauber  AG, Lansdorp-Vogelaar  I, Knudsen  AB, Wilschut  J, van Ballegooijen  M, Kuntz  KM.  Evaluating test strategies for colorectal cancer screening: a decision analysis for the U.S. Preventive Services Task Force.  Ann Intern Med. 2008;149(9):659-669.PubMedGoogle ScholarCrossref
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Joseph  DA, King  JB, Miller  JW, Richardson  LC; Centers for Disease Control and Prevention (CDC).  Prevalence of colorectal cancer screening among adults: Behavioral Risk Factor Surveillance System, United States, 2010.  MMWR Suppl. 2012;61(2)(suppl):51-56.PubMedGoogle Scholar
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Klabunde  CN, Cronin  KA, Breen  N, Waldron  WR, Ambs  AH, Nadel  MR.  Trends in colorectal cancer test use among vulnerable populations in the United States.  Cancer Epidemiol Biomarkers Prev. 2011;20(8):1611-1621.PubMedGoogle ScholarCrossref
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Shapiro  JA, Klabunde  CN, Thompson  TD, Nadel  MR, Seeff  LC, White  A.  Patterns of colorectal cancer test use, including CT colonography, in the 2010 National Health Interview Survey.  Cancer Epidemiol Biomarkers Prev. 2012;21(6):895-904.PubMedGoogle ScholarCrossref
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Diaz  JA, Roberts  MB, Goldman  RE, Weitzen  S, Eaton  CB.  Effect of language on colorectal cancer screening among Latinos and non-Latinos.  Cancer Epidemiol Biomarkers Prev. 2008;17(8):2169-2173.PubMedGoogle ScholarCrossref
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Klabunde  CN, Ballard-Barbash  R, White  MC, Thompson  T, Plescia  M, King  SC; Centers for Disease Control and Prevention (CDC).  Cancer screening: United States, 2010.  MMWR Morb Mortal Wkly Rep. 2012;61(3):41-45.PubMedGoogle Scholar
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Holden  DJ, Jonas  DE, Porterfield  DSDS, Reuland  D, Harris  R.  Systematic review: enhancing the use and quality of colorectal cancer screening.  Ann Intern Med. 2010;152(10):668-676.PubMedGoogle ScholarCrossref
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Hawley  ST, Volk  RJ, Krishnamurthy  P, Jibaja-Weiss  M, Vernon  SW, Kneuper  S.  Preferences for colorectal cancer screening among racially/ethnically diverse primary care patients.  Med Care. 2008;46(9)(suppl 1):S10-S16.PubMedGoogle ScholarCrossref
18.
Hawley  ST, McQueen  A, Bartholomew  LK,  et al.  Preferences for colorectal cancer screening tests and screening test use in a large multispecialty primary care practice.  Cancer. 2012;118(10):2726-2734.PubMedGoogle ScholarCrossref
19.
Ransohoff  DF, Sox  HC.  Clinical practice guidelines for colorectal cancer screening: new recommendations and new challenges.  JAMA. 2016;315(23):2529-2531.PubMedGoogle ScholarCrossref
20.
Inadomi  JM, Vijan  S, Janz  NK,  et al.  Adherence to colorectal cancer screening: a randomized clinical trial of competing strategies.  Arch Intern Med. 2012;172(7):575-582.PubMedGoogle ScholarCrossref
21.
Volk  RJ, Linder  SK, Lopez-Olivo  MA,  et al.  Patient decision aids for colorectal cancer screening: a systematic review and meta-analysis.  Am J Prev Med. 2016;51(5):779-791.PubMedGoogle ScholarCrossref
22.
Jandorf  L, Braschi  C, Ernstoff  E,  et al.  Culturally targeted patient navigation for increasing African Americans’ adherence to screening colonoscopy: a randomized clinical trial.  Cancer Epidemiol Biomarkers Prev. 2013;22(9):1577-1587.PubMedGoogle ScholarCrossref
23.
Paskett  ED, Harrop  JP, Wells  KJ.  Patient navigation: an update on the state of the science.  CA Cancer J Clin. 2011;61(4):237-249.PubMedGoogle ScholarCrossref
24.
Leone  LA, Reuland  DS, Lewis  CL,  et al.  Reach, usage, and effectiveness of a Medicaid patient navigator intervention to increase colorectal cancer screening, Cape Fear, North Carolina, 2011.  Prev Chronic Dis. 2013;10:E82.PubMedGoogle ScholarCrossref
25.
Percac-Lima  S, Ashburner  JM, Zai  AH,  et al.  Patient navigation for comprehensive cancer screening in high-risk patients using a population-based health information technology system: a randomized clinical trial.  JAMA Intern Med. 2016;176(7):930-937.PubMedGoogle ScholarCrossref
26.
Percac-Lima  S, Grant  RW, Green  AR,  et al.  A culturally tailored navigator program for colorectal cancer screening in a community health center: a randomized, controlled trial.  J Gen Intern Med. 2009;24(2):211-217.PubMedGoogle ScholarCrossref
27.
Lasser  KE, Murillo  J, Lisboa  S,  et al.  Colorectal cancer screening among ethnically diverse, low-income patients: a randomized controlled trial.  Arch Intern Med. 2011;171(10):906-912.PubMedGoogle ScholarCrossref
28.
Percac-Lima  S, Aldrich  LS, Gamba  GB, Bearse  AM, Atlas  SJ.  Barriers to follow-up of an abnormal Pap smear in Latina women referred for colposcopy.  J Gen Intern Med. 2010;25(11):1198-1204.PubMedGoogle ScholarCrossref
29.
Lasser  KE, Murillo  J, Medlin  E,  et al.  A multilevel intervention to promote colorectal cancer screening among community health center patients: results of a pilot study.  BMC Fam Pract. 2009;10:37.PubMedGoogle ScholarCrossref
30.
Atlas  SJ, Zai  AH, Ashburner  JM,  et al.  Non-visit-based cancer screening using a novel population management system.  J Am Board Fam Med. 2014;27(4):474-485.PubMedGoogle ScholarCrossref
31.
Ali-Faisal  SF, Colella  TJ, Medina-Jaudes  N, Benz Scott  L.  The effectiveness of patient navigation to improve healthcare utilization outcomes: a meta-analysis of randomized controlled trials  [published online October 14, 2016].  Patient Educ Couns. 2017;100(3):436-448. doi:10.1016/j.pec.2016.10.014PubMedGoogle ScholarCrossref
32.
Brenner  AT, Getrich  CM, Pignone  M,  et al.  Comparing the effect of a decision aid plus patient navigation with usual care on colorectal cancer screening completion in vulnerable populations: study protocol for a randomized controlled trial.  Trials. 2014;15(1):275.PubMedGoogle ScholarCrossref
33.
Brenner  AT, Hoffman  R, McWilliams  A,  et al.  Colorectal cancer screening in vulnerable patients: promoting informed and shared decisions.  Am J Prev Med. 2016;51(4):454-462.PubMedGoogle ScholarCrossref
34.
Pignone  M, Harris  R, Kinsinger  L.  Videotape-based decision aid for colon cancer screening: a randomized, controlled trial.  Ann Intern Med. 2000;133(10):761-769.PubMedGoogle ScholarCrossref
35.
Pignone  M, Winquist  A, Schild  LA,  et al.  Effectiveness of a patient and practice-level colorectal cancer screening intervention in health plan members: the CHOICE trial.  Cancer. 2011;117(15):3352-3362.PubMedGoogle ScholarCrossref
36.
Miller  DP  Jr, Spangler  JG, Case  LD, Goff  DC  Jr, Singh  S, Pignone  MP.  Effectiveness of a web-based colorectal cancer screening patient decision aid: a randomized controlled trial in a mixed-literacy population.  Am J Prev Med. 2011;40(6):608-615.PubMedGoogle ScholarCrossref
37.
Ko  LK, Reuland  D, Jolles  M, Clay  R, Pignone  M.  Cultural and linguistic adaptation of a multimedia colorectal cancer screening decision aid for Spanish-speaking Latinos.  J Health Commun. 2014;19(2):192-209.PubMedGoogle ScholarCrossref
38.
Reuland  DS, Ko  LK, Fernandez  A, Braswell  LC, Pignone  M.  Testing a Spanish-language colorectal cancer screening decision aid in Latinos with limited English proficiency: results from a pre-post trial and four month follow-up survey.  BMC Med Inform Decis Mak. 2012;12:53.PubMedGoogle ScholarCrossref
39.
Chew  LD, Griffin  JM, Partin  MR,  et al.  Validation of screening questions for limited health literacy in a large VA outpatient population.  J Gen Intern Med. 2008;23(5):561-566.PubMedGoogle ScholarCrossref
40.
Born  W, Engelman  K, Greiner  KA,  et al.  Colorectal cancer screening, perceived discrimination, and low-income and trust in doctors: a survey of minority patients.  BMC Public Health. 2009;9:363.PubMedGoogle ScholarCrossref
41.
Brenner  AT, Callan  D, Espaillat  M,  et al. Effect of a colorectal cancer screening decision aid on decision making outcomes in a low-income, majority Latino patient population. Paper presented at: 38th Annual Society for General Internal Medicine Conference. April 22-25, 2015; Toronto, ON, Canada.
42.
Brenner  AT, Ko  LK, Janz  N, Gupta  S, Inadomi  J.  Race/ethnicity and primary language: health beliefs about colorectal cancer screening in a diverse, low-income population.  J Health Care Poor Underserved. 2015;26(3):824-838.PubMedGoogle ScholarCrossref
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Clemans-Cope  L, Kenney  G.  Low income parents’ reports of communication problems with health care providers: effects of language and insurance.  Public Health Rep. 2007;122(2):206-216.PubMedGoogle ScholarCrossref
44.
Green  AR, Peters-Lewis  A, Percac-Lima  S,  et al.  Barriers to screening colonoscopy for low-income Latino and white patients in an urban community health center.  J Gen Intern Med. 2008;23(6):834-840.PubMedGoogle ScholarCrossref
45.
Stone  EG, Morton  SC, Hulscher  ME,  et al.  Interventions that increase use of adult immunization and cancer screening services: a meta-analysis.  Ann Intern Med. 2002;136(9):641-651.PubMedGoogle ScholarCrossref
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Klabunde  CN, Lanier  D, Breslau  ES,  et al.  Improving colorectal cancer screening in primary care practice: innovative strategies and future directions.  J Gen Intern Med. 2007;22(8):1195-1205.PubMedGoogle ScholarCrossref
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Original Investigation
July 2017

Effect of Combined Patient Decision Aid and Patient Navigation vs Usual Care for Colorectal Cancer Screening in a Vulnerable Patient Population: A Randomized Clinical Trial

Author Affiliations
  • 1Cecil G. Sheps Center for Health Services Research, University of North Carolina, Chapel Hill
  • 2Division of General Medicine & Clinical Epidemiology, University of North Carolina School of Medicine, Chapel Hill
  • 3Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill
  • 4Department of Medicine, University of Iowa Carver College of Medicine, Iowa City
  • 5University of Iowa Holden Comprehensive Cancer Center, University of Iowa, Iowa City
  • 6Department of Family and Community Medicine, University of New Mexico School of Medicine, Albuquerque
  • 7Department of Family Medicine, Carolinas HealthCare System, Charlotte, North Carolina
  • 8University of New Mexico Comprehensive Cancer Center, Albuquerque
  • 9Department of Anthropology, University of Maryland, College Park
  • 10Department of Biostatistics, University of North Carolina, Chapel Hill
  • 11Department of Internal Medicine, University of Texas Dell Medical School, Austin
JAMA Intern Med. 2017;177(7):967-974. doi:10.1001/jamainternmed.2017.1294
Key Points

Question  Compared with usual care, what is the effect of an intervention combining a colorectal cancer (CRC) screening decision aid and patient navigation on CRC screening completion in a diverse, vulnerable primary care population?

Findings  In this randomized clinical trial that included 265 patients, the rate of CRC screening completion at 6 months was greater in the intervention arm (68%) than in the control arm (27%), a significant difference.

Meaning  Given the substantial effect on screening, efforts to understand how this kind of intervention can be more broadly implemented are warranted.

Abstract

Importance  Colorectal cancer (CRC) screening is underused, especially among vulnerable populations. Decision aids and patient navigation are potentially complementary interventions for improving CRC screening rates, but their combined effect on screening completion is unknown.

Objective  To determine the combined effect of a CRC screening decision aid and patient navigation compared with usual care on CRC screening completion.

Design, Setting, and Participants  In this randomized clinical trial, data were collected from January 2014 to March 2016 at 2 community health center practices, 1 in North Carolina and 1 in New Mexico, serving vulnerable populations. Patients ages 50 to 75 years who had average CRC risk, spoke English or Spanish, were not current with recommended CRC screening, and were attending primary care visits were recruited and randomized 1:1 to intervention or control arms.

Interventions  Intervention participants viewed a CRC screening decision aid in English or Spanish immediately before their clinician encounter. The decision aid promoted screening and presented colonoscopy and fecal occult blood testing as screening options. After the clinician encounter, intervention patients received support for screening completion from a bilingual patient navigator. Control participants viewed a food safety video before the encounter and otherwise received usual care.

Main Outcomes and Measures  The primary outcome was CRC screening completion within 6 months of the index study visit assessed by blinded medical record review.

Results  Characteristics of the 265 participants were as follows: their mean age was 58 years; 173 (65%) were female, 164 (62%) were Latino; 40 (15%) were white non-Latino; 61 (23%) were black or of mixed race; 191 (78%) had a household income of less than $20 000; 101 (38%) had low literacy; 75 (28%) were on Medicaid; and 91 (34%) were uninsured. Intervention participants were more likely to complete CRC screening within 6 months (68% vs 27%); adjusted-difference, 40 percentage points (95% CI, 29-51 percentage points). The intervention was more effective in women than in men (50 vs 21 percentage point increase, interaction P = .02). No effect modification was observed across other subgroups.

Conclusions and Relevance  A patient decision aid plus patient navigation increased the rate of CRC screening completion in compared with usual care invulnerable primary care patients.

Trial Registration  clinicaltrials.gov Identifier: NCT02054598

Introduction

Colorectal cancer (CRC) is the third leading cause of cancer death in men and women in the United States.1 Although non-Hispanic whites have experienced declines in CRC incidence and mortality, other racial/ethnic minority groups have not experienced similar declines.2 Colorectal cancer screening is effective at reducing CRC mortality, and expert groups, including the US Preventive Services Task Force (USPSTF) recommend CRC screening with several testing options.3-5 The US National Colorectal Cancer Roundtable, a coalition of public, private, and volunteer organizations, has set a goal of increasing US screening rates to 80% by 2018, an ambitious target that would have a substantial public health impact.6,7 Unfortunately, screening remains underused, especially among vulnerable populations, including those with Medicaid, no health insurance, low educational attainment, limited English proficiency, and members of racial/ethnic minority groups.8-14 Screening rates among Latinos, the largest racial/ethnic minority group in the United States, are substantially lower than in the general population.9,13,15,16 To increase CRC screening nationally, interventions that address multiple patient- and system-level screening barriers are needed, particularly in care settings where diverse, vulnerable populations are served.

Accumulating evidence suggests that offering patients a choice of screening options, particularly a choice that includes fecal occult blood testing or fecal immunochemical testing (FOBT/FIT) in addition to primary endoscopic screening, may be especially important for increasing screening in vulnerable populations.17-20 Colorectal cancer screening decision aids provide a structured tool for offering such a choice to patients and have been consistently shown to increase patient knowledge of CRC screening, stated intent to complete screening, and CRC screening test ordering.21 However, their effect on actual screening completion has generally been limited, indicating that there are other important barriers to screening completion that are not addressed by decision aids alone.

Patient navigation represents another promising intervention, and several studies have found it to be effective in helping vulnerable patient populations to overcome barriers to recommended cancer screening, including CRC screening.22-27 However, the absolute effects of navigation on screening rates are often modest in size.24,28-31

Decision aids and patient navigation represent potentially complementary interventions for promoting CRC screening because they address multiple barriers that affect different steps in the screening process. Decision aids act “proximally” in the screening process to enhance patients’ initial awareness of screening, promote patient-clinician communication, build intent, and clarify preferences. Patient navigation acts more “distally” to address other (often practical) barriers to CRC screening completion that vulnerable patient populations face once an individual decides to be screened. An intervention that combines a decision aid and patient navigation has potential to be highly effective. However, to our knowledge, no study has tested an intervention combining a decision aid with patient navigation to improve CRC screening.

The objective of this study was to test, in a randomized clinical trial (RCT), the effect of a combined intervention that included visit-based delivery of a CRC screening decision aid plus patient navigation vs usual care on CRC screening test completion among patients in a primary care safety net setting. We hypothesized that the intervention would increase screening completion compared with usual care.

Methods
Study Design and Setting

Details of trial design, setting, eligibility, enrollment, interventions, and measures have been published previously in our protocol article and intermediate outcomes analysis.32,33 (The trial protocols are provided in the Supplement.) Briefly, this RCT tested a 2-component intervention including a patient decision aid (delivered immediately before the clinician encounter) and patient navigation (delivered after the clinician encounter).32 Participants were recruited from 2 community health centers, 1 in Albuquerque, New Mexico, and 1 in Charlotte, North Carolina. The sites serve diverse low-income communities including substantial numbers of Latino patients and had baseline CRC screening rates of approximately 35%. The study was approved by the institutional review boards at the University of North Carolina, the University of New Mexico, and Carolinas HealthCare System. Data were collected from January 2014 to March 2016, and analyzed in 2016.

Recruitment and Enrollment

We recruited participants ages 50 to 75 years who spoke English or Spanish, were at average CRC risk (no personal or family history of CRC, polyps, or inflammatory bowel disease), were not up-to-date with recommended CRC screening, and had upcoming appointments. Bilingual research assistants/patient navigators (“navigators”) contacted potentially eligible patients either before an upcoming visit or on the day of the visit to invite them to participate. Participants received a $40 incentive, and provided written informed consent.

Study Activities and Randomization

On the day of the clinician visit, navigators first collected the baseline survey data (prior to randomization). Next, participants were randomized 1:1 to intervention or control groups using sequentially numbered, opaque, sealed envelopes generated by the study biostatistician (M.A.W.). Allocation was thus concealed from navigators. After randomization, navigators (no longer masked to study group) administered a CRC screening decision aid to intervention participants and a food safety (attention control) video to control participants. English or Spanish videos were viewed in the waiting area or examination room on a handheld computer tablet before the clinician encounter. After the encounter, intervention participants received patient navigation; control participants received usual care.

Decision Aid

Development and testing of the English and Spanish language decision aids are described in detail elsewhere.34-38 Briefly, the videos are approximately 15 minutes long and consist of 3 parts: (1) overview of importance of CRC screening and review of fecal testing (FOBT/FIT) and colonoscopy; (2) head-to-head comparison of screening test options (after which viewers are asked to consider which test features are important to them); and (3) selection of a colored brochure corresponding to their screening readiness.

Patient Navigation

The patient navigation intervention is described in the published protocol article.32 Briefly, patient navigators (2 at each site, with a total of 0.75 full-time equivalent/site) were employees of the clinic or its affiliated health system with previous training as medical assistants, social workers, or master’s degree–level public health professionals. They received approximately 6 hours of initial training in CRC navigation, and had monthly check-ins with study team members. Navigators met participants immediately after their clinician encounter and assisted in carrying out the screening plan. Support was tailored based on individual patient factors, including preferred test strategy (FOBT/FIT or colonoscopy), screening barriers, and stage of readiness for screening. Navigators were also able to offer and distribute FOBT/FIT kits using standing orders. After the initial postencounter conversation, navigators periodically tracked intervention participants and attempted to contact unscreened participants at roughly 2-week intervals until participants refused, completed screening, or were deemed unreachable (after 5 attempts).

Main Outcome Measures

The primary study outcome was completion of a CRC screening test within 6 months after the initial study visit. Screening test completion was assessed through electronic health record (EHR) review conducted independently by 2 investigators (R.L.R. and R.H. at the New Mexico site; A.M. and H.T. at theNorth Carolina site) who were masked to study arm assignment and resolved discrepancies by consensus. Patients were considered current with screening if there was evidence of completion of a recommended CRC screening test.3

Power Calculations

Assuming that screening status would be assessed for at least 90% of enrolled participants and a 20% screening rate among controls, we calculated that a total sample of 250 would provide at least 90% power to detect a 20% difference in the primary outcome between the groups using a 2-sided 5% significance level.

Statistical Analysis

We used intention-to-treat analysis, including all participants in their assigned study arm. We used Mantel-Haenszel weights to estimate differences across study arms, adjusted for site. We explored subgroup differences and tested for interactions using a generalized linear model with identity link and binomial variance function.

Other Outcomes

To provide additional data regarding intervention implementation beyond what is published previously,32,33 we reviewed the patient navigation logs, and describe, semiquantitatively, the findings regarding decision aid video viewing, telephone contacts, FOBT/FIT distribution, and barriers addressed. We also summarize screening test results from participant laboratory and/or pathology reports.

Results

Figure 1 shows the flow of study participants. We contacted 670 patients with upcoming primary care appointments who were 50 to 75 years old and without evidence of current CRC screening in their EHRs. Of these, 161 declined to participate, 180 were ineligible, and 64 did not keep or cancelled their appointment, leaving 265 who were randomized. One participant was excluded from the intervention after randomization by his or her clinician (for medical comorbidity) but was included in analysis. We had primary outcome data (from EHR review) on all 265 randomized participants.

Participant characteristics (Table) include a mean age of 58 years; 173 (65%) were female; 164 (62%), Latino; 40 (15%), non-Latino white; and 61 (23%), non-Latino black or mixed race. Spanish was the preferred language in 118 (45%). Most (191 [78%]) reported a household income of less than $20 000; 101 ( 38%) had limited health literacy,39 75 (28%) had Medicaid, 67 (25%) had Medicare, and 91 (34%) were uninsured. Regarding site differences, among (n = 164) participants in New Mexico, 125 (76%) were Latino, 28 (17%) were non-Latino white, and 11 (7%) were non-Latino black, whereas among those recruited in North Carolina (n = 101), 49 (49%) were non-Latino black, 39 (39%) were Latino, and 12 (12%) were non-Latino white. Participants at the New Mexico site were more likely to have Medicaid than those in North Carolina (57 of 164 [35%] vs 18 of 101 [18%]). Demographic characteristics were otherwise similar across sites.

Main Result

Intervention participants were more likely to complete a CRC screening test within 6 months of the index visit: 68% (54% FOBT/FIT, 14% colonoscopy) in the intervention arm (n = 133) vs 27% (21% FOBT/FIT, 6% colonoscopy) in controls (n = 132) (adjusted difference 40 percentage points; 95% CI, 29-51 percentage points; number needed to be offered the intervention to screen 1 additional patient, 3) (Figure 2).

Subgroups

Figure 2 also shows the effect of the intervention by subgroups, along with interaction P values. The intervention was more effective in women than in men (50 vs 21 percentage point improvement in screening). We did observe somewhat larger effects at the New Mexico site vs the North Carolina site, among Latinos vs non-Latinos, and by insurance status, although these differences were not statistically significant. We did not observe differences by education, literacy, or language preference.

Implementation Findings

Pre–clinician encounter activities, including consent, baseline survey, and video viewing, took approximately 45 minutes. Most participants viewed their assigned video in its entirety (intervention group, 88%; controls, 95%). Navigators reported that clinics often ran behind schedule, allowing participants to complete video viewing. Regarding navigator contact, 42 intervention participants completed screening without additional contact after the index visit. Navigators had at least 1 additional contact (usually by phone) with 79 intervention participants, of whom 48 completed screening and 31 did not. Nine were deemed unreachable, 2 declined further intervention, and 1 was excluded by his or her clinician for comorbidities. Navigators reported that common barriers to screening were competing health priorities, forgetting about the stool tests, the time required to complete screening, and losing the FOBT/FIT kit.

Screening Test Results

Among 100 study participants who completed FOBT/FIT, 5 results (5%) were positive. Among the 28 study participants who underwent colonoscopy either as the primary screening test or for follow-up of an abnormal FOBT/FIT test result, 19 (18 had a primary colonoscopy; 1 had follow-up) had normal or hyperplastic polyps, 5 had 1 to 2 small adenomas (low risk), and 3 had 3 or more adenomas or large (≥ 1 cm) adenoma or villous histologic abnormalities (high-risk adenomas) (2 had a primary colonoscopy; 1 had follow-up). One intervention participant who underwent primary screening colonoscopy was found to have stage 0 (in situ) adenocarcinoma within a large, pedunculated polyp. Three participants with positive FOBT/FIT results did not complete a diagnostic colonoscopy: 1 who became critically ill with bowel obstruction (not due to CRC) and 2 who refused despite multiple entreaties from their primary care clinicians.

Discussion

We found that an intervention that combines a patient decision aid shown before a primary care encounter and practice-based patient navigator support delivered after the encounter substantially increased CRC screening test completion compared with usual care in a diverse, vulnerable primary care patient population. The intervention was broadly effective, improving screening completion across multiple subgroups known to have low CRC screening rates, including those with low-income, Spanish-speaking Latinos, those with low education levels, and those with Medicaid insurance.40-44

Several factors likely contributed to the effectiveness of the intervention, driven mainly by increasing FOBT/FIT (although colonoscopy also increased). First, as our previously published intermediate study findings showed,33 the decision aid component of the intervention successfully mitigated several “proximal” barriers to CRC screening by increasing screening-related knowledge of test options, intent, and clinician-patient discussions (including discussion of both FOBT/FIT and colonoscopy). This is consistent with observational studies showing that CRC screening preferences among US clinicians often differ from those of patients and that clinicians often fail to offer stool testing, instead tending to simply recommend colonoscopy.20,45-47

Second, the patient navigation component was apparently successful in addressing more “distal” barriers to CRC screening completion, including not consistently receiving FOBT/FIT kits from clinic staff, losing or forgetting to complete FOBT/FITs, and difficulties scheduling colonoscopy. Although we are unable to separate the relative contributions of the decision aid and patient navigation components, our observed effect size is considerably larger than has been shown in studies of either decision aids or patient navigation alone. A recent meta-analysis21 found that CRC screening decision aids alone typically increase screening by only about 8 percentage points. In addition, while trials of patient navigation have been promising at improving actual test completion in vulnerable populations, the effect sizes have generally been small to moderate, ranging from 2 to 15 percentage points.24-27,31 Our findings of a 40-percentage point increase in screening completion support our hypothesis that decision aids and patient navigation are complementary.32

Third, we suspect that the visit-based approach to patients who were due for screening contributed to the effectiveness of this intervention. Previous studies24,48-50 have found that non–visit-based approaches to delivering decision aids (eg, mailing and/or phone outreach) lead to low uptake of the materials. For many patients, particularly those in vulnerable groups for whom cancer screening may not be salient during their day-to-day lives, an optimal time to deliver the decision aid is during primary care visits. This allows care team members to facilitate viewing and to help patients act on their enhanced intent and informed preferences. Furthermore, we suspect that the visit-based approach caused patients to perceive that the intervention was endorsed by their clinician. This is consistent with strong observational evidence showing that clinician recommendation is a strong and independent predictor of CRC screening.51-55 Our data support the idea that such team-based interventions, which include but are not dependent on the clinician, can promote effective delivery of chronic and preventive care services in a care context in which the primary care clinician is often overwhelmed with competing demands.56,57

Our study reinforces the importance of offering FOBT/FIT testing and extends the findings of Inadomi et al,20 who found that offering FOBT/FIT as a screening option substantially increases CRC screening completion. Our trial differed from the one by Inadomi et al20 in several important ways. First, their study was conducted in a unique care context in which colonoscopy access was guaranteed to underinsured patients, colonoscopy wait times were reduced to 2 weeks or less, and transportation barriers were mitigated. Our trial was conducted in a care context that is more reflective of US community health centers generally. Second, the study by Inadomi et al did not use an explicit patient decision aid to leverage patient preferences regarding screening. In fact, their original hypothesis was that offering patients a choice of screening strategies would actually reduce screening adherence by introducing confusion and uncertainty. Third, their study did not use patient navigation per se, although the bilingual research assistants functioned at times as de facto navigators (eg, by ensuring delivery and assisting with return of FOBT/FIT) and helping with colonoscopy transportation.

Although our intervention was effective, the feasibility of its widespread implementation remains unclear. The primary objective of this study was to test the effectiveness of the combined intervention on screening completion. We assessed implementation only observationally, making this a type 1 “effectiveness-implementation hybrid” study.58 Much of our navigators’ effort was spent on research-related activities, including consent and survey delivery; however, partitioning these activities from intervention activities (eg, decision aid delivery or postencounter navigation) is challenging. In practice, research-related activities would be unnecessary. Furthermore, some intervention activities could be distributed among clinical support staff, constituting only a portion of an individual’s job. Nevertheless, even with optimized work distribution, additional resources may be necessary for high-quality implementation because other investigators have found that implementing patient navigation carries considerable unreimbursed costs.59,60 Hence, implementation may be challenging for community health centers with current resources.

Strengths and Limitations

Our study has methodologic strengths. The RCT design, masked primary outcome assessment, intention-to-treat analysis, and complete primary outcome data reduce risk of bias. Our study also has limitations. First, our design did not allow assessment of independent effects of the intervention components. Second, patient-level randomization could have affected usual care by clinicians, although this would likely have biased findings toward the null. Third, although our EHR review captured CRC screening within each clinic’s health system, some screening could have occurred outside each health system. However, given the access challenges faced by this population, the likelihood that our findings are explained by differential “extramural” CRC screening is extremely low. Finally, our main outcome represented only a single round of screening. Strategies for ensuring programmatic adherence and follow-up of abnormal FOBT/FITs will also be necessary to fully realize mortality benefits from CRC screening.61 Other practice-based interventions will be needed to achieve repeated FOBT/FIT testing adherence,62 including non–visit-based interventions to reach patients who infrequently attend clinic.63

Our study has implications for clinical practice and policy. The USPSTF recently issued new screening guidelines essentially recommending any of several acceptable screening tests. Their guidelines recommend “engaging patients in informed decision making about the screening strategy that would most likely result in completion….”4 Our study provides empirical trial evidence supporting the provision of structured patient decision support along with team-based facilitation of screening completion as part of a “medical home” strategy to increase uptake of this high-value clinical preventive service.

Conclusions

We have shown that this intervention substantially increases CRC screening completion rates in diverse, vulnerable patients, and does so in a way that acknowledges and leverages informed patient preferences. Broader implementation will require that primary practices have the resources to systematically identify patients due for screening and deliver the intervention components. To substantially increase rates of CRC screening in the United States, payment models that allow primary care practices to become true medical homes are needed.

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Article Information

Corresponding Author: Daniel S. Reuland, MD, MPH, Division of General Internal Medicine and Clinical Epidemiology, University of North Carolina School of Medicine, 5045 Old Clinic Building, Chapel Hill, NC 27599-7110 (dreuland@med.unc.edu).

Accepted for Publication: March 7, 2017.

Correction: This article was corrected online on July 3, 2017, to fix errors in the Abstract, Figure 2, and the Funding/Support paragraph.

Published Online: May 15, 2017. doi:10.1001/jamainternmed.2017.1294

Author Contributions: Drs Reuland and Brenner had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Reuland, Brenner, Hoffman, McWilliams, Rhyne, Getrich, Weaver, Callan, Pignone.

Acquisition, analysis, or interpretation of data: Reuland, Brenner, Hoffman, McWilliams, Getrich, Tapp, Weaver, Callan, Cubillos, Urquieta de Hernandez, Pignone.

Drafting of the manuscript: Reuland, Brenner, McWilliams, Weaver.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Reuland, Brenner, Weaver.

Obtained funding: Reuland, Rhyne, Getrich, Callan, Pignone.

Administrative, technical, or material support: Brenner, Rhyne, Getrich, Callan, Cubillos, Urquieta de Hernandez.

Study supervision: Reuland, Brenner, McWilliams, Rhyne, Getrich, Urquieta de Hernandez, Pignone.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was funded by the American Cancer Society (grant RSG-13-165-01–CPPB). Dr Brenner was supported by the Agency for Healthcare Research Quality’s National Research Service Award (grant No. 5-T32HSHS000032). Dr Weaver was also supported by the National Center for Advancing Translational Sciences, National Institutes of Health (grant No. 1UL1TR001111-01). Pilot work for this study was funded by University of New Mexico Clinical and Translational Science Center (grant No. 8UL1TR000041) and the North Carolina Translational and Clinical Sciences Institute at the University of North Carolina (grant No. 1UL1TR001111) and the UNC Lineberger Comprehensive Cancer Center. This study was supported in part by a grant from NIH (DK056350) to the University of North Carolina Nutrition Obesity Research Center OR from NCI (P30-CA16086) to the Lineberger Comprehensive Cancer Center.

Role of the Funder/Sponsor: The American Cancer Society played no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: Dr Pignone is a member of the US Preventive Services Task Force. The views presented herein are not necessarily those of the Task Force.

Additional Contributions: We thank the Colon Cancer Coalition for additional support. The authors also thank paid study team members Anita Martinez, CMA, Diana Gutierrez, CMA, Miriam Espaillat, MS, Patricia Avraham, MBA, and Khalil Harbi, MSPH for their work in data collection and project management.

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