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The American Journal of Managed Care July 2014
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Managed Care Patients' Preferences, Physician Recommendations, and Colon Cancer Screening
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Managed Care Patients' Preferences, Physician Recommendations, and Colon Cancer Screening

Sarah Hawley, PhD, MPH; Sarah Lillie, PhD; Greg Cooper, MD; and Jennifer Elston Lafata, PhD
CRC screening rates in a large managed care organization were low. Among those screened, use was associated more with physicians' recommendations than with patient preferences.
To evaluate associations between patients’ preferences for attributes of different colorectal (CRC) screening modalities, physician CRC screening recommendations during periodic health exams, and subsequent utilization of screening 12 months later in a large health maintenance organization (HMO).

Study Design
Multi-method study including baseline surveys from average-risk HMO members joined with audio recordings of 415 periodic health exams (PHEs) and electronic medical record (EMR) data.

Patient ratings of test attributes were used to create an algorithm reflecting type and strength of CRC screening modality preference at baseline. Physician recommendations were obtained from audio recordings. Attribute-based test preferences and physician recommendations were compared with CRC test use using chisquare tests. Associations between attribute-based preferences and physician recommendations were assessed using logistic regression.

Based on attribute rankings, most participants had a weak preference for colonoscopy (COL) (41%), an unclear preference (22.4%), or a weak preference for fecal occult blood testing (FOBT) (18.6%). About half (56%) of patients were screened at 12 months and there was no statistical association between attribute preferences and type of test received. Patients were significantly more likely to receive a recommendation including a test other than COL when they had an attribute-based test preference for FOBT (odds ratio [OR]: 2.17; 95% CI, 1.26-3.71; P <.01).

CRC screening test use in this large HMO was generally low. It was not associated with patients’ preferences for different attributes of CRC screening tests but was associated with physician recommendations. Physicians may have better success in getting patients to screen if they consider preferences for test attributes.

Am J Manag Care. 2014;20(7):555-561
  • Colorectal cancer (CRC) screening test use in a large health maintenance organization (HMO) was relatively low (56%).

  • Patients had CRC screening preferences that could be linked to attributes of different tests.

  • HMO members more often received the screening test that was recommended by their physician, usually colonoscopy, than the test that was consistent with their preferences.

  • Physicians appeared willing to consider preferences for tests other than colonoscopy, so adherence with CRC may be increased if patients' preferences can be incorporated into recommendations.
Studies have found variation in the proportion of adults who are adherent with colorectal cancer (CRC) screening, with reports ranging from 45% to 70%,1-3 yet there remains consensus that there is room for improvement, particularly in managed care settings where there is generally coverage for all types of CRC screening. There are several options for CRC screening,4-6 but increasingly, only colonoscopy (COL) and fecal occult blood testing (FOBT) are used in clinical practice.7,8 Low rates of CRC screening uptake, combined with the existence of more than 1 appropriate test, have led some to suggest that offering patients the test they prefer may be an effective method for increasing CRC screening adherence.9,10

This argument is supported by several studies that have documented variation in preferences for CRC screening tests across populations.9,11-19 Overall, these studies have shown that patient preferences can be linked to specific attributes of the screening tests, such as the preparation involved.13-18 Yet only a few studies have evaluated associations among patient preferences for key attributes of CRC screening tests, test ordering by physician, and test utilization.11,14,19

Missing from these studies is an examination of whether attribute-based test preferences are incorporated into physician CRC screening recommendations. The importance of having a physician recommendation in screening uptake has been well documented.18-20 Yet increasingly, physicians are recommending COL and often do not offer patients a choice of screening options.21 The recent National Institutes of Health State-of-the-Science Conference Statement on CRC screening has called for a continued need to understand the role of patient preferences in CRC screening adherence.22

We used data from an observational study conducted in a managed care setting to better understand associations among the preferences of average-risk adults for key attributes of CRC screening tests, physician test recommendations, and subsequent use of CRC screening. We had 3 objectives: 1) to describe the distribution of preferences for key attributes of CRC screening tests and to link these attributes to existing CRC screening modalities; 2) to evaluate the association between physician recommendation for CRC screening modalities and attribute-based CRC screening test preferences; and 3) to compare CRC screening utilization 12 months post visit with attribute-based CRC screening test preferences and physician recommendation.


The data used in this analysis came from a study of patient-provider discussions about CRC screening conducted in a large health maintenance organization (HMO) located in southeast Michigan (R01CA112379). Additional details about the study are provided elsewhere.1,13,23,24

Participant Eligibility Criteria and Recruitment

Participating physicians (N = 64) were salaried family and general internal medicine physicians affiliated with a managed care group in southeast Michigan. Participating physicians agreed to allow scheduled periodic health exam (PHE) visits of their eligible patients to be audiorecorded, with patient consent.

Patients (N = 500) were insured, aged 50 to 80 years, and due for CRC screening (eg, never screened with any of the recommended tests or overdue for screening based on US Preventive Services Task Force [USPSTF] guidelines) at the time of a PHE with a study-participating physician from February 2007 to June 2009. All patient participants in the study were able to receive either FOBT or COL for screening purposes without a co-payment as part of their managed care coverage. Patients identi- fied via electronic medical record (EMR) and appointment scheduling data were sent an introduction letter and called approximately 2 weeks prior to their PHE to confirm eligibility, and to complete a pre-visit telephone survey. Participants were asked to arrive at their scheduled PHE early to enable completion of informed consent prior to audio-recording of the PHE. Participants received a $25 gift card. All aspects of the study were approved by the Institutional Review Boards of the Henry Ford Medical Group, Case Western Reserve University, and Virginia Commonwealth University.

Data Sources & Measures

There were 3 primary outcomes for this analysis: 1) attribute-based CRC screening test preferences prior to the PHE, generated from patient survey responses to a list of key CRC screening attributes; 2) primary care physician recommendation for CRC screening test(s) that occurred during the PHE obtained via office visit audio recording; and 3) CRC test utilization 12 months following the PHE obtained via EMR data. Each is described below.

Attribute-based CRC screening test preferences: In the pre-visit telephone survey, patients ranked 7 key attributes of screening tests. These attributes were obtained from prior literature that had assessed CRC screening preferences via a list of attributes.9,13-18 Based on this literature, the attributes selected for the survey were test accuracy, preparation required, complications/side effects, need for sedation, frequency of the test, degree of pain/discomfort, and whether a stool sample was necessary. Participants ranked each attribute first, second, and third most important when deciding which screening test to use. We developed an algorithm (Table 1) from patient rankings to categorize patients into attribute-based CRC test preference groups. Our algorithm was based on other attribute-based preference elicitation methods, including conjoint analysis (CA) and the analytic hierarchy process (AHP), which require respondents to engage with complex scenarios or systematic deconstruction of decisions into subsets of attributes. Both CA and AHP have been used to assess preferences for CRC screening, and research has found that certain key attributes can be linked to preferences for specific CRC tests.9,25,26 Because these methods are conceptually difficult and typically cannot be done via a telephone survey, we developed a telephone-based approach to assessing them in our study and used our algorithm to link them to preferences for different CRC tests.

Using participant rankings, the following CRC screening test preference structures were generated: 1) strong COL preference (accuracy first, preparation and complications not ranked); 2) weak COL preference (accuracy first,preparation or complications second or third); 3) strong FOBT preference (preparation or complications first, accuracy not ranked); and 4) weak FOBT preference (preparation or complications second, accuracy second or third). Those whose attribute rankings did not fall into one of these 4 groups were categorized into a fifth group labeled “unclear preference.” An unclear preference included individuals who ranked any of the other attributes in their top 3, but where it was not possible to link these preferences to a test. Because of the small number of patients with strong preferences for either FOBT or COL, for analyses we consolidated the 2 FOBT preference groups and the 2 COL preference groups to create a final preference measure with 3 groups: FOBT, COL, or unclear.

Physician CRC screening recommendations: Physician CRC modality recommendation during the PHE was obtained from audio recordings. Details regarding the coding of the content of the PHE related to CRC screening discussions are provided elsewhere.23,24 Because of the high rate of recommendation for COL, we categorized recommendations into 2 groups: COL-only versus COL-plus another test, which was almost universally FOBT (eg, “COL-plus”). All visits included in this analysis were PHEs of patients who were eligible or overdue for CRC screening. Visits by patients who had received a prior screening test in the recommended time frame were not eligible for this study, and visits in which COL was recommended as an appropriate follow-up to a positive FOBT were not included in this study.

CRC Test Utilization

CRC test use in the 12 months post PHE was collected from the EMR. Because of the small number of patients receiving barium enema or sigmoidoscopy (N = 5), we excluded those patients and created a variable measuring CRC screening receipt at 12 months with the following categorization: 1) COL only; 2) FOBT only; 3) COL and FOBT; 4) no screening.

Independent Variables

The primary covariates used in this analysis were patient demographics that were assessed via patient self- report from the pre-visit survey. These characteristics included: age, race (white vs African American/other), gender, education (high school or less vs some college or more) and income (<$40,000 vs $40,000 to <$80,000 vs >$80,000 or more).


The analyses followed the research objectives and were conducted accordingly in 3 phases.

Attribute-Based CRC Screening Test Preferences

First, we generated a description of the sample according to the patients’ demographic factors. To assess the importance of each attribute, we calculated the proportion of patients who ranked each attribute 1st, 2nd, and 3rd. We then applied our algorithm to categorize baseline CRC test preferences into the 5 categories as described above. Next, we evaluated associations between baseline preferences and patient demographic factors using X2 tests. We then conducted multinomial logistic regression (MNL) to further evaluate associations between baseline preferences and participants’ demographic characteristics using the 3-level preferences variable (COL-strong/weak, FOBT−strong/weak, unclear), with COL−strong/weak as the referent category.

Physician CRC Screening Recommendations

We conducted a logistic regression of our 2-level recommendation variable (COL-only vs COL-plus) using the latter as the referent category. We conducted this regression in a stepwise manner, with Model 1 including only patient demographics as independent variables, and Model 2 including both demographics and baseline test preferences. In these analyses we adjusted for clustering by the physician’s identification number.

Associations With CRC Test Utilization

We compared both baseline test preferences and physician recommendations with CRC screening test utilization 12 months following the PHE using X2 tests.


Participant Characteristics

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