Impact of a Multifaceted Intervention on Promoting Adherence to Screening Colonoscopy Among Persons in HIV Primary Care: A Pilot Study Pansy Ferron, Ph.D., M.P.H., P.A.-C.N.P.1, Shihab S. Asfour, Ph.D.2, Lisa R. Metsch, Ph.D.1,3, Michael H. Antoni, Ph.D.1, Allan E. Rodriguez, M.D.1, Robert Duncan, Ph.D.1, and Sheila M. Findlay, L.C.S.W., M.S.W.1
Abstract HIV-positive patients have lower colon cancer screening rates and are at increased risk for colon adenocarcinoma. We tested a transdisciplinary prevention model to increase provider and patient adherence to screening colonoscopy. Of 1,339 HIV-positive patients with scheduled clinic appointments during the period September to November 2009, we identified 400 records of eligible patients ≥50 years and retrospectively reviewed for screening colonoscopy referral; if never referred, flagged for referral at next visit. Providers referred 43.5% (174/400) patients and 36.2% (63/174) kept appointment. Within 6 months before the study, 337 patients attended clinic and providers referred 18%. Note that 211/226 patients with flagged records attended clinic at least once during the study 6-month period and providers referred (43.6%). The referral rate for flagged records was significantly different from that for the prior 6 months (p < 0.0001). A randomized trial compared the efficacy of patient decision support versus usual care on screening adherence. Among patients randomized to intervention 17 (51.5%) compared to usual care only 16 (48.5%), intervention group showed significant adherence of 70.6% (12/17) versus 29.4% (5/16), (p = 0.024). In addition, intervention patients had good bowel preparation of 76.9% (10/13) versus usual care 23.1% (3/13), (p = 0.05). This transdisciplinary intervention model significantly increased provider and patient screening colonoscopy behavior. Clin Trans Sci 2015; Volume 8: 290–297
Keywords: behavioral studies, colon cancer, HIV, prevention, evidence based medicine
Introduction
Colorectal cancer (CRC) is the nation’s second leading cause of death. An estimated 139,830 men and women will be diagnosed and 50,310 deaths will occur in 2014.1 Among persons living with HIV infection, over one-third (571,500) are persons 45 years and over.2 Blacks have the highest cancer incidence rates, and CRC is the second leading cause of death in this group.3 Despite efforts to close the gap, racial and ethnic health disparities persist in both CRC screening adherence4 and postoperative survival.5 Studies have shown that HIV-positive patients compared to HIV-negative patients were less likely to have CRC screening 17.5% versus 27.5%, and less likely to have received at least one CRC screening procedure 49.3% versus 65.6%.6 Wasserberg et al. conducted a case-controlled study among HIV-infected patients with CRC with two HIV-negative control patients with CRC, matched by age, sex, race, and tumor stage at cancer diagnosis. They compared the results with the Surveillance Epidemiology and End results data. They identified and followed 12 (0.3%) HIV CRC patients out of 3,951 CRC patients for 30 months (6–65). Results showed the median age at CRC diagnosis was 41 years (29–52). The HIV-positive patients had a 3:1 ratio between patients younger and older than 50 years, compared to 1.33 ratio in the general HIV-negative population; also, 90% of HIV-positive patients had advanced stages at diagnosis and had a shorter disease-free survival, compared to 57% in the general population.7 Bini et al. followed HIV-positive patients, n = 131, and HIV negative, n =266 patients who were referred for screening colonoscopy prospectively for the identification of neoplastic lesions from April 2002 to October 2004. They diagnosed 62.5% HIV-positive and 41.5% HIV-negative patient with neoplastic lesions. The HIV-positive patients were more likely to have adenomatous polyps 6–9 mm in
diameter, two or more adenomatous polyps, advanced neoplastic lesions, and adenocarcinoma.8 Colon cancer screening guidelines to detect polyps and cancer The 2010–2011 US Preventive Services Task Force recommendation for colon cancer screening guidelines include recommendations for annual high sensitive fecal occult blood testing, flexible sigmoidoscopy every 5 years, colonoscopy every 10 years.9 Colonoscopy is frequently used for CRC screening in the United States contributing to the increase in CRC prevention rates.10 However, colonoscopy is associated with increased cost, and possible complications such as side effects from sedation, bleeding from biopsy site, or perforation of the colon.11 The barriers to this process include lack of provider recommendation, type of insurance coverage, inefficient referral process, and long wait times for the procedure.12 Elimination of some of these barriers has shown to increase the screening rates in the HIV-negative population though less is known about how the reduction of these barriers affects screening rates in HIV-positive persons.13–16 The behavioral component of the decision-making process is based on the decision maker’s self-efficacy,17 supported by the levels of judgment and capability to make the decision.18 Decision theory, used in human factors engineering decisionmaking research is the study of human decision making under uncertainty; this process involves the selection of one option of several alternatives from the available information, and enhance the performance of human interaction with systems.19,20 Specific to patients’ decision making, this process includes the perceived available choice of options, beliefs, desires, and preferences
University of Miami, Miller School of Medicine, Miami, Florida, USA ; 2University of Miami, Miami, Florida, USA ; 3Columbia University, New York , New York, USA .
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Correspondence: Pansy Ferron ( [email protected]) DOI: 10.1111/cts.12276
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Materials and Methods
Study population The study population was English-speaking persons only, due to budgetary limitations, with HIV/AIDS, 50 years and older receiving care at a university/urban hospital outpatient adult HIV/AIDS clinic population of 2,711 that is part of a safety net hospital and serves all low-income patients. The Institutional Review Board at this hospital approved this study. Study design and data collection This study was conducted in the adult HIV clinic at the UM/ JMH Special Immunology clinics, which serves population of 2,711 patients. The retrospective chart review (Study 1) examined HIV/AIDS provider adherence to referring patients for screening colonoscopy. The randomized controlled study (Study 2) evaluated the efficacy of PDS, colonoscopy video and decision tree, in promoting patient adherence to scheduled appointments and patient satisfaction with the screening experience.
Figure 1. Transdisciplinary patient-centered care model.
associated with the outcomes.21 In addition, the integration of decision theory and patient decision support (PDS) assumes that the decision maker has a preference among the possible presented outcomes.22 Patient-centered care integrates PDS, patient-provider communication, and quality healthcare.23 PDS aid functions as an adjunct to providers’ communication regarding the best available evidence about the screening or treatment.24 Studies show that PDS aids improve patient satisfaction,25 increases patient participation, and improves self-care.26,27 However, little is known about the efficacy of PDS-based interventions in persons with HIV. The increased interest in transdisciplinary initiatives, population health, and elimination of health disparities28 provided the catalyst for integrating evidence-based medicine, behavioral medicine, and human factors decision making into a patientcentered CRC prevention program among HIV-infected patients. This study examines the efficacy of a multifaceted, transdisciplinary intervention model shown in Figure 1. This intervention is based on decision theory, and uses provider and PDS methods to effect change in CRC screening behaviors in a HIV-positive clinic. The study had two components, an observational study of patterns of CRC screening referral in a HIV treatment setting and how the prevalence of screening was affected by raising clinician’s awareness of screening. We hypothesized that the use of a reminder system through chart flagging will promote provider adherence to ordering CRC screening. The second component was a randomized controlled study as a preliminary test of the efficacy of a PDS-based educational intervention for HIV-positive patients. We also hypothesized that that a PDS-based educational video and decision tree intervention will enhance adherence to screening colonoscopy among persons with HIV/AIDS attending an adult HIV primary care clinic and patients receiving the PDSbased educational intervention will show greater screening adherence than those assigned to treatment as usual. WWW.CTSJOURNAL.COM
Retrospective–prospective cohort (Study 1). Flagging of charts Prior to the start of Study 1, we informed each provider of the purpose of the study and that a reminder will be placed in the patients’ charts who are eligible for screening. The clinical team involved five providers board certified in infectious diseases, six internal medicine physicians with specialty in HIV care, and one advanced practice nurse practitioner. Providers were asked to discuss the screening colonoscopy with the patient during the clinic visit and sign the colonoscopy request form if the patient agreed to screening. We reviewed 1,339 medical records of HIV patients with scheduled appointments who kept at least one scheduled clinic appointment during the 12-month period before September 21, 2009 and identified 400 medical records of eligible patients over 50 years. We conducted retrospective review between September 21, 2009 and November 18, 2009 and identified prior provider referral ever made for screening colonoscopy at any period in the clinic visit history. Data collected included referrals made and referral outcomes. We also collected data on patients scheduled for screening colonoscopy within 6 months prior to the start of the study and the number of patients within the cohort who kept clinic appointments. Records of eligible patients were flagged for screening referral by writing, “please refer” on a colored post-it note, then placed on the colonoscopy referral form in the chart. This referral request served as a reminder for the physician to discuss screening colonoscopy with the patient. Figure 2 outlines the study schema. Flagged Records were reviewed up to 6 months after the start of the study for the main outcome measure, whether referrals were or were not made. Randomized controlled trial (Study 2) Study 2 was a randomized controlled trial (RCT) comparing the effects of two study arms: Education Video and Decision Aid and Usual Care versus Usual Care only (described below). Recruitment and randomization for the RCT took place from October 20, 2009 to July 28, 2010. Inclusion criteria included English speaking, willing to give informed consent, and not being treated for any type of cancer. Enrollment and randomization were ongoing throughout 8 months of the trial. The study coordinator/ physician assistant reviewed the medical records of patients for study eligibility on scheduled clinic days. Study participants were selected through a convenience sampling VOLUME 8 • ISSUE 4
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the video with the PA/study coordinator and were encouraged to ask questions after viewing. The video included anatomy of the digestive system, preprocedure preparation, colonoscopy procedures, possible risks, complications, and postprocedure care.30 The decision tree, developed from decision analysis of colorectal screening test by age to begin, age to end, and screening intervals.31 shows the options to screening colonoscopy and probable events, possible alternatives, and outcomes to screening (see Figure 3). The intervention group viewed the colonoscopy video and reviewed of the decision tree with the coordinator before visit with the provider, in addition to the usual process care whereas the control participants received usual care only. Usual care Usual care typically involved; after the patient visit, the provider signed and sent the referral request for colonoscopy to the University of Miami patient clinical associate for future appointment scheduling. The peer educator provided support to patients with Ryan White insurance who were referred for screening. The referral process was the same for both arms. Postintervention assessments Two weeks after randomization, the clinical therapist administered the postintervention colonoscopy self-efficacy questionnaire to both groups by telephone (see Figure 2). Within 2 weeks after the colonoscopy procedure, study patients who completed the procedure were administered a telephone survey about their satisfaction with the screening experience.32 We also collected the GI report and pathology results within 1 month. Ongoing quality assurance of the trial was conducted with the use of a study checklist to ensure that all aspects of the study were completed.
Figure 2. Screening colonoscopy quality process chart: adherence study schema.
method, and were invited verbally with the aid of a script, and then written consent was obtained. Patients were randomized into the intervention (education and decision aid) plus usual care, or usual care arm alone through an adapted Randomization and Allocation Concealment. This study allocation were concealed in envelopes and blocks of eight and 12, then shuffled, stacked by blocks, and numbered.29 We administered baseline assessments and the intervention prior to the patient visit with the provider. Providers were blinded to the randomization schedule and the PA/study coordinator was exempted from providing outpatient clinic care to study patients.
Analytic plan Descriptive statistics summarized patient demographics and covariates. Frequencies were calculated for binary (Y/N) variables, and means, medians, ranges, and standard deviations summarized the continuous variables. The main outcomes for Study 1 were provider adherence to screening colonoscopy guidelines, and for Study 2 the impact of multifaceted intervention on patient adherence, and satisfaction to screening colonoscopy. A chisquare test was used to evaluate provider adherence to screening colonoscopy guidelines in Study 1. For Study 2, analysis of the randomized trial was conducted using the intention to treat analysis. Chi-square statistics evaluated the impact of PDS intervention on patient adherence to screening appointments and analysis of variance (ANOVA) was conducted to examine intervention effects on continuous variables. Secondary analyses in Study 2 examined the effects of patient covariates on patient screening adherence, and the adequacy of patient bowel preparation as documented by the gastroenterologist. Statistical analyses were conducted using SPSS version 17.0 (IBM SPSS International Business Machines Corp Armonk, NY, USA; see Figure 4).
Intervention Conditions
Educational video and decision aid The educational video was a 10-minute module delivered over a computer in the examination room in the clinic. Patients viewed 292
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Results The chart flagging study (Study 1) and randomized sample’s (Study 2) demographic (Table 1) and disease characteristics (Table 2) are shown below. WWW.CTSJOURNAL.COM
Ferron et al. Persons in HIV Primary Care: A Pilot Study ■
Study 1 Results
Providers referred 174 of 400 (43.5%) patients for colonoscopy at least once and 63 (36.2%) patients kept at least one scheduled appointment, 89.6% for screening and 11.4% for diagnostic examinations. Several types of polyps were identified and removed in 19 of 63 (30.6%) patients; 10 of 19 (52.6%) patients were diagnosed with adenomatous polyp, 7 of 19 (36.9%) for hyperplasia, and two of 19 (10.5%) were benign. In addition, 70% (7/10) of patients with adenomatous polyps had CD4 cell count over 500. The number of adenomatous polyps were higher among blacks 7 of 10 (70%) compared to Hispanics 3 of 10 (30%), and the mean age of patients diagnosed with these polyps was 58 (53–69) years. Overall, 386 of 400 (96.5%) records reflected at least one clinic visit within 6 months. Providers referred 111 of 400 patients for screening colonoscopy before 6 months of the start of the study. Sixty-one of 337 (18.1%) patients who were seen within 6 months were referred during this period. Next, 226 of 400 (56.5%) charts were flagged for referral, and then followed for Figure 3. Basic decision tree for screening colonoscopy without probabilities and utilities. provider referrals made up to 6 months after the start of the study. Adherence to clinic appointments was 79.3% (211/266) within 6 months after the start of the study and 92 of 211 (43.6%) patients were referred compared to 61 of 337 (18.1%), within 6 months prior to the start of the study, chi-square p < 0.0001. Study 2 Results
Sample characteristics As shown in Table 3, 33 patients were recruited and randomized, N = 17, (51.5%) into the intervention arm and (N = 16, 48.5%) into usual care arms with mean CD4 cell count 435 mm3 (range = 55–1385). Overall 17 of 33 (51.5%) patients kept the screening colonoscopy appointment, with a greater frequency of adherence in the intervention group, 12 of 17 (70.6%), compared to usual care 5 of 16 (29.4%), p = 0.024, chi-square = 5.107, DF = 1. Polyps were detected and removed from 5 of 16 (29.5%) patients. In addition, 76.4% (13 of 17) had good bowel preparation overall, with a greater frequency evident in the intervention arm 76.9% (10 of 13) compared to 23.1% (3 of 13) in the usual care arm, p = 0.05, chi-square = 5.994, DF = 2. Females assigned to the intervention arm adherence was significantly greater than our observations in the retrospective study group used in Study 1, 81.25% versus 36.5%, p = 0.0003. The presence of multiple comorbid conditions on the quality of bowel preparation, adherence to HAART and to screening was not significantly associated with CRC screening outcomes in either the Study 1 or 2. Study 2: Secondary Analyses Figure 4. Flowchart of participants through each phase of the randomized trial adapted from Davidson et al.50 and Schulz et al.51
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Response to the decision making survey33 (cronbach α = 0.65) showed 72.7% reported providers discussed more than one choice for treatment for any condition. Note that 84.8% reported providers discussed the pros and cons of each choice, and 66.7% VOLUME 8 • ISSUE 4
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Retrospective cohort Gender Race
Male
Female
Age
n
Percentage
n
Percentage
Total
Percentage
Median
Black
159
64
117
77
276
69
55 years
Hispanic
82
33
31
20
113
28
Range 50–80 years
White
7
3
4
3
11
3
Total
248
100
152
100
400
100
Randomized trial Intervention Race
Black
Male
Female
Usual care Total percentage
Male
Female
Total percentage
Age
n
Percentage
n
Percentage
n
Percentage
n
Percentage
n
Percentage
n
Percentage
Median
6
40
9
80
15
88
10
99.1
5
100
30
91
52.8 years
Hispanic
0
00
1
10
1
5.1
1
9
0
00
2
6
Range
Asian
0
00
1
10
1
5.1
0
00
0
00
1
3
50–75 years
Total
6
100
11
100
17
100
11
100
5
100
33
100
Table 1. Patient demographic characteristics.
Retrospective cohort
Randomized trial Usual
Care
n
Percentage
n
Intervention Percentage
n
Percentage
Hypertension
226
56.5
10
58.8
10
62.5
Diabetes mellitus
91
22.8
0
0
3
18.8
Hyperlipidemia
90
22
5
29.4
4
25
Substance abuse
66
16.6
6
35.3
3
18.8
Psychiatric disorder
58
18.3
5
29.4
4
25
Hepatitis
42
10.5
3
17.6
3
18.8
Arthritis
40
9.8
5
29.4
2
12.5
Renal disorders
15
3.8
1
5.9
0
0
Comorbid conditions
n
Percentage
n
Percentage
n
Percentage
79
19.7
3
17.6
2
12.6
One to two
265
66.3
10
58.8
13
81.1
Three to four 50
12.5
4
23.6
1
6.3
6
1.5
0
0
0
0
400
100
17
100
16
100
None
Over four Total Table 2. Comorbid disease characteristics.
reported providers asked which choices they thought would be best for them. Reliability analysis with interitem analyses conducted for baseline CRC screening questionnaire34 showed adequate reliability for perceived susceptibility (α = 0.87) and selfefficacy (α = 0.83). ANOVA revealed no significant differences in perceived susceptibility or self-efficacy for CRC between groups. With regard to social support, when asked if someone in their environment understood their feelings about CRC screening, 294
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75.8% reported yes, 57.6% reported they know someone who was also invited for CRC and 54.5% reported receiving advice to go through CRC screening, and 39.4% reported someone offered to accompany them to CRC screening (cronbach α = 0.77). The Mantel-Haenszel chi-square, odds ratio for screening adherence in the intervention versus usual care arms were all greater than 4 and statistically significant at p < 0.035, and suggested greater perceived social support in the intervention group. Further, WWW.CTSJOURNAL.COM
Ferron et al. Persons in HIV Primary Care: A Pilot Study ■
Female Appointment
Retro
Kept
n
Percentage
n
Yes No
27
36.5
13
47
63.5
3
Total
74
100
16 Male
Appointment
Retro
Kept
n
Percentage
n
Yes
37
35.9
4
No
66
65.1
13
Total
103
100
17
Table 3. Adherence.
there were no group differences in patient satisfaction though satisfaction rates were high. Twenty-nine percent (5/17) in the usual care group and 80% in the intervention group did not recall going through the screening procedure. None of those in the control group reported pain during the procedure and only 2 of 12 (20%) of the intervention group reported some pain. Finally, the mean wait time to screening completion was 14 weeks (SD = 10.3) and ranged from 2 to 31 weeks with no differences between groups. Therefore, it appeared that satisfaction with the colonoscopy experience was positive and equivalent across the two groups. Discussion The provider and patient adherence to screening colonoscopy findings observed in both these studies are likely dependent on multiple factors including provider identification of eligible patients for screening, patients’ preferences, and values and the health system process. Results showed that within 6 months prior to the start of this study, providers referred 18.1% patients for screening colonoscopy; in contrast, they referred 43.6% patients after the reminder for screening was placed in the medical chart. In the randomized trial, 70.6% in the intervention arm were adherent to screening colonoscopy versus 29.4% in usual care. Interestingly we observed 36% prevalence of screening in the retrospective cohort suggesting that the intervention may have increased screening colonoscopy adherence compared to the base US population of 62%.35 Moreover, it appears that the intervention increased the screening rate to above the national rate. As reported in several studies, physicians’ referral for colonoscopy functions as a powerful facilitator that results in increased rates of screening colonoscopy.36 A study involving telephone interviews and onsite consultations reported colonoscopy attendance increasing from 23.4% among patients without intervention to 37.7 % in the intervention group.37 Our study found that a theory-based educational video and decision aid delivered on site improved colonoscopy adherence markedly beyond these levels. The decision-making processes and behaviors are important determinants of health outcomes as patients with multiple chronic illnesses have multiple self-management demands.38 Although study patients reported that providers discussed pros and cons WWW.CTSJOURNAL.COM
of specific treatments with them, educating patients about screening colonoscopy Random before the visit with providers ensures that Percentage they receive the required information to facilitate decision making and to potentiate 81.25 their abilities to ask their providers pertinent 18.75 questions and relevant to screening 100 colonoscopy. To date, this is the first study to test a PDS-based and video designed to promote Random CRC screening in HIV population. These low-income persons have multiple barriers Percentage including neurocognitive deficits and 23.5 lower health literacy39 to improved health 76.5 outcomes in the current healthcare system environment. Also, several studies have 100 identified the effectiveness of educational video among low-literacy population.40 The early diagnosis of adenomatous polyps decreases the probability of mortality from adenocarcinoma colon cancer.41 Over 52.6% (10/19) of the retrospective cohort (Study 1) and 40% of the patients in the RCT (Study 2) studied here were diagnosed with adenomatous polyps. Other studies found adenomatous polyps were more prevalent among HIV-infected compared to HIV-negative patients, 50% versus 23.8%.42 Interestingly, 70% of patients diagnosed with adenomatous polyps had CD4 cell counts over 500 mm3, suggesting that this may be a common condition in non-AIDS diagnosed HIV-positive patients. We provide some preliminary evidence that our intervention may have resulted in a better quality colonoscopy. Good bowel preparation is critical to a successful screening colonoscopy and 76.9% in the educational video intervention arm had good bowel preparation compared to 23.1% in the usual care arm. This illustrates the need for providers to reinforce education on bowel preparation to patients when they write the prescription for bowel cleansing. A few patients reported experiencing pain during the procedure, and the overall satisfaction with the care they received relevant to screening colonoscopy, though high across both study arms, was not significantly better in the intervention arm. In addition, the importance of adequate pain control in patients with chronic pain syndrome should be appropriately addressed, as patients were asked to stop taking NSAIDS 7 days before the procedure. Finally, the mean wait time for screening procedure from the date of referral to screening was over 14 weeks. This delay may have contributed to nonadherence. The presence of comorbid conditions was not associated with nonadherence in the study groups. Also 27.7% in the randomized trial reported some type of depressive symptoms; however, these symptoms were not significantly related to screening adherence. Previous research has shown that depressive symptoms43 and negative mood states44 negatively correlated with patient adherence to highly active antiretroviral therapy (HAART). However, the Women’s Health Initiative Observation Cohort Study showed no association between self-reported depressive symptoms and lower CRC screening45 in line with our observations. We considered the role of personality and interpersonal support factors on study outcomes. CRC screening behavior has been studied using several health behavioral models, and the health belief model emphasizing the perceived susceptibility VOLUME 8 • ISSUE 4
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construct has been among the most widely studied. McQueen et al. identified that perceived susceptibility moderated the change in perceived self-efficacy whereas family influence mediated the effect of perceived susceptibility on CRC screening intention and behavior.46 Interestingly, our patients in the intervention group with lower mean perceived susceptibility to colon cancer were more adherent to screening appointments compared to ones who reported higher susceptibility. Some work suggests that social support may moderate the influence of behavioral interventions on health behaviors including CRC screening.47 In contrast, we found that patients in the intervention group who reported no social support were more likely to keep appointments. This evidence suggests that among the patients with little or no perceived social support the intervention may have functioned as a surrogate for perceived social support. Recommendations Further studies are needed to evaluate the effectiveness of the transdisciplinary model tested in this study using a larger sample of persons with and without HIV infection who meet guidelines for CRC prevention, with emphasis on patient preferences. The relationship between patient perceived susceptibility, self-efficacy, and social support as moderators of patient CRC screening behaviors needs to be further explored in larger samples. A targeted intervention involving patients at greatest risk to screening nonadherence (e.g., socially isolated persons) may benefit those who need it most. Although CRC is identified as one of the non-AIDS defining cancers, it is increasing in the aging population of HIV-positive persons.48 Consequently, the integration of sustainable CRC prevention process supported by electronic medical record system and care coordination within routine HIV-negative and HIV-positive clinic activities may not significantly increase clinic staff and expenses. In addition, one aspect of patient centered care, improved patientprovider communication, is associated with increased delivery of preventive services.49 Limitations There are several limitations to this study. First, this study was conducted in one urban hospital outpatient adult HIV clinic. Second, study participants in the randomized trial were selected through convenience sampling and this is best viewed as a pilot study. Third, we did not include HIV-negative patients, therefore we will include this population in future studies to determine if these results are specific to HIV-positive persons. Fourth, the sample was too small to conduct fine-grained analyses of race/ ethnicity and other individual difference factors. Thus, results may not be generalized to other HIV-positive populations. In addition, we do not have data on patient-provider discussion about colonoscopy screening, and patients enrolled in the study were not offered an alternative screening test to screening colonoscopy. In addition, we did not explore providers’ attitudes and beliefs about patient-provider communication relative to screening colonoscopy among the HIV population; consequently, further studies will include providers caring for HIV-positive and HIV-negative patients Conclusion To date this is the first reported study of a transdisciplinary multifaceted intervention to increase screening colonoscopy adherence in the HIV population. We integrated provider reminder 296
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system, patient informed decision support of colonoscopy educational video and decision tree review, in addition to patient-provider communication to promote increased provider and patient screening colonoscopy behavior. This intervention may have enhanced decision-making support to our providers and patient population with higher disease burden. Therefore, this transdisciplinary CRC prevention model, may significantly decrease morbidity and mortality, and improve quality of life in this population Acknowledgments
The authors thank the patients for their participation and the providers for their contribution to this study, Daniel Sussman MD, division of gastroenterology, University of Miami, Miller School of Medicine for his critical review of this manuscript. This publication was made possible by mentoring support by the Miami Center for AIDS Research (CFAR) at the University of Miami Miller School of Medicine funded by a grant (P30AI073961) from the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. References 1. American Cancer Society. Cancer Facts and Figures 2014, Atlanta, Ga: American Cancer Society, 2014. 2. Centers for Disease Control and Prevention. Diagnoses of HIV infection among adults aged 50 years and older in the United States and dependent areas, 2007–2010. HIV Surveillance Supplemental Report 2013; 18(3): 17–18. 3. Altekruse SF, Kosary CL, Krapcho M, Neyman N, Aminou R, Waldron W, Ruhl J, Howlader N, Tatalovich Z, Cho H, et al., eds. SEER Cancer, Statistics Review, 1975—2007. Bethesda, MD, National Cancer Institute; 2010. Based on November 2009 SEER data Submission, posted to the SEER web site. Available at http://www.seer.cancer.gov/csr/1975_2007/. 4. White A, Vernon SW, Franzini L, Du X. Racial and ethnic disparities in colorectal cancer screening persisted despite expansion of medicare’s screening reimbursement. Cancer Epidemiol Biomarkers Prev. 2011; 20(5): 811–817. doi: 10.1158/1055-9965.EPI-09-0963. 5. Morris AM, Rhoads KF, Stain SC, Birkmeyer JD. Understanding racial disparities in cancer treatment and outcomes. J Am Coll Surg. 2010; 211(1): 105–113. 6. Reinhold JP, Moon M, Tenner CT, Poles MA, Bini EJ. Colorectal cancer screening in HIV-infected patients 50 years of age and older: missed opportunities for prevention. Am J Gastroenterol. 2005; 100: 1805–1812. 7. Wasserberg N, Nunoo-Mensah JW, Gonzalez-Ruiz C, Beart RW Jr, Kaiser AM. Colorectal cancer in HIV infected patients: a case control study. Int J Colorectal Dis. 2007; 910: 1217–1221. 8. Bini EJ, Green B, Poles MA: Screening colonoscopy for the detection of neoplastic lesions in asymptomatic HIV-infected subjects. Gut. 2009; 58(8): 1129–1134. 9. Winawer SJ, Zauber AG, Fletcher RH, Stillman JS, Obrien MJ, Levin B, Smith RA, Lieberman DA, Burt RW, Levin TR, et al. Guidelines for colonoscopy surveillance after polypectomy. Gastroenterology. 2006; 130: 1872–1885. 10. Agency for Healthcare Quality and Research AHRQ. 2011, available at http://www.ahrq.gov/ clinic/pocketgd1011/pocketgd1011.pdf. 11. Lieberman D. Screening for colorectal cancer in average-risk populations. Am J Med. 2006; 119: 728–735. 12. Sonnenberg A, Delco F, Inadomi JM. Cost-effectiveness of colonoscopy screening for colorectal cancer. Ann Inter Med. 2000; 133: 573–584. 13. Nash D, Azeez S, Vlahov D, Schori M. Evaluation of an intervention to increase screening colonoscopy in an urban public hospital setting. J Urban Health: BullNY Acad Med. 2006; 83(2): 231–243. 14. Christie J, Itzkowitz S, Lihau-Nkanza I, Castillo A, Redd W, Jandorf L. A randomized controlled trial using patient navigation to increase colonoscopy screening among low-income minorities. J Natl Med Assoc. 2008; 100(3): 278–284. 15. Carcaise-Edinboro P, Bradley CJ. Influence of patient provider communication on colorectal cancer screening. Med Care. 2008; 46: 738–745. 16. Vincent J, Hochhalter AK, Broglio K, Avotos-Avotins AE: Survey Respondents Planning to have Screening Colonoscopy Report Unique Barriers. Perm J. 2011; 15(1): 4–11. 17. Bandura A: Human agency in social cognitive theory. Am Psychol Am Psychol Assoc Inc. 1989; 44(9): 1175–1184. 18. Butler M, Talley KMC, Burns R, Ripley A, Rothman A, Johnson P, Kane RA, Kane RL: Values of older adults related to primary and secondary prevention. Agency For Healthcare Research and Quality, Report No: 11-05154-EF-1. 2011; Available at http://www.ncbi.nlm.nih.gov/books/ NBK53769.
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19. Endsley MR, Hoffman R, Kaber D, Roth E. Cognitive engineering and decision making. Hum Fact Ergonomics Soc. 2007; 1(1): 1–21. 20. Wickens CD, Lee JL, Liu Y, Gordon-Becker SE. An Introduction to Human Factors Engineering, 2nd edn, NJ: Pearson, Prentice Hill; 2004: 156–165. 21. Thomason R, Robinson A, Greenaway J, Lowe P. On behalf of DARTS team: development and description of a decision analysis based decision support tool for stroke prevention in atrial fibrillation. Qual Saf Health Care. 2002; 11: 25–31. 22. Pate VL, Kaufman DR, Arocha JF: Emerging paradigms of cognition in medical decisionmaking: methodological review. J Biomed Inform. 2002; 35: 52-75. 23. Holmes–Rovner M, Rover DL: Measuring improved patient choice. J Eval Clin Pract. 2000; 6(3): 263–272. 24. Beach M, Duggan P, Moore R. Is patients’ preferred involvement in health decisions related to outcomes. J Gen Intern Med. 2007; 22(8): 1119–1124. 25. Holmes-Rovner M, Nelson WL, Pignone M , Elwyn G, Rovner DR, O’Connor AM, Coulter A, Correa-de-Araujo R. Are patient decision making the best way to improve clinical decisionmaking? Report of the IPDAS symposium. Med Decis Making. 2007; 27: 599–608. doi: 10.1177/0272989×07307272. 26. Golin C, Dim atteo MR, Duan N. Impoverished diabetic patients whose doctors facilitate their participation in medical decision making is more satisfied with their care. J Gen Intern Med. 2002; 866–875. 27. Saba GW, Wong ST, Schillinger D. Shared decision making and the experience of partnership in primary care. Ann Fam Med. 2006; 4(1): 54–62. 28. Hiatt RA, Breen N. The social determinants of cancer: a challenge for transdisciplinary science. Am J Prev Med. 2008; 35(2S). doi:10.1016/j.amepre.2008.05.006. 29. Doig GS, Simpson F. Randomization, and allocation concealment: a practical guide for researchers. J Crit Care. 2005; 20: 189–193.
36. Klabunde CN, Lanier D, Bresiau ES, Zapka JG, Fletcher RH, Ransohoff DF, Winawer SJ. Improving colorectal cancer screening in primary care practice. J Gen Intern Med. 2007; 22(8): 1195–1205. 37. Meng W, Bi XW, Bai XY, Pan HF, Cai SR, Zhao Q, Zhang SZ:. Barrier-focused intervention to increase colonoscopy attendance among nonadherent high-risk populations. World J Gastroenterol. 2009; 15(48): 3920–3925. 38. Wagner EH, Bennett SM, Austin BT, Greene SM, Schaefer J K, Vonkorff MI. Finding common ground: patient–centered evidence-based chronic illness care. J Altern Complement Med. 2005; 11 (Suppl.): S7–S15. 39. Waldrop-Valverde D, Jones DL, Gould F, kumar M, Ownby RL. Neurocognition, health-related literacy, and neumeracy in medication management for HIV infection. AIDS Patient Care STDs. 2010; 24. doi:10.1089/apc.20009.0300. 40. Power E, Miles A, VonWagner C, Robb K, Wardie J. Uptake of colorectal cancer screening: system, provider and individual factors and strategies to improve participation. Future Oncol. 2009; 1371–1388. 41. Zauber AG, Winawer SJ, Obrien MJ, Lansdorp-Vogelaar I, van Ballegooijen M, Hankey BF, Shi W, Bond JH, Schapiro M, Panish JF, et al. Colonoscopic polypectomy and long term prevention of colorectal cancer deaths. N Engl J Med. 2012; 366: 687–696. 42. Iqbal S, Browne-McDonald V, Cerulli MA, Recent trends for colorectal cancer screening in HIV-infected patients. Dig Dis Sci. 2010; 55: 761–766. doi 10.1007/s10620-0009-0774-8. 43. Knowling A, Arnstein J, Eldred L, Wilkinson J, Gourevitch M, Shade S, Dowling K, Purcell D, INSPIRE Team: Individual, interpersonal, and structural correlates of effective HAART use among urban active injections drug users. Acquir Immune Defic Syndr. 2006; 41(4): 486-492. 44. Gonzalez JS, Penedo FJ, Llabre MM, Duran RE, Antoni MH, Schneiderman N, Horne R: Physical symptoms, beliefs about medications, negative mood and long term HIV medication adherence. Ann Behav Med. 2007; 34c(1): 46–55. doi:10,1007/BF02879920.
30. Patient Educational Institute. Colonoscopy interactive tutorial. 1995–2008, Available at http:// www.nlm.nih.gov/medlineplus/tutorials/colonoscopy/htm/index.htm. Accessed February 12, 2008.
45. Aggarwal A, Freund K, Sato A, Adams-Campbell LL, Lopez AM, Lessin LS, Ockene J, Wallace RB, Williams CD, Bonds DE: Are depressive symptoms associated with cancer screening and cancer stage at diagnosis among postmenopausal women? The women’s health initiative observation cohort. J Womens Health. 2008; 17(8): 1221–1223. doi: 10.1089/jwh.2007.0544.
31. 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 US preventive task force. Ann Intern Med. 2008; 149(9): 659–669.
46. McQueen A, Vernon SW, Rothman AJ, Norman GJ, Myers RE, Tilley BC: Examining the role of perceived susceptibility on colorectal cancer screening intention and behavior. Ann Behav Med. 2010; 40(2): 205–217.
32. Cancer Prevention and Control Program. (2006). A Practical Guide to Increasing Screening Colonoscopy. Bureau of Chronic Disease Prevention and Control, the New York City Department of Health and Mental Hygiene and New York Citywide Colon Cancer Control Coalition. Available at http://www.nyc.gov/html/doh/downloads/pdf/cancer/cancer-colonoscopyguide.pdf
47. Kinney AY, Bloor LE, Martin C, Social ties and colorectal cancer screening among Blacks and Whites in North Carolina. Cancer Epidemiol Biomarkers Prev. 2005; 14(1): 182–189.
33. CAHPS® Clinician & Group Survey–Adult Specialty Care Questionnaire. Rockville, MD: Agency for Healthcare Research and Quality; December 2006. Available at https://www.cahps.ahrq.gov/ content/products/CG/PROD_CG_Adult_Specialty.htm. Accessed November 14, 2007.
48. Phillips AA, Justman JE: Screening HIV/AIDS patients for non-AIDS defining malignancies. Curr HIV/AIDS Rep. 2009; 6(2): 83–92. 49. Flash SD, McCoy KD, Vaughn TE, Ward MM, BootsMiller BJ, Doebbeling BN: Does patient-centered care improve provision of preventive services? J Gen Intern Med. 2004; 1019– 1026.
34. Kemers SP, Mesters I, Pladdet IE, van den Borne B, Stockbrügger RW. Participation in a colorectal screening program: a pilot study. Cancer Epidemiol Biomarkers Prev. 2000; l9: 1127–1130.
50. Davidson KW, Goldstein M, Kaplan RM, Kaufmann PG, Knatterud GL, Orleans CT, Spring B, Trudeau KJ, Whitlock EP. Evidence-based behavioral medicine: what is it and how do we achieve it? Ann Behav Med. 2003; 26(3): 161–171.
35. CDC 2013 Colorectal Cancer Screening Rates. Available at http://www.cdc.gov/cancer/ colorectal/statistics/screening_rates.htm. Accessed July 2, 2014.
51. Schulz KF, Altman DG, Moher D. CONSORT 2010 Statement: updated guidelines reporting parallel group randomised trial. BMJ. 2010; 340: c332.
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Abstract HIV-positive patients have lower colon cancer screening rates and are at increased risk for colon adenocarcinoma. We tested a transdisciplinary prevention model to increase provider and patient adherence to screening colonoscopy. Of 1,339 HIV-positive patients with scheduled clinic appointments during the period September to November 2009, we identified 400 records of eligible patients ≥50 years and retrospectively reviewed for screening colonoscopy referral; if never referred, flagged for referral at next visit. Providers referred 43.5% (174/400) patients and 36.2% (63/174) kept appointment. Within 6 months before the study, 337 patients attended clinic and providers referred 18%. Note that 211/226 patients with flagged records attended clinic at least once during the study 6-month period and providers referred (43.6%). The referral rate for flagged records was significantly different from that for the prior 6 months (p < 0.0001). A randomized trial compared the efficacy of patient decision support versus usual care on screening adherence. Among patients randomized to intervention 17 (51.5%) compared to usual care only 16 (48.5%), intervention group showed significant adherence of 70.6% (12/17) versus 29.4% (5/16), (p = 0.024). In addition, intervention patients had good bowel preparation of 76.9% (10/13) versus usual care 23.1% (3/13), (p = 0.05). This transdisciplinary intervention model significantly increased provider and patient screening colonoscopy behavior. Clin Trans Sci 2015; Volume 8: 290–297
Keywords: behavioral studies, colon cancer, HIV, prevention, evidence based medicine
Introduction
Colorectal cancer (CRC) is the nation’s second leading cause of death. An estimated 139,830 men and women will be diagnosed and 50,310 deaths will occur in 2014.1 Among persons living with HIV infection, over one-third (571,500) are persons 45 years and over.2 Blacks have the highest cancer incidence rates, and CRC is the second leading cause of death in this group.3 Despite efforts to close the gap, racial and ethnic health disparities persist in both CRC screening adherence4 and postoperative survival.5 Studies have shown that HIV-positive patients compared to HIV-negative patients were less likely to have CRC screening 17.5% versus 27.5%, and less likely to have received at least one CRC screening procedure 49.3% versus 65.6%.6 Wasserberg et al. conducted a case-controlled study among HIV-infected patients with CRC with two HIV-negative control patients with CRC, matched by age, sex, race, and tumor stage at cancer diagnosis. They compared the results with the Surveillance Epidemiology and End results data. They identified and followed 12 (0.3%) HIV CRC patients out of 3,951 CRC patients for 30 months (6–65). Results showed the median age at CRC diagnosis was 41 years (29–52). The HIV-positive patients had a 3:1 ratio between patients younger and older than 50 years, compared to 1.33 ratio in the general HIV-negative population; also, 90% of HIV-positive patients had advanced stages at diagnosis and had a shorter disease-free survival, compared to 57% in the general population.7 Bini et al. followed HIV-positive patients, n = 131, and HIV negative, n =266 patients who were referred for screening colonoscopy prospectively for the identification of neoplastic lesions from April 2002 to October 2004. They diagnosed 62.5% HIV-positive and 41.5% HIV-negative patient with neoplastic lesions. The HIV-positive patients were more likely to have adenomatous polyps 6–9 mm in
diameter, two or more adenomatous polyps, advanced neoplastic lesions, and adenocarcinoma.8 Colon cancer screening guidelines to detect polyps and cancer The 2010–2011 US Preventive Services Task Force recommendation for colon cancer screening guidelines include recommendations for annual high sensitive fecal occult blood testing, flexible sigmoidoscopy every 5 years, colonoscopy every 10 years.9 Colonoscopy is frequently used for CRC screening in the United States contributing to the increase in CRC prevention rates.10 However, colonoscopy is associated with increased cost, and possible complications such as side effects from sedation, bleeding from biopsy site, or perforation of the colon.11 The barriers to this process include lack of provider recommendation, type of insurance coverage, inefficient referral process, and long wait times for the procedure.12 Elimination of some of these barriers has shown to increase the screening rates in the HIV-negative population though less is known about how the reduction of these barriers affects screening rates in HIV-positive persons.13–16 The behavioral component of the decision-making process is based on the decision maker’s self-efficacy,17 supported by the levels of judgment and capability to make the decision.18 Decision theory, used in human factors engineering decisionmaking research is the study of human decision making under uncertainty; this process involves the selection of one option of several alternatives from the available information, and enhance the performance of human interaction with systems.19,20 Specific to patients’ decision making, this process includes the perceived available choice of options, beliefs, desires, and preferences
University of Miami, Miller School of Medicine, Miami, Florida, USA ; 2University of Miami, Miami, Florida, USA ; 3Columbia University, New York , New York, USA .
1
Correspondence: Pansy Ferron ( [email protected]) DOI: 10.1111/cts.12276
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Materials and Methods
Study population The study population was English-speaking persons only, due to budgetary limitations, with HIV/AIDS, 50 years and older receiving care at a university/urban hospital outpatient adult HIV/AIDS clinic population of 2,711 that is part of a safety net hospital and serves all low-income patients. The Institutional Review Board at this hospital approved this study. Study design and data collection This study was conducted in the adult HIV clinic at the UM/ JMH Special Immunology clinics, which serves population of 2,711 patients. The retrospective chart review (Study 1) examined HIV/AIDS provider adherence to referring patients for screening colonoscopy. The randomized controlled study (Study 2) evaluated the efficacy of PDS, colonoscopy video and decision tree, in promoting patient adherence to scheduled appointments and patient satisfaction with the screening experience.
Figure 1. Transdisciplinary patient-centered care model.
associated with the outcomes.21 In addition, the integration of decision theory and patient decision support (PDS) assumes that the decision maker has a preference among the possible presented outcomes.22 Patient-centered care integrates PDS, patient-provider communication, and quality healthcare.23 PDS aid functions as an adjunct to providers’ communication regarding the best available evidence about the screening or treatment.24 Studies show that PDS aids improve patient satisfaction,25 increases patient participation, and improves self-care.26,27 However, little is known about the efficacy of PDS-based interventions in persons with HIV. The increased interest in transdisciplinary initiatives, population health, and elimination of health disparities28 provided the catalyst for integrating evidence-based medicine, behavioral medicine, and human factors decision making into a patientcentered CRC prevention program among HIV-infected patients. This study examines the efficacy of a multifaceted, transdisciplinary intervention model shown in Figure 1. This intervention is based on decision theory, and uses provider and PDS methods to effect change in CRC screening behaviors in a HIV-positive clinic. The study had two components, an observational study of patterns of CRC screening referral in a HIV treatment setting and how the prevalence of screening was affected by raising clinician’s awareness of screening. We hypothesized that the use of a reminder system through chart flagging will promote provider adherence to ordering CRC screening. The second component was a randomized controlled study as a preliminary test of the efficacy of a PDS-based educational intervention for HIV-positive patients. We also hypothesized that that a PDS-based educational video and decision tree intervention will enhance adherence to screening colonoscopy among persons with HIV/AIDS attending an adult HIV primary care clinic and patients receiving the PDSbased educational intervention will show greater screening adherence than those assigned to treatment as usual. WWW.CTSJOURNAL.COM
Retrospective–prospective cohort (Study 1). Flagging of charts Prior to the start of Study 1, we informed each provider of the purpose of the study and that a reminder will be placed in the patients’ charts who are eligible for screening. The clinical team involved five providers board certified in infectious diseases, six internal medicine physicians with specialty in HIV care, and one advanced practice nurse practitioner. Providers were asked to discuss the screening colonoscopy with the patient during the clinic visit and sign the colonoscopy request form if the patient agreed to screening. We reviewed 1,339 medical records of HIV patients with scheduled appointments who kept at least one scheduled clinic appointment during the 12-month period before September 21, 2009 and identified 400 medical records of eligible patients over 50 years. We conducted retrospective review between September 21, 2009 and November 18, 2009 and identified prior provider referral ever made for screening colonoscopy at any period in the clinic visit history. Data collected included referrals made and referral outcomes. We also collected data on patients scheduled for screening colonoscopy within 6 months prior to the start of the study and the number of patients within the cohort who kept clinic appointments. Records of eligible patients were flagged for screening referral by writing, “please refer” on a colored post-it note, then placed on the colonoscopy referral form in the chart. This referral request served as a reminder for the physician to discuss screening colonoscopy with the patient. Figure 2 outlines the study schema. Flagged Records were reviewed up to 6 months after the start of the study for the main outcome measure, whether referrals were or were not made. Randomized controlled trial (Study 2) Study 2 was a randomized controlled trial (RCT) comparing the effects of two study arms: Education Video and Decision Aid and Usual Care versus Usual Care only (described below). Recruitment and randomization for the RCT took place from October 20, 2009 to July 28, 2010. Inclusion criteria included English speaking, willing to give informed consent, and not being treated for any type of cancer. Enrollment and randomization were ongoing throughout 8 months of the trial. The study coordinator/ physician assistant reviewed the medical records of patients for study eligibility on scheduled clinic days. Study participants were selected through a convenience sampling VOLUME 8 • ISSUE 4
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the video with the PA/study coordinator and were encouraged to ask questions after viewing. The video included anatomy of the digestive system, preprocedure preparation, colonoscopy procedures, possible risks, complications, and postprocedure care.30 The decision tree, developed from decision analysis of colorectal screening test by age to begin, age to end, and screening intervals.31 shows the options to screening colonoscopy and probable events, possible alternatives, and outcomes to screening (see Figure 3). The intervention group viewed the colonoscopy video and reviewed of the decision tree with the coordinator before visit with the provider, in addition to the usual process care whereas the control participants received usual care only. Usual care Usual care typically involved; after the patient visit, the provider signed and sent the referral request for colonoscopy to the University of Miami patient clinical associate for future appointment scheduling. The peer educator provided support to patients with Ryan White insurance who were referred for screening. The referral process was the same for both arms. Postintervention assessments Two weeks after randomization, the clinical therapist administered the postintervention colonoscopy self-efficacy questionnaire to both groups by telephone (see Figure 2). Within 2 weeks after the colonoscopy procedure, study patients who completed the procedure were administered a telephone survey about their satisfaction with the screening experience.32 We also collected the GI report and pathology results within 1 month. Ongoing quality assurance of the trial was conducted with the use of a study checklist to ensure that all aspects of the study were completed.
Figure 2. Screening colonoscopy quality process chart: adherence study schema.
method, and were invited verbally with the aid of a script, and then written consent was obtained. Patients were randomized into the intervention (education and decision aid) plus usual care, or usual care arm alone through an adapted Randomization and Allocation Concealment. This study allocation were concealed in envelopes and blocks of eight and 12, then shuffled, stacked by blocks, and numbered.29 We administered baseline assessments and the intervention prior to the patient visit with the provider. Providers were blinded to the randomization schedule and the PA/study coordinator was exempted from providing outpatient clinic care to study patients.
Analytic plan Descriptive statistics summarized patient demographics and covariates. Frequencies were calculated for binary (Y/N) variables, and means, medians, ranges, and standard deviations summarized the continuous variables. The main outcomes for Study 1 were provider adherence to screening colonoscopy guidelines, and for Study 2 the impact of multifaceted intervention on patient adherence, and satisfaction to screening colonoscopy. A chisquare test was used to evaluate provider adherence to screening colonoscopy guidelines in Study 1. For Study 2, analysis of the randomized trial was conducted using the intention to treat analysis. Chi-square statistics evaluated the impact of PDS intervention on patient adherence to screening appointments and analysis of variance (ANOVA) was conducted to examine intervention effects on continuous variables. Secondary analyses in Study 2 examined the effects of patient covariates on patient screening adherence, and the adequacy of patient bowel preparation as documented by the gastroenterologist. Statistical analyses were conducted using SPSS version 17.0 (IBM SPSS International Business Machines Corp Armonk, NY, USA; see Figure 4).
Intervention Conditions
Educational video and decision aid The educational video was a 10-minute module delivered over a computer in the examination room in the clinic. Patients viewed 292
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Results The chart flagging study (Study 1) and randomized sample’s (Study 2) demographic (Table 1) and disease characteristics (Table 2) are shown below. WWW.CTSJOURNAL.COM
Ferron et al. Persons in HIV Primary Care: A Pilot Study ■
Study 1 Results
Providers referred 174 of 400 (43.5%) patients for colonoscopy at least once and 63 (36.2%) patients kept at least one scheduled appointment, 89.6% for screening and 11.4% for diagnostic examinations. Several types of polyps were identified and removed in 19 of 63 (30.6%) patients; 10 of 19 (52.6%) patients were diagnosed with adenomatous polyp, 7 of 19 (36.9%) for hyperplasia, and two of 19 (10.5%) were benign. In addition, 70% (7/10) of patients with adenomatous polyps had CD4 cell count over 500. The number of adenomatous polyps were higher among blacks 7 of 10 (70%) compared to Hispanics 3 of 10 (30%), and the mean age of patients diagnosed with these polyps was 58 (53–69) years. Overall, 386 of 400 (96.5%) records reflected at least one clinic visit within 6 months. Providers referred 111 of 400 patients for screening colonoscopy before 6 months of the start of the study. Sixty-one of 337 (18.1%) patients who were seen within 6 months were referred during this period. Next, 226 of 400 (56.5%) charts were flagged for referral, and then followed for Figure 3. Basic decision tree for screening colonoscopy without probabilities and utilities. provider referrals made up to 6 months after the start of the study. Adherence to clinic appointments was 79.3% (211/266) within 6 months after the start of the study and 92 of 211 (43.6%) patients were referred compared to 61 of 337 (18.1%), within 6 months prior to the start of the study, chi-square p < 0.0001. Study 2 Results
Sample characteristics As shown in Table 3, 33 patients were recruited and randomized, N = 17, (51.5%) into the intervention arm and (N = 16, 48.5%) into usual care arms with mean CD4 cell count 435 mm3 (range = 55–1385). Overall 17 of 33 (51.5%) patients kept the screening colonoscopy appointment, with a greater frequency of adherence in the intervention group, 12 of 17 (70.6%), compared to usual care 5 of 16 (29.4%), p = 0.024, chi-square = 5.107, DF = 1. Polyps were detected and removed from 5 of 16 (29.5%) patients. In addition, 76.4% (13 of 17) had good bowel preparation overall, with a greater frequency evident in the intervention arm 76.9% (10 of 13) compared to 23.1% (3 of 13) in the usual care arm, p = 0.05, chi-square = 5.994, DF = 2. Females assigned to the intervention arm adherence was significantly greater than our observations in the retrospective study group used in Study 1, 81.25% versus 36.5%, p = 0.0003. The presence of multiple comorbid conditions on the quality of bowel preparation, adherence to HAART and to screening was not significantly associated with CRC screening outcomes in either the Study 1 or 2. Study 2: Secondary Analyses Figure 4. Flowchart of participants through each phase of the randomized trial adapted from Davidson et al.50 and Schulz et al.51
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Response to the decision making survey33 (cronbach α = 0.65) showed 72.7% reported providers discussed more than one choice for treatment for any condition. Note that 84.8% reported providers discussed the pros and cons of each choice, and 66.7% VOLUME 8 • ISSUE 4
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Retrospective cohort Gender Race
Male
Female
Age
n
Percentage
n
Percentage
Total
Percentage
Median
Black
159
64
117
77
276
69
55 years
Hispanic
82
33
31
20
113
28
Range 50–80 years
White
7
3
4
3
11
3
Total
248
100
152
100
400
100
Randomized trial Intervention Race
Black
Male
Female
Usual care Total percentage
Male
Female
Total percentage
Age
n
Percentage
n
Percentage
n
Percentage
n
Percentage
n
Percentage
n
Percentage
Median
6
40
9
80
15
88
10
99.1
5
100
30
91
52.8 years
Hispanic
0
00
1
10
1
5.1
1
9
0
00
2
6
Range
Asian
0
00
1
10
1
5.1
0
00
0
00
1
3
50–75 years
Total
6
100
11
100
17
100
11
100
5
100
33
100
Table 1. Patient demographic characteristics.
Retrospective cohort
Randomized trial Usual
Care
n
Percentage
n
Intervention Percentage
n
Percentage
Hypertension
226
56.5
10
58.8
10
62.5
Diabetes mellitus
91
22.8
0
0
3
18.8
Hyperlipidemia
90
22
5
29.4
4
25
Substance abuse
66
16.6
6
35.3
3
18.8
Psychiatric disorder
58
18.3
5
29.4
4
25
Hepatitis
42
10.5
3
17.6
3
18.8
Arthritis
40
9.8
5
29.4
2
12.5
Renal disorders
15
3.8
1
5.9
0
0
Comorbid conditions
n
Percentage
n
Percentage
n
Percentage
79
19.7
3
17.6
2
12.6
One to two
265
66.3
10
58.8
13
81.1
Three to four 50
12.5
4
23.6
1
6.3
6
1.5
0
0
0
0
400
100
17
100
16
100
None
Over four Total Table 2. Comorbid disease characteristics.
reported providers asked which choices they thought would be best for them. Reliability analysis with interitem analyses conducted for baseline CRC screening questionnaire34 showed adequate reliability for perceived susceptibility (α = 0.87) and selfefficacy (α = 0.83). ANOVA revealed no significant differences in perceived susceptibility or self-efficacy for CRC between groups. With regard to social support, when asked if someone in their environment understood their feelings about CRC screening, 294
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75.8% reported yes, 57.6% reported they know someone who was also invited for CRC and 54.5% reported receiving advice to go through CRC screening, and 39.4% reported someone offered to accompany them to CRC screening (cronbach α = 0.77). The Mantel-Haenszel chi-square, odds ratio for screening adherence in the intervention versus usual care arms were all greater than 4 and statistically significant at p < 0.035, and suggested greater perceived social support in the intervention group. Further, WWW.CTSJOURNAL.COM
Ferron et al. Persons in HIV Primary Care: A Pilot Study ■
Female Appointment
Retro
Kept
n
Percentage
n
Yes No
27
36.5
13
47
63.5
3
Total
74
100
16 Male
Appointment
Retro
Kept
n
Percentage
n
Yes
37
35.9
4
No
66
65.1
13
Total
103
100
17
Table 3. Adherence.
there were no group differences in patient satisfaction though satisfaction rates were high. Twenty-nine percent (5/17) in the usual care group and 80% in the intervention group did not recall going through the screening procedure. None of those in the control group reported pain during the procedure and only 2 of 12 (20%) of the intervention group reported some pain. Finally, the mean wait time to screening completion was 14 weeks (SD = 10.3) and ranged from 2 to 31 weeks with no differences between groups. Therefore, it appeared that satisfaction with the colonoscopy experience was positive and equivalent across the two groups. Discussion The provider and patient adherence to screening colonoscopy findings observed in both these studies are likely dependent on multiple factors including provider identification of eligible patients for screening, patients’ preferences, and values and the health system process. Results showed that within 6 months prior to the start of this study, providers referred 18.1% patients for screening colonoscopy; in contrast, they referred 43.6% patients after the reminder for screening was placed in the medical chart. In the randomized trial, 70.6% in the intervention arm were adherent to screening colonoscopy versus 29.4% in usual care. Interestingly we observed 36% prevalence of screening in the retrospective cohort suggesting that the intervention may have increased screening colonoscopy adherence compared to the base US population of 62%.35 Moreover, it appears that the intervention increased the screening rate to above the national rate. As reported in several studies, physicians’ referral for colonoscopy functions as a powerful facilitator that results in increased rates of screening colonoscopy.36 A study involving telephone interviews and onsite consultations reported colonoscopy attendance increasing from 23.4% among patients without intervention to 37.7 % in the intervention group.37 Our study found that a theory-based educational video and decision aid delivered on site improved colonoscopy adherence markedly beyond these levels. The decision-making processes and behaviors are important determinants of health outcomes as patients with multiple chronic illnesses have multiple self-management demands.38 Although study patients reported that providers discussed pros and cons WWW.CTSJOURNAL.COM
of specific treatments with them, educating patients about screening colonoscopy Random before the visit with providers ensures that Percentage they receive the required information to facilitate decision making and to potentiate 81.25 their abilities to ask their providers pertinent 18.75 questions and relevant to screening 100 colonoscopy. To date, this is the first study to test a PDS-based and video designed to promote Random CRC screening in HIV population. These low-income persons have multiple barriers Percentage including neurocognitive deficits and 23.5 lower health literacy39 to improved health 76.5 outcomes in the current healthcare system environment. Also, several studies have 100 identified the effectiveness of educational video among low-literacy population.40 The early diagnosis of adenomatous polyps decreases the probability of mortality from adenocarcinoma colon cancer.41 Over 52.6% (10/19) of the retrospective cohort (Study 1) and 40% of the patients in the RCT (Study 2) studied here were diagnosed with adenomatous polyps. Other studies found adenomatous polyps were more prevalent among HIV-infected compared to HIV-negative patients, 50% versus 23.8%.42 Interestingly, 70% of patients diagnosed with adenomatous polyps had CD4 cell counts over 500 mm3, suggesting that this may be a common condition in non-AIDS diagnosed HIV-positive patients. We provide some preliminary evidence that our intervention may have resulted in a better quality colonoscopy. Good bowel preparation is critical to a successful screening colonoscopy and 76.9% in the educational video intervention arm had good bowel preparation compared to 23.1% in the usual care arm. This illustrates the need for providers to reinforce education on bowel preparation to patients when they write the prescription for bowel cleansing. A few patients reported experiencing pain during the procedure, and the overall satisfaction with the care they received relevant to screening colonoscopy, though high across both study arms, was not significantly better in the intervention arm. In addition, the importance of adequate pain control in patients with chronic pain syndrome should be appropriately addressed, as patients were asked to stop taking NSAIDS 7 days before the procedure. Finally, the mean wait time for screening procedure from the date of referral to screening was over 14 weeks. This delay may have contributed to nonadherence. The presence of comorbid conditions was not associated with nonadherence in the study groups. Also 27.7% in the randomized trial reported some type of depressive symptoms; however, these symptoms were not significantly related to screening adherence. Previous research has shown that depressive symptoms43 and negative mood states44 negatively correlated with patient adherence to highly active antiretroviral therapy (HAART). However, the Women’s Health Initiative Observation Cohort Study showed no association between self-reported depressive symptoms and lower CRC screening45 in line with our observations. We considered the role of personality and interpersonal support factors on study outcomes. CRC screening behavior has been studied using several health behavioral models, and the health belief model emphasizing the perceived susceptibility VOLUME 8 • ISSUE 4
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construct has been among the most widely studied. McQueen et al. identified that perceived susceptibility moderated the change in perceived self-efficacy whereas family influence mediated the effect of perceived susceptibility on CRC screening intention and behavior.46 Interestingly, our patients in the intervention group with lower mean perceived susceptibility to colon cancer were more adherent to screening appointments compared to ones who reported higher susceptibility. Some work suggests that social support may moderate the influence of behavioral interventions on health behaviors including CRC screening.47 In contrast, we found that patients in the intervention group who reported no social support were more likely to keep appointments. This evidence suggests that among the patients with little or no perceived social support the intervention may have functioned as a surrogate for perceived social support. Recommendations Further studies are needed to evaluate the effectiveness of the transdisciplinary model tested in this study using a larger sample of persons with and without HIV infection who meet guidelines for CRC prevention, with emphasis on patient preferences. The relationship between patient perceived susceptibility, self-efficacy, and social support as moderators of patient CRC screening behaviors needs to be further explored in larger samples. A targeted intervention involving patients at greatest risk to screening nonadherence (e.g., socially isolated persons) may benefit those who need it most. Although CRC is identified as one of the non-AIDS defining cancers, it is increasing in the aging population of HIV-positive persons.48 Consequently, the integration of sustainable CRC prevention process supported by electronic medical record system and care coordination within routine HIV-negative and HIV-positive clinic activities may not significantly increase clinic staff and expenses. In addition, one aspect of patient centered care, improved patientprovider communication, is associated with increased delivery of preventive services.49 Limitations There are several limitations to this study. First, this study was conducted in one urban hospital outpatient adult HIV clinic. Second, study participants in the randomized trial were selected through convenience sampling and this is best viewed as a pilot study. Third, we did not include HIV-negative patients, therefore we will include this population in future studies to determine if these results are specific to HIV-positive persons. Fourth, the sample was too small to conduct fine-grained analyses of race/ ethnicity and other individual difference factors. Thus, results may not be generalized to other HIV-positive populations. In addition, we do not have data on patient-provider discussion about colonoscopy screening, and patients enrolled in the study were not offered an alternative screening test to screening colonoscopy. In addition, we did not explore providers’ attitudes and beliefs about patient-provider communication relative to screening colonoscopy among the HIV population; consequently, further studies will include providers caring for HIV-positive and HIV-negative patients Conclusion To date this is the first reported study of a transdisciplinary multifaceted intervention to increase screening colonoscopy adherence in the HIV population. We integrated provider reminder 296
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system, patient informed decision support of colonoscopy educational video and decision tree review, in addition to patient-provider communication to promote increased provider and patient screening colonoscopy behavior. This intervention may have enhanced decision-making support to our providers and patient population with higher disease burden. Therefore, this transdisciplinary CRC prevention model, may significantly decrease morbidity and mortality, and improve quality of life in this population Acknowledgments
The authors thank the patients for their participation and the providers for their contribution to this study, Daniel Sussman MD, division of gastroenterology, University of Miami, Miller School of Medicine for his critical review of this manuscript. This publication was made possible by mentoring support by the Miami Center for AIDS Research (CFAR) at the University of Miami Miller School of Medicine funded by a grant (P30AI073961) from the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. References 1. American Cancer Society. Cancer Facts and Figures 2014, Atlanta, Ga: American Cancer Society, 2014. 2. Centers for Disease Control and Prevention. Diagnoses of HIV infection among adults aged 50 years and older in the United States and dependent areas, 2007–2010. HIV Surveillance Supplemental Report 2013; 18(3): 17–18. 3. Altekruse SF, Kosary CL, Krapcho M, Neyman N, Aminou R, Waldron W, Ruhl J, Howlader N, Tatalovich Z, Cho H, et al., eds. SEER Cancer, Statistics Review, 1975—2007. Bethesda, MD, National Cancer Institute; 2010. Based on November 2009 SEER data Submission, posted to the SEER web site. Available at http://www.seer.cancer.gov/csr/1975_2007/. 4. White A, Vernon SW, Franzini L, Du X. Racial and ethnic disparities in colorectal cancer screening persisted despite expansion of medicare’s screening reimbursement. Cancer Epidemiol Biomarkers Prev. 2011; 20(5): 811–817. doi: 10.1158/1055-9965.EPI-09-0963. 5. Morris AM, Rhoads KF, Stain SC, Birkmeyer JD. Understanding racial disparities in cancer treatment and outcomes. J Am Coll Surg. 2010; 211(1): 105–113. 6. Reinhold JP, Moon M, Tenner CT, Poles MA, Bini EJ. Colorectal cancer screening in HIV-infected patients 50 years of age and older: missed opportunities for prevention. Am J Gastroenterol. 2005; 100: 1805–1812. 7. Wasserberg N, Nunoo-Mensah JW, Gonzalez-Ruiz C, Beart RW Jr, Kaiser AM. Colorectal cancer in HIV infected patients: a case control study. Int J Colorectal Dis. 2007; 910: 1217–1221. 8. Bini EJ, Green B, Poles MA: Screening colonoscopy for the detection of neoplastic lesions in asymptomatic HIV-infected subjects. Gut. 2009; 58(8): 1129–1134. 9. Winawer SJ, Zauber AG, Fletcher RH, Stillman JS, Obrien MJ, Levin B, Smith RA, Lieberman DA, Burt RW, Levin TR, et al. Guidelines for colonoscopy surveillance after polypectomy. Gastroenterology. 2006; 130: 1872–1885. 10. Agency for Healthcare Quality and Research AHRQ. 2011, available at http://www.ahrq.gov/ clinic/pocketgd1011/pocketgd1011.pdf. 11. Lieberman D. Screening for colorectal cancer in average-risk populations. Am J Med. 2006; 119: 728–735. 12. Sonnenberg A, Delco F, Inadomi JM. Cost-effectiveness of colonoscopy screening for colorectal cancer. Ann Inter Med. 2000; 133: 573–584. 13. Nash D, Azeez S, Vlahov D, Schori M. Evaluation of an intervention to increase screening colonoscopy in an urban public hospital setting. J Urban Health: BullNY Acad Med. 2006; 83(2): 231–243. 14. Christie J, Itzkowitz S, Lihau-Nkanza I, Castillo A, Redd W, Jandorf L. A randomized controlled trial using patient navigation to increase colonoscopy screening among low-income minorities. J Natl Med Assoc. 2008; 100(3): 278–284. 15. Carcaise-Edinboro P, Bradley CJ. Influence of patient provider communication on colorectal cancer screening. Med Care. 2008; 46: 738–745. 16. Vincent J, Hochhalter AK, Broglio K, Avotos-Avotins AE: Survey Respondents Planning to have Screening Colonoscopy Report Unique Barriers. Perm J. 2011; 15(1): 4–11. 17. Bandura A: Human agency in social cognitive theory. Am Psychol Am Psychol Assoc Inc. 1989; 44(9): 1175–1184. 18. Butler M, Talley KMC, Burns R, Ripley A, Rothman A, Johnson P, Kane RA, Kane RL: Values of older adults related to primary and secondary prevention. Agency For Healthcare Research and Quality, Report No: 11-05154-EF-1. 2011; Available at http://www.ncbi.nlm.nih.gov/books/ NBK53769.
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