The Peace of Mind Program (PMP) is an active listening, tailored telephone reminder call intervention to counsel women through barriers to mammography screening appointment attendance.28-29 Each woman during the intervention period received up to three reminder call attempts for their scheduled mammography screening appointment at a clinical site. If the woman did not answer on the first attempt, two additional attempts were made to reach the woman. If the woman answered the phone call, but did not consent to participate in the study, she was reminded about her appointment in the usual care manner of each site. If she answered and consented to participate, a Certified Community Health Worker (CHW) who made the call assessed the woman’s confidence in attending their scheduled mammography appointment, counseled the woman through barriers to attending the appointment, and recorded the woman’s responses in an online interface program designed in RedCap. The results of each reminder phone call, whether the call was completed or a message left, and the woman’s resulting mammography appointment attendance or no-show status were also recorded in RedCap. RedCap served as the online platform for both data storage and initial data analysis for this study.
Prior to implementation of PMP, potential clinics were engaged through various adoption strategies including adoption meetings, webinars, and an adoption survey measuring Consolidated Framework for Implementation Research (CFIR) constructs across multiple domains. Those clinics who adopted the program then participated in several implementation strategies, including: stakeholder meetings, a continuing education unit (CEU) certified 2-day training for clinic community health workers (CHWs), and a site readiness assessment checklist to prepare for implementation. In addition, the community partner – the Breast Health Collaborative of Texas (BHCTexas) – and research team worked with participating clinics to align goals for mobile mammography drives and facilitated relationships with mobile providers as needed to support implementation. Onsite role modeling and support from BHCTexas CHWs and ongoing technical support from the research team was provided throughout PMP intervention implementation. Financial resources included a $7500 stipend for clinic participation and financial assistance for women to receive free screening. At eight weeks post-implementation, clinics were invited to complete an implementation survey to assess the same constructs as the adoption survey. A full description of the development, adoption, implementation, and stakeholder engagement components of the PMP intervention has been reported elsewhere.28-30
A non-randomized stepped wedge cluster design was used to assign clinics into two non-concurrent implementation waves with two to three groups in each wave. 28 In order to participate in PMP, clinics must: (1) have been members of BHCTexas within the Greater Houston service area, (2) had a designation as a FQHC by the Health Resources and Services Administration (HRSA) or be a charity clinic which provides free or reduced cost care to underserved populations in their service area, (3) serve women between the ages of 40 to 64 years old who were at or below 200 % of the federal poverty level for a family of four and who lacked health insurance, and (4) engage in provision of mammography screening services at least six times per year (three in baseline; three in intervention) and (5) women at the clinic must have been in need of mammography screening and be scheduled for an upcoming appointment. Patients must have completed a clinical breast exam prior to their scheduled screening appointment per mobile provider requirements. Variation across clinics existed in frequency of mammography drives, number of patients scheduled in each drive, number of staff available to participate in PMP, existing relationships with mobile mammography providers, and available funding and resources which resulted in differences in clinic readiness to start the PMP intervention. Due to these differences, the randomized allocation of the clinics into waves and groups as previously described was not possible. Clinics that had lower levels of readiness were assigned to later groups to benefit from more time to receive implementation strategies from PMP. Each clinic served as its own control during the baseline period and was required to have at least three mammography drives during both the baseline and intervention periods. Clinic, BHCTexas, and research team staff were not blinded in the study. Since each clinic served as its own control during the baseline period, blinding was not possible or necessary for this study.
The dependent variable was a dichotomous variable indicating mammography appointment adherence with a no-show or cancelled appointment categorized as “0” and an attended or rescheduled appointment categorized as “1.”
The independent variables of interest are two dichotomous variables indicating study period, baseline period (categorized as “0”) or intervention period (categorized as “1”) and for the intervention period, whether the patient did not complete (categorized as “0”) or did complete (categorized as “1”) the PMP intervention. A patient completed the intervention if they answered the reminder call, consented to the study, received the staging question assessing confidence and barriers counseling. In addition, patient, intervention, and clinic variables examined in the analysis of the data included age, season, wave, group, mobile mammography provider, and clinic racial/ethnic distribution. Age was categorized into three age groups – 55 and above, 45 to 54 and 25 to 44 years – to align with the age-based mammography screening guidelines. The season in which the patient scheduled their appointment was categorized by winter (January to March), spring (April - June), summer (July to September), and fall (October to December) to examine a possible seasonal effect.31-32 The wave was categorized as a dichotomous variable (0/1) for wave 1 and 2 and the group was categorized as a three-category variable (group 1, 2, and 3) based on when the clinic began the PMP intervention. Each of the three mobile mammography providers were categorized as a dichotomous variable based on if the provider assisted with mammography screenings at the clinic in which the patient was scheduled (categorized as “1”) or not scheduled (categorized as “0”) for a mammography appointment. The provider with an existing reminder call and group education program for usual care was defined as the reference group. The clinic racial/ethnicity distribution (percentage) of the population served by each clinic from 2015 to 2016 was collected from the Health Resources and Services Administration (HRSA) Uniform Data System (UDS) for FQHCs and the Texas Association of Community Health Centers (TACHC) for charity care clinics. The clinics were categorized based on the racial/ethnicity group with the highest percentage in five mutually exclusive groups: non-Hispanic Black, non-Hispanic white, non-Hispanic other (another race other than Black or white), Hispanic, and multi-racial/ethnicity group (equal percentage of non-Hispanic Black, non-Hispanic other, and Hispanic women served). Each of the five racial/ethnicity groups were also categorized as a dichotomous variable indicating if the racial/ethnicity group was the highest reported for the clinic (categorized as “1”) or not the highest (categorized as “0”).
To assess fidelity of PMP intervention implementation, implementation variables examined in the analysis of the data for those in the intervention period, included the CHW who made the appointment reminder call, if the patient answered the reminder call, the number of reminder call attempts made by the CHW, and language in which the reminder call was received. The CHW who made the reminder call was a dichotomous variable based on if they were a clinic staff member (categorized as “0”) or a BHCTexas staff member (categorized as “1”). A dichotomous variable determined if the patient answered the reminder call (categorized as “1”) or not (categorized as “0”). The number of reminder call attempts received by patient in the intervention period was a dichotomous variable for one call (categorized as “0”) or multiple call attempts (two or three calls categorized as “1”). Language was categorized by English, Spanish, or Vietnamese.
A descriptive analysis was performed to examine differences in patient, intervention, clinic, and implementation variables across the baseline and intervention periods. To test for statistically significant differences in mammography appointment adherence across the baseline period, intervention period, and covariate variables we used chi-square tests. For the primary analysis, we used a multivariable generalized estimating equation (GEE) regression model to examine mammography appointment adherence in two analytical models. In the first model, we included all patients in the baseline and intervention period (intent to treat analysis). In the second model, we included only patients in the intervention period to examine those who did and did not complete the intervention (i.e., completed the reminder phone call). We modeled clustering across the 19 clinical sites using a logistic GEE regression (logit link with odds ratio) and an independent correlation structure. We analyzed age, season, wave, group, mobile mammography provider, the group variable and the five dichotomous variables for clinic racial/ethnic distribution, and for those in the intervention period, the CHW who made the appointment reminder call, if the patient answered the call, the number of reminder call attempts, and language independently in each of the models and added each additional variable as a covariate. The Quasi-Akaike information criterion (QIC) value was used to identity covariates to include in the final models. All analysis was performed using Stata 14.0 (College Station, TX) with α=0.05 as the limit for statistical significance.
To measure adoption and implementation factors associated with each clinic, a survey was conducted with clinic leadership and staff with any potential role in PMP prior to adoption of PMP and eight weeks into PMP implementation. A total of 75 survey statement items were used to assess twelve constructs across three CFIR domains using a survey adapted from the Cancer Prevention and Control Research Network for cancer control EBIs with FQHCs [see Additional file 2].33-35 A mean score for each clinic was created to measure level of agreement with each statement item (5 = completely agree to 1 = completely disagree). Twenty survey statements were recoded to align with level of agreement and scoring direction (E.g., Question in Additional file 2: It will be hard to train providers and staff to implement the PMP). One-sided t-tests were conducted to analyze mean score changes (mean difference < 0) between the clinic adoption and implementation survey responses.