Study Design and Participants
We conducted a retrospective observational study among KPSC members eligible for CRC screening. Eligible patients were > 49 years of age and < 75 years old, had no history of CRC, had not completed CRC screening using any modality within the past 12 months, and had not completed a colonoscopy within the past 10 years or sigmoidoscopy within the past 5 years. (Note that KPSC members are identified as eligible 2–3 months prior to their 50th birthday, hence the inclusion of > 49 years.) Patients on hospice or palliative care were excluded. All materials were available in English and Spanish.
Setting
KPSC provides comprehensive care to over 4.6 million members with a long-standing electronic health record (EHR). The EHR features an online patient portal (kp.org) which provides patient access to appointments, results, and information about past visits. The patient portal also features the Online Personal Action Plan (oPAP). The oPAP was designed to enhance patient engagement, potentially improving efficacy of outreach efforts for prevention and other health services. The oPAP synthesizes information from the EHR to provide tailored information about recommended services including cancer screenings, immunizations, heart health, and other preventive care services. It features interactive content with links to enable patient actions. The oPAP has been shown to be an effective tool for closing care gaps, such as overdue HbA1c testing for diabetes management and overdue screenings.22
Intervention
In 2016, the oPAP team developed the interactive order button interface for the portal. A CRC screening reminder with the embedded button allows patients due for a FIT kit to order the kit directly from the patient portal. Email reminders for CRC screening with the embedded FIT kit order button were sent to eligible KPSC members due for their annual CRC screening. Those who used the order button were promptly sent a FIT kit and removed from the regional FIT kit mailing list. Those who did not use the button were mailed kits as part of the standard CRC screening outreach strategy. We included any eligible member who used the button to order a FIT kit up to October 2, 2017, in the button-user group; non-users were the comparison group. The index date was either the date the reminder was sent out or the date the button was first clicked, whichever came first. Participants were followed over time from initial invitation to completion of the FIT kit, other colorectal screening, terminated membership, death, or until May 1, 2018. All study activities were approved by the KPSC Institutional Review Board (IRB #11624).
Variables
Our primary outcome was completion of the FIT kit. Secondary outcomes included number of days to complete the kit and completion of recommended follow-up for positive results. We identified completion of the FIT kit using current procedural terminology (CPT) codes from the EHR and results of the test were designated as either “positive” or “negative,” or were indeterminate. Time to completion was calculated using the result date. We also evaluated diagnosis of CRC during the study period. We identified newly diagnosed cancers using ICD-10 diagnosis codes (C18.0, C18.2–9, C19.X, C20.X) and confirmed with chart review. For those diagnosed with CRC during the study period, we extracted pathological cancer stage from pathology reports (American Joint Committee on Cancer 8th edition).
We identified covariates from the EHR including demographic information on age, gender, race/ethnicity, need for interpreter, and primary medical center. Preferred primary medical center was determined using utilization records within the prior year. Zip code was used to estimate preferred (closest) medical center for members with no healthcare utilization data. We also included a weighted Charlson Comorbidity Index (CCI) score.23 The CCI was calculated using utilization data from the EHR 1 year prior to the index date, and the weighted score was generated using age and diagnostic (ICD) data; scores were categorized as 0, 1, 2, 3, and ≥ 4.
Lacking a survey-based measure of patient engagement, we relied on proxy measures of engagement including number of patient portal logins in the past year, no-show outpatient appointments in the past year, and overall outpatient healthcare utilization in the past year. These variables were selected based on association with patient engagement demonstrated in the scientific literature, including the association of higher engagement and increased use of health services24,25,26 and use of patient portals.27,28,29
Statistical Analysis
Initial binary comparisons of demographic and engagement characteristics were calculated with chi-square tests. To evaluate potential differences in completion of FIT kits between those who used the order button and those who did not, we used propensity score methods to control for pretreatment imbalances commonly seen in observational studies.30,31 A logistic regression was run with the inverse probability of treatment weights to balance the study groups with respect to demographic and utilization characteristics.32 Odds ratios with 95% confidence intervals were computed to compare the odds of completing a FIT kit among those who used the button compared to eligible members who had active logins on the patient portal but did not use the button. Additionally, to evaluate the potential effect of engagement, we compared the odds of completing a FIT kit among those who logged in to the patient portal but did not use the button to those who had zero logins during the study period. Missing values were included in an “unknown” category, ensuring that propensity score weighting could be conducted on all observations. Propensity scores were computed using the R package Toolkit for Weighting and Analysis of Nonequivalent Groups (TWANG), using age, gender, race and ethnicity, need for a language interpreter, preferred medical center, number of patient portal logins in the past year, no-show outpatient appointments in the past year, overall outpatient healthcare utilization in the past year, and the CCI. The average treatment effect (ATE) was estimated using KS Max as a stopping method.
To determine if the button led to patients completing CRC screening who had not been up-to-date on screening in the past, we compared the number of those in the button group who completed the FIT kit within the prior year to those in the button group who completed a FIT kit after the button became available using McNemar’s test. Analyses were conducted in SAS, version 9.4, and R, version 3.2.2.