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BACKGROUND: This report details the cost effectiveness of a non-nurse patient navigation (PN) program that was implemented at the University of Chicago Medical Center to increase colonoscopy-based colorectal cancer (CRC) screening. METHODS: The authors investigated the impact of the PN intervention by collecting process measures. Individuals who received navigation were compared with a historic cohort of non-navigated patients. In addition, a previously validated data-collection instrument was tailored and used to collect all costs related to developing, implementing, and administering the program; and the incremental cost per patient successfully navigated (the cost of the intervention divided by the change in the number who complete screening) was calculated. RESULTS: The screening colonoscopy completion rate was 85.1% among those who were selected to receive PN compared with 74.3% when no navigation was implemented. With navigation, the proportion of no-shows was 8.2% compared with 15.4% of a historic cohort of non-navigated patients. Because the perceived risk of noncompletion was greater among those who received PN (previous no-show or cancellation, poor bowel preparation) than that in the historic cohort, a scenario analysis was performed. Assuming no-show rates between 0% and 50% and using a navigated rate of 85%, the total incremental program cost per patient successfully navigated ranged from $148 to $359, whereas the incremental intervention-only implementation cost ranged from $88 to $215. CONCLUSIONS: The current findings indicate that non-nurse PN can increase colonoscopy completion, and this can be achieved at a minimal incremental cost for an insured population at an urban academic medical center.

Introduction We examine symptom variability in men and women with urological chronic pelvic pain syndrome (UCPPS). We describe symptom fluctuations as related to early symptom regression and its effect on estimated one-year symptom change. We then describe a method to quantify patient-specific symptom variability. Methods Symptoms were assessed biweekly in 424 UCPPS subjects over one year. Subjects were classified as ‘improved’, ‘no change’, or ‘worse’ according to their rate of change using 1) all data, 2) excluding week 0, and 3) excluding weeks 0 and 2 to evaluate the impact of early symptom regression. Patient-specific time-varying variability was calculated at each interval using a sliding window approach. Patients were classified as high, medium, or low variability at each time and ultimately as high or low variability overall based on their variability for the majority of contacts. Results Prior to excluding early weeks to adjust for early symptom regression 25–38% and 5–6% of patients were classified as improved and worse, respectively; after adjustment the percentage of patients improved or worse ranged from 15–25% and 6–9%. ‘High and ‘low’ variability phenotypes were each identified in 25–30% of participants. Conclusions Patients with UCPPS exhibit symptom variability. At enrollment, patients had, on average, worse symptoms, resulting in a regression effect that influenced the estimated proportion of improved or worse subjects. Prospective studies should include a run-in to account for regression to the mean and other causes of early symptom regression. Further, symptom variability may be quantified and used to characterize longitudinal UCPPS symptom profiles.

Asian Americans have experienced compounding stressors during the pandemic as a result of racial discrimination. We aim of to investigate the prevalence of depression symptoms among Asian Americans before and during the COVID-19 pandemic and examine differences based on socio-demographic factors. Data are from a cross-sectional study (N = 636) among Chinese and South Asian adults in Chicago collected between February and May 2020. One cohort of participants were surveyed from each ethnic group before the pandemic and a second cohort of participants were surveyed during the pandemic. Depression symptoms increased more than two-fold, from 9% pre-pandemic to 21% during the COVID-19 pandemic. We found an increase in depression symptoms during the pandemic for South Asians, men and adults older than 30 years. These findings call for public health education that effectively addresses anti-Asian harassment and violence and ensure that culturally competent mental health services are provided to Asian Americans from diverse ethnic backgrounds.

Background Many evidence-based interventions (EBIs) found to be effective in research studies often fail to translate into meaningful patient outcomes in practice. The purpose of this study was to identify facilitators and barriers that affect the implementation of three EBIs to improve colorectal cancer (CRC) screening in an urban federally qualified health center (FQHC) and offer actionable recommendations to improve future implementation efforts. Methods We conducted 16 semi-structured interviews guided by the Consolidation Framework for Implementation Research (CFIR) to describe diverse stakeholders’ implementation experience. The interviews were conducted in the participant’s clinic, audio-taped, and professionally transcribed for analysis. Results We used the five CFIR domains and 39 constructs and subconstructs as a coding template to conduct a template analysis. Based on experiences with the implementation of three EBIs, stakeholders described barriers and facilitators related to the intervention characteristics, outer setting, and inner setting. Implementation barriers included (1) perceived burden and provider fatigue with EHR (Electronic Health Record) provider reminders, (2) unreliable and ineffectual EHR provider reminders, (3) challenges to providing health care services to diverse patient populations, (4) lack of awareness about CRC screening among patients, (5) absence of CRC screening goals, (6) poor communication on goals and performance, and (7) absence of printed materials for frontline implementers to educate patients. Implementation facilitators included (1) quarterly provider assessment and feedback reports provided real-time data to motivate change, (2) integration with workflow processes, (3) pressure from funding requirement to report quality measures, (4) peer pressure to achieve high performance, and (5) a culture of teamwork and patient-centered mentality. Conclusions The CFIR can be used to conduct a post-implementation formative evaluation to identify barriers and facilitators that influenced the implementation. Furthermore, the CFIR can provide a template to organize research data and synthesize findings. With its clear terminology and meta-theoretical framework, the CFIR has the potential to promote knowledge-building for implementation. By identifying the contextual determinants, we can then determine implementation strategies to facilitate adoption and move EBIs to daily practice.