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We assessed whether proactive care management for artificial intelligence (AI)-identified at-risk patients reduced preventable emergency department (ED) visits and hospital admissions (HAs). Stepped-wedge cluster randomized design. Adults receiving primary care at 48 UCLA Health clinics and determined to be at risk based on a homegrown AI model were included. We employed a stepped-wedge cluster randomized design, assigning groups of clinics (pods) to 1 of 4 single-cohort waves during which the proactive care intervention was implemented. The primary end points were potentially preventable HAs and ED visits; secondary end points were all HAs and ED visits. Within each wave, we used an interrupted time series and segmented regression analysis to compare utilization trends. In the pooled analysis of high-risk and highest-risk patients (n = 3007), potentially preventable HAs showed a statistically significant level drop (-27% [95% CI, -44% to -6%]), without any corresponding change in trends. Potentially preventable ED visits did not show a substantial level drop in response to the intervention, although a nonsignificant differential change in trend was observed, with visit rates decelerating 7% faster in the intervention cohorts (95% CI, -13% to 0%). Nonsignificant drops were observed for all HAs (-19% [95% CI, -35% to 1%]; P = .06) and ED visits (-15% [95% CI, -28% to 1%]; P = .06). A care management intervention targeting AI-identified at-risk patients was followed by a onetime, significant, sizable reduction in preventable HA rates. Further exploration is needed to assess the potential of integrating AI and care management in preventing acute hospital encounters.

Population health interventions to increase colorectal cancer (CRC) screening rates often exclude individuals with a family history of CRC, and interventions to increase screening in this high-risk group are rare. We aimed to determine the screening rate and barriers and facilitators to screening in this population to inform interventions to increase screening participation. We performed a retrospective chart review and cross-sectional survey of patients excluded from mailed fecal immunochemical test (FIT) outreach because of a family history of CRC in a large health system. We used χ 2 , Fisher exact, and Student t tests to compare demographic and clinical characteristics of patients overdue and not overdue for screening. We then administered a survey (mailed and telephone) to overdue patients to assess barriers and facilitators to screening. There were 296 patients excluded from mailed FIT outreach, and 233 patients had a confirmed family history of CRC. Screening participation was low (21.9%), and there were no significant demographic or clinical differences between those overdue and not overdue for screening. There were 79 survey participants. Major patient-reported barriers to screening colonoscopy were patient forgetfulness (35.9%), fear of pain during colonoscopy (17.7%), and hesitancy about bowel preparation (29.4%). To facilitate screening colonoscopy, patients recommended reminders (56.3%), education about familial risk (50%), and colonoscopy education (35.9%). Patients with a family history of CRC who are excluded from mailed FIT outreach have low screening rates and report multiple mutable barriers to screening. They warrant targeted efforts to increase screening participation.

INTRODUCTION:Patients with abnormal fecal immunochemical test (FIT) results require diagnostic colonoscopy to reduce mortality from colorectal cancer (CRC). Barriers to follow-up are multifactorial and include patient-, provider-, and system-level factors. Patient navigators (PN) can be effective in improving follow-up by helping patients overcome these barriers. We aimed to assess the impact of PN on clinical care processes required for colonoscopy completion after positive FIT in a large, academic health care system.METHODS:We included all UCLA Health outpatients with an abnormal FIT result between 12/1/2016 and 12/01/2018 without documentation of a colonoscopy. Two PN underwent training with a gastroenterologist and quality officer. For all FIT positive patients, PN 1) conducted a chart review to confirm lack of colonoscopy completion, 2) contacted the primary care provider when there was an inappropriate reason for lack of colonoscopy, and 3) called patients to review FIT results, encourage follow-up, address barriers, and schedule a colonoscopy. Intervention endpoints were 1) colonoscopy completion, 2) patient refusal, 3) provider felt colonoscopy inappropriate, and 4) patient left the health system. We determined the proportion of patients that reached each endpoint at 4 months and reasons providers reported that colonoscopy was not indicated after positive FIT.RESULTS:Our cohort included 131 subjects. Mean age was 62.8 (±7.3), 50.3% were female, and 49.6% were White. In all, 87 (66.4%) reached an intervention endpoint at 4 months (Figure 1). Twenty-seven (31.0%) received diagnostic follow-up: 12 (44.5%) had colonoscopy, 3 (11.1%) had CT colonography, 1 (3.7%) had sigmoidoscopy, and 11 (40.7%) reported colonoscopies outside the health system. Primary care providers that were contacted by the PN often did not feel colonoscopy was indicated (25, 19.1%), and many (10, 40.0%) cited recent colonoscopy (Table 1). There were 19 (21.8%) patients that refused follow-up colonoscopy.CONCLUSION:PN was effective in increasing diagnostic follow-up after positive FIT and revealed persistent challenges to appropriate resolution of positive FIT. Future efforts will improve provider education about appropriate use of FIT and evaluate if PN can improve timely diagnostic follow-up when tracking positive FIT patients prospectively.

INTRODUCTION:Population health interventions to increase colorectal cancer (CRC) screening rates often exclude individuals with a family history of CRC, and interventions to increase screening in this high-risk group are rare. We aimed to determine the screening rate and barriers and facilitators to screening in this population to inform interventions to increase screening participation.METHODS:We performed a retrospective chart review and cross-sectional survey of patients excluded from mailed fecal immunochemical test (FIT) outreach because of a family history of CRC in a large health system. We used χ2, Fisher exact, and Student t tests to compare demographic and clinical characteristics of patients overdue and not overdue for screening. We then administered a survey (mailed and telephone) to overdue patients to assess barriers and facilitators to screening.RESULTS:There were 296 patients excluded from mailed FIT outreach, and 233 patients had a confirmed family history of CRC. Screening participation was low (21.9%), and there were no significant demographic or clinical differences between those overdue and not overdue for screening. There were 79 survey participants. Major patient-reported barriers to screening colonoscopy were patient forgetfulness (35.9%), fear of pain during colonoscopy (17.7%), and hesitancy about bowel preparation (29.4%). To facilitate screening colonoscopy, patients recommended reminders (56.3%), education about familial risk (50%), and colonoscopy education (35.9%).DISCUSSION:Patients with a family history of CRC who are excluded from mailed FIT outreach have low screening rates and report multiple mutable barriers to screening. They warrant targeted efforts to increase screening participation.

Colorectal cancer (CRC) screening reduces CRC mortality; however, screening rates remain well below the national benchmark of 80%. To determine whether an electronic primer message delivered through the patient portal increases the completion rate of CRC screening in a mailed fecal immunochemical test (FIT) outreach program. In this randomized clinical quality improvement trial at the University of California, Los Angeles Health of 2339 patients enrolled in a FIT mailing program from August 28, 2019, to September 20, 2020, patients were randomly assigned to either the control or intervention group, and the screening completion rate was measured at 6 months. Participants were average-risk managed care patients aged 50 to 75 years, with a valid mailing address, no mailed CRC outreach in the previous 6 months, and an active electronic health record (EHR) patient portal who were due for CRC screening. Data were analyzed on an intention-to-treat basis. Eligible patients were randomly assigned to receive either (1) the standard FIT mailed outreach (control group) or (2) the standard FIT mailed outreach plus an automated primer to notify patients of the upcoming mailed FIT sent through the electronic patient portal (intervention group). The primary outcome was the screening completion rate (ie, returning the FIT). Secondary outcomes were (1) were the time to CRC screening from the FIT mailing date, (2) screening modality completed, and (3) the effect of opening the electronic primer on screening completion rate. The study included 2339 patients (1346 women [57.5%]; mean [SD] age, 58.9 [7.5] years). The screening completion rate was higher in the intervention group than in the control group (37.6% [445 of 1182] vs 32.1% [371 of 1157]; P = .005). The time to screening was shorter in the intervention group than in the control group (adjusted hazard ratio, 1.24; 95% CI, 1.08-1.42; P = .003). The proportion of each screening test modality completed was similar in both groups. In a subanalysis of the 900 of 1182 patients (76.1%) in the intervention group who opened the patient portal primer message, there was a 7.3-percentage point (95% CI, 2.3-12.4 percentage points) increase in CRC screening (local mean treatment effect; P = .004). Implementation of an electronic patient portal primer message in a mailed FIT outreach program led to a significant increase in CRC screening and improvement in the time to screening completion. The findings provide an evidence base for additional refinements to mailed FIT outreach quality improvement programs in large health systems. ClinicalTrials.gov Identifier: NCT05115916.

Background Globally, emergency departments (EDs) are overcrowded and unable to meet an ever-increasing demand for care. The aim of this study is to comprehensively review and synthesise literature on potential solutions and challenges throughout the entire health system, focusing on ED patient flow. Methods An umbrella review was conducted to comprehensively summarise and synthesise the available evidence from multiple research syntheses. A comprehensive search strategy was employed in four databases alongside government or organisational websites in March 2023. Gray literature and reports were also searched. Quality was assessed using the JBI critical appraisal checklist for systematic reviews and research syntheses. We summarised and classified findings using qualitative synthesis, the Population-Capacity-Process (PCP) model, and the input/throughput/output (I/T/O) model of ED patient flow and synthesised intervention outcomes based on the Quadruple Aim framework. Results The search strategy yielded 1263 articles, of which 39 were included in the umbrella review. Patient flow interventions were categorised into human factors, management-organisation interventions, and infrastructure and mapped to the relevant component of the patient journey from pre-ED to post-ED interventions. Most interventions had mixed or quadruple nonsignificant outcomes. The majority of interventions for enhancing ED patient flow were primarily related to the 'within-ED' phase of the patient journey. Fewer interventions were identified for the 'post-ED' phase (acute inpatient transfer, subacute inpatient transfer, hospital at home, discharge home, or residential care) and the 'pre-ED' phase. The intervention outcomes were aligned with the aim (QAIM), which aims to improve patient care experience, enhance population health, optimise efficiency, and enhance staff satisfaction. Conclusions This study found that there was a wide range of interventions used to address patient flow, but the effectiveness of these interventions varied, and most interventions were focused on the ED. Interventions for the remainder of the patient journey were largely neglected. The metrics reported were mainly focused on efficiency measures rather than addressing all quadrants of the quadruple aim. Further research is needed to investigate and enhance the effectiveness of interventions outside the ED in improving ED patient flow. It is essential to develop interventions that relate to all three phases of patient flow: pre-ED, within-ED, and post-ED.

Despite the frequent co-occurrence of depression and diabetes, gender differences in their relationship remain unclear. This exploratory study examined if gender modifies the association between depressive symptoms, prediabetes and diabetes with cognitive-affective and somatic depressive symptom clusters. Cross-sectional analyses were conducted on 29 619 participants from the 2007-2018 National Health and Nutrition Examination Survey. Depressive symptoms were measured by the nine-item Patient Health Questionnaire. Multiple logistic regression was used to analyse the relationship between depressive symptoms and diabetes. Multiple linear regression was used to analyse the relationship between depressive symptom clusters and diabetes. The odds of having depressive symptoms were greater in those with diabetes compared to those without. Similarly, total symptom cluster scores were higher in participants with diabetes. Statistically significant diabetes-gender interactions were found in the cognitive-affective symptom cluster model. Mean cognitive-affective symptom scores were higher for females with diabetes (coefficient = 0.23, CI: 0.10, 0.36, = 0.001) than males with diabetes (coefficient = -0.05, CI: -0.16, 0.07, = 0.434) when compared to the non-diabetic groups. Diabetes was associated with higher cognitive-affective symptom scores in females than in males. Future studies should examine gender differences in causal pathways and how diabetic states interact with gender and influence symptom profiles.