Are breast cancer navigation programs cost-effective? Evidence from the Chicago Cancer Navigation Project.

Are breast cancer navigation programs cost-effective? Evidence from the Chicago Cancer Navigation Project

Are breast cancer navigation programs cost-effective? Evidence from the Chicago Cancer Navigation Project

Objectives One of the aims of the Chicago Cancer Navigation Project (CCNP) is to reduce the interval of time between abnormal breast cancer screening and definitive diagnosis in patients who are navigated as compared to usual care. In this article, we investigate the extent to which total costs of breast cancer navigation can be offset by survival benefits and savings in lifetime breast cancer-attributable costs.Methods Data sources for the cost-effectiveness analysis include data from published literature, secondary data from the NCI's Surveillance Epidemiology and End Results (SEER) program, and primary data from the CCNP.Results If women enrolled in CCNP receive breast cancer diagnosis earlier by 6 months as compared to usual care, then navigation is borderline cost-effective for $95,625 per life-year saved. Results from sensitivity analyses suggest that the cost-effectiveness of navigation is sensitive to: the interval of time between screening and diagnosis, percent increase in number of women who receive cancer diagnosis and treatment, women's age, and the positive predictive value of a mammogram.Conclusions In planning cost-effective navigation programs, special considerations should be made regarding the characteristics of the disease, program participants, and the initial screening test that determines program eligibility.Cost-effectiveness analysis Breast cancer Health care disparities Patient navigation

Online interest regarding violent attacks, gun control, and gun purchase: A causal analysis.

BackgroundIncreased interest about gun ownership and gun control are oftentimes driven by informational shocks in a common factor, namely violent attacks, and the perceived need for higher levels of safety. A causal depiction of the societal interest around violent attacks, gun control and gun purchase, both synchronous and over time, should be a stepping stone for designing future strategies regarding the safety concerns of the U.S. population.ObjectiveExamine the causal relationships between unexpected increases in population interest about violent attacks, gun control, and gun purchase.MethodsRelationships among online searches for information about violent attacks, gun control, and gun purchase occurring between 2004 and 2017 in the U.S. are explained through a novel structural vector autoregressive time series model to account for simultaneous causal relationships.ResultsMore than 20% of the stationary variability in each of gun control and gun purchase interest can be explained by the remaining factors. Gun control interest appears to be caused, in part, by violent attacks informational shocks, yet violent attacks, although impactful, have a lesser effect than gun control debate on long-term gun ownership interests.ConclusionsThe form in which gun control has been introduced in public debate may have further increased gun ownership interest. Reactive gun purchase interest may be an unintended side effect of gun control debate. U.S. policymakers may need to rethink current approaches to promotion of gun control, and whether societal policy debate without policy outcomes could be having unintended effects

Applying Customer Discovery Method to a Chronic Disease Self-Management Mobile App: Qualitative Study

BackgroundA significant health challenge is evident in the United States, with 6 in 10 adults having a chronic disease and 4 in 10 adults having 2 or more. Chronic disease self-management aims to prevent or delay disease progression and disability and reduce mortality risk. The evidence to support the use of information technology tools, including mobile apps, web-based portals, and web-based educational interventions, that support disease self-management and improve clinical outcomes is growing. Customer discovery and value proposition design methodology is a form of stakeholder engagement and is based on marketing and lean start-up business methods. As applied in health care, customer discovery and value proposition methodology can be used to understand the clinical problem and articulate the product’s hypothesized unique value proposition relative to alternative options that are available to end users. ObjectiveThis study aims to describe the experience and findings of academic researchers applying the customer discovery and value proposition methodology to identify stakeholders, needs, adaptability, and sustainability of a chronic disease self-management mobile app (CDapp). The motivation of the work is to make mobile health app interventions accessible and acceptable for all segments of patients’ chronic diseases. MethodsData were obtained through key informant interviews and analyzed using rapid qualitative analysis techniques. The value proposition framework was used to build the interview guide. The aim was to identify the needs, challenges (pains), and potential benefits (gains) of the CDapp for our stakeholders. ResultsOur results showed that the primary consumers (end users) of a CDapp were the patients. The app adopters (decision makers) can be medical center leaders including population health department managers or insurance providers, while the consumer adoption influencers (influencers or saboteurs) are clinicians and patient caregivers. We developed an ecosystem map to visualize the clinical practice workflow and how an app for chronic disease management might integrate within an academic health care center or system. A value proposition for the identified customer segments was generated. Each stakeholder segment was working within a different framework to improve patient self-management. Patients needed help to adhere to self-care activities and they needed tailored health education. Health care leaders aim to improve the quality of care while reducing costs and workload. Clinicians wanted to improve patient education and care while reducing the time burden. Our results also showed that within academic medical centers, there were variations regarding patients’ self-reported abilities to manage their diseases. ConclusionsCustomer discovery is a useful form of stakeholder engagement when designing studies that seek to implement, adapt, and sustain an intervention. The customer discovery and value proposition methodology can be used as an alternative or complementary approach to formative research to generate valuable information in a brief period

Prevalence and feasibility of assessing the frailty phenotype among hemodialysis patients in a dialysis unit

Background: Frailty increases risk of morbidity and mortality in hemodialysis patients. Frailty assessments could trigger risk reduction interventions if broadly adopted in clinical practice. We aimed to assess the clinical feasibility of frailty assessment among Veteran hemodialysis patients. Methods: Hemodialysis patients' ≥50 years were recruited from a single dialysis unit between 9/1/2021 and 3/31/2022.Patients who consented underwent a frailty phenotype assessment by clinical staff. Five criteria were assessed: unintentional weight loss, low grip strength, self-reported exhaustion, slow gait speed, and low physical activity. Participants were classified as frail (3-5 points), pre-frail (1-2 points) or non-frail (0 points). Feasibility was determined by the number of eligible participants completing the assessment. Results: Among 82 unique dialysis patients, 45 (52%) completed the assessment, 13 (16%) refused, 18 (23%) were not offered the assessment due to death, transfers, or switch to transplant or peritoneal dialysis, and 6 patients were excluded because they did not meet mobility criteria. Among assessed patients, 40(88%) patients were identified as pre-frail (46.6%) or frail (42.2%). Low grip strength was most common (90%). Those who refused were more likely to have peripheral vascular disease (p = 0.001), low albumin (p = 0.0187), low sodium (p = 0.0422), and ineligible for kidney transplant (p = 0.005). Conclusions: Just over half of eligible hemodialysis patients completed the frailty assessment suggesting difficulty with broad clinical adoption expectations. Among those assessed, frailty and pre-frailty prevalence was high. Given patients who were not tested were clinically high risk, our reported prevalence likely underestimates true frailty prevalence. Providing frailty reduction interventions to all hemodialysis patients could have high impact for this group.</p

The Evaluation of a Clinical Decision Support Tool Using Natural Language Processing to Screen Hospitalized Adults for Unhealthy Substance Use: Protocol for a Quasi-Experimental Design

BackgroundAutomated and data-driven methods for screening using natural language processing (NLP) and machine learning may replace resource-intensive manual approaches in the usual care of patients hospitalized with conditions related to unhealthy substance use. The rigorous evaluation of tools that use artificial intelligence (AI) is necessary to demonstrate effectiveness before system-wide implementation. An NLP tool to use routinely collected data in the electronic health record was previously validated for diagnostic accuracy in a retrospective study for screening unhealthy substance use. Our next step is a noninferiority design incorporated into a research protocol for clinical implementation with prospective evaluation of clinical effectiveness in a large health system. ObjectiveThis study aims to provide a study protocol to evaluate health outcomes and the costs and benefits of an AI-driven automated screener compared to manual human screening for unhealthy substance use. MethodsA pre-post design is proposed to evaluate 12 months of manual screening followed by 12 months of automated screening across surgical and medical wards at a single medical center. The preintervention period consists of usual care with manual screening by nurses and social workers and referrals to a multidisciplinary Substance Use Intervention Team (SUIT). Facilitated by a NLP pipeline in the postintervention period, clinical notes from the first 24 hours of hospitalization will be processed and scored by a machine learning model, and the SUIT will be similarly alerted to patients who flagged positive for substance misuse. Flowsheets within the electronic health record have been updated to capture rates of interventions for the primary outcome (brief intervention/motivational interviewing, medication-assisted treatment, naloxone dispensing, and referral to outpatient care). Effectiveness in terms of patient outcomes will be determined by noninferior rates of interventions (primary outcome), as well as rates of readmission within 6 months, average time to consult, and discharge rates against medical advice (secondary outcomes) in the postintervention period by a SUIT compared to the preintervention period. A separate analysis will be performed to assess the costs and benefits to the health system by using automated screening. Changes from the pre- to postintervention period will be assessed in covariate-adjusted generalized linear mixed-effects models. ResultsThe study will begin in September 2022. Monthly data monitoring and Data Safety Monitoring Board reporting are scheduled every 6 months throughout the study period. We anticipate reporting final results by June 2025. ConclusionsThe use of augmented intelligence for clinical decision support is growing with an increasing number of AI tools. We provide a research protocol for prospective evaluation of an automated NLP system for screening unhealthy substance use using a noninferiority design to demonstrate comprehensive screening that may be as effective as manual screening but less costly via automated solutions. Trial RegistrationClinicalTrials.gov NCT03833804; https://clinicaltrials.gov/ct2/show/NCT03833804 International Registered Report Identifier (IRRID)DERR1-10.2196/4297

Patient Barriers to Follow-Up Care for Breast and Cervical Cancer Abnormalities

BACKGROUND: Women with breast or cervical cancer abnormalities can experience barriers to timely follow-up care, resulting in delays in cancer diagnosis. Patient navigation programs that identify and remove barriers to ensure timely receipt of care are proliferating nationally. The study used a systematic framework to describe barriers, including differences between African American and Latina women; to determine recurrence of barriers; and to examine factors associated with barriers to follow-up care. METHODS: Data originated from 250 women in the intervention arm of the Chicago Patient Navigation Research Program (PNRP). The women had abnormal cancer screening findings and navigator encounters. Women were recruited from a community health center and a publicly owned medical center. After describing proportions of African American and Latina women experiencing particular barriers, logistic regression was used to explore associations between patient characteristics, such as race/ethnicity, and type of barriers. RESULTS: The most frequent barriers occurred at the intrapersonal level (e.g., insurance issues and fear), while institutional-level barriers such as system problems with scheduling care were the most commonly recurring over time (29%). The majority of barriers (58%) were reported in the first navigator encounter. Latinas (81%) reported barriers more often than African American women (19%). Differences in race/ethnicity and employment status were associated with types of barriers. Compared to African American women, Latinas were more likely to report an intrapersonal level barrier. Unemployed women were more likely to report an institutional level barrier. CONCLUSION: In a sample of highly vulnerable women, there is no single characteristic (e.g., uninsured) that predicts what kinds of barriers a woman is likely to have. Nevertheless, navigators appear able to easily resolve intrapersonal-level barriers, but ongoing navigation is needed to address system-level barriers. Patient navigation programs can adopt the PNRP barriers framework to assist their efforts in assuring timely follow-up care