Data-driven analyses to quantify information seeking behaviour for women with uterine fibroids.

Uterine fibroids (UF) are noncancerous growths of the uterus and impact the livelihood of over 26 million women in the United States. Although UF may not have accompanying symptoms, for some women their presence leads to surgical treatment, which can be a difficult decision-making process. Web-scraping of online media is used to identify information-seeking behavior of women searching for UF treatment options. We synthesize the data to describe trends in UF treatment, including the identification of gaps between the information individuals are seeking (demand) and information that is publicly available as a resource (supply), which contributes to this study's creation of the term "information desert." We perform statistical analysis to understand information-seeking behavior, determine the gap between information supply and information demand, and determine the correlation between a doctor's treatment recommendation and a patient's treatment decision as a function of age, symptoms, and knowledge obtained about specific types of treatment.

Engaging stakeholders in the use of an interactive simulation tool to support decision-making about the implementation of colorectal cancer screening interventions.

PURPOSE: We aimed to understand how an interactive, web-based simulation tool can be optimized to support decision-making about the implementation of evidence-based interventions (EBIs) for improving colorectal cancer (CRC) screening. METHODS: Interviews were conducted with decision-makers, including health administrators, advocates, and researchers, with a strong foundation in CRC prevention. Following a demonstration of the microsimulation modeling tool, participants reflected on the tool's potential impact for informing the selection and implementation of strategies for improving CRC screening and outcomes. The interviews assessed participants' preferences regarding the tool's design and content, comprehension of the model results, and recommendations for improving the tool. RESULTS: Seventeen decision-makers completed interviews. Themes regarding the tool's utility included building a case for EBI implementation, selecting EBIs to adopt, setting implementation goals, and understanding the evidence base. Reported barriers to guiding EBI implementation included the tool being too research-focused, contextual differences between the simulated and local contexts, and lack of specificity regarding the design of simulated EBIs. Recommendations to address these challenges included making the data more actionable, allowing users to enter their own model inputs, and providing a how-to guide for implementing the simulated EBIs. CONCLUSION: Diverse decision-makers found the simulation tool to be most useful for supporting early implementation phases, especially deciding which EBI(s) to implement. To increase the tool's utility, providing detailed guidance on how to implement the selected EBIs, and the extent to which users can expect similar CRC screening gains in their contexts, should be prioritized.

Assessing the impact of multicomponent interventions on colorectal cancer screening through simulation: What would it take to reach national screening targets in North Carolina?

Healthy People 2020 and the National Colorectal Cancer Roundtable established colorectal cancer (CRC) screening targets of 70.5% and 80%, respectively. While evidence-based interventions (EBIs) have increased CRC screening, the ability to achieve these targets at the population level remains uncertain. We simulated the impact of multicomponent interventions in North Carolina over 5 years to assess the potential for meeting national screening targets. Each intervention scenario is described as a core EBI with additional components indicated by the "+" symbol: patient navigation for screening colonoscopy (PN-for-Col+), mailed fecal immunochemical testing (MailedFIT+), MailedFIT+ targeted to Medicaid enrollees (MailedFIT + forMd), and provider assessment and feedback (PAF+). Each intervention was simulated with and without Medicaid expansion and at different levels of exposure (i.e., reach) for targeted populations. Outcomes included the percent up-to-date overall and by sociodemographic subgroups and number of CRC cases and deaths averted. Each multicomponent intervention was associated with increased CRC screening and averted both CRC cases and deaths; three had the potential to reach screening targets. PN-for-Col + achieved the 70.5% target with 97% reach after 1 year, and the 80% target with 78% reach after 5 years. MailedFIT+ achieved the 70.5% target with 74% reach after 1 year and 5 years. In the Medicaid population, assuming Medicaid expansion, MailedFIT + forMd reached the 70.5% target after 5 years with 97% reach. This study clarifies the potential for states to reach national CRC screening targets using multicomponent EBIs, but decision-makers also should consider tradeoffs in cost, reach, and ability to reduce disparities when selecting interventions.

Testing and extending strategies for identifying genetic disease-related encounters in pediatric patients.

PURPOSE: To better understand health care utilization and develop decision support tools, methods for identifying patients with suspected genetic diseases (GDs) are needed. Previous studies had identified inpatient-relevant International Classification of Diseases (ICD) codes that were possibly, probably, or definitely indicative of GDs. We assessed whether these codes identified GD-related inpatient, outpatient, and emergency department encounters among pediatric patients with suspected GDs from a previous study (the North Carolina Clinical Genomic Evaluation by Next-Generation Exome Sequencing [NCGENES] study). METHODS: Using the electronic medical records of 140 pediatric patients from the NCGENES study, we characterized the presence of ICD codes representing possible, probable, or definite GD-related diagnoses across encounter types. In addition, we examined codes from encounters for which initially no GD-related codes had been found and determined whether these codes were indicative of a GD. RESULTS: Among NCGENES patients with visits between 2014 and 2017, 92% of inpatient, 75% of emergency department, and 63% of outpatient encounters included ≥1 GD-related code. Encounters with highly specific (ie, definite) GD codes had fewer low-specificity GD codes than encounters with only low-specificity GD codes. We identified an additional 32 ICD-9 and 56 ICD-10 codes possibly indicative of a GD. CONCLUSION: Code-based strategies can be refined to assess health care utilization among pediatric patients and may contribute to a systematic approach to identify patients with suspected GDs.

A systematic review of the methodological quality of economic evaluations in genetic screening and testing for monogenic disorders.

PURPOSE: Understanding the value of genetic screening and testing for monogenic disorders requires high-quality, methodologically robust economic evaluations. This systematic review sought to assess the methodological quality among such studies and examined opportunities for improvement. METHODS: We searched PubMed, Cochrane, Embase, and Web of Science for economic evaluations of genetic screening/testing (2013-2019). Methodological rigor and adherence to best practices were systematically assessed using the British Medical Journal checklist. RESULTS: Across the 47 identified studies, there were substantial variations in modeling approaches, reporting detail, and sophistication. Models ranged from simple decision trees to individual-level microsimulations that compared between 2 and >20 alternative interventions. Many studies failed to report sufficient detail to enable replication or did not justify modeling assumptions, especially for costing methods and utility values. Meta-analyses, systematic reviews, or calibration were rarely used to derive parameter estimates. Nearly all studies conducted some sensitivity analysis, and more sophisticated studies implemented probabilistic sensitivity/uncertainty analysis, threshold analysis, and value of information analysis. CONCLUSION: We describe a heterogeneous body of work and present recommendations and exemplar studies across the methodological domains of (1) perspective, scope, and parameter selection; (2) use of uncertainty/sensitivity analyses; and (3) reporting transparency for improvement in the economic evaluation of genetic screening/testing.

Estimating the impact of insurance expansion on colorectal cancer and related costs in North Carolina: A population-level simulation analysis.

Although screening is effective in reducing incidence, mortality, and costs of treating colorectal cancer (CRC), it remains underutilized, in part due to limited insurance access. We used microsimulation to estimate the health and financial effects of insurance expansion and reduction scenarios in North Carolina (NC). We simulated the full lifetime of a simulated population of 3,298,265 residents age-eligible for CRC screening (ages 50-75) during a 5-year period starting January 1, 2018, including polyp incidence and progression and CRC screening, diagnosis, treatment, and mortality. Insurance scenarios included: status quo, which in NC includes access to the Health Insurance Exchange (HIE) under the Affordable Care Act (ACA); no ACA; NC Medicaid expansion, and Medicare-for-all. The insurance expansion scenarios would increase percent up-to-date with screening by 0.3 and 7.1 percentage points for Medicaid expansion and Medicare-for-all, respectively, while insurance reduction would reduce percent up-to-date by 1.1 percentage points, compared to the status quo (51.7% up-to-date), at the end of the 5-year period. Throughout these individuals' lifetimes, this change in CRC screening/testing results in an estimated 498 CRC cases averted with Medicaid expansion and 6031 averted with Medicare-for-all, and an additional 1782 cases if health insurance gains associated with ACA are lost. Estimated cost savings - balancing increased CRC screening/testing costs against decreased cancer treatment costs - are approximately $30 M and $970 M for Medicaid expansion and Medicare-for-all scenarios, respectively, compared to status quo. Insurance expansion is likely to improve CRC screening both overall and in underserved populations while saving money, with the largest savings realized by Medicare.

Mailed FIT (fecal immunochemical test), navigation or patient reminders? Using microsimulation to inform selection of interventions to increase colorectal cancer screening in Medicaid enrollees.

Colorectal cancer (CRC) can be effectively prevented or detected with guideline concordant screening, yet Medicaid enrollees experience disparities. We used microsimulation to project CRC screening patterns, CRC cases averted, and life-years gained in the population of 68,077 Oregon Medicaid enrollees 50-64 over a five year period starting in January 2019. The simulation estimated the cost-effectiveness of five intervention scenarios - academic detailing plus provider audit and feedback (Detailing+), patient reminders (Reminders), mailing a Fecal Immunochemical Test (FIT) directly to the patient's home (Mailed FIT), patient navigation (Navigation), and mailed FIT with Navigation (Mailed FIT + Navigation) - compared to usual care. Each intervention scenario raised CRC screening rates compared to usual care, with improvements as high as 11.6 percentage points (Mailed FIT + Navigation) and as low as 2.5 percentage points (Reminders) after one year. Compared to usual care, Mailed FIT + Navigation would raise CRC screening rates 20.2 percentage points after five years - averting nearly 77 cancer cases (a reduction of 113 per 100,000) and exceeding national screening targets. Over a five year period, Reminders, Mailed FIT and Mailed FIT + Navigation were expected to be cost effective if stakeholders were willing to pay $230 or less per additional year up-to-date (at a cost of $22, $59, and $227 respectively), whereas Detailing+ and Navigation were more costly for the same benefits. To approach national CRC screening targets, health system stakeholders are encouraged to implement Mailed FIT with or without Navigation and Reminders.

Simulation model of the relationship between cesarean section rates and labor duration.

Cesarean delivery is the most common major abdominal surgery in many parts of the world, and it accounts for nearly one-third of births in the United States. For a patient who requires a C-section, allowing prolonged labor is not recommended because of the increased risk of infection. However, for a patient who is capable of a successful vaginal delivery, performing an unnecessary C-section can have a substantial adverse impact on the patient's future health. We develop two stochastic simulation models of the delivery process for women in labor; and our objectives are (i) to represent the natural progression of labor and thereby gain insights concerning the duration of labor as it depends on the dilation state for induced, augmented, and spontaneous labors; and (ii) to evaluate the Friedman curve and other labor-progression rules, including their impact on the C-section rate and on the rates of maternal and fetal complications. To use a shifted lognormal distribution for modeling the duration of labor in each dilation state and for each type of labor, we formulate a percentile-matching procedure that requires three estimated quantiles of each distribution as reported in the literature. Based on results generated by both simulation models, we concluded that for singleton births by nulliparous women with no prior complications, labor duration longer than two hours (i.e., the time limit for labor arrest based on the Friedman curve) should be allowed in each dilation state; furthermore, the allowed labor duration should be a function of dilation state.