Citations

ABSTRACT Purpose This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

Background: The integration of artificial intelligence (AI) in dental and maxillofacial radiology is revolutionizing diagnostic accuracy and clinical decision-making. This bibliometric analysis investigates the research landscape, emerging trends, and scholarly impact of AI applications in this specialized field. Methods: A comprehensive search was conducted on 25 December 2024 using the Web of Science Core Collection database. Data analysis tools, including VOSviewer, CiteSpace, and Biblioshiny, were employed to examine publication trends, global contributions, collaborative networks, and keyword dynamics. Results: The analysis revealed a marked increase in AI-related publications in dental and maxillofacial radiology, particularly from 2016 onward. The number of studies rose steadily, reaching 218 publications in 2024. The United States led in research output, followed closely by China and South Korea, with KU Leuven emerging as the top-contributing institution. Reinhilde Jacobs was identified as the most prolific author, while Medical Physics was the most cited journal. Co-citation analysis highlighted influential works by authors such as J.H. Lee and F. Schwendicke . Keywords including “artificial intelligence,” “deep learning,” “CBCT,” and “classification” dominated research discussions, reflecting the field’s evolving focus. Recent research trends emphasize advanced applications in segmentation, accuracy enhancement, and predictive modeling. Conclusion: AI has become integral to the advancement of dental and maxillofacial radiology, offering significant improvements in diagnostic precision and treatment planning. This study underscores the importance of staying abreast of AI innovations to enhance patient care and foster future research opportunities. Researchers and clinicians are encouraged to adopt AI-driven approaches to maximize clinical efficiency and outcomes.

ABSTRACT Importance Rural-urban disparities in chronic disease prevalence are well established; however, the extent to which individual-level socioeconomic status (SES) contributes to these disparities remains unclear. Objective To examine the associations of rurality and SES with the prevalence of five most burdensome chronic diseases among adults. Design We conducted a retrospective cross-sectional study of adults across 27 Upper Midwest counties using the Expanded Rochester Epidemiology Project (E-REP) medical record data linkage system to evaluate associations between rurality, SES and chronic disease prevalence. Prevalence of clinically diagnosed asthma, diabetes, hypertension, coronary heart disease, and mood disorders was identified from International Classification of Diseases ICD9/10 codes over a five-year period (2014-2019). Setting Population based Participants Adults over 18 years residing in the 27 E-REP counties, excluding those missing rural-urban residence status. Exposure HOUSES index, an individual-level measure of SES, served as the primary measure, while rurality based on Rural Urban Commuting Area (RUCA) codes 4-10 was the secondary measure. Main Outcome Prevalence of the five clinically diagnosed chronic diseases was identified using ICD9/10 codes from 2014–2019. Mixed effect logistic regression models were used and adjusted for demographics and general medical examination receipt, to assess rural-urban and SES differences for prevalence of each chronic disease. Results Among 455,802 adults with available HOUSES index, 42.8% lived in rural areas, 53.8% were female and 87.4% were non-Hispanic White. In the unadjusted analysis, rural and urban populations showed comparable asthma and CHD prevalence, while mood disorders, hypertension, and diabetes were more common in urban areas. After adjusting for demographic factors and healthcare utilization, rural-urban differences were no longer statistically significant, whereas SES remained strongly associated with all diseases in a dose response manner (e.g., adjusted Odds Ratio for hypertension (ref: HOUSES index Q4): 1.14, 1.27, and 1.42 for HOUSES index Q3, Q2, and Q1, respectively). Conclusions and Relevance Individual-level SES measured by the HOUSES index, was more strongly associated with chronic disease prevalence than rurality, supporting its integration into population health assessment and risk stratification.

Healthcare organisations face mounting challenges to maintain financial sustainability given increasing expenses, decreasing reimbursements and changing patient needs. Because of the increasing costs of operating a healthcare institution, it is no longer viable to pursue achieving financial sustainability just by adding more clinical visits and capacity, increasing hospital admission and throughput, performing more surgeries or simply working harder. To address these challenges, healthcare leaders should adopt a culture of continuous process improvement that engages and empowers clinical and operational teams to identify and eliminate waste, optimise revenue and enhance quality and safety. This paper presents a case study of Project ROSE (Revenue Optimization and Supply Enhancement), a project initiated by a community-based integrated health system in the upper Midwest. The goal was to achieve substantial financial savings within one year through revenue optimisation, supply chain improvements and service and maintenance contract enhancements. We describe the vision, goals, methods, results and lessons learned. We also discuss the implications and recommendations for other healthcare institutions that seek to implement similar initiatives that may reduce the burden on their clinical teams and allow them to work smarter, not harder. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/ business/.

Background After an increase of central line–associated bloodstream infections (CLABSIs) at our community hospital in 2021, a case-control study suggested that patients with CLABSIs were 3.0 times more likely to have missed daily chlorhexidine gluconate (CHG) bathing than patients without CLABSIs. Objective To increase the rate of daily CHG bathing in hospitalized patients with central lines and subsequently reduce the number of CLABSIs. Methods Our pre-post intervention was launched on September 2022 and consisted of enhancements to the electronic health record (EHR) to simplify the identification of overdue CHG bathing instances to increase compliance, and therefore decrease the CLABSI rate at our hospital. A workflow was implemented Monday–Friday utilizing these EHR enhancements for active surveillance to engage frontline nursing staff and address gaps in care in real time. Results After the initiative was implemented, adherence to daily CHG bathing increased from 94.9% to 95.3%, with a considerable disparity between weekdays (97.6%) and weekends (89.3%). After weekend data were excluded, the post-intervention increase in the adherence rate was statistically significant ( p = .003). Discussion This initiative underscored the importance of involving health care informatics partners and showed how technology can bridge gaps in health care quality. Outreach and reminders effectively improved CHG bathing adherence by emphasizing the importance of consistent communication and follow-up.

Mayo Clinic Health System — Southwest Minnesota Region, one of four practice regions in the Midwest, provides primary and speciality care in ambulatory, procedural and hospital settings. Clinic appointment fill rates, no-show rates and late cancellation rates are closely monitored operational metrics, but at the time this study began, less was known about the refill rates of late appointment cancellations. This metric is of importance because these unfilled appointment times contribute to increased expenses for healthcare organisations, unnecessary delays in care and decreases in revenue. The main objectives of this study were to understand the current state and potential opportunities for refilling late cancellations. Qualitative and quantitative methods were used, including variance analysis, the Tukey post hoc test, Pareto analysis, the completion of interviews with important stakeholders and data extraction from the institution’s electronic health record. Findings showed that late cancellation rates remained steady in 2021 and that late cancellations were not being refilled consistently across departments and regions. Appointment refill rates were higher in departments with few or no requirements for preparatory evaluation, whereas in specialties that did require preparatory evaluations, refill rates were lower across the four regions of the Mayo Clinic Health System. Even in departments with high demand, the refill rates were lower, resulting in missed opportunities for patient visits. Mapping the workflow for late cancellations indicated inconsistent methods for refilling late cancellation openings and the lack of a defined process for refilling them that was understood by the entire care team. The logistics of optimising refill rates for late cancellations were affected by provider preference, selfscheduling functionality and appointment requirements. This study identified opportunities for optimising workflows to use the waiting list proactively to refill late cancellations.

As modern medicine offers novel surgical therapies for conditions simple and complex, the proper resource allocation of operating rooms, surgical staff and supporting services is becoming increasingly important for healthcare organisations. Surgical services are one of the most essential parts of any healthcare system, substantially influencing patient choice of healthcare services. These services are typically the centre for revenue but also impart considerable costs. Given the complexity of surgical schedule planning, expectations of high reliability and demand on resources, many healthcare organisations have resorted to using a static block schedule based on historic utilisation patterns. This is based on the dogma that surgical schedules are not predictable, surgical blocks are stable, and surgical yield has no direct correlation with outpatient schedules. Here we share our two-year experience with a Surgical Predictor Tool using our surgical practice management principles and the cost-effective use of these means to meet the needs of patients and our surgical staff in an integrated community health system.

The COVID-19 pandemic caused a transformation in healthcare delivery at a pace never before experienced, including by the child psychiatry practice at Mayo Clinic Health System in Mankato, Minnesota. The aim of this study was to describe the outcomes of that practice’s transition from in-person to virtual care. This retrospective study comprised two groups of patients who received care in the child psychiatry practice at our institution: before COVID-19, 1 March 2019 to 28 February 2020; and after COVID-19, 1 March 2020 to 28 February 2021. We extracted data related to patient visits from the electronic health record and satisfaction data from a Medical Practice Survey given to patients after visits. Virtual visits increased by 306 per cent within a month of transitioning to virtual care and remain the main visit type for established patients. Findings from patient surveys showed substantial overall improvements in patient experiences with virtual visits, and no-show appointments decreased substantially (from up to 23 per cent to 1 per cent). This study provided data for an overview of how the COVID-19 pandemic affected a child psychiatry practice and of the positive outcomes of transitioning from 100 per cent in-person visits before the pandemic to more than 80 per cent virtual visits. The quick transition to virtual care delivery in the child psychiatry practice was a positive change for patients, families and the care team. We believe that other healthcare systems can learn from our experience.

Background Communication gaps, whether incomplete or fragmented communication, have been the cause of many disasters in human civilisation. Coordination of healthcare is directly related to proper communication and handoffs among multidisciplinary teams throughout multiple shifts during a patient’s hospitalisation. Local problem Patient surveys and direct patient feedback at Mayo Clinic Health System in Mankato, Minnesota, indicated that patient communication with physicians and nurses had declined in 2017 and 2018. Viewing this as an opportunity for improvement, our leadership initiated several changes to increase physician and nurse communication with patients, which resulted in no notable improvements. Methods A systematic quality improvement approach was implemented by using Six Sigma methodology. Stakeholders from multidisciplinary teams were assembled as the project team. The five steps of Six Sigma methodology (Define, Measure, Analyse, Improve and Control) were followed to create a quality improvement intervention. Intervention We developed a standardised and easy-to-use bedside team rounding tool to improve patient communication with physicians and nurses. Results Postintervention patient satisfaction top-box scores exceeded target improvements for both physician (from 78.5% to 82.0%, p<0.01) and nurse (from 80.5% to 83.1%, p=0.04) communication domains. Physicians had a 33-point increase in percentile rank (from 41st to 74th percentile rank), and nurses had a 25-point increase in percentile rank (from 59th to 84th percentile rank). This increase in communication ranked our institution at the top of national benchmark organisations. Conclusions Overwhelmingly positive patient feedback was achieved, and postintervention employee satisfaction was primarily positive when compared with preintervention satisfaction.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has impacted health care organizations throughout the world. The Southwest Minnesota Region of Mayo Clinic Health System, a community-based health care system, was not immune, and in March 2020, our outpatient services were deferred and decreased by 90%. Method: This article is a review of the approach we used to safely reactivate outpatient care, the tools that we developed, and the outcomes of these reactivation efforts. A novel Outpatient Practice Reactivation Framework was established and used that included Outpatient Clinic Appointment Dashboard, Decision Matrix, Access Management, Virtual Care, and Patient Safety. This framework was guided by patient demand for care and by safety principles, as recommended by state and federal agencies and our internal infectious disease department guidelines. Results and Conclusions: Over the course of 9 weeks, ambulatory visit volumes and clinic utilization rates returned to pre-COVID levels (Pre-COVID fill rate range: 87% to 94%, post-COVID fill rate range: 86% to 89%) exceeding target fill rate of 80%, as a result of establishing the initiative as a shared priority, committing to a robust schedule and decisive actions, creating and maintaining a well-defined structure, taking an inclusive approach, overcommunicating and providing sufficient data for transparency, developing guiding principles, and training and educating staff.