Citations

Whether centralised or decentralised, healthcare access models provide varying degrees of benefit to customers and to the organisations they serve. Mayo Clinic Health System in Southwest Minnesota, United States, is a community-based practice of 23 clinics and 6 hospitals that has undergone an evolution of its access model. In 2010, a centralised access model was adopted, including the physical location of schedulers, which was expected to offer greater efficiency, flexibility and staff savings. However, in 2016, the region noted concerning trends of low patient and provider satisfaction with scheduling, decreasing patient access and less-than-optimal patient throughput, all subsequently contributing to declining financial performance. Early concerning trends led to further investigation of practice areas and geographical sites that had notable appointment capacity yet low patient access and throughput. Provider productivity rates, calendar management and patient access varied substantially. Performance in scheduling operations was below par because of limited connection with the practice. The combination of practice variation and a centralised access model was causing an increase in scheduling errors, consistent rework/rescheduling, less-than-optimal patient access, low provider calendar fill rates and high levels of dissatisfaction for patients and providers. Our group was tasked with analysing the problems and developing a new scheduling model. This paper describes the resulting model: a hybrid of centralised and decentralised models, which promised the benefits of both and involved transformation in clinical practice operations and access management. Standardisation for provider scheduling and template management was enhanced. Pods of scheduling personnel were embedded in practice areas. The proximity of the pods to physician, nursing and other clinical staff allowed for increased collaboration and communication. The hybrid model improved access metrics for average speed to answer, abandoned call rates, patient access and throughput, financial performance, and patient and provider satisfaction.

The novel severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19), has presented healthcare delivery challenges the world has never encountered before. Healthcare and its practitioners, while finding themselves in difficult situations, must still care for patients with emergent needs and ensure the safety and well-being of all patients and staff. At Mayo Clinic, effective navigation of the dynamic and complex situation created by COVID-19 required unique multidisciplinary collaborations to design and implement solutions quickly. Frontline care providers and staff of ancillary services and other critical healthcare functions partnered with the Department of Management Engineering and Consulting (ME&C) team to organise and re-engineer operations to iteratively adapt to the dynamic ‘new normal’. Health systems engineers (HSEs) and project managers (PMs) accelerated the implementation of innovative interventions by leveraging advanced engineering and consulting frameworks, models and methods. Utilising a patient and staff-centric systems approach to align electronic systems, operational processes, staffing resources and organisational infrastructure has been invaluable for speed and effectiveness. Harnessing the promise of digital technology and advanced analytics was imperative and set the stage for a broader set of possibilities to transform healthcare. These possibilities include scaling of consumerfocused virtual services in multiple and unfamiliar settings, new assets that could be reused for future emergencies, accelerating the implementation of time-sensitive solutions, applied analytics and modelling to predict clinical, financial and community impacts and reimaging the healthcare supply chain. As more has been learned about the trajectory and management of COVID-19, the need to rapidly evolve and pivot interventions for short-, medium-, and long-term applications continues. This article addresses the unique contributions of ME&C during the COVID-19 crisis and the results-oriented collaborations with staff in critical business functions. We believe that the experiences, outcomes and lessons learned through this journey are broadly transferable to other healthcare and nonhealthcare organisations.

The COVID-19 pandemic disrupted the workforce, resulting in a shift to a largely remote working population. As a result of this shift, Employee Occupational Health Services (EOHS) was required to develop a solution to evaluate new employees and provide occupational medical clearance without the physical presence of the candidate. An online candidate portal was created where individuals could complete evaluation paperwork and screenings asynchronously. The evaluation forms and screenings were then reviewed by occupational health nursing staff, and testing was conducted in the candidate’s home location. The virtual evaluation solution expedited the assessment process, added convenience for candidates and reduced the amount of time needed from EOHS staff. It is imperative that EOHS departments adjust to the changing workforce by offering virtual evaluation solutions that provide candidates with a seamless and efficient solution to complete required paperwork, testing and immunisations.

OBJECTIVE To compare postprandial glucose excursions following a bolus with inhaled technosphere insulin (TI) or subcutaneous rapid-acting analog (RAA) insulin. RESEARCH DESIGN AND METHODS A meal challenge was completed by 122 adults with type 1 diabetes who were using multiple daily injections (MDI), a nonautomated pump, or automated insulin delivery (AID) and who were randomized to bolus with their usual RAA insulin (n = 61) or TI (n = 61). RESULTS The primary outcome, the treatment group difference in area under the curve for glucose >180 mg/dL over 2 h, was less with TI versus RAA (adjusted difference −12 mg/dL, 95% CI −22 to −2, P = 0.02). With TI, the glucose excursion was smaller (P = 0.01), peak glucose lower (P = 0.01), and time to peak glucose shorter (P = 0.006). Blood glucose <70 mg/dL occurred in one participant in each group. CONCLUSIONS Postmeal glucose excursion was smaller with TI than with RAA insulin in a cohort that included both AID and MDI users.

Regulatory bodies in the United States have implemented quality metrics aimed at improving outcomes for patients with severe sepsis and septic shock. The current study was a quality improvement (QI) project in a community-based academic center aimed at improving adherence to sepsis quality metrics, time to antibiotic administration, and patient outcomes. Electronic health record systems were utilized to capture sepsis-related data. Regular audits and feedback sessions were conducted to identify areas for improvement, with a focus on the timely administration of antibiotics. Interventions included improving access to antibiotics, transitioning from intravenous piggyback to intravenous push formulations, and providing continuous staff education and training. This multidisciplinary QI initiative led to significant improvements in the mortality index, length of stay index, and direct cost index for patients with sepsis. Targeted multidisciplinary QI interventions resulted in improved quality metrics and patient outcomes.

BACKGROUND: Transcatheter mitral valve-in-valve replacement offers a less-invasive alternative for high-risk patients with bioprosthetic valve failure. Limited experience exists in intermediate-risk patients. We aim to evaluate 1-year outcomes of the PARTNER 3 mitral valve-in-valve study. METHODS: This prospective, single-arm, multicenter study enrolled symptomatic patients with a failing mitral bioprosthesis demonstrating greater than or equal to moderate stenosis and regurgitation and Society of Thoracic Surgeons score ≥3% and <8%. A balloon-expandable transcatheter heart valve (SAPIEN 3, Edwards Lifesciences) was used via a transeptal approach. The primary end point was the composite of all-cause mortality and stroke at 1 year. RESULTS: A total of 50 patients from 12 sites underwent mitral valve-in-valve from 2018 to 2021. The mean age was 70.1±9.7 years, mean Society of Thoracic Surgeons score was 4.1%±1.6%, and 54% were female. There were no primary end point events (mortality or stroke) through 1 year, and no left-ventricular outflow tract obstruction, endocarditis, or mitral valve reintervention was reported. Six patients (12%) required rehospitalization, including heart failure (n=2), minor procedural side effects (n=2), and valve thrombosis (n=2; both resolved with anticoagulation). An additional valve thrombosis was associated with no significant clinical sequelae. From baseline to 1 year, all subjects with available data had none/trace or mild (grade 1+) mitral regurgitation and the New York Heart Association class improved in 87.2% (41/47) of patients. CONCLUSIONS: Mitral valve-in-valve with a balloon-expandable valve via transseptal approach in intermediate-risk patients was associated with improved symptoms and quality of life, adequate transcatheter valve performance, and no mortality or stroke at 1-year follow-up. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03193801.

AbstractBackgroundIn carbon ion radiation therapy (CIRT) the predominant method of irradiation is raster scanning, called dose driven continuous scanning (DDCS) by Hitachi, allowing for continuous synchrotron extraction. The reduction in irradiation time is highly beneficial in minimizing the impact of patient and target movement on dose distribution. The RF knock out (RFKO) slow‐extraction method is commonly used for beam on/off control. When the Hitachi synchrotron receives a beam off signal the control system stops the RFKO and after some delay time (t‐delay) during which the beam intensity declines, a high‐speed steering magnet (HSST) is used to sweep the remaining beam from isocenter to a beam dump for safety reasons. Mayo Clinic Florida (MCF) will use a very short delay of the HSST operation from the RFKO beam OFF signal to minimize the delay time and delayed dose. MCF clinical beam intensity, a tenfold increase over HIMAK, is still less than 100 mMU/ms (approximately 4.9 × 109 pps for 430 MeV/u).PurposeThe rapid beam off control (RBOC) proposed for MCF is associated with the occurrence of flap dose (FD), which refers to the asymmetric shoulder of the spot dose profile formed from the beam bent by HSST deviating from its planned spot position on the isocenter plane. In this study, we quantitatively assessed FD, proposed a treatment planning system (TPS) implementation using a flap spot (FS) and evaluated its impact on dose distribution.MethodThe experiments were conducted at the Osaka Heavy Ion Therapy Center (HIMAK) varying the t‐delay from 0.01 to 1 ms in a research environment to simulate the MCF RBOC. We studied the dependence of FD position on beam transport and its dependence on energy and beam intensity. FD was generated by delivering 10000 continuous spots on the central axis that are occasionally triggered by an external 10 Hz gate signal. Measurements were conducted using an oscilloscope, and the nozzle's spot position monitor (SPM) and dose monitor (DM).ResultAll spot profile data were corrected for the gain of the SPM's beam intensity dependence. FD was determined by fitting the (SPM) Profile data to a double Gaussian. The position of the FS was found to be transport path dependent, with FS occurring on the opposite sides of the scanning x‐direction for vertical and horizontal ports, respectively, as predicted by transport calculations. It was observed that the FD increases with beam intensity and did not exhibit a significant dependence on energy. The effect of FD on treatment planning is shown to have no significant dose impact on the organs at risk (OARs) near the target for clinical beam intensities and a modest increase for very high intensities.ConclusionUsing HIMAK in research mode the implications are that the FD has no clinical impact on the clinical CIRT beam intensities for MCF and maybe planned for higher intensities by incorporating FS into the TPS to predict the modest increased dose to OARs. A method for commissioning and quality assurance of FD has been proposed.

The analytical microdosimetric function (AMF) implemented in the Monte Carlo code PHITS is a unique tool that bridges the gap between macro- and microscopic scales of radiation interactions, enabling accurate microdosimetric calculations over macroscopic bodies. The original AMF was published in 2006, based on the results of track structure calculations. Recently, a newer version of the AMF was proposed, incorporating an improved description of the energy loss at the microscopic scale. This study compares the older and the newer AMFs in computing microdosimetric probability distributions, mean values, and the relative biological effectiveness (RBE). To this end, 16000 microdosimetric lineal energy probability density distributions were simulated with PHITS for ions from 1H to 238U over a broad energy range (1–1000 MeV/n). The newer AMF was found to offer superior performance, particularly for very heavy ions, producing results that align more closely with published in vitro clonogenic survival experiments. These findings suggest that the updated AMF provides a more reliable tool for microdosimetric calculations and RBE modeling, essential for ion radiation therapy and space radiation protection.

AbstractBackgroundIntensity Modulated Proton Therapy (IMPT) is a sophisticated radiation treatment allowing for precise dose distributions. However, conventional spot selection strategies in IMPT face challenges, particularly with minimum monitor unit (MU) constraints, affecting planning quality and efficiency.PurposeThis study introduces an innovative Two‐Stage Mixed Integer Linear Programming (MILP) method to optimize spot intensity in IMPT with Lower Bound (LB) constraints. This method seeks to improve treatment planning efficiency and precision, overcoming limitations of existing strategies.MethodsOur approach evaluates prevalent IMPT spot selection strategies, identifying their limitations, especially concerning MU constraints. We integrated LB constraints into a MILP framework, using a novel three‐phase strategy for spot pool selection, to enhance performance over traditional heuristic methods and L1 + L∞ strategies. The method's efficacy was tested in eight study cases, using Dose‐Volume Histograms (DVHs), spot selection efficiency, and computation time analysis for benchmarking against established methods.ResultsThe proposed method showed superior performance in DVH quality, adhering to LB constraints while maintaining high‐quality treatment plans. It outperformed existing techniques in spot selection, reducing unnecessary spots and balancing precision with efficiency. Cases studies confirmed the method's effectiveness in producing clinically feasible plans with enhanced dose distributions and reduced hotspots, especially in cases with elevated LB constraints.ConclusionsOur Two‐Stage MILP strategy signifies a significant advancement in IMPT treatment planning. By incorporating LB constraints directly into the optimization process, it achieves superior plan quality and deliverability compared to current methods. This approach is particularly advantageous in clinical settings requiring minimum spot number and high MU LB constraints, offering the potential for improved patient outcomes through more precise and efficient radiation therapy plans.