A survey of health care models that encompass multiple departments

In this survey we review quantitative health care models to illustrate the extent to which they encompass multiple hospital departments. The paper provides general overviews of the relationships that exists between major hospital departments and describes how these relationships are accounted for by researchers. We find the atomistic view of hospitals often taken by researchers is partially due to the ambiguity of patient care trajectories. To this end clinical pathways literature is reviewed to illustrate its potential for clarifying patient flows and for providing a holistic hospital perspective

Scott & White Healthcare: Opening Up and Embracing Change to Improve Performance

Offers a case study of a multispeciality system with the attributes of an ideal healthcare delivery system as defined by the Fund. Describes a culture of continuous improvement, collaboration and peer accountability, and a comprehensive approach to care

Organizing Multidisciplinary Care for Children with Neuromuscular Diseases

The Academic Medical Center (AMC) in Amsterdam, The Netherlands, recently opened the `Children's Muscle Center Amsterdam' (CMCA). The CMCA diagnoses and treats children with neuromuscular diseases. These patients require care from a variety of clinicians. Through the establishment of the CMCA, children and their parents will generally visit the hospital only once a year, while previously they visited on average six times a year. This is a major improvement, because the hospital visits are both physically and psychologically demanding for the patients. This article describes how quantitative modelling supports the design and operations of the CMCA. First, an integer linear program is presented that selects which patients to invite for a treatment day and schedules the required combination of consultations, examinations and treatments on one day. Second, the integer linear program is used as input to a simulation to study to estimate the capacity of the CMCA, expressed in the distribution of the number patients that can be seen on one diagnosis day. Finally, a queueing model is formulated to predict the access time distributions based upon the simulation outcomes under various demand scenarios

Simulation and Modeling for Improving Access to Care for Underserved Populations

Indiana University-Purdue University Indianapolis (IUPUI)This research, through partnership with seven Community Health Centers (CHCs) in Indiana, constructed effective outpatient appointment scheduling systems by determining care needs of CHC patients, designing an infrastructure for meaningful use of patient health records and clinic operational data, and developing prediction and simulation models for improving access to care for underserved populations. The aims of this study are 1) redesigning appointment scheduling templates based on patient characteristics, diagnoses, and clinic capacities in underserved populations; 2) utilizing predictive modeling to improve understanding the complexity of appointment adherence in underserved populations; and 3) developing simulation models with complex data to guide operational decision-making in community health centers. This research addresses its aims by applying a multi-method approach from different disciplines, such as statistics, industrial engineering, computer science, health informatics, and social sciences. First, a novel method was developed to use Electronic Health Record (EHR) data for better understanding appointment needs of the target populations based on their characteristics and reasons for seeking health, which helped simplify, improve, and redesign current appointment type and duration models. Second, comprehensive and informative predictive models were developed to better understand appointment non-adherence in community health centers. Logistic Regression, Naïve Bayes Classifier, and Artificial Neural Network found factors contributing to patient no-show. Predictors of appointment non-adherence might be used by outpatient clinics to design interventions reducing overall clinic no-show rates. Third, a simulation model was developed to assess and simulate scheduling systems in CHCs, and necessary steps to extract information for simulation modeling of scheduling systems in CHCs are described. Agent-Based Models were built in AnyLogic to test different scenarios of scheduling methods, and to identify how these scenarios could impact clinic access performance. This research potentially improves well-being of and care quality and timeliness for uninsured, underinsured, and underserved patients, and it helps clinics predict appointment no-shows and ensures scheduling systems are capable of properly meeting the populations’ care needs.2021-12-2

Managerial Intervention Strategies to Reduce Patient No-Show Rates

High patient no-show rates increase health care costs, decrease healthcare access, and reduce the clinical efficiency and productivity of health care facilities. The purpose of this exploratory qualitative single case study was to explore and analyze the managerial intervention strategies healthcare administrators use to reduce patient no-show rates. The targeted research population was active American College of Healthcare Executives (ACHE), Hawaii-Pacific Chapter healthcare administrative members with operational and supervisory experience addressing administrative patient no-show interventions. The conceptual framework was the theory of planned behavior. Semistructured interviews were conducted with 4 healthcare administrators, and appointment cancellation policy documents were reviewed. Interpretations of the data were subjected to member checking to ensure the trustworthiness of the findings. Based on the methodological triangulation of the data collected, 5 common themes emerged after the data analysis: reform appointment cancellation policies, use text message appointment reminders, improve patient accessibility, fill patient no-show slots immediately, and create organizational and administrative efficiencies. Sharing the findings of this study may help healthcare administrators to improve patient health care accessibility, organizational performance and the social well-being of their communities

Optimising hospital designs and processes to improve efficiency and enhance the user experience

The health sector is facing increasing pressure to provide effective, efficient, and affordable care to the population it serves. The National Health Service (NHS) of the United Kingdom (UK) has regularly faced scrutiny with NHS England being issued a number of challenges in recent years to improve operational efficiency, reduce wasted space, and cut expenditure. The most recent challenge issued to NHS England has seen a requirement to save £5bn per annum by 2020, while reducing wasted space from 4.4% to 2.5% across the NHS estate. Similarly, satisfaction in the health service is also under scrutiny as staff retention and patient experiences are used in determining the performance of facilities. [Continues.

Head and neck radiotherapy amid the COVID‑19 pandemic: practice recommendations of the Italian Association of Radiotherapy and Clinical Oncology (AIRO)

Abstract Management of patients with head and neck cancers (HNCs) is challenging for the Radiation Oncologist, especially in the COVID-19 era. The Italian Society of Radiotherapy and Clinical Oncology (AIRO) identified the need of practice recommendations on logistic issues, treatment delivery and healthcare personnel’s protection in a time of limited resources. A panel of 15 national experts on HNCs completed a modified Delphi process. A five-point Likert scale was used; the chosen cut-offs for strong agreement and agreement were 75% and 66%, respectively. Items were organized into two sections: (1) general recommendations (10 items) and (2) special recommendations (45 items), detailing a set of procedures to be applied to all specific phases of the Radiation Oncology workflow. The distribution of facilities across the country was as follows: 47% Northern, 33% Central and 20% Southern regions. There was agreement or strong agreement across the majority (93%) of proposed items including treatment strategies, use of personal protection devices, set-up modifications and follow-up re-scheduling. Guaranteeing treatment delivery for HNC patients is well-recognized in Radiation Oncology. Our recommendations provide a flexible tool for management both in the pandemic and post-pandemic phase of the COVID-19 outbreak

Usability analysis of contending electronic health record systems

In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.Peer reviewe