Health Systems最新文献

Increasing efficiency and reducing risk in radiotherapy cancer treatment is of high importance. User assistance systems within a digitally connected radiotherapy environment can support all involved professionals to perform their individual tasks faster and better. This paper presents a qualitative analysis of radiotherapy workflows and a corresponding process modelling in order to identify hypothetical user assistance systems for specific process activities. In addition, the results of an empirical study on the identified systems are presented together with derived requirements and design principles for these systems. A structured online survey with 50 medical physicists in Germany has been conducted. Among others the acceptance, the increase of perceived efficiency and the risk reduction while using the assistance systems are analysed and discussed. The results support the creation of value adding user assistance systems for radiotherapy that improve efficiency, reduce treatment risks and reach high user acceptance levels.

In hospitals, scheduled operations can often be cancelled in large numbers due to the unavailability of beds for post-operation recovery. Operating theatre scheduling is known to be an $NP$ -hard optimisation problem. Previous studies have shown that the correct scheduling of surgical procedures can have a positive impact on the availability of beds in hospital wards, thereby allowing a reduction in number of elective operation cancellations. This study proposes an exact technique based on the partitioned graph colouring problem for constructing optimal master surgery schedules, with the goal of minimising the number of cancellations. The resultant schedules are then simulated in order to measure how well they cope with the stochastic nature of patient arrivals. Our results show that the utilisation of post-operative beds can be increased, whilst the number of cancellations can be decreased, which may ultimately lead to greater patient throughput and reduced waiting times. A scenario-based model has also been employed to integrate the stochastic-nature associated with the bed requirements into the optimisation process. The results indicate that the proposed model can lead to more robust solutions.

A primary goal of emergency services is to minimise the response times to emergencies whilst managing operational costs. This paper is motivated by real data from the Welsh Ambulance Service which in recent years has been criticised for not meeting its eight-minute response target. In this study, four forecasting approaches (ARIMA, Holt Winters, Multiple Regression and Singular Spectrum Analysis (SSA)) are considered to investigate whether they can provide more accurate predictions to the call volume demand (total and by category) than the current approach on a selection of planning horizons (weekly, monthly and 3-monthly). Each method is applied to a training and test set and root mean square error (RMSE) and mean absolute percentage error (MAPE) error statistics are determined. Results showed that ARIMA is the best forecasting method for weekly and monthly prediction of demand and the long-term demand is best predicted using the SSA method.

Patients diagnosed with rheumatoid arthritis require lifelong monitoring by a rheumatologist. Initiation of the disease-modifying anti-rheumatic drug therapy within twelve weeks of the onset of symptoms is crucial to prevent joint damage and functional disability. We examine the impact of the engagement of alternate care providers (ACP) in alleviating delay due to limited rheumatologist capacity. Using queueing theory and discrete-event simulation, we model rheumatologist-only and rheumatologist-with-ACP system configurations as closed, multi-class queueing networks with class switching.Using summary data from an actual rheumatology clinic for illustration, we analyze various parameter conditions to aid clinic managers and policymakers in decisions concerning capacity allocations and feasible patient panel size that impact timeliness of care and resource utilization.Results not only confirm that a substantial increase in RA patient panel size with an ACP involved in the care of follow-up patients but also demonstrates the boundaries for feasible panel sizes and workload allocation.

During intra-hospital transfers, multiple clinicians perform coordinated tasks that leave patients vulnerable to undesirable outcomes. Communication has been established as a challenge to care transitions, but less is known about the organisational complexities within which transfers take place. We performed a qualitative assessment that included various professions to capture a multi-faceted understanding of intra-hospital transfers. Ethnographic observations and semi-structured interviews were conducted with clinicians and staff from the Medical Intensive Care Unit, Emergency Department, and general medicine units at a large, urban, academic, tertiary medical centre. Results highlight the organisational factors that stakeholders view as important for successful transfers: the development, dissemination, and application of protocols; robustness of technology; degree of teamwork; hospital capacity; and the ways in which competing hospital priorities are managed. These factors broaden our understanding of the organisational context of intra-hospital transfers and informed the development of a practical guide that can be used prior to embarking on quality improvement efforts around transitions of care.

Health systems are critical to the realisation of Universal Health Coverage. There has been insufficient attention to the evaluation of priority setting for health system strengthening within low income countries, including evaluation of the local capacity to implement priorities. This study evaluated the extent to which health system strengthening was prioritized in Uganda. The Kapiriri & Martin framework was used to evaluate health system priority setting from 2005-2015. A document analysis was triangulated with interview data (n = 67) from global, national and subnational stakeholders and analysed using content analysis. Health system strengthening was perceived to be circumvented by a lack of resources as well as influential actors with disease focused, rather than system-oriented, interests. There were defined processes with explicit criteria for identifying priorities and evidence was highly valued. But sub-optimal transparency and weak accountability often compromised the integrity of priority setting and contributed to stalling progress on health system strengthening and achieving health system outcomes. The strengths in the current planning processes should be harnessed. In addition, a systematic approach to priority setting, potentially through the establishment of an independent body, and stronger oversight mechanisms, would strengthen health system planning in this setting.

On 11 March 2020, the World Health Organisation (WHO) declared COVID-19 a pandemic. Early epidemiological estimates show that COVID-19 is highly transmissible, infecting populations across the globe in a short amount of time. WHO has recommended widespread clinical testing in order to contain COVID-19. However, mass testing in emergency department (ED) settings may result in crowded EDs and increase transmission risk for healthcare staff and other ED patients. Drive-through COVID-19 testing sites are an effective solution to quickly collect samples from suspected cases with minimal risk to healthcare personnel and other patients. Nevertheless, there are many logistical and operational challenges, such as shortages of testing kits, limited numbers of healthcare staff and long delays for collecting samples. Solving these problems requires an understanding of disease dynamics and epidemiology, as well as the logistics of mass distribution. In this position paper, we provide a conceptual framework for addressing these challenges, as well as some insights from prior literature and experience on developing decision support tools for public health departments.

Large-scale immunisation programmes against seasonal influenza are characterised by logistical challenges related to the need for vaccinating large cohorts of people in a short amount of time. Careful operational planning of resources is essential for a successful implementation of such programmes. We focused on the process of child vaccination in schools and analysed the staffing and workflow aspects of a school-aged children vaccination programme in England. Our objectives were to document vaccination processes and analyse times and costs associated with different models deployed across England. We collected data through direct non-participatory observations. Statistical data analysis enabled us to identify potential factors influencing vaccine delivery time and informed the development of a tool to simulate vaccination sessions. Using this tool, we carried out scenario analyses and explored trade-offs between session times and costs in different settings. Our work ultimately supported the local implementation of school-based vaccination.

This paper presents a framework for understanding and improving the process of simulation model building involving a group of domain experts, classifying the different roles the model may play at various stages of its development. The framework consists of four different "object roles", defined along two dimensions: a functional dimension (boundary object vs. representational object) and a knowledge dimension (epistemic object vs. technical object). A model can take different roles during the development process, e.g. for facilitating communication, for gaining insight into the real-world system, or for experimentation and policy evaluation. The use of the framework is illustrated by two case studies in healthcare. Its relevance and applicability are examined through a survey on model use. The survey was conducted among a group of modelling consultants with experience of using both discrete-event simulation and system dynamics within the NHS, and indicated the potential usefulness of the framework.