Health Systems最新文献

Structured data formats are gaining momentum in electronic health records and can be leveraged for decision support and research. Nevertheless, such structured data formats have not been explored for clinical coding, which is an essential process requiring significant manual workload in health organisations. This article explores the extent to which fully structured clinical data can support assignment of clinical codes to inpatient episodes, through a methodology that tackles high dimensionality issues, addresses the multi-label nature of coding and optimises model parameters. The methodology encompasses transformation of raw data to define a feature set, build a data matrix representation, and testing combinations of feature selection methods with machine learning models to predict code assignment. The methodology was tested with a real hospital dataset and showed varying predictive power across codes, while demonstrating the potential of leveraging structuring data to reduce workload and increase efficiency in clinical coding.

Over the last decade, chemotherapy treatments have dramatically shifted to outpatient services such that nearly 90% of all infusions are now administered outpatient. This shift has challenged oncology clinics to make chemotherapy treatment as widely available as possible while attempting to treat all patients within a fixed period of time. Historical data from a Veterans Affairs chemotherapy clinic in the United States and staff input informed a discrete event simulation model of the clinic. The case study examines the impact of altering the current schedule, where all patients arrive at 8:00 AM, to a schedule that assigns patients to two or three different appointment times based on the expected length of their chemotherapy infusion. The results identify multiple scheduling policies that could be easily implemented with the best solutions reducing both average patient waiting time and average nurse overtime requirements.

Users with cognitive impairments use an assistive technology email system, CogLink, for socialisation and help in their activities of daily living. As users interact with the AT email client, the logged stream of events is monitored and analysed to aid decision-making. When caregivers receive monitor notifications, they know that the user has had a significant change in her emailing behaviour. Consequently, caregivers select adaptations to the email client that can challenge the user to gain still more emailing skills. The monitor in this emailing system analyzes user data to recognise when significant changes in user behaviour warrants caregiver attention. Moreover, the monitor can distinguish newly learned skills from new, but transient behaviours. This article summarises the CogLink assistive technology monitoring techniques, introduces the learning likelihood algorithm, which distinguishes transient from learned behaviour, and provides lessons learnt from a decade of monitoring CogLink users.

In this paper, we address the problem of finding an assignment of n surgeries to be performed in one of m parallel identical operating rooms (ORs), given each surgery has a stochastic duration with a known mean and standard deviation. The objective is to minimise the maximum of the c^th percentile of makespan of any OR. We formulate this problem as a nonlinear integer program, and small-sized instances are solved using the GAMS BONMIN solver. We develop a greedy heuristic and a genetic algorithm procedure for solving large-sized instances. Using real data from a major U.S. teaching hospital and benchmarking datasets from the literature, we report on the performance of the heuristics as compared to the GAMS BONMIN solver.

Despite being the principal measure of elective performance in Great Britain's National Health Service, there is little on-the-ground awareness of the dynamics at play behind the referral-to-treatment (RTT) standard. Through a simple worked analogy, it is shown how this performance measure - calculated as the proportion of unresolved RTT pathways within 18 weeks from referral - is dependent on the interplay between elective demand and capacity. Bringing in activity (cost) and waiting list size, the presented theory unifies the five key components of the pathway dynamics for the first time within the published literature. A computer simulation model based on these principles is thereafter constructed as part of a more quantitative analysis using publicly available national data for 2017-2018. In this, referral rates and capacity are varied in line with a range of "what if" scenarios known to be of interest to service planners, with the effect on performance and cost objectively assessed.

This special themed international issue explores the multiple facets of health informatics, healthcare quality and safety, and healthcare simulation from different parts of the world. The papers in this issue fall into two broad themes. The first theme uses the intersection to address better management of care including physical design layout. The second theme examines innovative uses of the triad to prevent critical and non-critical safety events. The collection of papers culminates with a position paper reporting on the interdependence that is emerging as an important triad for research and practice within medical education, system development and testing, and teamwork and communication and concludes with reducing imprecision and factual errors in handoffs. Findings from the special collection of papers can inform managers and leaders on advancing operations in healthcare settings.

The areas of health informatics, healthcare quality and safety, and healthcare simulation are often thought of as separate domains. The purpose of this position paper is to report on the interdependence that is emerging as an important triad across the healthcare/health system continuum. A qualitative review of 24 studies suggests the interdependence of health informatics, healthcare quality and safety, and healthcare simulation reaches much broader than traditional utilisation of simulation. We suggest ways that organisations can take advantage of the interdependence of this triad across a broader variety of healthcare environments, including teamwork, communication, and complex system relationships. In conclusion, the reviewed 24 studies suggest that the research in the triad focuses on simulation education and computerised simulation, and when coupled with health informatics, bears greater strength on quality improvement or patient safety.

Sizing and allocating health-care professionals are a critical problem in the management of emergency departments (EDs) managed by a public company in Rio de Janeiro (Brazil). An efficient ED configuration that is cost and time effective must be developed by this company for hospital managers. In this paper, the problem of health-care professional configurations in EDs is modelled to minimise the total labour cost while satisfying patient queues and waiting times as defined by the actual ED capacity and current clinical protocols. To solve this issue, mixed integer linear programming (MILP) that allocates health-care professionals and specifies the amount of professionals who must be hired is proposed. To consider the uncertainties in this environment and evaluate their impacts, a discrete-event simulation model is developed to reflect patient flow. An optimisation and simulation approach is used to search for efficiency leads for different ED configurations. These configurations change depending on the shift and the day of the week.

Coordinated systems of care are required to improve access to reperfusion therapies in paediatric stroke. A conceptual model was developed to map the process-of-care from symptom onset to confirmation of diagnosis. Value-Focused Process Engineering with event-driven process modelling was used to identify barriers and enablers to timely and accurate paediatric stroke diagnosis. Stakeholder interviews were conducted to inform model design, development, demonstration and validation. Barriers included: (i) ambulance dispatcher failure to allocate high-priority response, (ii) childrens' exclusion from paramedic clinical practice guidelines, (ii) non-allocation of high triage category on hospital arrival, (iii) absence of emergency department guidelines for focal neurological deficits, and (iv) computed tomography as the first imaging investigation. Enablers included: (i) public awareness programs, (ii) childrens' inclusion in prehospital emergency stroke algorithms, (iii) re-organisation of health services, with primary paediatric stroke centres, (iv) implementation of triage and neuroimaging decision support tools, and (iv) rapid stroke MRI imaging protocols.