ABSTRACT We examine how physicians’ perceptions of two computerized provider order entry (CPOE) capabilities, standardisation of care protocols and documentation quality, are associated with their perceptions of turnaround time, medical error, and job demand at three phases of CPOE implementation: pre-go-live, initial use, and continued use. Through a longitudinal study at a large urban hospital, we find standardisation of care protocols is positively associated with turnaround time reduction in all phases but positively associated with job demand increase only in the initial use phase. Standardisation also has a positive association with medical error reduction in the initial use phase, but later this effect becomes fully mediated through turnaround time reduction in the continued use phase. Documentation quality has a positive association with medical error reduction in the initial use phase and this association strengthens in the continued use phase. Our findings provide insights to effectively manage physicians’ response to CPOE implementation.

ABSTRACT Sleep is so important, particularly for the elderly. The lack of sleep may increase the risk of cognitive decline. Similarly, it may also increase the risk of Alzheimer’s disease. Nonetheless, many people underestimate the importance of getting enough rest and sleep. In-laboratory polysomnography is the gold-standard method for assessing the quality of sleep. This method is considered impractical in the clinical environment, seen as labour-intensive and expensive owing to its specialised equipment, leading to long waiting lists. Hence, user-friendly (remote and non-intrusive) devices are being developed to help patients monitor their sleep at home. In this paper, we first discuss commercially-available non-wearable devices that measure sleep, in which we highlight the features associated with each device, including sensor type, interface, outputs, dimensions, power supply, and connectivity. Second, we evaluate the feasibility of a non-wearable device in a free-living environment. The deployed device comprises a sensor mat with an integrated micro-bending multimode fibre. Raw sensor data were gathered from five senior participants living in a senior activity centre over a few to several weeks. We were able to analyse the participants’ sleep quality using various sleep parameters deduced from the sensor mat. These parameters include the wake-up time, bedtime, the time in bed, nap time. Vital signs, namely heart rate, respiratory rate, and body movements, were also reported to detect abnormal sleep patterns. We have employed pre-and post-surveys reporting each volunteer’s sleep hygiene to confirm the proposed system’s outcomes for detecting the various sleep parameters. The results of the system were strongly correlated with the surveys for reporting each sleep parameter. Furthermore, the system proved to be highly effective in detecting irregular patterns that occurred during sleep.

ABSTRACT Operating room (OR) resources are limited, and for this reason there is usually a competition among surgeons to win them. However, the methods developed for allocating OR sessions are mostly based on optimisation methods which compensate the preferences of surgeons or surgical specialities in favour of the productivity of the entire OR department. This leads to conflict and dissatisfaction among surgeons. To overcome this problem, a methodology based on game theoretic solutions is presented in this paper that formulates the allocation problem as a simple game. The surgeons or specialities as players then jointly pursue the goal of achieving overall stability. Stability is defined and measured using a method called Power Index. The proposed method is then combined with the Monte-Carlo technique to deal with uncertainties. To demonstrate the capability of the suggested procedures, they are applied to a case study from the literature and a set of hypothetical scenarios.

ABSTRACT The hospital outpatient non-attendance imposes a substantial financial burden on hospitals and roots in multiple diverse reasons. This research aims to build an advanced predictive model for predicting non-attendance regarding the whole spectrum of probable contributing factors to non-attendance that could be collated from heterogeneous sources including electronic patients records and external non-hospital data. We proposed a new non-attendance prediction model based on deep neural networks and machine learning models. The proposed approach works upon sparse stacked denoising autoencoders (SDAEs) to learn the underlying manifold of data and thereby compacting information and providing a better representation that can be utilised afterwards by other learning models as well. The proposed approach is evaluated over real hospital data and compared with several well-known and scalable machine learning models. The evaluation results reveal the proposed approach with softmax layer and logistic regression outperforms other methods in practice.

ABSTRACT The Thoraxcenter of Erasmus MC started an improvement project in 2015 in order to increase the number of open-heart surgeries by 150 for three consecutive years (450 in total, +46%), and to decrease the access time from 12–14 to 2–3 weeks by the end of 2016. This was required to attain economy of scale in a highly competitive market. In this paper we describe the first year of the project, focusing on its structure and interventions taken, resulting in 165 additional open-heart surgeries carried out in 2016 and a significantly shorter access time of 2–3 weeks.

ABSTRACT 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.

ABSTRACTThis issue is the second in the series to explore the intersection of health informatics, healthcare quality and safety, and healthcare simulation. The uses of all three domains to advance healthcare operations has been diverse and intentional across a variety of domestic and international organisations. This issue focuses primarily on studies that use throughput modelling and system modelling. Findings from this special collection of papers demonstrate the value of modelling techniques and their role in predicting and enhancing healthcare operations.

ABSTRACTSizing 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.

ABSTRACT The objective of this study is two-fold: to propose an alternative approach for computing the productivity of physicians in emergency departments (EDs); and, to allocate productivity-driven schedules to ED physicians so as to align physician productivity with demand (patient arrivals), without decreasing fairness between physicians, in order to improve patient wait times. Historical data between 2008 and 2017 from the Sacré-Coeur Montreal Hospital ED is analysed and used to predict the demand and to estimate the productivity of each physician. These estimates are incorporated into a mathematical programming model that identifies feasible schedules to physicians that minimise the difference between patients’ demand and physicians’ productivity, along with the violation of physicians’ preferences and fairness in the distribution of shifts. Results on real-world-based data show that when physician productivity is included in the allocation of schedules, demand under-covering is reduced by 10.85% and the fairness between physicians is maintained. However, physicians’ preferences (e.g., sum of the differences between the number of wanted shifts and the number of allocated shifts) deteriorates by 7.61%. By incorporating the productivity of physicians in the scheduling process, we see a reduction in EDs overcrowding and an improvement in the overall quality of health-care services.

ABSTRACTThe aim of this paper is to demonstrate the potential of the systemic innovations approach for transforming transplantation systems. It explores potential leverage points for intervening in the LTx-system as well as possible paths of transformation. We present possible transition pathways giving the example of the German Lung transplantation system that teeters on the brink of collapse due to system failures and organ scarcity and illustrate systemic innovations as core mechanisms for systems change in health systems. Desk research and semi-structured experts interviews provided qualitative data for a deductive-inductive coding and a rigorous qualitative content analysis of the data. Depending on the systemic innovations chosen to achieve systems change, transplant systems follow different transformational paths: from a collapse to a leapfrogging towards a non-human transplantation system. Thus, global health areas like transplantation benefit from analysis on systemic innovations as these support researchers, public policy and regulators by developing transformative strategies in healthcare systems.