Maximising patient throughput using discrete-event simulation

As the National Health Service (NHS) of England continues to face tighter cost saving and utilisation government set targets, finding the optimum between costs, patient waiting times, utilisation of resources, and user satisfaction is increasingly challenging. Patient scheduling is a subject which has been extensively covered in the literature, with many previous studies offering solutions to optimise the patient schedule for a given metric. However, few analyse a large range of metrics pertinent to the NHS. The tool presented in this paper provides a discrete-event simulation tool for analysing a range of patient schedules across nine metrics, including: patient waiting, clinic room utilisation, waiting room utilisation, staff hub utilisation, clinician utilisation, patient facing time, clinic over-run, post-clinic waiting, and post-clinic patients still being examined. This allows clinic managers to analyse a number of scheduling solutions to find the optimum schedule for their department by comparing the metrics and selecting their preferred schedule. Also provided is an analysis of the impact of variations in appointment durations and their impact on how a simulation tool provides results. This analysis highlights the need for multiple simulation runs to reduce the impact of non-representative results from the final schedule analysis

Maximising patient throughput using discrete-event simulation

As the National Health Service (NHS) of England continues to face tighter cost saving and utilisation government set targets, finding the optimum between costs, patient waiting times, utilisation of resources, and user satisfaction is increasingly challenging. Patient scheduling is a subject which has been extensively covered in the literature, with many previous studies offering solutions to optimise the patient schedule for a given metric. However, few analyse a large range of metrics pertinent to the NHS. The tool presented in this paper provides a discrete-event simulation tool for analysing a range of patient schedules across nine metrics, including: patient waiting, clinic room utilisation, waiting room utilisation, staff hub utilisation, clinician utilisation, patient facing time, clinic over-run, post-clinic waiting, and post-clinic patients still being examined. This allows clinic managers to analyse a number of scheduling solutions to find the optimum schedule for their department by comparing the metrics and selecting their preferred schedule. Also provided is an analysis of the impact of variations in appointment durations and their impact on how a simulation tool provides results. This analysis highlights the need for multiple simulation runs to reduce the impact of non-representative results from the final schedule analysis

Modeling and simulating hospital operations in a 3D environment

The use of dashboards to aid hospital decision makers in managerial and clinical decisions is well documented in the literature, though few broach the challenging subject of combining cost measurement with user satisfaction and building layout optimization. This paper presents an innovative dashboard in a 3D environment, providing decision makers with simulation capabilities using agent based simulation, allowing examination of their facility and the impact of policy, process and layout changes on patients and finances. An example is presented for an Emergency Department, wherein the presented dashboard revealed that the costs of constructing additional triage rooms would produce no benefit to patients; rather, a change in the process would be more beneficial compared with the existing situation. It is concluded that the developed dashboard allows users to make comparisons between multiple scenarios and visualize data in an intuitive format, allowing for decision makers to optimize their facility and operations

A Random Parameter Logit model for modeling Health Care Provider Choice in Bolivia

In this paper we model health care provider choice in Bolivia with a Random Parameter Logit (RPL) using MECOVI data during the period 1999 and 2000. To our knowledge this is the first time that a RPL is used for modeling health care provider choice in Bolivia. We found that price and income are determinants of the decision choice of health care provider. Increasing government prices or fees shift the demand from government to private health facilities for children and women. In addition, women are more sensitive than children and adults to changes in price and income. The perception of Quality is significant just for private health facilities except for children. Finally, people would rather private instead of government facilities and self care treatment when they are ill.Random Parameter Logit; Government and Private Health Facilities; Quality; Prices or User Fees

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.

Planning for resilience in screening operations using discrete event simulation modeling: example of HPV testing in Peru

ABSTRACT: Background: The World Health Organization (WHO) has called for the elimination of cervical cancer. Unfortunately, the implementation of cost-effective prevention and control strategies has faced significant barriers, such as insufficient guidance on best practices for resource and operations planning. Therefore, we demonstrate the value of discrete event simulation (DES) in implementation science research and practice, particularly to support the programmatic and operational planning for sustainable and resilient delivery of healthcare interventions. Our specific example shows how DES models can inform planning for scale-up and resilient operations of a new HPV-based screen and treat program in Iquitos, an Amazonian city of Peru. Methods: Using data from a time and motion study and cervical cancer screening registry from Iquitos, Peru, we developed a DES model to conduct virtual experimentation with “what-if” scenarios that compare different workflow and processing strategies under resource constraints and disruptions to the screening system. Results: Our simulations show how much the screening system’s capacity can be increased at current resource levels, how much variability in service times can be tolerated, and the extent of resilience to disruptions such as curtailed resources. The simulations also identify the resources that would be required to scale up for larger target populations or increased resilience to disruptions, illustrating the key tradeoff between resilience and efficiency. Thus, our results demonstrate how DES models can inform specific resourcing decisions but can also highlight important tradeoffs and suggest general “rules” for resource and operational planning. Conclusions: Multilevel planning and implementation challenges are not unique to sustainable adoption of cervical cancer screening programs but represent common barriers to the successful scale-up of many preventative health interventions worldwide. DES represents a broadly applicable tool to address complex implementation challenges identified at the national, regional, and local levels across settings and health interventions—how to make effective and efficient operational and resourcing decisions to support program adaptation to local constraints and demands so that they are resilient to changing demands and more likely to be maintained with fidelity over time

An analysis of the determinants of access to medicines and health care in developing country settings

The research question of this thesis is what are the determinants of access to medicines and health care in developing countries? First, this thesis hypothesises that income is an important determinant of access to medicines and health care and that access is low for low income individuals. Second, this thesis hypothesises that an expectation of a high level of expenditure on medicines reduces the propensity to consume which implies a negative price elasticity. This thesis sets out to understand demand structures to answer this research question. The first chapter conducts an exploratory exercise to study government demand for medicines using price procurement data across a sample of developing countries. A different approach is used to impute price elasticities for medicines and range from -1.0 and -2.0. This means that a 1% increase in medicine prices, government demand for medicines will drop from 1% to 2%. The thesis begins the econometric analysis at the patient level using household survey data across a cross-section of 35 developing countries. Demand for health care is inelastic ranging from -0.19 to 0.6. The next two stages of empirical work use national household level data from India as a country case study. Price elasticities for outpatient care range from -0.17 to 0.43 and for inpatient care range from -0.13 to 0.03. Overall, the statistically significant price elasticity results are intuitive with a negative sign but are inelastic and at the lower end of the range found in the literature. The main determinants of health seeking behaviour are similar across different health settings studied in this thesis. These include having insurance and high household expenditure which implies that the poor will experience access problems. Other drivers include health status, gender, marital status, geographical location, education, employment and regulation. This thesis contributes to the evidence base because current research is limited and has typically drawn from smaller datasets. With a particular focus on medicines, the empirical findings offer policy implications in settings where pharmaceutical policies are not well developed. A broader approach to pharmaceutical policy making is necessary that considers reform measures on the demand and supply side from a health systems perspective

Human and physical infrastructure : public investment and pricing policies in developing countries

Almost by definition, the basis for development is infrastructure - whether services for human infrastructure (health, education, nutrition) or physical infrastructure (transport, energy, water). Although the infrastructure sectors are diverse, what they have in common is that public policy has had a great deal to do with how these services are provided and financed in almost all countries. The author reviews the recent literature on two key aspects of that involvement: investment and pricing. While the quality of the econometric evidence varies, recent literature reinforces the view that human and physical infrastructure are critical for economic growth and the reduction of poverty. And the state is recognized as playing a key role in ensuring the efficient, equitable allocation of resources for infrastructure. Despite many sound theoretical reasons for such public involvement, however, recent studies have shown that it leaves much to be desired in efficiency and equity. One symptom is underinvestment in key subsectors that have high economic returns and that help the poor the most, such as primary education and rural health clinics, in relation to more expensive interventions, such as tertiary education and urban hospitals. Another common malaise is the poor use of scarce resources, leading to low quality (students learning little) and reliability (irregular power and water flows), poor maintenance (dilapilated roads), and inappropriate input use (too many school adminstrators or health workers and not enough books or drugs in producing education health outcomes). Just as market failures necessitate government intervention in the infrastructure sectors, so government failures should be considered in deciding the depth and extent of that intervention. The literature has made some advances in diagnosing these problems in poor countries and proposing solutions. But information gaps remain, particularly in developing robust methodologies for: 1) making intersectoral comparisons across the wide range of infrastructure services; 2) crafting more diverse policies about the public-private balance in infrastructure investment, depending on the nature of"public goods"characteristics for various types of infrastructure services, or even across activities for the same service (for example, power transmission versus distribution); and 3) taking issues of political economy into account, such as the vested interests of those with large financial interests in infrastructure. The author also highlights public pricing as a policy initiative that has recently gotten much attention.After briefly reviewing the basic concepts of pricing, he focuses on the literature about pricing reform. Most commonly, the public sector is the main provider of infrastructure services, usually free or at subsidized prices. But the recent literature has aired a rethinking of the balance between public and private financing of infrastructure. The debate in this area is often heated. Health and education are traditionally provided free and some recent literature argues for positive prices, at least for higher tiers of service. The principle of public pricing has been more widely accepted in transport, energy, and to a lesser extent water, but often the levels are too low and do not provide the appropriate incentives for efficient and equitable use.Environmental Economics&Policies,Banks&Banking Reform,Health Monitoring&Evaluation,Public Sector Economics&Finance,Economic Theory&Research

The Community IntraVenous Antibiotic Study (CIVAS): a mixed methods evaluation of patient preferences for and cost effectiveness of different service models for delivering outpatient parenteral antimicrobial therapy

Background: Outpatient parenteral antimicrobial therapy (OPAT) is widely used in most developed countries, providing considerable opportunities for improved cost savings. However, it is implemented only partially in the UK, using a variety of service models. Objectives: The aims of this research were to (1) establish the extent of OPAT service models in England and identify their development; (2) evaluate patients’ preferences for different OPAT service delivery models; (3) assess the cost-effectiveness of different OPAT service delivery models; and (4) convene a consensus panel to consider our evidence and make recommendations. Methods: This mixed-methods study included seven centres providing OPAT using four main service models: (1) hospital outpatient (HO) attendance; (2) specialist nurse (SN) visiting at home; (3) general nurse (GN) visiting at home; and (4) self-administration (SA) or carer administration. Health-care providers were surveyed and interviewed to explore the implementation of OPAT services in England. OPAT patients were interviewed to determine key service attributes to develop a discrete choice experiment (DCE). This was used to perform a quantitative analysis of their preferences and attitudes. Anonymised OPAT case data were used to model cost-effectiveness with both Markov and simulation modelling methods. An expert panel reviewed the evidence and made recommendations for future service provision and further research. Results: The systematic review revealed limited robust literature but suggested that HO is least effective and SN is most effective. Qualitative study participants felt that different models of care were suited to different types of patient and they also identified key service attributes. The DCE indicated that type of service was the most important factor, with SN being strongly preferred to HO and SA. Preferences were influenced by attitudes to health care. The results from both Markov and simulation models suggest that a SN model is the optimal service for short treatment courses (up to 7 days). Net monetary benefit (NMB) values for HO, GN and SN services were £2493, £2547 and £2655, respectively. For longer treatment, SA appears to be optimal, although SNs provide slightly higher benefits at increased cost. NMB values for HO, GN, SN and SA services were £8240, £9550, £10,388 and £10,644, respectively. The simulation model provided useful information for planning OPAT services. The expert panel requested more guidance for service providers and commissioners. Overall, they agreed that mixed service models were preferable. Limitations: Recruitment to the qualitative study was suboptimal in the very elderly and ethnic minorities, so the preferences of patients from these groups might not be represented. The study recruited from Yorkshire, so the findings may not be applicable nationally. Conclusions: The quantitative preference analysis and economic modelling favoured a SN model, although there are differences between sociodemographic groups. SA provides cost savings for long-term treatment but is not appropriate for all. Future work: Further research is necessary to replicate our results in other regions and populations and to evaluate mixed service models. The simulation modelling and DCE methods used here may be applicable in other health-care settings. Funding: The National Institute for Health Research Health Service and Delivery Research programme

BMC Public Health

BackgroundDespite WHO advocating for an integrated approach to antenatal care (ANC), testing coverage for conditions other than HIV remains low and women are referred to distant laboratories for testing. Using point-of-care tests (POCTs) at peripheral dispensaries could improve access to testing and timely treatment. However, the effect of providing additional services on nurse workload and client wait times are unknown. We use discrete-event simulation (DES) modelling to understand the effect of providing four point-of-care tests for ANC on nurse utilization and wait times for women seeking maternal and child health (MCH) services.MethodsWe collected detailed time-motion data over 20\u2009days from one high volume dispensary in western Kenya during the 8-month implementation period (2014\u20132015) of the intervention. We constructed a simulation model using empirical arrival distributions, activity durations and client pathways of women seeking MCH services. We removed the intervention from the model to obtain wait times, length-of-stay and nurse utilization rates for the baseline scenario where only HIV testing was offered for ANC. Additionally, we modelled a scenario where nurse consultations were set to have minimum durations for sufficient delivery of all WHO-recommended services.ResultsA total of 183 women visited the dispensary for MCH services and 14 of these women received point-of-care testing (POCT). The mean difference in total waiting time was 2\u2009min (95%CI: <\u20091\u20134\u2009min, p\u2009=\u20090.026) for MCH women when integrated POCT was given, and 9\u2009min (95%CI: 4\u201314\u2009min, p\u2009<\u20090.001) when integrated POCT with adequate ANC consult times was given compared to the baseline scenario. Mean\ua0length-of-stay increased by 2\u2009min (95%CI: <\u20091\u20134\u2009min, p\u2009=\u20090.015) with integrated POCT and by 16\u2009min (95%CI: 10\u201321\u2009min, p\u2009<\u20090.001) with integrated POCT and adequate consult times compared to the baseline scenario. The two nurses\u2019 overall daily utilization in the scenario with sufficient minimum consult durations were 72 and 75%.ConclusionThe intervention had a modest overall impact on wait times and length-of-stay\ua0for women seeking MCH services while ensuring pregnant women received essential diagnostic testing. Nurse utilization rates fluctuated among days: nurses experienced spikes in workload on some days but were under-utilized on the majority of days. Overall, our model suggests there was sufficient time to deliver all WHO\u2019s required ANC activities and offer integrated testing for ANC first and re-visits with the current number of healthcare staff. Further investigations on improving healthcare worker, availability, performance and quality of care are needed. Delivering four point-of-care tests together for ANC at dispensary level would be a low burden strategy to improve ANC.2019-12-03T00:00:00Z31795999PMC6892244779