Beyond ratios - flexible and resilient nurse staffing options to deliver cost-effective hospital care and address staff shortages: A simulation and economic modelling study.

BACKGROUND: In the face of pressure to contain costs and make best use of scarce nurses, flexible staff deployment (floating staff between units and temporary hires) guided by a patient classification system may appear an efficient approach to meeting variable demand for care in hospitals. OBJECTIVES: We modelled the cost-effectiveness of different approaches to planning baseline numbers of nurses to roster on general medical/surgical units while using flexible staff to respond to fluctuating demand. DESIGN AND SETTING: We developed an agent-based simulation, where hospital inpatient units move between being understaffed, adequately staffed or overstaffed as staff supply and demand (as measured by the Safer Nursing Care Tool patient classification system) varies. Staffing shortfalls are addressed by floating staff from overstaffed units or hiring temporary staff. We compared a standard staffing plan (baseline rosters set to match average demand) with a higher baseline 'resilient' plan set to match higher than average demand, and a low baseline 'flexible' plan. We varied assumptions about temporary staff availability and estimated the effect of unresolved low staffing on length of stay and death, calculating cost per life saved. RESULTS: Staffing plans with higher baseline rosters led to higher costs but improved outcomes. Cost savings from lower baseline staff mainly arose because shifts were left understaffed and much of the staff cost saving was offset by costs from longer patient stays. With limited temporary staff available, changing from low baseline flexible plan to the standard plan cost £13,117 per life saved and changing from the standard plan to the higher baseline 'resilient' plan cost £8,653 per life saved. Although adverse outcomes from low baseline staffing reduced when more temporary staff were available, higher baselines were even more cost-effective because the saving on staff costs also reduced. With unlimited temporary staff, changing from low baseline plan to the standard cost £4,520 per life saved and changing from the standard plan to the higher baseline cost £3,693 per life saved. CONCLUSION: Shift-by-shift measurement of patient demand can guide flexible staff deployment, but the baseline number of staff rostered must be sufficient. Higher baseline rosters are more resilient in the face of variation and appear cost-effective. Staffing plans that minimise the number of nurses rostered in advance are likely to harm patients because temporary staff may not be available at short notice. Such plans, which rely heavily on flexible deployments, do not represent an efficient or effective use of nurses. STUDY REGISTRATION: ISRCTN 12307968 Tweetable abstract: Economic simulation model of hospital units shows low baseline staff levels with high use of flexible staff are not cost-effective and don't solve nursing shortages.

Costs and consequences of using average demand to plan baseline nurse staffing levels: a computer simulation study.

BACKGROUND: Planning numbers of nursing staff allocated to each hospital ward (the 'staffing establishment') is challenging because both demand for and supply of staff vary. Having low numbers of registered nurses working on a shift is associated with worse quality of care and adverse patient outcomes, including higher risk of patient safety incidents. Most nurse staffing tools recommend setting staffing levels at the average needed but modelling studies suggest that this may not lead to optimal levels. OBJECTIVE: Using computer simulation to estimate the costs and understaffing/overstaffing rates delivered/caused by different approaches to setting staffing establishments. METHODS: We used patient and roster data from 81 inpatient wards in four English hospital Trusts to develop a simulation of nurse staffing. Outcome measures were understaffed/overstaffed patient shifts and the cost per patient-day. We compared staffing establishments based on average demand with higher and lower baseline levels, using an evidence-based tool to assess daily demand and to guide flexible staff redeployments and temporary staffing hires to make up any shortfalls. RESULTS: When baseline staffing was set to meet the average demand, 32% of patient shifts were understaffed by more than 15% after redeployment and hiring from a limited pool of temporary staff. Higher baseline staffing reduced understaffing rates to 21% of patient shifts. Flexible staffing reduced both overstaffing and understaffing but when used with low staffing establishments, the risk of critical understaffing was high, unless temporary staff were unlimited, which was associated with high costs. CONCLUSION: While it is common practice to base staffing establishments on average demand, our results suggest that this may lead to more understaffing than setting establishments at higher levels. Flexible staffing, while an important adjunct to the baseline staffing, was most effective at avoiding understaffing when high numbers of permanent staff were employed. Low staffing establishments with flexible staffing saved money because shifts were unfilled rather than due to efficiencies. Thus, employing low numbers of permanent staff (and relying on temporary staff and redeployments) risks quality of care and patient safety.

A mathematical model for designing networks of C-Reactive Protein point of care testing.

One approach to improving antibiotic stewardship in primary care may be to support all General Practitioners (GPs) to have access to point of care C-Reactive Protein tests to guide their prescribing decisions in patients presenting with symptoms of lower respiratory tract infection. However, to date there has been no work to understand how clinical commissioning groups might approach the practicalities of system-wide implementation. We aimed to develop an accessible service delivery modelling tool that, based on open data, could generate a layout of the geographical distribution of point of care facilities that minimised the cost and travel distance for patients across a given region. We considered different implementation models where point of care tests were placed at either GP surgeries, pharmacies or both. We analysed the trade-offs between cost and travel found by running the model under different configurations and analysing the model results in four regions of England (two urban, two rural). Our model suggests that even under assumptions of short travel distances for patients (e.g. under 500m), it is possible to achieve a meaningful reduction in the number of necessary point of care testing facilities to serve a region by referring some patients to be tested at nearby GP surgeries or pharmacies. In our test cases pharmacy-led implementation models resulted in some patients having to travel long distances to obtain a test, beyond the desired travel limits. These results indicate that an efficient implementation strategy for point of care tests over a geographic region, potentially building on primary care networks, might lead to significant cost reduction in equipment and associated personnel training, maintenance and quality control costs; as well as achieving fair access to testing facilities.

A mixed methods study of the impact of consultant overnight working in an English Emergency Department.

BACKGROUND: There is a growing expectation that consultant-level doctors should be present within an ED overnight. However, there is a lack of robust evidence substantiating the impact on patient waiting times, safety or the workforce. OBJECTIVES: To evaluate the impact of consultant-level doctors overnight working in ED in a large university hospital. METHODS: We conducted a controlled interrupted time series analysis to study ED waiting times before and after the introduction of consultant night working. Adverse event reports (AER) were used as a surrogate for patient safety. We conducted interviews with medical and nursing staff to explore attitudes to night work. RESULTS: The reduction seen in average time in department relative to the day, following the introduction of consultant was non-significant (-12 min; 95% CI -28 to 4, p=0.148). Analysis of hourly arrivals and departures indicated that overnight work was inherited from the day. There were three (0.9%) moderate and 0 severe AERs in 1 year. The workforce reported that night working had a negative impact on sleep patterns, performance and well-being and there were mixed views about the benefits of consultant night presence. Additional time off during the day acted as compensation for night work but resulted in reduced contact with ED teams. CONCLUSIONS: Our single-site study was unable to demonstrate a clinically important impact of consultant night working on total time patients spend in the department. Our analysis suggests there may be more potential to reduce total time in department during the day, at our study site. Negative impacts on well-being, and likely resistance to consultant night working should not be ignored. Further studies of night working are recommended to substantiate our results.

Funding and policy incentives to encourage implementation of point-of-care C-reactive protein testing for lower respiratory tract infection in NHS primary care: a mixed-methods evaluation.

OBJECTIVES: Utilisation of point-of-care C-reactive protein testing for lower respiratory tract infection has been limited in UK primary care, with costs and funding suggested as important barriers. We aimed to use existing National Health Service funding and policy mechanisms to alleviate these barriers and engage with clinicians and healthcare commissioners to encourage implementation. DESIGN: A mixed-methods study design was adopted, including a qualitative survey to identify clinicians' and commissioners' perceived benefits, barriers and enablers post-implementation, and quantitative analysis of results from a real-world implementation study. INTERVENTIONS: We developed a funding specification to underpin local reimbursement of general practices for test delivery based on an item of service payment. We also created training and administrative materials to facilitate implementation by reducing organisational burden. The implementation study provided intervention sites with a testing device and supplies, training and practical assistance. RESULTS: Despite engagement with several groups, implementation and uptake of our funding specification were limited. Survey respondents confirmed costs and funding as important barriers in addition to physical and operational constraints and cited training and the value of a local champion as enablers. CONCLUSIONS: Although survey respondents highlighted the clinical benefits, funding remains a barrier to implementation in UK primary care and appears not to be alleviated by the existing financial incentives available to commissioners. The potential to meet incentive targets using lower cost methods, a lack of policy consistency or competing financial pressures and commissioning programmes may be important determinants of local priorities. An implementation champion could help to catalyse support and overcome operational barriers at the local level, but widespread implementation is likely to require national policy change. Successful implementation may reproduce antibiotic prescribing reductions observed in research studies.

A facility location model for analysis of current and future demand for sexual health services.

In this paper we address the clinic location selection problem for a fully integrated Sexual Health Service across Hampshire. The service provides outpatient services for Genito-Urinary Medicine, contraceptive and reproductive health, sexual health promotion and a sexual assault referral centre. We aim to assist the planning of sexual health service provision in Hampshire by conducting a location analysis using both current and predicted patient need. We identify the number of clinic locations required and their optimal geographic location that minimise patient travel time. To maximise the chances of uptake of results we validate the developed simple algorithm with an exact method as well as three well-known, but complex meta-heuristics. The analysis was conducted using car travel and public transport times. Two scenarios were considered: current clinic locations only; and anywhere within Hampshire. The results show that the clinic locations could be reduced from 28 to 20 and still keep 90% of all patient journeys by public transport (e.g. by bus or train) to a clinic within 30 minutes. The number of clinics could be further reduced to 8 if the travel time is based on car travel times within 15 minutes. Results from our simple solution method compared favourably to the exact solution as well as the complex meta-heuristics.

Systems modelling and simulation in health service design, delivery and decision making.

The ever increasing pressures to ensure the most efficient and effective use of limited health service resources will, over time, encourage policy makers to turn to system modelling solutions. Such techniques have been available for decades, but despite ample research which demonstrates potential, their application in health services to date is limited. This article surveys the breadth of approaches available to support delivery and design across many areas and levels of healthcare planning. A case study in emergency stroke care is presented as an exemplar of an impactful application of health system modelling. This is followed by a discussion of the key issues surrounding the application of these methods in health, what barriers need to be overcome to ensure more effective implementation, as well as likely developments in the future.

Will delays in treatment jeopardize the population benefit from extending the time window for stroke thrombolysis?

BACKGROUND AND PURPOSE: Pooled analyses show benefits of intravenous alteplase (recombinant tissue-type plasminogen activator) treatment for acute ischemic stroke up to 4.5 hours after onset despite marketing approval for up to 3 hours. However, the benefit from thrombolysis is critically time-dependent and if extending the time window reduces treatment urgency, this could reduce the population benefit from any extension. METHODS: Based on 3830 UK patients registered between 2005 to 2010 in the Safe Implementation of Treatments in Stroke-International Stroke Thrombolysis Registry (SITS-ISTR), a Monte Carlo simulation was used to model recombinant tissue-type plasminogen activator treatment up to 4·5 hours from onset and assess the impact (numbers surviving with little or no disability) from changes in hospital treatment times associated with this extended time window. RESULTS: We observed a significant relation between time remaining to treat and time taken to treat in the UK SITS-ISTR data set after adjustment for censoring. Simulation showed that as this "deadline effect" increases, an extended treatment time window entails that an increasing number of patients are treated at a progressively lower absolute benefit to a point where the population benefit from extending the time window is entirely negated. CONCLUSIONS: Despite the benefit for individual patients treated up to 4.5 hours after onset, the population benefit may be reduced or lost altogether if extending the time window results in more patients being treated but at a lower absolute benefit. A universally applied reduction in hospital arrival to treatment times of 8 minutes would confer a population benefit as large as the time window extension.