Assessing efficiency of public health and medical care provision in OECD countries after a decade of reform

Central European Journal of Operations Research - The objective of this study was to examine the change in efficiency of health care systems of 34 OECD countries between 2000 and 2012, a period...     

Improving health care through community OR

Two examples of Community OR (COR) applied to public and patient involvement in improving health services in the UK are described—the Hull and East Riding Impact project and Trailblazers. These projects are consumer controlled but professionally facilitated. The team members have or have had mental illnesses but are committed to improving mental health services by applying COR methods. These projects illustrate how COR can contribute to the improvement of health services by enabling service users to take the lead in facilitating multi-stakeholder planning and problem solving. The Impact team produced a tool based around Ulrich's critical heuristics and have used this in several successful consultations in the NHS. The Trailblazer project used an idealized planning approach in a novel way to produce a distance method of consultation aimed at enabling stakeholders to negotiate commitments to action. Longer-term evaluation of these approaches is planned.     

Computationally efficient evaluation of appointment schedules in health care

We consider the problem of evaluating and constructing appointment schedules for patients in a health care facility where a single physician treats patients in a consecutive manner, as is common for general practitioners, clinics and for outpatients in hospitals. Specifically, given a fixed-length session during which a physician sees K patients, each patient has to be given an appointment time during this session in advance. Optimising a schedule with respect to patient waiting times, physician idle times, session overtime, etc. usually requires a heuristic search method involving a huge number of repeated schedule evaluations. Hence, our aim is to obtain accurate predictions at very low computational cost. This is achieved by (1) using Lindley’s recursion to allow for explicit expressions and (2) choosing a discrete-time (slotted) setting to make those expressions easy to compute. We assume general, possibly distinct, distributions for the patients’ consultation times, which allows to account for multiple treatment types, emergencies and patient no-shows. The moments of waiting and idle times are obtained and the computational complexity of the algorithm is discussed. Additionally, we calculate the schedule’s performance in between appointments in order to assist a sequential scheduling strategy.     

Risk-adjusted control charts for health care assessment

The recent Joint Commission on Accreditation of Healthcare Organization (JCAHO) requirement that hospital accreditation be based upon a Total Quality Management (TQM) approach has focused the attention of health care administrations on the use of techniques such as control charts. However, control charts are not typically adjusted for severity of illness. This adjustment is needed because, unlike industrial organizations, hospitals are not able to control all of their inputs and must accept variances in their patients. In this paper, we present a methodology for adjusting a health care organization's control charts to reflect their patient population's severity of illness during different time intervals. We then demonstrate that risk-adjusting expected patient outcomes can change our assessments of the relative quality of care offered by a health care organization in different time periods.     

Modelling toolkit to assist with introducing a stepped care system design in mental health care

We describe a modelling toolkit that was developed with the aim of assisting those responsible for introducing stepped care systems to local mental health services in the UK. The toolkit was pre-populated with real patient flow data collected from four sites that piloted the stepped care system design. Two analytical models were developed and coded as part of the toolkit to provide insights concerning workload, patient throughput, and changes in waiting times and waiting list size. An interface was built to allow users to specify their own stepped care system and input their own estimates or data of service demands and capacities at different steps. Despite the challenges and limitations, the use of modelling to inform the design of new service configurations is an important step in the right direction and we would recommend this as a reasonable way forward.     

Data envelopment analysis applied to quality in primary health care

The performance of primary care should ultimately be judged on its effect on the health outcome of individual patients. However, for the foreseeable future, it is inconceivable that the outcome data necessary to come to a judgement on performance will be available. And in any case, specification of the statistical model necessary to analyze outcome is fraught with difficulty. This paper therefore sets out a model of primary care performance which is based on the premise that certain measurable quality indicators can act as proxies for outcome. This being the case, a model of performance can be deduced which takes into account the effect of resources and patient characteristics on outcome. The most appropriate analytic technique to make this model operational is data envelopment analysis (DEA). It is argued that DEA can handle multiple dimensions of performance more comfortably, and is less vulnerable to the misspecification bias that afflicts statistically based models. The issues are illustrated with an example from English Family Health Service Authorities.     

Advanced computing solutions for health care and medicine

This guest editorial introduces the special issue on “Advanced Computing Solutions for Health Care and Medicine”. The goal of this special issue was to collect high quality papers describing the application of computer science methods and techniques to main health care and clinical problems, resulting in high performance applications or prototypes for medical and clinical environments. The special issue touched different health informatics hot topics and is organized in four sections: (i) clinical decision support systems; (ii) biomedical imaging; (iii) high performance computing and biomedical simulations; (iv) bioinformatics data analysis.     

System dynamics applications to European health care issues

Taking a European perspective, a review is made of some system dynamics models which address health care issues. Suggestions are made for the types of role which these models should take, bearing in mind the strategic orientation of system dynamics modelling. Examples are described of qualitative models where influence diagrams are the main analytical tool. Quantitative system dynamics models have a contribution to make in epidemiological studies and have been used to analyse the AIDS epidemic. A detailed example of one aspect of model formulation is given. This concerns the AIDS incubation time distribution and shows how real-world complications arising from virological staging and treatment effects are handled in a model of AIDS spread.