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Biomedical subjects

P H Millard

Publications and source records attributed to P H Millard.

At least 19 recordsLinked to original sources
PubMed2001

Modelling hospital and social care bed occupancy and use by elderly people in an English health district.

The paper confirms that exponential equations can be used to model the total system and sub-systems of institutional health and social care for elderly people using bed occupancy census data for 6,068 elderly aged 65 and over. Two streams of flow were present in NHS acute hospitals, Local Authority residential homes and independent sector nursing homes. Three streams of flow were present in the overall data set and in the NHS geriatric hospital beds, NHS psychiatry beds and independent sector residential care homes. In total 22% of patients/residents stayed an average of 24 days (short stay), 69% for 825 days (medium stay) and 9% for 3,384 days (long stay). In both sexes, the older a patient/resident, the longer the time they occupied short stay beds and the shorter the time they occupied long stay beds.

Aged↗
PubMed2001

Developing a Bayesian belief network for the management of geriatric hospital care.

Resource management is an essential feature of hospital management. This is especially true for geriatric services, as older people often have complex medical and social needs. Hospital management should benefit from an explanatory model that provides predictions of duration of stay and destination on discharge. We describe how a Bayesian belief network models the behaviour of geriatric patients using predictive variables: personal details, admission reasons and dependency levels. This approach is illustrated using data on 4,722 patients admitted to geriatric medicine at St. George's Hospital, London; distributions of the patient outcome given typical values of the predictive variables are provided.

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PubMed2000

Measuring and modelling surgical bed usage.

Surgical departments treat two groups of inpatients--the simple and the complex--consequently a single average fails to describe the use being made of the occupied beds. Using decision support techniques, we show why indicators such as the average length, the average occupancy and the average admissions mislead. Furthermore, by analysing the fluctuating pattern of weekly admissions we show how weekends and the Christmas holiday periods impact on bed usage. Next, we demonstrate that flow process models can be used to describe how the in-patient workload concerns two groups of patients. On an average day, 71.4% of the beds contained patients who will have an average (exponential) stay of 4.8 days, and the other beds, 28.6%, contain patients who will have an average (exponential) stay of 22.8 days. The article concludes by demonstrating the short and long-term impact on daily admissions of a 10% change in four different parameters of the model. The data used come from a surgical department in Adelaide, as UK data sets report finished consultant episodes rather than completed in-patient spells.

Bed Occupancy↗
PubMed1999

Application and comparison of two modelling techniques for hospital bed management.

The use of the bed occupancy management and planning system (BOMPS) and the Sorensen multi-phased bed model were used to assess the implications of a hospital expanding its emergency facility. BOMPS flow modelling generates resource utilisation data dependent on the best visual and statistical fit between mixed exponential equations and time of bed occupancy; the Sorensen model creates models based on probabilities and length of stay distributions. Both models identified the presence of two streams of flow. However, there were differences in the number of beds identified as being short and longer stay. The advantage of flow modelling is that it enables decision-makers to pre-test their decisions.

Australia↗
PubMed1998

A three compartment model of the patient flows in a geriatric department: a decision support approach.

As users of long term geriatric services occupy the beds for prolonged periods of time it is important that decision makers understand how clinical and social decisions interact to influence long term care costs. A flow modelling approach enables us to estimate current inpatient activity and to test different care options, thereby optimising decision making. In previous work we developed a two compartment model of patient flows within a geriatric hospital, where patients are initially admitted to an acute or rehabilitative state from which they either are discharged or die or are converted to a long-stay state. Long-stay patients are discharged or die at a slower rate. This initial research discussed the use of a compartmental model to describe flows through the hospital system. We now discuss a three compartment model where the compartments may be described as consisting of acute care, rehabilitation and long-stay care. A Markov model is then used to count and cost the movements of geriatric patients within a hospital system. Such an approach enables health service managers and clinicians to assess performance and evaluate the effect of possible changes to the system. By attaching costs to various parts of the system we may facilitate the evaluation and comparison of different strategies and scenarios. Using the model, we show that a geriatric medical service that improved the acute management of in-patients became more cost-efficient. Hospital planners may thus identify cost-effective options.

Aged↗
PubMed1998

Evaluating the costs of alternative options for dementia services.

In the next decade the number of demented people is likely to increase. This has a financial impact on the resources allocated for health and social care. Classical methodologies for dealing with dementia include the historic model that has been criticised for its poor co-ordination between general practitioners, psychiatrists, social workers and the treatment services, and the needs-based approach that, although it involves a co-ordinating needs manager, does not prevent leapfrogging of patients. In order to overcome these problems we propose an annual screening of patients to take place in the needs-based models and compare this with a more sophisticated model in which after being screened patients are investigated for potential drug treatment. We also consider mix intervals for under 75 and over 75. Decision analysis is used to assess the different screening options. Assuming a 20% reduction by treatment of the cost of care we find optimal the investigation/treatment of all patients after screening. Sensitivity analysis shows that even an 8.5% reduction would make the needs-based models non-optimal.

Costs and Cost Analysis↗
PubMed1998

A simulation modelling approach to evaluating length of stay, occupancy, emptiness and bed blocking in a hospital geriatric department.

The flow of patients through geriatric hospitals has been previously described in terms of acute (short-stay), rehabilitation (medium-stay), and long-stay states where the bed occupancy at a census point is modelled by a mixed exponential model using BOMPS (Bed Occupancy Modelling and Planning System). In this a patient is initially admitted to acute care. The majority of the patients are discharged within a few days into their own homes or through death. The rest are converted into medium-stay patients where they could stay for a few months and thereafter either leave the system or move on to a long-stay compartment where they could stay until they die. The model forecasts the average length of stay as well as the average number of patients in each state. The average length of stay in the acute compartment is artificially high if some would-be long-term patients are kept waiting in the short-stay compartment until beds become available in long-stay (residential and nursing homes). In this paper we consider the problem as a queueing system to assess the effect of blockage on the flow of patients in geriatric departments. What-if analysis is used to allow a greater understanding of bed requirements and effective utilisation of resources.

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PubMed1998

An analysis of admission, discharge and bed occupancy of stroke patients aged 65 and over in English hospitals.

Stroke illness is a common problem in the UK. Factors such as incidence, age, and ethnicity have already been shown to affect admission patterns and discharge outcomes. Our analysis of an English Hospital Episode Statistics database shows that weekends and public holidays also influence the admission and discharge patterns of elderly stroke patients. We discuss the possible reasons for this.

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