Contents of August 2007 Issue

Nosokinetics

August 2007 Issue

(c)Authors for content; Peter Millard, Roy Johnston for e-version

(comments to rjtechne at iol dot ie)

In this issue:

A new initiative: Mark Fackrell's article explaining the mystery of exponential and phase-type modelling, summarised here, is mailed separately and on the web.

Readers responses to old and new physics lead to concepts based on structure, pattern and process.

Martin Pitt reports the success of the 33rd ORAHS conference in St. Etienne.

Below we have leads to several journal articles; also HSCM Portrush 18 - 20 March 2008.

First congratulations to Thierry:

Professor Thierry Chaussalet

Thierry's research and scholarship, as Leader of the Health and Social Care Modelling Group at the University of Westminster, has now been recognised by the University as a full professor. Also his research, with Haifeng Xie, into modelling the committed cost of currently funded clients in residential and nursing home care, is being prototyped by the Department of Health for use by English Social Service Departments. Success heralds a break through in understanding the benefits of modelling the process and cost of care.

Abstracts

Multi-stage model for whole hospital planning: Cochran JK, Bharti A. "A multi-stage stochastic methodology for whole hospital bed planning under peak loading." International Journal of Industrial and Systems Engineering 2006;1(1/2):8-36.
A two stage process to modelling a hospital with 400 beds. Flow diagrams show the pathways of patient care for the whole hospital and in medicine and surgery. A queing network is used to describe insights into optimal bed allocation at peak occupancy. And a system dynamic model is used to gain insight into the use of beds by department and to identify services that have too much or too little resources. Further work includes estimation of bed-blocking, staffing, schedules and patient classification. The long term aim is real time integration of the models with the hospital database.

History teaches: 1976 stochastic model of bed distribution: Esogbue AO, Singk AJ. "A stochastic model for an optimal priority bed distribution problem in a hospital ward." Operations Research 1976;24(5):884-898.
A historic paper drawn to our attention by Asad in Thierry Chausalet's group, presents a patient centred mathematical model of admission policies, a hybrid of traditional models, which seeks to maximise occupancy and minimize unsatisfied needs. Specifically, the object is to provide a quantitative, rational and operational basis for establishing a priority "cut-off occupancy" that will maximise the medical benefits while differentiating for case types. Three types of cost are considered - Holding costs, shortage costs and fixed operating costs. A decision tree shows the possible patient outcomes - getting better, staying the same and getting worse. Use is demonstrated with data from a 1000 bed hospital in Cleveland.

Mathematical model of maternal services: why bother: Galväo RD, Espejo LGA, Boffey B. "A hierarchical model for the location of perinatal facilities in the municipality of Rio de Janeiro." European Journal of Operational Research 2002;138: 495-517
With the aim of reducing perinatal mortality, a three level hierarchical model for the location of maternal and perinatal health care facilities in Rio was created. The mathematical solution is presented using two basic heuristics and tested using 1995 data. The authors end with a warning "Why embark on a mathematical model if the Municipality are not going to use it?" I've got the answer to that. The problem is complicated and has methodological problems that are difficult to overcome. It's a step forward on the path. Also if they don't use it, someone else might.

Two studies focusing on delayed transfer: Poulos C, Eagar K, Poulos RG. "Managing the interface between acute care and rehabilitation - can utilisation review help?" Australian Health Review 2007;31 Suppl 1(S1):129-140; Poulos, C. J. and K. Eagar (2007). Determining appropriateness for rehabilitation or other subacute care: is there a role for utilisation review. Australian and New Zealand Health Policy 4(3).
What is best practice? Early transfer for rehabilitation or one stop shops? Clinically, it probably depends on the quality of patient management and available resources in both places. The observational study pilots the use of a commercially available tool (InterQual Criteria) which is being used in some American and Canadian hospitals to identify appropriateness of care. The pilot study, in one hospital, shows differences in practice with delays in referral and resource availability. The study population had stroke illness, hip fracture or amputation.

Delays in admission from A&E effect outcome of care: Chalfin, D. B., S. Trzeciak, et al. (2007). "Impact of delayed transfer of critically ill patients from the emergency department to the intensive care unit." Crit Care Med 35(6): 1477-83.
Using a multi-centre US database of intensive care (Project IMPACT) a cross-sectional study of 50,332 admitted patients showed that 2% of patients stayed longer than six hours in emergency care. Their in hospital mortality was 17.4% (delayed) vs. 12.9% (non-delayed) p=0.01. Determinants were increased age, males, diagnostic category and neurological disease. Which clinically may be associated with more deaths whenever admitted.

Predicting outcome of trauma patients: Clark, D. E., F. L. Lucas, et al. (2007). "Predicting hospital mortality, length of stay, and transfer to long-term care for injured patients." J Trauma 62(3): 592-600.
Data 369,829 patient records from the 1999 to 2993 National Trauma Data Bank. A multistate model, divided into four time periods, each with constant rates of death, discharge home and LTC transfer was used. Early mortality associated with severity of illness diminished with time. Age was a strong predictor of death and transfer: LTC transfer peaked at 6 to 9 days.

Controlled trials of different style stroke units - should all get good result? Foley, N., K. Salter, et al. (2007). "Specialized stroke services: a meta-analysis comparing three models of care." Cerebrovasc Dis 23(2-3): 194-202.
Meta analysis of three styles of stroke units poses more questions than it answers. Maybe it just shows the strength of self-fulfilling prophecies. Five acute stroke units admitting patients up to 36 hours and staying for two weeks; four combining acute and rehabilitation and five post-acute rehabilitation units were all associated with significant reductions in mortality and dependency compared with their control group. Not surprisingly, post-acute units had significant reductions in mortality. Clearly the jury is still out. Pay your money and take your choice.

Transferred patients cost more: Golestanian, E., J. E. Scruggs, et al. (2007). "Effect of interhospital transfer on resource utilization and outcomes at a tertiary care referral center." Crit Care Med 35(6): 1470-6.
The observational cohort study of 4569 consecutive admissions to the intensive care unit in a large academic hospital showed transferred patients were sicker and had higher mortality and longer length of stay Stratified by disease severity and hospital mortality there was no difference between admitted and transferred patients in either ICU or hospital mortality. Risk stratification revealed that higher costs $9,600 (95% c.i. $6000-$13,400) was entirely confined to the longer stay of low risk transferred patients.

Modellers Beware: Recalibration of isk assessment scores in ICU: Higgins, T. L. (2007). "Quantifying risk and benchmarking performance in the adult intensive care unit." J Intensive Care Med 22(3): 141-56.
Risk assessment measures in ICU - APACHE (Acute Physiology And Chronic Health Evaluation); MPM (Mortality Probability Model); and SAPS (Simplified Acute Physiology Score) have recently been recalibrated to reflect contemporary results.

Aims of HSCM 2008, Portrush, 18 - 20 March 2008

* Widening international understanding of the potential benefits of modelling;
* Highlighting instances where theory and practice meet;
* Encouraging close working relationships modellers and practitioners; and
* Increasing understanding of the different computational and data analytical methods used to measure and model health and social care services.

We are indebted to IMS MAXIMS plc's sponsorship for enabling the website version to be developed. IMS is a significant supplier to NHS and has an ongoing interest in enhancing the scope of IT support in the NHS, especially in the areas of clinical knowledge and decision support. Developers of systems looking for market opportunities are invited to contact IMS at their UK office, or by e-mail to Paul Cooper (pcooper at imsmaxims dot com). Accessing their web-site http://www.imsmaxims.com will give a feel for the scope of their work.

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