Effect of population ageing on emergency department speed and efficiency: a historical perspective from a district general hospital in the UK.

OBJECTIVE: To examine changes in the rate of seeing patients between 1990 and 2004 and to see whether performance might be related to patient age, using data held on the patient administration system. METHOD: Data collected in 1990 were compared with those collected in 2004. Age related data were examined for the following parameters: the number of patients arriving by ambulance; the time taken to process the attendance; the number of investigations; the number of emergency admissions; and the length of inpatient stay. RESULTS: Emergency department (ED) performance has fallen markedly since 1990. Between 1990 and 2004, there was a 54% increase in total patients with a disproportionate 198% increase in patients aged more than 70 years, including a 671% increase in those aged more than 90 years. The time taken to manage patients increased with age. In 2004, there was a marked rise in investigation rates, and the probability of having investigations increased with age. In 2004, older patients (aged more than 70 years) were 4.9 times more likely to require admission to hospital than younger patients (aged 30 years or less). Their average length of stay was 6.9 times longer. Younger patients were 3.3 times more numerous than older patients but older patients occupied 9.8 times more emergency bed days. CONCLUSIONS: Pressure on emergency care is associated with a disproportionate increase in the number of elderly patients and with an increased tendency to investigate them. Population ageing is of central importance in planning health services.

A computer program for generating New Deal compliant SHO rosters.

In the UK, the introduction of the New Deal on junior doctors' hours has placed constraints on permissible senior house officer (SHO) rosters. This makes it difficult to construct a rota that satisfies SHOs' annual leave and study leave requirements, yet remains compliant with the New Deal. A solution is the use of a computer. A computer program is described that generates compliant, full shift, SHO rosters in accordance with annual leave requests. This has been in routine use at the Oxford Radcliffe Hospitals Trust emergency department for the past 18 months. The program lends itself to, but is not specific to A&E applications; it can be used to generate compliant full shift rosters for other specialties. A copy of the program can be downloaded free of charge from a web site.

A mathematical specification of the New Deal on junior doctors' hours.

OBJECTIVES: Our objective is to make the New Deal on junior doctors' hours sufficiently precise that the definitions may be used as a basis for computer software that checks the compliance of rotas or that automatically generates compliant rotas. METHODS: We formalize the clauses of the New Deal, as relevant to 'full shifts', using the Z specification language. RESULTS: The mathematical definitions are simple and concise. CONCLUSIONS: Mathematical specification is a useful way to express constraints on rotas unambiguously.

The identification of peaks in physiological signals.

The identification of peaks is fundamental in the processing of physiological signals. For example, it is common to the analysis of electrocardiograms, electroencephalograms, sympathetic neuronal activity, pulse oximetry, respiratory movement, hormone pulse secretion, and even chromatography. Often it is necessary to detect peaks in real time, but the task is frequently complicated by baseline wander and other interference. Current approaches to the problem tend to be complicated, specific to a particular domain, and reliant on several tunable parameters. There is a need for a simple and general mathematical formalization of peaks and troughs that has easily examinable properties and is readily implementable as an efficient algorithm. In this paper we present such a mathematical model together with an algorithm for the detection of peaks and troughs. We illustrate the generality of the method with some actual physiological data.

The formal specification of an electrocardiogram compressor.

Remote telemonitoring of physiological parameters is being used increasingly both for medical research and for clinical management. However, the technique entails the collection of large volumes of information for transmission and storage which necessitates efficient means of data compression. This paper presents a simple mathematical model of the lossy compression of physiological signals. The model is developed in a top-down style making design decisions progressively. First a general model of lossy compression is developed and some lemmas presented. Then the model is refined to take advantage of inherent cyclicity in many types of physiological signal. Finally the model is specialized to the compression of electrocardiograms. An algorithm is described for implementing the model. The algorithm is a table-based method capable of achieving very low output bit rates (50 bps) with reasonable fidelity. This compares favourably with the results obtained by other workers and holds promise for further evaluation. The generality of the model should ultimately allow a coherent approach to the compression of the various types of physiological signal currently being recorded.

A survey of teaching and the use of clinical guidelines in accident and emergency departments.

OBJECTIVE: To investigate organised teaching in accident and emergency (A&E) departments in England and Wales. METHODS: A survey was carried out by postal questionnaire. Directed to senior house officers (SHOs), the questionnaire examined the nature and extent of departmental teaching, and measured the availability, suitability, and actual use made of guidelines. Of 231 questionnaires sent, 164 were returned (response rate 71%). RESULTS: The results show that most SHOs attended A&E induction courses at the beginning of their attachments, although the scope of these coursed varied widely. Most SHOs also received regular teaching, although the programmes were generally of less than 3 h in duration. The majority of respondents were well supported with written documentation in a variety of formats. However, a significant minority (29%) of SHOs requested more detailed clinical guidance, and these tended to be the respondents who received the most departmental teaching. CONCLUSIONS: More time could be allocated to structured teaching than at present, and greater use made of complementary educational methods such as practical skill teaching, case presentation, clinical audit, and involvement in journal clubs. More extensive departmental teaching should also be supported by making available more detailed and comprehensive clinical guidelines.

A computer-based flowcharting system for clinical protocols.

In medicine, scientific and technological developments for investigation and treatment are proceeding at an ever increasing rate. Protocols for patient management are becoming ever more complicated. Rational design and scientific evaluation of protocols requires precise documentation. We propose a notation based on a series of simple flowcharts which describe procedures in increasing detail. Each step in a flowchart is justified by a reasoned argument, possibly including reference to published articles. General correctness requirements of a protocol include, for example, conformity with known indications and contraindications for investigations and treatments. These correctness requirements can be specified declaratively in mathematical logic and justified by reasoned argument. This makes the correspondence between a protocol and its scientific foundation even more explicit. Flowcharts of this nature are more easily created and modified using a personal computer. Furthermore, use of the computer enables a protocol to be checked automatically against its specification for more rapid identification of errors during development and maintenance of the protocol. We present the structured design of our flowcharting system in the 'Z' specification language, and we examine the practicality of our approach by means of a case study; the management of infertility. Our flowcharting system may also have application outside medicine where it is necessary to describe formal protocols for complex procedures.

The relative accuracy of a variety of medical diagnostic programs.

Acute abdominal pain is one of the most widely studied applications of computer-aided diagnosis. The usual approach is to apply Bayes' theorem with the assumption of conditional independence ("independence Bayes"). We compared various approaches to designing diagnostic programs for abdominal pain of suspected gynaecological origin. The methods range from statistical to knowledge-based. All programs were evaluated using a database of 1,270 cases collected retrospectively. Our results suggest that in this application no significant improvement in accuracy can be made by taking interactions into account, either by statistical or by knowledge-based means; independence Bayes is near-optimal. As far as accuracy is concerned, there appears to be little point in pursuing knowledge-based approaches. However, the "nearest neighbours" method using a new metric appears to be at least as accurate as independence Bayes. We argue that the nearest neighbours method is more suitable than independence Bayes for clinical use because of greater accountability.

A probabilistic simulation model to assist the localization of nerve lesions.

I present a formal, mathematical specification of a probabilistic expert system to assist the localization of nerve lesions. The program is based on an anatomical model of the peripheral nervous system of the human upper limb. The simulation model defines a joint probability distribution over the states of nerves and clinical manifestations. A simple, general-purpose heuristic algorithm is used to approximate conditional probabilities of interest. It is shown how an upper bound on the expected approximation error can be measured experimentally; this upper bound is 0.05 for the system described here, although the bound can be made arbitrarily small by expending more computational effort. The expert system is compared with the nearest-neighbour statistical classification rule on two databases of 26 and 25 cases respectively. The expert system makes fewer errors, although the observed difference does not reach statistical significance. Possible future refinements to the model are explored, and the advantages of specifying expert systems formally are discussed.

Case-based explanation for medical diagnostic programs, with an example from gynaecology.

One of the most accountable methods of providing machine assistance in medical diagnosis is to retrieve and display similar previously diagnosed cases from a database. In practice, however, classifying cases according to the diagnoses of their nearest neighbours is often significantly less accurate than other statistical classifiers. In this paper the transparency of the nearest neighbours method is combined with the accuracy of another statistical method. This is achieved by using the other statistical method to define a measure of similarity between the presentations of two cases. The diagnosis of abdominal pain of suspected gynaecological origin is used as a case study to evaluate this method. Bayes' theorem, with the usual assumption of conditional independence, is used to define a metric on cases. This new metric was found to correspond as well as Hamming distance to the clinical notion of "similarity" between cases, while significantly increasing accuracy to that of the Bayes' method itself.

The design and construction of a medical simulation model.

This paper describes the design, construction and validation of a probabilistic simulation model of patients who present with abdominal pain. The model incorporates text-book medical knowledge, clinical judgment, and statistics collected from real cases. The knowledge representation combines techniques of Bayesian network modelling with ideas of logistic discrimination. The model is shown to generate convincing, realistic cases; large numbers of artificial cases with no missing observations can be generated quickly. This should make the model a useful tool for investigating factors which limit achievable computer accuracy in the diagnosis of abdominal pain.

A probabilistic rule-based expert system.

This paper explores a medical expert system combining techniques of Bayesian network modelling with ideas of weighted inference rules. The weights of the individual rules can be estimated objectively from a training set of actual cases; and they can be used in a Monte Carlo stimulation to estimate objectively conditional probabilities of diagnosis given particular combinations of symptoms. The paper describes and evaluates a medical expert system built according to this design. The diagnostic accuracy of the program was found to be similar to that obtained through the usual application of Bayes theorem with the assumption of conditional independence of symptoms given disease, even though the Bayesian classifier has more than 70 times as many numerical parameters. The method may be promising in cases where small training sets do not permit accurate estimation of large numbers of parameters.

Limits to diagnostic accuracy.

This paper explores the limits to computer-aided medical diagnosis. A specific application area (the diagnosis of abdominal pain of suspected gynaecological origin) is chosen, and the factors limiting the accuracy of computer programs are investigated by means of a simulation model which has been shown previously to generate realistic cases. The model is used to generate arbitrarily large training and test sets. The results suggest that, while statistical dependencies exist amongst symptoms and signs, there is little to be gained by taking interactions into account. However, failure to record all possible observations does limit diagnostic accuracy significantly. The results suggest that near-optimal diagnostic accuracy (75-80%) can be obtained with a training set size of 10(5) cases simply by applying Bayes' theorem with the usual assumption of conditional independence.

An algorithm for approximating conditional probabilities.

When diagnostic programs are constructed within a probabilistic framework, it is often the case that computation of joint probabilities of exhaustive combinations of events is easy, but computation of the kind of conditional probabilities the user wishes to know, is hard. This paper describes a simple algorithm for computing the required values, and then suggests several heuristic optimizations that may enable suitable approximations to be obtained in a feasible time when the task is otherwise intractable. An account is given of a specific application of the method in the construction of a medical diagnostic program, which is described in more detail elsewhere.