Systems thinking, complexity and managerial decision-making: an analytical review.

One feature that characterizes the organization and delivery of health care is its inherent complexity. All too often, with so much information and so many activities involved, it is difficult for decision-makers to determine in an objective fashion an appropriate course of action. It would appear that a holistic rather than a reductionist approach would be advantageous. The aim of this paper is to review how formal systems thinking can aid decision-making in complex situations. Consideration is given as to how the use of a number of systems modelling methodologies can help in gaining an understanding of a complex decision situation. This in turn can enhance the possibility of a decision being made in a more rational, explicit and transparent fashion. The arguments and approaches are illustrated using examples taken from the public health arena.

A proposed semantic framework for diabetes education content management, customisation and delivery within the M2DM project.

M2DM (multi access services for telematic management of diabetes mellitus, ) is an EU-funded telemedicine project that aims at increasing the quality of diabetes care by improving communication between patients and caregivers. As part of this project, we have undertaken the initial work of describing the necessary requirements (framework) of an advanced educational component for M2DM in accordance with the latest Semantic Web concepts. This paper describes our proposed semantic framework for educational content management, customisation and delivery. A big internet challenge today is to find and push situation and user-specific quality knowledge to users based on their actual individual needs, circumstances and profiles at any given time. We believe that the semantic framework presented in this paper could be a good step towards meeting this challenge. Benefits for users, both developers and end users, of adopting such framework are also discussed. The ideas discussed in this paper could be easily adapted to other similar services besides M2DM and to different health topics besides diabetes mellitus.

User requirements and understanding of public health networks in England.

BACKGROUND: The movement of public health professionals from health authorities to primary care trusts has increased their isolation and dependence on public health networks for communication. METHODS: A cross sectional survey of 60 public health professionals working in England was performed to determine their understanding of the term "public health network" and to explore the functions that they would like these networks to perform. It also assessed their attitudes towards a national network and towards individual, local, and national web sites to support these networks. RESULTS: The most popular functions were the support of CPD/education, the identification of expertise and maximisation of scarce resources, information sharing, and efficient information/knowledge management. The local and national networks and their web sites should provide information on current projects of the network and searches to identify people, expertise, and reports. CONCLUSION: Public health professionals have a similar but broader understanding of the term "public health network" than that of the government with greater emphasis on sharing of information. The network is more likely to be successful if its priorities are maximising scarce resources, identification of expertise, CPD/education, and knowledge management.

A dynamic problem to knowledge linking Semantic Web service based on clinical codes.

Many information needs arise during everyday clinical practice. Problem to knowledge linking aims to answer these needs by providing contextually appropriate medical knowledge in the right place and at the right time. Empirical evidence shows that well-informed physicians and patients are able to make better clinical decisions that positively affect healthcare outcomes. This paper reports on the design and development of a re-usable and flexible Semantic Web problem to knowledge linking service. The service makes use of metadata and clinical codes contextually to link disparate Electronic Patient Record clients to resources in an online medical knowledge service (HealthCyberMap). Clinical codes act as crisp knowledge hooks, providing a reliable common backbone language for communication between Electronic Patient Records and HealthCyberMap. Ideas to improve the service are also discussed. By minimizing irrelevant leads (noise) and reducing the time needed to find relevant information (the right contextually relevant knowledge is linked to real patient data in the Electronic Patient Record), the system is potentially beneficial. The actual success of the system will depend on the quality and granularity of metadata it uses and the topical coverage and quality of resources to which it points.

Health geomatics: an enabling suite of technologies in health and healthcare.

This Methodolical Review describes how health geomatics can improve our understanding of the important relationship between location and health, and thus assist us in Public Health tasks like disease prevention, and also in better healthcare service planning. The reader is first introduced to health geography and its two main divisions, disease ecology and healthcare delivery, followed by an overview of the basic concepts and principles of health geomatics. Topics covered include geographical information systems (GIS), GIS modeling, and GIS-related technologies (remote sensing and the global positioning system). We also present a number of real-life health geomatics applications and projects, with pointers to further studies and resources. Finally, we discuss the barriers facing the adoption of GIS technology in the health sector, including data availability/quality issues. The authors believe that we still need to combat many cultural and organizational barriers, including "spatial illiteracy" among healthcare workers, while making the tools cheaper and easier to learn and use, before health geomatics can become a mainstream technology in the health sector like today's spreadsheets and databases.

Decision support systems in diabetes: a systems perspective.

This paper examines, from a systems perspective, some of the major issues associated with the provision of computer-based decision support in the management of the diabetic patient. The importance of understanding the underlying dynamics is emphasised, as is the value of a systems approach to the specification, design and evaluation of decision support systems if they are to find clinical acceptance.

Preliminary experience of the DIAS computer model in providing insulin dose advice to patients with insulin dependent diabetes.

The Diabetes Advisory System (DIAS) is a model of human glucose metabolism which predicts hourly blood glucose concentrations and provides advice on insulin dose. Its ability to provide appropriate advice was assessed in 20 well-controlled IDDM patients (mean (SD) age 38 (11), duration 17 (9) years; HbA1 8.8 (0.9)%, reference range 5.4-7.6%). Patients recorded blood glucose measurements, insulin dose and food intake for 4 days. These data were used to generate insulin dose advice by both DIAS and a diabetes specialist nurse. Patients were then allocated to follow either DIAS or nurse advice for a further 4 days. There was no significant difference in mean recorded blood glucose values or frequency of reported hypoglycaemia between the DIAS and nurse groups either before or after insulin dose adjustment. The DIAS model, however, generated significantly lower insulin dose advice than the nurse (median (range)% change in insulin dose: DIAS group -13.3% (-25.0 to +11.6) versus nurse group 0% (-8.7 to +2.5), P < 0.05). We conclude that, in the patients studied, DIAS provided insulin dose advice which maintained good short term control of diabetes, despite significant reductions in dose in some cases.

Clinical decision support, systems methodology, and telemedicine: their role in the management of chronic disease.

In this paper, the design and evaluation of decision support systems, including those incorporating a telematic component, are considered. It is argued that effective design and evaluation are dependent upon the adoption of appropriate methodology set firmly within a systemic framework. Systems modeling is proposed as an approach to system design, with evaluation adopting an approach incorporating evaluability analysis and formative and summative evaluation, including the use of stakeholder matrix analysis. The relevance of such systemic methodology is demonstrated in the context of diabetes and end-stage renal disease as examples of the generic clinical problem of the management of chronic disease.

Clinical-HINTS: integrated intelligent ICU patient monitoring and information management system.

Clinical-HINTS (Health Intelligence System) is a horizontally integrated decision support system (DSS) designed to meet the requirements for intelligent real-time clinical information management in critical care medical environments and to lay the foundation for the development of the next generation of intelligent medical instrumentation. The system presented was developed to refine and complement the information yielded by clinical laboratory investigations, thereby benefiting the management of the intensive care unit (ICU) patient. More specifically, Clinical-HINTS was developed to provide computer-based assistance with the acquisition, organisation and display, storage and retrieval, communication and generation of real-time patient-specific clinical information in an ICU. Clinical-HINTS is an object-oriented system developed in C+2 to run under Microsoft Windows as an embryo intelligent agent. Current generic reasoning skills include perception and reactive cognition of patient status but exclude therapeutic action. The system monitors the patient by communicating with the available sources of data and uses generic reasoning skills to generate intelligent alarms, or HINTS, on various levels of interpretation of an observed dysfunction, even in the presence of complex disorders. The system's communication and information management capabilities are used to acquire physiological data, and to store them along with their interpretations and any interventions for the dynamic recognition of interrelated pathophysiological states or clinical events.

Acid-base chemistry of the blood--a general model.

This paper describes a general model of acid-base chemistry of the blood which can be used to simulate physiological perturbation of acid-base chemistry on addition or removal of any buffer acid or base. In particular, it is shown how this model can be used to estimate the concentrations of buffer acid or base. In particular, it is shown how this model can be used to estimate the concentrations of buffer acids and bases when blood is equilibrated to a new pCO2, when hydrogen ions H+ are added to the blood, or when two pools of blood with different concentrations of buffer acids and bases are mixed. The ability of the model to represent the addition or removal of any acid or base is a significant increase in functionality above the Siggaard-Andersen nomogram which is limited to simulating the effects of equilibrating the blood to a new pCO2. When used to represent the situation where blood is equilibrated at a new pCO2 the model enables calculation of the amount CO2 removed during equilibration, a further increase in functionality above the Siggaard-Andersen nomogram. In two experimental situations, equilibrating blood to a new pCO2 and addition of H+ ions, the model predictions are shown to be consistent with existing experimental data in the form of the Siggaard-Andersen nomogram.

UTOPIA: a consultation system for visit-by-visit diabetes management.

UTOPIA (UTilities for OPtimizing Insulin Adjustment) is a prototype computer system proposed to support home data analysis and therapy recommendations for the individual patient. The paper describes methods of analysis and their incorporation into an overall system design that matches the iterative practices at the physician-patient consultation from visit to visit. Four modules support home data display and comparison with clinical measurements; extraction of blood glucose trends and daily cycles using time series analysis, learning relationships between insulin adjustments and changes in time series patterns via a parametric, linear systems model; and advice generation by solving the linear equation for candidate insulin adjustments. Concepts and methods are placed in context, with a discussion of comparable and related research.

Effects of intravenous infusion of lipid-free apo A-I in humans.

Apolipoprotein (apo) A-I is the principal protein component of the plasma high density lipoproteins (HDLs). Tissue culture studies have suggested that lipid-free apo A-I may, by recruiting phospholipids (PLs) and unesterified cholesterol from cell membranes, initiate reverse cholesterol transport and provide a nidus for the formation, via lipid-poor, pre-beta-migrating HDLs, of spheroidal alpha-migrating HDLs. Apo A-I has also been shown to inhibit hepatic lipase (HL) and lipoprotein lipase (LPL) in vitro. To further study its functions and fate in vivo, we gave lipid-free apo A-I intravenously on a total of 32 occasions to six men with low HDL cholesterol (30 to 38 mg/dL) by bolus injection (25 mg/kg) and/or by infusion over 5 hours (1.25, 2.5, 5.0, and 10.0 mg.kg-1.h-1). The procedure was well tolerated: there were no clinical, biochemical, or hematologic changes, and there was no evidence of allergic, immunologic, or acute-phase responses. The 5-hour infusions increased plasma total apo A-I concentration in a dose-related manner by 10 to 50 mg/dL after which it decreased, with a half-life of 15 to 54 hours. Coinfusion of Intralipid reduced the clearance rate. The apparent volume of distribution exceeded the known extracellular space in humans, suggesting extensive first-pass clearance by one or more organs. No apo A-I appeared in the urine. Increases in apo A-I mass were confined to the pre-beta region on crossed immunoelectrophoresis of plasma and to HDL-size particles on size exclusion chromatography. Increases were recorded in HDL PL, but not in HDL unesterified or esterified cholesterol. Increases also occurred in LDL PL and in very low density lipoprotein cholesterol, triglycerides, and PL but not in plasma total apo B concentration. These results can all be explained by combined inhibition of HL and LPL activities. Owing to the effects that this would have had on HDL metabolism, no conclusions can be drawn from these data about the role of lipid-free apo A-I in the removal of PL and cholesterol from peripheral tissues in humans. The kinetic data suggest that the fractional catabolic rate of lipid-free apo A-I exceeds that of spheroidal HDLs and is reduced in the presence of surplus PL.

Combining rule-based reasoning and mathematical modelling in diabetes care.

A prototype computer system utilising a model of carbohydrate metabolism linked to an expert system is described. The prototype which integrates quantitative and qualitative computational methodologies can be used to predict blood glucose profiles and adjust insulin doses in insulin-dependent (type I) diabetic subjects. A feedback loop insulin-dosage optimisation procedure which allows quantitative advice to be generated is also described. Possible clinical applications for the system, which is intended for educational use and clinically as a research tool to try and attain normoglycaemia, are discussed.

Methodological issues in validating decision-support systems for insulin dosage adjustment.

Safety and reliability of advice from new computer systems should be confirmed before embarking on prospective hospital trials. This process of preliminary testing is termed 'validation'. Though it forms a fundamental stage in system development, few standards exist for choosing and implementing tests. In the present paper, a validation methodology is developed in the domain of diabetes and intended for general use in chronic health management. It is based on a peer review protocol and incorporates empirical measures indicating: applicability of results to the real environment; variation among doctors; comparisons between doctors' and computer advice; and relative merits of different computer algorithms.

Modelling the dynamic ventilatory response to hypoxia in normal subjects.

We have developed a mathematical model to describe the dynamic ventilatory response to hypoxia. The ventilatory response to both transient (two to three breaths nitrogen) and 3 min step change hypoxic stimuli were measured in ten normal subjects during moderate exercise (oxygen consumption 0.96 +/- 0.08 1 min-1). The simplest model relating ventilation to ear oxygen saturation which adequately described the responses in all subjects consisted of two linear differential equations in parallel; both using the fall in oxygen saturation as input, and with the outputs summed to give the rise in ventilation. One equation had a fast time constant (< 3 sec), and the other a slow time constant. Non-linear terms included were (i) a "saturating" effect, similar to that described by the Michaelis-Menten equation, reducing the gain of the equation with the slow time constant as oxygen saturation falls, and (ii) "inhibition" or "potentiation" of the gain of the equation with a slow time constant as the output of the fast time constant equation increased. Repeated measurements in four subjects showed intra- and inter-subject variability for all parameters, with significant between-subject variability for the gain of the fast time constant equation. The final model structure is similar to that describing the peripheral chemoreceptor-mediated hypoxic ventilatory response in anaesthetized cats.

A probabilistic approach to glucose prediction and insulin dose adjustment: description of metabolic model and pilot evaluation study.

A model of carbohydrate metabolism has been implemented as a causal probabilistic network, allowing explicit representation of the uncertainties involved in the prediction of 24-h blood glucose profiles in insulin-dependent diabetic subjects. The parameters of the model were based on experimental data from the literature describing insulin and carbohydrate absorption, renal loss of glucose, insulin-independent glucose utilisation and insulin-dependent glucose utilisation and production. The model can be adapted to the observed glucose metabolism in the individual patient and can be used to generate predicted 24-h blood glucose profiles. A penalty is assigned to each level of blood glucose, to indicate that high and low blood glucose levels are undesirable. The system can be asked to find the insulin doses that result in the most desirable 24-h blood glucose profile. In a series of 12 patients, the system predicted blood glucose with a mean error of 3.3 mmol/l. The insulin doses suggested by the system seemed reasonable and in several cases seemed more appropriate than the doses actually administered to the patients.

Time series analysis and control of blood glucose levels in diabetic patients.

This paper describes features of a computer-based decision support system which is being developed to assist in the management of insulin-dependent diabetic patients. The clinical context is the provision of advice on the adjustment of the basic insulin regimen such as occurs at regular visits to the clinician. The integrated system combines data processing and interpretation, generation of qualitative advice and testing the implications of that advice using a glucose/insulin dynamic simulator. The two major features described in this paper are time series analysis of blood glucose data, and their interpretation in relation to the provision of advice for controlling the patient's blood glucose level. It is demonstrated that two approaches may be adopted in such time series analysis: an intuitive approach, manipulating symbolic representations of the data, and formal time series methods which decompose the series into clinically related components.