Information and Decision Support Systems in the National Health Service

Abstract

The goal of improving managerial effectiveness within the National Health Service has long been recognised as being inextricably linked to the improvement of information systems. However, recommendations concerning the latter have primarily concentrated on issues of capture and content of standardised information and not on the need for flexibility in the mechanisms by which this information is delivered to management. Such mechanisms must integrate rather than conflict with the diversity of the decision-making environment if information is to be used and therefore translate into improvements in managerial effectiveness. Thus there are several reasons why any information system within an organisation such as the Health Service needs to be a dynamic and responsive tool. Integration of data access with analytic power should allow requisite information to be derived and adjusted iteratively by managerial demand, rather than be standardised and pre-defined.This paper argues that more encouragement should be given to develop a variety of such 'Decision Support Systems' within the Service. Although the establishment of better base-line information throughout the organisation will extend the limits of what can be achieved with such systems, their justification is not necessarily contingent on developments in this area. It is suggested that local initiatives are possible and desirable using existing information sources. An example of one such system, developed to assist District management in planning and monitoring hospital inpatient and outpatient services, is discussed.

Study on the Accuracy of Official Recording of Nosological Codes in an Italian Regional Hospital Registry

“…Furthermore, the quasi-independence model is rejected (likelihood ratio test = 41.0 with 5 d. f., P = 0.00). The comparison of observed and expected frequencies (in italics in Table 2) shows that this rejection is mainly due to four cells: (1,2), (1,4), (3,1), (3,4). Table 5 Fitting of log it-models for disagreement proportions in Table 4 Model More can be said about the source of inaccuracy by considering the results of the explanatory analysis described in the subsection Analysis.…”

“…Hospital discharge data are important for observational studies in epidemiology and for health service planning and evaluation [2][3][4][5][6].…”