What is a reasonable time from decision to delivery by Caesarean section? Evidence from 533 deliveries.

Objective To determine how long it takes from the decision to achieve delivery by non-elective caesarean section (DDI), the influence on this interval, and the impact on neonatal condition at birth. Design Twelve months prospective data collection on all non-elective caesarean sections. Methods Prospective collection of data relating to all caesarean sections in 1996 in a major teaching hospital obstetric unit was conducted, without the knowledge of the other clinicians providing clinical care. Details of the indication for section, the day and time of the decision and the interval till delivery were recorded as well as the seniority of the surgeon, and condition of the baby at birth. Results The mean time from decision-to-delivery for 100 emergency intrapartum caesarean sections was 42.9 minutes for fetal distress and 71.1 minutes for 230 without fetal distress (P<0.0001). For 22 'crash' sections the mean time from decision-to-delivery was 27.4 minutes; for 13 urgent antepartum deliveries for fetal reasons it was 124.7 minutes and for 21 with maternal reasons it was 97.4 minutes. The seniority of the surgeon managing the patient did not appear to influence the interval, nor did the time of day or day of the week when the delivery occurred. Intrapartum sections were quicker the more advanced the labour, and general anaesthesia was associated with shorter intervals than regional anaesthesia for emergency caesarean section for fetal distress (P<0.001). Babies born within one hour of the decision tended to be more acidaemic than those born later, irrespective of the indication for delivery. Babies tended to be in better condition when a time from decision-to-delivery was not recorded than those for whom the information had been recorded. Conclusion Fewer than 40% intrapartum deliveries by caesarean section for fetal distress were achieved within 30 minutes of the decision, despite that being the unit standard. There was, however, no evidence to indicate that overall an interval up to 120 minutes was detrimental to the neonate unless the delivery was a 'crash' caesarean section. These data thus do not provide evidence to sustain the recommendation of a standard of 30 minutes for intrapartum delivery by caesarean section.

Modelling the flow of congestive heart failure patients through a hospital system

The number of hospital admissions in England due to heart failure is projected to increase by over 50% during the next 25 years. This will incur greater pressures on hospital managers to allocate resources in an effective manner. A reliable indicator for measuring the quantity of resources consumed by hospital patients is their length of stay (LOS) in care. This paper proposes modelling the length of time heart failure patients spend in hospital using a special type of Markov model, where the flow of patients through hospital can be thought of as consisting of three stages of care—short-, medium- and longer-term care. If it is assumed that new admissions into the ward are replacements for discharges, such a model may be used to investigate the case-mix of patients in hospital and the expected patient turnover during some specified period of time. An example is illustrated by considering hospital admissions to a Belfast hospital in Northern Ireland, between 2000 and 2004.

Risk adjustment for hospital use using social security data: cross sectional small area analysis

Objectives: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. Design: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. Setting: Northern Ireland. Main outcome measure: Intensity of use of inpatient services. Results: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. Conclusions: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula.