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.

Decision making in childhood asthma exacerbation – a clinical judgement analysis

Background: Clinical decisions which impact directly on patient safety and quality of care are made during acute asthma attacks by individual doctors on the basis of their knowledge and experience. These include administration of systemic corticosteroids (CS), oral antibiotics, and admission to hospital. Clinical judgement analysis provides a methodology for comparing decisions between practitioners with different training and experience, and improving decision making. Methods: Stepwise linear regression was used to select clinical cues based on visual analogue scale assessments of the propensity of 62 clinicians to prescribe a short course of oral CS (decision 1), a course of antibiotics (decision 2), and/or admit to hospital (decision 3) for 60 â??paperâ?? patients. Results:When compared by specialty, paediatriciansâ?? models for decision 1 were more likely to include as a cue level of alertness (54% v. 16%); for decision 2 presence of crepitations (49% v. 16%), and less likely to include inhaled CS (8% v. 40%), respiratory rate (0% v. 24%), and air entry (70% v. 100%). When compared to other grades, the models derived for decision 3 by consultants/general practitioners were more likely to include wheeze severity as a cue (39% v. 6%). Conclusions: Clinicians differed in their use of individual cues and the number included in their models. Patient safety and quality of care will benefit from clarification of decision making strategies as general learning points during medical training, in the development of guidelines and care pathways, and by clinicians developing self-awareness of their own preferences.

Implementing a resuscitation policy for patients at the end of life in an acute hospital setting: qualitative study

Objective : To explore attitudes and experiences of doctors and nurses regarding cardiopulmonary resuscitation for patients with end stage illness in an acute hospital. Design : Qualitative study; thematic analysis of two audio-taped focus groups and four semi-structured interviews. Setting : Acute district hospital, Northern Ireland. Participants : Seven nurses and nine doctors; varying nationality, gender and years of professional experience; involved in cardiopulmonary resuscitation decision-making. Results : Participants reported different interpretations of resuscitation policy and of what do not attempt to resuscitate (DNAR) decisions meant in relation to practical care for patients. This confusion in translating policy into practice contributed to communication difficulties in initiating, documenting and implementing cardiopulmonary resuscitation decisions. Participants were aware of how clinical conditions could change and reported uncertainty in determining end stage illness; they expressed fears of potential consequences of DNAR decisions for patients' care. The more disease-centred approach of doctors to patients' management, compared to nurses' more patient-centred approach, contributed to inter-professional conflict within teams. Doctors identified training needs in applying resuscitation policy and ethical principles in `real life' and nurses identified a need for ongoing professional support, which was perceived as being less available to junior doctors. Personal relationships between staff and patients, cultural reluctance to address sensitive issues and local community expectations of relatives being involved in decisions added to policy implementation difficulties. Conclusions : The findings indicate a need for ongoing staff support and training in applying resuscitation policy to decisions for patients with end stage illness in an acute hospital. They support suggestions that reviews of local resuscitation policy and of national guidelines should be undertaken with openness and honesty regarding the goals, opportunities and difficulties involved in trying to deliver good end of life care in local settings. Palliative Medicine 2007; 21 : 305—312 Key Words: do not attempt resuscitation (DNAR) • end stage illness • inter-professional • policy • resuscitation decisions