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PubMed · 10125315

Death trap.

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J Hacking. 1993-03-11. Death trap.. https://pubmed.ncbi.nlm.nih.gov/10125315/

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[Factors affecting drug expenditure in the primary care centre in a health area].

OBJECTIVE: To identify the factors affecting drug expenditure.Design. Cross-sectional study.Setting. Madrid Primary Care area. PARTICIPANTS: 21 health centres. MEASUREMENTS: Association of the drug expenditure per inhabitant of each health centre during 1999 with the characteristics of its staff and operation of the centre. MAIN RESULTS: Expenditure on drugs per inhabitant, 14360 plus minus 3040 pesetas (86.31 plus minus 18.27; general practitioners, 19.62 plus minus 23.8%; doctors working as locums, 40.48 plus minus 20.72%; women doctors, 59.76 plus minus 13.36%; family doctors, 38.57 plus minus 21.35%; team nurses, 86.6 plus minus 18.27%; population over 65, 18.03 plus minus 7.73%; patients per day attended by each general practitioner, 32.82 plus minus 3.81; number of sessions per year on prescription profiles, 5 plus minus 3.91; prescription avoidable because of health card: 3106 plus minus 808 pesetas (18.67 plus minus 4.86 ); compliance with service offer, 1.7 plus minus 3.78. Drug expenditure per inhabitant dropped when sessions on prescription profiles (p = 0.013), the percentage of women doctors (p = 0.067) and the percentage of family doctors (p = 0.035) increased; and it dropped too when the over-65 population (p = 0.099) and the amount of prescription avoidable through the card (p = 0.034) dropped. In the multivariate analysis, the sessions on prescription profiles (ss = -843), the percentage of nurses in the reformed model (ss = -155), the percentage of family doctors (ss = -142) and the percentage of doctors from the traditional model (ss = -121) explain 71.2% of the variability in drug expenditure per inhabitant (F = 6.909; p = 0.002). CONCLUSIONS: The sessions to discuss prescription profiles, the presence of nurses from the reform model, postgraduate medical training and the employment of doctors under the traditional model are the factors that our study finds are linked to lower drug expenditure per inhabitant.

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Management of tuberculosis in a British inner-city population.

BACKGROUND: The aim of the study was to investigate the management of patients with tuberculosis (TB) in terms of their utilization of health service resources. METHODS: An analysis of patient records was carried out in an NHS Trust in East London, United Kingdom, serving a socioeconomically deprived population. The subjects were all residents of Tower Hamlets treated for drug-sensitive TB in the in-patient and out-patient departments of the Trust in 1998. RESULTS: Of the 62 patients with TB studied, 38 (61 per cent) had an in-patient stay at some stage of their management. Twenty-six of these 38 were admitted acutely ill via the Accident and Emergency Department, 16 having self-presented and 10 after urgent referral by their general practitioner. Only four of the total 62 patients were admitted with previously diagnosed disease, and all four had significant complications necessitating admission. Eight patients were admitted electively for investigation, typically being brief admissions for surgical biopsy. Median in-patient stay was 14 days (range 1-144 days), and in six cases we identified potentially remediable delays in diagnosis and initiation of therapy. CONCLUSIONS: UK and US guidelines for TB imply out-patient management as the norm. Our study shows a very high rate of in-patient care, largely a consequence of the emergency admission of acutely ill, previously undiagnosed cases. There are public health implications in terms of spread of infection from individuals with advanced disease. The high utilization of expensive in-patient resources has significant implications for purchasers and providers of care for TB in socio-economically deprived areas. Further, the cost-effectiveness of public health interventions aimed at limiting the spread of TB should be assessed by reference to this true, high cost of managing TB, not a low cost based on false assumptions about rates of out-patient versus in-patient care.

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