Computerized advice on drug dosage to improve prescribing practice.

BACKGROUND: Maintaining therapeutic concentrations of drugs with a narrow therapeutic window is a complex task. Several computer systems have been designed to help doctors determine optimum drug dosage. Significant improvements in health care could be achieved if computer advice improved health outcomes and could be implemented in routine practice in a cost effective fashion. This is an updated version of an earlier Cochrane systematic review, by Walton et al, published in 2001. OBJECTIVES: To assess whether computerised advice on drug dosage has beneficial effects on the process or outcome of health care. SEARCH STRATEGY: We searched the Cochrane Effective Practice and Organisation of Care Group specialized register (June 1996 to December 2006), MEDLINE (1966 to December 2006), EMBASE (1980 to December 2006), hand searched the journal Therapeutic Drug Monitoring (1979 to March 2007) and the Journal of the American Medical Informatics Association (1996 to March 2007) as well as reference lists from primary articles. SELECTION CRITERIA: Randomized controlled trials, controlled trials, controlled before and after studies and interrupted time series analyses of computerized advice on drug dosage were included. The participants were health professionals responsible for patient care. The outcomes were: any objectively measured change in the behaviour of the health care provider (such as changes in the dose of drug used); any change in the health of patients resulting from computerized advice (such as adverse reactions to drugs). DATA COLLECTION AND ANALYSIS: Two reviewers independently extracted data and assessed study quality. MAIN RESULTS: Twenty-six comparisons (23 articles) were included (as compared to fifteen comparisons in the original review) including a wide range of drugs in inpatient and outpatient settings. Interventions usually targeted doctors although some studies attempted to influence prescriptions by pharmacists and nurses. Although all studies used reliable outcome measures, their quality was generally low. Computerized advice for drug dosage gave significant benefits by:1.increasing the initial dose (standardised mean difference 1.12, 95% CI 0.33 to 1.92)2.increasing serum concentrations (standradised mean difference 1.12, 95% CI 0.43 to 1.82)3.reducing the time to therapeutic stabilisation (standardised mean difference -0.55, 95%CI -1.03 to -0.08)4.reducing the risk of toxic drug level (rate ratio 0.45, 95% CI 0.30 to 0.70)5.reducing the length of hospital stay (standardised mean difference -0.35, 95% CI -0.52 to -0.17). AUTHORS' CONCLUSIONS: This review suggests that computerized advice for drug dosage has some benefits: it increased the initial dose of drug, increased serum drug concentrations and led to a more rapid therapeutic control. It also reduced the risk of toxic drug levels and the length of time spent in the hospital. However, it had no effect on adverse reactions. In addition, there was no evidence to suggest that some decision support technical features (such as its integration into a computer physician order entry system) or aspects of organization of care (such as the setting) could optimise the effect of computerised advice.

Governor’s Office of Drug Control Policy Agency Performance Reporting, 2007

The Agency Performance Report for the Governor’s Office of Drug Control Policy is published in accordance with the Accountable Government Act. The information provided within this report is to aid in decision-making and to illustrate accountability to stakeholders and citizens. The report is indicative of the agency’s progress in meeting performance targets and achieving goals consistent with the enterprise strategic plan, the agency strategic plan and agency performance plan.

An integrative review of drug utilization by the elderly in primary health care

ABSTRACT OBJECTIVE To identify knowledge produced about drug utilization by the elderly in the primary health care context from 2006 to 2014. METHOD An integrative review of the PubMed, LILACS, BDENF, and SCOPUS databases, including qualitative research papers in Portuguese, English, and Spanish. It excluded papers with insufficient information regarding the methodological description. RESULTS Search found 633 papers that, after being subjected to the inclusion and exclusion criteria, made up a corpusof 76 publications, mostly in English and produced in the United States, England, and Brazil. Results were pooled in eight thematic categories showing the current trend of drug use in the elderly, notably the use of psychotropics, polypharmacy, the prevention of adverse events, and adoption of technologies to facilitate drug management by the elderly. Studies point out the risks posed to the elderly as a consequence of changes in metabolism and simultaneous use of several drugs. CONCLUSION There is strong concern about improving communications between professionals and the elderly in order to promote an exchange of information about therapy, and in this way prevent major health complications in this population.

Audit report of the Governor's Office of Drug Control Policy for the year ended June 30, 2006

Audit report of the Governor's Office of Drug Control Policy for the year ended June 30, 2006

Predictability of drug expenditures: An application using morbidity data

The growth of pharmaceutical expenditure and its prediction is a major concern for policy makers and health care managers. This paper explores different predictive models to estimate future drug expenses, using demographic and morbidity individual information from an integrated healthcare delivery organization in Catalonia for years 2002 and 2003. The morbidity information consists of codified health encounters grouped through the Clinical Risk Groups (CRGs). We estimate pharmaceutical costs using several model specifications, and CRGs as risk adjusters, providing an alternative way of obtaining high predictive power comparable to other estimations of drug expenditures in the literature. These results have clear implications for the use of risk adjustment and CRGs in setting the premiums for pharmaceutical benefits.