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This paper aims to explore lot quality assurance sampling (LQAS) applicability and usefulness in the evaluation of quality indicators in a hospital emergency department (ED) and to determine the degree of compliance with quality standards according to this sampling method.

Descriptive observational research in the Hospital General Universitario Gregorio Marañón (HGUGM) emergency department (ED). Patients older than 15 years, diagnosed with dyspnoea, chest pain, urinary tract colic or bronchial asthma attending the HGUGM ED from December 2005 to May 2006, and patients admitted during 2005 with exacerbation of chronic obstructive pulmonary disease or acute meningitis were included in the study. Sample sizes were calculated using LQAS. Different quality indicators, one for each process, were selected. The upper (acceptable quality level (AQL)) and lower thresholds (rejectable quality level (RQL)) were established considering risk α=5 per cent and β=20 per cent, and the minimum number of observations required was calculated.

It was impossible to reach the necessary sample size for bronchial asthma and urinary tract colic patients. For chest pain, acute exacerbation of chronic obstructive pulmonary disease, and acute meningitis, quality problems were detected. The lot was accepted only for the dyspnoea indicator.

The usefulness of LQAS to detect quality problems in the management of health processes in one hospital's ED. The LQAS could complement traditional sampling methods.

Healthcare risk epidemiology identifies medication error as the commonest cause of adverse effects on patients. Medication error can occur at any phase of the complex medication process so prevalence rates need to be estimated at each drug treatment phase: prescription, transcription and administration along with their clinical repercussions. This paper aims to investigate this issue.

Medication errors were recorded on an ad hoc sheet and staff were observed handling medications. Recorded errors were later classified and their clinical repercussions determined by experts.

In total 757 inpatients and 5,466 drug prescriptions were studied. The prescription error rate was 4.79 percent (95 percent CI 4.21‐5.36). The most frequent error in this phase was failing to observe international prescribing standards. The highest error rate was found in transcription (14.61 percent, 95 percent CI 13.67‐15.54). Almost 1,900 dose administrations were observed. There was a 9.32 percent error rate (95 percent CI 7.98‐10.67). The commonest error in this phase was omission. Most were transcription errors, which were detected before harm was done.

The dispensation phase is absent.

Errors can be reduced if they are understood. Education and training based on the study's findings can reduce medication errors.

The paper highlights ways to reduce errors in the medication process.