Multifactorial influences on and deviations from medication administration safety and quality in the acute medical/surgical context

Background and Aims: Although numerous factors influence medication administration, our understanding of the interplay of these factors on medication quality and safety is limited. The aim of this study was to explore the multifactorial influences on medication quality and safety in the context of a single checking policy for medication administration in acute care.

Approach: An exploratory/descriptive study using non-participant observation and follow-up interview was used to identify factors influencing medication quality and safety in medication administration episodes (n = 30). Observations focused on nurses’ interactions with patients during medication administration, and the characteristics of the environment in which these took place. Confirmation of observed data occurred on completion of the observation period during short semi-structured interviews with participant nurses.

Findings: Findings showed nurses developed therapeutic relationships with patients in terms of assessing patients before administering medications and educating patients about drugs during medication administration. Nurses experienced more frequent distractions when medications were stored and prepared in a communal drug room according to ward design. Nurses deviated from best-practice guidelines during medication administration.

Implications: Nurses’ abilities and readiness to develop therapeutic relationships with patients increased medication quality and safety, thereby protecting patients from potential adverse events. Deviations from best-practice medication administration had the potential to decrease medication safety. System factors such as ward design determining medication storage areas can be readily addressed to minimise potential error.

Conclusions: Nurses displayed behaviours that increased medication administration quality and safety; however, violations of practice standards were observed. These findings will inform future intervention studies to improve medication quality and safety.

There are plenty of medical problems, but only one real crisis

Fixing the disgraceful state of indigenous health conditions would benefit us all in the long-term, writes Jim Hyde.

A new re-ranking method using enhanced pseudo-relevance feedback for content-based medical image retrieval

We propose a novel re-ranking method for content-based medical image retrieval based on the idea of pseudo-relevance feedback (PRF). Since the highest ranked images in original retrieval results are not always relevant, a naive PRF based re-ranking approach is not capable of producing a satisfactory result. We employ a two-step approach to address this issue. In step 1, a Pearson's correlation coefficient based similarity update method is used to re-rank the high ranked images. In step 2, after estimating a relevance probability for each of the highest ranked images, a fuzzy SVM ensemble based approach is adopted to re-rank the images. The experiments demonstrate that the proposed method outperforms two other re-ranking methods.

Illness burden and medical comorbidity in the systematic treatment enhancement program for bipolar disorder

Objective:  Coexisting chronic medical conditions are common in bipolar disorder. Here, we report the prevalence and correlates of medical comorbidity in patients enrolled in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). We were particularly interested in associations between variables reflecting illness chronicity and burden with comorbid medical conditions.

Method:  We used intake data from the open-label component of the STEP-BD. History of medical comorbidity was obtained from the affective disorders evaluation, and its presence was the outcome of interest. The sample size in analyses varied from 3399 to 3534. We used multiple Poisson regression to obtain prevalence ratios.

Results:  The prevalence of any medical comorbidity in the sample was 58.8%. In addition to demographic variable, several clinical characteristics were associated with the frequency of medical comorbidity. Having more than 10 previous mood episodes, childhood onset, smoking, lifetime comorbidity with anxiety, and substance use disorders were independently associated with having a medical comorbidity in the final multivariate model.

Conclusion:  The results presented here reveal strong associations between variables related to illness chronicity and medical burden in bipolar disorder. This lends further support to recent multidimensional models incorporating medical morbidity as a core feature of bipolar disorder.