Reducing failures in daily medical practice: Healthcare failure mode and effect analysis combined with computer simulation.

This study proposes a risk analysis approach for complex healthcare processes that combines qualitative and quantitative methods to improve patient safety. We combine Healthcare Failure Mode and Effect Analysis with Computer Simulation (HFMEA-CS), to overcome widely recognised HFMEA drawbacks regarding the reproducibility and validity of the outcomes due to human interpretation, and show the application of this methodology in a complex healthcare setting. HFMEA-CS is applied to analyse drug adherence performance in the surgical admission to discharge process of pheochromocytoma patients. The multidisciplinary team identified and scored the failure modes, and the simulation model supported in prioritisation of failure modes, uncovered dependencies between failure modes, and predicted the impact of measures on system behaviour. The results show that drug adherence, defined as the percentage of required drugs received at the right time, can be significantly improved with 12%, to reach a drug adherence of 99%. We conclude that HFMEA-CS is both a viable and effective risk analysis approach, combining strengths of expert opinion and quantitative analysis, for analysing human-system interactions in socio-technical systems. Practitioner summary: We propose combining Healthcare Failure Mode and Effects Analysis with Computer Simulation (HFMEA-CS) for prospective risk analysis of complex and potentially harmful processes, to prevent critical incidents from occurring. HFMEA-CS combines expert opinions with quantitative analyses, such that the results are more reliable, reproducible, and fitting for complex healthcare settings.

Impact of integration of clinical and outpatient units on cancer patient satisfaction.

OBJECTIVE: There is an ongoing drive to measure and improve quality of care. Donabedians' quality framework with structure, process and outcome domains provides a useful hold to examine quality of care. The aim of this study was to address the effect of an intervention in hospital structure (integration of three units into one) with the purpose of improving processes (increase meeting, cooperation and communication between professionals and patients) and its effect on the outcome (cancer patient satisfaction). DESIGN: Pre-test-post-test. SETTING: University Medical Center Utrecht, The Netherlands, Department of Medical Oncology. PARTICIPANTS: Cancer patients (n = 174, n = 97). INTERVENTIONS: Physical integration by bringing separately located units (outpatient clinic, day-care clinic, clinical ward) together in one wing of the hospital and adjustments in communication and coordination structures. MAIN OUTCOME MEASURE: Patient satisfaction questionnaire. RESULTS: Satisfaction with care improved for six scales (27%) after integration. Effect sizes (ESs) ranged from 0.36 to 0.80, indicating a small to moderate effect. The most important improvement was found at the day-care clinic on aspects like 'the degree in which the nurses were informed about a patients situation', 'privacy', 'interior design', 'quality of hospital equipment', 'sanitary supplies' and 'waiting periods'. With regard to continuity and coordination of care, satisfaction increased for five items (28% of items concerning continuity and coordination of care). ESs ranged from 0.42 to 0.75. CONCLUSIONS: Integration of three oncology units into one unit had a positive impact on care delivery processes and resulted in improved patient satisfaction concerning care and treatment.

Acute activation of hippocampal glucocorticoid receptors results in different waves of gene expression throughout time.

Several aspects of hippocampal cell function are influenced by adrenal-secreted glucocorticoids in a delayed, genomic fashion. Previously, we used Serial Analysis of Gene Expression to identify glucocorticoid receptor (GR)-induced transcriptional changes in the hippocampus at a fixed time point. However, because changes in mRNA levels are transient and most likely precede the effects on hippocampal cell function, the aim of the current study was to assess the transcriptional changes in a broader time window by generating a time curve of GR-mediated gene expression changes. Therefore, we used rat hippocampal slices obtained from adrenalectomised rats, substituted in vivo with low corticosterone pellets, predominantly occupying the hippocampal mineralocorticoid receptors. To activate GR, slices were treated in vitro with a high (100 nM) dose of corticosterone and gene expression was profiled 1, 3 and 5 h after GR-activation. Using Affymetrix GeneChips, a striking pattern with different waves of gene expression was observed, shifting from exclusively down-regulated genes 1 h after GR-activation to both up and down regulated genes 3 h after GR-activation. After 5 h, the response was almost back to baseline. Additionally, real-time quantitative polymerase chain reaction was used for validation of a selection of responsive genes including genes involved in neurotransmission and synaptic plasticity such as the corticotropin releasing hormone receptor 1, monoamine oxidase A, LIMK1 and calmodulin 2. This permitted confirmation of GR-responsiveness of 15 out of 18 selected genes. In conclusion, direct activation of GR in hippocampal slices results in transient changes in gene expression. The pattern in which gene expression was modulated suggests that the fast genomic effects of glucocorticoids may be realised via transrepression, preceding a later wave of transactivation. Furthermore, we identified a number of interesting candidate genes which may underlie the glucocorticoid-mediated effects on hippocampal cell function.