Redistribution does matter

Peer reviewe

The occurrence of adverse events in low-risk non-survivors in pediatric intensive care patients: an exploratory study

We studied the occurrence of adverse events (AEs) in low-risk non-survivors (LNs), compared to low-risk survivors (LSs), high-risk non-survivors (HNs), and high-risk survivors (HSs) in two pediatric intensive care units (PICUs). The study was performed as a retrospective patient record review study, using a PICU-trigger tool. A random sample of 48 PICU patients (0–18 years) was chosen, stratified into four subgroups of 12 patients: LNs, LSs, HNs, and HSs. Primary outcome was the occurrence of AEs. The severity, preventability, and nature of the indentified AEs were determined. In total, 45 AEs were found in 20 patients. The occurrence of AEs in the LN group was significantly higher compared to that in the LS group and HN group (AE occurrence: LN 10/12 patients, LS 1/12 patients; HN 2/12 patients; HS 7/12 patients; LN-LS difference, p < 0.001; LN-HN difference, p < 0.01). The AE rate in the LN group was significantly higher compared to that in the LS and HN groups (median [IQR]: LN 0.12 [0.07–0.29], LS 0 [0–0], HN 0 [0–0], and HS 0.03 [0.0–0.17] AE/PICU day; LN-LS difference, p < 0.001; LN-HN difference, p < 0.01). The distribution of the AEs among the four groups was as follows: 25 AEs (LN), 2 AEs (LS), 8 AEs (HN), and 10 AEs (HS). Fifteen of forty-five AEs were preventable. In 2/12 LN patients, death occurred after a preventable AE. Conclusion: The occurrence of AEs in LNs was higher compared to that in LSs and HNs. Some AEs were severe and preventable and contributed to mortality.(Table presented.

Using patient experience in optimizing the total knee arthroplasty patient journey

Information was used to improve the patient journey and to achieve patient-centered care. Patients (\u3e18 years, purposive sampling) were interviewed once at one point of their total knee arthrosis journey within the hospital setting. Patients were accompanied and observed during their hospital visit by one of the 19 healthcare professionals which were trained as interviewers. A qualitative research approach with in-depth and semi-structured interviews using a standardized interview guide were used to gather an in-depth understanding of the perceptions of patients. Interviews were written out with the emphasis on positive and negative feedback, quotes and observations that were made. The audio recordings were verbatim transcribed and coded using selective and open coding. Thirty-five semi-structured interviews were conducted. Five different themes were identified: overall experience, waiting, communication, information and facilities. Several easy fixes were dealt with immediately to improve service quality, productivity and the organization of the healthcare service. Other improvements were discussed with the stakeholders and were resolved directly or were planned for the long-term. Involving patients and let them collaborate with healthcare professionals is essential in optimizing patient-centered care. Most feedback was related to clarification and comprehensibility of the patient journey, to improve autonomy and to remove uncertainty of the patients. Continuity of care with medical personnel, personal attention and recognition of the problem are fundamental during the knee arthrosis patient journey. Experience Framework This article is associated with the Quality & Clinical Excellence lens of The Beryl Institute Experience Framework. (http://bit.ly/ExperienceFramework) Access other PXJ articles related to this lens. Access other resources related to this lens

Intensive care unit depth of sleep:proof of concept of a simple electroencephalography index in the non-sedated

INTRODUCTION: Intensive care unit (ICU) patients are known to experience severely disturbed sleep, with possible detrimental effects on short- and long- term outcomes. Investigation into the exact causes and effects of disturbed sleep has been hampered by cumbersome and time consuming methods of measuring and staging sleep. We introduce a novel method for ICU depth of sleep analysis, the ICU depth of sleep index (IDOS index), using single channel electroencephalography (EEG) and apply it to outpatient recordings. A proof of concept is shown in non-sedated ICU patients. METHODS: Polysomnographic (PSG) recordings of five ICU patients and 15 healthy outpatients were analyzed using the IDOS index, based on the ratio between gamma and delta band power. Manual selection of thresholds was used to classify data as either wake, sleep or slow wave sleep (SWS). This classification was compared to visual sleep scoring by Rechtschaffen & Kales criteria in normal outpatient recordings and ICU recordings to illustrate face validity of the IDOS index. RESULTS: When reduced to two or three classes, the scoring of sleep by IDOS index and manual scoring show high agreement for normal sleep recordings. The obtained overall agreements, as quantified by the kappa coefficient, were 0.84 for sleep/wake classification and 0.82 for classification into three classes (wake, non-SWS and SWS). Sensitivity and specificity were highest for the wake state (93% and 93%, respectively) and lowest for SWS (82% and 76%, respectively). For ICU recordings, agreement was similar to agreement between visual scorers previously reported in literature. CONCLUSIONS: Besides the most satisfying visual resemblance with manually scored normal PSG recordings, the established face-validity of the IDOS index as an estimator of depth of sleep was excellent. This technique enables real-time, automated, single channel visualization of depth of sleep, facilitating the monitoring of sleep in the ICU