Adverse events (AEs) seriously affect patient safety and quality of care, and remain a pressing global issue. This study had three objectives: (1) to describe the proportions of patients affected by ...in-hospital AEs; (2) to explore the types and consequences of observed AEs; and (3) to estimate the preventability of in-hospital AEs.
We applied a scoping review method and concluded a comprehensive literature search in PubMed and CINAHL in May 2017 and in February 2018. Our target was retrospective medical record review studies applying the Harvard method-or similar methods using screening criteria-conducted in acute care hospital settings on adult patients (≥18 years).
We included a total of 25 studies conducted in 27 countries across six continents. Overall, a median of 10% patients were affected by at least one AE (range: 2.9-21.9%), with a median of 7.3% (range: 0.6-30%) of AEs being fatal. Between 34.3 and 83% of AEs were considered preventable (median: 51.2%). The three most common types of AEs reported in the included studies were operative/surgical related, medication or drug/fluid related, and healthcare-associated infections.
Evidence regarding the occurrence of AEs confirms earlier estimates that a tenth of inpatient stays include adverse events, half of which are preventable. However, the incidence of in-hospital AEs varied considerably across studies, indicating methodological and contextual variations regarding this type of retrospective chart review across health care systems. For the future, automated methods for identifying AE using electronic health records have the potential to overcome various methodological issues and biases related to retrospective medical record review studies and to provide accurate data on their occurrence.
Understanding how comorbidity measures contribute to patient mortality is essential both to describe patient health status and to adjust for risks and potential confounding. The Charlson and ...Elixhauser comorbidity indices are well-established for risk adjustment and mortality prediction. Still, a different set of comorbidity weights might improve the prediction of in-hospital mortality. The present study, therefore, aimed to derive a set of new Swiss Elixhauser comorbidity weightings, to validate and compare them against those of the Charlson and Elixhauser-based van Walraven weights in an adult in-patient population-based cohort of general hospitals.
Retrospective analysis was conducted with routine data of 102 Swiss general hospitals (2012-2017) for 6.09 million inpatient cases. To derive the Swiss weightings for the Elixhauser comorbidity index, we randomly halved the inpatient data and validated the results of part 1 alongside the established weighting systems in part 2, to predict in-hospital mortality. Charlson and van Walraven weights were applied to Charlson and Elixhauser comorbidity indices. Derivation and validation of weightings were conducted with generalized additive models adjusted for age, gender and hospital types.
Overall, the Elixhauser indices, c-statistic with Swiss weights (0.867, 95% CI, 0.865-0.868) and van Walraven's weights (0.863, 95% CI, 0.862-0.864) had substantial advantage over Charlson's weights (0.850, 95% CI, 0.849-0.851) and in the derivation and validation groups. The net reclassification improvement of new Swiss weights improved the predictive performance by 1.6% on the Elixhauser-van Walraven and 4.9% on the Charlson weights.
All weightings confirmed previous results with the national dataset. The new Swiss weightings model improved slightly the prediction of in-hospital mortality in Swiss hospitals. The newly derive weights support patient population-based analysis of in-hospital mortality and seek country or specific cohort-based weightings.
High bed-occupancy (capacity utilization) rates are commonly thought to increase in-hospital mortality; however, little evidence supports a causal relationship between the two. This observational ...study aimed to assess three time-varying covariates-capacity utilization, patient turnover and clinical complexity level- and to estimate causal effect of time-varying high capacity utilization on 14 day in-hospital mortality.
This retrospective population-based analysis was based on routine administrative data (n = 1,152,506 inpatient cases) of 102 Swiss general hospitals. Considering the longitudinal nature of the problem from available literature and expert knowledge, we represented the underlying data generating mechanism as a directed acyclic graph. To adjust for patient turnover and patient clinical complexity levels as time-varying confounders, we fitted a marginal structure model (MSM) that used inverse probability of treatment weights (IPTWs) for high and low capacity utilization. We also adjusted for patient age and sex, weekdays-vs-weekend, comorbidity weight, and hospital type.
For each participating hospital, our analyses evaluated the ≥85th percentile as a threshold for high capacity utilization for the higher risk of mortality. The mean bed-occupancy threshold was 83.1% (SD 8.6) across hospitals and ranged from 42.1 to 95.9% between hospitals. For each additional day of exposure to high capacity utilization, our MSM incorporating IPTWs showed a 2% increase in the odds of 14-day in-hospital mortality (OR 1.02, 95% CI: 1.01 to 1.03).
Exposure to high capacity utilization increases the mortality risk of inpatients. Accurate monitoring of capacity utilization and flexible human resource planning are key strategies for hospitals to lower the exposure to high capacity utilization.
Background
Variations in hospitals’ care demand relies not only on the patient volume but also on the disease severity. Understanding both daily severity and patient volume in hospitals could help to ...identify hospital pressure zones to improve hospital-capacity planning and policy-making.
Objective
This longitudinal study explored daily care demand dynamics in Swiss general hospitals for 3 measures: (1) capacity utilization, (2) patient turnover, and (3) patient clinical complexity level.
Methods
A retrospective population-based analysis was conducted with 1 year of routine data of 1.2 million inpatients from 102 Swiss general hospitals. Capacity utilization was measured as a percentage of the daily maximum number of inpatients. Patient turnover was measured as a percentage of the daily sum of admissions and discharges per hospital. Patient clinical complexity level was measured as the average daily patient disease severity per hospital from the clinical complexity algorithm.
Results
There was a pronounced variability of care demand in Swiss general hospitals. Among hospitals, the average daily capacity utilization ranged from 57.8% (95% CI 57.3-58.4) to 87.7% (95% CI 87.3-88.0), patient turnover ranged from 22.5% (95% CI 22.1-22.8) to 34.5% (95% CI 34.3-34.7), and the mean patient clinical complexity level ranged from 1.26 (95% CI 1.25-1.27) to 2.06 (95% CI 2.05-2.07). Moreover, both within and between hospitals, all 3 measures varied distinctly between days of the year, between days of the week, between weekdays and weekends, and between seasons.
Conclusions
While admissions and discharges drive capacity utilization and patient turnover variation, disease severity of each patient drives patient clinical complexity level. Monitoring—and, if possible, anticipating—daily care demand fluctuations is key to managing hospital pressure zones. This study provides a pathway for identifying patients’ daily exposure to strained hospital systems for a time-varying causal model.
•The severity of SARS-CoV-2 patients is difficult to quickly assess in the ED.•The ABG test is a quick and easy tool that can help identify more severe patients.•CT cannot be used on all suspected ...SARS-CoV-2 infected patients admitted in ED.•The CT volumetry correlates well with the values of severity reported by the ABG test.
Adverse event (AE) detection is a major patient safety priority. However, despite extensive research on AEs, reported incidence rates vary widely. This study aimed: (1) to synthesize available ...evidence on AE incidence in acute care inpatient settings using Trigger Tool methodology; and (2) to explore whether study characteristics and study quality explain variations in reported AE incidence. To identify relevant studies, we queried PubMed, EMBASE, CINAHL, Cochrane Library and three journals in the patient safety field (last update search 25.05.2022). Eligible publications fulfilled the following criteria: adult inpatient samples; acute care hospital settings; Trigger Tool methodology; focus on specialty of internal medicine, surgery or oncology; published in English, French, German, Italian or Spanish. Systematic reviews and studies addressing adverse drug events or exclusively deceased patients were excluded. Risk of bias was assessed using an adapted version of the Quality Assessment Tool for Diagnostic Accuracy Studies 2. Our main outcome of interest was AEs per 100 admissions. We assessed nine study characteristics plus study quality as potential sources of variation using random regression models. We received no funding and did not register this review. Screening 6,685 publications yielded 54 eligible studies covering 194,470 admissions. The cumulative AE incidence was 30.0 per 100 admissions (95% CI 23.9-37.5; I.sup.2 = 99.7%) and between study heterogeneity was high with a prediction interval of 5.4-164.7. Overall studies' risk of bias and applicability-related concerns were rated as low. Eight out of nine methodological study characteristics did explain some variation of reported AE rates, such as patient age and type of hospital. Also, study quality did explain variation. Estimates of AE studies using trigger tool methodology vary while explaining variation is seriously hampered by the low standards of reporting such as the timeframe of AE detection. Specific reporting guidelines for studies using retrospective medical record review methodology are necessary to strengthen the current evidence base and to help explain between study variation.
Care workers in nursing homes often perform tasks that are rather related to organizational or management activities than 'direct patient care'. 'Indirect care activities', such as documentation or ...other administrative tasks are often considered by care workers as a burden, as they increase overall workload and keep them away from caring for residents. So far, there is little investigation into what kind of administrative tasks are being performed in nursing homes, by which type of care workers, and to which extent, nor how administrative burden is associated with care workers' outcomes.
The objective of this study was to describe care workers' administrative burden in Swiss nursing homes and to explore the association with four care worker outcomes (i.e., job dissatisfaction, emotional exhaustion, intention to leave the current job and the profession).
This multicenter cross-sectional study used survey data from the Swiss Nursing Homes Human Resources Project 2018. It included a convenience sample of 118 nursing homes and 2'207 care workers (i.e., registered nurses, licensed practical nurses) from Switzerland's German- and French-speaking regions. Care workers completed questionnaires assessing the administrative tasks and burden, staffing and resource adequacy, leadership ability, implicit rationing of nursing care and care worker characteristics and outcomes. For the analysis, we applied generalized linear mixed models, including individual-level nurse survey data and data on unit and facility characteristics.
Overall, 73.9% (n = 1'561) of care workers felt strongly or rather strongly burdened, with one third (36.6%, n = 787) reporting to spend 2 h or more during a "normal" day performing administrative tasks. Ratings for administrative burden ranged from 42.6% (n = 884; ordering supplies and managing stocks) to 75.3% (n = 1'621; filling out the resident's health record). One out of four care workers (25.5%, n = 561) intended to leave the profession, whereby care workers reporting higher administrative task burden (OR = 1.24; 95%CI: 1.02-1.50) were more likely to intend to leave the profession.
This study provides first insights on care workers' administrative burden in nursing homes. By limiting care workers' burdensome administrative tasks and/or shifting such tasks from higher to lower educated care workers or administrative personnel when appropriate, nursing home managers could reduce care workers' workload and improve their job satisfaction and retention in the profession.
We aimed to (1) describe the course of the emotional burden (i.e., depression, anxiety, and stress) in a general population sample during the coronavirus pandemic in 2020 and 2021 and (2) explore the ...association between emotional burden and a serologically proven infection with SARS-CoV-2.
This longitudinal study involved a sample of community-dwelling persons aged ≥14 years from the general population of South Tyrol (Province of Bolzano-Bozen, Northern Italy). Data were collected at two stages over a 1-year period in 2020 and 2021.
Persons were invited to participate in a survey on socio-demographic, health-related and psychosocial variables (e.g., age, chronic diseases, Depression Anxiety Stress Scale, DASS-21), as well as in the serological testing for of SARS-CoV-2-specific immunoglobulins.
In 2020, 855 (23.8%) out of 3,600 persons participated; in 2021, 305 (35.7%) out of 855 were tested again. We observed a statistically significant decrease in mean DASS-21 scores for depression, stress, and total scores between 2020 and 2021, yet not for anxiety. Persons with a confirmed SARS-CoV-2-infection between the first and second data collection exhibited increased emotional burden compared to those without SARS-CoV-2-infection. The odds of participants with a self-reported diagnosis of mental disorder for future infection with SARS-CoV-2 was almost four times higher than that of participants without mental disorders (OR:3.75; 95%CI:1.79-7.83).
Our findings support to the hypothesis of a psycho-neuroendocrine-immune interplay in COVID-19. Further research is necessary to explore the mechanisms underlying the interplay between mental health and SARS-CoV-2 infections.
To describe care worker-reported quality of care and to examine its relationship with staffing variables, work environment, work stressors, and implicit rationing of nursing care.
Cross-sectional ...study.
National, randomly selected sample of Swiss nursing homes, stratified according to language region and size.
A total of 4311 care workers of all educational backgrounds (registered nurses, licensed practical nurses, nurse aides) from 402 units in 155 nursing homes completed a survey between May 2012 and April 2013.
Care worker-reported quality of care was measured with a single item; predictors were assessed with established instruments (eg, Practice Environment Scale-Nurse Working Index) adapted for nursing home use. A multilevel logistic regression model was applied to assess predictors for quality of care.
Overall, 7% of care workers rated the quality of care provided as rather low or very low. Important factors related to better quality of care were higher teamwork and safety climate (odds ratio OR 6.19, 95% confidence interval CI 4.36-8.79); better staffing and resources adequacy (OR 2.94, 95% CI 2.08-4.15); less stress due to workload (OR 0.71, 95% CI 0.55-0.93); less implicit rationing of caring, rehabilitation, and monitoring (OR 0.34, 95% CI 0.24-0.49); and less rationing of social care (OR 0.80, 95% CI 0.69-0.92). Neither leadership nor staffing levels, staff mix, or turnover was significantly related to quality of care.
Work environment factors and organizational processes are vital to provide high quality of care. The improvement of work environment, support in handling work stressors, and reduction of rationing of nursing care might be intervention points to promote high quality of care in nursing homes.
Interprofessional education (IPE) interventions are not always successful in achieving learning outcomes. Team-Based Learning (TBL) would appear to be a suitable pedagogical method for IPE, as it ...focuses on team performance; however, little is known about interprofessional TBL as an instructional framework for patient safety. In this pilot-study, we aimed to (1) describe participants' reactions to TBL, (2) observe their achievement with respect to interprofessional education learning objectives, and (3) document their attitudinal shifts with regard to patient safety behaviours.
We developed and implemented a three-day course for pre-qualifying, non-medical healthcare students to give instruction on non-technical skills related to 'learning from errors'. The course consisted of three sequential modules: 'Recognizing Errors', 'Analysing Errors', and 'Reporting Errors'. The evaluation took place within a quasi-experimental pre-test-post-test study design. Participants completed self-assessments through valid and reliable instruments such as the Mennenga's TBL Student Assessment Instrument and the University of the West of England's Interprofessional Questionnaire. The mean scores of the individual readiness assurance tests were compared with the scores of the group readiness assurance test in order to explore if students learned from each other during group discussions. Data was analysed using descriptive (i.e. mean, standard deviation), parametric (i.e. paired t-test), and non-parametric (i.e. Wilcoxon signed-rank test) methods.
Thirty-nine students from five different bachelor's programs attended the course. The participants positively rated TBL as an instructional approach. All teams outperformed the mean score of their individual members during the readiness assurance process. We observed significant improvements in 'communication and teamwork' and 'interprofessional learning' but not in 'interprofessional interaction' and 'interprofessional relationships.' Findings on safety attitudes and behaviours were mixed.
TBL was well received by the students. Our first findings indicate that interprofessional TBL seems to be a promising pedagogical method to achieve patient safety learning objectives. It is crucial to develop relevant clinical cases that involve all professions. Further research with larger sample sizes (e.g. including medical students) and more rigorous study designs (e.g. pre-test post-test with a control group) is needed to confirm our preliminary findings.
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