Publikationen

A multi-group path analysis of medication documentation quality using cross-sectional survey data

2025-09-12T00:00:00Z

A multi-group path analysis of medication documentation quality using cross-sectional survey data Gambashidze, Nikoloz; Wagner, Anke; Manser, Tanja; Rieger, Monika A.; Martus, Peter; Hammer, Antje Elamir, Hossam Medication-related adverse events are a major problem for patient safety and quality of care. This study explored the effects of leadership, job satisfaction, patient-related burnout and patient safety culture, measured through surveys of frontline workers, on documentation quality. Perceptions of physicians and nurses were surveyed using established instruments including the Transformational Leadership Inventory, the Copenhagen Psychosocial Questionnaire, the Copenhagen Burnout Inventory, and the Hospital Survey on Patient Safety Culture. Documentation quality was evaluated using retrospective review of patient records with the MediDoq instrument. Data from 24 departments, covering 282 physicians, 417 nurses, and 802 patient records, were analysed through a multi-group (physicians and nurses) path analysis to evaluate the theoretical model. The theoretical model revealed satisfactory fit, explaining about 76–80% of the variance in Documentation Quality for physicians and nurses. Perceived Patient Safety had a significant effect on Documentation Quality only for nurses. The analyses revealed differences between professional groups. Based on these results, (i) medication documentation quality may be affected by various organizational factors; (ii) perceived Patient Safety reported by the nurses may mediate some of these effects; (iii) the effects of various organizational factors on documentation quality may vary significantly across professional groups.

Psychological safety, job satisfaction, and the intention to leave among German early-career physicians

2025-01-17T00:00:00Z

Psychological safety, job satisfaction, and the intention to leave among German early-career physicians Etti, Nicola; Weigl, Matthias; Gambashidze, Nikoloz Background Healthcare systems worldwide experience shortages of healthcare professionals. Retention of physicians is becoming an increasing problem. The psychological safety among physicians affects not only performance but also their emotional well-being and job satisfaction. This study aims to evaluate early career physicians' perception of psychological safety and its influence on job satisfaction and intention to leave.
Methods In a cross-sectional study, early career physicians, currently in fellowship programs in Germany were invited to fill in an electronic survey. The instrument consisted of demographic variables and sections from validated and well-established questionnaires. Psychological safety was evaluated on three levels—in relation to the team leader, team as a whole, and peers. Also, job satisfaction was assessed with standardized measures, and participants were asked if they were considering leaving their current employer. Participants were recruited via a nationwide learning platform—an online educational portal for medical students and early career physicians. Data analyses included descriptive, correlation analysis, and regression analyses to determine univariate and multivariate associations with job satisfaction and intention to leave.
Results The study sample consisted of 432 early career physicians. Most were fulltime employed (85.6%), female (78.2%), and in first 3 years of their postgraduate education (77.5%). A total of 47.2% indicated intention to leave their current employment. On a Likert-10 agreement scale, with high scores indicating greater psychological safety, the mean scores for leader-related, team-related, and peer-related psychological safety were 6.01 [95% confidence interval = 5.81–6.21), 7.30 (7.11–7.49), and 7.95 (7.78–8.12), respectively. In correlation analysis, all dimensions of psychological safety showed significant associations with job satisfaction and the intention to leave. In the multiple regression analyses, female gender (B = −0.10; P = .04) and age group (B = −0.08; P < .01) were associated with lower job satisfaction. High leader and team-related psychological safety were significantly associated with higher job satisfaction (B = 0.18, P < .01; B = 0.10, P < .01), and negatively related to intention to leave (OR = 0.53, P < 0.01; OR = 0.77, P < .01).
Conclusion This survey enhances our understanding of the nuances of psychological safety among early career physicians. In Germany, they reported low-to-medium levels of psychological safety related to the leader and low job satisfaction. Almost every second participant indicated intention to leave the organization. Leader-related psychological safety had highest effect on job satisfaction and intention to leave. Our findings corroborate the eminent role of leadership, workplace, and safety culture for job satisfaction and retention of early career physicians, what consequently affects quality and safety of healthcare.

Assessing Electronic Health Literacy in Individuals With the Post–COVID-19 Condition Using the German Revised eHealth Literacy Scale

2024-04-25T00:00:00Z

Assessing Electronic Health Literacy in Individuals With the Post–COVID-19 Condition Using the German Revised eHealth Literacy Scale Marsall, Matthias; Dinse, Hannah; Schröder, Julia; Skoda, Eva-Maria; Teufel, Martin; Bäuerle, Alexander Background: The eHealth Literacy Scale (eHEALS) is a widely used instrument for measuring eHealth literacy (eHL). However, little is known so far about whether the instrument is valid for the assessment of eHL in persons who are affected by the post–COVID-19 condition. This is particularly important as people with the post–COVID-19 condition are frequently affected by false information from the internet.
Objective: The objective of our study was to evaluate the validity and reliability of the German Revised eHealth Literacy Scale (GR-eHEALS) in individuals with the post–COVID-19 condition.
Methods: A cross-sectional study was conducted from January to May 2022. The self-assessment survey consisted of the GR-eHEALS, health status– and internet use–related variables, sociodemographic data, and (post)–COVID-19–related medical data. Confirmatory factor analysis (CFA), correlational analyses, and tests of measurement invariance were deployed.
Results: In total, 330 participants were included in the statistical analyses. CFA revealed that the 2-factor model reached an excellent model fit (comparative fit index=1.00, Tucker–Lewis index=0.99, root mean square error of approximation=0.036, standardized root mean square residual=0.038). Convergent validity was confirmed by significant positive correlations between eHL and knowledge of internet-based health promotion programs, experience in using these programs, and the duration of private internet use. In addition, a significantly negative relationship of eHL with internet anxiety supported convergent validity. Further, significant relationships of eHL with mental health status and internal health locus of control confirmed the criterion validity of the instrument. However, relationships of eHL with physical health status and quality of life could not be confirmed. The 2-factor model was fully measurement invariant regarding gender. Regarding age and educational level, partial measurement invariance was confirmed. The subscales as well as the overall GR-eHEALS reached good-to-excellent reliability (Cronbach α≥.86).
Conclusions: The GR-eHEALS is a reliable and largely valid instrument for assessing eHL in individuals with the post–COVID-19 condition. Measurement invariance regarding gender was fully confirmed and allows the interpretation of group differences. Regarding age and educational level, group differences should be interpreted with caution. Given the high likelihood that individuals with the post–COVID-19 condition will be confronted with misinformation on the Internet, eHL is a core competency that is highly relevant in this context, in both research and clinical practice. Therefore, future research should also explore alternative instruments to capture eHL to overcome shortcomings in the validity of the GR-eHEALS.

Prospective effects of an artificial intelligence-based computer-aided detection system for prostate imaging on routine workflow and radiologists' outcomes

2023-12-06T00:00:00Z

Prospective effects of an artificial intelligence-based computer-aided detection system for prostate imaging on routine workflow and radiologists' outcomes Wenderott, Katharina; Krups, Jim; Luetkens, Julian A.; Gambashidze, Nikoloz; Weigl, Matthias Objectives: Artificial intelligence (AI) is expected to alleviate the negative consequences of rising case numbers for radiologists. Currently, systematic evaluations of the impact of AI solutions in real-world radiological practice are missing. Our study addresses this gap by investigating the impact of the clinical implementation of an AI-based computer-aided detection system (CAD) for prostate MRI reading on clinicians' workflow, workflow throughput times, workload, and stress.
Materials and methods: CAD was newly implemented into radiology workflow and accompanied by a prospective pre-post study design. We assessed prostate MRI case readings using standardized work observations and questionnaires. The observation period was three months each in a single department. Workflow throughput times, PI-RADS score, CAD usage and radiologists' self-reported workload and stress were recorded. Linear mixed models were employed for effect identification.
Results: In data analyses, 91 observed case readings (pre: 50, post: 41) were included. Variation of routine workflow was observed following CAD implementation. A non-significant increase in overall workflow throughput time was associated with CAD implementation (mean 16.99 ± 6.21 vs 18.77 ± 9.69 min, p = .51), along with an increase in diagnostic reading time for high suspicion cases (mean 15.73 ± 4.99 vs 23.07 ± 8.75 min, p = .02). Changes in radiologists' self-reported workload or stress were not found.
Conclusion: Implementation of an AI-based detection aid was associated with lower standardization and no effects over time on radiologists' workload or stress. Expectations of AI decreasing the workload of radiologists were not confirmed by our real-world study.