OBJECTIVE: This study investigates the care provision and the role of infectious disease (ID) specialists during the coronavirus disease-2019 (COVID-19) pandemic.
METHODS: A survey was conducted at German study sites participating in the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS). Hospitals certified by the German Society of Infectious diseases (DGI) were identified as ID centers. We compared care provision and the involvement of ID specialists between ID and non-ID hospitals. Then we applied a multivariable regression model to analyse how clinical ID care influenced the mortality of COVID-19 patients in the LEOSS cohort.
RESULTS: Of the 40 participating hospitals in the study, 35% (14/40) were identified as ID centers. Among those, clinical ID care structures were more commonly established, and ID specialists were always involved in pandemic management and the care of COVID-19 patients. Overall, 68% (27/40) of the hospitals involved ID specialists in the crisis management team, 78% (31/40) in normal inpatient care, and 80% (28/35) in intensive care. Multivariable analysis revealed that COVID-19 patients in ID centers had a lower mortality risk compared to those in non-ID centers (odds ratio: 0.61 (95% CI 0.40-0.93), p = 0.021).
CONCLUSIONS: ID specialists played a crucial role in pandemic management and inpatient care.

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This study examined health information technology-related incidents to characterise system issues as a basis for improvement in Swedish clinical practice. Incident reports were collected through interviews together with retrospectively collected incidents from voluntary incident databases, which were analysed using deductive and inductive approaches. Most themes pertained to system issues, such as functionality, design, and integration. Identified system issues were dominated by technical factors (74%), while human factors accounted for 26%. Over half of the incidents (55%) impacted on staff or the organisation, and the rest on patients - patient inconvenience (25%) and patient harm (20%). The findings indicate that it is vital to choose and commission suitable systems, design out \"error-prone\" features, ensure contingency plans are in place, implement clinical decision-support systems, and respond to incidents on time. Such strategies would improve the health information technology systems and Swedish clinical practice.

The Veterans Health Administration (VA) increasingly purchases community-based care (CC) to improve healthcare access, including behavioral health. In 2018, VA introduced standardized episodes of care (SEOCs) to guide authorization and purchase of CC services for specific indications in a defined timeframe without bundling payment. In this retrospective cross-sectional study, we describe trends in VA and CC behavioral healthcare utilization using the VA Outpatient Psychiatry SEOC definition. Counts of Outpatient Psychiatry SEOC-allowable service and procedure codes during fiscal years 2016-2019 were organized according to four SEOC-defined service types (evaluation and management, laboratory services, psychiatry services, transitional care) and measured as percentages of all included codes. Trends comparing behavioral healthcare utilization between Veterans using any CC versus VA only were analyzed using a linear mixed effects model. We identified nearly 3 million Veterans who registered 60 million qualifying service and procedure codes, with overall utilization increasing 77.8% in CC versus 5.2% in VA. Veterans receiving any CC comprised 3.9% of the cohort and 4.7% of all utilization. When examining service type as a percent of all Outpatient Psychiatry SEOC-allowable care among Veterans using CC, psychiatry services increased 12.2%, while transitional care decreased 8.8%. In regression analysis, shifts in service type utilization reflected descriptive results but with attenuated effect sizes. In sum, Outpatient Psychiatry SEOC-allowable service utilization grew, and service type composition changed, significantly more in CC than in VA. The role of SEOCs and their incentives may be important when evaluating future behavioral healthcare quality and value in bundled services.

BACKGROUND: Measures of patient safety culture and patient experience are both commonly utilised to evaluate the quality of healthcare services, including hospitals, but the relationship between these two domains remains uncertain. In this study, we aimed to explore and synthesise published literature regarding the relationships between these topics in hospital settings.
METHODS: This study was performed using the five stages of Arksey and O\'Malley\'s Framework, refined by the Joanna Briggs Institute. Searches were conducted in the CINAHL, Cochrane Library, ProQuest, MEDLINE, PsycINFO, SciELO and Scopus databases. Further online search on the websites of pertinent organisations in Australia and globally was conducted. Data were extracted against predetermined criteria.
RESULTS: 4512 studies were initially identified; 15 studies met the inclusion criteria. Several positive statistical relationships between patient safety culture and patient experience domains were identified. Communication and teamwork were the most influential factors in the relationship between patient safety culture and patient experience. Managers and clinicians had a positive view of safety and a positive relationship with patient experience, but this was not the case when managers alone held such views. Qualitative methods offered further insights into patient safety culture from patients\' and families\' perspectives.
CONCLUSIONS: The findings indicate that the patient can recognise safety-related issues that the hospital team may miss. However, studies mostly measured staff perspectives on patient safety culture and did not always include patient experiences of patient safety culture. Further, the relationship between patient safety culture and patient experience is generally identified as a statistical relationship, using quantitative methods. Further research assessing patient safety culture alongside patient experience is essential for providing a more comprehensive picture of safety. This will help to uncover issues and other factors that may have an indirect effect on patient safety culture and patient experience.

UNASSIGNED: In the healthcare system, in the last 30 years, the prognostically negative value of the so-called Weekend Effect (WE) has been internationally recognized. The WE is regarded as the increased risk a patient might incur when hospitalized during non-working days, of enduring severe complications in comparison to the same hospitalization that occur on working days. The aim of this study was to retrospectively verify whether, once a mistake was made during weekends or on holidays, in comparison to a mistake occurred on workdays, it subsequently implied a higher risk of complications, death included, in a statistical and medico-legal way.
UNASSIGNED: Three different evaluators independently examined a total of 378 medico-legal cases over a more than 20-year period. Eventual medical actions and omissions were labelled as \'mistake\' when the AJ claimed that at least one occurred; \'alleged mistake\' included the cases where the EW\'s report disagreed with the AJ\'s one; finally, \'no mistake\' when both the AJ and the EW agreed in their evaluations. During weekends there is a higher risk that a mistake occurs (OR=3.3, 95% CI=1.6;7.4; p-value<0.001) compared to weekdays. When death occurs, delayed diagnosis is the main cause (p=0.02), whereas a damaging action is more frequently claimed in general.
UNASSIGNED: We verified as actual the impact of the WE on patients\' outcome from a medico-legal point of view. The implications for an improvement of the several settings of the Italian NHS are various, and many are the consequences in the healthcare management.

BACKGROUND: Patients increasingly rely on web-based physician reviews to choose a physician and share their experiences. However, the unstructured text of these written reviews presents a challenge for researchers seeking to make inferences about patients\' judgments. Methods previously used to identify patient judgments within reviews, such as hand-coding and dictionary-based approaches, have posed limitations to sample size and classification accuracy. Advanced natural language processing methods can help overcome these limitations and promote further analysis of physician reviews on these popular platforms.
OBJECTIVE: This study aims to train, test, and validate an advanced natural language processing algorithm for classifying the presence and valence of 2 dimensions of patient judgments in web-based physician reviews: interpersonal manner and technical competence.
METHODS: We sampled 345,053 reviews for 167,150 physicians across the United States from Healthgrades.com, a commercial web-based physician rating and review website. We hand-coded 2000 written reviews and used those reviews to train and test a transformer classification algorithm called the Robustly Optimized BERT (Bidirectional Encoder Representations from Transformers) Pretraining Approach (RoBERTa). The 2 fine-tuned models coded the reviews for the presence and positive or negative valence of patients\' interpersonal manner or technical competence judgments of their physicians. We evaluated the performance of the 2 models against 200 hand-coded reviews and validated the models using the full sample of 345,053 RoBERTa-coded reviews.
RESULTS: The interpersonal manner model was 90% accurate with precision of 0.89, recall of 0.90, and weighted F1-score of 0.89. The technical competence model was 90% accurate with precision of 0.91, recall of 0.90, and weighted F1-score of 0.90. Positive-valence judgments were associated with higher review star ratings whereas negative-valence judgments were associated with lower star ratings. Analysis of the data by review rating and physician gender corresponded with findings in prior literature.
CONCLUSIONS: Our 2 classification models coded interpersonal manner and technical competence judgments with high precision, recall, and accuracy. These models were validated using review star ratings and results from previous research. RoBERTa can accurately classify unstructured, web-based review text at scale. Future work could explore the use of this algorithm with other textual data, such as social media posts and electronic health records.

UNASSIGNED: Continuity of care is one of the main principles of family medicine, described as a relationship with a single provider that extends beyond a single illness episode. This retrospective study, conducted at King Saud University Family Medicine Center in Riyadh, Saudi Arabia, aimed to investigate the impact of having a regular primary care provider on clinical outcomes and preventive service delivery for patients with diabetes and/or hypertension.
UNASSIGNED: The study, spanning 2017 to 2019, included 400 patients diagnosed with diabetes and/or hypertension for at least six months before the 6-month pre-attachment period to regular family medicine physicians in 2018. Data before and after attachment for at least six months were compared using electronic health records.
UNASSIGNED: The mean age of the patients was 60.9, with a predominant female representation (66.8%) and 90.7% Saudis. Results indicated a significant improvement in glycated hemoglobin (HbA1c) levels (p = 0.005) and systolic blood pressure (p = 0.014) post-attachment. Preventive service delivery saw notable enhancements, with increased colon cancer screening (p = 0.03), breast cancer screening (p < 0.001), and retinal screening (p < 0.001) post-attachment.
UNASSIGNED: This study\'s findings underscore the importance of continuity of care in chronic disease management and provide valuable and promising insights into the Saudi healthcare context, aligning with the Saudi Ministry of Health\'s vision for universal access to regular primary care providers.

UNASSIGNED: When performance data are provided as feedback to healthcare professionals, they may use it to significantly improve care quality. However, the question of how to provide effective feedback remains unanswered, as decades of evidence have produced a consistent pattern of effects-with wide variation. From a coaching perspective, feedback is often based on a learner\'s objectives and goals. Furthermore, when coaches provide feedback, it is ideally informed by their understanding of the learner\'s needs and motivation. We anticipate that a \"coaching\"-informed approach to feedback may improve its effectiveness in two ways. First, by aligning feedback with healthcare professionals\' chosen goals and objectives, and second, by enabling large-scale feedback systems to use new types of data to learn what kind of performance information is motivating in general. Our objective is to propose a conceptual model of precision feedback to support these anticipated enhancements to feedback interventions.
UNASSIGNED: We iteratively represented models of feedback\'s influence from theories of motivation and behavior change, visualization, and human-computer interaction. Through cycles of discussion and reflection, application to clinical examples, and software development, we implemented and refined the models in a software application to generate precision feedback messages from performance data for anesthesia providers.
UNASSIGNED: We propose that precision feedback is feedback that is prioritized according to its motivational potential for a specific recipient. We identified three factors that influence motivational potential: (1) the motivating information in a recipient\'s performance data, (2) the surprisingness of the motivating information, and (3) a recipient\'s preferences for motivating information and its visual display.
UNASSIGNED: We propose a model of precision feedback that is aligned with leading theories of feedback interventions to support learning about the success of feedback interventions. We plan to evaluate this model in a randomized controlled trial of a precision feedback system that enhances feedback emails to anesthesia providers.

BACKGROUND: In France, the COVID-19 vaccination campaign started in January 2021. This study reports the one-year experience of a multidisciplinary team from university hospital in operating a vaccination center created in a metropolitan sports arena.
METHODS: Some of the data derive from an online appointment scheduling software. Daily traceability sheets were utilized as a formalized method to gather data on non-conformities, adverse events, and to estimate the duration of the vaccination pathway. The professional satisfaction assessment was carried out via an anonymous online questionnaire. The collected data were examined with descriptive statistics.
RESULTS: We propose strengths of our organization to obtain efficient and safe vaccination pathway. In one year, 572,491 immunization shots were administered. The operational team size increased from 31 (500 vaccinations per day) to 71 (3000 vaccinations per day). In March 2021, the average duration to vaccination (excluding post-vaccination monitoring) was 12 [5-37] minutes for patients without medical consultation vs 16 [5-45] minutes for patients with medical consultation. 0.11 % non-conformities on vaccines got notified not allowing them to be used for vaccination. One error regarding the volume administered got reported. Among the professionals working in the vaccination center, 97 % were satisfied with the organization and 88 % with the quality of the information received from team leader or team project. Main difficulties encountered were managing the leftover doses at night and communicating with patients.
CONCLUSIONS: Overall, the ability to vaccinate a population efficiently and safely on a large scale during a pandemic is based on the engagement of skilled multidisciplinary teams and securing the vaccination pathway.