Early impact of the COVID-19 pandemic on in-person outpatient care utilisation: a rapid review.

To quantitatively assess the early impact of the COVID-19 pandemic on in-person outpatient care utilisation worldwide, as well as across categories of services, types of care and medical specialties. Rapid review. A search of MEDLINE and Embase was conducted to identify studies published from 1 January 2020 to 12 February 2021, which quantitatively reported the impact of the COVID-19 pandemic on the amount of outpatient care services delivered (in-person visits, diagnostic/screening procedures and treatments). There was no restriction on the type of medical care (emergency/primary/specialty care) or target population (adult/paediatric). All articles presenting primary data from studies reporting on outpatient care utilisation were included. Studies describing conditions requiring hospitalisation or limited to telehealth services were excluded. A total of 517 articles reporting 1011 outpatient care utilisation measures in 49 countries worldwide were eligible for inclusion. Of those, 93% focused on the first semester of 2020 (January to June). The reported results showed an almost universal decline in in-person outpatient care utilisation, with a 56% overall median relative decrease. Heterogeneity across countries was high, with median decreases ranging from 10% to 91%. Diagnostic and screening procedures (-63%), as well as in-person visits (-56%), were more affected than treatments (-36%). Emergency care showed a smaller relative decline (-49%) than primary (-60%) and specialty care (-58%). The provision of in-person outpatient care services has been strongly impacted by the COVID-19 pandemic, but heterogeneously across countries. The long-term population health consequences of the disruption of outpatient care service delivery remain currently unknown and need to be studied. CRD42021237366

Hospital discharge data is not accurate enough to monitor the incidence of postpartum hemorrhage.

Postpartum hemorrhage remains a leading cause of maternal morbidity and mortality worldwide. Therefore, cumulative incidence of postpartum hemorrhage and severe postpartum hemorrhage are commonly monitored within and compared across maternity hospitals or countries for obstetrical safety improvement. These indicators are usually based on hospital discharge data though their accuracy is seldom assessed. We aimed to measure postpartum hemorrhage and severe postpartum hemorrhage using electronic health records and hospital discharge data separately and compare the detection accuracy of these methods to manual chart review, and to examine the temporal trends in cumulative incidence of these potentially avoidable adverse outcomes. We analyzed routinely collected data of 7904 singleton deliveries from a large Swiss university hospital for a three year period (2014-2016). We identified postpartum hemorrhage and severe postpartum hemorrhage in electronic health records by text mining discharge letters and operative reports and calculating drop in hemoglobin from laboratory tests. Diagnostic and procedure codes were used to identify cases in hospital discharge data. A sample of 334 charts was reviewed manually to provide a reference-standard and evaluate the accuracy of the other detection methods. Sensitivities of detection algorithms based on electronic health records and hospital discharge data were 95.2% (95% CI: 92.6% 97.8%) and 38.2% (33.3% to 43.0%), respectively for postpartum hemorrhage, and 87.5% (85.2% to 89.8%) and 36.2% (26.3% to 46.1%) for severe postpartum hemorrhage. Postpartum hemorrhage cumulative incidence based on electronic health records decreased from 15.6% (13.1% to 18.2%) to 8.5% (6.7% to 10.5%) from the beginning of 2014 to the end of 2016, with an average of 12.5% (11.8% to 13.3%). The cumulative incidence of severe postpartum hemorrhage remained at approximately 4% (3.5% to 4.4%). Hospital discharge data-based algorithms provided significantly underestimated incidences. Hospital discharge data is not accurate enough to assess the incidence of postpartum hemorrhage at hospital or national level. Instead, automated algorithms based on structured and textual data from electronic health records should be considered, as they provide accurate and timely estimates for monitoring and improvement in obstetrical safety. Furthermore, they have the potential to better code for postpartum hemorrhage thus improving hospital reimbursement

Impact of a comprehensive prevention programme aimed at reducing incivility and verbal violence against healthcare workers in a French ophthalmic emergency department: an interrupted time-series study.

Primary prevention, comprising patient-oriented and environmental interventions, is considered to be one of the best ways to reduce violence in the emergency department (ED). We assessed the impact of a comprehensive prevention programme aimed at preventing incivility and verbal violence against healthcare professionals working in the ophthalmology ED (OED) of a university hospital. The programme was designed to address long waiting times and lack of information. It combined a computerised triage algorithm linked to a waiting room patient call system, signage to assist patients to navigate in the OED, educational messages broadcast in the waiting room, presence of a mediator and video surveillance. All patients admitted to the OED and those accompanying them. Single-centre prospective interrupted time-series study conducted over 18 months. Violent acts self-reported by healthcare workers committed by patients or those accompanying them against healthcare workers. Waiting time and length of stay. There were a total of 22 107 admissions, including 272 (1.4%) with at least one act of violence reported by the healthcare workers. Almost all acts of violence were incivility or verbal harassment. The rate of violence significantly decreased from the pre-intervention to the intervention period (24.8, 95% CI 20.0 to 29.5, to 9.5, 95% CI 8.0 to 10.9, acts per 1000 admissions, p<0.001). An immediate 53% decrease in the violence rate (incidence rate ratio=0.47, 95% CI 0.27 to 0.82, p=0.0121) was observed in the first month of the intervention period, after implementation of the triage algorithm. A comprehensive prevention programme targeting patients and environment can reduce self-reported incivility and verbal violence against healthcare workers in an OED. NCT02015884

Geriatric Patient Safety Indicators Based on Linked Administrative Health Data to Assess Anticoagulant-Related Thromboembolic and Hemorrhagic Adverse Events in Older Inpatients: A Study Proposal.

Frail older people with multiple interacting conditions, polypharmacy, and complex care needs are particularly exposed to health care-related adverse events. Among these, anticoagulant-related thromboembolic and hemorrhagic events are particularly frequent and serious in older inpatients. The growing use of anticoagulants in this population and their substantial risk of toxicity and inefficacy have therefore become an important patient safety and public health concern worldwide. Anticoagulant-related adverse events and the quality of anticoagulation management should thus be routinely assessed to improve patient safety in vulnerable older inpatients. This project aims to develop and validate a set of outcome and process indicators based on linked administrative health data (ie, insurance claims data linked to hospital discharge data) assessing older inpatient safety related to anticoagulation in both Switzerland and France, and enabling comparisons across time and among hospitals, health territories, and countries. Geriatric patient safety indicators (GPSIs) will assess anticoagulant-related adverse events. Geriatric quality indicators (GQIs) will evaluate the management of anticoagulants for the prevention and treatment of arterial or venous thromboembolism in older inpatients. GPSIs will measure cumulative incidences of thromboembolic and bleeding adverse events based on hospital discharge data linked to insurance claims data. Using linked administrative health data will improve GPSI risk adjustment on patients' conditions that are present at admission and will capture in-hospital and postdischarge adverse events. GQIs will estimate the proportion of index hospital stays resulting in recommended anticoagulation at discharge and up to various time frames based on the same electronic health data. The GPSI and GQI development and validation process will comprise 6 stages: (1) selection and specification of candidate indicators, (2) definition of administrative data-based algorithms, (3) empirical measurement of indicators using linked administrative health data, (4) validation of indicators, (5) analyses of geographic and temporal variations for reliable and valid indicators, and (6) data visualization. Study populations will consist of 166,670 Swiss and 5,902,037 French residents aged 65 years and older admitted to an acute care hospital at least once during the 2012-2014 period and insured for at least 1 year before admission and 1 year after discharge. We will extract Swiss data from the Helsana Group data warehouse and French data from the national health insurance information system (SNIIR-AM). The study has been approved by Swiss and French ethics committees and regulatory organizations for data protection. Validated GPSIs and GQIs should help support and drive quality and safety improvement in older inpatients, inform health care stakeholders, and enable international comparisons. We discuss several limitations relating to the representativeness of study populations, accuracy of administrative health data, methods used for GPSI criterion validity assessment, and potential confounding bias in comparisons based on GQIs, and we address these limitations to strengthen study feasibility and validity

Control limits to identify outlying hospitals based on risk-stratification.

Outcome indicators are routinely used to compare hospitals with respect to quality of care. Indicators might be based on observed proportions of adverse events (binary outcomes) or observed averages of e.g. lengths or costs of hospital stays (continuous outcomes). These observed values are compared with expected ones in an average hospital, which might be estimated from a reference sample and should be appropriately adjusted for the case mix of patients. One possibility to achieve a reliable adjustment is to stratify the patients according to their risks, where each patient belongs to one and only one stratum. Control limits calculated under the null hypothesis of an average hospital, allowing to decide whether a discrepancy between an observed and an expected value might be explained by chance or not, are then plotted around the indicator, such that hospitals falling above those control limits are detected as being statistically worse than an average hospital. Calculation of valid control limits is however not always obvious. In this article, we propose a simple and unified framework to calculate such control limits when adjustment is based on stratification, where we allow to distinguish and disentangle the variability explained by stratification and the variability due to chance, where we take into account the uncertainty about the estimation of the expected values, and where it is possible not only to detect those hospitals which are statistically worse, but also those which are statistically much worse than an average hospital. The method applies both to binary and continuous outcomes and is illustrated on Swiss hospital discharge data

Données de santé : le nouvel or numérique, mais pour qui ? [Health data: the new digital gold, but for whom?]

Rapidly growing health-related data have the potential to improve health and healthcare, as well as to make health systems more efficient and focused on patients' needs. Their efficient and secure management represents major technological, organizational and societal challenges. Currently too compartmentalized and insufficiently accessible, these data are often in the hands of private providers and their collection does not necessarily guarantee data security and privacy protection. Professionals as well as some private for-profit companies are on the lookout for this new digital "gold". It is therefore urgent to define a democratic and legal framework for the governance, collection and use of health data in the highly decentralized and fragmented Swiss context

Asylum Seekers' Responses to Government COVID-19 Recommendations: A Cross-sectional Survey in a Swiss Canton.

Asylum seekers face multiple language, cultural and administrative barriers that could result in the inappropriate implementation of COVID-19 measures. This study aimed to explore their knowledge and attitudes to recommendations about COVID-19. We conducted a cross-sectional survey among asylum seekers living in the canton of Vaud, Switzerland. We used logistic regressions to analyze associations between knowledge about health recommendations, the experience of the pandemic and belief to rumors, and participant sociodemographic characteristics. In total, 242 people participated in the survey, with 63% of men (n = 150) and a median age of 30 years old (IQR 23-40). Low knowledge was associated with linguistic barriers (aOR 0.36, 95% CI 0.14-0.94, p = 0.028) and living in a community center (aOR 0.43, 95% CI 0.22-0.85, p = 0.014). Rejected asylum seekers were more likely to believe COVID-19 rumors (aOR 2.81, 95% CI 1.24-6.36, p = 0.013). This survey underlines the importance of tailoring health recommendations and interventions to reach asylum seekers, particularly those living in community centers or facing language barriers

Development of elderly patient safety indicators using Swiss and French administrative linked data

Background and objectives: Population ageing has hugely increased hospital utilization and expenditures in Europe. Older inpatients aged 65 and over account now for half of acute care hospitals’ admissions and bed-days. However, frailty, chronic multimorbidity, disability, polypharmacy and the complexity of care expose elderly inpatients to an increased risk of potentially preventable adverse events (PPAEs). According to the Swiss Health2020 Reform and the French National Health Strategy that both promote safety measurements in inpatient and outpatient settings, we aim to develop and validate in-hospital and post-hospital elderly patient safety indicators (EPSIs) using hospital administrative data linked to insurance claims data to inform health policies, help patients’ choice, and improve equity and efficiency

Facing the COVID-19 Pandemic: A Mixed-Method Analysis of Asylum Seekers' Experiences and Worries in the Canton of Vaud, Switzerland.

Objectives: The clinical and social burden of the COVID-19 pandemic were high among asylum seekers (ASs). We aimed to understand better ASs' experiences of the pandemic and their sources of worries. Methods: Participants (n = 203) completed a survey about their worries, sleep disorders, and fear of dying. We also conducted semi-structured interviews with ASs living in a community center (n = 15), focusing on how social and living conditions affected their experiences and worries. Results: ASs in community centers experienced more sleep disorders related to the COVID-19 pandemic than those living in private apartments (aOR 2.01, p = 0.045). Similarly, those with lower education had greater fear for their life due to the COVID-19 pandemic (aOR 2.31, p = 0.015). Qualitative findings showed that sharing living spaces was an important source of worries for ASs and that protective measures were perceived to increase social isolation. Conclusion: Our study highlighted the impact of the COVID-19 pandemic for ASs and the importance of tailoring public health measures to their needs and living conditions