Did the organization of primary care practices during the COVID-19 pandemic influence quality and safety? - an international survey.

BACKGROUND: Changes in demographics with an older population, the illness panorama with increasing prevalence of non-communicable diseases, and the shift from hospital care to home-based care place demand on primary health care, which requires multiprofessional collaboration and team-based organization of work. The COVID-19 pandemic affected health care in various ways, such as heightened infection control measures, changing work practices, and increased workload. OBJECTIVES: This study aimed to investigate the association between primary care practices' organization, and quality and safety changes during the COVID-19 pandemic. DESIGN: Data were collected from 38 countries in a large online survey, the PRICOV-19 study. For this paper, the participating practices were categorized as "Only GPs", comprising practices with solely general practitioners (GPs) and/or GP trainees, without any other health care professionals (n = 1,544), and "Multiprofessional," comprising practices with at least one GP or GP trainee and one or more other health professionals (n = 3,936). RESULTS: Both categories of practices improved in infection control routines when compared before and during the COVID-19 pandemic. A larger proportion of the multiprofessional practices changed their routines to protect vulnerable patients. Telephone triage was used in more "Multiprofessional" practices, whereas "Only GPs" were more likely to perform video consultations as an alternative to physical visits. Both types of practices reported that the time to review new guidelines and scientific literature decreased during the pandemic. However, both had more meetings to discuss directives than before the pandemic. CONCLUSIONS: Multiprofessional teams were keener to introduce changes to the care organization to protect vulnerable patients. However, practices with only GPs were found to be more aligned with video consultations, perhaps reflecting the close patient-doctor relationship. In contrast, telephone triage was used more in multiprofessional teams.

COVID-19: Forecasting confirmed cases and deaths with a simple time series model.

Forecasting the outcome of outbreaks as early and as accurately as possible is crucial for decision-making and policy implementations. A significant challenge faced by forecasters is that not all outbreaks and epidemics turn into pandemics, making the prediction of their severity difficult. At the same time, the decisions made to enforce lockdowns and other mitigating interventions versus their socioeconomic consequences are not only hard to make, but also highly uncertain. The majority of modeling approaches to outbreaks, epidemics, and pandemics take an epidemiological approach that considers biological and disease processes. In this paper, we accept the limitations of forecasting to predict the long-term trajectory of an outbreak, and instead, we propose a statistical, time series approach to modelling and predicting the short-term behavior of COVID-19. Our model assumes a multiplicative trend, aiming to capture the continuation of the two variables we predict (global confirmed cases and deaths) as well as their uncertainty. We present the timeline of producing and evaluating 10-day-ahead forecasts over a period of four months. Our simple model offers competitive forecast accuracy and estimates of uncertainty that are useful and practically relevant.

Patient outcomes vs. service workload: an analysis of outcomes in the burn service of England and Wales.

BACKGROUND: Patient outcomes in specialist burns units have been used as a metric of care needs and quality. Besides patient factors there are service factors that might influence Length of Stay (LOS) and mortality, e.g. pressure on beds. Although the bed needs of UK hospitals have dropped significantly over the past three decades, with changes in policies and practices, recent reports suggest that hospitals have 90% bed occupancy for 48 weeks of the year. In the UK, the specialist burn injury service is organised so that patients are assessed on arrival at hospital, and those needing admission are found a nearby bed in a suitable unit through the National Burn Bed Bureau. The aim of this study was to investigate the effect on outcomes of service pressures due to shortages of beds. METHODS: We took an extract of the anonymised patient data from the specialised burn injury database, iBID, and created a new database based on matching that data with bed availability data provided by the national Burn Bed Bureau. Cox proportional hazard modelling was used for analysis to investigate if there is an impact of bed occupancy (a proxy measure of workload) on LOS. RESULTS: Cox proportional hazard modelling indicated that half of the services in England and Wales are less likely to discharge a patient if the bed availability is high. Two of the services have abnormally high bed availability and LOS, therefore a model without these two services indicates a general reluctance to discharge patients when beds are available. CONCLUSIONS: It is possible that the effect we observed is a result of gaming as service providers are paid by the number of admissions. In addition, providers many not all give the same level of accuracy of bed availability information to the NBBB: some may under report availability, for example at times of high pressure on staff. Furthermore, burn services may not empty beds to avoid being filled up by work from other specialties, thus making them unable to admit a burn when referred.

Characteristics of primary care practices associated with patient education during COVID-19: results of the cross-sectional PRICOV-19 study in 38 countries.

BACKGROUND: In response to the COVID-19 pandemic, the World Health Organization established a number of key recommendations such as educational activities especially within primary care practices (PCPs) which are a key component of this strategy. This paper aims to examine the educational activities of PCPs during COVID-19 pandemic and to identify the factors associated with these practices across 38 countries. METHODS: A "Patient Education (PE)" score was created based on responses to six items from the self-reported questionnaire among PCPs (n = 3638) compiled by the PRICOV-19 study. Statistical analyses were performed on 3638 cases, with PCPs with missing PE score values were excluded. RESULTS: The PE score features a mean of 2.55 (SD = 0.68) and a median of 2.50 (2.16 - 3.00), with a maximum of 4.00, and varies quite widely between countries. Among all PCPs characteristics, these factors significantly increase the PE score: the payment system type (with a capitation payment system or another system compared to the fee for service), the perception of average PCP with patients with chronic conditions and the perception of adequate governmental support. CONCLUSION: The model presented in this article is still incomplete and requires further investigation to identify other configuration elements favorable to educational activities. However, the results already highlight certain levers that will enable the development of this educational approach appropriate to primary care.

Developing and validating a predictive model for future emergency hospital admissions.

Although many emergency hospital admissions may be unavoidable, a proportion of these admissions represent a failure of the care system. The adverse consequences of avoidable emergency hospital admissions affect patients, carers, care systems and substantially increase care costs. The aim of this study was to develop and validate a risk prediction model to estimate the individual probability of emergency admission in the next 12 months within a regional population. We deterministically linked routinely collected data from secondary care with population level data, resulting in a comprehensive research dataset of 190,466 individuals. The resulting risk prediction tool is based on a logistic regression model with five independent variables. The model indicated a discrimination of area under the receiver operating characteristic curve of 0.9384 (95% CI 0.9325-0.9443). We also experimented with different probability cut-off points for identifying high risk patients and found the model's overall prediction accuracy to be over 95% throughout. In summary, the internally validated model we developed can predict with high accuracy the individual risk of emergency admission to hospital within the next year. Its relative simplicity makes it easily implementable within a decision support tool to assist with the management of individual patients in the community.

Safety Culture and the Positive Association of Being a Primary Care Training Practice during COVID-19: The Results of the Multi-Country European PRICOV-19 Study.

The day-to-day work of primary care (PC) was substantially changed by the COVID-19 pandemic. Teaching practices needed to adapt both clinical work and teaching in a way that enabled the teaching process to continue, while maintaining safe and high-quality care. Our study aims to investigate the effect of being a training practice on a number of different outcomes related to the safety culture of PC practices. PRICOV-19 is a multi-country cross-sectional study that researches how PC practices were organized in 38 countries during the pandemic. Data was collected from November 2020 to December 2021. We categorized practices into training and non-training and selected outcomes relating to safety culture: safe practice management, community outreach, professional well-being and adherence to protocols. Mixed-effects regression models were built to analyze the effect of being a training practice for each of the outcomes, while controlling for relevant confounders. Of the participating practices, 2886 (56%) were non-training practices and 2272 (44%) were training practices. Being a training practice was significantly associated with a lower risk for adverse mental health events (OR: 0.83; CI: 0.70-0.99), a higher number of safety measures related to patient flow (Beta: 0.17; CI: 0.07-0.28), a higher number of safety incidents reported (RR: 1.12; CI: 1.06-1.19) and more protected time for meetings (Beta: 0.08; CI: 0.01-0.15). No significant associations were found for outreach initiatives, availability of triage information, use of a phone protocol or infection prevention measures and equipment availability. Training practices were found to have a stronger safety culture than non-training practices. These results have important policy implications, since involving more PC practices in education may be an effective way to improve quality and safety in general practice.

Mental Health Disorders During the COVID-19 Outbreak in Cyprus.

Cyprus has been affected by COVID-19 since March 2019. With a case fatality rate of 2.6% (until June 2020) and the social isolation measures enforced on the population, the population's mental health has been affected. We aimed to assess the mental health burden of the Cypriot population during the outbreak and to explore the potential influence factors. Using a web-based cross-sectional survey, we collected data from 216 volunteers regarding demographic data, COVID-19-related knowledge, generalized anxiety disorder (GAD), and major depressive symptoms. The overall prevalence of GAD and major depressive symptoms of the public were 13.89% and 8.33%, respectively. No demographic had shown any statistical significance with GAD. The younger age group of the study showed a statistically significant association with major depressive symptoms when compared to the adult population in both univariate and multivariable analyses. Our study identified a mental health burden of the Cypriot population, especially the younger age groups. As part of the preparedness for situations as the one we are experiencing and the future impact the pandemic may have on society, interventions should be focused on vulnerable groups of the population to alleviate the psychosocial effects.

Are medical outliers associated with worse patient outcomes? A retrospective study within a regional NHS hospital using routine data.

OBJECTIVE: To explore the quality and safety of patients' healthcare provision by identifying whether being a medical outlier is associated with worse patient outcomes. A medical outlier is a hospital inpatient who is classified as a medical patient for an episode within a spell of care and has at least one non-medical ward placement within that spell. DATA SOURCES: Secondary data from the Patient Administration System of a district general hospital were provided for the financial years 2013/2014-2015/2016. The data included 71 038 medical patient spells for the 3-year period. STUDY DESIGN: This research was based on a retrospective, cross-sectional observational study design. Multivariate logistic regression and zero-truncated negative binomial regression were used to explore patient outcomes (in-hospital mortality, 30-day mortality, readmissions and length of stay (LOS)) while adjusting for several confounding factors. PRINCIPAL FINDINGS: Univariate analysis indicated that an outlying medical in-hospital patient has higher odds for readmission, double the odds of staying longer in the hospital but no significant difference in the odds of in-hospital and 30-day mortality. Multivariable analysis indicates that being a medical outlier does not affect mortality outcomes or readmission, but it does prolong LOS in the hospital. CONCLUSIONS: After adjusting for other factors, medical outliers are associated with an increased LOS while mortality or readmissions are not worse than patients treated in appropriate specialty wards. This is in line with existing but limited literature that such patients experience worse patient outcomes. Hospitals may need to revisit their policies regarding outlying patients as increased LOS is associated with an increased likelihood of harm events, worse quality of care and increased healthcare costs.

A review of the international Burn Injury Database (iBID) for England and Wales: descriptive analysis of burn injuries 2003-2011.

OBJECTIVE: To describe, for the first time, distribution (by geography, age, sex) and time trends in burn injury in England and Wales over the period that the international Burn Injury Database (iBID) has been in place. SETTING: Data from the iBID for the years 2003-2011 were used for a retrospective descriptive observational study of specialised services workload and admissions in England and Wales. PARTICIPANTS: All patients who have been visited or admitted to the burn injury specialised health service of England and Wales during the time period 2003-2011. Data cleaning was performed omitting patients with incomplete records (missingness never exceeded 5%). OUTCOME MEASURES: Workload, admissions, mortality, length of stay (LOS), geographical distribution, sex differences, age differences, total burn surface area, mechanism of Injury. RESULTS: During 2003-2011, 81,181 patients attended the specialised burn service for assessment and admission in England and Wales. Of these, 57,801 were admitted to the services. Males accounted for 63% of the total workload in specialised burn injury services, and females for 37%. The median (IQR) burn surface area was 1.5% (3.5%). The most frequent reason for burn injury was scald (38%). The median (IQR) age for all the referred workload for both genders was 21 (40). The overall mortality of the admitted patients was 1.51% and the median (IQR) LOS was 1 (5) days. CONCLUSIONS: Mortality from burn injuries in England and Wales is decreasing in line with western world trends. There is an observed increase in admissions to burn services but that could be explained in various ways. These results are vital for service development and planning, as well as the development and monitoring of prevention strategies and for healthcare commissioning.

Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

INTRODUCTION: Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. METHODS: An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. RESULTS: All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. DISCUSSION: The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts.

A model of British in-hospital mortality among burns patients.

INTRODUCTION: Mortality among patients treated in hospital for burn is routinely examined, but none of the many models in use in the UK was developed using nationwide data. The aim of this research was to develop a prediction model using national data, representative of the British population. METHODS: Data were gathered from the international Burns Injury Database (iBID) and included 66,611 patients from England and Wales from 2003 to 2011. Core variables were selected following systematic review of the literature, expert consultation and then supplemented with variables selected through logistic regression. Discrimination and calibration of the model were assessed using the area under the receiver operating characteristic curve and the Hosmer-Lemeshow χ2 test respectively. RESULTS: Overall mortality for the years of the study in England and Wales was 1.27%. Mortality was predicted by age (and quadratic term) total burn surface area, presence of inhalation injury, presence of existing disorders and category of injury. The model gave a discrimination area under the curve of 0.97 in both internal and external validation. The calibration of the model gave a Hosmer-Lemeshow χ2 of 11.9 (p=0.3). CONCLUSION: We have reported a strongly predictive and theoretically well-founded model of in-patient mortality using nine years of data from all burn care services in England and Wales. We recommend this model for British burn service development and for international consideration of the variables to use in developing similar models with other data sources.

Impacts of a national strategy to reduce population salt intake in England: serial cross sectional study.

BACKGROUND: The UK introduced an ambitious national strategy to reduce population levels of salt intake in 2003. The aim of this study was to evaluate the impact of this strategy on salt intake in England, including potential effects on health inequalities. METHODS: Secondary analysis of data from the Health Survey for England. Our main outcome measure was trends in estimated daily salt intake from 2003-2007, as measured by spot urine. Secondary outcome measures were knowledge of government guidance and voluntary use of salt in food preparation over this time period. RESULTS: There were significant reductions in salt intake between 2003 and 2007 (-0.175 grams per day per year, p<0.001). Intake decreased uniformly across all other groups but remained significantly higher in younger persons, men, ethnic minorities and lower social class groups and those without hypertension in 2007. Awareness of government guidance on salt use was lowest in those groups with the highest intake (semi-skilled manual v professional; 64.9% v 71.0% AOR 0.76 95% CI 0.58-0.99). Self reported use of salt added at the table reduced significantly during the study period (56.5% to 40.2% p<0.001). Respondents from ethnic minority groups remained significantly more likely to add salt during cooking (white 42.8%, black 74.1%, south Asian 88.3%) and those from lower social class groups (unskilled manual 46.6%, professional 35.2%) were more likely to add salt at the table. CONCLUSIONS: The introduction a national salt reduction strategy was associated with uniform but modest reductions in salt intake in England, although it is not clear precisely which aspects of the strategy contributed to this. Knowledge of government guidance was lower and voluntary salt use and total salt intake was higher among occupational and ethnic groups at greatest risk of cardiovascular disease.