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Nowadays, evaluating the quality of health services, especially in primary health care (PHC), is increasingly important. In a historical perspective, the Department of Health (United Kingdom) developed and proposed a range of indicators in 1998, and lately several health, social and political organizations have defined and implemented different sets of PHC quality indicators. Some systematic reviews in PHC quality indicators are reported but only in specific contexts and conditions. The aim of this study is to characterize and provide a list of indicators discussed in the literature to support managers and clinicians in decision-making processes, through an umbrella review on PHC quality indicators. The methodology was performed according to PRISMA Statement. Indicators from 33 eligible systematic reviews were categorized according to the dimensions of care, function, type of care, domains and condition contexts. Of a total of 727 indicators or groups of indicators, 74.5% (n = 542) were classified in process category and 89.5% (n = 537) with chronic type of care (n = 428; 58.8%) and effective domain (n = 423; 58.1%) with the most frequent values in categorizations by dimensions. The results of this overview of reviews are valuable and imply the need for future research and practice regarding primary health care quality indicators in the most varied conditions and contexts to generate new discussions about their use, comparison and implementation.

Purpose The main goal of this study is to identify the associated factors with avoidable admissions in ED, comparing pre-COVID and COVID periods. Methods This was retrospective study that took place in a Paediatric Emergency Department of a metropolitan, university-affiliated hospital in Portugal. All visits to paediatric emergency department between 2014 and 2020 were considered. Results There was a decrease of 7.2% points in avoidable visits between pre-COVID and COVID periods. Considering both periods, this study identifies older ages, being admitted to the paediatric emergency department between 4 and 7 a.m., referral and having visited the emergency department previously within 72 h as major factors associated with a reduced likelihood for avoidable visits. On the other hand, it identifies an increased likelihood of avoidable visits in the 3 to 5 years old age group, visits that occurred during the Summer and visits that occurred between 8 and 11 p.m. When considering what changed between pre-COVID and COVID periods, while having visited the paediatric emergency department 72 h prior made it less likely for the patient to be an avoidable visit during the pandemic period, this tendency has inverted, making it more likely for return visits to be avoidable. Conclusions The relatively low decrease in avoidable visits’ ratios between pre-COVID and COVID periods, associated with the similar distribution of attendance during the day and lower odds ratio of avoidable visits during periods when primary care is available, suggests that avoidable visits are a chronical problem of the National Health system’s structure and its usage, not having a single factor nor a combination of factors as a driving force. Nevertheless, this study identified several factors associated with avoidable visits to the emergency department. Therefore, it can aid policy makers to create targeted interventions to mitigate this problem. Significance What is Known - Excess of avoidable visits have been a problem in the Emergency Department for several decades. - The fear experienced during COVID-19 pandemic, influenced the visits to the emergency departments. What is New - The change in demand introduced by the COVID-19 was used to provide insights regarding the factors associated with avoidable visits. - A triage system’s agnostic definition of avoidable visit was chosen, to better reflect the visit’s lack of necessity of hospital resources, including hospital admission.

The need to control the sanitary situation during the COVID-19 pandemic has led governments to implement several restrictions with substantial social and economic impacts. We explored people’s trade-offs in terms of their income, life restrictions, education, and poverty in the society, compared to their willingness to avoid deaths. We applied a web-based discrete choice experiment to elicit preferences of the Portuguese citizens for these attributes and computed the marginal rate of substitution in terms of avoided deaths. We recorded 2,191 responses that faced the possibility of having 250 COVID-19 related deaths per day as the worst possible outcome from the choice levels presented. Estimates suggested that individuals would be willing to sacrifice 30% instead of 10% of their income to avoid approximately 47 deaths per day during the first six months of 2021. For the same period, they would also accept 30% of the students’ population to become educationally impaired, instead of 10%, to avoid approximately 25 deaths; a strict lockdown, instead of mild life restrictions, to avoid approximately 24 deaths; and 45% of the population to be in risk of poverty, instead of 25%, to avoid approximately 101 deaths. Our paper shows that avoiding deaths was strongly preferred to the remaining societal impacts; and that being a female, as well as working on site, led individuals to be more averse to such health hazards. Furthermore, we show how a DCE can be used to assess the societal support to decision-making during times of crisis.

Background Transitional cell carcinoma (TCC) accounts for around 95% of bladder cancers and is the 4th most common cancer among men and the tenth most common in women, in the US. There is a constant need to clarify current TCC incidence and mortality rates among different population groups for better clinical practice guidelines. We aimed to describe the TCC incidence and incidence-based mortality by demographic and tumor-related characteristics over the last 40 years in the US. Methods We obtained data from the SEER 18 registries to study TCC cases that were diagnosed between the years 1973 and 2014. We calculated incidence rates and incidence-based mortality rates in different demographic and tumor-related characteristics and expressed rates by 100,000 person-years. We then calculated the annual changes in incidence and incidence-based mortality rates and displayed them as annual percent changes (APCs). Results There were 182,114 patients with TCC between 1973 and 2014 in the United States. Overall incidence rates of TCC increased 0.16% (95% CI, 0.02–0.30, p  = .02) per year over the study period. However, the incidence declined significantly since 2007; (95%CI,-1.89- -0.77, p  < .001), except among the elderly and African Americans, which increased significantly over the study period. Overall TCC mortality rates did not change over the study period. However, since 2000 it started to decrease significantly. Conclusion TCC incidence and incidence-based mortality rates had been showing significant increases over the previous decades. However, significant declines in both incidence and incidence-based mortality rates have been observed over the recent years, except in some patients with certain racial groups. Improved understanding of the etiological and ecological factors of TCC could lead to further declines in incidence and incidence-based mortality rates.

The COVID-19 pandemic has led to disruptive changes worldwide, with different implications across countries. The evolution of citizens' concerns and behaviours over time is a central piece to support public policies. To unveil perceptions and behaviours of the Portuguese population regarding social and economic impacts of the COVID-19 pandemic, allowing for more informed public policies. Online panel survey distributed in three waves between March 13th and May 6th 2020. Data collected from a non-representative sample of 7,448 respondents includes socio-demographic characteristics and self-reported measures on levels of concern and behaviours related to COVID-19. We performed descriptive analysis and probit regressions to understand relationships between the different variables. Most participants (85%) report being at least very concerned with the consequences of the COVID-19 pandemic and social isolation reached a high level of adherence during the state of emergency. Around 36% of the sample anticipated consumption decisions, stockpiling ahead of the state of emergency declaration. Medical appointments suffered severe consequences, being re-rescheduled or cancelled. We find important variation in concerns with the economic impact across activity sectors. We show that high level of concern and behaviour adaptation in our sample preceded the implementation of lockdown measures in Portugal around mid-March. One month later, a large share of individuals had suffered disruption in their routine health care and negative impacts in their financial status.

Coded data are the basis of information systems in all countries that rely on Diagnosis Related Groups in order to reimburse/finance hospitals, including both administrative and clinical data. To identify the problems and barriers that affect the quality of the coded data is paramount to improve data quality as well as to enhance its usability and outcomes. This study aims to explore problems and possible solutions associated with the clinical coding process. Problems were identified according to the perspective of ten medical coders, as the result of four focus groups sessions. This convenience sample was sourced from four public hospitals in Portugal. Questions relating to problems with the coding process were developed from the literature and authors’ expertise. Focus groups sessions were taped, transcribed and analyzed to elicit themes. Variability in the documents used for coding, illegibility of hand writing when coding on paper, increase of errors due to an extra actor in the coding process when transcribed from paper, difficulties in the diagnoses’ coding, coding delay and unavailability of resources and tools designed to help coders, were some of the problems identified. Some problems were identified and solutions such as the standardization of the documents used for coding an episode, the adoption of the electronic coding, the development of tools to help coding and audits, and the recognition of the importance of coding by the management were described as relevant factors for the improvement of the quality of data.

A mixed methods bibliometric analysis was performed to ascertain the characteristic of scientific literature published in a 10-year period (2007–2016) regarding the application of remote sensing data in human health. A search was performed on the Scopus database, followed by manual revision using synthesis studies’ techniques, requiring the authors to sort through more than 8000 medical concepts to create the query, and to manually select relevant papers from over 2000 documents. From the initial 2752 papers identified, 520 articles were selected for analysis, showing that the United States ranked first, with a total of 250 (48.1% of the total) documents, followed by France and the United Kingdom, with 67 (12.9% of the total) and 54 (10.4% of the total) documents, respectively. When considering authorship, the top three authors were Vounatsou P (22 articles), Utzinger J (19 articles), and Vignolles C (13 articles). Regarding disease-specific keywords, malaria, dengue, and schistosomiasis were the most frequent keywords, occurring 142, 34, and 24 times, respectively. For some infectious diseases and other highly pathogenic or emerging infectious diseases, remote sensing has become a very powerful instrument. Also, several studies relate different environmental factors retrieved by remote sensing data with other diseases, such as asthma exacerbations. Health-related remote sensing publications are increasing and this paper highlights the importance of these related technologies toward better information and, ideally, better provision of healthcare. On the other hand, this paper provides an overall picture of the state of the research regarding the application of remote sensing data in human health and identifies the most active stakeholders e.g., authors and institutions in the field, informing possible new collaboration research groups.

IntroductionHealthcare expenditure, a common input used in health systems efficiency analyses is affected by population age structure. However, while age structure is usually considered to adjust health system outputs, health expenditure and other inputs are seldom adjusted. We propose methods for adjusting Health Expenditure per Capita (HEpC) for population age structure on health system efficiency analyses and assess the goodness-of-fit, correlation, reliability and disagreement of different approaches.MethodsWe performed a worldwide (188 countries) cross-sectional study of efficiency in 2015, using a stochastic frontier analysis. As single outputs, healthy life expectancy (HALE) at birth and at 65 years-old were considered in different models. We developed five models using as inputs: (1) HEpC (unadjusted); (2) age-adjusted HEpC; (3) HEpC and the proportion of 0–14, 15–64 and 65 + years-old; (4) HEpC and 5-year age-groups; and (5) HEpC ageing index. Akaike and Bayesian information criteria, Spearman’s rank correlation, intraclass correlation coefficient and information-based measure of disagreement were computed. ResultsModels 1 and 2 showed the highest correlation (0.981 and 0.986 for HALE at birth and HALE at 65 years-old, respectively) and reliability (0.986 and 0.988) and the lowest disagreement (0.011 and 0.014). Model 2, with age-adjusted HEpC, presented the lowest information criteria values.ConclusionsDespite different models showing good correlation and reliability and low disagreement, there was important variability when age structure is considered that cannot be disregarded. The age-adjusted HE model provided the best goodness-of-fit and was the closest option to the current standard.

Background Performance-based risk-sharing agreements (PBRSA) represent an innovative tool for managing uncertainty and balanced distribution of the financial risk of high-cost drugs. By linking reimbursement to real-world treatment performance, these agreements help mitigate budgetary impacts. This study poses an illustrative patient-level PBRSA reimbursement model for non-small cell lung cancer (NSCLC) immunotherapy based on collected real-world data (RWD). Methods A retrospective analysis of 266 patients with NSCLC treated with immunotherapy was performed. Progression-free survival (PFS) served as the primary outcome measure of therapeutic effectiveness. An illustrative patient-level PBRSA model was developed to quantify the manufacturer’s financial participation based on deviations from established PFS thresholds reported in randomised controlled trials (RCT). The manufacturer’s financial responsibility increased proportionally to greater deviations in patient outcomes from the RCT benchmark. Cost calculations were limited exclusively to the acquisition price of immunotherapies, excluding administration, toxicity management, and other indirect costs. The potential PBRSA scenario was compared with the current reimbursement situation. Results Using this reimbursement method, cost savings per checkpoint inhibitor for healthcare payers could represent between 27.3% and 66.2% of the total cost, depending on the individual PFS reached. For the RWD cohort of NSCLC patients unsuccessfully treated with pembrolizumab monotherapy was 57.5% (a reduction in cost to payers from $27 996 to $11 893 per patient); pembrolizumab in combination 51.7% ($33 595 to $16 237); nivolumab 37.1% ($5 608 to $3 531); atezolizumab 27.3% ($11 799 to $8 583); and durvalumab 66.2% ($44 005 to $14 882). Conclusions This study proposes an illustrative patient-level PBRSA reimbursement model leveraging real-world clinical data to enhance risk-sharing for high-cost therapies. Unlike conventional cost-effectiveness analyses, this method directly links clinical performance and manufacturer financial responsibility. Future research should integrate comprehensive cost considerations and validate model performance in broader clinical settings.

Introduction Population ageing increases long-term care (LTC) needs. Understanding which hospitalised patients are more likely to be discharged to LTC is essential for adapting services and policies. This study aims to assess clusters of hospitalised patients with a higher proportion of discharges to LTC (LTCD) in Portugal and to test clustering methods as a solution for the early identification of potential users using different approaches. Methods This nationwide Portuguese study used inpatient data from Portuguese hospitals between 2012 and 2017. The variables considered in this study were age, sex, principal diagnosis, comorbidities (identified using secondary diagnoses), admission type and hospital transfer. The main outcome of this analysis is discharge to long-term and maintenance units ( Unidades de Longa Duração e Manutenção —ULDM). Different approaches were applied to categorise the principal diagnosis for each inpatient episode, using ICD-9-CM and ICD-10-CM main groups, ICD-9-CM and ICD-10-CM more detailed categories, Clinical Classification Software (CCS) and CCS Refined (CCSR). Subsequently, hierarchical clustering techniques were applied to determine the number of clusters in each dataset and decision tree methods were used to characterise each cluster. Results A total of 4427 inpatient episodes (0.23%) were discharged to LTC. Across clustering methods, the proportion of patients discharged to LTC varied widely, from 0.7% to 60.8%. Certain categorisation methods, such as CCSM2, showed more concentrated high-risk groups compared to other methods with more categories. The models showed high performance (F1 score > 0.97). Conclusion The clustering results exhibit considerable variability when comparing the different approaches to categorising principal diagnoses. The “quality” of the principal diagnosis categorisation (i.e. the grouping method) overcomes the “quantity” (i.e., the number of categories). This can have important implications for health services and hospital management. Clustering methods serve as effective options for identifying high-risk groups, although different approaches should be assessed and compared.