Influence of Pharmaceutical Copayment on Emergency Hospital Admissions: A 1978-2018 Time Series Analysis in Spain.

No studies have evaluated the influence of pharmaceutical copayment on hospital admission rates using time series analysis. Therefore, we aimed to analyze the relationship between hospital admission rates and the influence of the introduction of a pharmaceutical copayment system (PCS). In July 2012, a PCS was implemented in Spain, and we designed a time series analysis (1978-2018) to assess its impact on emergency hospital admissions. Hospital admission rates were estimated between 1978 and 2018 each month using the Hospital Morbidity Survey in Spain (the number of urgent hospital admissions per 100,000 inhabitants). This was conducted for men, women and both and for all-cause, cardiovascular and respiratory hospital discharges. Life expectancy was obtained from the National Institute of Statistics. The copayment variable took a value of 0 before its implementation (pre-PCS: January 1978-June 2012) and 1 after that (post-PCS: July 2012-December 2018). ARIMA (Autoregressive Integrated Moving Average) (2,0,0)(1,0,0) models were estimated with two predictors (life expectancy and copayment implementation). Pharmaceutical copayment did not influence hospital admission rates (with p-values between 0.448 and 0.925) and there was even a reduction in the rates for most of the analyses performed. In conclusion, the PCS did not influence hospital admission rates. More studies are needed to design health policies that strike a balance between the amount contributed by the taxpayer and hospital admission rates.

Clinical relevance of an intervention assessed by a meta-analysis of randomized clinical trials.

OBJECTIVES: Many meta-analyses usually omit the number needed to treat, or perform the calculation incorrectly, despite its importance in clinical decision-making. Accordingly, we will explain in an easily understandable way how to perform this procedure to assess the clinical relevance of the intervention. STUDY DESIGN AND SETTING: The expressions of the Cochrane Library and the concepts of clinical relevance and evidence-based medicine were applied. Simple cutoff points were also established to facilitate the task of interpreting results. The method was applied to two published meta-analyses to illustrate its application to real cases (treatment nonadherence). RESULTS: In the first example, with a risk in the control group ranging from 0.22 to 0.70, sending mobile phone messages to remind chronic patients to take their medication is clinically relevant with a high degree of evidence. For the second example (single-pill regimen in patients suffering from hypertension and/or dyslipidemia after 6 months), the range of the assumed control risk was between 0.28 and 0.57. CONCLUSION: The constructed algorithm could be applied to published meta-analyses or incorporated systematically in all meta-analyses with these characteristics.

Clinical effectiveness of a cardiology outpatient management plan to reduce inefficiency in consultations.

Objectives: Longer delays in carrying out complementary tests in cardiology services have resulted in patients arriving for consultation without these tests being performed (inefficient consultations). To ameliorate this situation, a management-based intervention was designed, optimizing the available resources and modifying the appointment system. Therefore, our objective was to determine the effectiveness of this intervention to reduce the number of inefficient consultations and improve the clinical care process.Methods: A non-randomized experimental study comparing two periods (pre- and post-intervention) was designed, analyzing a total of 473 outpatients attending cardiology consultations in a Spanish region in February 2014 (pre-intervention) and 441 patients attending cardiology consultations in November 2014 (post-intervention). The outcome of management measures aimed at optimizing coordination in outpatient care to reduce inefficient consultations was analyzed. After the visit, treatment modifications, requests for new examinations or tests, outpatient discharges, and new diagnoses were evaluated.Results: In the pre-intervention period, 37.2% of the patients had not had the tests performed, while in the post-intervention period, this figure dropped to 10.7% (p < 0.001). When the patients had all the tests completed, there was an increase in the number of new examinations (p < 0.001), outpatient discharges (p < 0.001) and new diagnoses (p = 0.004). Treatment modifications were not significant (p = 0.223).Conclusions: The intervention proved effective, clinically relevant, and statistically significant in reducing the proportion of inefficient consultations, thereby enabling continuation of the clinical care process.

Development, and Internal, and External Validation of a Scoring System to Predict 30-Day Mortality after Having a Traffic Accident Traveling by Private Car or Van: An Analysis of 164,790 Subjects and 79,664 Accidents.

Predictive factors for fatal traffic accidents have been determined, but not addressed collectively through a predictive model to help determine the probability of mortality and thereby ascertain key points for intervening and decreasing that probability. Data on all road traffic accidents with victims involving a private car or van occurring in Spain in 2015 (164,790 subjects and 79,664 accidents) were analyzed, evaluating 30-day mortality following the accident. As candidate predictors of mortality, variables associated with the accident (weekend, time, number of vehicles, road, brightness, and weather) associated with the vehicle (type and age of vehicle, and other types of vehicles in the accident) and associated with individuals (gender, age, seat belt, and position in the vehicle) were examined. The sample was divided into two groups. In one group, a logistic regression model adapted to a points system was constructed and internally validated, and in the other group the model was externally validated. The points system obtained good discrimination and calibration in both the internal and the external validation. Consequently, a simple tool is available to determine the risk of mortality following a traffic accident, which could be validated in other countries.

Quality assessment of meta-analyses evaluating randomized clinical trials to improve the prognosis of septic shock: an overview of systematic reviews.

Objective: Clinical guidelines for the treatment of septic shock are based on the studies with the best scientific evidence, which are meta-analyses of clinical trials. However, these meta-analyses may have methodological limitations that prevent their conclusions from being extrapolated to routine clinical practice. Therefore, the objective of this study is to determine the quality of these meta-analyses through a systematic review.Methods: In this systematic review, we searched MEDLINE, Scopus and EMBASE from inception to May 2019. We selected meta-analyses from clinical trials that determined the effectiveness of an intervention in reducing the incidence of mortality in patients with septic shock. All items were extracted from the Overview Quality Assessment Questionnaire (OQAQ), which collects information from both systematic reviews and meta-analyses.Results: A total of 34 studies were included. Most elements of the OQAQ were conducted satisfactorily, although 35.3% of meta-analyses did not use a quality assessment of the studies included in other analyses. In 52.9% of meta-analyses, the quality of the studies was high or very high.Conclusions: The methods used to obtain the results should be taken into account when recommending an intervention to treat septic shock if the evidence comes from a meta-analysis of the analyzed characteristics.

A critical appraisal of the clinical applicability and risk of bias of the predictive models for mortality and recurrence in patients with oropharyngeal cancer: Systematic review.

The use of predictive models is becoming widespread. However, these models should be developed appropriately (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modeling Studies [CHARMS] and Prediction model Risk Of Bias ASsessment Tool [PROBAST] statements). Concerning mortality/recurrence in oropharyngeal cancer, we are not aware of any systematic reviews of the predictive models. We carried out a systematic review of the MEDLINE/EMBASE databases of those predictive models. In these models, we analyzed the 11 domains of the CHARMS statement and the risk of bias and applicability, using the PROBAST tool. Six papers were finally included in the systematic review and all of them presented high risk of bias and several limitations in the statistical analysis. The applicability was satisfactory in five out of six studies. None of the models could be considered ready for use in clinical practice.