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.

The aim of this study was to assess the validity of the estimation of 24-h urinary sodium (UNa) and urinary potassium (UK) excretion obtained through four formulae based on occasional urine samples. We analysed 2399 individuals (51% females) aged 18 to 96 years representatives of Portuguese population. Tanaka, Kawasaki, INTERSALT and NHANES formulae were used to predict 24-h UNa and UK excretions from spot morning urinary samples (OUrS). We compared it with validated real 24-h urine samples (VUrS) (24-h UNa: 4052 ± 1432 mg/day, 24-h UK = 2928 ± 1004 mg/day). We compared observed vs. estimated measurements by examining bias (observed minus predicted UNa and UK), the correlation and intraclass correlation (ICC) coefficients between measurements, and Bland–Altman plots. We analysed the differences between observed and estimated Na and K excretion across subgroups defined by quintiles of observed Na and K excretion and subgroups defined hypertension status and control. The area under the ROC curve was used to assess the discriminatory capacity of formulas between high-intake salt individuals from low-intake individuals, taking the arbitrary values 3000 and 3900 mg/day for, respectively, Na and K intake. Formulas produced significant mean bias for UNa: Kawasaki−1277, INTERSALT−569, NHANES−116 and for UK Tanaka−754, Kawasaki−95 mg/day. Correlation coefficients were less than 0.360 and ICC coefficients were all less than 0.458 for both UNa and UK estimations. Bias varied across quintiles with overestimation of UNa at lower quintiles (by 29–105%) and underestimation at higher quintile (by 7–37%) regardless of formula. The Bland–Altman plots indicated a high dispersion of the estimates biases regardless of the formulae and normotension/hypertension condition particularly at higher levels. All formulas exhibited an area under the receiver operating characteristic curve below 0.67 both in normotensive individuals and hypertensive individuals. We found a poor agreement between estimated and observed measurements of UNa and UK in our large population. All these formulas incur in over- or underestimations of UNa and UK excretion that may be unreliable for clinical evaluation of individual's and mean population daily UNa and UK excretion.

Cost of cardiovascular disease prevention: towards economic evaluations in prevention programs

Simulation provides a risk free and controllable environment for training of healthcare providers. The limited realism of available simulators and training programs impedes immersive training in obstetric emergencies. In developed countries, intrapartum monitoring in high-risk cases involves continuous evaluation of foetal heart rate and uterine contractions signals. We present an essential component of a high-fidelity simulator for normal and critical situations in labour and delivery, namely an intrauterine pressure generator. The signal model behind the generator consists of a truncated Gaussian curve with the programmable features: amplitude, frequency, duration, and resting tone. Through analysis of 44h of physiological data, we demonstrate that the natural variability of these features and of the baseline pressure can be approximated by deterministic trends and stationary stochastic processes. Signal parameters can be controlled by simulation instructors, scripts, or other models to reflect different patients, pathologies, and evolving clinical situations. Twelve 40-min tracings reflecting three different patients in labour were presented to three clinical experts, who attributed similar realism scores to simulated and to real tracings.