Summary of the most often studied indicators (n = number of studies).

*<p>if a study reported more than 1 model, a variable selected in at least 1 model was counted one time.</p

Distribution of electronic medical records (EMR) system according to type of general practices in the Netherlands.

<p>Distribution of electronic medical records (EMR) system according to type of general practices in the Netherlands.</p

Univariate analysis of proportions of concomitant gastroprotection with NSAIDS based on brand of electronic medical record system and type of general practice.

<p>+—reference group in univariate analysis, *—statistically significant different from the reference group, SOLO- A single practitioner’ practice, DUO–A two practitioners’ practice, GROUP- A more than two practitioners’ practice, CENTER- A health center, usually with more primary health care services EMR–Electronic Medical Record System.</p

Regression analysis of determinants of rate of concomitant coprescription of gastroprotective medications with NSAIDs.

<p><b>LL</b>- Lower limit of confidence interval.</p><p><b>UL</b>-Upper limit of confidence interval.</p><p>* Statistically significant difference</p><p>Regression analysis of determinants of rate of concomitant coprescription of gastroprotective medications with NSAIDs.</p

Characteristics of general practices and determinants of coprescription of gastroprotective medication with NSAIDS.

<p>Characteristics of general practices and determinants of coprescription of gastroprotective medication with NSAIDS.</p

Time trends of the rate of concomitant prescription of gastroprotective medication with NSAIDs between various electronic medical record (EMR) systems.

<p>Time trends of the rate of concomitant prescription of gastroprotective medication with NSAIDs between various electronic medical record (EMR) systems.</p

List of Non Steroidal Anti-inflammatory Drugs (NSAIDs) included in the study grouped by pharmacological class.

<p>List of Non Steroidal Anti-inflammatory Drugs (NSAIDs) included in the study grouped by pharmacological class.</p

External Validation of European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) for Risk Prioritization in an Iranian Population

<div><p>Abstract Introduction: The European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) is a prediction model which maps 18 predictors to a 30-day post-operative risk of death concentrating on accurate stratification of candidate patients for cardiac surgery. Objective: The objective of this study was to determine the performance of the EuroSCORE II risk-analysis predictions among patients who underwent heart surgeries in one area of Iran. Methods: A retrospective cohort study was conducted to collect the required variables for all consecutive patients who underwent heart surgeries at Emam Reza hospital, Northeast Iran between 2014 and 2015. Univariate and multivariate analysis were performed to identify covariates which significantly contribute to higher EuroSCORE II in our population. External validation was performed by comparing the real and expected mortality using area under the receiver operating characteristic curve (AUC) for discrimination assessment. Also, Brier Score and Hosmer-Lemeshow goodness-of-fit test were used to show the overall performance and calibration level, respectively. Results: Two thousand five hundred eight one (59.6% males) were included. The observed mortality rate was 3.3%, but EuroSCORE II had a prediction of 4.7%. Although the overall performance was acceptable (Brier score=0.047), the model showed poor discriminatory power by AUC=0.667 (sensitivity=61.90, and specificity=66.24) and calibration (Hosmer-Lemeshow test, P<0.01). Conclusion: Our study showed that the EuroSCORE II discrimination power is less than optimal for outcome prediction and less accurate for resource allocation programs. It highlights the need for recalibration of this risk stratification tool aiming to improve post cardiac surgery outcome predictions in Iran.</p></div

Range of possible relationships between the patient visit, the letter due date, and the first reminder.

<p>Recheck patients should get a letter every year (or 2 years for internal medicine). If a recheck patient had a visit during the trial, they were eligible for a reminder if the letter was due before the visit (sometimes, long before the start of the trial) or up to 1 week after the visit. Reminders were sent for appointments that had already occurred and appointments scheduled for the coming week, meaning that reminders were sent no more than 2 weeks before the letter was due. New patients should get a letter within 8 weeks of their visit. Patients were considered eligible for a reminder if they did not yet have a letter at 6 weeks after their visit, meaning that the first reminder for a patient was issued 6 to 10 weeks (an average of 8 weeks) after the visit.</p

Forest plot of effect of intervention on each matched pair of clinicians, with correction for the (non-significant) differences in baseline performance (the percentage of patients with letters sent within 90 days of the visit) at the time of randomization.

<p>For each pair of doctors, we show the number of letters sent before 90 days/ the total number of letters which were due during the trial, and the resulting percentage of letters sent on time. The log odds ratio and confidence intervals are shown graphically (black bars = actual performance, grey diamonds = predicted performance according to the meta-analytic model), and numerically (in the right column).</p