Missing data methods for intensive care unit SOFA scores in electronic health records studies: results from a Monte Carlo simulation

Aim: Missing data cause problems through decreasing sample size and the potential for introducing bias. We tested four missing data methods on the Sequential Organ Failure Assessment (SOFA) score, an intensive care research severity adjuster. Methods: Simulation study using 2015–2017 electronic health record data, where the complete dataset was sampled, missing SOFA score elements imposed and performance examined of four missing data methods – complete case analysis, median imputation, zero imputation (recommended by SOFA score creators) and multiple imputation (MI) – on the outcome of in-hospital mortality. Results: MI performed well, whereas other methods introduced varying amounts of bias or decreased sample size. Conclusion: We recommend using MI in analyses where SOFA score component values are missing in administrative data research.

The Most Dominant Predictability Factor of Boey Score on The Level of Mortality in Perforation Gaster Boey Score 1 and Boey Scores 2 Patients in RSUD Dr Soetomo Surabaya

Introduction: The Boey score is the most commonly used scoring system for risk stratification because of its simplicity and high predictive value for mortality and morbidity in cases of gastric perforation. This score is widely used in daily practice because it only assesses 3 assessment components; namely the onset of perforation, shock at first admission, and comorbid disease; which is easy to do and has a fairly good accuracy. In Boey score 2, the mortality rate is still high, so research on the factors that most influence mortality at Boey Score 2 needs to be done.Methods: This study uses secondary data from medical records of patients who meet criteria of inclusion and exclusion. This study is a comparative test using a cohort analytic observational study design (longitudinal retrospective), comparing the components of the Boey score which is the most influential in predicting the mortality rate in gastric perforated patients. Boey score 1 and Boey score 2 at RSUD Dr. Soetomo SurabayaResults: Total subject of the study was 65 people, consisting of 43 men (66.2%) and 22 women (33.8%). The Boey score was 16 people (24.6%) with a Boey score of 1 and 49 people (75.4%) with a Boey score 2.From the Boey score component, 49 people (75.4%) were obtained with the onset of perforation> 24 hours, 31 people (47.7%) with preoperative shock, and 34 people (52.3%) with comorbidities. Comorbidity in study subjects included hypertension in 17 people (26.2%), diabetes mellitus in 4 people (6.2%), heart disease in 4 people (6.2%), lung disease in 5 people (7.7%), and kidney disease in 7 people. people (10.8%)Conclusion: Shock is the most dominant Boey Score predictability factor that affects the mortality rate in gastric perforation patients with Boey score 1 and Boey score 2.

The Most Dominant Predictability Factor of Boey Score on The Level of Mortality in Perforation Gaster Boey Score 1 and Boey Scores 2 Patients in RSUD Dr Soetomo Surabaya

Introduction: The Boey score is the most commonly used scoring system for risk stratification because of its simplicity and high predictive value for mortality and morbidity in cases of gastric perforation. This score is widely used in daily practice because it only assesses 3 assessment components; namely the onset of perforation, shock at first admission, and comorbid disease; which is easy to do and has a fairly good accuracy. In Boey score 2, the mortality rate is still high, so research on the factors that most influence mortality at Boey Score 2 needs to be done.Methods: This study uses secondary data from medical records of patients who meet criteria of inclusion and exclusion. This study is a comparative test using a cohort analytic observational study design (longitudinal retrospective), comparing the components of the Boey score which is the most influential in predicting the mortality rate in gastric perforated patients. Boey score 1 and Boey score 2 at RSUD Dr. Soetomo SurabayaResults: Total subject of the study was 65 people, consisting of 43 men (66.2%) and 22 women (33.8%). The Boey score was 16 people (24.6%) with a Boey score of 1 and 49 people (75.4%) with a Boey score 2.From the Boey score component, 49 people (75.4%) were obtained with the onset of perforation> 24 hours, 31 people (47.7%) with preoperative shock, and 34 people (52.3%) with comorbidities. Comorbidity in study subjects included hypertension in 17 people (26.2%), diabetes mellitus in 4 people (6.2%), heart disease in 4 people (6.2%), lung disease in 5 people (7.7%), and kidney disease in 7 people. people (10.8%)Conclusion: Shock is the most dominant Boey Score predictability factor that affects the mortality rate in gastric perforation patients with Boey score 1 and Boey score 2.

Comparing the measures of consumer knowledge calibration

Purpose Studies on consumer knowledge calibration have used different measures of calibration. The purpose of this paper is to undertake a comparative assessment of important measures. In addition, it seeks to identify the best performing measure. Design/methodology/approach The paper reports on three studies. The first study uses eight survey data sets. The second and third studies use experiments. Findings The study found that the Brier score component measure is most responsive to feedback and is the most suitable measure of knowledge calibration. The results also indicate that researchers should use measures that use item-level confidence judgements, as against an overall confidence judgement. Research limitations/implications By documenting the relationship between the different measures of knowledge calibration, the study enables proper interpretation and accumulation of results of various studies that have used different measures. The study also provides guidance to researchers in psychology and education where this issue has been noted. Practical implications The study provides guidance to managers in knowledge intensive industries, such as finance and insurance, interested in understanding their consumers’ knowledge calibration. Originality/value This is the first study in consumer research that examines this issue.

Chance Success Due to Guessing and Non-Independence of True Scores and Error Scores in Multiple-Choice Tests: Computer Trials with Prepared Distributions

The effect of chance success due to guessing upon the variance of multiple-choice test scores was estimated from prepared distributions of large numbers of scores. Each score consisted of an assumed “true score” component and an “error score” component generated by a computer. A large negative correlation was found between true scores and error scores and a positive correlation between error scores and error scores. The equation showing reliability in terms of components of variance was derived under the more restrictive assumption that there is a correlation between true scores and error scores, and the result [Formula: see text] was obtained. The fact that reliability can be positive even though error variance and observed variance are equal was discussed.