Dataset Information

Risk factors at medical school for subsequent professional misconduct: multicentre retrospective case-control study.

ABSTRACT:

Objective

To determine whether there are risk factors in a doctor's time at medical school that are associated with subsequent professional misconduct.

Design

Matched case-control study. Setting Records from medical schools and the General Medical Council (GMC).

Participants

59 doctors who had graduated from any one of eight medical schools in the United Kingdom in 1958-97 and had a proved finding of serious professional misconduct in GMC proceedings in 1999-2004 (cases); 236 controls (four for each case) were selected by systematic sampling from matching graduation cohorts. Case-control status was revealed by the GMC after completion of data entry.

Main outcome measure

Odds ratios for being a "case," with multivariable conditional logistic regression of potential risk factors including pre-admission characteristics and progress during the course. These data were obtained from anonymised copies of the students' progress files held by their original medical schools.

Results

Univariate conditional logistic regression analysis found that cases were more likely to be men, to be of lower estimated social class, and to have had academic difficulties during their medical course, especially in the early years. Multivariable analysis showed that male sex (odds ratio 9.80, 95% confidence interval 2.43 to 39.44, P=0.001), lower social class (4.28, 1.52 to 12.09, P=0.006), and failure of early or preclinical examinations (5.47, 2.17 to 13.79, P<0.001) were independently associated with being a case.

Conclusions

This small study suggests that male sex, a lower socioeconomic background, and early academic difficulties at medical school could be risk factors for subsequent professional misconduct. The findings are preliminary and should be interpreted with caution. Most doctors with risk factors will not come before the GMC's disciplinary panels.

SUBMITTER: Yates J

PROVIDER: S-EPMC3191727 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectivesWe aimed to evaluate recompensation factors among patients with decompensated cirrhosis.DesignA multicentre retrospective case-control study was conducted. Data were collected from and compared between groups of patients with recompensated and acute decompensated cirrhosis. Univariable and multivariable logistic regressions were used to select indicators associated with recompensation among patients with decompensated cirrhosis with different complications. A decision tree with 10-fold cross-validation was used to develop the model to identify patients with recompensation. We followed the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guideline for development and reporting of the new model.SettingThe study was conducted in six tertiary public hospitals in Chongqing, China.ParticipantsThis study included 3953 patients with decompensated cirrhosis.ResultsIn the total sample of included patients, there were 553 patients with recompensation and 3400 patients with acute decompensation, including 1158 patients with gastrointestinal bleeding, 1715 patients with a bacterial infection, 104 patients with hepatic encephalopathy and 423 patients with ascites. The most relevant indicator of recompensation selected by the decision tree model was albumin, with a threshold of 40 g/L. Total protein, haemoglobin, basophil percentage, alanine aminotransferase, neutrophil-to-lymphocyte ratio and diabetes were also selected to subsequently distinguish patients. The terminal nodes with a probability of recompensation was 0.89. The overall accuracy rate of the model was 0.92 (0.91-0.93), and it exhibited high specificity (86.9%) and sensitivity (92.6%).ConclusionsThe occurrence of recompensated cirrhosis could be identified by albumin, total protein, haemoglobin, basophil percentage, alanine aminotransferase, neutrophil-to-lymphocyte ratio and diabetes. These simple variables may help clinicians develop a treatment plan to encourage patients with decompensated cirrhosis to recompensate.

Project description:Objectives: A potential new avenue to address the shortage of country doctors is to change the rules for admission to medical school. We therefore study the link between high-school grade point average and prospective physicians' choice to work in rural areas. To further inform the discussion about rules for admission, we also study the effects of other predictors: a measure of students' attitudes towards risk; whether they waited for their place of study (Wartesemester); whether their parents worked as medical doctors; and whether they have some practical experience in the medical sector. Methods: We conducted two internet surveys in 2012 and 2014. In the first survey, the sample comprised 701 students and in the second, 474 students. In both surveys, we asked students for their regional preferences; in the 2014 survey, we additionally asked students for their first, second, and third preferences among a comprehensive set of specializations, including becoming a general practitioner. In both surveys, we asked students for basic demographic information (age and gender), their parents' occupation, a measure of subjective income expectations, a measure of risk attitudes, and their high-school grade point average (Abiturnote), and First National Boards Examination grade (Physikum). In 2014, we additionally asked for waiting periods (Wartesemester) as well as for prior professional experience in the health-care sector. Results: We find that three factors increase the probability of having a preference for working in a rural area significantly, holding constant all other influences: having a medical doctor among the parents, having worse grades in the high-school grade point average, and being more risk averse. Moreover, we find that those willing to work in the countryside have significantly more experience in the medical sector before admission to medical school. Discussion: Our results suggest that a change in the selection process for medical school may increase the supply of country doctors. Instead of focusing on the high-school grade point average, universities could even more intensely screen for study motivation through interviews or by taking into account students' background, extracurricular activities, or waiting periods.

Project description:BackgroundDespite the growing number of patients with limited English proficiency in the United States, not all medical schools offer medical language courses to train future physicians in practicing language-concordant care. Little is known about the long-term use of non-English languages among physicians who took language courses in medical school. We conducted a cross-sectional study to characterize the professional language use of Harvard Medical School (HMS) alumni who took a medical language course at HMS and identify opportunities to improve the HMS Medical Language Program.MethodsBetween October and November 2019, we sent an electronic survey to 803 HMS alumni who took a medical language course at HMS between 1991 and 2019 and collected responses. The survey had questions about the language courses and language use in the professional setting. We analyzed the data using descriptive statistics and McNemar's test for comparing proportions with paired data. The study was determined not to constitute human subjects research.ResultsThe response rate was 26% (206/803). More than half of respondents (n = 118, 57%) cited their desire to use the language in their future careers as the motivation for taking the language courses. Twenty-eight (14%) respondents indicated a change from not proficient before taking the course to proficient at the time of survey whereas only one (0.5%) respondent changed from proficient to not proficient (McNemar's p-value < 0.0001). Respondents (n = 113, 56%) reported that clinical electives abroad influenced their cultural understanding of the local in-country population and their language proficiency. Only 13% (n = 27) of respondents have worked in a setting that required formal assessments of non-English language proficiency.ConclusionsHMS alumni of the Medical Language Program reported improved language proficiency after the medical language courses' conclusion, suggesting that the courses may catalyze long-term language learning. We found that a majority of respondents reported that the medical language courses influenced their desire to work with individuals who spoke the language of the courses they took. Medical language courses may equip physicians to practice language-concordant care in their careers.

Project description:BACKGROUND:Difficult peripheral intravenous cannulation (DPIVC) is associated with serious complications related to vascular access. These complications might be avoided if the risk factors were identified previously, enabling the detection of potentially difficult situations at an early stage. The aim of this study is to consider these risk factors, to determine the influence of the hospital setting, to examine the association between DPIVC and the different techniques of catheter insertion and to analyse the importance of the clinician's experience in this context. METHODS:Case-control study following a previously published protocol, conducted in 48 units of eight public hospitals in Spain. Adult patients requiring a peripheral intravenous cannula were prospectively included in the study population during their hospital stay. Over a period of 11 months, for consecutive eligible patients, nurses in each participating unit recorded data on their assessment of the vascular access performed and the technique used. Variables related to these medical personnel were also recorded. One of the researchers reviewed the patients' clinical history to compile the relevant health variables and to characterise the healthcare process. The statistical analysis included association tests among the main study variables. The risk factors were analysed using bivariate logistic regression. The variables found to be statistically significant were included in a multivariate logistic regression model incorporating each of the healthcare environments identified. RESULTS:The study population was composed of 2662 patients, of whom 221 (8.3%) presented with DPIVC. A previous history of difficulty, the presence of non-palpable veins, acute upper limb alterations and punctures in the ante-cubital fossa were found to be independent risk factors for DPIVC. Differences were found in the frequency of occurrence of DPIVC and in some risk factors, according to the healthcare context. The variables related to the characteristics of the hospital personnel did not influence the study event. CONCLUSION:The present study identifies four independent risk factors for DPIVC that can be incorporated into algorithms aimed at preventing its occurrence and facilitating the referral of patients to vascular access specialist teams.

Project description:BackgroundElectronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary for the optimisation of prediction accuracy. Myopia is a common cause of vision loss. Current approaches to control myopia progression are effective but have significant side effects. Therefore, identifying those at greatest risk who should undergo targeted therapy is of great clinical importance. The objective of this study was to apply big data and machine learning technology to develop an algorithm that can predict the onset of high myopia, at specific future time points, among Chinese school-aged children.Methods and findingsReal-world clinical refraction data were derived from electronic medical record systems in 8 ophthalmic centres from January 1, 2005, to December 30, 2015. The variables of age, spherical equivalent (SE), and annual progression rate were used to develop an algorithm to predict SE and onset of high myopia (SE ≤ -6.0 dioptres) up to 10 years in the future. Random forest machine learning was used for algorithm training and validation. Electronic medical records from the Zhongshan Ophthalmic Centre (a major tertiary ophthalmic centre in China) were used as the training set. Ten-fold cross-validation and out-of-bag (OOB) methods were applied for internal validation. The remaining 7 independent datasets were used for external validation. Two population-based datasets, which had no participant overlap with the ophthalmic-centre-based datasets, were used for multi-resource validation testing. The main outcomes and measures were the area under the curve (AUC) values for predicting the onset of high myopia over 10 years and the presence of high myopia at 18 years of age. In total, 687,063 multiple visit records (≥3 records) of 129,242 individuals in the ophthalmic-centre-based electronic medical record databases and 17,113 follow-up records of 3,215 participants in population-based cohorts were included in the analysis. Our algorithm accurately predicted the presence of high myopia in internal validation (the AUC ranged from 0.903 to 0.986 for 3 years, 0.875 to 0.901 for 5 years, and 0.852 to 0.888 for 8 years), external validation (the AUC ranged from 0.874 to 0.976 for 3 years, 0.847 to 0.921 for 5 years, and 0.802 to 0.886 for 8 years), and multi-resource testing (the AUC ranged from 0.752 to 0.869 for 4 years). With respect to the prediction of high myopia development by 18 years of age, as a surrogate of high myopia in adulthood, the algorithm provided clinically acceptable accuracy over 3 years (the AUC ranged from 0.940 to 0.985), 5 years (the AUC ranged from 0.856 to 0.901), and even 8 years (the AUC ranged from 0.801 to 0.837). Meanwhile, our algorithm achieved clinically acceptable prediction of the actual refraction values at future time points, which is supported by the regressive performance and calibration curves. Although the algorithm achieved balanced and robust performance, concerns about the compromised quality of real-world clinical data and over-fitting issues should be cautiously considered.ConclusionsTo our knowledge, this study, for the first time, used large-scale data collected from electronic health records to demonstrate the contribution of big data and machine learning approaches to improved prediction of myopia prognosis in Chinese school-aged children. This work provides evidence for transforming clinical practice, health policy-making, and precise individualised interventions regarding the practical control of school-aged myopia.

Project description:BackgroundMirror syndrome (MS) is a rare obstetric disorder complicated with high maternal morbidity and fetal mortality. MS is often misdiagnosed or underdiagnosed due to the low incidence and lack of awareness of its diverse features. This study aimed to summarise the etiology, clinical characteristics, and risk factors of MS among mothers with fetal hydrops.MethodsThis retrospective case-control study included 37 pregnant women with fetal hydrops in the second and third trimesters from 58,428 deliveries performed at the Third Affiliated Hospital of Sun Yat-Sen University between January 2012 and December 2020. Cases were categorized as MS and non-MS according to the presence or absence of maternal mirroring symptoms. Binary logistic regression was performed for analysis.ResultsFourteen women developed MS with an overall incidence of 0.024% (14/58,428) and 37.8% (14/37) in the fetal hydrops cases. Among the 11 MS cases with known associated etiologies, seven had alpha thalassemia major. Onset of fetal hydrops was later (27.8 vs. 23.0 weeks) and the rate of placental thickening was higher (85.7% vs. 34.8%) in the MS group than in the non-MS group (P < 0.05). Regarding maternal characteristics, the MS group had higher maternal morbidity (85.7% vs. 8.7%), more weight gain (9.0 vs. 5.5 kg), higher rates of hypertension (35.7 vs. 0%) and proteinuria (64.3% vs. 4.3%), and lower levels of hemoglobin (88 vs. 105 g/L) and serum albumin (25.8 vs. 35.0 g/L) than the non-MS group (P < 0.05). Logistic regression analysis showed that onset of fetal hydrops at ≥24 weeks and placental thickening were associated with the risk of MS among fetal hydrops cases (OR 15.83, 95% CI 1.56-160.10 and OR 8.63, 95% CI 1.29-57.72, respectively).ConclusionsMS is relatively common among fetal hydrops cases in the late second and third trimesters, and alpha thalassemia major is the main etiology for fetal hydrops and also MS in this population. Complicated with high maternal morbidity, the key maternal features of MS include more weight gain, hemodilution, and hypertension. Among those with fetal hydrops, the onset time of ≥24 weeks and placental thickening are risk factors for MS.

Project description:Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder triggered by several factors, including those of genetic and environmental nature. ASD can alter communication, behavior, and children's nutritional status, placing them at high risk for nutritional imbalances. Therefore, this study aims to assess preschool autistic children's nutritional status as compared to that of Typically Developing (TD) children of the same age. The study also revealed some of the ASD risk factors among the Jordanian population. It included 52 ASD and 51 TD children (3-6 years), and considered sociodemographic, obstetric, and nutritional factors of the two groups, stratified by gender. Nutritional status was evaluated through a comprehensive questionnaire, 3-day food record, and anthropometric and biochemical measurements. Differences between groups were identified using the chi-square and independent-sample t-test. The logistic regression model was used after the adjustment of confounders to detect an autistic child's determinants. The study showed little difference between ASD and TD children with respect to nutrients' intake inadequacy and biochemical-nutritional deficiencies, but did reveal gender-based differences. Autistic girls were at higher risk of inadequate carbohydrate intake, while autistic boys were at higher risk of inadequate vitamin E, vitamin K, and fluoride compared to TD children. More autistic children had been treated in neonatal care units after birth than had TD children. The regression analysis revealed that lower maternal education level (OR, 12.25; 95% CI, 1.18-126.91), vaginal delivery (OR, 0.273; 95% CI, 0.105-0.712), family history of autism (OR, 0.189; 95% CI, 0.059-0.612), and taking dietary supplements during pregnancy (OR, 4.665; 95% CI, 1.158-18.79) were all determinants of ASD in children. In conclusion, maternal nutrition, postnatal conditions, and nutritional status might be contributors to ASD in children. Pre-school children are at high risk for developing nutritional deficiencies. It is therefore important to maintain optimal nutritional status in pregnant patients, and in children after delivery and during early childhood. Future studies that investigate the role of nutrient deficiencies and nutritional interventions in ASD are necessary. Also required are studies that focus on gender differences in the prevalence of ASD, types and severity of symptoms, and ASD nutrition-related problems.