Dataset Information

A Randomized Trial on the Efficacy of Mastery Learning for Primary Care Provider Melanoma Opportunistic Screening Skills and Practice.

ABSTRACT: BACKGROUND:Early detection of melanoma represents an opportunity to reduce the burden of disease among people at increased risk for melanoma. OBJECTIVE:To develop and demonstrate the efficacy of online training. DESIGN:Randomized educational trial. PARTICIPANTS:Primary care providers (PCPs). INTERVENTION:Mastery learning course with visual and dermoscopic assessment, diagnosis and management, and deliberate practice with feedback to reach a minimum passing standard. MAIN MEASURES:Pre-test/post-test diagnostic accuracy. Referral of concerning lesions for 3 months before and after the educational intervention. KEY RESULTS:Among the 89 PCPs, 89.8% were internal medicine physicians, and the remainder were physician assistants embedded in internists' practices. There were no differences between control and intervention groups regarding gender, age, race, or percentage of full-time PCPs. The control group had more PCPs who reported less than 5 years of practice (n?=?18) than the intervention group (n?=?6) (?2 [6, n?=?89]?=?14.34, p?=?0.03). PCPs in the intervention group answered more melanoma detection questions correctly on the post-test (M?=?10.05, SE?=?1.24) compared to control group PCPs (M?=?7.11, SE?=?0.24), and had fewer false-positive and no false-negative melanoma diagnoses (intervention, M?=?1.09, SE?=?0. 20; control, M?=?3.1, SE?=?0.23; ANCOVA, F[1,378] =27.86, p?

SUBMITTER: Robinson JK

PROVIDER: S-EPMC5975143 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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A Randomized Trial on the Efficacy of Mastery Learning for Primary Care Provider Melanoma Opportunistic Screening Skills and Practice.

Robinson June K JK Jain Namita N Marghoob Ashfaq A AA McGaghie William W MacLean Michael M Gerami Pedram P Hultgren Brittney B Turrisi Rob R Mallett Kimberly K Martin Gary J GJ

Journal of general internal medicine 20180205 6

<h4>Background</h4>Early detection of melanoma represents an opportunity to reduce the burden of disease among people at increased risk for melanoma.<h4>Objective</h4>To develop and demonstrate the efficacy of online training.<h4>Design</h4>Randomized educational trial.<h4>Participants</h4>Primary care providers (PCPs).<h4>Intervention</h4>Mastery learning course with visual and dermoscopic assessment, diagnosis and management, and deliberate practice with feedback to reach a minimum passing sta ...[more]

PMID: 29404948

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Project description:BACKGROUND: Internal medicine residents must be competent in advanced cardiac life support (ACLS) for board certification. OBJECTIVE: To use a medical simulator to assess postgraduate year 2 (PGY-2) residents' baseline proficiency in ACLS scenarios and evaluate the impact of an educational intervention grounded in deliberate practice on skill development to mastery standards. DESIGN: Pretest-posttest design without control group. After baseline evaluation, residents received 4, 2-hour ACLS education sessions using a medical simulator. Residents were then retested. Residents who did not achieve a research-derived minimum passing score (MPS) on each ACLS problem had more deliberate practice and were retested until the MPS was reached. PARTICIPANTS: Forty-one PGY-2 internal medicine residents in a university-affiliated program. MEASUREMENTS: Observational checklists based on American Heart Association (AHA) guidelines with interrater and internal consistency reliability estimates; deliberate practice time needed for residents to achieve minimum competency standards; demographics; United States Medical Licensing Examination Step 1 and Step 2 scores; and resident ratings of program quality and utility. RESULTS: Performance improved significantly after simulator training. All residents met or exceeded the mastery competency standard. The amount of practice time needed to reach the MPS was a powerful (negative) predictor of posttest performance. The education program was rated highly. CONCLUSIONS: A curriculum featuring deliberate practice dramatically increased the skills of residents in ACLS scenarios. Residents needed different amounts of training time to achieve minimum competency standards. Residents enjoy training, evaluation, and feedback in a simulated clinical environment. This mastery learning program and other competency-based efforts illustrate outcome-based medical education that is now prominent in accreditation reform of residency education.

Project description:BACKGROUND & AIMS:Low rates of hepatocellular carcinoma (HCC) surveillance are primarily due to provider-related process failures. However, few studies have evaluated primary care provider (PCP) practice patterns, attitudes, and barriers to HCC surveillance at academic tertiary care referral centers. METHODS:We conducted a web-based survey of PCPs at 2 tertiary care referral centers (133 providers) from June 2017 through December 2017. The survey was adapted from pretested surveys and included questions about practice patterns, attitudes, and barriers to HCC surveillance. We used the Fisher exact and Mann-Whitney rank-sum tests to identify factors associated with adherence to HCC surveillance recommendations, for categoric and continuous variables, respectively. RESULTS:We obtained a provider-level response rate of 75% and clinic-level response rate of 100% (133 providers). Whereas most PCPs performed HCC surveillance themselves, one-third deferred surveillance to subspecialists and referred patients to a hepatology clinic. Providers believed the combination of ultrasound and ?-fetoprotein analysis to be highly effective for early stage tumor detection and reported using the combination for assessment of most patients. However, PCPs were more likely to use computed tomography- or magnetic resonance imaging-based surveillance for patients with nonalcoholic steatohepatitis or decompensated cirrhosis. Most providers believed HCC surveillance to be efficacious for early tumor detection and increasing survival. However, they desired increased high-quality evidence to characterize screening benefits and harms. Providers expressed notable misconceptions about HCC surveillance, including the role for measurement of liver enzyme levels in HCC surveillance and cost effectiveness of surveillance in patients without cirrhosis. They also reported barriers, including not being up to date on HCC surveillance recommendations, limited time in the clinic, and competing clinical concerns. CONCLUSIONS:In a web-based survey, PCPs reported misconceptions and barriers to HCC surveillance. This indicates the need for interventions, including provider education, to improve HCC surveillance effectiveness in clinical practice.

Project description:BackgroundEarly detection and management of sarcopenia is of clinical importance. We aimed to develop a chest X-ray-based deep learning model to predict presence of sarcopenia.MethodsData of participants who visited osteoporosis clinic at Severance Hospital, Seoul, South Korea, between January 2020 and June 2021 were used as derivation cohort as split to train, validation and test set (65:15:20). A community-based older adults cohort (KURE) was used as external test set. Sarcopenia was defined based on Asian Working Group 2019 guideline. A deep learning model was trained to predict appendicular lean mass (ALM), handgrip strength (HGS) and chair rise test performance from chest X-ray images; then the machine learning model (SARC-CXR score) was built using the age, sex, body mass index and chest X-ray predicted muscle parameters along with estimation uncertainty values.ResultsMean age of the derivation cohort (n = 926; women n = 700, 76%; sarcopenia n = 141, 15%) and the external test (n = 149; women n = 95, 64%; sarcopenia n = 18, 12%) cohort was 61.4 and 71.6 years, respectively. In the internal test set (a hold-out set, n = 189, from the derivation cohort) and the external test set (n = 149), the concordance correlation coefficient for ALM prediction was 0.80 and 0.76, with an average difference of 0.18 ± 2.71 and 0.21 ± 2.28, respectively. Gradient-weight class activation mapping for deep neural network models to predict ALM and HGS commonly showed highly weight pixel values at bilateral lung fields and part of the cardiac contour. SARC-CXR score showed good discriminatory performance for sarcopenia in both internal test set [area under the receiver-operating characteristics curve (AUROC) 0.813, area under the precision-recall curve (AUPRC) 0.380, sensitivity 0.844, specificity 0.739, F1-score 0.540] and external test set (AUROC 0.780, AUPRC 0.440, sensitivity 0.611, specificity 0.855, F1-score 0.458). Among SARC-CXR model features, predicted low ALM from chest X-ray was the most important predictor of sarcopenia based on SHapley Additive exPlanations values. Higher estimation uncertainty of HGS contributed to elevate the predicted risk of sarcopenia. In internal test set, SARC-CXR score showed better discriminatory performance than SARC-F score (AUROC 0.813 vs. 0.691, P = 0.029).ConclusionsChest X-ray-based deep leaning model improved detection of sarcopenia, which merits further investigation.

Dataset Information

A Randomized Trial on the Efficacy of Mastery Learning for Primary Care Provider Melanoma Opportunistic Screening Skills and Practice.

Publications

A Randomized Trial on the Efficacy of Mastery Learning for Primary Care Provider Melanoma Opportunistic Screening Skills and Practice.

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