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BackgroundResults GME completed all design, start-up, reviews, assessment tool and inter-program comparisons, statistics PDs completed the ‘field work’

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Presentation on theme: "BackgroundResults GME completed all design, start-up, reviews, assessment tool and inter-program comparisons, statistics PDs completed the ‘field work’"— Presentation transcript:

1 BackgroundResults GME completed all design, start-up, reviews, assessment tool and inter-program comparisons, statistics PDs completed the ‘field work’ – Identified milestone levels for consideration – Evaluated Kalamazoo Essential Elements Communication Checklist-Adapted( KEECC- A.) Does it inform milestones? Is it effective ? What’s better? – Selected CAT-M tool ( Communication Assessment Tool- Modified) – Field-tested CAT-M using existing videos – Made sure this adds value with no additional work work Methods Discussion OSCE is a direct observation tool to evaluate learner interpersonal communication skills (ICS) This presentation marries the language of structured observations with the behavioral anchors of Milestone reporting. An observation from our analyses points to the variation in word usage and expected learning progression in a set of interpersonal and communication skills that ought to be nearly identical and consistent across specialties, but is not. When you get back,look at your OSCEs already in place at your institution/program and see if they meet the needs of your PDs and CCCs for milestone assessment? We had assumed the tool we had used for years would help inform milestones, but it did not. This is an opportunity to capture direct observation data. Translating Objective Structured Clinical Exam (OCSE) Observations into Milestone Speak Roopina Sangha, MD, MPH; Maria Kokas, Phd Henry Ford Hospital, Detroit, MI Share the Henry Ford program as a model Assess current OSCE observations to inform ICS on the Milestones scale Build ICS OSCE exercises using Milestone ICS scale Strategize OSCE observations as an earlier identifier of the struggling resident and as a yardstick for successful intervention How can we use non-procedural institutional OSCEs to inform Milestones as a direct observation tool Purpose §The relationships between the OSCE variables and the Milestones variables were computed using the Spearman-Rho correlation coefficients. §Associations between being above or below the cut-off for the OSCE variables and being above or below the cut-off for the Milestones variables were computed using the Fisher ’ s Exact test. No correlations were found between OSCEs and Milestone variables Our PDs felt that the CAT-M worked best for them due to the folowing reasons Each item is one direct observation Validated instrument meeting psychometric properties and quality criteria Simple to use, adds no extra time §The relationships between the OSCE variables and the Milestones variables were computed using the Spearman-Rho correlation coefficients. §Associations between being above or below the cut-off for the OSCE variables and being above or below the cut-off for the Milestones variables were computed using the Fisher ’ s Exact test. No correlations were found between OSCEs and Milestone variables Our PDs felt that the CAT-M worked best for them due to the folowing reasons Each item is one direct observation Validated instrument meeting psychometric properties and quality criteria Simple to use, adds no extra time The relationships between the OSCE variables and the Milestones variables were computed using the Spearman-Rho correlation coefficients. Associations between being above or below the cut-off for the OSCE variables and being above or below the cut-off for the Milestones variables were computed using the Fisher’s Exact test. No correlations were found between OSCEs and Milestone variables Our PDs felt that the CAT-M worked best for them due to the following reasons  Each item is one direct observation  Validated instrument meeting psychometric properties and quality criteria  Simple to use, adds no extra time

2 Abstract Conclusions Clinically EBL is not strongly associated with either the absolute or percent change in hemoglobin from pre- to post-myomectomy We need to incorporate a more accurate measure to determine actual blood loss during surgery, as this can impact outcomes. Measurements Data: Data collected from patient medical records included: − EBL − Hemoglobin before and after surgery −Absolute change −Percent change − BMI (kg/m 2 ) Analyses: –Spearman correlations –Subgroup analyses (BMI group) Is estimated blood loss during surgery associated with hemoglobin level changes? Roopina Sangha, MD; David I. Eisenstein, MD; Ganesa Wegienka, PhD. Henry Ford Hospital, Detroit, Michigan Study Objective: Examine whether estimated blood loss (EBL) during myomectomy correlates with hemoglobin level changes. Design: Retrospective cohort Setting: Henry Ford Hospital, Detroit (community based) Patients: All robotic assisted laparoscopic myomectomy (RM) cases 9/13/200406/30/2009 (n=100); all laparotomic myomectomy (LM) cases 1/1/2007- 6/30/2009 (n=48). Five RM patients had missing hemoglobin levels. Interventions: N/A Measurements & Main Results: Height, weight and EBL were collected from the anesthesiologists’ reports. Body mass index (BMI- kg/m2) was calculated. Pre-surgical and post-surgical hemoglobin (Hb) levels were taken from the patients’ clinical laboratory reports. Spearman correlations were used to assess associations between EBL and both the absolute (AC) and percent change (PC) in hemoglobin levels from before to after surgery. Associations in subgroups of women defined by procedure type and BMI were also examined. Results: EBL was not strongly correlated with either the AC (r=-0.25, p=0.003) or PC (r=-0.25, p=0.0028). Among LM patients EBL was not strongly correlated with either the AC (r=-0.25, p=0.08) or PC (r=-0.27, p=0.06). Among RM patients EBL was only modestly correlated with the AC (r=- 0.31, p=0.002) and the PC (r=-0.31, p=0.002). The correlation between EBL and hemoglobin level changes varied a little by BMI group (underweight (<18.5), normal (18.5-24.9), overweight (25-29.9), obese (30-34.9) and morbidly obese (≥35)). However, there was no strictly increasing or decreasing trend, meaning the correlations did not improve with either increasing or decreasing body size. BMI:Normal (18.5-24.9)N=37Overweight (25- 29.9)N=46Obese (30-34.9)N=34Morbidly obese (≥35)N=26Percent change-0.18 (p=0.27)-0.30 (p=0.04)-0.20 (p=0.26)-0.36 (p=0.07)Absolute change-0.15 (p=0.37)-0.35 (p=0.02)-0.19 (p=0.29)-0.40 (p=0.04) Conclusion: Clinically EBL is not strongly associated with either the absolute or percent change in hemoglobin from pre- to post- myomectomy, irrespective of surgical mode. EBL was not strongly correlated with either the absolute change in hemoglobin (r=-0.25, p=0.003) or the percent change in hemoglobin (r=-0.25, p=0.0028). Correlations did not vary by procedure type. While correlations varied slightly by BMI group, there was no strictly increasing or decreasing trend meaning the correlations did not get better with increasing body size. Main Results Main Results – cont’d Table 1. Spearman correlations between hemoglobin changes and EBL. Figure 1. Absolute Change in Hemoglobin Level Versus EBL BMI:Normal (18.5-24.9) N=37 Overweight (25-29.9) N=46 Obese (30- 34.9) N=34 Morbidly obese (≥35) N=26 Percent change -0.18 (p=0.27)-0.30 (p=0.04)-0.20 (p=0.26) -0.36 (p=0.07) Absolute change -0.15 (p=0.37)-0.35 (p=0.02)-0.19 (p=0.29) -0.40 (p=0.04)


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