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Jo Leuck

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NCBI: db=pubmed; Term=(Leuck J[Author]) AND (John Peter Smith[Affiliation] OR JPS Health Network[Affiliation] OR JPS [Affiliation] NOT Japan Pancreas Society[Affiliation])
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Unifying interdisciplinary education: designing and implementing an intern simulation educational curriculum to increase confidence in critical care from PGY1 to PGY2.

Wed, 01/30/2019 - 08:23
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Unifying interdisciplinary education: designing and implementing an intern simulation educational curriculum to increase confidence in critical care from PGY1 to PGY2.

BMC Res Notes. 2017 Nov 06;10(1):563

Authors: Bullard MJ, Leuck JA, Howley LD

Abstract
BACKGROUND: A longitudinal, multidisciplinary critical care simulation curriculum was developed and implemented within a teaching hospital to address the need for consistent, safe, efficient, and unified critical care training within graduate medical education. Primary goals were to increase learner confidence in critical care topics and procedural skills across all specialties. Secondary goals included improving communication skills and obtaining a high level of learner satisfaction. All interns caring for adult patients within our hospital participated in three 4-h simulation-based sessions scheduled over the second half of their intern year. Pre- and postcurricular surveys evaluated self-confidence in critical care topics, procedures, and communication skills. The Debriefing Assessment for Simulation in Healthcare Student Version (DASH-SV) Short Form was used to evaluate facilitator debriefing. Data were compared with Wilcoxon rank sum and signed rank test.
RESULTS: Pre- and postcurricular surveys were collected from 51 of 52 interns (98% response rate) in curricular year 1 and 59 of 59 interns (100% response rate) in curricular year 2 in six programs within the hospital. Resident confidence significantly improved in all areas (p < .05). DASH-SV demonstrated overall effective facilitator debriefing and > 75% of interns in both curricular years 1 and 2 expressed a desire for future educational sessions.
CONCLUSIONS: The implemented curriculum increased learner confidence in select critical care topics, procedures, and communication skills and demonstrated a high level of learner satisfaction. The curriculum has expanded to learners from three other teaching hospitals within our system to unify critical care education for all interns caring for adult patients.

PMID: 29110695 [PubMed - indexed for MEDLINE]

The role of patient perception of crowding in the determination of real-time patient satisfaction at Emergency Department.

Wed, 01/30/2019 - 08:23
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The role of patient perception of crowding in the determination of real-time patient satisfaction at Emergency Department.

Int J Qual Health Care. 2017 Oct 01;29(5):722-727

Authors: Wang H, Kline JA, Jackson BE, Robinson RD, Sullivan M, Holmes M, Watson KA, Cowden CD, Phillips JL, Schrader CD, Leuck J, Zenarosa NR

Abstract
Objective: To evaluate the associations between real-time overall patient satisfaction and Emergency Department (ED) crowding as determined by patient percepton and crowding estimation tool score in a high-volume ED.
Design: A prospective observational study.
Setting: A tertiary acute hospital ED and a Level 1 trauma center.
Participants: ED patients.
Intervention(s): Crowding status was measured by two crowding tools [National Emergency Department Overcrowding Scale (NEDOCS) and Severely overcrowded-Overcrowded-Not overcrowded Estimation Tool (SONET)] and patient perception of crowding surveys administered at discharge.
Main outcome measure(s): ED crowding and patient real-time satisfaction.
Results: From 29 November 2015 through 11 January 2016, we enrolled 1345 participants. We observed considerable agreement between the NEDOCS and SONET assessment of ED crowding (bias = 0.22; 95% limits of agreement (LOAs): -1.67, 2.12). However, agreement was more variable between patient perceptions of ED crowding with NEDOCS (bias = 0.62; 95% LOA: -5.85, 7.09) and SONET (bias = 0.40; 95% LOA: -5.81, 6.61). Compared to not overcrowded, there were overall inverse associations between ED overcrowding and patient satisfaction (Patient perception OR = 0.49, 95% confidence limit (CL): 0.38, 0.63; NEDOCS OR = 0.78, 95% CL: 0.65, 0.95; SONET OR = 0.82, 95% CL: 0.69, 0.98).
Conclusions: While heterogeneity exists in the degree of agreement between objective and patient perceived assessments of ED crowding, in our study we observed that higher degrees of ED crowding at admission might be associated with lower real-time patient satisfaction.

PMID: 28992161 [PubMed - indexed for MEDLINE]

Optimal Measurement Interval for Emergency Department Crowding Estimation Tools.

Wed, 01/30/2019 - 08:23
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Optimal Measurement Interval for Emergency Department Crowding Estimation Tools.

Ann Emerg Med. 2017 Nov;70(5):632-639.e4

Authors: Wang H, Ojha RP, Robinson RD, Jackson BE, Shaikh SA, Cowden CD, Shyamanand R, Leuck J, Schrader CD, Zenarosa NR

Abstract
STUDY OBJECTIVE: Emergency department (ED) crowding is a barrier to timely care. Several crowding estimation tools have been developed to facilitate early identification of and intervention for crowding. Nevertheless, the ideal frequency is unclear for measuring ED crowding by using these tools. Short intervals may be resource intensive, whereas long ones may not be suitable for early identification. Therefore, we aim to assess whether outcomes vary by measurement interval for 4 crowding estimation tools.
METHODS: Our eligible population included all patients between July 1, 2015, and June 30, 2016, who were admitted to the JPS Health Network ED, which serves an urban population. We generated 1-, 2-, 3-, and 4-hour ED crowding scores for each patient, using 4 crowding estimation tools (National Emergency Department Overcrowding Scale [NEDOCS], Severely Overcrowded, Overcrowded, and Not Overcrowded Estimation Tool [SONET], Emergency Department Work Index [EDWIN], and ED Occupancy Rate). Our outcomes of interest included ED length of stay (minutes) and left without being seen or eloped within 4 hours. We used accelerated failure time models to estimate interval-specific time ratios and corresponding 95% confidence limits for length of stay, in which the 1-hour interval was the reference. In addition, we used binomial regression with a log link to estimate risk ratios (RRs) and corresponding confidence limit for left without being seen.
RESULTS: Our study population comprised 117,442 patients. The time ratios for length of stay were similar across intervals for each crowding estimation tool (time ratio=1.37 to 1.30 for NEDOCS, 1.44 to 1.37 for SONET, 1.32 to 1.27 for EDWIN, and 1.28 to 1.23 for ED Occupancy Rate). The RRs of left without being seen differences were also similar across intervals for each tool (RR=2.92 to 2.56 for NEDOCS, 3.61 to 3.36 for SONET, 2.65 to 2.40 for EDWIN, and 2.44 to 2.14 for ED Occupancy Rate).
CONCLUSION: Our findings suggest limited variation in length of stay or left without being seen between intervals (1 to 4 hours) regardless of which of the 4 crowding estimation tools were used. Consequently, 4 hours may be a reasonable interval for assessing crowding with these tools, which could substantially reduce the burden on ED personnel by requiring less frequent assessment of crowding.

PMID: 28688771 [PubMed - indexed for MEDLINE]

Roles of disease severity and post-discharge outpatient visits as predictors of hospital readmissions.

Wed, 01/30/2019 - 08:23
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Roles of disease severity and post-discharge outpatient visits as predictors of hospital readmissions.

BMC Health Serv Res. 2016 10 10;16(1):564

Authors: Wang H, Johnson C, Robinson RD, Nejtek VA, Schrader CD, Leuck J, Umejiego J, Trop A, Delaney KA, Zenarosa NR

Abstract
BACKGROUND: Risks prediction models of 30-day all-cause hospital readmissions are multi-factorial. Severity of illness (SOI) and risk of mortality (ROM) categorized by All Patient Refined Diagnosis Related Groups (APR-DRG) seem to predict hospital readmission but lack large sample validation. Effects of risk reduction interventions including providing post-discharge outpatient visits remain uncertain. We aim to determine the accuracy of using SOI and ROM to predict readmission and further investigate the role of outpatient visits in association with hospital readmission.
METHODS: Hospital readmission data were reviewed retrospectively from September 2012 through June 2015. Patient demographics and clinical variables including insurance type, homeless status, substance abuse, psychiatric problems, length of stay, SOI, ROM, ICD-10 diagnoses and medications prescribed at discharge, and prescription ratio at discharge (number of medications prescribed divided by number of ICD-10 diagnoses) were analyzed using logistic regression. Relationships among SOI, type of hospital visits, time between hospital visits, and readmissions were also investigated.
RESULTS: A total of 6011 readmissions occurred from 55,532 index admissions. The adjusted odds ratios of SOI and ROM predicting readmissions were 1.31 (SOI: 95 % CI 1.25-1.38) and 1.09 (ROM: 95 % CI 1.05-1.14) separately. Ninety percent (5381/6011) of patients were readmitted from the Emergency Department (ED) or Urgent Care Center (UCC). Average time interval from index discharge date to ED/UCC visit was 9 days in both the no readmission and readmission groups (p > 0.05). Similar hospital readmission rates were noted during the first 10 days from index discharge regardless of whether post-index discharge patient clinic visits occurred when time-to-event analysis was performed.
CONCLUSIONS: SOI and ROM significantly predict hospital readmission risk in general. Most readmissions occurred among patients presenting for ED/UCC visits after index discharge. Simply providing early post-discharge follow-up clinic visits does not seem to prevent hospital readmissions.

PMID: 27724889 [PubMed - indexed for MEDLINE]

A Derivation and Validation Study of an Early Blood Transfusion Needs Score for Severe Trauma Patients.

Wed, 01/30/2019 - 08:23
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A Derivation and Validation Study of an Early Blood Transfusion Needs Score for Severe Trauma Patients.

J Clin Med Res. 2016 Aug;8(8):591-7

Authors: Wang H, Umejiego J, Robinson RD, Schrader CD, Leuck J, Barra M, Buca S, Shedd A, Bui A, Zenarosa NR

Abstract
BACKGROUND: There is no existing adequate blood transfusion needs determination tool that Emergency Medical Services (EMS) personnel can use for prehospital blood transfusion initiation. In this study, a simple and pragmatic prehospital blood transfusion needs scoring system was derived and validated.
METHODS: Local trauma registry data were reviewed retrospectively from 2004 through 2013. Patients were randomly assigned to derivation and validation cohorts. Multivariate logistic regression was used to identify the independent approachable risks associated with early blood transfusion needs in the derivation cohort in which a scoring system was derived. Sensitivity, specificity, and area under the receiver operational characteristic (AUC) were calculated and compared using both the derivation and validation data.
RESULTS: A total of 24,303 patients were included with 12,151 patients in the derivation and 12,152 patients in the validation cohorts. Age, penetrating injury, heart rate, systolic blood pressure, and Glasgow coma scale (GCS) were risks predictive of early blood transfusion needs. An early blood transfusion needs score was derived. A score > 5 indicated risk of early blood transfusion need with a sensitivity of 83% and a specificity of 80%. A sensitivity of 82% and a specificity of 80% were also found in the validation study and their AUC showed no statistically significant difference (AUC of the derivation = 0.87 versus AUC of the validation = 0.86, P > 0.05).
CONCLUSIONS: An early blood transfusion scoring system was derived and internally validated to predict severe trauma patients requiring blood transfusion during prehospital or initial emergency department resuscitation.

PMID: 27429680 [PubMed]