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Richard Robinson, MD

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NCBI: db=pubmed; Term=(robinson rd[Author]) AND (John Peter Smith[Affiliation] OR JPS Health Network[Affiliation] OR JPS [Affiliation] NOT Japan Pancreas Society[Affiliation])
Updated: 13 hours 55 min ago

Emergency Medicine Resident Efficiency and Emergency Department Crowding.

Fri, 08/02/2019 - 04:01
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Emergency Medicine Resident Efficiency and Emergency Department Crowding.

AEM Educ Train. 2019 Jul;3(3):209-217

Authors: Kirby R, Robinson RD, Dib S, Mclarty D, Shaikh S, Cheeti R, Ho AF, Schrader CD, Zenarosa NR, Wang H

Abstract
Objectives: Provider efficiency has been reported in the literature but there is a lack of efficiency analysis among emergency medicine (EM) residents. We aim to compare efficiency of EM residents of different training levels and determine if EM resident efficiency is affected by emergency department (ED) crowding.
Methods: We conducted a single-center retrospective observation study from July 1, 2014, to June 30, 2017. The number of new patients per resident per hour and provider-to-disposition (PTD) time of each patient were used as resident efficiency markers. A crowding score was assigned to each patient upon the patient's arrival to the ED. We compared efficiency among EM residents of different training levels under different ED crowding statuses. Dynamic efficiency changes were compared monthly through the entire academic year (July to next June).
Results: The study enrolled a total of 150,920 patients. A mean of 1.9 patients/hour was seen by PGY-1 EM residents in comparison to 2.6 patients/hour by PGY-2 and -3 EM residents. Median PTD was 2.8 hours in PGY-1 EM residents versus 2.6 hours in PGY-2 and -3 EM residents. There were no significant differences in acuity across all patients seen by EM residents. When crowded conditions existed, residency efficiency increased, but such changes were minimized when the ED became overcrowded. A linear increase of resident efficiency was observed only in PGY-1 EM residents throughout the entire academic year.
Conclusion: Resident efficiency improved significantly only during their first year of EM training. This efficiency can be affected by ED crowding.

PMID: 31360813 [PubMed]

Common step-wise interventions improved primary care clinic visits and reduced emergency department discharge failures: a large-scale retrospective observational study.

Fri, 07/12/2019 - 00:24
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Common step-wise interventions improved primary care clinic visits and reduced emergency department discharge failures: a large-scale retrospective observational study.

BMC Health Serv Res. 2019 Jul 04;19(1):451

Authors: Schrader CD, Robinson RD, Blair S, Shaikh S, Ho AF, D'Etienne JP, Kirby JJ, Cheeti R, Zenarosa NR, Wang H

Abstract
BACKGROUND: It is critical to understand whether providing health insurance coverage, assigning a dedicated Primary Care Physician (PCP), and arranging timely post-Emergency Department (ED) clinic follow-up can improve compliance with clinic visits and reduce ED discharge failures. We aim to determine the benefits of providing these common step-wise interventions and further investigate the necessity of urgent PCP referrals on behalf of ED discharged patients.
METHODS: This is a single-center retrospective observational study. All patients discharged from the ED over the period Jan 1, 2015 through Dec 31, 2017 were included in the study population. Step-wise interventions included providing charity health insurance, assigning a dedicated PCP, and providing ED follow-up clinics. PCP clinic compliance and ED discharge failures were measured and compared among groups receiving different interventions.
RESULT: A total of 227,627 patients were included. Fifty-eight percent of patients receiving charity insurance had PCP visits in comparison to 23% of patients without charity insurance (p < 0.001). Seventy-seven percent of patients with charity insurance and PCP assignments completed post-ED discharge PCP visits in comparison to only 4.5% of those with neither charity insurance nor PCP assignments (p < 0.001).
CONCLUSIONS: Step-wise interventions increased patient clinic follow-up compliance while simultaneously reducing ED discharge failures. Such interventions might benefit communities with similar patient populations.

PMID: 31272442 [PubMed - in process]

Identifying diverse concepts of discharge failure patients at emergency department in the USA: a large-scale retrospective observational study.

Thu, 07/04/2019 - 21:46
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Identifying diverse concepts of discharge failure patients at emergency department in the USA: a large-scale retrospective observational study.

BMJ Open. 2019 Jun 27;9(6):e028051

Authors: Schrader CD, Robinson RD, Blair S, Shaikh S, d'Etienne JP, Kirby JJ, Cheeti R, Zenarosa NR, Wang H

Abstract
OBJECTIVES: Identifying patients who are at high risk for discharge failure allows for implementation of interventions to improve their care. However, discharge failure is currently defined in literature with great variability, making targeted interventions more difficult. We aim to derive a screening tool based on the existing diverse discharge failure models.
DESIGN, SETTING AND PARTICIPANTS: This is a single-centre retrospective cohort study in the USA. Data from all patients discharged from the emergency department were collected from 1 January 2015 through 31 December 2017 and followed up within 30 days.
METHODS: Scoring systems were derived using modified Framingham methods. Sensitivity, specificity and area under the receiver operational characteristic (AUC) were calculated and compared using both the broad and restricted discharge failure models.
RESULTS: A total of 227 627 patients were included. The Screening for Healthcare fOllow-Up Tool (SHOUT) scoring system was derived based on the broad and restricted discharge failure models and applied back to the entire study cohort. A sensitivity of 80% and a specificity of 71% were found in SHOUT scores to identify patients with broad discharge failure with AUC of 0.83 (95% CI 0.83 to 0.84). When applied to a 3-day restricted discharge failure model, a sensitivity of 86% and a specificity of 60% were found to identify patients with AUC of 0.79 (95% CI 0.78 to 0.80).
CONCLUSION: The SHOUT scoring system was derived and used to screen and identify patients that would ultimately become discharge failures, especially when using broad definitions of discharge failure. The SHOUT tool was internally validated and can be used to identify patients across a wide spectrum of discharge failure definitions.

PMID: 31248927 [PubMed - in process]

Large observational study on risks predicting emergency department return visits and associated disposition deviations.

Thu, 05/02/2019 - 07:44
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Large observational study on risks predicting emergency department return visits and associated disposition deviations.

Clin Exp Emerg Med. 2019 May 07;:

Authors: Huggins C, Robinson RD, Knowles H, Cizenski J, Mbugua R, Laureano-Phillips J, Schrader CD, Zenarosa NR, Wang H

Abstract
Objective: A common emergency department (ED) patient care outcome metric is 72-hour ED return visits (EDRVs). Risks predictive of EDRV vary in different studies. However, risk differences associated with related versus unrelated EDRV and subsequent EDRV disposition deviations (EDRVDD) are rarely addressed. We aim to compare the potential risk patterns predictive of related and unrelated EDRV and further determine those potential risks predictive of EDRVDD.
Methods: We conducted a large retrospective observational study from September 1, 2015 through June 30, 2016. ED Patient demographic characteristics and clinical metrics were compared among patients of 1) related; 2) unrelated; and 3) no EDRVs. EDRVDD was defined as obvious disposition differences between initial ED visit and return visits. A multivariate multinomial logistic regression was performed to determine the independent risks predictive of EDRV and EDRVDD after adjusting for all confounders.
Results: A total of 63,990 patients were enrolled; 4.65% were considered related EDRV, and 1.80% were unrelated. The top risks predictive of EDRV were homeless, patient left without being seen, eloped, or left against medical advice. The top risks predictive of EDRVDD were geriatric and whether patients had primary care physicians regardless as to whether patient returns were related or unrelated to their initial ED visits.
Conclusion: Over 6% of patients experienced ED return visits within 72 hours. Though risks predicting such revisits were multifactorial, similar risks were identified not only for ED return visits, but also for return ED visit disposition deviations.

PMID: 31036785 [PubMed - as supplied by publisher]

Status of Emergency Department Seventy-Two Hour Return Visits Among Homeless Patients.

Wed, 03/06/2019 - 17:13
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Status of Emergency Department Seventy-Two Hour Return Visits Among Homeless Patients.

J Clin Med Res. 2019 Mar;11(3):157-164

Authors: Knowles H, Huggins C, Robinson RD, Mbugua R, Laureano-Phillips J, Trivedi SM, Kirby J, Zenarosa NR, Wang H

Abstract
Background: We aim to externally validate the status of emergency department (ED) appropriate utilization and 72-h ED returns among homeless patients.
Methods: This is a retrospective single-center observational study. Patients were divided into two groups (homeless versus non-homeless). Patients' general characteristics, clinical variables, ED appropriate utilization, and ED return disposition deviations were compared and analyzed separately.
Results: Study enrolled a total of 63,990 ED visits. Homeless patients comprised 9.3% (5,926) of visits. Higher ED 72-h returns occurred among homeless patients in comparison to the non-homeless patients (17% versus 5%, P < 0.001). Rate of significant ED disposition deviations (e.g., admission, triage to operation room, or death) on return visits were lower in homeless patients when compared to non-homeless patient populations (15% versus 23%, P < 0.001).
Conclusions: Though ED return rate was higher among homeless patients, return visit case management seems appropriate, indicating that 72-h ED returns might not be an optimal healthcare quality measurement for homeless patients.

PMID: 30834037 [PubMed]

HEART Score Risk Stratification of Low-Risk Chest Pain Patients in the Emergency Department: A Systematic Review and Meta-Analysis.

Wed, 02/06/2019 - 09:11
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HEART Score Risk Stratification of Low-Risk Chest Pain Patients in the Emergency Department: A Systematic Review and Meta-Analysis.

Ann Emerg Med. 2019 Feb 01;:

Authors: Laureano-Phillips J, Robinson RD, Aryal S, Blair S, Wilson D, Boyd K, Schrader CD, Zenarosa NR, Wang H

Abstract
STUDY OBJECTIVE: The objectives of this systematic review and meta-analysis are to appraise the evidence in regard to the diagnostic accuracy of a low-risk History, ECG, Age, Risk Factors, and Troponin (HEART) score for prediction of major adverse cardiac events in emergency department (ED) patients. These included 4 subgroup analyses: by geographic region, the use of a modified low-risk HEART score (traditional HEART score [0 to 3] in addition to negative troponin results), using conventional versus high-sensitivity troponin assays in the HEART score, and a comparison of different post-ED-discharge patient follow-up intervals.
METHODS: We searched MEDLINE, EBSCO, Web of Science, and Cochrane Database for studies on the diagnostic performance of low-risk HEART scores to predict major adverse cardiac events among ED chest pain patients. Two reviewers independently screened articles for inclusion, assessed the quality of studies with both an adapted Quality Assessment of Diagnostic Accuracy Studies version 2 tool and an internally developed tool that combined components of the Quality in Prognostic Studies; Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies; and Grading of Recommendations Assessment, Development and Evaluation. Pooled sensitivity, specificity, positive predictive value, negative predictive value, and positive and negative likelihood ratios were calculated.
RESULTS: There were 25 studies published from 2010 to 2017, with a total of 25,266 patients included in the final meta-analysis, of whom 9,919 (39.3%) were deemed to have low-risk HEART scores (0 to 3). Among patients with low-risk HEART scores, short-term major adverse cardiac events (30 days to 6 weeks) occurred in 2.1% of the population (182/8,832) compared with 21.9% of patients (3,290/15,038) with non-low-risk HEART scores (4 to 10). For patients with HEART scores of 0 to 3, the pooled sensitivity of short-term major adverse cardiac event predictions was 0.96 (95% confidence interval [CI] 0.93 to 0.98), specificity was 0.42 (95% CI 0.36 to 0.49), positive predictive value was 0.19 (95% CI 0.14 to 0.24), negative predictive value was 0.99 (95% CI 0.98 to 0.99), positive likelihood ratio was 1.66 (95% CI 1.50 to 1.85), and negative likelihood ratio was 0.09 (95% CI 0.06 to 0.15). Subgroup analysis showed that lower short-term major adverse cardiac events occurred among North American patients (0.7%), occurred when modified low-risk HEART score was used (0.8%), or occurred when high-sensitivity troponin was used for low-risk HEART score calculations (0.8%).
CONCLUSION: In this meta-analysis, despite its use in different patient populations, the troponin type used, and timeline of follow-up, a low-risk HEART score had high sensitivity, negative predictive value, and negative likelihood ratio for predicting short-term major adverse cardiac events, although risk of bias and statistical heterogeneity were high.

PMID: 30718010 [PubMed - as supplied by publisher]

Risks predicting prolonged hospital discharge boarding in a regional acute care hospital.

Wed, 01/30/2019 - 08:31
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Risks predicting prolonged hospital discharge boarding in a regional acute care hospital.

BMC Health Serv Res. 2018 01 30;18(1):59

Authors: Shaikh SA, Robinson RD, Cheeti R, Rath S, Cowden CD, Rosinia F, Zenarosa NR, Wang H

Abstract
BACKGROUND: Prolonged hospital discharge boarding can impact patient flow resulting in upstream Emergency Department crowding. We aim to determine the risks predicting prolonged hospital discharge boarding and their direct and indirect effects on patient flow.
METHODS: Retrospective review of a single hospital discharge database was conducted. Variables including type of disposition, disposition boarding time, case management consultation, discharge medications prescriptions, severity of illness, and patient homeless status were analyzed in a multivariate logistic regression model. Hospital charges, potential savings of hospital bed hours, and whether detailed discharge instructions provided adequate explanations to patients were also analyzed.
RESULTS: A total of 11,527 admissions was entered into final analysis. The median discharge boarding time was approximately 2 h. Adjusted Odds Ratio (AOR) of patients transferring to other hospitals was 7.45 (95% CI 5.35-10.37), to court or law enforcement custody was 2.51 (95% CI 1.84-3.42), and to a skilled nursing facility was 2.48 (95% CI 2.10-2.93). AOR was 0.57 (95% CI 0.47-0.71) if the disposition order was placed during normal office hours (0800-1700). AOR of early case management consultation was 1.52 (95% CI 1.37-1.68) versus 1.73 (95% CI 1.03-2.89) for late consultation. Eighty-eight percent of patients experiencing discharge boarding times within 2 h of disposition expressed positive responses when questioned about the quality of explanations of discharge instructions and follow-up plans based on satisfaction surveys. Similar results (86% positive response) were noted among patients whose discharge boarding times were prolonged (> 2 h, p = 0.44). An average charge of $6/bed/h was noted in all hospital discharges. Maximizing early discharge boarding (≤ 2 h) would have resulted in 16,376 hospital bed hours saved thereby averting $98,256.00 in unnecessary dwell time charges in this study population alone.
CONCLUSION: Type of disposition, case management timely consultation, and disposition to discharge dwell time affect boarding and patient flow in a tertiary acute care hospital. Efficiency of the discharge process did not affect patient satisfaction relative to the perceived quality of discharge instruction and follow-up plan explanations. Prolonged disposition to discharge intervals result in unnecessary hospital bed occupancy thereby negatively impacting hospital finances while delivering no direct benefit to patients.

PMID: 29378577 [PubMed - indexed for MEDLINE]