Search this website

Richard Robinson, MD

Association between burnout and wellness culture among emergency medicine providers

Mon, 04/12/2021 - 05:00

Clin Exp Emerg Med. 2021 Mar;8(1):55-64. doi: 10.15441/ceem.20.074. Epub 2021 Mar 31.

ABSTRACT

OBJECTIVE: Burnout is a common occurrence among healthcare providers and has been associated with provider wellness culture. However, this association has not been extensively studied among emergency medicine (EM) providers. We aim to determine the association between EM provider burnout and their culture of wellness, and to elicit the independent wellness culture domains most predictive of burnout prevention.

METHODS: This was a multi-center observational study. We enrolled EM physicians and advanced practice providers from sixteen different emergency departments (EDs). Provider wellness culture and burnout surveys were performed. The wellness culture domains included in this study are personal/organizational value alignment, provider appreciation, leadership quality, self-controlled scheduling, peer support, and family support. Correlations between each wellness culture domain and burnout were analyzed by Pearson correlation co-efficiency, and their associations were measured by multivariate logistic regression with adjustments of other confounders.

RESULTS: A total of 242 ED provider surveys were entered for final analysis. The overall burnout rate was 54% (130/242). Moderate correlations were found between burnout and two wellness culture domains (value alignment: r=-0.43, P<0.001 and provider appreciation: r=-0.49, P<0.001). The adjusted odds ratio of provider appreciation associated with burnout was 0.44 (95% confidence interval, 0.25-0.77; P=0.004), adjusted odds ratio of family support was 0.67 (95% confidence interval, 0.48-0.95; P=0.025).

CONCLUSION: ED providers have a relatively high burnout rate. Provider burnout might have certain associations with wellness culture domains. Provider appreciation and family support seem to play important roles in burnout protection.

PMID:33845524 | DOI:10.15441/ceem.20.074

Mortality association between obesity and pneumonia using a dual restricted cohort model.

Tue, 07/28/2020 - 04:29
Related Articles

Mortality association between obesity and pneumonia using a dual restricted cohort model.

Obes Res Clin Pract. 2020 Jul 16;:

Authors: Wang H, Lee CC, Chou EH, Hsu WT, Robinson RD, Su KY, Kirby JJ, Hassani D

Abstract
BACKGROUND: An obesity survival paradox has been reported among obese patients with pneumonia.
AIMS: To determine the impact of obesity on pneumonia outcomes and analyze the correlation between in-hospital all-cause mortality and obesity among patients with pneumonia.
METHODS: The United States Nationwide Readmissions Database (NRD) was retrospectively analyzed for patients with pneumonia from 2013 to 2014. We used a step-wise restricted and propensity score matching cohort model (dual model) to compare mortality rates and other outcomes among pneumonia patients based on BMI. Mortality was calculated by a Cox proportional hazard model, adjusted for potential confounders with propensity score matched analysis.
RESULTS: A total of 70,886,775 patients were registered in NRD during the study period. Of these, 7,786,913 patients (11.0%) were considered obese and 1,652,456 patients (2.3%) were admitted to the hospital with pneumonia. Based on the step-wise restricted cohort model, the hazard ratio comparing the mortality rates among obese pneumonia patients to mortality rates among normal BMI pneumonia patients was 0.75 (95% CI 0.60-0.94). The propensity score matched analysis estimated a hazard rate of 0.84 (95% CI 0.79-0.90) and the hazard ratio estimated from the dual model was 0.82 (95% CI 0.63-1.07).
CONCLUSIONS: With the application of a dual model, there appears to be no significant difference in mortality of obese patients with pneumonia compared to normal BMI patients with pneumonia.

PMID: 32684413 [PubMed - as supplied by publisher]

Productivity, efficiency, and overall performance comparisons between attendings working solo versus attendings working with residents staffing models in an emergency department: A Large-Scale Retrospective Observational Study.

Sun, 02/09/2020 - 12:56
Related Articles

Productivity, efficiency, and overall performance comparisons between attendings working solo versus attendings working with residents staffing models in an emergency department: A Large-Scale Retrospective Observational Study.

PLoS One. 2020;15(2):e0228719

Authors: Robinson RD, Dib S, Mclarty D, Shaikh S, Cheeti R, Zhou Y, Ghasemi Y, Rahman M, Schrader CD, Wang H

Abstract
BACKGROUND AND OBJECTIVE: Attending physician productivity and efficiency can be affected when working simultaneously with Residents. To gain a better understanding of this effect, we aim to compare productivity, efficiency, and overall performance differences among Attendings working solo versus working with Residents in an Emergency Department (ED).
METHODS: Data were extracted from the electronic medical records of all patients seen by ED Attendings and/or Residents during the period July 1, 2014 through June 30, 2017. Attending productivity was measured based on the number of new patients enrolled per hour per provider. Attending efficiency was measured based on the provider-to-disposition time (PDT). Attending overall performance was measured by Attending Performance Index (API). Furthermore, Attending productivity, efficiency, and overall performance metrics were compared between Attendings working solo and Attendings working with Residents. The comparisons were analyzed after adjusting for confounders via propensity score matching.
RESULTS: A total of 15 Attendings and 266 Residents managing 111,145 patient encounters over the study period were analyzed. The mean (standard deviation) of Attending productivity and efficiency were 2.9 (1.6) new patients per hour and 2.7 (1.8) hours per patient for Attendings working solo, in comparison to 3.3 (1.9) and 3.0 (2.0) for Attendings working with Residents. When paired with Residents, the API decreased for those Attendings who had a higher API when working solo (average API dropped from 0.21 to 0.19), whereas API increased for those who had a lower API when working solo (average API increased from 0.13 to 0.16).
CONCLUSION: In comparison to the Attending working solo staffing model, increased productivity with decreased efficiency occurred among Attendings when working with Residents. The overall performance of Attendings when working with Residents varied inversely against their performance when working solo.

PMID: 32023302 [PubMed - in process]

Role of ED crowding relative to trauma quality care in a Level 1 Trauma Center.

Sat, 12/21/2019 - 08:22
Related Articles

Role of ED crowding relative to trauma quality care in a Level 1 Trauma Center.

Am J Emerg Med. 2019 04;37(4):579-584

Authors: Singh N, Robinson RD, Duane TM, Kirby JJ, Lyell C, Buca S, Gandhi R, Mann SM, Zenarosa NR, Wang H

Abstract
OBJECTIVE: Trauma Quality Improvement Program participation among all trauma centers has shown to improve patient outcomes. We aim to identify trauma quality events occurring during the Emergency Department (ED) phase of care.
METHODS: This is a single-center observational study using consecutively registered data in local trauma registry (Jan 1, 2016-Jun 30, 2017). Four ED crowding scores as determined by four different crowding estimation tools were assigned to each enrolled patient upon arrival to the ED. Patient related (age, gender, race, severity of illness, ED disposition), system related (crowding, night shift, ED LOS), and provider related risk factors were analyzed in a multivariate logistic regression model to determine associations relative to ED quality events.
RESULTS: Total 5160 cases were enrolled among which, 605 cases were deemed ED quality improvement (QI) cases and 457 cases were ED provider related. Similar percentages of ED QI cases (10-12%) occurred across the ED crowding status range. No significant difference was appreciated in terms of predictability of ED QI cases relative to different crowding status after adjustment for potential confounders. However, an adjusted odds ratio of 1.64 (95% CI, 1.17-2.30, p < 0.01) regarding ED LOS ≥2 h predictive of ED related quality issues was noted when analyzed using multivariate logistic regression.
CONCLUSION: Provider related issues are a common contributor to undesirable outcomes in trauma care. ED crowding lacks significant association with poor trauma quality care. Prolonged ED LOS (≥2 h) appears to be linked with unfavorable outcomes in ED trauma care.

PMID: 30139579 [PubMed - indexed for MEDLINE]

Mortality association between obesity and pneumonia using a dual restricted cohort model.

Fri, 10/25/2019 - 19:28
Related Articles

Mortality association between obesity and pneumonia using a dual restricted cohort model.

Obes Res Clin Pract. 2019 Oct 18;:

Authors: Wang H, Lee CC, Chou EH, Hsu WT, Robinson RD, Su KY, Kirby JJ, Hassani D

Abstract
BACKGROUND: An obesity survival paradox has been reported among obese patients with pneumonia.
AIMS: To determine the impact of obesity on pneumonia outcomes and analyze the correlation between in-hospital all-cause mortality and obesity among patients with pneumonia.
METHODS: The United States Nationwide Readmissions Database (NRD) was retrospectively analyzed for patients with pneumonia from 2013 to 2014. We used a step-wise restricted and propensity score matching cohort model (dual model) to compare mortality rates and other outcomes among pneumonia patients based on BMI. Mortality was calculated by a Cox proportional hazard model, adjusted for potential confounders with propensity score matched analysis.
RESULTS: A total of 70,886,775 patients were registered in NRD during the study period. Of these, 7,786,913 patients (11.0%) were considered obese and 1,652,456 patients (2.3%) were admitted to the hospital with pneumonia. Based on the step-wise restricted cohort model, the hazard ratio comparing the mortality rates among obese pneumonia patients to mortality rates among normal BMI pneumonia patients was 0.75 (95% CI 0.60-0.94). The propensity score matched analysis estimated a hazard rate of 0.84 (95% CI 0.79-0.90) and the hazard ratio estimated from the dual model was 0.82 (95% CI 0.63-1.07).
CONCLUSIONS: With the application of a dual model, there appears to be no significant difference in mortality of obese patients with pneumonia compared to normal BMI patients with pneumonia.

PMID: 31635969 [PubMed - as supplied by publisher]

Emergency Medicine Resident Efficiency and Emergency Department Crowding.

Fri, 08/02/2019 - 04:01
Related Articles

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
Related Articles

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
Related Articles

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
Related Articles

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
Related Articles

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
Related Articles

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
Related Articles

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]

Association between emergency physician self-reported empathy and patient satisfaction

Fri, 09/14/2018 - 05:00

PLoS One. 2018 Sep 13;13(9):e0204113. doi: 10.1371/journal.pone.0204113. eCollection 2018.

ABSTRACT

BACKGROUND: Higher physician self-reported empathy has been associated with higher overall patient satisfaction. However, more evidence-based research is needed to determine such association in an emergent care setting.

OBJECTIVE: To evaluate the association between physician self-reported empathy and after-care instant patient-to-provider satisfaction among Emergency Department (ED) healthcare providers with varying years of medical practice experience.

RESEARCH DESIGN: A prospective observational study conducted in a tertiary care hospital ED.

METHODS: Forty-one providers interacted with 1,308 patients across 1,572 encounters from July 1 through October 31, 2016. The Jefferson Scale of Empathy (JSE) was used to assess provider empathy. An after-care instant patient satisfaction survey, with questionnaires regarding patient-to-provider satisfaction specifically, was conducted prior to the patient moving out of the ED. The relation between physician empathy and patient satisfaction was estimated using risk ratios (RR) and their corresponding 95% confidence limits (CL) from log-binomial regression models.

RESULTS: Emergency Medicine (EM) residents had the lowest JSE scores (median 111; interquartile range [IQR]: 107-122) and senior physicians had the highest scores (median 119.5; IQR: 111-129). Similarly, EM residents had the lowest percentage of "very satisfied" responses (65%) and senior physicians had the highest reported percentage of "very satisfied" responses (69%). There was a modest positive association between JSE and satisfaction (RR = 1.04; 95% CL: 1.00, 1.07).

CONCLUSION: This study provides evidence of a positive association between ED provider self-reported empathy and after-care instant patient-to-provider satisfaction. Overall higher empathy scores were associated with higher patient satisfaction, though minor heterogeneity occurred between different provider characteristics.

PMID:30212564 | PMC:PMC6136813 | DOI:10.1371/journal.pone.0204113

Standardized Reporting System Use During Handoffs Reduces Patient Length of Stay in the Emergency Department

Wed, 03/28/2018 - 05:00

J Clin Med Res. 2018 May;10(5):445-451. doi: 10.14740/jocmr3375w. Epub 2018 Mar 16.

ABSTRACT

BACKGROUND: Emergency department (ED) shift handoffs are potential sources of delay in care. We aimed to determine the impact that using standardized reporting tool and process may have on throughput metrics for patients undergoing a transition of care at shift change.

METHODS: We performed a prospective, pre- and post-intervention quality improvement study from September 1 to November 30, 2015. A handoff procedure intervention, including a mandatory workshop and personnel training on a standard reporting system template, was implemented. The primary endpoint was patient length of stay (LOS). A comparative analysis of differences between patient LOS and various handoff communication methods were assessed pre- and post-intervention. Communication methods were entered a multivariable logistic regression model independently as risk factors for patient LOS.

RESULTS: The final analysis included 1,006 patients, with 327 comprising the pre-intervention and 679 comprising the post-intervention populations. Bedside rounding occurred 45% of the time without a standard reporting during pre-intervention and increased to 85% of the time with the use of a standard reporting system in the post-intervention period (P < 0.001). Provider time (provider-initiated care to patient care completed) in the pre-intervention period averaged 297 min, but decreased to 265 min in the post-intervention period (P < 0.001). After adjusting for other communication methods, the use of a standard reporting system during handoff was associated with shortened ED LOS (OR = 0.60, 95% CI 0.40 - 0.90, P < 0.05).

CONCLUSIONS: Standard reporting system use during emergency physician handoffs at shift change improves ED throughput efficiency and is associated with shorter ED LOS.

PMID:29581808 | PMC:PMC5862093 | DOI:10.14740/jocmr3375w

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

Tue, 10/10/2017 - 05:00

Int J Qual Health Care. 2017 Oct 1;29(5):722-727. doi: 10.1093/intqhc/mzx097.

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 | DOI:10.1093/intqhc/mzx097

Optimal Measurement Interval for Emergency Department Crowding Estimation Tools

Mon, 07/10/2017 - 05:00

Ann Emerg Med. 2017 Nov;70(5):632-639.e4. doi: 10.1016/j.annemergmed.2017.04.012. Epub 2017 Jul 6.

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 | DOI:10.1016/j.annemergmed.2017.04.012

Traumatic Abdominal Solid Organ Injury Patients Might Benefit From Thromboelastography-Guided Blood Component Therapy

Tue, 04/11/2017 - 05:00

J Clin Med Res. 2017 May;9(5):433-438. doi: 10.14740/jocmr3005w. Epub 2017 Apr 1.

ABSTRACT

BACKGROUND: Thromboelastography (TEG) has been utilized for the guidance of blood component therapy (BCT). We aimed to investigate the association between emergent TEG-guided BCT and clinical outcomes in patients with traumatic abdominal solid organ (liver and/or spleen) injuries.

METHODS: A single center retrospective study of patients who sustained traumatic liver and/or spleen injuries receiving emergent BCT was conducted. TEG was ordered in all these patients. Patient demographics, general injury information, outcomes, BCT, and TEG parameters were analyzed and compared in patients receiving TEG-guided BCT versus those without.

RESULTS: A total of 166 patients were enrolled, of whom 52% (86/166) received TEG-guided BCT. A mortality of 12% was noted among patients with TEG-guided BCT when compared with 19% of mortality in patients with non-TEG-guided BCT (P > 0.05). An average of 4 units of packed red blood cell (PRBC) was received in patients with TEG-guided BCT when compared to an average of 9 units of PRBC received in non-TEG-guided BCT patients (P < 0.01). A longer hospital length of stay (LOS, 19 ± 16 days) was found among non-TEG-guided BCT patients when compared to the TEG-guided BCT group (14 ± 12 days, P < 0.05). TEG-guided BCT showed as an independent factor associated with hospital LOS after other variables were adjusted (coefficiency: 5.44, 95% confidence interval: 0.69 - 10.18).

CONCLUSIONS: Traumatic abdominal solid organ injury patients receiving blood transfusions might benefit from TEG-guided BCT as indicated by less blood products needed and less hospitalization stay among the cohort.

PMID:28392864 | PMC:PMC5380177 | DOI:10.14740/jocmr3005w

Chest Pain Risk Scores Can Reduce Emergent Cardiac Imaging Test Needs With Low Major Adverse Cardiac Events Occurrence in an Emergency Department Observation Unit

Wed, 11/16/2016 - 05:00

Crit Pathw Cardiol. 2016 Dec;15(4):145-151. doi: 10.1097/HPC.0000000000000090.

ABSTRACT

OBJECTIVE: To compare and evaluate the performance of the HEART, Global Registry of Acute Coronary Events (GRACE), and Thrombolysis in Myocardial Infarction (TIMI) scores to predict major adverse cardiac event (MACE) rates after index placement in an emergency department observation unit (EDOU) and to determine the need for observation unit initiation of emergent cardiac imaging tests, that is, noninvasive cardiac stress tests and invasive coronary angiography.

METHODS: A prospective observational single center study was conducted from January 2014 through June 2015. EDOU chest pain patients were included. HEART, GRACE, and TIMI scores were categorized as low (HEART ≤ 3, GRACE ≤ 108, and TIMI ≤1) versus elevated based on thresholds suggested in prior studies. Patients were followed for 6 months postdischarge. The results of emergent cardiac imaging tests, EDOU length of stay (LOS), and MACE occurrences were compared. Student t test was used to compare groups with continuous data, and χ testing was used for categorical data analysis.

RESULTS: Of 986 patients, emergent cardiac imaging tests were performed on 62%. A majority of patients were scored as low risk by all tools (85% by HEART, 81% by GRACE, and 80% by TIMI, P < 0.05). The low-risk patients had few abnormal cardiac imaging test results as compared with patients scored as intermediate to high risk (1% vs. 11% in HEART, 1% vs. 9% in TIMI, and 2% vs. 4% in GRACE, P < 0.05). The average LOS was 33 hours for patients with emergent cardiac imaging tests performed and 25 hours for patients without (P < 0.05). MACE occurrence rate demonstrated no significant difference regardless of whether tests were performed emergently (0.31% vs. 0.97% in HEART, 0.27% vs. 0.95% in TIMI, and 0% vs. 0.81% in GRACE, P > 0.05).

CONCLUSIONS: Chest pain risk stratification via clinical decision tool scores can minimize the need for emergent cardiac imaging tests with less than 1% MACE occurrence, especially when the HEART score is used.

PMID:27846006 | DOI:10.1097/HPC.0000000000000090

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

Wed, 10/12/2016 - 05:00

BMC Health Serv Res. 2016 Oct 10;16(1):564. doi: 10.1186/s12913-016-1814-7.

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 | PMC:PMC5057382 | DOI:10.1186/s12913-016-1814-7

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

Tue, 07/19/2016 - 05:00

J Clin Med Res. 2016 Aug;8(8):591-7. doi: 10.14740/jocmr2598w. Epub 2016 Jul 1.

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 | PMC:PMC4931805 | DOI:10.14740/jocmr2598w

Pages