- Email: [email protected]
15: Satisfaction of Emergency Department Hallway Patients
Research Forum Abstracts in 2008. 2008 patients were admitted in 2007 compared to 2522 patients in 2008. LOS of admitted patients from decision to admit until they leave the department increased from 551 minutes (⫹/⫺105) in 2007 to 979 minutes (⫹/⫺ 89) in 2008. LOS of patients from arrival till disposition reduced from 279 minutes (⫹/⫺ 28) in 2007 to 270 minutes (⫹/⫺ 22) in 2008. Conclusion: Despite the significant increase in input and output, implementation of triage physician and clinical operation management consultant provided benefits to throughput of crowded ED. The results strongly suggest that the implementation of this intervention could provide significant improvement to the delivery of emergency medical care in a tertiary care ED.
12
When the Emergency Department Is Packed Can Physician Assistants Pick Up the Pace? An Analysis of Physician Assistant Productivity Related to Patient Volume
Brook C, Chomut A, Jeanmonod R/Albany Medical College, Albany, NY; St. Luke’s Hospital, Bethlehem, PA
Background: The volume of patients seen in an emergency department (ED) is highly variable. It has been determined that resident productivity is not highly correlated with volume, but the relationship between physician assistant (PA) productivity and volume has not been studied. Study Objective: To determine whether PA productivity varies with ED census. Methods: A retrospective review was conducted of all ED visits at a level one trauma center during June and July 2007. The PA who first signed up for the patient and dictated the patient’s chart was considered to be the primary caregiver. All patients seen by PAs were included in the study. The hour during which care was initiated was defined as the hour that a PA electronically signed up for a patient. Productivity was calculated as the number of patients upon which care was initiated each hour. Data was collected regarding the total number of patients registered in the ED from 0700 to 2359 each day of the study period, as PAs do not work overnights at our institution. This was then broken down to patients registered per hour to determine ED volume per hour. Regression analysis was used to determine the relationship that hourly and daily volume had on PA productivity. Monthly Relative Value Units (RVUs) were also collected for the PAs during the study period. Results: During June and July 2007, there were 160 PA shifts. The number of patients seen in the ED per hour ranged from 0 –22 patients (Mean: 9.4 Standard Deviation: 3.9). Anywhere from 133–198 patients were seen daily (Mean: 160.4, Standard Deviation: 14.8). Regression analysis examining shift productivity related to daily volume showed a R2 of 0.01. Regression analysis of productivity per hour plotted against volume per hour yielded a R2 of 0.02. Productivity in terms of mean RVUs per hour during the study period was calculated as 2.35 RVUs/hour (95% CI ⫽ 1.98 –2.72). Conclusion: PA productivity does not correlate with the total or hourly volume of patients seen in the ED.
13
Utilizing Time-Driven Activity-Based Costing in the Emergency Department
Bank DE, McIlrath T/Phoenix Children’s Hospital, Phoenix, AZ
Study Objectives: Traditionally employed health care costing methods may not accurately reflect actual costs of emergency department (ED) service. The introduction of a practical costing tool using a time driven activity-based costing (TDABC) model allows ED directors to understand the costs of ED service and make decisions on the allocation of resources. Methods: This study was conducted using data from a high volume pediatric ED in a free-standing children’s hospital. The TDABC model was utilized to estimate costs of provider resources and apply them to three specific clinical scenarios common to any ED service: a simple laceration repair of an extremity (⬍2.5cm), a mild asthma exacerbation requiring respiratory therapy, and acute gastroenteritis with mild dehydration requiring intravenous fluid therapy. We compared our calculated costs for each of these three clinical scenarios with the standard Medicaid Outpatient Prospective Payment System (OPPS) and physician fee reimbursement schedules for 2008. The total direct and indirect costs to the ED were obtained from 2008 hospital accounting. Costs of medications and supplies were obtained from hospital materials management and pharmacy accounting and were treated as separate entities. Results: In each of the 3 clinical scenarios, combined 2008 OPPS and physician reimbursement was greater than the total ED costs derived using TDABC. In
Volume , . : September
Scenario 1: a simple laceration repair of an extremity (⬍2.5cm), the Medicaid reimbursement was $581.77 and the estimated actual cost was $365.53 (profit margin 37%). In Scenario 2: a child with mild asthma exacerbation requiring respiratory therapy, the Medicaid reimbursement was $501.87 versus the estimated actual cost of $491.61 (profit margin 2%). In Scenario 3: a child with acute gastroenteritis and mild dehydration requiring intravenous fluid therapy, the Medicaid reimbursement was $523.00 versus the estimated actual cost of $491.43 (profit margin 6%). Conclusion: TDABC may be utilized as an effective and accurate tool to estimate the true cost of ED service. For any given patient encounter, the costs of service vary greatly based on the proportion and time of resources utilized. TDABC analysis can be used by ED directors to help determine the allocation of ED clinical resources. TDABC analysis of service can be used as a tool to help development professional and facility reimbursement strategies with commercial payers.
14
An Analysis of Emergency Department Flow, Severity and Congestion Factors That Are Associated With Decreases in the Left Without Being Seen Rate
Sattarian M, Shesser R/George Washington University, Washington, DC
Study Objective: During the last 3 years, the overall left without being seen (LWBS) rate in our academic, urban emergency department (ED) decreased from 4.6% (2006) to 3.2 % (2008) despite an increase in ED census and the absence of specific process change that focused on LWBS rate reduction. This analysis examines the strengths of association between the LWBS rate and a group of standard ED flow, congestion, and severity parameters. Methods: Data on all visits during calendar years 2006 – 8 to the GW Hospital ED were tracked with an EMR application that required assignment of a specific discharge category for every arrival. The LWBS category included all registrants who left either before or after nursing triage, but before being seen by a physician. Data were analyzed by hour for each of the 26,304 hours in the study period. The LWBS patient number for each hour during this period was compared to the mean arrivalbed (waiting) times for ambulatory patients arriving that same hour who successfully completed their evaluation, their mean Emergency Severity Index scores, the number of patient arrivals during that hour, and the total number of patients in the ED treatment area and lobby at each hour’s end. Results: During the analysis period, 187,663 patients were registered; 128,430 walk-ins (68.4%) and 59,233 ambulance arrivals (31.6%). 7,543 patients LWBS, 6,705 (88.9%) of whom were walk-ins and 838 (11.1%) arrived by EMS. LWBS rates for the three year analysis period were 4.0% overall, 5.2% for walk-ins and 1.4% for ambulance arrivals. The LWBS rate for walk-ins decreased by 36% from 5.5% (July–December, 2006) to 3.5% (July–December 2008) (P ⬍ 0.001). During the analysis period, mean waiting times for ambulatory arrivals decreased from 61.4 minutes (2006) to 52.6 minutes (2008); mean total hourly arrival volume increased from 6.9 patients (2006) to 7.5 patients (2008); and mean, total end-hourly ED census increased from 36.5 patients (2006) to 39.5 patients (2008). Measuring the strength of association between the hourly LWBS patients and that same hour’s waiting times, arrival volume, Emergency Severity Index acuity, and total end-hourly ED census demonstrated highly significant relationships between LWBS and waiting times (P ⬍ 0.001, r: 0.48) and total ED census (P ⬍ 0.001, r: 0.34). There was a weaker relationship with arrival intensity (P ⬍ 0.001, r: 0.26), and no relationship with mean patient acuity. Conclusion: ED process improvements that lead to a modest decrease in patient waiting time, may achieve larger, proportional decreases in the ED’s LWBS rate. Although decreased waiting time in our setting was achieved by “front-end” process improvement, “back-end” strategies that reduce total ED census may have a greater effect on reducing the LWBS rate due to the strong association between LWBS and total ED census. It is still possible to lower LWBS rates during periods of increasing ED census and congestion.
15
Satisfaction of Emergency Department Hallway Patients
Stiffler KA, Wilber ST, Blanda M, Nielson J, Winot S, Kline J/ Summa Health System/NEOUCOMP, Akron, OH
Study Objectives: Emergency department (ED) crowding is recognized as a national problem and has reached epidemic proportions. During times of acute ED crowding, patients experience their most significant delay while waiting for an ED bed. Many EDs attempt to ameliorate this problem by treating non-urgent conditions in hallway treatment areas instead of regular treatment rooms. Many studies are
Annals of Emergency Medicine S5
Research Forum Abstracts available on patient satisfaction, but none specifically address the satisfaction of patients who are assigned hallway beds in the ED. We conducted a study to evaluate patients’ opinions, concerns, and satisfaction about being placed in hallway treatment spaces for their ED care. Methods: A cross-sectional study of patients assigned to a hallway treatment space at Akron City Hospital ED, a 72,500 adult visit urban community teaching hospital, was performed. Sequential patients who were placed in hallway treatment spaces during peak volume hours were asked to complete a confidential, self-administered survey regarding hallway treatment issues. The initial questions asked how patients felt about various issues pertaining to being treated in the hallway using a 5-point Likert scale. The second portion of the survey used 100mm visual analog scale questions (0⫽not satisfied, 100⫽satisfied) to determine satisfaction levels with regard to treatment location, medical care, and overall satisfaction. Data are reported as means and proportions with 95% confidence intervals (mean 95% CI). Results: A total of 100 patients with a mean age of 41.6⫾16.4 years completed the survey. Fifty nine percent were female. Areas of greatest concern for patients included feeling in the way (60%, 95% CI 49.7– 69.7), having no room for visitors (57%, 95% CI 46.7– 66.9), and a lack of privacy (56%, 95% CI 45.7– 65.9). Forty two percent (95% CI 32.2–52.3) identified safety as a concern. Overall visit satisfaction scores were 52.77 (95% CI 46.9 –58.6), while satisfaction with regard to medical care revealed 70.27 (95% CI 65.0 –75.5). Satisfaction with regard to hallway treatment location scored 46.31 (95% CI 39.7–52.9). Thirty-four percent of patients (95% CI 24.8 – 44.1) surveyed were less likely to recommend our ED to others based on treatment location, while 26% (95% CI 17.7–35.7) were less likely to recommend this hospital system. When questioned about willingness to wait any longer for a treatment room, 75% (95% CI 65.3– 83.1) preferred to be treated in the hallway immediately. The most common Emergency Severity Index score of surveyed hallway patients was 3 (72%, 95% CI 62.1– 80.5). Emergency Severity Index category 4 patients represented 25% (95% CI 16.9 –34.7) of the population. The remaining 3 patients had an Emergency Severity Index of 5 (95% CI 0.62– 8.5). Conclusion: Overall satisfaction and satisfaction with treatment area are low for patients treated in the hallway. Patients feel as if they are in the way, and cite lack of visitor space, lack of privacy, and a fear for safety. Despite these issues, most patients would prefer to be treated in the hallway as opposed to waiting any longer in the waiting room.
16
Emergency Department Consultation Practices and Documentation Vary Widely Across Hospitals
Schuur J, Moreau J, Bohan J, Fauchet G, Lobon L, Lyn E, Nathanson L, Stack A, Temin E, Tibbles C/Brigham and Women’s Hospital, Boston, MA; Cambridge Health Alliance, Cambridge, MA; North Shore Medical Center, Salem, MA; Beth Israel Deaconess Medical Center, Boston, MA; Children’s Hospital Boston, Boston, MA; Massachusetts General Hospital, Boston, MA
Study Objectives: Emergency department (ED) specialty consultation carries significant patient safety and medico-legal risk, as it involves information transfer between multiple providers. We aimed to determine the frequency that information considered critical to consultations is documented and the prevalence of informal consults. Methods: We conducted retrospective chart review at 6 hospitals (2 community teaching hospitals [CHs] and 4 academic/urban Level 1 trauma centers [AHs]) in a Northeastern metro area. At each hospital, we consulted with ED and consultant service leaders to determine critical elements of consults. We identified the following time points: consult called, consult acknowledged, and consult completed. Other elements identified as critical to document included: reason for consult, supervision of trainees, and real-time “closed-loop” communication between the consultant and the emergency physician at the beginning and completion of the consultation. Each ED reviewed 20 charts from each of 4 commonly consulted services for documentation of the critical elements of consultation (80 – 87 charts at each AH and 10 and 75 charts at CHs). To determine the prevalence of informal (ie, “curbside”) consults, we reviewed 100 –200 consecutive ED charts at each hospital (n⫽737). We identified documented mentions of specialty consults within emergency physician documentation and matching consultant documentation. We determined the percent of informal consults from all services by calculating the ratio between explicit consult mentions and written consult notes. Results: Documentation of critical elements varied widely across services and hospitals (Table). Time consult requested was logged 100% of the time at one ED with a dashboard that logged consults, and two other hospitals had high percentages of documented consult request time due to formal recording policies (55% and 100%
S6 Annals of Emergency Medicine
compliance). Time consult acknowledged was rarely recorded (8% across all hospitals), except at the ED with the electronic dashboard (25%). Documentation of other critical communication elements also varied across hospitals: reason for consult: 37–96%; role of supervising MD: 38 –78%; and real-time closed loop communication at consult completion: 19 – 88%. Evidence of informal consultation in ED documentation was common, with 17– 43% of consult mentions unaccompanied by consultant documentation. There was significant variation in all measures between services at each hospital (see table). Conclusion: Consultation practice varied significantly across 6 hospitals in a metropolitan area and within each hospital by service. Timeliness, supervision and communication between emergency physicians and consultants is not routinely documented in the medical record, and informal ED consults (“curbsides”) are common. There is an opportunity to standardize communication and documentation, which may improve patient safety and reduce medico-legal risk.
17
Emergency Department Rapid Assessment Unit at the Cambridge Hospital: Why and How?
Lobon LF, Sayah AJ, Rivard L, Brady M, Skura S/The Cambridge Hospital/Cambridge Health Alliance, Cambridge, MA
Background: Before having contact with a provider and receiving medical treatment the majority of emergency department (ED) patients in the US are screened by clinical and non-clinical staff. This screening follows a sequential process including triage, registration and initial assessment which requires patients to move through different areas of the ED. Our model at The Cambridge Hospital ED (TCH ED) followed that operational structure until 4/2/08. We believe that delays in patient care were caused by the factors described above and contributed to: ● Increase in time for provider evaluation and management ● Increase total length of stay with long “waiting room” times ● Crowding/ambulance diversion situations ● Very low patient satisfaction scores Study Objectives: Rapid Assessment Unit (RAU) implementation on 4/2/08 impact on time-to-provider (TTP), turn-around-times (TAT) and ED quality indicators: Press Ganey scores (PG) and left without been seeing (LWBS). RAU has 5 dedicated front-end multipurpose treatment areas and is staffed 10am-10pm by 1 PA (supervised by an ED attending), 2 RNs, 1 ED tech and 1 patient partner (PP). Immediately upon arrival to the ED reception area patients are greeted by our PP and entered into our electronic record system. Subsequently they are escorted into the RAU where the clinical team assesses their condition and determines based on the Emergency Scale Index (ESI) if: 1. the patient can stay in RAU for treatment and release 2. the patient needs to be evaluated immediately in the acute care area due to the severity of the presentation 3. management will start in RAU and will continue in the acute care area when appropriate. Registration and triage are brought to the patient’s bedside avoiding delays and uncomfortable transfers. Methods: Retrospective data analysis includes ED visits pre-implementation of a RAU in Jan 08 and post-implementation in Jan 09, during the hours that RAU is operational, 10am-10pm. We will compare mean values for time -to-provider and turn-around-times.
Volume , . : September
12
When the Emergency Department Is Packed Can Physician Assistants Pick Up the Pace? An Analysis of Physician Assistant Productivity Related to Patient Volume
Brook C, Chomut A, Jeanmonod R/Albany Medical College, Albany, NY; St. Luke’s Hospital, Bethlehem, PA
Background: The volume of patients seen in an emergency department (ED) is highly variable. It has been determined that resident productivity is not highly correlated with volume, but the relationship between physician assistant (PA) productivity and volume has not been studied. Study Objective: To determine whether PA productivity varies with ED census. Methods: A retrospective review was conducted of all ED visits at a level one trauma center during June and July 2007. The PA who first signed up for the patient and dictated the patient’s chart was considered to be the primary caregiver. All patients seen by PAs were included in the study. The hour during which care was initiated was defined as the hour that a PA electronically signed up for a patient. Productivity was calculated as the number of patients upon which care was initiated each hour. Data was collected regarding the total number of patients registered in the ED from 0700 to 2359 each day of the study period, as PAs do not work overnights at our institution. This was then broken down to patients registered per hour to determine ED volume per hour. Regression analysis was used to determine the relationship that hourly and daily volume had on PA productivity. Monthly Relative Value Units (RVUs) were also collected for the PAs during the study period. Results: During June and July 2007, there were 160 PA shifts. The number of patients seen in the ED per hour ranged from 0 –22 patients (Mean: 9.4 Standard Deviation: 3.9). Anywhere from 133–198 patients were seen daily (Mean: 160.4, Standard Deviation: 14.8). Regression analysis examining shift productivity related to daily volume showed a R2 of 0.01. Regression analysis of productivity per hour plotted against volume per hour yielded a R2 of 0.02. Productivity in terms of mean RVUs per hour during the study period was calculated as 2.35 RVUs/hour (95% CI ⫽ 1.98 –2.72). Conclusion: PA productivity does not correlate with the total or hourly volume of patients seen in the ED.
13
Utilizing Time-Driven Activity-Based Costing in the Emergency Department
Bank DE, McIlrath T/Phoenix Children’s Hospital, Phoenix, AZ
Study Objectives: Traditionally employed health care costing methods may not accurately reflect actual costs of emergency department (ED) service. The introduction of a practical costing tool using a time driven activity-based costing (TDABC) model allows ED directors to understand the costs of ED service and make decisions on the allocation of resources. Methods: This study was conducted using data from a high volume pediatric ED in a free-standing children’s hospital. The TDABC model was utilized to estimate costs of provider resources and apply them to three specific clinical scenarios common to any ED service: a simple laceration repair of an extremity (⬍2.5cm), a mild asthma exacerbation requiring respiratory therapy, and acute gastroenteritis with mild dehydration requiring intravenous fluid therapy. We compared our calculated costs for each of these three clinical scenarios with the standard Medicaid Outpatient Prospective Payment System (OPPS) and physician fee reimbursement schedules for 2008. The total direct and indirect costs to the ED were obtained from 2008 hospital accounting. Costs of medications and supplies were obtained from hospital materials management and pharmacy accounting and were treated as separate entities. Results: In each of the 3 clinical scenarios, combined 2008 OPPS and physician reimbursement was greater than the total ED costs derived using TDABC. In
Volume , . : September
Scenario 1: a simple laceration repair of an extremity (⬍2.5cm), the Medicaid reimbursement was $581.77 and the estimated actual cost was $365.53 (profit margin 37%). In Scenario 2: a child with mild asthma exacerbation requiring respiratory therapy, the Medicaid reimbursement was $501.87 versus the estimated actual cost of $491.61 (profit margin 2%). In Scenario 3: a child with acute gastroenteritis and mild dehydration requiring intravenous fluid therapy, the Medicaid reimbursement was $523.00 versus the estimated actual cost of $491.43 (profit margin 6%). Conclusion: TDABC may be utilized as an effective and accurate tool to estimate the true cost of ED service. For any given patient encounter, the costs of service vary greatly based on the proportion and time of resources utilized. TDABC analysis can be used by ED directors to help determine the allocation of ED clinical resources. TDABC analysis of service can be used as a tool to help development professional and facility reimbursement strategies with commercial payers.
14
An Analysis of Emergency Department Flow, Severity and Congestion Factors That Are Associated With Decreases in the Left Without Being Seen Rate
Sattarian M, Shesser R/George Washington University, Washington, DC
Study Objective: During the last 3 years, the overall left without being seen (LWBS) rate in our academic, urban emergency department (ED) decreased from 4.6% (2006) to 3.2 % (2008) despite an increase in ED census and the absence of specific process change that focused on LWBS rate reduction. This analysis examines the strengths of association between the LWBS rate and a group of standard ED flow, congestion, and severity parameters. Methods: Data on all visits during calendar years 2006 – 8 to the GW Hospital ED were tracked with an EMR application that required assignment of a specific discharge category for every arrival. The LWBS category included all registrants who left either before or after nursing triage, but before being seen by a physician. Data were analyzed by hour for each of the 26,304 hours in the study period. The LWBS patient number for each hour during this period was compared to the mean arrivalbed (waiting) times for ambulatory patients arriving that same hour who successfully completed their evaluation, their mean Emergency Severity Index scores, the number of patient arrivals during that hour, and the total number of patients in the ED treatment area and lobby at each hour’s end. Results: During the analysis period, 187,663 patients were registered; 128,430 walk-ins (68.4%) and 59,233 ambulance arrivals (31.6%). 7,543 patients LWBS, 6,705 (88.9%) of whom were walk-ins and 838 (11.1%) arrived by EMS. LWBS rates for the three year analysis period were 4.0% overall, 5.2% for walk-ins and 1.4% for ambulance arrivals. The LWBS rate for walk-ins decreased by 36% from 5.5% (July–December, 2006) to 3.5% (July–December 2008) (P ⬍ 0.001). During the analysis period, mean waiting times for ambulatory arrivals decreased from 61.4 minutes (2006) to 52.6 minutes (2008); mean total hourly arrival volume increased from 6.9 patients (2006) to 7.5 patients (2008); and mean, total end-hourly ED census increased from 36.5 patients (2006) to 39.5 patients (2008). Measuring the strength of association between the hourly LWBS patients and that same hour’s waiting times, arrival volume, Emergency Severity Index acuity, and total end-hourly ED census demonstrated highly significant relationships between LWBS and waiting times (P ⬍ 0.001, r: 0.48) and total ED census (P ⬍ 0.001, r: 0.34). There was a weaker relationship with arrival intensity (P ⬍ 0.001, r: 0.26), and no relationship with mean patient acuity. Conclusion: ED process improvements that lead to a modest decrease in patient waiting time, may achieve larger, proportional decreases in the ED’s LWBS rate. Although decreased waiting time in our setting was achieved by “front-end” process improvement, “back-end” strategies that reduce total ED census may have a greater effect on reducing the LWBS rate due to the strong association between LWBS and total ED census. It is still possible to lower LWBS rates during periods of increasing ED census and congestion.
15
Satisfaction of Emergency Department Hallway Patients
Stiffler KA, Wilber ST, Blanda M, Nielson J, Winot S, Kline J/ Summa Health System/NEOUCOMP, Akron, OH
Study Objectives: Emergency department (ED) crowding is recognized as a national problem and has reached epidemic proportions. During times of acute ED crowding, patients experience their most significant delay while waiting for an ED bed. Many EDs attempt to ameliorate this problem by treating non-urgent conditions in hallway treatment areas instead of regular treatment rooms. Many studies are
Annals of Emergency Medicine S5
Research Forum Abstracts available on patient satisfaction, but none specifically address the satisfaction of patients who are assigned hallway beds in the ED. We conducted a study to evaluate patients’ opinions, concerns, and satisfaction about being placed in hallway treatment spaces for their ED care. Methods: A cross-sectional study of patients assigned to a hallway treatment space at Akron City Hospital ED, a 72,500 adult visit urban community teaching hospital, was performed. Sequential patients who were placed in hallway treatment spaces during peak volume hours were asked to complete a confidential, self-administered survey regarding hallway treatment issues. The initial questions asked how patients felt about various issues pertaining to being treated in the hallway using a 5-point Likert scale. The second portion of the survey used 100mm visual analog scale questions (0⫽not satisfied, 100⫽satisfied) to determine satisfaction levels with regard to treatment location, medical care, and overall satisfaction. Data are reported as means and proportions with 95% confidence intervals (mean 95% CI). Results: A total of 100 patients with a mean age of 41.6⫾16.4 years completed the survey. Fifty nine percent were female. Areas of greatest concern for patients included feeling in the way (60%, 95% CI 49.7– 69.7), having no room for visitors (57%, 95% CI 46.7– 66.9), and a lack of privacy (56%, 95% CI 45.7– 65.9). Forty two percent (95% CI 32.2–52.3) identified safety as a concern. Overall visit satisfaction scores were 52.77 (95% CI 46.9 –58.6), while satisfaction with regard to medical care revealed 70.27 (95% CI 65.0 –75.5). Satisfaction with regard to hallway treatment location scored 46.31 (95% CI 39.7–52.9). Thirty-four percent of patients (95% CI 24.8 – 44.1) surveyed were less likely to recommend our ED to others based on treatment location, while 26% (95% CI 17.7–35.7) were less likely to recommend this hospital system. When questioned about willingness to wait any longer for a treatment room, 75% (95% CI 65.3– 83.1) preferred to be treated in the hallway immediately. The most common Emergency Severity Index score of surveyed hallway patients was 3 (72%, 95% CI 62.1– 80.5). Emergency Severity Index category 4 patients represented 25% (95% CI 16.9 –34.7) of the population. The remaining 3 patients had an Emergency Severity Index of 5 (95% CI 0.62– 8.5). Conclusion: Overall satisfaction and satisfaction with treatment area are low for patients treated in the hallway. Patients feel as if they are in the way, and cite lack of visitor space, lack of privacy, and a fear for safety. Despite these issues, most patients would prefer to be treated in the hallway as opposed to waiting any longer in the waiting room.
16
Emergency Department Consultation Practices and Documentation Vary Widely Across Hospitals
Schuur J, Moreau J, Bohan J, Fauchet G, Lobon L, Lyn E, Nathanson L, Stack A, Temin E, Tibbles C/Brigham and Women’s Hospital, Boston, MA; Cambridge Health Alliance, Cambridge, MA; North Shore Medical Center, Salem, MA; Beth Israel Deaconess Medical Center, Boston, MA; Children’s Hospital Boston, Boston, MA; Massachusetts General Hospital, Boston, MA
Study Objectives: Emergency department (ED) specialty consultation carries significant patient safety and medico-legal risk, as it involves information transfer between multiple providers. We aimed to determine the frequency that information considered critical to consultations is documented and the prevalence of informal consults. Methods: We conducted retrospective chart review at 6 hospitals (2 community teaching hospitals [CHs] and 4 academic/urban Level 1 trauma centers [AHs]) in a Northeastern metro area. At each hospital, we consulted with ED and consultant service leaders to determine critical elements of consults. We identified the following time points: consult called, consult acknowledged, and consult completed. Other elements identified as critical to document included: reason for consult, supervision of trainees, and real-time “closed-loop” communication between the consultant and the emergency physician at the beginning and completion of the consultation. Each ED reviewed 20 charts from each of 4 commonly consulted services for documentation of the critical elements of consultation (80 – 87 charts at each AH and 10 and 75 charts at CHs). To determine the prevalence of informal (ie, “curbside”) consults, we reviewed 100 –200 consecutive ED charts at each hospital (n⫽737). We identified documented mentions of specialty consults within emergency physician documentation and matching consultant documentation. We determined the percent of informal consults from all services by calculating the ratio between explicit consult mentions and written consult notes. Results: Documentation of critical elements varied widely across services and hospitals (Table). Time consult requested was logged 100% of the time at one ED with a dashboard that logged consults, and two other hospitals had high percentages of documented consult request time due to formal recording policies (55% and 100%
S6 Annals of Emergency Medicine
compliance). Time consult acknowledged was rarely recorded (8% across all hospitals), except at the ED with the electronic dashboard (25%). Documentation of other critical communication elements also varied across hospitals: reason for consult: 37–96%; role of supervising MD: 38 –78%; and real-time closed loop communication at consult completion: 19 – 88%. Evidence of informal consultation in ED documentation was common, with 17– 43% of consult mentions unaccompanied by consultant documentation. There was significant variation in all measures between services at each hospital (see table). Conclusion: Consultation practice varied significantly across 6 hospitals in a metropolitan area and within each hospital by service. Timeliness, supervision and communication between emergency physicians and consultants is not routinely documented in the medical record, and informal ED consults (“curbsides”) are common. There is an opportunity to standardize communication and documentation, which may improve patient safety and reduce medico-legal risk.
17
Emergency Department Rapid Assessment Unit at the Cambridge Hospital: Why and How?
Lobon LF, Sayah AJ, Rivard L, Brady M, Skura S/The Cambridge Hospital/Cambridge Health Alliance, Cambridge, MA
Background: Before having contact with a provider and receiving medical treatment the majority of emergency department (ED) patients in the US are screened by clinical and non-clinical staff. This screening follows a sequential process including triage, registration and initial assessment which requires patients to move through different areas of the ED. Our model at The Cambridge Hospital ED (TCH ED) followed that operational structure until 4/2/08. We believe that delays in patient care were caused by the factors described above and contributed to: ● Increase in time for provider evaluation and management ● Increase total length of stay with long “waiting room” times ● Crowding/ambulance diversion situations ● Very low patient satisfaction scores Study Objectives: Rapid Assessment Unit (RAU) implementation on 4/2/08 impact on time-to-provider (TTP), turn-around-times (TAT) and ED quality indicators: Press Ganey scores (PG) and left without been seeing (LWBS). RAU has 5 dedicated front-end multipurpose treatment areas and is staffed 10am-10pm by 1 PA (supervised by an ED attending), 2 RNs, 1 ED tech and 1 patient partner (PP). Immediately upon arrival to the ED reception area patients are greeted by our PP and entered into our electronic record system. Subsequently they are escorted into the RAU where the clinical team assesses their condition and determines based on the Emergency Scale Index (ESI) if: 1. the patient can stay in RAU for treatment and release 2. the patient needs to be evaluated immediately in the acute care area due to the severity of the presentation 3. management will start in RAU and will continue in the acute care area when appropriate. Registration and triage are brought to the patient’s bedside avoiding delays and uncomfortable transfers. Methods: Retrospective data analysis includes ED visits pre-implementation of a RAU in Jan 08 and post-implementation in Jan 09, during the hours that RAU is operational, 10am-10pm. We will compare mean values for time -to-provider and turn-around-times.
Volume , . : September