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152 Applying Network Adequacy Standards to Emergency Medicine
Research Forum Abstracts
151
The Effect of Helmet Use on Emergency Department Costs in Central Florida
Vaizer J, Eskandari AM, Patel N, Avgeropoulos G, Ono SK, Cassidy DD/University of Central Florida College of Medicine, Orlando, FL; University of Central Florida, Orlando, FL; Orlando Regional Medical Center, Orlando, FL
Study Objectives: As of 2011, Florida’s 627,613 registered motorcycles accounted for 3.6% of motor vehicles in Florida and a disproportionate 18.8% of traffic fatalities. Motorcycle helmet use is estimated to reduce risk of death by 42% and reduce risk of head injury by 69%. It has been shown that helmet use is directly influenced by whether or not a state has a universal helmet law, with an average of 89% of motorcyclists using helmets in states with a universal helmet law vs 49% in states without one. Florida repealed its universal helmet law in 2000, resulting in an increase in unhelmeted riders from 0.5% in 1998 to 44.7% in 2010. This study evaluates the impact of helmet use on trauma resource utilization and the extent of injuries in victims of motorcycle accidents in Central Florida based on data collected from the Orlando Regional Medical Center (ORMC) Trauma Registry. Methods: This was a retrospective cohort study of all motorcycle accidents recorded within the ORMC Trauma Database between January 1, 2012 and July 1, 2014. The analysis included all patients involved in two-wheeled motor vehicle crashes with a known helmet status, and did not discriminate based on age, race, or other demographic data. Patients were stratified into two groups based on their helmet status (ie, helmet used versus no helmet used). Odds ratios were calculated for skull fracture, intracranial bleeding, and death between the two groups. Independent two sample ttests were used to elicit the mean emergency department (ED) cost and mean injury severity score (ISS) for each group. Results: A total of 728 patients (n¼728) were included in the study: 633 males and 95 females. There were 406 riders between the ages of 15 and 40, 290 riders between 41 and 65, and 32 riders over the age of 66. Incidentally, exactly half of the patients studied (n1¼364) wore a helmet while the other half did not (n2¼364). The patients were assigned to two groups based on their helmet status for the data analysis. The study yielded a statistically significant difference between the means of ED costs for helmeted and unhelmeted riders at $6790.00 and $5825.83 respectively (P < .01). Hence, the average ED visit cost for unhelmeted riders was 16.6% higher than the average for the helmeted group (average cost difference ¼ $964.17; 95% confidence intervals [CI] 317.86 to 1610.46, P < .0.1). Additionally, when compared to riders who wore a helmet, an observed odds ratio of skull fracture was calculated to be 4.27 times higher in the unhelmeted group (95% CI 2.73-6.45, P < .01). Risk of death was 2.67 times higher in unhelmeted group (95% CI 1.31 to 5.46, P < .01). Risk of intracranial bleeding was 2.09 times higher in unhelmeted group (95% CI 1.41 to 3.08, P < .01). Lastly, the unhelmeted group had an ISS mean of 13.3 which is 1.5 higher (95% CI 0.10 to 2.91, P < .01) than the mean ISS of the helmeted group, 11.8. Conclusion: This study supports the hypothesis that inconsistent use of helmets significantly impacts Central Florida ED costs and leads to increased risk of serious and fatal injuries in motorcycle riders. Hence, it is likely that the repeal of Florida’s universal helmet law in 2000 and subsequent increase in unhelmeted riders has led to increased ED costs among hospitals throughout Florida.
152
Applying Network Adequacy Standards to Emergency Medicine
Dorner SC, Camargo CA, Jr., Raja AS/Harvard T.H. Chan School of Public Health, Boston, MA; Massachusetts General Hospital, Boston, MA
Study Objectives: The Affordable Care Act authorized the U.S. Department of Health and Human Services (HHS) to regulate qualified health plans’ (QHPs) network adequacy. QHPs must include a sufficient number and type of physicians within their provider network to deliver contracted benefits and services. HHS determines adequacy by applying a “reasonable access” standard using provider network data reported by QHPs. While the regulations apply to all specialties, emergency medicine (EM) is clinically and operationally unique due to emergency physicians’ distinct billing and employment practices. Although many emergency physicians employed by large urban hospitals are paid rates negotiated between the hospital and insurers, approximately 65% of hospitals staff their emergency departments with independently contracted emergency physicians, many of whom do not negotiate with insurers. We investigated whether applying the reasonable access standard to in-network emergency physicians
S54 Annals of Emergency Medicine
provides sufficient information for determining network adequacy. We hypothesized that roughly 10% of plans would lack in-network emergency physicians. Methods: We examined Silver QHPs offered in the 34 states in the Marketplace in 2015. An estimated 65% of participants select Silver Plans. In each state, we sampled four plans available in the insurance rating area containing the most populous county: the lowest, second-lowest, median, and highest premium plans. Premium pricing information was obtained using publicly available QHP Marketplace data from the Center for Medicare and Medicaid Services. Using each QHP’s publicly available provider directory, we identified the number of in-network emergency physicians within 100 miles of the primary ZIP code for the rating area’s most populous city. If a directory’s maximum search radius was less than 100 miles, we selected the broadest search radius available. We applied this same methodology to identify in-network hospitals within the same search radius. Data were summarized using descriptive statistics. Results: Among the 136 QHPs analyzed, the total number of identifiable innetwork emergency physicians ranged from 0 to 840 (median: 28). We identified 30 plans (22%) with networks completely lacking emergency physician coverage. The number of in-network hospitals ranged from 0 to 500 (median: 28). Five plans (3.7%) lacked hospital coverage. Three plans (2.2%) covered emergency physicians but did not cover a hospital. Two plans (1.5%) lacked both in-network emergency physician and hospital coverage. Information regarding whether emergency physicians were hospital employees or independent contractors was not available. Conclusion: Our findings raise serious questions about the application of the network adequacy framework to EM. One-in-five plans lacked identifiable in-network emergency physicians, a situation that does not meet the reasonable access standard. The same is true of hospital coverage. There is a broad range of in-network coverage of both emergency physicians and hospitals. While some health plans cover a large number of in-network emergency physicians and hospitals, others lack coverage of both. The opaque nature of physician-hospital contracts and billing obscures the ability to identify whether an in-network hospital employs out-of-network emergency physicians, or vice-versa. In light of these obstacles, regulators seeking to determine emergency physician network adequacy will require additional information beyond that presently requested of QHPs.
153
Patient Length of Stay in the Context of the “2-Midnight Rule”: Assessing the Accuracy of Attending Providers’ Predictions
Lindor RA, Sadosty AT, Madsen BE, Goyal DG, Newman JS, Schatz AL, Bellolio MF/ Mayo Clinic College of Medicine, Rochester, MN
Study Objectives: Since the enactment of the “2-midnight rule” in October 2013, CMS requires admitting providers to predict whether patients will require hospitalization less than 2 midnights, in which case they are designated as observation status (OS), or 2 midnights or longer, designated as inpatient (IP). Providers’ inaccurate designation of patients as OS or IP has financial consequences for hospitals and patients. For hospital stays originally designated as IP but lasting <2 midnights, hospitals may not be able to capture CMS payment and patients may be held financially responsible for more of the services provided during the stay. For hospital stays originally designated as OS but lasting 2+ midnights, hospitals are more likely to have a negative margin for the stay and patients may not be eligible for insurance coverage of subsequent skilled nursing facility care. We sought to: a) determine providers’ accuracy in predicting which patients require hospitalization greater than two midnights and b) identify patient characteristics that providers may use to improve prediction accuracy. Methods: We conducted an analysis of consecutive adult (18+ years) emergency department (ED) visits resulting in admission to the hospital within a 90-day period (May 2014 through August 2014) where an attending emergency physician prospectively designated the admission type (OS versus IP). Inaccurate predictions were defined as those involving patients who were designated as IP but stayed <2 midnights and patients designated as OS but stayed 2+ midnights. Patient characteristics associated with inaccurate predictions were identified. Linear regression models were fit to explore associations and predictors of accurate versus inaccurate predictions. IRB approval was obtained. Results: A total of 4760 adult patients were admitted to the hospital through the ED during our study period; 58% (n¼2760) were IP and 42% (n¼2000) OS. Overall 53.7% were males and median age was 63 years (IQR 46 to 78). The overall rate of error in predicted length of stay was 38.3%. Inpatient cohort: Of 2760 patients admitted as IP, 27.6% (761) stayed for < 2 midnights. Patient
Volume 66, no. 4s : October 2015
151
The Effect of Helmet Use on Emergency Department Costs in Central Florida
Vaizer J, Eskandari AM, Patel N, Avgeropoulos G, Ono SK, Cassidy DD/University of Central Florida College of Medicine, Orlando, FL; University of Central Florida, Orlando, FL; Orlando Regional Medical Center, Orlando, FL
Study Objectives: As of 2011, Florida’s 627,613 registered motorcycles accounted for 3.6% of motor vehicles in Florida and a disproportionate 18.8% of traffic fatalities. Motorcycle helmet use is estimated to reduce risk of death by 42% and reduce risk of head injury by 69%. It has been shown that helmet use is directly influenced by whether or not a state has a universal helmet law, with an average of 89% of motorcyclists using helmets in states with a universal helmet law vs 49% in states without one. Florida repealed its universal helmet law in 2000, resulting in an increase in unhelmeted riders from 0.5% in 1998 to 44.7% in 2010. This study evaluates the impact of helmet use on trauma resource utilization and the extent of injuries in victims of motorcycle accidents in Central Florida based on data collected from the Orlando Regional Medical Center (ORMC) Trauma Registry. Methods: This was a retrospective cohort study of all motorcycle accidents recorded within the ORMC Trauma Database between January 1, 2012 and July 1, 2014. The analysis included all patients involved in two-wheeled motor vehicle crashes with a known helmet status, and did not discriminate based on age, race, or other demographic data. Patients were stratified into two groups based on their helmet status (ie, helmet used versus no helmet used). Odds ratios were calculated for skull fracture, intracranial bleeding, and death between the two groups. Independent two sample ttests were used to elicit the mean emergency department (ED) cost and mean injury severity score (ISS) for each group. Results: A total of 728 patients (n¼728) were included in the study: 633 males and 95 females. There were 406 riders between the ages of 15 and 40, 290 riders between 41 and 65, and 32 riders over the age of 66. Incidentally, exactly half of the patients studied (n1¼364) wore a helmet while the other half did not (n2¼364). The patients were assigned to two groups based on their helmet status for the data analysis. The study yielded a statistically significant difference between the means of ED costs for helmeted and unhelmeted riders at $6790.00 and $5825.83 respectively (P < .01). Hence, the average ED visit cost for unhelmeted riders was 16.6% higher than the average for the helmeted group (average cost difference ¼ $964.17; 95% confidence intervals [CI] 317.86 to 1610.46, P < .0.1). Additionally, when compared to riders who wore a helmet, an observed odds ratio of skull fracture was calculated to be 4.27 times higher in the unhelmeted group (95% CI 2.73-6.45, P < .01). Risk of death was 2.67 times higher in unhelmeted group (95% CI 1.31 to 5.46, P < .01). Risk of intracranial bleeding was 2.09 times higher in unhelmeted group (95% CI 1.41 to 3.08, P < .01). Lastly, the unhelmeted group had an ISS mean of 13.3 which is 1.5 higher (95% CI 0.10 to 2.91, P < .01) than the mean ISS of the helmeted group, 11.8. Conclusion: This study supports the hypothesis that inconsistent use of helmets significantly impacts Central Florida ED costs and leads to increased risk of serious and fatal injuries in motorcycle riders. Hence, it is likely that the repeal of Florida’s universal helmet law in 2000 and subsequent increase in unhelmeted riders has led to increased ED costs among hospitals throughout Florida.
152
Applying Network Adequacy Standards to Emergency Medicine
Dorner SC, Camargo CA, Jr., Raja AS/Harvard T.H. Chan School of Public Health, Boston, MA; Massachusetts General Hospital, Boston, MA
Study Objectives: The Affordable Care Act authorized the U.S. Department of Health and Human Services (HHS) to regulate qualified health plans’ (QHPs) network adequacy. QHPs must include a sufficient number and type of physicians within their provider network to deliver contracted benefits and services. HHS determines adequacy by applying a “reasonable access” standard using provider network data reported by QHPs. While the regulations apply to all specialties, emergency medicine (EM) is clinically and operationally unique due to emergency physicians’ distinct billing and employment practices. Although many emergency physicians employed by large urban hospitals are paid rates negotiated between the hospital and insurers, approximately 65% of hospitals staff their emergency departments with independently contracted emergency physicians, many of whom do not negotiate with insurers. We investigated whether applying the reasonable access standard to in-network emergency physicians
S54 Annals of Emergency Medicine
provides sufficient information for determining network adequacy. We hypothesized that roughly 10% of plans would lack in-network emergency physicians. Methods: We examined Silver QHPs offered in the 34 states in the Marketplace in 2015. An estimated 65% of participants select Silver Plans. In each state, we sampled four plans available in the insurance rating area containing the most populous county: the lowest, second-lowest, median, and highest premium plans. Premium pricing information was obtained using publicly available QHP Marketplace data from the Center for Medicare and Medicaid Services. Using each QHP’s publicly available provider directory, we identified the number of in-network emergency physicians within 100 miles of the primary ZIP code for the rating area’s most populous city. If a directory’s maximum search radius was less than 100 miles, we selected the broadest search radius available. We applied this same methodology to identify in-network hospitals within the same search radius. Data were summarized using descriptive statistics. Results: Among the 136 QHPs analyzed, the total number of identifiable innetwork emergency physicians ranged from 0 to 840 (median: 28). We identified 30 plans (22%) with networks completely lacking emergency physician coverage. The number of in-network hospitals ranged from 0 to 500 (median: 28). Five plans (3.7%) lacked hospital coverage. Three plans (2.2%) covered emergency physicians but did not cover a hospital. Two plans (1.5%) lacked both in-network emergency physician and hospital coverage. Information regarding whether emergency physicians were hospital employees or independent contractors was not available. Conclusion: Our findings raise serious questions about the application of the network adequacy framework to EM. One-in-five plans lacked identifiable in-network emergency physicians, a situation that does not meet the reasonable access standard. The same is true of hospital coverage. There is a broad range of in-network coverage of both emergency physicians and hospitals. While some health plans cover a large number of in-network emergency physicians and hospitals, others lack coverage of both. The opaque nature of physician-hospital contracts and billing obscures the ability to identify whether an in-network hospital employs out-of-network emergency physicians, or vice-versa. In light of these obstacles, regulators seeking to determine emergency physician network adequacy will require additional information beyond that presently requested of QHPs.
153
Patient Length of Stay in the Context of the “2-Midnight Rule”: Assessing the Accuracy of Attending Providers’ Predictions
Lindor RA, Sadosty AT, Madsen BE, Goyal DG, Newman JS, Schatz AL, Bellolio MF/ Mayo Clinic College of Medicine, Rochester, MN
Study Objectives: Since the enactment of the “2-midnight rule” in October 2013, CMS requires admitting providers to predict whether patients will require hospitalization less than 2 midnights, in which case they are designated as observation status (OS), or 2 midnights or longer, designated as inpatient (IP). Providers’ inaccurate designation of patients as OS or IP has financial consequences for hospitals and patients. For hospital stays originally designated as IP but lasting <2 midnights, hospitals may not be able to capture CMS payment and patients may be held financially responsible for more of the services provided during the stay. For hospital stays originally designated as OS but lasting 2+ midnights, hospitals are more likely to have a negative margin for the stay and patients may not be eligible for insurance coverage of subsequent skilled nursing facility care. We sought to: a) determine providers’ accuracy in predicting which patients require hospitalization greater than two midnights and b) identify patient characteristics that providers may use to improve prediction accuracy. Methods: We conducted an analysis of consecutive adult (18+ years) emergency department (ED) visits resulting in admission to the hospital within a 90-day period (May 2014 through August 2014) where an attending emergency physician prospectively designated the admission type (OS versus IP). Inaccurate predictions were defined as those involving patients who were designated as IP but stayed <2 midnights and patients designated as OS but stayed 2+ midnights. Patient characteristics associated with inaccurate predictions were identified. Linear regression models were fit to explore associations and predictors of accurate versus inaccurate predictions. IRB approval was obtained. Results: A total of 4760 adult patients were admitted to the hospital through the ED during our study period; 58% (n¼2760) were IP and 42% (n¼2000) OS. Overall 53.7% were males and median age was 63 years (IQR 46 to 78). The overall rate of error in predicted length of stay was 38.3%. Inpatient cohort: Of 2760 patients admitted as IP, 27.6% (761) stayed for < 2 midnights. Patient
Volume 66, no. 4s : October 2015