The Health Care Manager Volume 32, Number 4, pp. 321–328 Copyright # 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins
Emergency Department Utilization at a Large Regional Hospital A Strategy for Survivability Timothy Rotarius, PhD, MBA; Aaron Liberman, PhD; Kendall Cortelyou-Ward, PhD; Dawn Oetjen, PhD; Reid Oetjen, PhD This research effort provides a brief picture of the operational, patient, and financial patterns of the multiple emergency departments of a large hospital system located in the southeastern United States. The results are presented anonymously as a descriptive case study. A multifaceted strategy is presented to assist hospital leaders as they strive to ensure the survivability of their emergency departments in this era of high uncompensated care. Key words: emergency department, financial characteristics, operational variables, patient characteristics, uncompensated care
HIS ARTICLE BRIEFLY describes the emergency services provided via multiple distinct locations of a large hospital system located in the southeastern United States. To maintain the requested anonymity of the studied hospital system, the organization will be referred to simply as Hospital System (HS). The data described in this article are from 2007. To ensure anonymity of data for both HS and its patients, HS requested that the data not be published until a certain period of time had transpired. This brief description is provided to serve as a backdrop for the presentation of a strategy for hospital leaders to use to ensure continued survivability of their emergency departments (EDs).
T
Author Affiliation: Department of Health Management and Informatics, College of Health and Public Affairs, University of Central Florida, Orlando, Florida. This research was funded by a grant from a regional hospital system that prefers to remain unidentified for this article. The authors have no conflicts of interest. Correspondence: Timothy Rotarius, PhD, MBA, Department of Health Management and Informatics, College of Health and Public Affairs, University of Central Florida, Orlando, Florida, 32816-2205 ([email protected]). DOI: 10.1097/HCM.0b013e3182a9d80b
Hospital System operates multiple EDs located within several free-standing, acute care hospitals. These EDs (1) provide emergency care to patients and (2) as a consequence of that emergency care, operate as a referral to sustained inpatient care. This comprehensive study offers a summation of the activities within these EDs, including an examination of patient demographics, level of treatment provided, and financial patterns. Like all acute care hospitals located in the United States, HS serves many patients who are classified into the relatively broad category of uncompensated care, including patient populations classified as uninsured, uninsurable, underinsured, indigent, and Medicaid eligible. The uncompensated care issue is even more prevalent and pronounced in EDs because of the high acuity level of care normally required. Therefore, this study offers a descriptive profile of uncompensated care in the target EDs, including trends in both real dollar costs and resource utilization. In addition, both the strategic and operational implications of these profiles are presented as trends, such as (a) assessing the effects of treating the uncompensated patient groups in ED space and what resources are used and (b) determining the 321
Copyright © 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
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long-term effects to the community of a resolution/ nonresolution of the utilization problem. The timeliness and importance of this study were indicated by several factors, including the following: There is a strong sense among HS’s emergency services medical staff that patient volume has risen faster than treatment resources. Patients who need emergency care and who receive definitive health care within 1 hour of injury see their chances of survival increase by 85% (ie, this 1-hour time period is commonly referred to as The Golden Hour). Uncompensated care as a percentage of total care has continued to be on the rise. Coupling these facts with 1 state (Massachusetts) that has ordered hospital EDs to halt diversions,1 one can easily sense the looming risk to the financial sustainability of hospital EDs. Emergency departments typically receive inadequate reimbursement for their services from most government agencies.2 3 The Centers for Disease Control estimates that there were 119 million ED visits in 2006 (the year before the data was collected), which represented a 36% increase over the 1996 number. The average charge per hospital admission for a trauma patient was about 3 times higher than that for a nontrauma, acute care admission.2 Nationally, the number of EDs decreased from 4019 to 3833 from 1996 to 2006.3 This follows an earlier reduction of 1100 EDs from 1996 to 1998.4 These losses in ED capacity place a further strain on already overcrowded EDs. Many hospitals are exploring efforts to improve reimbursement for emergency care, with 53% of surveyed hospitals indicating that they are active in (a) lobbying local and state legislators and (b) initiating letter-writing campaigns through hospital associations to convince senators and representatives of the importance of the continuation of emergency care.5 The above factors indicate strongly that there is a need for all hospitals and hospital
systems to understand the patient services and operational cost profiles of its EDs to develop viable strategic plans with attainable goals in terms of both organizational survivability and high-quality patient outcomes.
OVERVIEW OF HS The 2007 financial profile of the multiple EDs of HS indicates that there were 223 273 ED visits amassing almost $2 billion in total gross charges. Contractual adjustments equaled 63.6% of gross charges, with charity care and bad debt equaling 6.3% and 6.2%, respectively, of gross charges. Thus, net collectible charges for the multiple EDs of HS amounted to a maximum of 23.9% of total gross charges. In other words, 76.1% of HS’s gross charges were ultimately deemed uncollectible (because of contractual allowances, charity care, or bad debt). Each of the multiple EDs contributes to the overall HS in different ways. This is likely because of such diverse explanations as differing socioeconomic variables within the specific ED’s market area, differing strategic goals for each ED, and myriad other reasons. To reinforce the differences between the multiple EDs, one only needs to look at broad categories of patients and charges. For example, the number of patients seen in 2007 at each of the EDs was quite uneven. The busiest ED saw 81 286 patients (36.4% of total HS ED patient visits) during 2007, whereas the least busy ED saw 19 940 patients (8.9% of total HS ED patient visits). When factoring in selected financial variables, the following overarching points appear: The ED with the most patient visits (36.4% of total patient visits) generated only 29.7% of total gross charges. The ED generating the most gross charges (42.9% of total gross charges) had only 27.4% of total patient visits. The highest average charge (gross charges divided by number of patients) at any 1 of the EDs was $11 781 per patient. The lowest average charge (gross charges divided by number of patients) at any 1 of the EDs was $3062 per patient.
Copyright © 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
ED Utilization at a Large Regional Hospital The highest collection rate at any 1 of the EDs was 88.9%. The lowest collection rate at any 1 of the EDs was 77.4%. In addition, a review of the financial status of the ED patients provides insight into the notion that the financial characteristics of the patients being seen in the respective ED facilities are not the same. For example, 195 131 ED patients of the 223 273 total ED patients (a rate of 87.4%) had contractual allowances associated with the charges for services rendered, which means that these patients had some type of third party–supported private or government insurance. It should be noted that, for 1 visit, patients can be classified into multiple financial status classifications as they move from, for example, commercial insurance coverage to the self-pay obligation. With regard to charity patients, HS’s EDs had 21 813 charity patients at the EDs. Charity is defined as the amount of a patient’s total charges that are written off as charity care. There is no expectation of getting paid for this portion of care because it has been determined via government formulas that these patients have no ability to pay. This figure (21 813 charity patients) represents 9.8% of all patients. Bad debt is the amount of a patient’s total charges that is written off because the patient or the patient intermediary refused to pay for services rendered. In other words, the hospital planned on getting paid for this care but the patient or payer did not pay the entire bill. Of all of the patients seen in the multiple EDs, 74 231 (33.2%) had treatment bills that were not settled (ie, bills that were not paid). In other words, approximately 1 in 3 HS ED patients had some portion of their charges written off as bad debt. Additional points related to the financial characteristics of HS’s ED patients include the following: The highest percentage of charity patients at any 1 of the EDs was 12.3%. The lowest percentage of charity patients at any 1 of the EDs was 5.7%. The highest percentage of bad debt patients at any 1 of the EDs was 36.4%.
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The lowest percentage of bad debt patients at any 1 of the EDs was 25.0%. From the overarching perspective of the entire hospital, an ED performs 2 readily apparent functions: (1) the provision of treatment using ED facilities and (2) as a referral source for the hospital’s inpatient facilities. Emergency patient charges are those charges that are incurred in the ED by patients who are treated and released. These charges include ED charges, nursing services, laboratory charges, and radiology charges. The total emergency treatment patient charges for HS’s multiple EDs equaled 41.4% of the almost $2 billion in total gross charges. Inpatient charges are computed as those charges for patients who, after being treated in the ED, are then admitted as inpatients. Inpatient charges include all of the other charges that the patient incurred after being admitted (if the patient was admitted). Inpatient charges represented 58.6% of HS’s total gross charges. After triaging the patient upon presentation at the ED, HS’s 223 273 ED patients were assigned a service level. These levels of acuity range from 1 to 6, with Service Level 1 being the lowest level of acuity, and Service Level 6, the highest level of acuity. The ED patients were classified as follows: 40% of ED patients were Level 4. 35% of ED patients were Level 3. 17% of ED patients were Level 1. Approximately 400 patients (of 223 273 patients) were classified as Level 5 or Level 6. In other words, for this study, Service Level 4 is, effectively, the highest level of service provided. With regard to measurement for length of stay, when examining ED treatment, one must also review any subsequent inpatient stay. This variable was measured using 7 categories: less than 1 day, 1 day, 2 days, 3 days, 4 days, 5 days, and more than 5 days. For HS, 82% of the 223 273 total ED patient visits were for less than 1 day. The next highest category was more than 5 days at 5%. Thus, only 13% of ED patients stayed between 1 and 5 days. This did not vary when looking at the data for each individual ED.
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Regarding discharge status, an overwhelming percentage of ED patients (95%) were discharged to home, leaving only 5% to be discharged to another health care facility. This variable also did not vary when looking at the data for each individual ED. In reviewing all of HS’s EDs combined, the day admitted to the ED does not show much variance. Monday, with 33 760 visits (15% of the 223 273 total ED visits), was the busiest day. The other 6 days of the week each represented approximately 14% of the total ED visits. These percentages were consistent across each of the individual EDs. For all of HS’s EDs, the preferred patient method of arrival was car (66%), with ambulance (17%) the next most frequent. In general, individual EDs followed this pattern as well. With regard to the primary payer for the ED visit, managed care was the most represented payer (30%) for all of HS’s EDs. Self-pay was the next highest patient financial status classification, followed by Medicaid (20%) and Medicare (15%). From an individual ED perspective, there were several differences in the ranking of payers. For example, 1 ED’s patients were 49% Medicaid and 30% managed care. At another ED, self-pay was the largest category of patients (30%), followed by Medicare (22%) and managed care (21%). In looking at the combined ED data, the age group of 25 to 44 years old was the most frequent user of the EDs at 30% of the total ED patient population. All age groups younger than 25 years (ie, 0-5, 6-17, and 18-24 years) and the 45 to 54 years age group were similar, with percentiles ranging from 11% to 15%. The age groups who least often used the ED were those older than 54 years, making up between 5% and 8% of the ED population. The lone individual ED exception occurred with the ED located within the children’s hospital. As one would expect at a children’s hospital, most patients (67%) were younger than 6 years. With regard to gender, in looking at the combined data for all of HS’s EDs, male and female patients were found to use the EDs relatively equally (47% and 53%, respectively). This percentile did not vary when looking at the individual EDs.
When looking at marital status, unmarried patients made up the largest group of ED users, comprising 61% of the ED patient population. Only 37% of ED users were married. This martial status variable was consistent across the individual EDs. Regarding ethnicity, whites comprised 46% of the patient population of all of HS’s EDs, with blacks (26%) and Hispanics (24%) following. However, several differences were noted when examining the individual EDs. For example, 1 ED identified its patient population as 33% black, 32% Hispanic, and 30% white. Two other EDs identified their patients as more than two-thirds white. This concludes the overview of HS. Next, the research methodology shall be presented. This will be followed by a brief discussion of selected statistically significant variable interactions related to HS’s EDs. A discussion of the implications is next presented. Finally, conclusions are offered to assist hospital leaders as they develop strategies and action items to ensure the survivability of their EDs.
RESEARCH METHODOLOGY This type of analysis was exploratory in nature. As such, it lent itself to using a descriptive case study methodology. Descriptive case studies have been shown to be particularly useful as tools for developing insights as to the particular details of a specific research topic.6 This descriptive case study approach was used to develop a structured assessment of HS’s EDs. Data were derived from a variety of sources, including HS’s internal reports; public reports from federal, state, and local governments; and business and health care journals. Data analysis techniques included the recoding and creation of pertinent variables, cross-tabulations, and the calculation of frequencies and means. Output is presented at the entity level (ie, specific EDs) and at collective levels (ie, all EDs totaled together). The researchers received the HS’s patient encounter database for fiscal year 2007 in 1 database file. This database housed 223 273 patient encounters from all of the EDs to be
Copyright © 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
ED Utilization at a Large Regional Hospital studied. To facilitate the conversion from a database program to a spreadsheet program, the data were divided by ‘‘first location’’ or the location at which a patient first presented. After this initial conversion, the data were transformed from the spreadsheet program to a statistical computer program file. The data were put through a rigorous statistical analysis to determine the integrity of the data. Check values were provided in summary form from HS to ensure that double-counting of patient records had not occurred. To ensure the anonymity of the data, the recoding and calculation of several variables were necessary. Continuous variables, such as total charges, were transformed from ratio-level data into categorical-level data. Because the continuous variables in this study were not normally distributed, the traditional mechanism of dividing numbers into randomly selected equal categories is not generally acceptable and could produce an incorrect correlation coefficient. Therefore, the percentile method of variable conversion was used for both total charges (an existing variable) and uncompensated charges (a new variable). The variable total charges was provided by HS in their patient encounter database of ratiolevel variables. The variable uncompensated charges was calculated by the researchers by summing charity and bad debt to create a new variable. In their original form as ratio-level variables, the use of these variables when they are compared with other variables within the data set is limited. To overcome this limitation when examining ratio-level variables in 2 analyses, the researchers used a statistical process called quantile building, which partitions data into equal-sized categories. This quantile-building process yielded quartiles (4 categories), quintiles (5 categories), octiles (8 categories), and deciles (10 categories) for both the total charges and the uncompensated charges variables. A thorough review of these 4 reclassifications for each variable led to the determination that quintiles provided the most efficient and effective mechanism for categorizing total charges and uncompensated charges. Therefore, each variable was recoded to represent the 20th, 40th, 60th,
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and 80th percentile points for the EDs. The quintiles follow. The quintiles used for total charges are as follows: $0 to $330 $331 to $940 $941 to $2150 $2151 to $7600 $7601 or greater The quintiles used for uncompensated charges are as follows: $0 to $85 $86 to $200 $201 to $600 $601 to $1600 $1601 or greater The demographic variable age also presented a challenge in this research project. In this data set, the variable age, like total costs, is not normally distributed. Therefore, dividing the population into same-size categories is not appropriate and the use of percentiles in this context does not fit the nature of the variable. Therefore, in an attempt to create a logical method to divide age into groups, and to ensure that the results of this project could be compared with other studies, the age categories used by the Centers for Disease Control were used in this analysis. The age categories are as follows: 0 to 5 years 6 to 17 years 18 to 24 years 25 to 44 years 45 to 54 years 55 to 64 years 65 to 74 years 75 years or older After all of the variables in the patient encounter database were examined and appropriately coded (as discussed above), the following 12 variables remained: Total charges (total gross charges in 5 categories; see above) Uncompensated charges (charity care + bad debt; shown in 5 categories) Service level (from 1, lowest, to 4, highest) Length of stay (in days; shown in 7 categories) Discharge status (to home or a health care facility)
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Day admitted (day of the week) Method of arrival (ambulance, car, or helicopter) Primary payer (Medicare, Medicaid, managed care, commercial, self-pay) Age group (8 categories; see above) Marital status (2 categories) Sex Ethnicity (white, black, Hispanic) These 12 variables were used to provide a detailed picture of the patients and utilization patterns of HS’s EDs. To explore the financial relationships that exist within the data set, all variables were compared to both total charges and uncompensated charges. In addition, each of the variables was compared to one another to determine other important relationships. Please note, only key findings that are both statistically significant and of substantive importance (ie, that are scientifically rigorous and that are relevant within the confines of this study) will be presented. Variable correlations allow the researchers to explore the relationship and association between variables. For purposes of this project, the relationship between 2 variables was considered statistically significant if the Pearson correlation, captured in the 2 analysis, is less than 0.001 (ie, P < .001). All of the statistical and methodological issues discussed above were brought to bear on the analysis that follows.
KEY FINDINGS This section shows variable interactions for which the Pearson correlation indicates statistical significance at the .001 level. Only those statistically significant variable interactions that are also substantively significant will be examined. After each set of variable interactions is presented, a brief summary is also presented. Regarding ED patients who are younger than 6 years: 22.5% were Hispanic. 37.3% received Service Level 1 care. 94.4% had a length of stay of less than 1 day. 52.3% had Medicaid. 22.1% had uncompensated charges less than $86. 33.4% had total charges less than $331.
Given (a) the lower level of treatment provided, (b) the short treatment time, and (c) the low charges, these results may indicate that these patients are using the ED as a substitute for the primary care setting. Regarding ED patients who were between 18 and 24 years old: 42.5% were self-pay. These younger adults may present themselves to the ED as uninsured. Regarding ED patients who are older than 74 years: 45.1% arrived via ambulance. 66.7% received Service Level 4 care. 19.4% had a length of stay of more than 5 days. 75.1% were discharged to home. These elderly patients tend to use a high proportion of resources (ambulances, highlevel treatment, and longer inpatient stays), yet their medical condition seems to be controllable to the point that they can return directly home. Regarding ED patients who arrived via ambulance: 45.1% were older than 74 years. 59.8% received Service Level 4 care. 11.8% had a length of stay of more than 5 days. 35.6% had Medicare. 35.6% had total charges greater than $7600. The arrival of an elderly patient by ambulance likely indicates a more serious patient acuity level, which will lead to a much greater use of hospital resources. Regarding ED patients who received Service Level 1 care: 37.3% were younger than 6 years. 25.1% had Medicare. 51.1% had uncompensated charges less than $86. 77.9% had total charges less than $331. It may be that many uninsured parents present their children to an ED because they view the ED as a proxy for a primary care setting. Regarding ED patients who received Service Level 4 care: 66.7% were older than 74 years. 59.8% arrived via ambulance.
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ED Utilization at a Large Regional Hospital 95.8% had a length of stay of 1 day. 63.3% had Medicare. 70.5% were discharged to another health care facility. Elderly patients who arrived via ambulance and also received the highest level of health care services were often quickly transferred to a different treatment facility. Regarding ED patients with Medicare: 35.6% arrived via ambulance. 25.1% received Service Level 1 care. 63.3% received Service Level 4 care. 16.8% had a length of stay of more than 5 days. 82.7% were discharged to home. Medicare patients who arrived via ambulance tended to need either primary care services or the highest level of treatment services. In addition, it is likely that a Medicare patient will be discharged directly to his/her own home. The presentation of the key findings is concluded. Of all of the possible variable interactions, very few interactions were statistically significant, with even fewer interactions being substantively significant.
IMPLICATIONS OF STUDY RESULTS The advantages afforded residents and communities through the availability of a hospital’s ED are unassailable. Without the lifesaving and health-preserving services offered through these facilities, the quality of life and, indeed, the attractiveness of any region as a place to reside would be compromised. The question thus becomes how to preserve the availability of that essential resource to residents. All health care organizations operate in a marketplace separated by those who have insurance versus those who do not have insurance. Those who do not have resources to pay for services become a drain on the capacity of a health system to sustain its commitment to emergency services. Accordingly, a hospital system must consider the adoption of an aggressive proactive strategy that will encourage government leaders in the region to begin effecting financing adjustments at the local and regional levels. This must necessarily include a determined drive to secure support for
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a tax-based subsidy to support the ED services offered through a local hospital system. The bottom line to the current health care reality is that a hospital system’s capacity to continue providing high-level emergency services cannot be sustained indefinitely without positive action by the communities and governments comprising the local region. Therefore, the conclusions next offered present a recommended strategy for both (1) informing community residents about the problem and (2) encouraging substantive action to correct the problem now confronting most health care markets. CONCLUSION The value, in terms of enhancing the quality of life through world-class health care and providing services to all persons in need, regardless of ability to pay, indicates strongly that the loss to any local region of its EDs’ capacity would severely impair the ability of the region to provide urgent, acute services to those in need, with the region’s poorest constituents ultimately feeling the effect upon their health care choices. The hospital system examined during the conduct of this study serves as a major provider of health care services to its local region. Its reach as a health services resource, as a teaching and learning organization, and through the extensive array of services it provides continues to represent an important asset in treating emergency cases and offering health care to all patients regardless of ability to pay. The political leadership of the local region has a clear choice to provide a material means of support to the hospital system’s EDs. Without an offset of funding to defray the growing costs of uncompensated care, hospital systems ultimately will have to begin drawing down the curtain on ED services and the communities, and their residents will be forced to seek other treatment modalities to meet these needs. Inevitably, this will result in higher mortality rates for persons experiencing serious trauma as a result of an accident. The choices, therefore, are 2-fold and are very clear both for the political leaders of the region and
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for the governing board of the local hospital systems: Provide a limited taxing authority to the governing board of local hospital systems to defray a portion of the cost of uncompensated care. Establish a tax rate for uncompensated care and control the rate of taxes assessed at the county level. The fundamental issue becomes: How can a hospital system proceed? The following strategy is offered for consideration: The local hospital system should first convene an Emergency Care Summit of local and regional leaders to hear the results of analyses such as those presented herein. This should be a no-holds barred presentation of the realities being confronted by the communities receiving services from the local EDs. As part of the Summit, the local hospital system should present specific examples of the lifesaving results of having this resource in the local health care market. Most hospital systems are flush with ‘‘good news’’ testimonials about the exceptional care received by the local residents. The results of these services are both poignant and compelling. This information must and should be presented for public consumption and thought.
As part of the Summit, the hospital system should offer to make presentations to each of their government entity stakeholders showing the government leaders how many citizens from their respective communities are both directly and indirectly impacted by the hospital system’s facilities and services each year. The hospital system’s Governing Board then should set a timetable for substantive action and notify the affected government entities formally that, absent substantive action, certain services will, out of necessity, have to be curtailed. Those services should be specified for one and all to see, along with the expiration date for action to be affected. The hospital system then should begin contacting individual citizen organizations to enlist their support for encouraging political authorities to act affirmatively. This will be neither an easy sell nor an effort that will likely produce immediate action. One reality of political governance is that our leaders likely will act only after the stark reality of the choices they are confronting becomes apparent. As such, this strategy for hospital systems to follow serves as a means of commencing the process of change in the financing of emergency care services.
REFERENCES 1. Kowalczyk L. State orders hospital ERs to halt diversions. The Boston Globe. September 13, 2008. www.boston .com. Accessed September 16, 2008. 2. Thomas S, McGwin S, Rue L. The financial impact of delayed discharge at a level I trauma center. J Trauma Inj Infect Crit Care. 2005;58(1):121-125. 3. Pitts SR, Niska RW, Xu J, Burt CW. National Hospital Ambulatory Medical Care Survey: 2006 emergency department summary. National health statistics reports; no 7. Hyattsville, MD: National Center for Health Statistics. 2008
4. Langland-Orban B, Pracht E, Salyani S. Uncompensated care provided by emergency physicians in Florida emergency departments. Health Care Manage Rev. 2005;30(4):315-321. 5. Eastman A, Bishop G, Walsh J, Richardson J, Rice C. The economic status of trauma centers on the eve of health care reform. J Trauma. 1994;36(6): 835-846. 6. Veney JE, Kaluzny AD. Evaluation and Decision Making for Health Services. Chicago, IL: Health Administration Press; 1998.
Copyright © 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Emergency Department Utilization at a Large Regional Hospital A Strategy for Survivability Timothy Rotarius, PhD, MBA; Aaron Liberman, PhD; Kendall Cortelyou-Ward, PhD; Dawn Oetjen, PhD; Reid Oetjen, PhD This research effort provides a brief picture of the operational, patient, and financial patterns of the multiple emergency departments of a large hospital system located in the southeastern United States. The results are presented anonymously as a descriptive case study. A multifaceted strategy is presented to assist hospital leaders as they strive to ensure the survivability of their emergency departments in this era of high uncompensated care. Key words: emergency department, financial characteristics, operational variables, patient characteristics, uncompensated care
HIS ARTICLE BRIEFLY describes the emergency services provided via multiple distinct locations of a large hospital system located in the southeastern United States. To maintain the requested anonymity of the studied hospital system, the organization will be referred to simply as Hospital System (HS). The data described in this article are from 2007. To ensure anonymity of data for both HS and its patients, HS requested that the data not be published until a certain period of time had transpired. This brief description is provided to serve as a backdrop for the presentation of a strategy for hospital leaders to use to ensure continued survivability of their emergency departments (EDs).
T
Author Affiliation: Department of Health Management and Informatics, College of Health and Public Affairs, University of Central Florida, Orlando, Florida. This research was funded by a grant from a regional hospital system that prefers to remain unidentified for this article. The authors have no conflicts of interest. Correspondence: Timothy Rotarius, PhD, MBA, Department of Health Management and Informatics, College of Health and Public Affairs, University of Central Florida, Orlando, Florida, 32816-2205 ([email protected]). DOI: 10.1097/HCM.0b013e3182a9d80b
Hospital System operates multiple EDs located within several free-standing, acute care hospitals. These EDs (1) provide emergency care to patients and (2) as a consequence of that emergency care, operate as a referral to sustained inpatient care. This comprehensive study offers a summation of the activities within these EDs, including an examination of patient demographics, level of treatment provided, and financial patterns. Like all acute care hospitals located in the United States, HS serves many patients who are classified into the relatively broad category of uncompensated care, including patient populations classified as uninsured, uninsurable, underinsured, indigent, and Medicaid eligible. The uncompensated care issue is even more prevalent and pronounced in EDs because of the high acuity level of care normally required. Therefore, this study offers a descriptive profile of uncompensated care in the target EDs, including trends in both real dollar costs and resource utilization. In addition, both the strategic and operational implications of these profiles are presented as trends, such as (a) assessing the effects of treating the uncompensated patient groups in ED space and what resources are used and (b) determining the 321
Copyright © 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
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long-term effects to the community of a resolution/ nonresolution of the utilization problem. The timeliness and importance of this study were indicated by several factors, including the following: There is a strong sense among HS’s emergency services medical staff that patient volume has risen faster than treatment resources. Patients who need emergency care and who receive definitive health care within 1 hour of injury see their chances of survival increase by 85% (ie, this 1-hour time period is commonly referred to as The Golden Hour). Uncompensated care as a percentage of total care has continued to be on the rise. Coupling these facts with 1 state (Massachusetts) that has ordered hospital EDs to halt diversions,1 one can easily sense the looming risk to the financial sustainability of hospital EDs. Emergency departments typically receive inadequate reimbursement for their services from most government agencies.2 3 The Centers for Disease Control estimates that there were 119 million ED visits in 2006 (the year before the data was collected), which represented a 36% increase over the 1996 number. The average charge per hospital admission for a trauma patient was about 3 times higher than that for a nontrauma, acute care admission.2 Nationally, the number of EDs decreased from 4019 to 3833 from 1996 to 2006.3 This follows an earlier reduction of 1100 EDs from 1996 to 1998.4 These losses in ED capacity place a further strain on already overcrowded EDs. Many hospitals are exploring efforts to improve reimbursement for emergency care, with 53% of surveyed hospitals indicating that they are active in (a) lobbying local and state legislators and (b) initiating letter-writing campaigns through hospital associations to convince senators and representatives of the importance of the continuation of emergency care.5 The above factors indicate strongly that there is a need for all hospitals and hospital
systems to understand the patient services and operational cost profiles of its EDs to develop viable strategic plans with attainable goals in terms of both organizational survivability and high-quality patient outcomes.
OVERVIEW OF HS The 2007 financial profile of the multiple EDs of HS indicates that there were 223 273 ED visits amassing almost $2 billion in total gross charges. Contractual adjustments equaled 63.6% of gross charges, with charity care and bad debt equaling 6.3% and 6.2%, respectively, of gross charges. Thus, net collectible charges for the multiple EDs of HS amounted to a maximum of 23.9% of total gross charges. In other words, 76.1% of HS’s gross charges were ultimately deemed uncollectible (because of contractual allowances, charity care, or bad debt). Each of the multiple EDs contributes to the overall HS in different ways. This is likely because of such diverse explanations as differing socioeconomic variables within the specific ED’s market area, differing strategic goals for each ED, and myriad other reasons. To reinforce the differences between the multiple EDs, one only needs to look at broad categories of patients and charges. For example, the number of patients seen in 2007 at each of the EDs was quite uneven. The busiest ED saw 81 286 patients (36.4% of total HS ED patient visits) during 2007, whereas the least busy ED saw 19 940 patients (8.9% of total HS ED patient visits). When factoring in selected financial variables, the following overarching points appear: The ED with the most patient visits (36.4% of total patient visits) generated only 29.7% of total gross charges. The ED generating the most gross charges (42.9% of total gross charges) had only 27.4% of total patient visits. The highest average charge (gross charges divided by number of patients) at any 1 of the EDs was $11 781 per patient. The lowest average charge (gross charges divided by number of patients) at any 1 of the EDs was $3062 per patient.
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ED Utilization at a Large Regional Hospital The highest collection rate at any 1 of the EDs was 88.9%. The lowest collection rate at any 1 of the EDs was 77.4%. In addition, a review of the financial status of the ED patients provides insight into the notion that the financial characteristics of the patients being seen in the respective ED facilities are not the same. For example, 195 131 ED patients of the 223 273 total ED patients (a rate of 87.4%) had contractual allowances associated with the charges for services rendered, which means that these patients had some type of third party–supported private or government insurance. It should be noted that, for 1 visit, patients can be classified into multiple financial status classifications as they move from, for example, commercial insurance coverage to the self-pay obligation. With regard to charity patients, HS’s EDs had 21 813 charity patients at the EDs. Charity is defined as the amount of a patient’s total charges that are written off as charity care. There is no expectation of getting paid for this portion of care because it has been determined via government formulas that these patients have no ability to pay. This figure (21 813 charity patients) represents 9.8% of all patients. Bad debt is the amount of a patient’s total charges that is written off because the patient or the patient intermediary refused to pay for services rendered. In other words, the hospital planned on getting paid for this care but the patient or payer did not pay the entire bill. Of all of the patients seen in the multiple EDs, 74 231 (33.2%) had treatment bills that were not settled (ie, bills that were not paid). In other words, approximately 1 in 3 HS ED patients had some portion of their charges written off as bad debt. Additional points related to the financial characteristics of HS’s ED patients include the following: The highest percentage of charity patients at any 1 of the EDs was 12.3%. The lowest percentage of charity patients at any 1 of the EDs was 5.7%. The highest percentage of bad debt patients at any 1 of the EDs was 36.4%.
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The lowest percentage of bad debt patients at any 1 of the EDs was 25.0%. From the overarching perspective of the entire hospital, an ED performs 2 readily apparent functions: (1) the provision of treatment using ED facilities and (2) as a referral source for the hospital’s inpatient facilities. Emergency patient charges are those charges that are incurred in the ED by patients who are treated and released. These charges include ED charges, nursing services, laboratory charges, and radiology charges. The total emergency treatment patient charges for HS’s multiple EDs equaled 41.4% of the almost $2 billion in total gross charges. Inpatient charges are computed as those charges for patients who, after being treated in the ED, are then admitted as inpatients. Inpatient charges include all of the other charges that the patient incurred after being admitted (if the patient was admitted). Inpatient charges represented 58.6% of HS’s total gross charges. After triaging the patient upon presentation at the ED, HS’s 223 273 ED patients were assigned a service level. These levels of acuity range from 1 to 6, with Service Level 1 being the lowest level of acuity, and Service Level 6, the highest level of acuity. The ED patients were classified as follows: 40% of ED patients were Level 4. 35% of ED patients were Level 3. 17% of ED patients were Level 1. Approximately 400 patients (of 223 273 patients) were classified as Level 5 or Level 6. In other words, for this study, Service Level 4 is, effectively, the highest level of service provided. With regard to measurement for length of stay, when examining ED treatment, one must also review any subsequent inpatient stay. This variable was measured using 7 categories: less than 1 day, 1 day, 2 days, 3 days, 4 days, 5 days, and more than 5 days. For HS, 82% of the 223 273 total ED patient visits were for less than 1 day. The next highest category was more than 5 days at 5%. Thus, only 13% of ED patients stayed between 1 and 5 days. This did not vary when looking at the data for each individual ED.
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Regarding discharge status, an overwhelming percentage of ED patients (95%) were discharged to home, leaving only 5% to be discharged to another health care facility. This variable also did not vary when looking at the data for each individual ED. In reviewing all of HS’s EDs combined, the day admitted to the ED does not show much variance. Monday, with 33 760 visits (15% of the 223 273 total ED visits), was the busiest day. The other 6 days of the week each represented approximately 14% of the total ED visits. These percentages were consistent across each of the individual EDs. For all of HS’s EDs, the preferred patient method of arrival was car (66%), with ambulance (17%) the next most frequent. In general, individual EDs followed this pattern as well. With regard to the primary payer for the ED visit, managed care was the most represented payer (30%) for all of HS’s EDs. Self-pay was the next highest patient financial status classification, followed by Medicaid (20%) and Medicare (15%). From an individual ED perspective, there were several differences in the ranking of payers. For example, 1 ED’s patients were 49% Medicaid and 30% managed care. At another ED, self-pay was the largest category of patients (30%), followed by Medicare (22%) and managed care (21%). In looking at the combined ED data, the age group of 25 to 44 years old was the most frequent user of the EDs at 30% of the total ED patient population. All age groups younger than 25 years (ie, 0-5, 6-17, and 18-24 years) and the 45 to 54 years age group were similar, with percentiles ranging from 11% to 15%. The age groups who least often used the ED were those older than 54 years, making up between 5% and 8% of the ED population. The lone individual ED exception occurred with the ED located within the children’s hospital. As one would expect at a children’s hospital, most patients (67%) were younger than 6 years. With regard to gender, in looking at the combined data for all of HS’s EDs, male and female patients were found to use the EDs relatively equally (47% and 53%, respectively). This percentile did not vary when looking at the individual EDs.
When looking at marital status, unmarried patients made up the largest group of ED users, comprising 61% of the ED patient population. Only 37% of ED users were married. This martial status variable was consistent across the individual EDs. Regarding ethnicity, whites comprised 46% of the patient population of all of HS’s EDs, with blacks (26%) and Hispanics (24%) following. However, several differences were noted when examining the individual EDs. For example, 1 ED identified its patient population as 33% black, 32% Hispanic, and 30% white. Two other EDs identified their patients as more than two-thirds white. This concludes the overview of HS. Next, the research methodology shall be presented. This will be followed by a brief discussion of selected statistically significant variable interactions related to HS’s EDs. A discussion of the implications is next presented. Finally, conclusions are offered to assist hospital leaders as they develop strategies and action items to ensure the survivability of their EDs.
RESEARCH METHODOLOGY This type of analysis was exploratory in nature. As such, it lent itself to using a descriptive case study methodology. Descriptive case studies have been shown to be particularly useful as tools for developing insights as to the particular details of a specific research topic.6 This descriptive case study approach was used to develop a structured assessment of HS’s EDs. Data were derived from a variety of sources, including HS’s internal reports; public reports from federal, state, and local governments; and business and health care journals. Data analysis techniques included the recoding and creation of pertinent variables, cross-tabulations, and the calculation of frequencies and means. Output is presented at the entity level (ie, specific EDs) and at collective levels (ie, all EDs totaled together). The researchers received the HS’s patient encounter database for fiscal year 2007 in 1 database file. This database housed 223 273 patient encounters from all of the EDs to be
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ED Utilization at a Large Regional Hospital studied. To facilitate the conversion from a database program to a spreadsheet program, the data were divided by ‘‘first location’’ or the location at which a patient first presented. After this initial conversion, the data were transformed from the spreadsheet program to a statistical computer program file. The data were put through a rigorous statistical analysis to determine the integrity of the data. Check values were provided in summary form from HS to ensure that double-counting of patient records had not occurred. To ensure the anonymity of the data, the recoding and calculation of several variables were necessary. Continuous variables, such as total charges, were transformed from ratio-level data into categorical-level data. Because the continuous variables in this study were not normally distributed, the traditional mechanism of dividing numbers into randomly selected equal categories is not generally acceptable and could produce an incorrect correlation coefficient. Therefore, the percentile method of variable conversion was used for both total charges (an existing variable) and uncompensated charges (a new variable). The variable total charges was provided by HS in their patient encounter database of ratiolevel variables. The variable uncompensated charges was calculated by the researchers by summing charity and bad debt to create a new variable. In their original form as ratio-level variables, the use of these variables when they are compared with other variables within the data set is limited. To overcome this limitation when examining ratio-level variables in 2 analyses, the researchers used a statistical process called quantile building, which partitions data into equal-sized categories. This quantile-building process yielded quartiles (4 categories), quintiles (5 categories), octiles (8 categories), and deciles (10 categories) for both the total charges and the uncompensated charges variables. A thorough review of these 4 reclassifications for each variable led to the determination that quintiles provided the most efficient and effective mechanism for categorizing total charges and uncompensated charges. Therefore, each variable was recoded to represent the 20th, 40th, 60th,
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and 80th percentile points for the EDs. The quintiles follow. The quintiles used for total charges are as follows: $0 to $330 $331 to $940 $941 to $2150 $2151 to $7600 $7601 or greater The quintiles used for uncompensated charges are as follows: $0 to $85 $86 to $200 $201 to $600 $601 to $1600 $1601 or greater The demographic variable age also presented a challenge in this research project. In this data set, the variable age, like total costs, is not normally distributed. Therefore, dividing the population into same-size categories is not appropriate and the use of percentiles in this context does not fit the nature of the variable. Therefore, in an attempt to create a logical method to divide age into groups, and to ensure that the results of this project could be compared with other studies, the age categories used by the Centers for Disease Control were used in this analysis. The age categories are as follows: 0 to 5 years 6 to 17 years 18 to 24 years 25 to 44 years 45 to 54 years 55 to 64 years 65 to 74 years 75 years or older After all of the variables in the patient encounter database were examined and appropriately coded (as discussed above), the following 12 variables remained: Total charges (total gross charges in 5 categories; see above) Uncompensated charges (charity care + bad debt; shown in 5 categories) Service level (from 1, lowest, to 4, highest) Length of stay (in days; shown in 7 categories) Discharge status (to home or a health care facility)
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Day admitted (day of the week) Method of arrival (ambulance, car, or helicopter) Primary payer (Medicare, Medicaid, managed care, commercial, self-pay) Age group (8 categories; see above) Marital status (2 categories) Sex Ethnicity (white, black, Hispanic) These 12 variables were used to provide a detailed picture of the patients and utilization patterns of HS’s EDs. To explore the financial relationships that exist within the data set, all variables were compared to both total charges and uncompensated charges. In addition, each of the variables was compared to one another to determine other important relationships. Please note, only key findings that are both statistically significant and of substantive importance (ie, that are scientifically rigorous and that are relevant within the confines of this study) will be presented. Variable correlations allow the researchers to explore the relationship and association between variables. For purposes of this project, the relationship between 2 variables was considered statistically significant if the Pearson correlation, captured in the 2 analysis, is less than 0.001 (ie, P < .001). All of the statistical and methodological issues discussed above were brought to bear on the analysis that follows.
KEY FINDINGS This section shows variable interactions for which the Pearson correlation indicates statistical significance at the .001 level. Only those statistically significant variable interactions that are also substantively significant will be examined. After each set of variable interactions is presented, a brief summary is also presented. Regarding ED patients who are younger than 6 years: 22.5% were Hispanic. 37.3% received Service Level 1 care. 94.4% had a length of stay of less than 1 day. 52.3% had Medicaid. 22.1% had uncompensated charges less than $86. 33.4% had total charges less than $331.
Given (a) the lower level of treatment provided, (b) the short treatment time, and (c) the low charges, these results may indicate that these patients are using the ED as a substitute for the primary care setting. Regarding ED patients who were between 18 and 24 years old: 42.5% were self-pay. These younger adults may present themselves to the ED as uninsured. Regarding ED patients who are older than 74 years: 45.1% arrived via ambulance. 66.7% received Service Level 4 care. 19.4% had a length of stay of more than 5 days. 75.1% were discharged to home. These elderly patients tend to use a high proportion of resources (ambulances, highlevel treatment, and longer inpatient stays), yet their medical condition seems to be controllable to the point that they can return directly home. Regarding ED patients who arrived via ambulance: 45.1% were older than 74 years. 59.8% received Service Level 4 care. 11.8% had a length of stay of more than 5 days. 35.6% had Medicare. 35.6% had total charges greater than $7600. The arrival of an elderly patient by ambulance likely indicates a more serious patient acuity level, which will lead to a much greater use of hospital resources. Regarding ED patients who received Service Level 1 care: 37.3% were younger than 6 years. 25.1% had Medicare. 51.1% had uncompensated charges less than $86. 77.9% had total charges less than $331. It may be that many uninsured parents present their children to an ED because they view the ED as a proxy for a primary care setting. Regarding ED patients who received Service Level 4 care: 66.7% were older than 74 years. 59.8% arrived via ambulance.
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ED Utilization at a Large Regional Hospital 95.8% had a length of stay of 1 day. 63.3% had Medicare. 70.5% were discharged to another health care facility. Elderly patients who arrived via ambulance and also received the highest level of health care services were often quickly transferred to a different treatment facility. Regarding ED patients with Medicare: 35.6% arrived via ambulance. 25.1% received Service Level 1 care. 63.3% received Service Level 4 care. 16.8% had a length of stay of more than 5 days. 82.7% were discharged to home. Medicare patients who arrived via ambulance tended to need either primary care services or the highest level of treatment services. In addition, it is likely that a Medicare patient will be discharged directly to his/her own home. The presentation of the key findings is concluded. Of all of the possible variable interactions, very few interactions were statistically significant, with even fewer interactions being substantively significant.
IMPLICATIONS OF STUDY RESULTS The advantages afforded residents and communities through the availability of a hospital’s ED are unassailable. Without the lifesaving and health-preserving services offered through these facilities, the quality of life and, indeed, the attractiveness of any region as a place to reside would be compromised. The question thus becomes how to preserve the availability of that essential resource to residents. All health care organizations operate in a marketplace separated by those who have insurance versus those who do not have insurance. Those who do not have resources to pay for services become a drain on the capacity of a health system to sustain its commitment to emergency services. Accordingly, a hospital system must consider the adoption of an aggressive proactive strategy that will encourage government leaders in the region to begin effecting financing adjustments at the local and regional levels. This must necessarily include a determined drive to secure support for
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a tax-based subsidy to support the ED services offered through a local hospital system. The bottom line to the current health care reality is that a hospital system’s capacity to continue providing high-level emergency services cannot be sustained indefinitely without positive action by the communities and governments comprising the local region. Therefore, the conclusions next offered present a recommended strategy for both (1) informing community residents about the problem and (2) encouraging substantive action to correct the problem now confronting most health care markets. CONCLUSION The value, in terms of enhancing the quality of life through world-class health care and providing services to all persons in need, regardless of ability to pay, indicates strongly that the loss to any local region of its EDs’ capacity would severely impair the ability of the region to provide urgent, acute services to those in need, with the region’s poorest constituents ultimately feeling the effect upon their health care choices. The hospital system examined during the conduct of this study serves as a major provider of health care services to its local region. Its reach as a health services resource, as a teaching and learning organization, and through the extensive array of services it provides continues to represent an important asset in treating emergency cases and offering health care to all patients regardless of ability to pay. The political leadership of the local region has a clear choice to provide a material means of support to the hospital system’s EDs. Without an offset of funding to defray the growing costs of uncompensated care, hospital systems ultimately will have to begin drawing down the curtain on ED services and the communities, and their residents will be forced to seek other treatment modalities to meet these needs. Inevitably, this will result in higher mortality rates for persons experiencing serious trauma as a result of an accident. The choices, therefore, are 2-fold and are very clear both for the political leaders of the region and
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for the governing board of the local hospital systems: Provide a limited taxing authority to the governing board of local hospital systems to defray a portion of the cost of uncompensated care. Establish a tax rate for uncompensated care and control the rate of taxes assessed at the county level. The fundamental issue becomes: How can a hospital system proceed? The following strategy is offered for consideration: The local hospital system should first convene an Emergency Care Summit of local and regional leaders to hear the results of analyses such as those presented herein. This should be a no-holds barred presentation of the realities being confronted by the communities receiving services from the local EDs. As part of the Summit, the local hospital system should present specific examples of the lifesaving results of having this resource in the local health care market. Most hospital systems are flush with ‘‘good news’’ testimonials about the exceptional care received by the local residents. The results of these services are both poignant and compelling. This information must and should be presented for public consumption and thought.
As part of the Summit, the hospital system should offer to make presentations to each of their government entity stakeholders showing the government leaders how many citizens from their respective communities are both directly and indirectly impacted by the hospital system’s facilities and services each year. The hospital system’s Governing Board then should set a timetable for substantive action and notify the affected government entities formally that, absent substantive action, certain services will, out of necessity, have to be curtailed. Those services should be specified for one and all to see, along with the expiration date for action to be affected. The hospital system then should begin contacting individual citizen organizations to enlist their support for encouraging political authorities to act affirmatively. This will be neither an easy sell nor an effort that will likely produce immediate action. One reality of political governance is that our leaders likely will act only after the stark reality of the choices they are confronting becomes apparent. As such, this strategy for hospital systems to follow serves as a means of commencing the process of change in the financing of emergency care services.
REFERENCES 1. Kowalczyk L. State orders hospital ERs to halt diversions. The Boston Globe. September 13, 2008. www.boston .com. Accessed September 16, 2008. 2. Thomas S, McGwin S, Rue L. The financial impact of delayed discharge at a level I trauma center. J Trauma Inj Infect Crit Care. 2005;58(1):121-125. 3. Pitts SR, Niska RW, Xu J, Burt CW. National Hospital Ambulatory Medical Care Survey: 2006 emergency department summary. National health statistics reports; no 7. Hyattsville, MD: National Center for Health Statistics. 2008
4. Langland-Orban B, Pracht E, Salyani S. Uncompensated care provided by emergency physicians in Florida emergency departments. Health Care Manage Rev. 2005;30(4):315-321. 5. Eastman A, Bishop G, Walsh J, Richardson J, Rice C. The economic status of trauma centers on the eve of health care reform. J Trauma. 1994;36(6): 835-846. 6. Veney JE, Kaluzny AD. Evaluation and Decision Making for Health Services. Chicago, IL: Health Administration Press; 1998.
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