American Journal of Emergency Medicine 33 (2015) 155–158
Contents lists available at ScienceDirect
American Journal of Emergency Medicine journal homepage: www.elsevier.com/locate/ajem
Original Contribution
Factors associated with hospital admission for proximal ★ humerus fracture☆ ,☆☆ , Mariano E. Menendez, MD ⁎, David Ring, MD, PhD Orthopaedic Hand and Upper Extremity Service, Yawkey Center, Massachusetts General Hospital, Suite 2100, 55 Fruit St, Boston, MA 02114
a r t i c l e
i n f o
Article history: Received 29 September 2014 Received in revised form 24 October 2014 Accepted 29 October 2014
a b s t r a c t Background: The number of inpatient admissions for proximal humerus fracture is increasing, but the factors that determine hospitalization are not well documented. We sought to identify predictors of hospital admission among individuals presenting to the emergency department (ED) with a fracture of the proximal humerus. Methods: Using the Nationwide Emergency Department Sample for 2010 and 2011, an estimated 285 661 patients were identified and separated into those who were admitted to hospital (19%) and those who were discharged directly home (81%). Multivariable logistic regression modeling was used to identify independent predictors of hospital admission. Results: Factors associated with admission included increasing age and Charlson comorbidity index, ED visit on a weekday, Medicare and Medicaid insurance, open fracture, injury due to motor vehicle crash, polytrauma, urban teaching hospital, and residence in the Northeast. The lowest ratio of hospital admission to home discharge was noted for uninsured patients (0.09). Discussion: Factors unrelated to medical complexity such as insurance status, geographic region, timing of ED visit, and hospital type are associated with inpatient admission for proximal humerus fracture. Interventions to reduce variation in hospital admission and the influence of nonclinical factors merit attention. Level of Evidence: Level II, prognostic study. © 2014 Elsevier Inc. All rights reserved.
1. Introduction Although fractures of the proximal humerus are generally managed as an outpatient, many patients are hospitalized after injury [1,2]. The number of inpatient admissions for proximal humerus fracture appears to be on the rise, driven by both an increase in emergency department (ED) visits and a growing tendency to manage these fractures operatively, which ultimately results in higher health care resource use [2–6]. There is currently no consensus on whom to admit for inpatient care rather than managing as an outpatient, including outpatient surgery. A recent study in patients presenting to the ED with transient ischemic attacks suggested that, apart from clinical factors (eg, age and comorbidity), there might as well be nonclinical factors implicated such as insurance status, household income, and hospital type [7]. In times of
☆ This work was performed at the Orthopaedic Hand and Upper Extremity Service, Massachusetts General Hospital, Boston, MA, USA. ☆☆ Conflict of interest statement: M.M. and D.R. certify that they had nothing of value related to this study. ★ Ethical review committee statement: No institutional review board approval is mandatory for this study. The data are deidentified and commercially available for use. The study has been performed in accordance with the ethical standards in the 1964 Declaration of Helsinki and has been carried out in accordance with relevant regulations of the US Health Insurance Portability and Accountability Act. ⁎ Corresponding author. Tel.: +1 352 871 3851; fax: +1 617 726 0460. E-mail addresses: [email protected] (M.E. Menendez), [email protected] (D. Ring). http://dx.doi.org/10.1016/j.ajem.2014.10.045 0735-6757/© 2014 Elsevier Inc. All rights reserved.
intense scrutiny of health care costs, a better understanding of clinical and nonclinical factors affecting the decision to admit a patient to the hospital for proximal humerus fracture can help reduce variation and cost, and perhaps improve the quality, safety, and efficiency of care by informing efforts to better manage a greater number of fractures as outpatients. Using a large administrative database, this study sought to determine predictors of inpatient admission among individuals who present to US hospital-based EDs with a fracture of the proximal humerus. Specifically, we tested the null hypothesis that there are no factors associated with hospital admission.
2. Methods We conducted this retrospective cross-sectional study using ED encounter data from the Nationwide Emergency Department Sample (NEDS). The NEDS is operated by the Agency for Healthcare Research and Quality and currently represents the largest all-payer ED database in the United States [8,9]. Unweighted, each data set year contains records on approximately 30 million ED visits from more than 900 hospitals, representing a 20% stratified sample of US hospital-based EDs. Weighted, it estimates roughly 130 million ED visits. Besides collecting patient- and provider-related characteristics, the NEDS uses the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes to standardize the reporting of up to 15 diagnoses
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M.E. Menendez, D. Ring / American Journal of Emergency Medicine 33 (2015) 155–158
and procedures. Since its inception in 2006, the NEDS database has been increasingly used for comparative health services research [2,10–14]. Formal approval by our institutional review board was not required as we used anonymous data. We identified all patients presenting to the ED with an ICD-9-CM primary diagnosis code of closed (812.00-812.03, 812.09) or open (812.10-812.13, 812.19) fracture of the proximal humerus [2]. Records for patients who were transferred to another hospital or died in the ED were excluded from analysis [7]. Between January 1, 2010, and December 31, 2011, an estimated 285 661 patients met the inclusion criteria for our study. Patient-level variables included age (both continuous and categorized into the age groups: b60, 60-79, and ≥ 80 years), sex, primary health insurance (Medicare, Medicaid, private, uninsured, and other), and household income of the patient's zip code of residence ($1-$38 999, $39 000-$47 999, $48 000-$63 999, and ≥$64 000). Baseline comorbidity status was quantified using the Charlson comorbidity index [15,16]. We also assessed fracture type (closed and open), trauma type (single trauma and polytrauma), mechanism of injury (fall, motor vehicle traffic crash, struck by person or object, and other), and whether or not the ED visit occurred on a weekend. The study population was aged 62 ± 23 years and predominantly comprised female patients (72%). Most patients sustained an isolated proximal humerus fracture (88%), and the most frequent mechanism of injury was falls (79%; Table 1). Hospitals were classified according to their location and teaching status (nonmetropolitan, metropolitan nonteaching, and metropolitan teaching), geographic region (Northeast, Midwest, South, and West), and trauma level (trauma levels I-III and nontrauma). Our primary outcome of interest was ED disposition, specifically whether a patient was admitted to hospital or was discharged directly to home. We performed bivariate analyses using independentsamples t test for continuous data and Pearson χ 2 test for categorical data to evaluate the association between each explanatory variable to ED disposition. Ratios of hospital admissions to home discharges were calculated for all explanatory variables. Multivariable logistic regression modeling was then used to determine factors independently associated with hospital admission among patients presenting to the ED with a proximal humerus fracture. All predictor variables were included simultaneously in the multivariable regression model [17]. Results were reported as odds ratios (ORs) with 95% confidence intervals (CIs). We evaluated the model's discriminatory performance using the area under the receiver operating characteristic (ROC) curve, which measured the ability of our model to assign a high probability of admission to those patients who were actually admitted to hospital. Area under curve values range from 0.50 to 1.0, with higher values meaning better discrimination. In general, values less than 0.70 can be considered as poor discrimination, between 0.70 and 0.80 as acceptable, between 0.80 and 0.90 as excellent, and above 0.90 as outstanding [18]. We also assessed model performance using the Nagelkerke pseudo R-square, a measure of the proportion of the variation of hospital admission risk explained by our model. Hence, as to set stricter standards owing to multiple testing and the large weighted sample size, the statistical threshold for α error was set at .001.
Table 1 Characteristics of patients presenting to the ED with a proximal humerus fracture Parameter
All patients
ED disposition Home
Weighted, n (%) Age (y), mean ± SD Age group (y), % b60 60-79 ≥80 Sex (%) Male Female Charlson comorbidity index, mean ± SD Insurance status (%) Private Medicare Medicaid Uninsured Other Median household income (%) $1-$38 999 $39 000-$47 999 $48 000-$63 999 ≥$64 000 Hospital location and teaching status (%) Nonmetropolitan Metropolitan nonteaching Metropolitan teaching Hospital geographic region (%) Northeast Midwest South West Trauma center (%) Nontrauma center Trauma levels I-III Visit on weekend (%) No Yes Fracture type (%) Closed Open Mechanism of injury (%) Fall Motor vehicle traffic crash Struck by person or object Other Trauma type (%) Single trauma Polytrauma
P Admitted to hospital
Ratio of admissions to home discharges
285661 (100) 231095 (81) 62 ± 23 60 ± 24
54566 (19) 0.24 72 ± 18 b.001 –
36 38 26
40 38 22
20 37 43
b.001 0.12 0.23 0.46
28 72 0.52 ± 1.2
29 71 0.34 ± 0.89
26 74 1.3 ± 1.8
b.001 0.22 0.24 b.001 –
28 53 8.1 7.1 4.5
30 48 8.8 8.0 4.7
17 72 4.9 3.0 3.5
b.001 0.13 0.35 0.13 0.09 0.17
24 26 25 25
24 26 25 24
22 26 26 27
b.001 0.21 0.23 0.25 0.26
18 45
20 46
11 45
b.001 0.13 0.23
36
35
44
0.30
19 23 38 20
18 23 38 21
21 24 36 20
b.001 0.27 0.24 0.22 0.22
65 35
67 33
56 46
b.001 0.20 0.32
69 31
69 32
72 28
b.001 0.25 0.21
99 0.60
100 0.40
98 1.6
b.001 0.23 0.90
79 3.4
79 2.8
79 5.8
b.001 0.23 0.49
2.6
3.0
0.80
0.06
15
15
15
0.23
88 12
91 8.7
73 27
b.001 0.19 0.73
3. Results Approximately 1 (19%) in 5 patients presenting to the ED with a fracture of the proximal humerus were admitted to hospital (Table 1). When compared with patients discharged directly home, those admitted to hospital were more likely (P b .001) to be older (72 ± 18 vs 60 ± 24 years), be female (74% vs 71%), be Medicare insured (72% vs 48%), be injured in a motor vehicle crash (5.8% vs 2.8%), to present with an open fracture (1.6% vs 0.4%) or polytrauma (27% vs 8.7%), to reside in higher-income neighborhoods (27% vs 24%) or in the Northeast (21% vs 18%), to have more medical comorbidities (Charlson
comorbidity index: 1.3 ± 1.8 vs 0.34 ± 0.89), and to visit the ED on a weekday (72% vs 69%). In addition, patients presenting to metropolitan teaching hospital EDs (44% vs 35%) and trauma-level centers (46% vs 33%) were admitted for inpatient care more often. In multivariable modeling (Table 2), factors independently associated with hospital admission included increasing age and Charlson comorbidity index (OR, 1.7 per 1-unit increase; 95% CI, 1.7-1.7; P b .001), ED visit on a weekday (OR, 1.1; 95% CI, 1.1-1.1; P b .001), Medicare (OR, 1.6; 95% CI, 1.6-1.7; P b .001) and Medicaid (OR, 1.1; 95% CI, 1.11.2; P b .001) insurance, injury due to motor vehicle crash (OR, 3.5;
M.E. Menendez, D. Ring / American Journal of Emergency Medicine 33 (2015) 155–158 Table 2 Multivariable regression modeling: factors associated with hospital admission among patients presenting to the ED with a proximal humerus fracture 95% CI Predictor Age (reference: b60 y) 60-79 ≥80 Female sex (reference: male) Charlson comorbidity index, per 1-unit increase Primary health insurance (reference: private) Medicare Medicaid Uninsured Other Household income (reference: $1-$38 999) $39 000-$47 999 $48 000-$63 999 ≥$64 000 Hospital location and teaching status (reference: nonmetropolitan) Metropolitan nonteaching Metropolitan teaching Hospital geographic region (reference: West) Northeast Midwest South Trauma centers I-III (reference: nontrauma center) Visit on a weekday (reference: weekend visit) Open fracture (reference: closed fracture) Mechanism of injury (reference: fall) Motor vehicle traffic crash Struck by person or object Other Polytrauma (reference: single trauma) Model performance Area under the ROC curve (95% CI) Nagelkerke R-square
Coefficient (β) OR
Lower Upper P
1.4 2.6 1.0 1.7
1.4 2.5 1.0 1.7
1.4 2.7 1.0 1.7
b.001 b.001 .62 b.001
0.47 0.14 −0.31 0.26
1.6 1.1 0.73 1.3
1.6 1.1 0.69 1.2
1.7 1.2 0.78 1.4
b.001 b.001 b.001 b.001
−0.002 0.0030 0.028
1.0 1.0 1.0
1.0 1.0 1.0
1.0 1.0 1.1
.89 .86 .097
0.43 0.52
1.5 1.7
1.5 1.6
1.6 1.7
b.001 b.001
0.21 −0.039 0.010 0.41
1.2 1.0 1.0 1.5
1.2 0.9 1.0 1.5
1.3 1.0 1.0 1.5
b.001 .022 .53 b.001
0.10
1.1
1.1
1.1
b.001
1.6
5.1
4.6
5.7
b.001
1.3 −0.75 0.17 1.3
3.5 0.47 1.2 3.7
3.3 0.42 1.1 3.6
3.7 0.52 1.2 3.8
b.001 b.001 b0.001 b.001
0.33 0.97 0.0060 0.52
0.79 (0.79-0.80) 0.26
95% CI, 3.3-3.7; P b .001), the presence of polytrauma (OR, 3.7; 95% CI, 3.6-3.8; P b .001) or open fracture (OR, 5.1; 95% CI, 4.6-5.7; P b .001), metropolitan nonteaching (OR, 1.5; 95% CI, 1.5-1.6; P b .001) and teaching (OR, 1.7; 95% CI, 1.6-1.7; P b .001) facilities, and residence in the Northeast (OR, 1.2; 95% CI, 1.2-1.3; P b .001). The area under the ROC curve derived from the multivariable model predicting hospital admission was 0.79 (95% CI, 0.79-0.80), indicating near-excellent discriminatory ability. 4. Discussion A better understanding of factors associated with inpatient management of fracture of the proximal humerus can inform efforts to better manage such patients without hospital admission. Anecdotal evidence suggests that the decision to hospitalize a patient with a proximal humerus fracture is influenced primarily by clinical factors such as patient age and medical complexity, but sometimes, careful study reveals nonclinical factors. We therefore sought to identify clinical and nonclinical factors associated with hospital admission after fracture of the proximal humerus. Notwithstanding the large sample size and associated power, our study should be interpreted cautiously in light of several limitations inherent to the analysis of administrative claims data. First, the NEDS data set is based on billing data from ICD-9-CM codes, which are subject to
157
human bias and error. Because the NEDS data are de-identified, validation through cross-referencing medical records was not possible. However, validation of the NEDS data is regularly performed by the Agency for Healthcare Research and Quality. Second, the retrospective nature of the NEDS does not allow ascertainment of the exact reasons (clinical and nonclinical) for which patients were admitted to hospital from the ED. Third, we were unable to adjust for radiographic severity and time from injury to ED visit, both of which may influence ED disposition [19]. Fourth, another limitation was our inability to account for patient/family preferences and hospital bed availability [20]. Fifth, we were unable to compare functional and patient-reported outcomes between patients who were admitted to hospital and those discharged directly to home. Sixth, the NEDS does not allow for long-term follow-up, and we were thus unable to evaluate the impact of ED disposition on outcomes such as mortality, morbidity, and readmissions. Seventh, as each record in the NEDS represents a single ED visit and not a patient, it is possible that there are multiple records for the same patient with frequent ED visits. Finally, the reader should be aware that findings in large-scale studies can be statistically significant yet clinically insignificant. In this study of nationally representative data, we estimated the annual number of ED visits for proximal humerus fractures to be 142830, an estimate consistent with a previous analysis by Kim and colleagues [11] on the epidemiology of humerus fractures in US hospital-based EDs. Approximately 1 in 5 patients presenting to the ED with proximal humerus fracture were subsequently admitted for inpatient care. In agreement with the hip fracture literature [21,22], we found that advanced age was associated with greater odds of hospital admission. Notably, patients 80 years or older were 2.6 times more likely to be admitted compared with patients younger than 60 years. Increasing medical comorbidity was independently associated with risk of hospitalization, which is consistent with previous studies by Neuhaus and colleagues [5,6] indicating that preinjury infirmity plays an important role in health care resource use after proximal humerus fracture. What remains uncertain is the degree to which hospital admission improves health and function after proximal humerus fractures in older, infirm patients and whether there are better or more resourceful options. As expected, the presence of an open fracture, polytrauma, or violent mechanism of injury (eg, motor vehicle crash) was linked to higher rates of hospital admission; however, we also identified sociodemographic disparities in ED disposition after proximal humerus fracture, statistically independent of these measures of patient frailty and injury. Compared with privately insured patients, those with Medicare and Medicaid were more likely to be admitted to the hospital. Conversely, patients without insurance coverage were less likely to be hospitalized and more likely to be discharged directly home. On the one hand, the lower likelihood of admission among the uninsured might place them at risk for suboptimal care and prolonged disability [23]. On the other, it is possible that insured patients are being admitted unnecessarily. Reasons for the observed variation in admission rates according to insurance status merit further investigation. Among the uninsured, factors that could account for some of the variability include lower levels of health literacy, fear of economic repercussions, and provider bias [24]. Patients presenting to the ED on a weekday were 10% more likely to be hospitalized than those visiting the ED during the weekend. It could be argued that patients presenting on weekdays may be older and sicker patients; however, our analysis controlled for these and other important measures of complexity, so it is likely that there is some differential recommendation of inpatient admission on nonmedical grounds. Patients in the Northeast were 20% more likely to be admitted to the hospital than those in the rest of the United States, which is in agreement with a recent study in patients presenting to the ED with urolithiasis [10]. It is well known that the Northeast has the highest per capita spending in health care [25], but reasons for the
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increased rate of admissions remain incompletely understood. Admissions occurred more frequently in urban EDs than in rural EDs. Among urban EDs, hospitalizations were more common in teaching institutions. A plausible explanation might be that urban hospitals—teaching hospitals in particular—are more willing to admit patients because they have more nursing staff available, access to high-technology equipment, and higher hospital bed availability. It might also be that either patient expectations or physician practice habits are different in various regions of the country. In conclusion, there is variation in hospitalization rates after proximal humerus fracture attributable to factors seemingly unrelated to medical complexity such as insurance status, geographic region, timing of ED visit, and hospital type. Measures for reducing variation in admission rates and the influence of nonclinical factors are merited. References [1] Baron JA, Karagas M, Barrett J, Kniffin W, Malenka D, Mayor M, et al. Basic epidemiology of fractures of the upper and lower limb among Americans over 65 years of age. Epidemiology 1996;7:612–8. [2] Kim SH, Szabo RM, Marder RA. Epidemiology of humerus fractures in the United States: nationwide emergency department sample, 2008. Arthritis Care Res (Hoboken) 2012;64:407–14. [3] Jain NB, Kuye I, Higgins LD, Warner JJ. Surgeon volume is associated with cost and variation in surgical treatment of proximal humeral fractures. Clin Orthop Relat Res 2013;471:655–64. [4] Khatib O, Onyekwelu I, Zuckerman JD. The incidence of proximal humeral fractures in New York State from 1990 through 2010 with an emphasis on operative management in patients aged 65 years or older. J Shoulder Elbow Surg 2014;23:1356–62. [5] Neuhaus V, Bot AG, Swellengrebel CH, Jain NB, Warner JJ, Ring DC. Treatment choice affects inpatient adverse events and mortality in older aged inpatients with an isolated fracture of the proximal humerus. J Shoulder Elbow Surg 2013;23:800–6. [6] Neuhaus V, Swellengrebel CH, Bossen JK, Ring D. What are the factors influencing outcome among patients admitted to a hospital with a proximal humeral fracture? Clin Orthop Relat Res 2013;471:1698–706. [7] Chaudhry SA, Tariq N, Majidi S, Afzal MR, Hassan AE, Watanabe M, et al. Rates and factors associated with admission in patients presenting to the ED with TIA in the United States—2006 to 2008. Am J Emerg Med 2013;31:516–9. [8] Elangovan S, Nalliah R, Allareddy V, Karimbux NY, Allareddy V. Outcomes in patients visiting hospital emergency departments in the United States because of periodontal conditions. J Periodontol 2011;82:809–19.
[9] Owens PL, Barrett ML, Gibson TB, Andrews RM, Weinick RM, Mutter RL. Emergency department care in the United States: a profile of national data sources. Ann Emerg Med 2010;56:150–65. [10] Eaton SH, Cashy J, Pearl JA, Stein DM, Perry K, Nadler RB. Admission rates and costs associated with emergency presentation of urolithiasis: analysis of the Nationwide Emergency Department Sample 2006-2009. J Endourol 2013;27:1535–8. [11] Kim SH, Meehan JP, Blumenfeld T, Szabo RM. Hip fractures in the United States: 2008 nationwide emergency department sample. Arthritis Care Res (Hoboken) 2012;64:751–7. [12] Myer PA, Mannalithara A, Singh G, Singh G, Pasricha PJ, Ladabaum U. Clinical and economic burden of emergency department visits due to gastrointestinal diseases in the United States. Am J Gastroenterol 2013;108:1496–507. [13] Selvarajah S, Schneider EB, Becker D, Sadowsky C, Haider AH, Hammond ER. The epidemiology of childhood and adolescent traumatic spinal cord injury in the united states: 2007-2010. J Neurotrauma 2014;31:1548–60. [14] Sharp AL, Choi H, Hayward RA. Don't get sick on the weekend: an evaluation of the weekend effect on mortality for patients visiting US EDs. Am J Emerg Med 2013;31:835–7. [15] Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373–83. [16] Marquez-Lara A, Nandyala SV, Hassanzadeh H, Noureldin M, Sankaranarayanan S, Singh K. Sentinel events in cervical spine surgery. Spine (Phila Pa 1976) 2014;39:715–20. [17] Clarke H, Soneji N, Ko DT, Yun L, Wijeysundera DN. Rates and risk factors for prolonged opioid use after major surgery: population based cohort study. BMJ 2014;348:g1251. [18] Schneeweiss S, Wang PS, Avorn J, Glynn RJ. Improved comorbidity adjustment for predicting mortality in Medicare populations. Health Serv Res 2003;38:1103–20. [19] Kindermann DR, Mutter RL, Cartright-Smith L, Rosenbaum S, Pines JM. Admit or transfer? The role of insurance in high-transfer-rate medical conditions in the emergency department. Ann Emerg Med 2014;63:561–71 [e568]. [20] Forster AJ, Stiell I, Wells G, Lee AJ, van Walraven C. The effect of hospital occupancy on emergency department length of stay and patient disposition. Acad Emerg Med 2003;10:127–33. [21] Johansen A, Evans R, Bartlett C, Stone M. Trauma admissions in the elderly: how does a patient's age affect the likelihood of their being admitted to hospital after a fracture? Injury 1998;29:779–84. [22] West J, Hippisley-Cox J, Coupland CA, Price GM, Groom LM, Kendrick D, et al. Do rates of hospital admission for falls and hip fracture in elderly people vary by socio-economic status? Public Health 2004;118:576–81. [23] Nirula R, Nirula G, Gentilello LM. Inequity of rehabilitation services after traumatic injury. J Trauma 2009;66:255–9. [24] Ruger JP, Richter CJ, Lewis LM. Association between insurance status and admission rate for patients evaluated in the emergency department. Acad Emerg Med 2003;10: 1285–8. [25] Lubell J. It's more expensive there. Health spending 20% higher in Northeast: CMS. Mod Healthc 2007;37:10–1.
Contents lists available at ScienceDirect
American Journal of Emergency Medicine journal homepage: www.elsevier.com/locate/ajem
Original Contribution
Factors associated with hospital admission for proximal ★ humerus fracture☆ ,☆☆ , Mariano E. Menendez, MD ⁎, David Ring, MD, PhD Orthopaedic Hand and Upper Extremity Service, Yawkey Center, Massachusetts General Hospital, Suite 2100, 55 Fruit St, Boston, MA 02114
a r t i c l e
i n f o
Article history: Received 29 September 2014 Received in revised form 24 October 2014 Accepted 29 October 2014
a b s t r a c t Background: The number of inpatient admissions for proximal humerus fracture is increasing, but the factors that determine hospitalization are not well documented. We sought to identify predictors of hospital admission among individuals presenting to the emergency department (ED) with a fracture of the proximal humerus. Methods: Using the Nationwide Emergency Department Sample for 2010 and 2011, an estimated 285 661 patients were identified and separated into those who were admitted to hospital (19%) and those who were discharged directly home (81%). Multivariable logistic regression modeling was used to identify independent predictors of hospital admission. Results: Factors associated with admission included increasing age and Charlson comorbidity index, ED visit on a weekday, Medicare and Medicaid insurance, open fracture, injury due to motor vehicle crash, polytrauma, urban teaching hospital, and residence in the Northeast. The lowest ratio of hospital admission to home discharge was noted for uninsured patients (0.09). Discussion: Factors unrelated to medical complexity such as insurance status, geographic region, timing of ED visit, and hospital type are associated with inpatient admission for proximal humerus fracture. Interventions to reduce variation in hospital admission and the influence of nonclinical factors merit attention. Level of Evidence: Level II, prognostic study. © 2014 Elsevier Inc. All rights reserved.
1. Introduction Although fractures of the proximal humerus are generally managed as an outpatient, many patients are hospitalized after injury [1,2]. The number of inpatient admissions for proximal humerus fracture appears to be on the rise, driven by both an increase in emergency department (ED) visits and a growing tendency to manage these fractures operatively, which ultimately results in higher health care resource use [2–6]. There is currently no consensus on whom to admit for inpatient care rather than managing as an outpatient, including outpatient surgery. A recent study in patients presenting to the ED with transient ischemic attacks suggested that, apart from clinical factors (eg, age and comorbidity), there might as well be nonclinical factors implicated such as insurance status, household income, and hospital type [7]. In times of
☆ This work was performed at the Orthopaedic Hand and Upper Extremity Service, Massachusetts General Hospital, Boston, MA, USA. ☆☆ Conflict of interest statement: M.M. and D.R. certify that they had nothing of value related to this study. ★ Ethical review committee statement: No institutional review board approval is mandatory for this study. The data are deidentified and commercially available for use. The study has been performed in accordance with the ethical standards in the 1964 Declaration of Helsinki and has been carried out in accordance with relevant regulations of the US Health Insurance Portability and Accountability Act. ⁎ Corresponding author. Tel.: +1 352 871 3851; fax: +1 617 726 0460. E-mail addresses: [email protected] (M.E. Menendez), [email protected] (D. Ring). http://dx.doi.org/10.1016/j.ajem.2014.10.045 0735-6757/© 2014 Elsevier Inc. All rights reserved.
intense scrutiny of health care costs, a better understanding of clinical and nonclinical factors affecting the decision to admit a patient to the hospital for proximal humerus fracture can help reduce variation and cost, and perhaps improve the quality, safety, and efficiency of care by informing efforts to better manage a greater number of fractures as outpatients. Using a large administrative database, this study sought to determine predictors of inpatient admission among individuals who present to US hospital-based EDs with a fracture of the proximal humerus. Specifically, we tested the null hypothesis that there are no factors associated with hospital admission.
2. Methods We conducted this retrospective cross-sectional study using ED encounter data from the Nationwide Emergency Department Sample (NEDS). The NEDS is operated by the Agency for Healthcare Research and Quality and currently represents the largest all-payer ED database in the United States [8,9]. Unweighted, each data set year contains records on approximately 30 million ED visits from more than 900 hospitals, representing a 20% stratified sample of US hospital-based EDs. Weighted, it estimates roughly 130 million ED visits. Besides collecting patient- and provider-related characteristics, the NEDS uses the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes to standardize the reporting of up to 15 diagnoses
156
M.E. Menendez, D. Ring / American Journal of Emergency Medicine 33 (2015) 155–158
and procedures. Since its inception in 2006, the NEDS database has been increasingly used for comparative health services research [2,10–14]. Formal approval by our institutional review board was not required as we used anonymous data. We identified all patients presenting to the ED with an ICD-9-CM primary diagnosis code of closed (812.00-812.03, 812.09) or open (812.10-812.13, 812.19) fracture of the proximal humerus [2]. Records for patients who were transferred to another hospital or died in the ED were excluded from analysis [7]. Between January 1, 2010, and December 31, 2011, an estimated 285 661 patients met the inclusion criteria for our study. Patient-level variables included age (both continuous and categorized into the age groups: b60, 60-79, and ≥ 80 years), sex, primary health insurance (Medicare, Medicaid, private, uninsured, and other), and household income of the patient's zip code of residence ($1-$38 999, $39 000-$47 999, $48 000-$63 999, and ≥$64 000). Baseline comorbidity status was quantified using the Charlson comorbidity index [15,16]. We also assessed fracture type (closed and open), trauma type (single trauma and polytrauma), mechanism of injury (fall, motor vehicle traffic crash, struck by person or object, and other), and whether or not the ED visit occurred on a weekend. The study population was aged 62 ± 23 years and predominantly comprised female patients (72%). Most patients sustained an isolated proximal humerus fracture (88%), and the most frequent mechanism of injury was falls (79%; Table 1). Hospitals were classified according to their location and teaching status (nonmetropolitan, metropolitan nonteaching, and metropolitan teaching), geographic region (Northeast, Midwest, South, and West), and trauma level (trauma levels I-III and nontrauma). Our primary outcome of interest was ED disposition, specifically whether a patient was admitted to hospital or was discharged directly to home. We performed bivariate analyses using independentsamples t test for continuous data and Pearson χ 2 test for categorical data to evaluate the association between each explanatory variable to ED disposition. Ratios of hospital admissions to home discharges were calculated for all explanatory variables. Multivariable logistic regression modeling was then used to determine factors independently associated with hospital admission among patients presenting to the ED with a proximal humerus fracture. All predictor variables were included simultaneously in the multivariable regression model [17]. Results were reported as odds ratios (ORs) with 95% confidence intervals (CIs). We evaluated the model's discriminatory performance using the area under the receiver operating characteristic (ROC) curve, which measured the ability of our model to assign a high probability of admission to those patients who were actually admitted to hospital. Area under curve values range from 0.50 to 1.0, with higher values meaning better discrimination. In general, values less than 0.70 can be considered as poor discrimination, between 0.70 and 0.80 as acceptable, between 0.80 and 0.90 as excellent, and above 0.90 as outstanding [18]. We also assessed model performance using the Nagelkerke pseudo R-square, a measure of the proportion of the variation of hospital admission risk explained by our model. Hence, as to set stricter standards owing to multiple testing and the large weighted sample size, the statistical threshold for α error was set at .001.
Table 1 Characteristics of patients presenting to the ED with a proximal humerus fracture Parameter
All patients
ED disposition Home
Weighted, n (%) Age (y), mean ± SD Age group (y), % b60 60-79 ≥80 Sex (%) Male Female Charlson comorbidity index, mean ± SD Insurance status (%) Private Medicare Medicaid Uninsured Other Median household income (%) $1-$38 999 $39 000-$47 999 $48 000-$63 999 ≥$64 000 Hospital location and teaching status (%) Nonmetropolitan Metropolitan nonteaching Metropolitan teaching Hospital geographic region (%) Northeast Midwest South West Trauma center (%) Nontrauma center Trauma levels I-III Visit on weekend (%) No Yes Fracture type (%) Closed Open Mechanism of injury (%) Fall Motor vehicle traffic crash Struck by person or object Other Trauma type (%) Single trauma Polytrauma
P Admitted to hospital
Ratio of admissions to home discharges
285661 (100) 231095 (81) 62 ± 23 60 ± 24
54566 (19) 0.24 72 ± 18 b.001 –
36 38 26
40 38 22
20 37 43
b.001 0.12 0.23 0.46
28 72 0.52 ± 1.2
29 71 0.34 ± 0.89
26 74 1.3 ± 1.8
b.001 0.22 0.24 b.001 –
28 53 8.1 7.1 4.5
30 48 8.8 8.0 4.7
17 72 4.9 3.0 3.5
b.001 0.13 0.35 0.13 0.09 0.17
24 26 25 25
24 26 25 24
22 26 26 27
b.001 0.21 0.23 0.25 0.26
18 45
20 46
11 45
b.001 0.13 0.23
36
35
44
0.30
19 23 38 20
18 23 38 21
21 24 36 20
b.001 0.27 0.24 0.22 0.22
65 35
67 33
56 46
b.001 0.20 0.32
69 31
69 32
72 28
b.001 0.25 0.21
99 0.60
100 0.40
98 1.6
b.001 0.23 0.90
79 3.4
79 2.8
79 5.8
b.001 0.23 0.49
2.6
3.0
0.80
0.06
15
15
15
0.23
88 12
91 8.7
73 27
b.001 0.19 0.73
3. Results Approximately 1 (19%) in 5 patients presenting to the ED with a fracture of the proximal humerus were admitted to hospital (Table 1). When compared with patients discharged directly home, those admitted to hospital were more likely (P b .001) to be older (72 ± 18 vs 60 ± 24 years), be female (74% vs 71%), be Medicare insured (72% vs 48%), be injured in a motor vehicle crash (5.8% vs 2.8%), to present with an open fracture (1.6% vs 0.4%) or polytrauma (27% vs 8.7%), to reside in higher-income neighborhoods (27% vs 24%) or in the Northeast (21% vs 18%), to have more medical comorbidities (Charlson
comorbidity index: 1.3 ± 1.8 vs 0.34 ± 0.89), and to visit the ED on a weekday (72% vs 69%). In addition, patients presenting to metropolitan teaching hospital EDs (44% vs 35%) and trauma-level centers (46% vs 33%) were admitted for inpatient care more often. In multivariable modeling (Table 2), factors independently associated with hospital admission included increasing age and Charlson comorbidity index (OR, 1.7 per 1-unit increase; 95% CI, 1.7-1.7; P b .001), ED visit on a weekday (OR, 1.1; 95% CI, 1.1-1.1; P b .001), Medicare (OR, 1.6; 95% CI, 1.6-1.7; P b .001) and Medicaid (OR, 1.1; 95% CI, 1.11.2; P b .001) insurance, injury due to motor vehicle crash (OR, 3.5;
M.E. Menendez, D. Ring / American Journal of Emergency Medicine 33 (2015) 155–158 Table 2 Multivariable regression modeling: factors associated with hospital admission among patients presenting to the ED with a proximal humerus fracture 95% CI Predictor Age (reference: b60 y) 60-79 ≥80 Female sex (reference: male) Charlson comorbidity index, per 1-unit increase Primary health insurance (reference: private) Medicare Medicaid Uninsured Other Household income (reference: $1-$38 999) $39 000-$47 999 $48 000-$63 999 ≥$64 000 Hospital location and teaching status (reference: nonmetropolitan) Metropolitan nonteaching Metropolitan teaching Hospital geographic region (reference: West) Northeast Midwest South Trauma centers I-III (reference: nontrauma center) Visit on a weekday (reference: weekend visit) Open fracture (reference: closed fracture) Mechanism of injury (reference: fall) Motor vehicle traffic crash Struck by person or object Other Polytrauma (reference: single trauma) Model performance Area under the ROC curve (95% CI) Nagelkerke R-square
Coefficient (β) OR
Lower Upper P
1.4 2.6 1.0 1.7
1.4 2.5 1.0 1.7
1.4 2.7 1.0 1.7
b.001 b.001 .62 b.001
0.47 0.14 −0.31 0.26
1.6 1.1 0.73 1.3
1.6 1.1 0.69 1.2
1.7 1.2 0.78 1.4
b.001 b.001 b.001 b.001
−0.002 0.0030 0.028
1.0 1.0 1.0
1.0 1.0 1.0
1.0 1.0 1.1
.89 .86 .097
0.43 0.52
1.5 1.7
1.5 1.6
1.6 1.7
b.001 b.001
0.21 −0.039 0.010 0.41
1.2 1.0 1.0 1.5
1.2 0.9 1.0 1.5
1.3 1.0 1.0 1.5
b.001 .022 .53 b.001
0.10
1.1
1.1
1.1
b.001
1.6
5.1
4.6
5.7
b.001
1.3 −0.75 0.17 1.3
3.5 0.47 1.2 3.7
3.3 0.42 1.1 3.6
3.7 0.52 1.2 3.8
b.001 b.001 b0.001 b.001
0.33 0.97 0.0060 0.52
0.79 (0.79-0.80) 0.26
95% CI, 3.3-3.7; P b .001), the presence of polytrauma (OR, 3.7; 95% CI, 3.6-3.8; P b .001) or open fracture (OR, 5.1; 95% CI, 4.6-5.7; P b .001), metropolitan nonteaching (OR, 1.5; 95% CI, 1.5-1.6; P b .001) and teaching (OR, 1.7; 95% CI, 1.6-1.7; P b .001) facilities, and residence in the Northeast (OR, 1.2; 95% CI, 1.2-1.3; P b .001). The area under the ROC curve derived from the multivariable model predicting hospital admission was 0.79 (95% CI, 0.79-0.80), indicating near-excellent discriminatory ability. 4. Discussion A better understanding of factors associated with inpatient management of fracture of the proximal humerus can inform efforts to better manage such patients without hospital admission. Anecdotal evidence suggests that the decision to hospitalize a patient with a proximal humerus fracture is influenced primarily by clinical factors such as patient age and medical complexity, but sometimes, careful study reveals nonclinical factors. We therefore sought to identify clinical and nonclinical factors associated with hospital admission after fracture of the proximal humerus. Notwithstanding the large sample size and associated power, our study should be interpreted cautiously in light of several limitations inherent to the analysis of administrative claims data. First, the NEDS data set is based on billing data from ICD-9-CM codes, which are subject to
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human bias and error. Because the NEDS data are de-identified, validation through cross-referencing medical records was not possible. However, validation of the NEDS data is regularly performed by the Agency for Healthcare Research and Quality. Second, the retrospective nature of the NEDS does not allow ascertainment of the exact reasons (clinical and nonclinical) for which patients were admitted to hospital from the ED. Third, we were unable to adjust for radiographic severity and time from injury to ED visit, both of which may influence ED disposition [19]. Fourth, another limitation was our inability to account for patient/family preferences and hospital bed availability [20]. Fifth, we were unable to compare functional and patient-reported outcomes between patients who were admitted to hospital and those discharged directly to home. Sixth, the NEDS does not allow for long-term follow-up, and we were thus unable to evaluate the impact of ED disposition on outcomes such as mortality, morbidity, and readmissions. Seventh, as each record in the NEDS represents a single ED visit and not a patient, it is possible that there are multiple records for the same patient with frequent ED visits. Finally, the reader should be aware that findings in large-scale studies can be statistically significant yet clinically insignificant. In this study of nationally representative data, we estimated the annual number of ED visits for proximal humerus fractures to be 142830, an estimate consistent with a previous analysis by Kim and colleagues [11] on the epidemiology of humerus fractures in US hospital-based EDs. Approximately 1 in 5 patients presenting to the ED with proximal humerus fracture were subsequently admitted for inpatient care. In agreement with the hip fracture literature [21,22], we found that advanced age was associated with greater odds of hospital admission. Notably, patients 80 years or older were 2.6 times more likely to be admitted compared with patients younger than 60 years. Increasing medical comorbidity was independently associated with risk of hospitalization, which is consistent with previous studies by Neuhaus and colleagues [5,6] indicating that preinjury infirmity plays an important role in health care resource use after proximal humerus fracture. What remains uncertain is the degree to which hospital admission improves health and function after proximal humerus fractures in older, infirm patients and whether there are better or more resourceful options. As expected, the presence of an open fracture, polytrauma, or violent mechanism of injury (eg, motor vehicle crash) was linked to higher rates of hospital admission; however, we also identified sociodemographic disparities in ED disposition after proximal humerus fracture, statistically independent of these measures of patient frailty and injury. Compared with privately insured patients, those with Medicare and Medicaid were more likely to be admitted to the hospital. Conversely, patients without insurance coverage were less likely to be hospitalized and more likely to be discharged directly home. On the one hand, the lower likelihood of admission among the uninsured might place them at risk for suboptimal care and prolonged disability [23]. On the other, it is possible that insured patients are being admitted unnecessarily. Reasons for the observed variation in admission rates according to insurance status merit further investigation. Among the uninsured, factors that could account for some of the variability include lower levels of health literacy, fear of economic repercussions, and provider bias [24]. Patients presenting to the ED on a weekday were 10% more likely to be hospitalized than those visiting the ED during the weekend. It could be argued that patients presenting on weekdays may be older and sicker patients; however, our analysis controlled for these and other important measures of complexity, so it is likely that there is some differential recommendation of inpatient admission on nonmedical grounds. Patients in the Northeast were 20% more likely to be admitted to the hospital than those in the rest of the United States, which is in agreement with a recent study in patients presenting to the ED with urolithiasis [10]. It is well known that the Northeast has the highest per capita spending in health care [25], but reasons for the
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increased rate of admissions remain incompletely understood. Admissions occurred more frequently in urban EDs than in rural EDs. Among urban EDs, hospitalizations were more common in teaching institutions. A plausible explanation might be that urban hospitals—teaching hospitals in particular—are more willing to admit patients because they have more nursing staff available, access to high-technology equipment, and higher hospital bed availability. It might also be that either patient expectations or physician practice habits are different in various regions of the country. In conclusion, there is variation in hospitalization rates after proximal humerus fracture attributable to factors seemingly unrelated to medical complexity such as insurance status, geographic region, timing of ED visit, and hospital type. Measures for reducing variation in admission rates and the influence of nonclinical factors are merited. References [1] Baron JA, Karagas M, Barrett J, Kniffin W, Malenka D, Mayor M, et al. Basic epidemiology of fractures of the upper and lower limb among Americans over 65 years of age. Epidemiology 1996;7:612–8. [2] Kim SH, Szabo RM, Marder RA. Epidemiology of humerus fractures in the United States: nationwide emergency department sample, 2008. Arthritis Care Res (Hoboken) 2012;64:407–14. [3] Jain NB, Kuye I, Higgins LD, Warner JJ. Surgeon volume is associated with cost and variation in surgical treatment of proximal humeral fractures. Clin Orthop Relat Res 2013;471:655–64. [4] Khatib O, Onyekwelu I, Zuckerman JD. The incidence of proximal humeral fractures in New York State from 1990 through 2010 with an emphasis on operative management in patients aged 65 years or older. J Shoulder Elbow Surg 2014;23:1356–62. [5] Neuhaus V, Bot AG, Swellengrebel CH, Jain NB, Warner JJ, Ring DC. Treatment choice affects inpatient adverse events and mortality in older aged inpatients with an isolated fracture of the proximal humerus. J Shoulder Elbow Surg 2013;23:800–6. [6] Neuhaus V, Swellengrebel CH, Bossen JK, Ring D. What are the factors influencing outcome among patients admitted to a hospital with a proximal humeral fracture? Clin Orthop Relat Res 2013;471:1698–706. [7] Chaudhry SA, Tariq N, Majidi S, Afzal MR, Hassan AE, Watanabe M, et al. Rates and factors associated with admission in patients presenting to the ED with TIA in the United States—2006 to 2008. Am J Emerg Med 2013;31:516–9. [8] Elangovan S, Nalliah R, Allareddy V, Karimbux NY, Allareddy V. Outcomes in patients visiting hospital emergency departments in the United States because of periodontal conditions. J Periodontol 2011;82:809–19.
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