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Available online at www.sciencedirect.com
ScienceDirect journal homepage: www.JournalofSurgicalResearch.com
When to Admit to Observation: Predicting Length of Stay for Anticoagulated Elderly Fall Victims Kathleen M. O’Neill, MD,a,* Raymond A. Jean, MD, MS, MHS,a Alisa Savetamal, MD,b Ann Dyke, RN,b Roseanne Prunty, PT,b Andrew Stone, BS,b Andrea Castillo, BS,b and Shea C. Gregg, MDb a b
Department of Surgery, Yale School of Medicine, New Haven, Connecticut Department of Surgery, Yale-New Haven Health, Bridgeport Hospital, Bridgeport, Connecticut
article info
abstract
Article history:
Background: Geriatric patients who fall while taking an anticoagulant have a small but
Received 23 April 2019
significant risk of delayed intracranial hemorrhage requiring observation for 24 h. How-
Received in revised form
ever, the medical complexity associated with geriatric care may necessitate a longer stay in
28 October 2019
the hospital. Little is known about the factors associated with a successful observational
Accepted 19 January 2020
status stay (<2 d) for this population.
Available online xxx
Materials and methods: Elderly patients who fell while taking an anticoagulant admitted from 2012 to 2017 at an ACS level II trauma center were included in a retrospective cohort
Keywords:
study to determine what factors were associated with a stay consistent with observational
Financial toxicity
status. Inclusion criteria: age> 65 y old, negative initial head CT, and one of the following:
Head injury
INR>3.5 if on warfarin, GCS<14, external signs of trauma, or focal neurological deficits.
Geriatric
Results: The cohort included 369 patients. Factors associated with decreased likelihood of
Trauma
successful observational status included the need for services after discharge such as an extended care facility (OR 0.06, 95% CI 0.02-0.19, P < 0.001) or visiting nurse agency services (OR 0.27, 95% CI 0.10-0.75, P < 0.001), a dementia diagnosis (OR 0.17, 95% CI 0.04-0.70, P ¼ 0.014), increasing number of medications (OR 0.91, 95% CI 0.84-0.99, P ¼ 0.031), and the use of coumadin (OR 0.28, 95% CI 0.12-0.70, P ¼ 0.006). Conclusions: For trauma providers, knowing your patient’s medication use and particularly type of anticoagulant, comorbidities including dementia, and likely need for services after discharge will help guide the decision to admit the patient for what may be a reasonably lengthy stay versus a brief observation in the hospital for elderly fall victims on anticoagulation. ª 2020 Elsevier Inc. All rights reserved.
Background The rising costs of health care are a major national and social issue in the United States. The financial burden associated with a major medical illness can be substantialdleading to home foreclosure, going without other necessities, stress/
anxiety, and even bankruptcy.1,2 The most common cause of bankruptcy in the United States is due to medical debt.2 This is particularly relevant for elderly patients as out-of-pocket expenses increase with age.3 Geriatric patients who fall while taking an anticoagulant have a small but significant risk of delayed intracranial
* Corresponding author. Department of Surgery, Yale School of Medicine, 330 Cedar Street, FMB 107, New Haven, CT 06510. Tel.: þ(203) 843 4583; fax: þ(203) 737 1718. 0022-4804/$ e see front matter ª 2020 Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jss.2020.01.006
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o’neill et al predicting los for elderly fall victims
hemorrhage.4,5 Most guidelines recommend an observation period for 24 h after a negative head CT, with or without a repeat head CT.5-8 A stay of 24 h would normally only require an observational status admission to the hospital. However, for many of these patients, further workup of other medical conditions or related symptoms is necessary. Falls are often precipitated by neurological or cardiovascular symptoms that require a longer workup and inpatient stay before the patient’s being safe to go home. Further underappreciated is the contribution of physical deterioration leading patients to need further services. All of these issues can lead to an inpatient stay of unpredictable length. This leaves providers in a quandary as they try to decide whether to admit to observation status or inpatient. While seemingly trivial, there is a substantial difference in cost to the hospital as well as to the patient. The observation stay is billed under outpatient services (part B for Medicare patients) while full inpatient admission is billed under inpatient services (part A for Medicare patients). While they both have a 20% coinsurance, the charges for an inpatient stay (part A) are normally substantially higher and patients often have larger out-of-pocket payments for inpatient stays.9 To better understand how to make this decision, we conducted a retrospective cohort study of elderly patients who fell while taking an anticoagulant and had an initial negative head CT to determine what factors are associated with a stay consistent with observational status.
Methods Patients admitted between January 2012 and January 2017 underwent retrospective chart review at our ACS level II trauma center to develop the cohort. Patients were included in the database if they were greater than 65 y old and presented after a fall with head strike while taking a form of anticoagulation. All patients also needed at least one of the following inclusion criteria: INR>3.5 if on warfarin, GCS<14, external signs of head or face trauma, or focal neurological deficits. In prior studies, INR>3 has been associated with an increased risk of delayed intracranial hemorrhage.10 As such, INR>3.5 was used as a hard indication for admission. Patients with a positive head CT on initial presentation were excluded
from the study. This study was approved by Bridgeport Hospital Institutional Review Board. The primary outcome was length of stay. Patients were separated into those with length of stay greater than 2 d and those with length of stay less than or equal to 2 d (consistent with the length of stay of admission for observation). These two groups were compared in a bivariate analysis to determine whether there was a statistical difference in where patients came from, their discharge destination, presence of other injuries, use of an ambulatory assist device, type of anticoagulant, number of comorbidities and type of comorbidities, injury severity score, and number of medications. We used a logistic regression to create a final model that adjusted for all variables. Further sensitivity analyses examined number of medications on the Beer’s Criteria Medication List, presence of multiple injuries, mechanism of injury, recent weight loss, and walking distance. All of these sensitivity analyses were not significant and did not change the conclusions of the study. We performed all statistical analyses using Stata 14 (StataCorp LLC, College Station, Texas).
Results In total 428 patients were included in the database. Our final cohort consisted of 369 patients after excluding those with a positive head CT. The average age of the cohort was 81.7 y (95% CI 10.8-82.7). The average length of stay was 5.36 d (95% CI 4.86-5.85) (Table 1). Within the cohort, 95 patients (24.5%) had a length of stay less than 2 d, consistent with observation status. Twelve patients (2.8% of cohort) were missing data for the length of stay and were excluded. The rest of the cohort had a length of stay greater than 2 d, with an average stay of 6.69 d (95% CI 6.097.28). There was no significant difference in age between those with a stay less than or more than 2 d (P ¼ 0.99). Within the cohort, 45 patients (12.2%) were admitted from an extended care facility (ECF). These patients had eight times the odds of an observational stay compared with those admitted from home (OR 8.71, 95% CI 1.97-38.60, P ¼ 0.041) (Table 2). Discharge destination also had a significant association with length of stay. Those discharged to an ECF, 170 patients (46.1%), had decreased the odds of an observational stay by 94% compared with those discharged to home (OR 0.06,
Table 1 e Variation of study variables between outcome groups. Characteristic Number of patients Average age in years (95% CI) Average length of stay in days (95% CI)
Total
LOS <2 d
LOS>2 d
P-value
369
95
242
n/a
81.7 (80.7-82.7)
81.7 (79.6-83.8)
81.7 (80.5-82.9)
0.99
5.4 (4.9-5.9)
1.7 (1.6-1.8)
6.7 (6.1-7.3)
n/a
Average number of comorbidities (95% CI)
10.7 (10.2-11.3)
11.1 (9.9-12.2)
10.5 (9.8-11.1)
0.34
Average number of medications (95% CI)
12.2 (11.6-12.8)
10.9 (9.6-12.1)
12.6 (11.8-13.3)
0.02
2.7 (2.4-3.1)
1.29 (1.0-1.6)
3.3 (2.9-3.8)
<0.001
Average injury severity score (ISS)
Continuous data are presented as a mean with 95% CI. P-values are from t-test analysis or chi-squared analysis as appropriate. All definitions of variables can be found in the article. CI ¼ confidence interval.
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Table 2 e Bivariate and multivariate associations between study variables and having a length of stay (LOS) less than 2 d. Characteristic
N
% LOS <2 d
222
22.1
1.00
1.00
45
31.1
1.59 (0.79-3.23)
8.71 (1.97-38.60)
Bivariate analysis OR (95% CI)
Multivariate analysis OR (95% CI)
P-value
Where patient came from Home ECF Assisted living
12
33.3
1.77 (0.51-6.11)
1.46 (0.08-25.08)
Outside/public
44
31.8
1.65 (0.81-3.35)
1.41 (0.42-4.77)
70
55.7
1.00
170
10.6
0.09 (0.05-0.19)
0.041
Where patient went to Home ECF Assisted living
1.00
3
66.7
1.59 (0.14-18.36)
5.09 (0.07-352.65)
VNA
60
31.8
0.31 (0.15-0.65)
0.27 (0.10-0.75)
Death/hospice
18
22.2
Number of comorbidities
<0.001
0.06 (0.02-0.19)
0.23 (0.07-0.76)
0.30 (0.03-3.01)
1.02 (0.98-1.07)
1.02 (0.94-1.11)
0.631
Dementia Without dementia With dementia
315
27.3
1.00
53
17.0
0.53 (0.25-1.14)
0.17 (0.04-0.70)
0.014
0.95 (0.92-0.99)
0.91 (0.84-0.99)
0.031
Number of medications
1.00
Type of anticoagulant Eliquis/Pradaxa/Xarelto
95
33.7
1.00
238
24.0
0.58 (0.38-0.90)
Uses assist device
226
21.2
1.00
Walks unassisted
34
47.1
3.82 (1.76-8.29)
2.30 (0.76-6.94)
0.138
0.76 (0.67-0.86)
0.84 (0.69-1.01)
0.061
Coumadin
1.00 0.28 (0.12-0.70)
0.006
Walking ability
Injury severity score
1.00
Logistic regression was used for both bivariate and multivariate analyses. P-values are from multivariate analysis regression. All definitions of variables can be found in the article. CI ¼ confidence interval; OR ¼ odds ratio.
95% CI 0.02-0.19, P < 0.001). In addition, being discharged with a visiting nurse agency (VNA) decreased the odds of an observational stay by 73% compared to those being sent home (OR 0.27, 95% CI 0.10-0.75, P < 0.001). The number of comorbidities had no association with length of stay (OR 1.02, 95% CI 0.93-1.11, P ¼ 0.631). The average number of comorbidities was 10.7 (95% CI 10.2-11.3). There was no difference in number of comorbidities between groups (P ¼ 0.34). The most common comorbidities were cardiac and respiratory conditions. However, only a diagnosis of dementia was found to make a difference in length of stay, significantly decreasing the odds of an observational stay by 83% compared with those without dementia (OR 0.17, 95% CI 0.04-0.70, P ¼ 0.014). There was a significant association between number of medications and the likelihood of observational status. The average number of medications per patient was 12.2 (95% CI 11.6-12.8). Those with a length of stay greater than 2 d took more medications (P ¼ 0.02) (Table 1). With each additional medication on the patient’s medication list, there was a 9% decrease in the likelihood of having observational status (OR 0.91, 95% CI 0.84-0.99, P ¼ 0.031) (Figure). Of note, a sensitivity analysis of the use of medications on the Beer’s Criteria Medication List was also carried out to assess the effect of
those medications on length of stay but was found to not be significant on bivariate analysis or in the risk adjusted model (OR 0.87, 95% CI 0.66-1.15, P ¼ 0.335). Length of stay also varied with the type of anticoagulant used by the patient. Use of warfarin as opposed to dabigatran, apixaban, or rivaroxaban decreased the likelihood of a successful observational status by 72% (OR 0.28, 95% CI 0.12-0.70, P ¼ 0.006). In the risk-adjusted model, there was no association between length of stay and either the ability to walk unassisted or the injury severity score. Unadjusted, an increase of one point in the injury severity score decreased the likelihood of observational status stay by 24% (OR 0.76, 0.67-0.86, P < 0.001). However, this association was attenuated in the fully adjusted model to 16% and was no longer statistically significant (OR 0.84, 95% CI 0.69-1.01, P ¼ 0.061). Similarly, in the unadjusted logistic regression walking without an assistive device more than tripled the likelihood of observational status compared to walking with an assistive device (OR 3.82, 95% CI 1.76-8.29, P < 0.001). In the fully adjusted model, this relationship was no longer significant (OR 2.30, 95% CI 0.76-6.94, P ¼ 0.138). Of note, a sensitivity analysis of the mechanism of injury was carried out and was found to not be significant on bivariate analysis or in the risk-adjusted model (P ¼ 0.26).
o’neill et al predicting los for elderly fall victims
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Fig e Probability of observation status by number of medications. In the fully adjusted model, the probability of successful observation status decreased with the number of medications on the patient’s medication list. (Color version of figure is available online.)
Discussion In this retrospective cohort study of geriatric patients who fell while taking an anticoagulant, we identified several key factors that decreased the likelihood of observational status including the need for services after discharge such as an ECF or VNA services, a dementia diagnosis, increasing number of medications, and the use of warfarin as opposed to a direct thrombin inhibitor or direct factor Xa inhibitor. While prior studies have examined causes of extended length of stay in the elderly,11-15 to the authors knowledge, this is the first study specifically examining factors associated with successful observation status in geriatric patients on anticoagulation presenting with a head injury. Our findings are consistent with some of the prior literature that has demonstrated delay in discharge for elderly patients due to administrative and/or organizational issues,12,16 reimbursement regulations,11 and cognitive decline and functional dependence.13-15 Our findings indicating an association between failure to qualify for observational status with the number of medications and the use of warfarin have not been reported in the literature to the authors’ knowledge. Admission from an extended care facility decreased length of stay, whereas discharge to an extended care facility increased length of stay. The latter association is likely due to those patients who do not come from an extended care facility but require an extended care facility after their injury. The care coordination necessary to place a patient in a new extended care facility is one explanation for this association. Prior literature has indicated that much of the delay in discharging elderly patients from the hospital is due to administrative and/or organizational issues.12,16 Another factor
identified in prior studies is role of reimbursement and insurance in delaying discharge.11 All of the patients in this study are recipients of Medicare, which requires an inpatient stay of more than 3 d before a patient can qualify for placement in an extended care facility. This regulation likely increases these patients’ length of stay and negates the possibility of an observational status admission. While discharge destination may not be known on admission, it can certainly be suspected and taken into account when considering whether to admit the patient to observation versus inpatient. Patients in this cohort had a high number of comorbidities, with an average between ten and eleven. This demonstrates the medical complexity of this patient population. Some of these comorbidities made more of a difference in failure to qualify for observational status than others. Most notably, patients with dementia had longer stays than those without that diagnosis, as has been noted in prior literature.13-15 The number of medications appeared to have a stepwise association with decreasing probability of a successful observation status stay. This reflects the increasing complexity of these patients’ medical care and difficulty with discharge related to managing that care. Finally, in this study, we also found that use of dabigatran, apixaban, or rivaroxaban (direct thrombin inhibitor or direct factor Xa inhibitor) as compared with warfarin significantly increased the likelihood of a successful observational stay. Warfarin requires considerably more testing and can take several days to reach an appropriate INR after reversal. This is the most likely explanation for the increased length of stays associated with warfarin. Length of stay is a complex outcome with many contributing factors. There are a number of confounding factors that
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we did not collect in our data set including socioeconomic status and presence of live-in caregivers or other social support. We were unable to examine these parameters using our data set. As this is a single-center, retrospective study at a level 2 trauma center, it is possible that not all results are generalizable to the rest of the population at large. For providers, the factors identified in this study are important considerations to take into account when determining a patient’s disposition on admission. If a patient needs extra care at homedsuch as an admission to an ECF or VNAdand they already have these services in place, they can likely be safely admitted to an observational status. However, if the patient seems likely to need an increased number of outpatient services, in particular VNA services or transfer to an ECF on discharge, then that patient should have a regular inpatient admission. Other major considerations would include the presence of a dementia diagnosis as well as the type of anticoagulant. If the patient is on warfarin, he or she is likely to need an inpatient admission regardless of other factors.
Conclusion The decision to admit to observation or inpatient is only one in a number of critical decisions made by providers every day. However, providers have a responsibility to consider the financial ramifications of different types of care to protect our patients from the financial toxicity associated with medical care in the United States. Knowing a patient’s ECF status or needs, comorbidities including dementia, medication use, and particularly type of anticoagulant, will help guide the decision to admit the patient for what may be a lengthy stay versus a brief observation in the hospital.
Acknowledgment Authors’ contributions: K.M.O., R.A.J., A.S., and S.C.G. were all intimately involved with the conception and design of the project. A.D., R.P., A.S., and A.C. were critical for the acquisition and curation of the data. K.M.O., R.A.J., and S.C.G. were critically important for the analysis and interpretation of the data. All authors contributed to editing of the final manuscript and gave final approval of this submission. The authors would like to thank Walter Cholewczynski, MD; Roselle Crombie, MD; Kristen Glasgow, MD; John Tyson, MD; Paul Possenti, PA-C; Nabil A. Atweh, MD. Dr. O’Neill acknowledges that this publication was made possible by CTSA Grant Number TL1 TR001864 from the National Center for Advancing Translational Science (NCATS), a component of the National Institutes of Health (NIH). Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NIH. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Disclosure Dr. Shea Gregg is the Founder and President of FallCall Solutions, a company that creates simplified safety applications for those who live an active lifestyle on popular mobile ecosystems. He received no funding to support or conduct this research from FallCall Solutions. All other authors have no conflicts to disclose. This work was presented at The EAST Annual Scientific Assembly Jan 10-14, 2017 in Hollywood, FL.
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