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Posterior Cervical Decompression and Fusion: Assessing Risk Factors for Nonhome Discharge and the Impact of Disposition on Postdischarge Outcomes
Original Article
Posterior Cervical Decompression and Fusion: Assessing Risk Factors for Nonhome Discharge and the Impact of Disposition on Postdischarge Outcomes Daniel J. Snyder1, Sean N. Neifert1, Jonathan S. Gal2, Brian C. Deutsch1, John M. Caridi3,4
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BACKGROUND: The purpose of this study was to identify predictors for postacute care facility discharge for patients undergoing posterior cervical decompression and fusion (PCDF) and to determine if discharge placement impacts postdischarge outcomes.
1.14e1.5; P [ 0.0002). Patients with PCDF with nonhome discharges had an increased likelihood of having a severe postdischarge AE (OR, 1.71; 95% CI, 1.26e2.33; P [ 0.0006) and an unplanned readmission (OR, 1.45; 95% CI, 1.15e1.82; P [ 0.002).
METHODS: Patients undergoing PCDF from 2012 to 2015 were queried from the NSQIP database (n [ 8743) and separated by discharge placement. Outcomes included nonhome discharge, unplanned 30-day readmission, and adverse events (AEs), both before and after discharge. Demographics and comorbidities were analyzed using bivariate analysis. Multivariate logistic regression was used to identify predictors for nonhome discharge, readmission, and severe AE after discharge.
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RESULTS: Patients with nonhome discharges were significantly older (67.4 vs. 58.6 years; P < 0.001), sicker (82% vs. 54% American Society of Anesthesiologists >2; P < 0.001), and more functionally dependent (16% vs. 3.4%; P < 0.001), with a greater comorbidity burden. Patients with PCDF had an increased likelihood of nonhome discharge if they had a dependent functional status (odds ratio [OR], 2.99; 95% confidence interval [CI], 2.33e3.82; P < 0.001), diabetes (OR, 1.32; 95% CI, 1.13e1.55; P [ 0.0007), and an American Society of Anesthesiologists >2 (OR, 1.75; 95% CI, 1.5e2.05; P < 0.001), as well as if they were older (OR, 1.06; 95% CI, 1.05e1.06; P < 0.001) and female (OR, 1.31; 95% CI,
osterior cervical decompression and fusion (PCDF) is an effective surgical intervention used to treat a variety of cervical spine disorders.1 The age and medical complexity of the surgical population eligible for this procedure has increased in recent years, leading to an exponential increase in the number of cervical fusion procedures performed per year.2 Costs associated with this procedure have also increased; spinal fusion procedures such as PCDF have amounted to almost $290 billion dollars in total expenditure between 2000 and 2010, with almost 4 million surgical procedures in the United States alone.3 In response to concurrent increases in cost and volume, cervical fusion procedures such as PCDF have been identified as a possible target for bundled payments by the Centers for Medicare and
Key words Bundled payments - Episode-based outcomes - Nonhome discharge - Outcomes - SNF - Unplanned readmission
PCDF: Posterior cervical decompression and fusion SNF: Skilled nursing facility UTI: Urinary tract infection
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Abbreviations and Acronyms ACDF: Anterior cervical discectomy and fusion ASA: American Society of Anesthesiologists CPT: Current Procedural Terminology DVT: Deep vein thrombosis IRF: Inpatient rehabilitation facility LOS: Length of stay NSQIP: National Surgical Quality Improvement Program PAC: Postacute care
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CONCLUSIONS: Results of this cross-sectional study suggest that patients with PCDF discharged to a postacute care facility have a higher likelihood of having a severe AE after discharge as well as a higher likelihood of being readmitted.
INTRODUCTION
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From the 1Department of Medical Education, Icahn School of Medicine at Mount Sinai, New York, New York; and Departments of 2Anesthesiology, Perioperative and Pain Medicine, 3 Neurosurgery, and 4Orthopedics, Mount Sinai Hospital, New York, New York, USA To whom correspondence should be addressed: Daniel J. Snyder, B.S. [E-mail: [email protected]] Citation: World Neurosurg. (2019). https://doi.org/10.1016/j.wneu.2019.01.214 Journal homepage: www.journals.elsevier.com/world-neurosurgery Available online: www.sciencedirect.com 1878-8750/$ - see front matter ª 2019 Elsevier Inc. All rights reserved.
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ORIGINAL ARTICLE DANIEL J. SNYDER ET AL.
PCDF: DISCHARGE PLACEMENT AND OUTCOMES
Medicaid Services.4 The bundled payment structure, a fixed payment per episode of care, is intended to shift the focus of care from service quantity to care quality, with the goal of simultaneously improving outcomes and decreasing costs.5 Although the primary areas targeted for cost reduction and care improvement include decreasing length of stay (LOS) and mitigating unplanned readmissions and emergency room visits,6 studies of total joint arthroplasty have indicated that discharge destination can also affect the cost per episode of care, not only directly7 but also through increased adverse events after discharge and unplanned readmissions.8,9 Risk factors for increased LOS and unplanned readmission in posterior cervical fusion have been examined in the literature,10,11 and predictors for discharge destination have been examined for anterior cervical discectomy and fusion (ACDF).12 Determining the factors predisposing patients with PCDF to nonhome discharge and elucidating the implications of nonhome discharge in this patient population are a critical step toward making the bundled payment model viable for PCDF. This study aims to characterize patients with PCDF by discharge disposition using American College of Surgeons National Surgical Quality Improvement Program (NSQIP) data from 2012 to 2015. Rates of predischarge and postdischarge adverse events are compared between patients with home and nonhome discharges. Predictors of nonhome discharge, the occurrence of a severe postdischarge adverse event, and unplanned readmission are also evaluated. METHODS The NSQIP Database After institutional review board approval, all patients undergoing PCDF between 2012 and 2015 were queried from the American College of Surgeons NSQIP database. The NSQIP database prospectively collects data from more than 350 institutions13 and contains information such as patient factors, comorbidities, and postoperative outcomes up to 30 days from discharge. The validity and reproducibility of this database have been shown in the literature.14 Defining the Cohort To establish the cohort, PCDF cases were preliminarily identified using Current Procedural Terminology (CPT) codes 63045, 63001, 63015, 22110, 22210, and 22600. Patients who underwent anterior cervical fusion during the same hospital stay (i.e., a fronteback) were then excluded using the CPT codes 63075, 22554, and 22551. Variables Collected Demographic variables collected included age, gender, and race. Patient factors collected included principal postoperative diagnosis, body mass index, American Society of Anesthesiologists (ASA) physical status classification, functional status, and history of smoking. Comorbidities collected included history of diabetes, pulmonary disease, cardiac disease, hypertension requiring medication, renal failure, stroke, steroid requirement, and bleeding disorder. Perioperative variables collected included operative time and total LOS. Readmissions within 30 days were also collected.
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Both minor and severe adverse events were queried from the NSQIP database. Minor adverse events included urinary tract infection (UTI), pneumonia, and superficial surgical site infection. Severe adverse events included deep wound infection, organ/space infection, wound dehiscence, reintubation, deep vein thrombosis (DVT), pulmonary embolism, weaning failure, renal insufficiency, renal failure, cerebrovascular accident, cardiac arrest, myocardial infarction, sepsis, septic shock, reoperation, and death. Events were further separated based on if they occurred before discharge or after discharge. Discharge destination was also collected. Statistical Analysis All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, North Carolina, USA). A 2-tailed P value of 0.05 was considered to be significant. Demographic data, principal diagnoses, comorbidities, operative time, predischarge adverse events, postdischarge adverse events, infections, and unplanned readmissions were compared between 4 cohorts: patients discharged home, patients discharged to a skilled nursing facility (SNF), patients discharged to an inpatient rehabilitation facility (IRF), and patients discharged to either an SNF or an IRF (i.e., nonhome discharge). This strategy yielded 4 comparisons: home discharge versus SNF, home discharge versus IRF, SNF versus IRF, and home discharge versus nonhome discharge. Continuous variables were analyzed using Student t tests, whereas categorical variables were compared using c2 or Fisher exact tests, depending on the complication frequency. Stepwise multivariate logistic regression using backward elimination with an inclusion P value of 0.2 was used to identify risk factors for nonhome discharge, unplanned 30-day readmission, and the occurrence of a severe adverse event after discharge. Patient-level factors (e.g., age, principal diagnosis, and comorbidities) were included in the regression models if they were significant predictors of the outcome of interest (i.e., unplanned readmission and severe adverse event after discharge) to help determine if nonhome discharge was a predictor of these outcomes after correcting for differences in patient population. Cervical spondylolysis without myelopathy was set as the reference principal diagnosis in the models. RESULTS A total of 8743 patients underwent PCDF between 2012 and 2015. Discharge destinations were distributed as follows: 73% home, 12% to a SNF, and 15% to an IRF. Patients with nonhome discharges were older on average, with a higher likelihood of having a dependent functional status and an ASA designation >2 (Table 1). Patients with nonhome discharges also had higher rates of the following comorbidities: diabetes, pulmonary disease, cardiac disease, hypertension requiring medication, stroke, steroids, and bleeding disorder. Operative time was significantly higher for patients with nonhome discharges. Principal diagnoses also varied significantly by discharge destination; more patients discharged to a SNF or IRF had myelopathy accompanying either cervical spondylolysis or an intervertebral disc disorder. When predischarge adverse events were compared by discharge destination, patients with nonhome discharges had a significantly higher proportion of severe adverse events (11% vs. 2.1%;
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ORIGINAL ARTICLE DANIEL J. SNYDER ET AL.
PCDF: DISCHARGE PLACEMENT AND OUTCOMES
Table 1. Patient Demographics by Discharge Disposition for Patients Undergoing Posterior Cervical Decompression and Fusion Home (n [ 6407)
SNF IRF Nonhome Home versus (n [ 1023) (n [ 1313) (n [ 2336) SNF (P Value)
Age (years), mean (standard deviation)
58.6 (12.3)
69.2 (11.9)
66 (12.5)
67.4 (12.3)
Sex (male)
3829 (60)
539 (53)
813 (62)
1352 (58)
Race White
4966 (78)
771 (75)
896 (68)
1667 (71)
African American
694 (11)
172 (17)
251 (19)
423 (18)
Asian
140 (2.2)
26 (2.5)
32 (2.4)
58 (2.5)
<0.0001
Home versus IRF (P Value) <0.0001
Home versus Nonhome SNF versus (P Value) IRF (P Value) <0.0001
<0.0001
<0.0001
0.15
0.11
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
Other
87 (1.4)
12 (1.2)
8 (0.6)
20 (0.9)
Unknown
520 (8.1)
42 (4.1)
126 (9.6)
168 (7.2)
386 (6)
56 (5.5)
93 (7.1)
149 (6.4)
0.49
0.15
0.54
0.11
American Society of Anesthesiology physical status classification >2
3469 (54)
859 (84)
1064 (81)
1923 (82)
<0.0001
<0.0001
<0.0001
0.07
History of smoking
1680 (26)
202 (20)
295 (22)
497 (21)
<0.0001
0.005
<0.0001
0.11
Dependent functional status
216 (3.4)
182 (18)
187 (14)
369 (16)
<0.0001
<0.0001
<0.0001
0.02
Body mass index >40 kg/m2
Comorbidities History of diabetes
1029 (16)
267 (26)
327 (25)
594 (25.4)
<0.0001
<0.0001
<0.0001
0.51
History of pulmonary disease
332 (5.2)
102 (10)
99 (7.5)
201 (8.6)
<0.0001
0.0007
<0.0001
0.04
36 (0.6)
33 (3.2)
23 (1.8)
56 (2.4)
<0.0001
<0.0001
<0.0001
0.02
3262 (51)
718 (70)
860 (66)
1578 (68)
<0.0001
<0.0001
<0.0001
0.02
History of renal failure
7 (0.1)
6 (0.6)
3 (0.2)
9 (0.4)
0.005
0.39
0.02
0.19
History of stroke
10 (0.2)
5 (0.5)
8 (0.6)
13 (0.6)
0.04
0.006
0.001
0.7
History of cardiac disease History of hypertension requiring medication
History of steroids
281 (4.4)
74 (7.2)
100 (7.6)
174 (7.5)
<0.0001
<0.0001
<0.0001
0.73
History of bleeding disorder
109 (1.7)
60 (5.9)
47 (3.6)
107 (4.6)
<0.0001
<0.0001
<0.0001
0.009
158 (92)
193 (104)
197 (109)
195 (107)
<0.0001
<0.0001
<0.0001
0.32
<0.0001
<0.0001
<0.0001
0.13
Operative time (minutes), mean (standard deviation) Principal postoperative diagnosis Cervical spondylolysis with myelopathy
1770 (37)
391 (59)
496 (57)
887 (58)
Spinal stenosis in cervical region
1383 (29)
170 (26)
232 (26)
402 (26)
Cervical spondylolysis without myelopathy
472 (9.8)
27 (4.0)
17 (1.9)
44 (2.9)
Intervertebral disc disorder with myelopathy
324 (6.8)
55 (8.3)
92 (11)
147 (9.5)
Other mechanical complication
273 (5.7)
14 (2.1)
17 (1.9)
31 (2.0)
Brachial neuritis or radiculitis not otherwise specified
241 (5.0)
2 (0.3)
4 (0.5)
6 (0.4)
Displacement cervical intervertebral disc without myelopathy
210 (4.4)
2 (0.3)
7 (0.8)
9 (0.6)
Degeneration of cervical intervertebral disc
128 (2.7)
5 (0.8)
11 (1.3)
16 (1.0)
Values are number (%) except where indicated otherwise. SNF, skilled nursing facility; IRF, inpatient rehabilitation facility.
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PCDF: DISCHARGE PLACEMENT AND OUTCOMES
Table 2. Predischarge and Postdischarge Adverse Events by Discharge Disposition for Patients Undergoing Posterior Cervical Decompression and Fusion Home versus Nonhome SNF versus IRF (P Value) (P Value)
Home (n [ 6407)
SNF (n [ 1023)
IRF (n [ 1313)
Nonhome (n [ 2336)
Home versus SNF (P Value)
Home versus IRF (P Value)
50 (0.8)
68 (6.7)
67 (5.1)
135 (5.8)
<0.0001
<0.0001
<0.0001
0.11
Urinary tract infection
22 (0.3)
30 (2.9)
27 (2.1)
57 (2.4)
<0.0001
<0.0001
<0.0001
0.17
Pneumonia
21 (0.3)
36 (3.5)
41 (3.1)
77 (3.3)
<0.0001
<0.0001
<0.0001
0.59
Superficial infection
7 (0.1)
3 (0.3)
3 (0.2)
6 (0.3)
0.15
0.39
0.11
1
Infectiony
28 (0.4)
43 (4.2)
35 (2.7)
78 (3.3)
<0.0001
<0.0001
<0.0001
0.04
Severe adverse eventz
Predischarge Minor adverse event*
134 (2.1)
125 (12)
132 (10)
257 (11)
<0.0001
<0.0001
<0.0001
0.1
Deep wound infection
6 (0.1)
7 (0.7)
4 (0.3)
11 (0.5)
0.0007
0.07
0.0004
0.23
Organ/space infection
3 (0.1)
4 (0.4)
5 (0.4)
9 (0.4)
0.009
0.005
0.0007
1
Would dehiscence
4 (0.1)
2 (0.2)
1 (0.1)
3 (0.1)
0.19
1
0.39
0.58
Reintubation
19 (0.3)
20 (2)
30 (2.3)
50 (2.1)
<0.0001
<0.0001
<0.0001
0.58
Deep vein thrombosis
11 (0.2)
18 (1.8)
21 (1.6)
39 (1.7)
<0.0001
<0.0001
<0.0001
0.76
Pulmonary embolism
10 (0.2)
7 (0.7)
10 (0.8)
17 (0.7)
0.001
<0.0001
<0.0001
0.83
Weaning failure
18 (0.3)
45 (4.4)
36 (2.7)
81 (3.5)
<0.0001
<0.0001
<0.0001
0.03
Renal insufficiency
1 (<0.1)
1 (0.1)
1 (0.1)
2 (0.1)
0.26
0.31
0.18
1
Renal failure
2 (<0.1)
5 (0.5)
0 (0.0)
5 (0.2)
0.0008
1
0.02
0.02
Cerebrovascular accident
5 (0.1)
4 (0.4)
5 (0.4)
9 (0.4)
0.03
0.006
0.002
1
Cardiac arrest
3 (0.1)
8 (0.8)
7 (0.5)
15 (0.6)
<0.0001
0.0003
<0.0001
0.46
Myocardial infarction
7 (0.1)
10 (1)
6 (0.5)
16 (0.7)
<0.0001
0.005
<0.0001
0.13
Sepsis
10 (0.2)
22 (2.2)
20 (1.5)
42 (1.8)
<0.0001
<0.0001
<0.0001
0.26
Septic shock
3 (0.1)
12 (1.2)
8 (0.6)
20 (0.9)
<0.0001
<0.0001
<0.0001
0.14
Reoperation
72 (1.1)
50 (4.9)
58 (4.4)
108 (4.6)
<0.0001
<0.0001
<0.0001
0.59
Death
0 (0.0)
2 (0.2)
0 (0.0)
2 (0.1)
0.02
1
0.07
0.19
3.4 (5.4)
8.5 (8.4)
8.4 (8.3)
8.5 (8.3)
<0.0001
<0.0001
<0.0001
0.74
Total length of stay (days), mean (standard deviation) Postdischarge Minor adverse event* Urinary tract infection
138 (2.2)
37 (3.6)
79 (6)
116 (5)
0.004
<0.0001
<0.0001
0.008
51 (0.8)
22 (2.2)
53 (4)
75 (3.2)
<0.0001
<0.0001
<0.0001
0.01
Pneumonia
16 (0.3)
13 (1.3)
11 (0.8)
24 (1)
<0.0001
0.001
<0.0001
0.3
Superficial infection
73 (1.1)
5 (0.5)
19 (1.5)
24 (1)
0.06
0.35
0.66
0.02
Infectiony
153 (2.4)
28 (2.7)
41 (3.1)
69 (3)
0.51
0.12
0.14
0.59
Severe adverse eventz
214 (3.3)
72 (7)
72 (5.5)
144 (6.2)
<0.0001
0.0002
<0.0001
0.12
Deep wound infection
58 (0.9)
6 (0.6)
10 (0.8)
16 (0.7)
0.31
0.62
0.32
0.61
Organ/space infection
12 (0.2)
6 (0.6)
4 (0.3)
10 (0.4)
0.02
0.33
0.05
0.35
Would dehiscence
30 (0.5)
10 (1)
7 (0.5)
17 (0.7)
0.04
0.76
0.14
0.21
Reintubation
9 (0.1)
3 (0.3)
4 (0.3)
7 (0.3)
0.22
0.26
0.12
1
Deep vein thrombosis
17 (0.3)
6 (0.6)
16 (1.2)
22 (0.9)
0.09
<0.0001
<0.0001
0.12
Pulmonary embolism
13 (0.2)
7 (0.7)
8 (0.6)
15 (0.6)
0.006
0.01
0.001
0.82 Continues
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PCDF: DISCHARGE PLACEMENT AND OUTCOMES
Table 2. Continued
Weaning failure Renal insufficiency
Home versus Nonhome SNF versus IRF (P Value) (P Value)
Home (n [ 6407)
SNF (n [ 1023)
IRF (n [ 1313)
Nonhome (n [ 2336)
Home versus SNF (P Value)
Home versus IRF (P Value)
4 (0.1)
5 (0.5)
1 (0.1)
6 (0.3)
0.004
1
0.03
0.09
1 (<0.1)
4 (0.4)
1 (0.1)
5 (0.2)
0.002
0.31
0.006
0.18
Renal failure
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
—
—
—
—
Cerebrovascular accident
7 (0.1)
2 (0.2)
0 (0.0)
2 (0.1)
0.36
0.61
1
0.19
2 (<0.1)
4 (0.4)
3 (0.2)
7 (0.3)
0.004
0.04
0.002
0.71
Cardiac arrest Myocardial infarction
3 (0.1)
6 (0.6)
0 (0.0)
6 (0.3)
0.0004
1
0.01
0.007
Sepsis
24 (0.4)
15 (1.5)
8 (0.6)
23 (1)
<0.0001
0.23
0.0006
0.04
Septic shock
3 (0.1)
1 (0.1)
4 (0.3)
5 (0.2)
0.45
0.02
0.04
0.39
Reoperation
135 (2.1)
26 (2.5)
34 (2.6)
60 (2.6)
0.38
0.28
0.2
0.94
Death
16 (0.3)
17 (1.7)
10 (0.8)
27 (1.2)
<0.0001
0.004
<0.0001
0.04
Readmission
381 (6)
116 (11)
122 (9.3)
238 (10)
<0.0001
<0.0001
<0.0001
0.1
Values are number (%) except where indicated otherwise. SNF, skilled nursing facility; IRF, inpatient rehabilitation facility. *Number of patients with any minor adverse event listed. yNumber of patients with superficial wound infection, deep wound infection, organ/space infection, sepsis, or septic shock. zNumber of patients with any severe adverse event listed.
P < 0.001) (Table 2). When severe adverse events were examined individually, substantial discrepancies were seen between rates of reintubation (2.1% vs. 0.3%), DVT (1.7% vs. 0.2%), weaning failure (3.5% vs. 0.3%), sepsis (1.8% vs. 0.2%), and reoperation (4.6% vs. 1.1%) between patients with nonhome and home discharges (all P < 0.001). Patients with nonhome discharges also had a significantly higher proportion of minor adverse events (5.8% vs. 0.8%), mainly being driven by higher rates of UTI (2.4% vs. 0.3%) and pneumonia (3.3% vs. 0.3%) (all P < 0.001). Overall rates of infection were higher for patients with nonhome discharges (3.3% vs. 0.4%; P < 0.001), and total LOS was significantly higher on average for patients with nonhome discharges (8.5 vs. 3.4 days; P < 0.001). With the exception of renal failure (0.5% vs. 0%; P ¼ 0.02), weaning failure (4.4% vs. 2.7%; P ¼ 0.03), and overall rates of infection (4.2% vs. 2.7%; P ¼ 0.04), predischarge adverse events did not differ significantly between those discharged to an SNF versus those discharged to an IRF. When postdischarge adverse events were compared by discharge destination, patients with nonhome discharges also had a significantly higher proportion of severe adverse events (6.2% vs. 3.3%; P < 0.001) (Table 2). This finding was mainly driven by higher rates of DVT (0.9% vs. 0.3%; P < 0.001), pulmonary embolism (0.6% vs. 0.2%; P ¼ 0.001), renal insufficiency (0.2% vs. <0.1%), cardiac arrest (0.3% vs. <0.1%), myocardial infarction (0.3% vs. 0.1%), and sepsis (1% vs. 0.4%) (all P < 0.01); mortality was significantly higher in patients with nonhome discharges (1.2% vs. 0.3%; P < 0.001), with 1.7% of patients discharged to an SNF dying after discharge. Patients with nonhome discharges also experienced a greater proportion of minor adverse events postdischarge (5% vs. 2.2%), again
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driven mainly by increased rates of UTI (3.2% vs. 0.8%) and pneumonia (1% vs. 0.3%) (all P < 0.001). Patients with nonhome discharges also had significantly more readmissions (10% vs. 6%; P < 0.001). When adverse event rates were compared between SNFs and IRFs, patients discharged to a SNF had higher rates of sepsis (1.5% vs. 0.6%; P ¼ 0.04) and death (1.7% vs. 0.8%; P ¼ 0.04), whereas patients discharged to an IRF had higher rates of UTI (4% vs. 2.2%; P ¼ 0.01). On multivariate analysis, having a dependent functional status (OR, 2.99), an ASA designation >2 (OR, 1.75), and a diagnosis of spinal stenosis (OR, 2.37), cervical spondylolysis with myelopathy (OR, 3.2), or intervertebral disc disorder with myelopathy (OR, 3.04) were the strongest predictors of nonhome discharge (all P < 0.001) (Table 3). Female sex (OR, 1.31; P ¼ 0.0002) and a history of diabetes (OR, 1.32; P ¼ 0.0007) were also associated with an increased likelihood of nonhome discharge. Other significant predictors of nonhome discharge included age, operative time, and total LOS (all OR, <1.2; P < 0.001). In a multivariate model correcting for patient-level factors, the strongest predictors of having a severe adverse event after discharge were having a nonhome discharge (OR, 1.71; P ¼ 0.0006) and a severe adverse event before discharge (OR, 1.91; P ¼ 0.02) (Table 3). Similarly, nonhome discharge (OR, 1.45; P ¼ 0.002) and having a severe adverse event before discharge (OR, 1.59; P ¼ 0.03) were significant predictors for unplanned readmission, along with having an ASA designation >2 (OR, 1.3; P ¼ 0.02). DISCUSSION With the implementation of bundled payments, properly riskstratifying patients for nonhome discharge is critical. Although
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Table 3. Predictors for Nonhome Discharge, Severe Postdischarge Adverse Events, and Unplanned Readmission for Patients Undergoing Posterior Cervical Decompression and Fusion Outcome/Predictors
Odds Ratio (95% Confidence Interval)
P Value
Nonhome discharge*
C Statistic 0.84
2.99 (2.33e3.82)
<0.0001
ASA status >2
1.75 (1.5e2.05)
<0.0001
Age
1.06 (1.05e1.06)
<0.0001
Dependent functional status
1.002 (1.002e1.003)
<0.0001
Female sex
1.31 (1.14e1.5)
0.0002
History of diabetes
1.32 (1.13e1.55)
0.0007
Total length of stay
1.19 (1.16e1.21)
<0.0001
Cervical spondylolysis with myelopathy
3.2 (2.25e4.56)
<0.0001
Spinal stenosis in cervical region
2.37 (1.65e3.41)
<0.0001
Intervertebral disc disorder with myelopathy
3.04 (2.02e4.58)
<0.0001
Brachial neuritis or radiculitis not otherwise specified
0.43 (0.17e1.13)
0.004
History of stroke
2.27 (0.72e7.15)
0.16
History of renal failure
2.77 (0.72e7.15)
0.14
Operative time
Severe postdischarge adverse eventy
0.64
Nonhome discharge
1.71 (1.26e2.33)
0.0006
Predischarge severe adverse event
1.91 (1.13e3.21)
0.02
1.002 (1.001e1.003)
0.004
Intervertebral disc disorder with myelopathyx
Operative time
0.82 (0.46e1.47)
0.04
Female sex
1.32 (0.99e1.76)
0.06
ASA status >2
1.35 (0.99e1.83)
0.06
Age
0.99 (0.98e1.004)
0.19
Nonhome discharge
1.45 (1.15e1.82)
0.002
Predischarge severe adverse event
1.59 (1.04e2.43)
0.03
Unplanned readmissionz
0.62
Age Operative time
1.01 (1.002e1.02)
0.02
1.002 (1.001e1.003)
0.003
ASA status >2
1.3 (1.04e1.64)
0.02
Dependent functional status
1.29 (0.91e1.83)
0.16
History of pulmonary disease
1.29 (0.9e1.84)
0.16
ASA status, American Society of Anesthesiologists physical status classification. *Number of patients with any minor adverse event listed. yNumber of patients with superficial wound infection, deep wound infection, organ/space infection, sepsis, or septic shock. zNumber of patients with any severe adverse event listed. xOverall, diagnosis was not a significant predictor of severe adverse event postdischarge (P ¼ 0.08).
some patients are unable to go home immediately after PCDF, the importance of correctly identifying patients in need of facilities discharge and minimizing the number of patients unnecessarily discharged to postacute care (PAC) facilities has become increasingly important. Studies by Bozic et al.7 indicate that >20% of total
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episode-of-care payments stem from the use of PAC facilities, and outcomes are poor, with >17% of all patients discharged to PAC facility being readmitted within 30 days.15 The goal of this study was to use nationally representative data to identify factors predictive of nonhome discharge after PCDF and to compare unplanned
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ORIGINAL ARTICLE DANIEL J. SNYDER ET AL.
readmission rates and severe postdischarge adverse event rates between patients with home and nonhome discharges. In procedures in which mandatory bundled payment models have already been implemented, tools for predicting discharge location (e.g., the Predicting Location after Arthroplasty Nomogram; C statistic 0.87) are being used to risk-stratify patients preoperatively, enabling care teams to start planning a patient’s discharge even before the operation begins.16,17 This process has been shown to help optimize hospital resources and improve postoperative outcome.18,19 Our analyses identified the patient characteristics of older age, prolonged operative time, female sex, ASA status >2, dependent functional status, and history of diabetes as predictive factors for nonhome discharge (Table 3). These results are supported by a study in patients with ACDF by Di Capua et al.,12 which found that that age, ASA status >2, dependent functional status, diabetes, and prolonged operative time significantly increased the likelihood of discharge to a PAC facility. These results also add to the literature in posterior cervical fusion, which shows that wound complication, pulmonary complication, cardiac complication, venous thromboembolism, UTI, transfusion, and sepsis contribute to an increased risk for nonhome discharge.20 Aside from principal diagnosis, dependent functional status was the strongest predictor of nonhome discharge for the patients with PCDF in this study, a result also discovered for patients undergoing ACDF and total joint arthroplasty.8,12 Future research is needed to validate the predictive model developed in our study using external patient populations. The importance of developing and validating a predictive tool for use after cervical fusion cannot be understated; results in the literature suggest that early identification and preparation of discharge placement has a strong potential to reduce patient’s LOS by avoiding delays associated with nonhome discharge and frequent lack of open beds in rehabilitation centers.12,21 This situation can have a substantial impact on costs, because each day of hospitalization has been shown to cost a minimum of $1000.22,23 Of the predictive factors identified in this study, diabetes is the only risk factor for nonhome discharge identified that has the potential to be modified before surgery.12 Despite the well-known effectiveness of diabetic medications, the chronic and insidious nature of this disease makes it challenging for patients to understand the benefits of properly managing this disease and prioritize taking medication on a day-to-day basis. As a result, several studies suggest that medication adherence is lower than expected, with a study by the World Health Organization citing that almost 50% of patients with chronic conditions such as diabetes fail to take their medications as prescribed.24,25 Although a causal relationship between diabetic management and nonhome discharge cannot be identified with the data used in this study, considering the high rates of noncompliance with diabetic medications, it is an important opportunity to remind readers to ensure that diabetes medications are optimized and compliance is achieved before surgery. Patient-centered models such as the perioperative surgical home have been put forth to address this issue,26 ensuring that medications are optimized and care is coordinated throughout the entire surgical experience. Future research should work to establish a causal relationship between diabetes and nonhome
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PCDF: DISCHARGE PLACEMENT AND OUTCOMES
discharge and determine whether strict glucose treatment preoperatively reduces a patient’s risk for facilities discharge. To fully assess the value of discharge to a PAC facility, outcomes for patients discharged to PAC facilities must be evaluated against those who are discharged home. In the arthroplasty literature, patients discharged to an SNF or IRF have been shown to have higher proportions of severe adverse events after discharge and unplanned readmissions.8 In a recent article by Ye et al.,20 patients with nonhome discharge were found to have significantly high rates of pulmonary complications, cardiac complications, venous thromboembolism, UTI, and sepsis. Results of this study found similar results, showing that patients with PCDF discharged to a PAC facility had a significantly higher proportion of both minor (5% vs. 2.2%; P < 0.001) and severe adverse events (6.2% vs. 3.3%; P < 0.001), as well as unplanned readmissions (10% vs. 6%; P < 0.001). The complexity of the patient population discharged to PAC facilities is often referenced as the reason for differences in outcomes.8,9,27 However, it is unlikely that this is the sole factor driving this discrepancy. Publicly reported readmission rates for SNFs reach up to 27%, almost 4 times the national average reported after posterior cervical fusion, and emergency department visit rates reach up to 14%.10,28 When adverse events occurring at SNFs were investigated by the Office of the Inspector General, most events were deemed preventable by physician reviewers.29 This finding is supported by our analysis of a nationally representative sample that found nonhome discharge to be a significant predictor of severe adverse events after discharge and unplanned readmission in regression analyses even after correcting for differences in patient populations (Table 3). Although some patients may be unable to return directly home after PCDF, these findings suggest that for those who are able, home discharge may be an effective method to reduce costs while simultaneously avoiding the negative outcomes associated with SNF discharge. This study was subject to several limitations. First, the retrospective nature of this study allows us to identify only associative rather than causal relationships between nonhome discharge and postdischarge outcomes. Regarding the data source, NSQIP collects only adverse events and readmissions occurring up to 30 days after discharge. A study by Burke et al.15 indicated that 20% of readmissions occurred more than 30 days after discharge, suggesting that the numbers reported in this study may be underestimations. This theory is compounded by the fact that NSQIP contains data only on readmissions and complications occurring within the index hospital or hospital system. Because bundles include 90-day options, accurate estimation of complication and readmission rates after the 30-day interval is key if this model is going to be viable for spinal fusion. In addition, cases were pulled from the NSQIP database using CPT code; although this strategy reliably identifies procedures, it does not specify procedural technique or surgeon factors such as volume or years of experience, which have the potential to affect outcomes. The NSQIP database is mostly made up of patients from large academic medical centers, which may decrease the generalizability of these results for patients treated at nonacademic medical centers or smaller community hospitals.30
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CONCLUSIONS This study identified multiple factors that can help care teams identify patients who have a high likelihood of nonhome discharge after PCDF. Although most of these factors were nonmodifiable, diabetes was identified as a modifiable risk factor that can be actively addressed preoperatively to help minimize a patient’s likelihood of nonhome discharge. This study also found
REFERENCES 1. Kuhns CA, Geck MJ, Wang JC, Delamarter RB. An outcomes analysis of the treatment of cervical pseudarthrosis with posterior fusion. Spine (Phila Pa 1976). 2005;30:2424-2429. 2. Marquez-Lara A, Nandyala SV, Fineberg SJ, Singh K. Current trends in demographics, practice, and in-hospital outcomes in cervical spine surgery. Spine (Phila Pa 1976). 2014;39:476-481. 3. Mok J, Martinez M, Smith HE, et al. Impact of a bundled payment system on resource utilization during spine surgery. Int J Spine Surg. 2016;10:19. 4. Bundled Payments for Care Improvement (BPCI) Initiative: General Information. Available at: http://innovation.cms.gov/initiatives/bundledpayments/, Accessed 11 June, 2018. 5. Ugiliweneza B, Kong M, Nosova K, et al. Spinal surgery: variations in health care costs and implications for episode-based bundled payments. Spine (Phila Pa 1976). 2014;39:1235-1242. 6. Sibia US, Mandelblatt AE, Callanan MA, MacDonald JH, King PJ. Incidence, risk factors, and costs for hospital returns after total joint arthroplasties. J Arthroplasty. 2017;32:381-385. 7. Bozic KJ, Ward L, Vail TP, Maze M. Bundled payments in total joint arthroplasty: targeting opportunities for quality improvement and cost reduction knee. Clin Orthop Relat Res. 2014;472: 188-193. 8. Keswani A, Tasi MC, Fields A, Lovy AJ, Moucha CS, Bozic KJ. Discharge destination after total joint arthroplasty: an analysis of postdischarge outcomes, placement risk factors, and recent trends. J Arthroplasty. 2016;31:1155-1162. 9. Bini SA, Fithian DC, Paxton LW, Khatod MX, Inacio MC, Namba RS. Does discharge disposition after primary total joint arthroplasty affect readmission rates? J Arthroplasty. 2010;25:114-117.
that patients discharged to a PAC facility had a higher likelihood of having a severe adverse event after discharge and being readmitted. Because the use of PAC facilities accounts for a large percentage of episode-of-care payments7 and is associated with poor outcomes, minimizing unnecessary PAC facility discharge is a key step in optimizing cost and outcomes for patients undergoing PCDF.
reoperations in posterior cervical fusion. Spine (Phila Pa 1976). 2016;41:1477-1483.
posterior lumbar spine surgery: a multivariate analysis. Spine J. 2015;15:1188-1195.
12. Di Capua J, Somani S, Kim JS, et al. Predictors for patient discharge destination after elective anterior cervical discectomy and fusion. Spine (Phila Pa 1976). 2017;42:1538-1544.
23. Aldebeyan S, Aoude A, Fortin M, et al. Predictors of discharge destination after lumbar spine fusion surgery. Spine (Phila Pa 1976). 2016;41:1535-1541.
13. American College of Surgeons National Surgical Quality Improvement Program. Participants 2016. Available at: https://www.facs.org/ quality-programs/acs-nsqip/program-specifics/ participant-use, Accessed 18 June, 2018. 14. Schoenfeld AJ, Carey PA, Cleveland AW, Bader JO, Bono CM. Patient factors, comorbidities, and surgical characteristics that increase mortality and complication risk after spinal arthrodesis: a prognostic study based on 5,887 patients. Spine J. 2013;13:1171-1179. 15. Burke RE, Whitfield EA, Hittle D, et al. Hospital readmission from post-acute care facilities: risk factors, timing, and outcomes. J Am Med Dir Assoc. 2016;17:249-255. 16. Oldmeadow LB, McBurney H, Robertson VJ. Predicting risk of extended inpatient rehabilitation after hip or knee arthroplasty. J Arthroplasty. 2003; 18:775-779. 17. Barsoum WK, Murray TG, Klika AK, et al. Predicting patient discharge disposition after total joint arthroplasty in the United States. J Arthroplasty. 2010;25:885-892. 18. Shepperd S, Doll H, Broad J, et al. Hospital at home early discharge. Cochrane Database Syst Rev. 2009;1:CD000356. 19. Shepperd S, Lannin NA, Clemson LM, McCluskey A, Cameron ID, Barras SL. Discharge planning from hospital to home. Cochrane Database Syst Rev. 2013;1:CD000313. 20. Ye I, Phan K, Cheung ZB, et al. Predictive risk factors of nonhome discharge following elective posterior cervical fusion. World Neurosurg. 2018; 119:e574-e579.
10. Choy W, Lam SK, Smith ZA, Dahdaleh NS. Predictors of 30-day hospital readmission after posterior cervical fusion in 3401 patients. Spine (Phila Pa 1976). 2018;43:356-363.
21. Brasel KJ, Rasmussen J, Cauley C, Weigelt JA. Reasons for delayed discharge of trauma patients. J Surg Res. 2002;107:223-226.
11. Medvedev G, Wang C, Cyriac M, Amdur R, O’Brien J. Complications, readmissions, and
22. Gruskay JA, Fu M, Bohl DD, Webb ML, Grauer JN. Factors affecting length of stay after elective
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24. Brown MT, Bussell JK. Medication adherence: WHO cares? Mayo Clin Proc. 2011;86:304-314. 25. Cramer JA, Benedict A, Muszbek N, Keskinaslan A, Khan ZM. The significance of compliance and persistence in the treatment of diabetes, hypertension and dyslipidaemia: a review. Int J Clin Pract. 2008;62:76-87. 26. Raphael DR, Cannesson M, Schwarzkopf R, et al. Total joint Perioperative Surgical Home: an observational financial review. Perioper Med (London, England). 2014;3:6. 27. Bozic KJ, Wagie A, Naessens JM, Berry DJ, Rubash HE. Predictors of discharge to an inpatient extended care facility after total hip or knee arthroplasty. J Arthroplasty. 2006;21(6 suppl): 151-156. 28. Medicare. Find and compare Nursing Homes j Nursing Home Compare. Available at: https:// www.medicare.gov/nursinghomecompare/search. html?. Accessed October 12, 2018. 29. Adverse Events in Skilled Nursing Facilities: National Incidence among Medicare Beneficiaries. 2014. Available at: https://oig.hhs.gov/oei/reports/oei-06-11-00370.pdf. Accessed 13 June 2018. 30. Yi F. The future of quality measurement in the United States. Clin Colon Rectal Surg. 2014;27:32-38.
Conflict of interest statement: J.M.C. discloses his consulting relationship with Zimmer Biomet. All other authors declare that no conflicts of interest exist. Received 13 October 2018; accepted 22 January 2019 Citation: World Neurosurg. (2019). https://doi.org/10.1016/j.wneu.2019.01.214 Journal homepage: www.journals.elsevier.com/worldneurosurgery Available online: www.sciencedirect.com 1878-8750/$ - see front matter ª 2019 Elsevier Inc. All rights reserved.
WORLD NEUROSURGERY, https://doi.org/10.1016/j.wneu.2019.01.214
Posterior Cervical Decompression and Fusion: Assessing Risk Factors for Nonhome Discharge and the Impact of Disposition on Postdischarge Outcomes Daniel J. Snyder1, Sean N. Neifert1, Jonathan S. Gal2, Brian C. Deutsch1, John M. Caridi3,4
-
BACKGROUND: The purpose of this study was to identify predictors for postacute care facility discharge for patients undergoing posterior cervical decompression and fusion (PCDF) and to determine if discharge placement impacts postdischarge outcomes.
1.14e1.5; P [ 0.0002). Patients with PCDF with nonhome discharges had an increased likelihood of having a severe postdischarge AE (OR, 1.71; 95% CI, 1.26e2.33; P [ 0.0006) and an unplanned readmission (OR, 1.45; 95% CI, 1.15e1.82; P [ 0.002).
METHODS: Patients undergoing PCDF from 2012 to 2015 were queried from the NSQIP database (n [ 8743) and separated by discharge placement. Outcomes included nonhome discharge, unplanned 30-day readmission, and adverse events (AEs), both before and after discharge. Demographics and comorbidities were analyzed using bivariate analysis. Multivariate logistic regression was used to identify predictors for nonhome discharge, readmission, and severe AE after discharge.
-
-
RESULTS: Patients with nonhome discharges were significantly older (67.4 vs. 58.6 years; P < 0.001), sicker (82% vs. 54% American Society of Anesthesiologists >2; P < 0.001), and more functionally dependent (16% vs. 3.4%; P < 0.001), with a greater comorbidity burden. Patients with PCDF had an increased likelihood of nonhome discharge if they had a dependent functional status (odds ratio [OR], 2.99; 95% confidence interval [CI], 2.33e3.82; P < 0.001), diabetes (OR, 1.32; 95% CI, 1.13e1.55; P [ 0.0007), and an American Society of Anesthesiologists >2 (OR, 1.75; 95% CI, 1.5e2.05; P < 0.001), as well as if they were older (OR, 1.06; 95% CI, 1.05e1.06; P < 0.001) and female (OR, 1.31; 95% CI,
osterior cervical decompression and fusion (PCDF) is an effective surgical intervention used to treat a variety of cervical spine disorders.1 The age and medical complexity of the surgical population eligible for this procedure has increased in recent years, leading to an exponential increase in the number of cervical fusion procedures performed per year.2 Costs associated with this procedure have also increased; spinal fusion procedures such as PCDF have amounted to almost $290 billion dollars in total expenditure between 2000 and 2010, with almost 4 million surgical procedures in the United States alone.3 In response to concurrent increases in cost and volume, cervical fusion procedures such as PCDF have been identified as a possible target for bundled payments by the Centers for Medicare and
Key words Bundled payments - Episode-based outcomes - Nonhome discharge - Outcomes - SNF - Unplanned readmission
PCDF: Posterior cervical decompression and fusion SNF: Skilled nursing facility UTI: Urinary tract infection
-
-
Abbreviations and Acronyms ACDF: Anterior cervical discectomy and fusion ASA: American Society of Anesthesiologists CPT: Current Procedural Terminology DVT: Deep vein thrombosis IRF: Inpatient rehabilitation facility LOS: Length of stay NSQIP: National Surgical Quality Improvement Program PAC: Postacute care
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CONCLUSIONS: Results of this cross-sectional study suggest that patients with PCDF discharged to a postacute care facility have a higher likelihood of having a severe AE after discharge as well as a higher likelihood of being readmitted.
INTRODUCTION
P
From the 1Department of Medical Education, Icahn School of Medicine at Mount Sinai, New York, New York; and Departments of 2Anesthesiology, Perioperative and Pain Medicine, 3 Neurosurgery, and 4Orthopedics, Mount Sinai Hospital, New York, New York, USA To whom correspondence should be addressed: Daniel J. Snyder, B.S. [E-mail: [email protected]] Citation: World Neurosurg. (2019). https://doi.org/10.1016/j.wneu.2019.01.214 Journal homepage: www.journals.elsevier.com/world-neurosurgery Available online: www.sciencedirect.com 1878-8750/$ - see front matter ª 2019 Elsevier Inc. All rights reserved.
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PCDF: DISCHARGE PLACEMENT AND OUTCOMES
Medicaid Services.4 The bundled payment structure, a fixed payment per episode of care, is intended to shift the focus of care from service quantity to care quality, with the goal of simultaneously improving outcomes and decreasing costs.5 Although the primary areas targeted for cost reduction and care improvement include decreasing length of stay (LOS) and mitigating unplanned readmissions and emergency room visits,6 studies of total joint arthroplasty have indicated that discharge destination can also affect the cost per episode of care, not only directly7 but also through increased adverse events after discharge and unplanned readmissions.8,9 Risk factors for increased LOS and unplanned readmission in posterior cervical fusion have been examined in the literature,10,11 and predictors for discharge destination have been examined for anterior cervical discectomy and fusion (ACDF).12 Determining the factors predisposing patients with PCDF to nonhome discharge and elucidating the implications of nonhome discharge in this patient population are a critical step toward making the bundled payment model viable for PCDF. This study aims to characterize patients with PCDF by discharge disposition using American College of Surgeons National Surgical Quality Improvement Program (NSQIP) data from 2012 to 2015. Rates of predischarge and postdischarge adverse events are compared between patients with home and nonhome discharges. Predictors of nonhome discharge, the occurrence of a severe postdischarge adverse event, and unplanned readmission are also evaluated. METHODS The NSQIP Database After institutional review board approval, all patients undergoing PCDF between 2012 and 2015 were queried from the American College of Surgeons NSQIP database. The NSQIP database prospectively collects data from more than 350 institutions13 and contains information such as patient factors, comorbidities, and postoperative outcomes up to 30 days from discharge. The validity and reproducibility of this database have been shown in the literature.14 Defining the Cohort To establish the cohort, PCDF cases were preliminarily identified using Current Procedural Terminology (CPT) codes 63045, 63001, 63015, 22110, 22210, and 22600. Patients who underwent anterior cervical fusion during the same hospital stay (i.e., a fronteback) were then excluded using the CPT codes 63075, 22554, and 22551. Variables Collected Demographic variables collected included age, gender, and race. Patient factors collected included principal postoperative diagnosis, body mass index, American Society of Anesthesiologists (ASA) physical status classification, functional status, and history of smoking. Comorbidities collected included history of diabetes, pulmonary disease, cardiac disease, hypertension requiring medication, renal failure, stroke, steroid requirement, and bleeding disorder. Perioperative variables collected included operative time and total LOS. Readmissions within 30 days were also collected.
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Both minor and severe adverse events were queried from the NSQIP database. Minor adverse events included urinary tract infection (UTI), pneumonia, and superficial surgical site infection. Severe adverse events included deep wound infection, organ/space infection, wound dehiscence, reintubation, deep vein thrombosis (DVT), pulmonary embolism, weaning failure, renal insufficiency, renal failure, cerebrovascular accident, cardiac arrest, myocardial infarction, sepsis, septic shock, reoperation, and death. Events were further separated based on if they occurred before discharge or after discharge. Discharge destination was also collected. Statistical Analysis All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, North Carolina, USA). A 2-tailed P value of 0.05 was considered to be significant. Demographic data, principal diagnoses, comorbidities, operative time, predischarge adverse events, postdischarge adverse events, infections, and unplanned readmissions were compared between 4 cohorts: patients discharged home, patients discharged to a skilled nursing facility (SNF), patients discharged to an inpatient rehabilitation facility (IRF), and patients discharged to either an SNF or an IRF (i.e., nonhome discharge). This strategy yielded 4 comparisons: home discharge versus SNF, home discharge versus IRF, SNF versus IRF, and home discharge versus nonhome discharge. Continuous variables were analyzed using Student t tests, whereas categorical variables were compared using c2 or Fisher exact tests, depending on the complication frequency. Stepwise multivariate logistic regression using backward elimination with an inclusion P value of 0.2 was used to identify risk factors for nonhome discharge, unplanned 30-day readmission, and the occurrence of a severe adverse event after discharge. Patient-level factors (e.g., age, principal diagnosis, and comorbidities) were included in the regression models if they were significant predictors of the outcome of interest (i.e., unplanned readmission and severe adverse event after discharge) to help determine if nonhome discharge was a predictor of these outcomes after correcting for differences in patient population. Cervical spondylolysis without myelopathy was set as the reference principal diagnosis in the models. RESULTS A total of 8743 patients underwent PCDF between 2012 and 2015. Discharge destinations were distributed as follows: 73% home, 12% to a SNF, and 15% to an IRF. Patients with nonhome discharges were older on average, with a higher likelihood of having a dependent functional status and an ASA designation >2 (Table 1). Patients with nonhome discharges also had higher rates of the following comorbidities: diabetes, pulmonary disease, cardiac disease, hypertension requiring medication, stroke, steroids, and bleeding disorder. Operative time was significantly higher for patients with nonhome discharges. Principal diagnoses also varied significantly by discharge destination; more patients discharged to a SNF or IRF had myelopathy accompanying either cervical spondylolysis or an intervertebral disc disorder. When predischarge adverse events were compared by discharge destination, patients with nonhome discharges had a significantly higher proportion of severe adverse events (11% vs. 2.1%;
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ORIGINAL ARTICLE DANIEL J. SNYDER ET AL.
PCDF: DISCHARGE PLACEMENT AND OUTCOMES
Table 1. Patient Demographics by Discharge Disposition for Patients Undergoing Posterior Cervical Decompression and Fusion Home (n [ 6407)
SNF IRF Nonhome Home versus (n [ 1023) (n [ 1313) (n [ 2336) SNF (P Value)
Age (years), mean (standard deviation)
58.6 (12.3)
69.2 (11.9)
66 (12.5)
67.4 (12.3)
Sex (male)
3829 (60)
539 (53)
813 (62)
1352 (58)
Race White
4966 (78)
771 (75)
896 (68)
1667 (71)
African American
694 (11)
172 (17)
251 (19)
423 (18)
Asian
140 (2.2)
26 (2.5)
32 (2.4)
58 (2.5)
<0.0001
Home versus IRF (P Value) <0.0001
Home versus Nonhome SNF versus (P Value) IRF (P Value) <0.0001
<0.0001
<0.0001
0.15
0.11
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
Other
87 (1.4)
12 (1.2)
8 (0.6)
20 (0.9)
Unknown
520 (8.1)
42 (4.1)
126 (9.6)
168 (7.2)
386 (6)
56 (5.5)
93 (7.1)
149 (6.4)
0.49
0.15
0.54
0.11
American Society of Anesthesiology physical status classification >2
3469 (54)
859 (84)
1064 (81)
1923 (82)
<0.0001
<0.0001
<0.0001
0.07
History of smoking
1680 (26)
202 (20)
295 (22)
497 (21)
<0.0001
0.005
<0.0001
0.11
Dependent functional status
216 (3.4)
182 (18)
187 (14)
369 (16)
<0.0001
<0.0001
<0.0001
0.02
Body mass index >40 kg/m2
Comorbidities History of diabetes
1029 (16)
267 (26)
327 (25)
594 (25.4)
<0.0001
<0.0001
<0.0001
0.51
History of pulmonary disease
332 (5.2)
102 (10)
99 (7.5)
201 (8.6)
<0.0001
0.0007
<0.0001
0.04
36 (0.6)
33 (3.2)
23 (1.8)
56 (2.4)
<0.0001
<0.0001
<0.0001
0.02
3262 (51)
718 (70)
860 (66)
1578 (68)
<0.0001
<0.0001
<0.0001
0.02
History of renal failure
7 (0.1)
6 (0.6)
3 (0.2)
9 (0.4)
0.005
0.39
0.02
0.19
History of stroke
10 (0.2)
5 (0.5)
8 (0.6)
13 (0.6)
0.04
0.006
0.001
0.7
History of cardiac disease History of hypertension requiring medication
History of steroids
281 (4.4)
74 (7.2)
100 (7.6)
174 (7.5)
<0.0001
<0.0001
<0.0001
0.73
History of bleeding disorder
109 (1.7)
60 (5.9)
47 (3.6)
107 (4.6)
<0.0001
<0.0001
<0.0001
0.009
158 (92)
193 (104)
197 (109)
195 (107)
<0.0001
<0.0001
<0.0001
0.32
<0.0001
<0.0001
<0.0001
0.13
Operative time (minutes), mean (standard deviation) Principal postoperative diagnosis Cervical spondylolysis with myelopathy
1770 (37)
391 (59)
496 (57)
887 (58)
Spinal stenosis in cervical region
1383 (29)
170 (26)
232 (26)
402 (26)
Cervical spondylolysis without myelopathy
472 (9.8)
27 (4.0)
17 (1.9)
44 (2.9)
Intervertebral disc disorder with myelopathy
324 (6.8)
55 (8.3)
92 (11)
147 (9.5)
Other mechanical complication
273 (5.7)
14 (2.1)
17 (1.9)
31 (2.0)
Brachial neuritis or radiculitis not otherwise specified
241 (5.0)
2 (0.3)
4 (0.5)
6 (0.4)
Displacement cervical intervertebral disc without myelopathy
210 (4.4)
2 (0.3)
7 (0.8)
9 (0.6)
Degeneration of cervical intervertebral disc
128 (2.7)
5 (0.8)
11 (1.3)
16 (1.0)
Values are number (%) except where indicated otherwise. SNF, skilled nursing facility; IRF, inpatient rehabilitation facility.
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PCDF: DISCHARGE PLACEMENT AND OUTCOMES
Table 2. Predischarge and Postdischarge Adverse Events by Discharge Disposition for Patients Undergoing Posterior Cervical Decompression and Fusion Home versus Nonhome SNF versus IRF (P Value) (P Value)
Home (n [ 6407)
SNF (n [ 1023)
IRF (n [ 1313)
Nonhome (n [ 2336)
Home versus SNF (P Value)
Home versus IRF (P Value)
50 (0.8)
68 (6.7)
67 (5.1)
135 (5.8)
<0.0001
<0.0001
<0.0001
0.11
Urinary tract infection
22 (0.3)
30 (2.9)
27 (2.1)
57 (2.4)
<0.0001
<0.0001
<0.0001
0.17
Pneumonia
21 (0.3)
36 (3.5)
41 (3.1)
77 (3.3)
<0.0001
<0.0001
<0.0001
0.59
Superficial infection
7 (0.1)
3 (0.3)
3 (0.2)
6 (0.3)
0.15
0.39
0.11
1
Infectiony
28 (0.4)
43 (4.2)
35 (2.7)
78 (3.3)
<0.0001
<0.0001
<0.0001
0.04
Severe adverse eventz
Predischarge Minor adverse event*
134 (2.1)
125 (12)
132 (10)
257 (11)
<0.0001
<0.0001
<0.0001
0.1
Deep wound infection
6 (0.1)
7 (0.7)
4 (0.3)
11 (0.5)
0.0007
0.07
0.0004
0.23
Organ/space infection
3 (0.1)
4 (0.4)
5 (0.4)
9 (0.4)
0.009
0.005
0.0007
1
Would dehiscence
4 (0.1)
2 (0.2)
1 (0.1)
3 (0.1)
0.19
1
0.39
0.58
Reintubation
19 (0.3)
20 (2)
30 (2.3)
50 (2.1)
<0.0001
<0.0001
<0.0001
0.58
Deep vein thrombosis
11 (0.2)
18 (1.8)
21 (1.6)
39 (1.7)
<0.0001
<0.0001
<0.0001
0.76
Pulmonary embolism
10 (0.2)
7 (0.7)
10 (0.8)
17 (0.7)
0.001
<0.0001
<0.0001
0.83
Weaning failure
18 (0.3)
45 (4.4)
36 (2.7)
81 (3.5)
<0.0001
<0.0001
<0.0001
0.03
Renal insufficiency
1 (<0.1)
1 (0.1)
1 (0.1)
2 (0.1)
0.26
0.31
0.18
1
Renal failure
2 (<0.1)
5 (0.5)
0 (0.0)
5 (0.2)
0.0008
1
0.02
0.02
Cerebrovascular accident
5 (0.1)
4 (0.4)
5 (0.4)
9 (0.4)
0.03
0.006
0.002
1
Cardiac arrest
3 (0.1)
8 (0.8)
7 (0.5)
15 (0.6)
<0.0001
0.0003
<0.0001
0.46
Myocardial infarction
7 (0.1)
10 (1)
6 (0.5)
16 (0.7)
<0.0001
0.005
<0.0001
0.13
Sepsis
10 (0.2)
22 (2.2)
20 (1.5)
42 (1.8)
<0.0001
<0.0001
<0.0001
0.26
Septic shock
3 (0.1)
12 (1.2)
8 (0.6)
20 (0.9)
<0.0001
<0.0001
<0.0001
0.14
Reoperation
72 (1.1)
50 (4.9)
58 (4.4)
108 (4.6)
<0.0001
<0.0001
<0.0001
0.59
Death
0 (0.0)
2 (0.2)
0 (0.0)
2 (0.1)
0.02
1
0.07
0.19
3.4 (5.4)
8.5 (8.4)
8.4 (8.3)
8.5 (8.3)
<0.0001
<0.0001
<0.0001
0.74
Total length of stay (days), mean (standard deviation) Postdischarge Minor adverse event* Urinary tract infection
138 (2.2)
37 (3.6)
79 (6)
116 (5)
0.004
<0.0001
<0.0001
0.008
51 (0.8)
22 (2.2)
53 (4)
75 (3.2)
<0.0001
<0.0001
<0.0001
0.01
Pneumonia
16 (0.3)
13 (1.3)
11 (0.8)
24 (1)
<0.0001
0.001
<0.0001
0.3
Superficial infection
73 (1.1)
5 (0.5)
19 (1.5)
24 (1)
0.06
0.35
0.66
0.02
Infectiony
153 (2.4)
28 (2.7)
41 (3.1)
69 (3)
0.51
0.12
0.14
0.59
Severe adverse eventz
214 (3.3)
72 (7)
72 (5.5)
144 (6.2)
<0.0001
0.0002
<0.0001
0.12
Deep wound infection
58 (0.9)
6 (0.6)
10 (0.8)
16 (0.7)
0.31
0.62
0.32
0.61
Organ/space infection
12 (0.2)
6 (0.6)
4 (0.3)
10 (0.4)
0.02
0.33
0.05
0.35
Would dehiscence
30 (0.5)
10 (1)
7 (0.5)
17 (0.7)
0.04
0.76
0.14
0.21
Reintubation
9 (0.1)
3 (0.3)
4 (0.3)
7 (0.3)
0.22
0.26
0.12
1
Deep vein thrombosis
17 (0.3)
6 (0.6)
16 (1.2)
22 (0.9)
0.09
<0.0001
<0.0001
0.12
Pulmonary embolism
13 (0.2)
7 (0.7)
8 (0.6)
15 (0.6)
0.006
0.01
0.001
0.82 Continues
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ORIGINAL ARTICLE DANIEL J. SNYDER ET AL.
PCDF: DISCHARGE PLACEMENT AND OUTCOMES
Table 2. Continued
Weaning failure Renal insufficiency
Home versus Nonhome SNF versus IRF (P Value) (P Value)
Home (n [ 6407)
SNF (n [ 1023)
IRF (n [ 1313)
Nonhome (n [ 2336)
Home versus SNF (P Value)
Home versus IRF (P Value)
4 (0.1)
5 (0.5)
1 (0.1)
6 (0.3)
0.004
1
0.03
0.09
1 (<0.1)
4 (0.4)
1 (0.1)
5 (0.2)
0.002
0.31
0.006
0.18
Renal failure
0 (0.0)
0 (0.0)
0 (0.0)
0 (0.0)
—
—
—
—
Cerebrovascular accident
7 (0.1)
2 (0.2)
0 (0.0)
2 (0.1)
0.36
0.61
1
0.19
2 (<0.1)
4 (0.4)
3 (0.2)
7 (0.3)
0.004
0.04
0.002
0.71
Cardiac arrest Myocardial infarction
3 (0.1)
6 (0.6)
0 (0.0)
6 (0.3)
0.0004
1
0.01
0.007
Sepsis
24 (0.4)
15 (1.5)
8 (0.6)
23 (1)
<0.0001
0.23
0.0006
0.04
Septic shock
3 (0.1)
1 (0.1)
4 (0.3)
5 (0.2)
0.45
0.02
0.04
0.39
Reoperation
135 (2.1)
26 (2.5)
34 (2.6)
60 (2.6)
0.38
0.28
0.2
0.94
Death
16 (0.3)
17 (1.7)
10 (0.8)
27 (1.2)
<0.0001
0.004
<0.0001
0.04
Readmission
381 (6)
116 (11)
122 (9.3)
238 (10)
<0.0001
<0.0001
<0.0001
0.1
Values are number (%) except where indicated otherwise. SNF, skilled nursing facility; IRF, inpatient rehabilitation facility. *Number of patients with any minor adverse event listed. yNumber of patients with superficial wound infection, deep wound infection, organ/space infection, sepsis, or septic shock. zNumber of patients with any severe adverse event listed.
P < 0.001) (Table 2). When severe adverse events were examined individually, substantial discrepancies were seen between rates of reintubation (2.1% vs. 0.3%), DVT (1.7% vs. 0.2%), weaning failure (3.5% vs. 0.3%), sepsis (1.8% vs. 0.2%), and reoperation (4.6% vs. 1.1%) between patients with nonhome and home discharges (all P < 0.001). Patients with nonhome discharges also had a significantly higher proportion of minor adverse events (5.8% vs. 0.8%), mainly being driven by higher rates of UTI (2.4% vs. 0.3%) and pneumonia (3.3% vs. 0.3%) (all P < 0.001). Overall rates of infection were higher for patients with nonhome discharges (3.3% vs. 0.4%; P < 0.001), and total LOS was significantly higher on average for patients with nonhome discharges (8.5 vs. 3.4 days; P < 0.001). With the exception of renal failure (0.5% vs. 0%; P ¼ 0.02), weaning failure (4.4% vs. 2.7%; P ¼ 0.03), and overall rates of infection (4.2% vs. 2.7%; P ¼ 0.04), predischarge adverse events did not differ significantly between those discharged to an SNF versus those discharged to an IRF. When postdischarge adverse events were compared by discharge destination, patients with nonhome discharges also had a significantly higher proportion of severe adverse events (6.2% vs. 3.3%; P < 0.001) (Table 2). This finding was mainly driven by higher rates of DVT (0.9% vs. 0.3%; P < 0.001), pulmonary embolism (0.6% vs. 0.2%; P ¼ 0.001), renal insufficiency (0.2% vs. <0.1%), cardiac arrest (0.3% vs. <0.1%), myocardial infarction (0.3% vs. 0.1%), and sepsis (1% vs. 0.4%) (all P < 0.01); mortality was significantly higher in patients with nonhome discharges (1.2% vs. 0.3%; P < 0.001), with 1.7% of patients discharged to an SNF dying after discharge. Patients with nonhome discharges also experienced a greater proportion of minor adverse events postdischarge (5% vs. 2.2%), again
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driven mainly by increased rates of UTI (3.2% vs. 0.8%) and pneumonia (1% vs. 0.3%) (all P < 0.001). Patients with nonhome discharges also had significantly more readmissions (10% vs. 6%; P < 0.001). When adverse event rates were compared between SNFs and IRFs, patients discharged to a SNF had higher rates of sepsis (1.5% vs. 0.6%; P ¼ 0.04) and death (1.7% vs. 0.8%; P ¼ 0.04), whereas patients discharged to an IRF had higher rates of UTI (4% vs. 2.2%; P ¼ 0.01). On multivariate analysis, having a dependent functional status (OR, 2.99), an ASA designation >2 (OR, 1.75), and a diagnosis of spinal stenosis (OR, 2.37), cervical spondylolysis with myelopathy (OR, 3.2), or intervertebral disc disorder with myelopathy (OR, 3.04) were the strongest predictors of nonhome discharge (all P < 0.001) (Table 3). Female sex (OR, 1.31; P ¼ 0.0002) and a history of diabetes (OR, 1.32; P ¼ 0.0007) were also associated with an increased likelihood of nonhome discharge. Other significant predictors of nonhome discharge included age, operative time, and total LOS (all OR, <1.2; P < 0.001). In a multivariate model correcting for patient-level factors, the strongest predictors of having a severe adverse event after discharge were having a nonhome discharge (OR, 1.71; P ¼ 0.0006) and a severe adverse event before discharge (OR, 1.91; P ¼ 0.02) (Table 3). Similarly, nonhome discharge (OR, 1.45; P ¼ 0.002) and having a severe adverse event before discharge (OR, 1.59; P ¼ 0.03) were significant predictors for unplanned readmission, along with having an ASA designation >2 (OR, 1.3; P ¼ 0.02). DISCUSSION With the implementation of bundled payments, properly riskstratifying patients for nonhome discharge is critical. Although
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PCDF: DISCHARGE PLACEMENT AND OUTCOMES
Table 3. Predictors for Nonhome Discharge, Severe Postdischarge Adverse Events, and Unplanned Readmission for Patients Undergoing Posterior Cervical Decompression and Fusion Outcome/Predictors
Odds Ratio (95% Confidence Interval)
P Value
Nonhome discharge*
C Statistic 0.84
2.99 (2.33e3.82)
<0.0001
ASA status >2
1.75 (1.5e2.05)
<0.0001
Age
1.06 (1.05e1.06)
<0.0001
Dependent functional status
1.002 (1.002e1.003)
<0.0001
Female sex
1.31 (1.14e1.5)
0.0002
History of diabetes
1.32 (1.13e1.55)
0.0007
Total length of stay
1.19 (1.16e1.21)
<0.0001
Cervical spondylolysis with myelopathy
3.2 (2.25e4.56)
<0.0001
Spinal stenosis in cervical region
2.37 (1.65e3.41)
<0.0001
Intervertebral disc disorder with myelopathy
3.04 (2.02e4.58)
<0.0001
Brachial neuritis or radiculitis not otherwise specified
0.43 (0.17e1.13)
0.004
History of stroke
2.27 (0.72e7.15)
0.16
History of renal failure
2.77 (0.72e7.15)
0.14
Operative time
Severe postdischarge adverse eventy
0.64
Nonhome discharge
1.71 (1.26e2.33)
0.0006
Predischarge severe adverse event
1.91 (1.13e3.21)
0.02
1.002 (1.001e1.003)
0.004
Intervertebral disc disorder with myelopathyx
Operative time
0.82 (0.46e1.47)
0.04
Female sex
1.32 (0.99e1.76)
0.06
ASA status >2
1.35 (0.99e1.83)
0.06
Age
0.99 (0.98e1.004)
0.19
Nonhome discharge
1.45 (1.15e1.82)
0.002
Predischarge severe adverse event
1.59 (1.04e2.43)
0.03
Unplanned readmissionz
0.62
Age Operative time
1.01 (1.002e1.02)
0.02
1.002 (1.001e1.003)
0.003
ASA status >2
1.3 (1.04e1.64)
0.02
Dependent functional status
1.29 (0.91e1.83)
0.16
History of pulmonary disease
1.29 (0.9e1.84)
0.16
ASA status, American Society of Anesthesiologists physical status classification. *Number of patients with any minor adverse event listed. yNumber of patients with superficial wound infection, deep wound infection, organ/space infection, sepsis, or septic shock. zNumber of patients with any severe adverse event listed. xOverall, diagnosis was not a significant predictor of severe adverse event postdischarge (P ¼ 0.08).
some patients are unable to go home immediately after PCDF, the importance of correctly identifying patients in need of facilities discharge and minimizing the number of patients unnecessarily discharged to postacute care (PAC) facilities has become increasingly important. Studies by Bozic et al.7 indicate that >20% of total
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episode-of-care payments stem from the use of PAC facilities, and outcomes are poor, with >17% of all patients discharged to PAC facility being readmitted within 30 days.15 The goal of this study was to use nationally representative data to identify factors predictive of nonhome discharge after PCDF and to compare unplanned
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ORIGINAL ARTICLE DANIEL J. SNYDER ET AL.
readmission rates and severe postdischarge adverse event rates between patients with home and nonhome discharges. In procedures in which mandatory bundled payment models have already been implemented, tools for predicting discharge location (e.g., the Predicting Location after Arthroplasty Nomogram; C statistic 0.87) are being used to risk-stratify patients preoperatively, enabling care teams to start planning a patient’s discharge even before the operation begins.16,17 This process has been shown to help optimize hospital resources and improve postoperative outcome.18,19 Our analyses identified the patient characteristics of older age, prolonged operative time, female sex, ASA status >2, dependent functional status, and history of diabetes as predictive factors for nonhome discharge (Table 3). These results are supported by a study in patients with ACDF by Di Capua et al.,12 which found that that age, ASA status >2, dependent functional status, diabetes, and prolonged operative time significantly increased the likelihood of discharge to a PAC facility. These results also add to the literature in posterior cervical fusion, which shows that wound complication, pulmonary complication, cardiac complication, venous thromboembolism, UTI, transfusion, and sepsis contribute to an increased risk for nonhome discharge.20 Aside from principal diagnosis, dependent functional status was the strongest predictor of nonhome discharge for the patients with PCDF in this study, a result also discovered for patients undergoing ACDF and total joint arthroplasty.8,12 Future research is needed to validate the predictive model developed in our study using external patient populations. The importance of developing and validating a predictive tool for use after cervical fusion cannot be understated; results in the literature suggest that early identification and preparation of discharge placement has a strong potential to reduce patient’s LOS by avoiding delays associated with nonhome discharge and frequent lack of open beds in rehabilitation centers.12,21 This situation can have a substantial impact on costs, because each day of hospitalization has been shown to cost a minimum of $1000.22,23 Of the predictive factors identified in this study, diabetes is the only risk factor for nonhome discharge identified that has the potential to be modified before surgery.12 Despite the well-known effectiveness of diabetic medications, the chronic and insidious nature of this disease makes it challenging for patients to understand the benefits of properly managing this disease and prioritize taking medication on a day-to-day basis. As a result, several studies suggest that medication adherence is lower than expected, with a study by the World Health Organization citing that almost 50% of patients with chronic conditions such as diabetes fail to take their medications as prescribed.24,25 Although a causal relationship between diabetic management and nonhome discharge cannot be identified with the data used in this study, considering the high rates of noncompliance with diabetic medications, it is an important opportunity to remind readers to ensure that diabetes medications are optimized and compliance is achieved before surgery. Patient-centered models such as the perioperative surgical home have been put forth to address this issue,26 ensuring that medications are optimized and care is coordinated throughout the entire surgical experience. Future research should work to establish a causal relationship between diabetes and nonhome
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discharge and determine whether strict glucose treatment preoperatively reduces a patient’s risk for facilities discharge. To fully assess the value of discharge to a PAC facility, outcomes for patients discharged to PAC facilities must be evaluated against those who are discharged home. In the arthroplasty literature, patients discharged to an SNF or IRF have been shown to have higher proportions of severe adverse events after discharge and unplanned readmissions.8 In a recent article by Ye et al.,20 patients with nonhome discharge were found to have significantly high rates of pulmonary complications, cardiac complications, venous thromboembolism, UTI, and sepsis. Results of this study found similar results, showing that patients with PCDF discharged to a PAC facility had a significantly higher proportion of both minor (5% vs. 2.2%; P < 0.001) and severe adverse events (6.2% vs. 3.3%; P < 0.001), as well as unplanned readmissions (10% vs. 6%; P < 0.001). The complexity of the patient population discharged to PAC facilities is often referenced as the reason for differences in outcomes.8,9,27 However, it is unlikely that this is the sole factor driving this discrepancy. Publicly reported readmission rates for SNFs reach up to 27%, almost 4 times the national average reported after posterior cervical fusion, and emergency department visit rates reach up to 14%.10,28 When adverse events occurring at SNFs were investigated by the Office of the Inspector General, most events were deemed preventable by physician reviewers.29 This finding is supported by our analysis of a nationally representative sample that found nonhome discharge to be a significant predictor of severe adverse events after discharge and unplanned readmission in regression analyses even after correcting for differences in patient populations (Table 3). Although some patients may be unable to return directly home after PCDF, these findings suggest that for those who are able, home discharge may be an effective method to reduce costs while simultaneously avoiding the negative outcomes associated with SNF discharge. This study was subject to several limitations. First, the retrospective nature of this study allows us to identify only associative rather than causal relationships between nonhome discharge and postdischarge outcomes. Regarding the data source, NSQIP collects only adverse events and readmissions occurring up to 30 days after discharge. A study by Burke et al.15 indicated that 20% of readmissions occurred more than 30 days after discharge, suggesting that the numbers reported in this study may be underestimations. This theory is compounded by the fact that NSQIP contains data only on readmissions and complications occurring within the index hospital or hospital system. Because bundles include 90-day options, accurate estimation of complication and readmission rates after the 30-day interval is key if this model is going to be viable for spinal fusion. In addition, cases were pulled from the NSQIP database using CPT code; although this strategy reliably identifies procedures, it does not specify procedural technique or surgeon factors such as volume or years of experience, which have the potential to affect outcomes. The NSQIP database is mostly made up of patients from large academic medical centers, which may decrease the generalizability of these results for patients treated at nonacademic medical centers or smaller community hospitals.30
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PCDF: DISCHARGE PLACEMENT AND OUTCOMES
CONCLUSIONS This study identified multiple factors that can help care teams identify patients who have a high likelihood of nonhome discharge after PCDF. Although most of these factors were nonmodifiable, diabetes was identified as a modifiable risk factor that can be actively addressed preoperatively to help minimize a patient’s likelihood of nonhome discharge. This study also found
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that patients discharged to a PAC facility had a higher likelihood of having a severe adverse event after discharge and being readmitted. Because the use of PAC facilities accounts for a large percentage of episode-of-care payments7 and is associated with poor outcomes, minimizing unnecessary PAC facility discharge is a key step in optimizing cost and outcomes for patients undergoing PCDF.
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23. Aldebeyan S, Aoude A, Fortin M, et al. Predictors of discharge destination after lumbar spine fusion surgery. Spine (Phila Pa 1976). 2016;41:1535-1541.
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10. Choy W, Lam SK, Smith ZA, Dahdaleh NS. Predictors of 30-day hospital readmission after posterior cervical fusion in 3401 patients. Spine (Phila Pa 1976). 2018;43:356-363.
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Conflict of interest statement: J.M.C. discloses his consulting relationship with Zimmer Biomet. All other authors declare that no conflicts of interest exist. Received 13 October 2018; accepted 22 January 2019 Citation: World Neurosurg. (2019). https://doi.org/10.1016/j.wneu.2019.01.214 Journal homepage: www.journals.elsevier.com/worldneurosurgery Available online: www.sciencedirect.com 1878-8750/$ - see front matter ª 2019 Elsevier Inc. All rights reserved.
WORLD NEUROSURGERY, https://doi.org/10.1016/j.wneu.2019.01.214