Background

Although peripheral nerve blocks decrease pain after total knee arthroplasty, the population-level impact of nerve blocks on arthroplasty resource utilization is unknown.

Methods

We conducted a population-based cohort study using linked administrative data from Ontario, Canada. We identified all adults having their first primary knee arthroplasty between 2002 and 2013. Using propensity scores to adjust for measureable confounders, we matched nerve block patients to a patient who did not receive a block. Within the matched cohort, we estimated the independent association of blocks with outcomes (length of hospital stay [primary]; and readmissions, emergency department visits, and falls [secondary]).

Results

One hundred seventy-eight thousand two hundred fourteen patients were identified; 61,588 (34.6%) had a block. The mean hospital stay was 4.6 days with a block compared to 4.8 without. After matching, there was a statistically significant decrease in the length of stay in the block group (relative risk, 0.98; 95% CI, 0.97 to 0.99; P < 0.001). Blocks were associated with a significant decrease in readmissions (relative risk, 0.87; 95% CI, 0.79 to 0.88; P < 0.001) but not emergency department visits (relative risk, 1.02; 95% CI, 0.98 to 1.05) or falls (relative risk, 1.37; 95% CI, 0.90 to 2.08). The association of blocks with length of stay after 2008 was inconsistent; overall, they were associated with longer stays; however, single-shot blocks were associated with shorter stays, while continuous techniques prolonged the length of stay.

Conclusions

Nerve blocks in total knee arthroplasty patients were associated with statistically significant reductions in length of stay and readmissions, but not emergency department visits or falls. The significance of these findings at the patient level and in contemporary practice requires further exploration in prospective randomized studies at low risk of indication bias.

• Peripheral nerve blocks reduce pain, but their effect on resource utilization after total knee arthroplasty remains unknown.

• In a propensity-matched retrospective cohort of 178,214 patients from Ontario, Canada, the authors estimated the independent association of peripheral nerve blocks with hospital length of stay, readmissions, emergency department visits, and falls.

• The length of stay was reduced in the nerve block group (relative risk [RR] 0.98; 95% CI, 0.97 to 0.99; P < 0.001). Nerve blocks were associated with a significant decrease in readmissions (RR, 0.87; 95% CI, 0.79 to 0.88; P < 0.001) but not emergency department visits (RR, 1.02; 95% CI, 0.98 to 1.05) or falls (RR, 1.37; 95% CI, 0.90 to 2.08).

• Peripheral nerve blocks very slightly reduced the hospital length of stay and reduced readmissions.

TOTAL knee arthroplasty (TKA) is one of the most common surgeries performed worldwide. In the United States alone, more than 700,000 knee replacements are performed annually,1  a number which is increasing rapidly.2  Despite advances in surgical and anesthetic techniques, poorly controlled pain after TKA continues to be an important issue for patients, clinicians, and the healthcare system.3–5  While poor postoperative pain control can negatively affect patient-centered outcomes, including experience and satisfaction, it can also increase hospital length of stay (LOS)6  and subsequent hospital readmissions and emergency department (ED) visits.7

Multiple strategies exist to optimize pain control after TKA including systemic opioids, intrathecal opioids, multimodal analgesia, local infiltration analgesia, and peripheral nerve blockade (PNB).8  Recent Cochrane reviews of randomized trials demonstrate that PNB for knee surgery is associated with improved postoperative pain control up to 72 h after surgery.9  Small randomized trials show that femoral nerve blocks for TKA decrease time to meet discharge criteria,10  improve early adherence to physical therapy, and accelerate rehabilitation.11  However, no meta-analysis or large multicenter studies exist to estimate the impact of PNB on hospital LOS or healthcare resource utilization.12  Based on the improved analgesia and accelerated recovery associated with PNBs, we hypothesized that the receipt of a PNB for TKA would decrease resource utilization and improve outcomes after surgery including decreased hospital LOS, decreased rates of hospital readmission, and fewer ED visits. We also investigated the association between PNBs and in-hospital falls.

### Setting and Data

After ethics approval by the Sunnybrook Health Sciences Center (Toronto, Ontario, Canada), we conducted a population-based cohort study in Ontario, Canada, where hospital and physician services are provided to all residents through a publicly funded healthcare system and recorded in health administrative datasets that are collected using standardized methods.13,14  All data were linked deterministically using encrypted patient-specific identifiers. Datasets used for the study included the Discharge Abstract Database (DAD), which captures all hospitalizations; the Ontario Health Insurance Plan (OHIP) database, which captures physician service claims; the National Ambulatory Care Reporting System, which captures details of all emergency and outpatient care; the Continuing Care Reporting System, which records details of long-term and respite care; the Ontario Drug Benefits Database, which captures prescription drug claims for residents 65 yr and older; and the Registered Persons Database (RPDB), which captures all death dates for residents of Ontario. The analytic dataset was created by a trained data analyst independent from the study team. Because the analytic data were generated from data normally collected at Institute for Clinical Evaluative Sciences (Toronto, Ontario, Canada), no further data processing was required. Analysis was performed by the lead author and overseen by the senior author. The study protocol was registered at clinicaltrials.gov (NCT02742961), and this manuscript is reported per the STrengthening the Reporting of OBservational studies in Epidemiology and the REporting of studies Conducted using Observational Routinely-collected health Data guidelines.15,16

### Cohort

We identified all Ontario residents who were aged 18 yr or older on the day of their elective primary knee arthroplasty. These patients were identified using Canadian Classification of Interventions code 1VG53. Reabstraction studies of the DAD show this code to have a κ statistic of 0.99, sensitivity of 100% (95% CI, 98 to 100), and positive predictive value of 99% (95% CI, 96 to 100; prevalence, 1.4%).17  The elective status of each admission was designated in the DAD. We included only the first surgery for each individual to ensure a patient-level analysis. Participants were identified from April 2002 (the date of introduction of the International Classification of Diseases, Tenth Edition (ICD-10), was introduced to identify diagnoses and the Canadian Classification of Interventions to identify procedures) to March 2014 (the latest time at which all datasets were complete).

### Exposure

The provision of a PNB was identified from the OHIP database using physician fee-for-service claims. We identified all plexus or major nerve blocks performed on the day of surgery using OHIP codes G260 or G060, which identify lumbar plexus or 3-in-1 blocks and femoral nerve or fascia iliaca blocks, respectively. In 2008, a separate code was introduced for the insertion of a continuous PNB catheter (CPNB; G279); therefore, CPNBs were identified in patients cared for in 2008 and later. Physician procedural codes in Ontario are highly accurate, with 88 to 95% interrater agreement in reabstraction studies.18  We categorized the PNB exposure as present or absent.

### Outcomes

The primary outcome was hospital LOS. Secondary outcomes included 30-day all-cause readmissions and 30-day ED visits. We also identified in-hospital falls during the index hospital admission. All deaths in the 30 days after surgery were recorded. Acute hospital LOS was calculated as the days from surgery to discharge from acute care in the DAD, readmissions were identified from the creation of a new DAD record within 30 days of discharge, and falls were identified from the DAD using validated ICD-10 codes with high specificity (91%) and sensitivity (96%).19  Deaths were identified from the RPDB and ED visits from the National Ambulatory Care Reporting System.

### Covariates

Demographics were identified from the RPDB and the Canadian Census, including age, gender, neighborhood income quintile, and rural residence status. Standard methods were used to identify all Elixhauser comorbidities based on ICD-9 and ICD-10 codes from the DAD in the 3-yr preceding surgery.20  For patients aged 65 yr and older, we identified the receipt of the following prescription medications in the 6 months before surgery: immediate release opioid analgesics, extended release opioid analgesics (including fentanyl patch), angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, antiarrythmatics, anticoagulants, anticonvulsants, antidepressants, antipsychotics, insulin, oral antihyperglycemics, antiplatelet agents, benzodiazepines, β blockers, oral corticosteroids, inhaled corticosteroids, inhaled bronchodilators, donepezil, rivastigmine, memantine, or galantamine. All acute care hospitalizations and ED visits in the year before the index admission were identified. The anesthesia type was captured from the DAD. The receipt of a preoperative anesthesia consultation and use of an intraoperative arterial line were also identified from OHIP data.

### Analysis

SAS Enterprise Guide 6.1 (SAS Institute, USA) was used for all analyses. Patient characteristics were compared between PNB categories using absolute standardized differences, which are less sensitive to sample size than P values. For continuous variables, standardized differences are calculated as the difference in means divided by the square root of the mean sample variance between exposure groups; for dichotomous variables, the standardized difference represents the difference in the proportion with the covariate divided by the square root of the mean variance of the proportion with the covariate between exposure groups. Although no universal threshold has been established, differences of 10% or less are considered to indicate an adequate balance of covariates.21

Unadjusted analyses were performed for all outcomes. Because the indication for a PNB could be confounded by patient factors that are also related to the likelihood of experiencing our outcomes of interest, we also performed propensity score–matched analyses. We developed a nonparsimonious logistic regression model to predict the likelihood of receiving a PNB. Our propensity score model included patient gender, age (represented as a restricted cubic spline with five knots), year of surgery (represented as a restricted cubic spline with three knots), rural residence (binary), neighborhood income quintile (five-level categorical variable), all Elixhauser comorbidities (as binary variables), acute care hospitalizations in the year before admission (binary), ED visits in the year before surgery (binary), anesthesia type (categorized as general anesthesia [which included combined spinal or epidural plus general] or neuraxial anesthesia [spinal or epidural alone]), receipt of a preoperative anesthesia consult (binary), use of an intraoperative arterial line (binary), and each prescription medication described in the Covariates (each coded as three-level categorical variables representing no prescription drug coverage, drug coverage but no prescription for the medication, or drug coverage with a prescription for the medication). Because CPNBs could not be identified across the study period, the propensity score model grouped single-shot PNBs and CPNBs into a single exposure level.

A propensity score was assigned to each patient; individuals who received a PNB were matched 1 to 1 without replacement using a greedy matching algorithm that accounted for their propensity to receive a PNB (with caliper width equal to 0.2 SDs of the propensity score logit) to a patient with a similar propensity score who did not receive a PNB and who was operated on in the same hospital. Matching 1:1 has been shown to reduce bias relative to 1: many matching.22  By matching on the propensity score between patients within the same hospitals, we were able to account for unobserved hospital-level characteristics and the hierarchal nature of population-based health administrative data. Studies demonstrate that within-cluster matching decreases bias and error compared to matching only on the propensity score.23  Propensity score match success was assessed by (1) achieving a balance of all measured covariates between groups defined by a standardized difference of less than or equal to 10%; (2) visual inspection of pre- and postmatch propensity score distributions; and (3) ensuring that a large number of matched pairs were created to support the precision and generalizability of our findings.24

For our primary analysis, unadjusted and propensity score match–adjusted analyses measured the association between PNB and LOS using a generalized linear model with negative binomial distributed errors and a log link to account for the skewed LOS distribution.25  For our secondary analyses (risk of readmission, ED visits, and falls), we used chi-square tests. For all outcomes, we calculated absolute differences, as well as relative risk and 95% CI.

We performed three-subgroup analyses to test the robustness of our primary findings. For each subgroup analysis, a new propensity score was generated for each member of the specified subgroup and a new match performed within the specific subgroup (i.e., we generated three new sets of propensity scores and three specific matched subgroup cohorts). Our subgroups of interest were patients 66 yr or older (all of whom had complete prescription drug data), patients operated on in the first half of the study period (2002 to 2007), and patients operated on in the second half of the study period (2008 to 2013/2014, the period where CPNBs could be identified). Matching and outcome analyses within each subgroup were done as described for the primary and secondary analyses.

To explore the impact of CPNBs on outcomes, we preformed post hoc sensitivity analyses using multivariable regression in the subgroup of patients whose surgery was in 2008 or later (generalized linear models with γ distributed errors and a log link for LOS, logistic models for all other binary outcomes) with a three-level categorical variable as the exposure of interest (no PNB [reference], PNB no nerve catheter, and PNB plus nerve catheter). All models controlled for gender, age, year of surgery, rural residence, neighborhood income quintile, all Elixhauser comorbidities, acute care hospitalizations in the year before admission, ED visits in the year before surgery, anesthesia type, receipt of a preoperative anesthesia consult, use of an intraoperative arterial line, and preoperative opioid use.

### Missing Data

Main outcome and exposure variables were complete for all participants. Neighborhood income quintile was imputed for with the group median for 0.4% of patients; rurality was imputed with the most common value (nonrural residence) for 0.1% of patients. No other data were missing, and all linkages were complete.

We identified 234,884 episodes of elective primary TKA between 2002 and 2014 (fig. 1). After excluding subsequent knee replacements in the same patient (i.e., future operations on the other knee), we were left with 178,214 patients for analysis. Peripheral nerve blocks were performed in 61,588 (34.6%) patients. CPNBs were placed in 7,685 individuals (7.9% of all patients in 2008 and later, 16.4% of all patients receiving a PNB in this time period). Patient characteristics are described in table 1. Before matching, standardized differences were less than 10% for most covariates. Patients who received a block were less likely to live in a rural setting, had a higher American Society of Anesthesiology score, and were more likely to be seen preoperatively in consultation with an anesthesiologist.

Table 1.

Baseline Characteristics of Study Population

Fig. 1.

Creation of analytical dataset.

Fig. 1.

Creation of analytical dataset.

Close modal

The use of PNBs increased substantially over the course of our study (fig. 2). Major plexus blocks (which would represent a lumbar plexus or a 3-in-1 block) were billed in 48,791 (79%) of patients receiving a PNB with the remainder being billed as a major nerve block (femoral or fascia iliaca block). All CPNBs were placed in conjunction with a major nerve block.

Fig. 2.

Yearly proportion of patients receiving any peripheral nerve block (PNB) or a continuous PNB (continuous techniques could only be identified from 2008 onward; data are aggregated by administrative years. For example, the 2002 year includes patients from April 2002 to March 2003).

Fig. 2.

Yearly proportion of patients receiving any peripheral nerve block (PNB) or a continuous PNB (continuous techniques could only be identified from 2008 onward; data are aggregated by administrative years. For example, the 2002 year includes patients from April 2002 to March 2003).

Close modal

Propensity score matching resulted in 38,557 PNB patients (62.6% of all PNB patients) being matched to a similar patient from the same hospital who did not receive a PNB. The balance of covariates assessed by a standardized difference of 10% or less was achieved across all measured confounders (table 1), and propensity score distribution overlap improved noticeably (Appendix).

In the 30 days after surgery, 438 (0.25%) patients died (282 in the no PNB group and 156 in the PNB group). The overall rate of falls was 0.7 per 1,000 in-hospital patient days.

Unadjusted and propensity score match–adjusted results of our primary and secondary analyses are described in table 2. LOS was shorter in the PNB group before and after adjustment. The risk of readmission was lower in the PNB group in both crude and adjusted analyses. Before propensity score adjustment, the risk of an ED visit was lower in the PNB group; however, the adjusted association was nonsignificant. PNBs were not associated with the risk of falling before or after propensity score adjustment, although the total number of falls in the study was small.

Table 2.

Study Outcomes

The findings of the subgroup analysis are provided in table 3 In patients more than 65 yr old, adjusted results mirrored the findings of the primary analysis, except that ED visits were more likely in the PNB group. However, the associations between PNBs with decreased LOS and readmission risk were not consistent over time. Before 2008, findings across outcome measures were similar to the results of the primary analysis, including a significant reduction in LOS and readmissions; after 2008, we found that PNBs were associated with a small but statistically significant increase in LOS, while their association with a decreased risk of readmission was no longer present.

Table 3.

Outcomes of Subgroup Analyses

Our sensitivity analyses demonstrated that compared to no block, CPNBs were associated with significant increases in LOS, no difference in readmission risk, decreased risk of ED visits, and no difference in fall risk (table 4). Single-shot PNBs were significantly associated with decreases in LOS, readmissions, and ED visits. Although our regression model analyzing postoperative falls did converge, due to the small number of outcomes (i.e., falls) relative to degrees of freedom in the model, these results must be interpreted with greater caution as this model may overfit our available data.

Table 4.

Sensitivity Analyses (2008 to 2013)

In this population-based cohort study of peripheral nerve blocks for primary TKA, the receipt of a PNB was associated with significantly decreased postoperative LOS and decreased risk of 30-day hospital readmission. However, these positive impacts of PNBs on postoperative resource utilization were not entirely consistent over time and across subgroups. This heterogeneity may reflect a variety of factors, including different impacts of single-shot versus continuous nerve block techniques, or changes in the application of perioperative multimodal analgesia strategies over time. Given this heterogeneity and the finding that our primary outcome of LOS was statistically, but possibly not clinically, significant at the individual patient level, randomized evaluations of continuous versus single-shot PNBs in high-priority patient populations are needed to inform the optimized provision of perioperative care for TKA patients, including the study of patient-reported outcome measures.

The current study provides important and generalizable information that enhances the current body of knowledge regarding PNBs for TKA. In a real-world setting, PNBs were significantly associated with a decrease in LOS and readmissions after surgery, outcomes that are both important drivers of healthcare resource utilization. An independent decrease in LOS of 0.1 days may not be highly relevant at the individual patient level and is substantially less than the 1.7-day decrease in time to discharge readiness found in a recent randomized trial.10  However, when extrapolated across the 719,000 TKAs performed in the United States in 2010,26  this equates to a 79,000-hospital bed days per year decrease. At an average cost of $1,600 per hospital bed day,27 this could translate into annual savings of over$100 million. With an average readmission cost of approximately \$10,200, a 0.6% decrease in readmission rates could also be projected to save millions of dollars per year.28  However, the lack of consistent association between PNBs and decreased resource since 2008 requires that these projections be tempered and underlying changes in practice be considered when explaining this temporal trend.

Overall, changes in the utilization of PNBs, as well as in postoperative resource utilization, were clear across our study period. Patients cared for between 2002 and 2007 had longer LOS and higher readmission rates than those cared for between 2008 and 2013, regardless of PNB exposure. Therefore, the broad focus on more efficient use of healthcare resources in the setting of constrained hospital and health system budgets, as well as the use of these outcomes as hospital quality metrics, may have driven down LOS and readmission rates to the point that the additional analgesic impact of a PNB no longer translates into expedited discharge and avoidance of readmissions at a population level. Additionally, important changes to the perioperative care of TKA patients have recently emerged, such as increased use of standard perioperative care pathways,29  increased uptake of perioperative multimodal analgesia,30  and routine use of local infiltration analgesia.31  In fact, a recent systematic review found that, compared to femoral nerve blocks, LOS in local infiltration analgesia patients after TKA was not significantly different.32

The divergence between outcomes over time was also informed by our sensitivity analysis. When the association between PNBs and CPNBs with outcomes was looked at separately in patients from 2008 onward, single-shot PNBs continued to be associated with improved resource utilization, while CPNBs were associated with an increase in LOS and no change in readmission risk. The increase in LOS attributable to CPNBs could be related to complexities with in-hospital management of catheters and discharge planning, or it could suggest that unmeasured sources of indication bias underlying a clinician’s decision to place a CPNB as opposed to a single-shot PNB (such as higher risk of poor recovery or pain tolerance) were present and inadequately captured by administrative data. However, the lack of clear resource use benefit with CPNBs in particular should be considered and requires future study. The divergence in findings related to ED visits when PNBs and CPNBs were considered separately may relate to the fact that propensity score–matched analyses provide an average treatment effect in the treated (i.e., the impact of treatment is only measured in the subset of the population that can be matched) compared to a regression analysis that provides an average treatment effect (i.e., the impact of moving the whole population between different interventions).33

Overall, it does appear that at least for single-shot PNBs, there is a consistent and generalizable association with improved resource utilization after surgery. However, as with any intervention, the risks and benefits of PNBs must be considered for each patient. In our study, we addressed two pertinent safety issues. First, in some major orthopedic surgeries, decreased LOS is associated with an increased risk of postdischarge adverse events.34  Reassuringly, despite a reduced LOS, we found that PNB patients were less likely to be readmitted, and there was no consistent signal toward an increase in ED visits. Second, the proven efficacy of PNBs in improving pain outcomes9,12  must be weighed against risks of adverse events (such as falls). As in previous studies,35  our findings support a lack of statistically significant association between single-shot PNBs and fall risk after TKA. Based on our findings using a validated definition of falls in health administrative data, there also does not appear to be an association between CPNBs and falls.36,37  However, this finding is by no means definitive. Despite the lack of statistically significant association, falls were rare in our study but were more frequent in the PNB group (37% relative risk increase). We suggest that falls should continue to be studied as an important safety issue in the setting of lower limb PNB.

### Strengths and Limitations

This study features several strengths, as well as limitations, that must be considered when appraising our findings. Our use of population-based data allowed us to study the broad range of TKA patients across a universal healthcare system; therefore, our findings may be generalizable to similar patients in similar jurisdictions. While the propensity score methods used in this study to control for indication and confounding bias are robust, account for clustering within hospitals, and include preoperative data that many studies of anesthesia interventions do not (such as longitudinal prescription drug records and a 3-yr lookback window for comorbidity data), we could control only for measured confounders. By its nature, observational research of interventions is at the risk of indication bias, and our findings must be considered in the context of this important limitation. The health administrative data used were not initially collected for research purposes and have limitations. The codes used to define our TKA cohort and to measure outcomes have been studied and are known to be accurate and reliable. Physician fee-for-service claims have been found to be highly accurate; however, the specific diagnostic accuracy of the codes used to identify PNBs in this study has not been formally measured. Additionally, we cannot know with certainty the specific block that was performed (3-in-1, lumbar plexus, fascia iliaca, femoral nerve, or possibly adductor canal block) although surveys suggest that over 80% of PNBs for TKA are femoral blocks.38  It appears that most single-shot blocks for TKA in Ontario are billed as major plexus blocks, while CPNB insertion is billed in conjunction with a major nerve block. This is credible, since the physician services agreement dictates that a catheter cannot be billed in addition to a major plexus block, but billing a major nerve block plus a continuous catheter would result in a higher payment to the physician. We are also unable to control for the clinical effectiveness of the PNBs, provision of local infiltration analgesia, or systemic multimodal analgesia; however, we would predict that these missing data would bias our results toward the null (i.e., decrease the impact of PNBs). Finally, our outcomes were limited to measures of healthcare resource utilization. The development of a full understanding of the value attributable to PNBs for TKA will require a prospective study, including patient-centered outcome measures.

The provision of a peripheral nerve block for TKA was associated with a small but significant decrease in the hospital LOS and a significant reduction in the risk of readmission. For single-shot peripheral nerve blocks, this finding was consistent over time, while the positive impact of continuous catheter techniques on outcomes was less clear. Furthermore, neither single-shot or continuous catheter techniques were significantly associated with an increased risk of in-hospital falls. Future research on the impact of peripheral nerve blocks on patient-reported outcome measures is needed.

Supported in part by the Institute for Clinical Evaluative Sciences (ICES), which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC), Toronto, Ontario, Canada. The opinions, results, and conclusions reported in this article are those of the authors and are independent from the funding sources. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred. These datasets were held securely in a linked, deidentified form and analyzed at the Institute for Clinical Evaluative Sciences.

Dr. McIsaac receives salary support from the Ottawa Hospital Anesthesiology Associates Alternate Funds Association via the Ottawa Hospital Department of Anesthesiology, Ottawa, Ontario, Canada. The other authors declare no competing interests.

1.
Number of All-listed Procedures for Discharges from Short-stay Hospitals, by Procedure Category and Age: United States, 2010
.
Atlanta, GA
,
2010
2.
OECD
:
Hip and knee replacement
in
Health at a Glance: Europe 2012
.
Paris
,
OECD Publishing
,
2012
, pp
10
3
3.
Chan
EY
,
Blyth
FM
,
Nairn
L
,
Fransen
M
:
Acute postoperative pain following hospital discharge after total knee arthroplasty.
Osteoarthritis Cartilage
2013
;
21
:
1257
63
4.
Baker
PN
,
van der Meulen
JH
,
Lewsey
J
,
Gregg
P
;
National Joint Registry for England and Wales
:
The role of pain and function in determining patient satisfaction after total knee replacement. Data from the National Joint Registry for England and Wales.
J Bone Joint Surg Br
2007
;
89
:
893
900
5.
Beswick
,
Wylde
V
,
Gooberman-Hill
R
,
Blom
A
,
Dieppe
P
:
What proportion of patients report long-term pain after total hip or knee replacement for osteoarthritis? A systematic review of prospective studies in unselected patients.
BMJ Open
2012
;
2
:
e000435
6.
Morrison
RS
,
Magaziner
J
,
McLaughlin
MA
,
Orosz
G
,
Silberzweig
SB
,
Koval
KJ
,
Siu
AL
:
The impact of post-operative pain on outcomes following hip fracture.
Pain
2003
;
103
:
303
11
7.
Coley
KC
,
Williams
BA
,
DaPos
SV
,
Chen
C
,
Smith
RB
:
Retrospective evaluation of unanticipated admissions and readmissions after same day surgery and associated costs.
J Clin Anesth
2002
;
14
:
349
53
8.
Fischer
HB
,
Simanski
CJ
,
Sharp
C
,
Bonnet
F
,
Camu
F
,
Neugebauer
EA
,
Rawal
N
,
Joshi
GP
,
Schug
SA
,
Kehlet
H
;
PROSPECT Working Group
:
A procedure-specific systematic review and consensus recommendations for postoperative analgesia following total knee arthroplasty.
Anaesthesia
2008
;
63
:
1105
23
9.
Chan
E-Y
,
Fransen
M
,
Parker
DA
,
Assam
PN
,
Chua
N
:
Femoral nerve blocks for acute postoperative pain after knee replacement surgery.
Cochrane database Syst Rev
2014
;
5
:
CD009941
10.
Ilfeld
BM
,
Le
LT
,
Meyer
RS
,
Mariano
ER
,
Vandenborne
K
,
Duncan
PW
,
Sessler
DI
,
Enneking
FK
,
Shuster
JJ
,
Theriaque
DW
,
Berry
LF
,
EH
,
Gearen
PF
:
Ambulatory continuous femoral nerve blocks decrease time to discharge readiness after tricompartment total knee arthroplasty: A randomized, triple-masked, placebo-controlled study.
Anesthesiology
2008
;
108
:
703
13
11.
Capdevila
X
,
Barthelet
Y
,
Biboulet
P
,
Ryckwaert
Y
,
Rubenovitch
J
,
D’Athis
F
:
Effects of perioperative analgesic technique on the surgical outcome and duration of rehabilitation after major knee surgery.
Anesthesiology
1999
;
91
:
8
15
12.
Xu
J
,
Chen
X-M
,
Ma
C-K
,
Wang
X-R
:
Peripheral nerve blocks for postoperative pain after major knee surgery.
Cochrane database Syst Rev
2014
;
12
:
CD010937
13.
.
14.
Institute for Clinical and Evaluative Sciences
.
About Us. Available at: http://www.ices.on.ca/webpage.cfm?site_id=1&org_id=26. Accessed May 1, 2016
15.
von Elm
E
,
Altman
DG
,
Egger
M
,
Pocock
SJ
,
Gøtzsche
PC
,
Vandenbroucke
JP
;
STROBE Initiative
:
Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies.
BMJ
2007
;
335
:
806
8
16.
Benchimol
EI
,
Smeeth
L
,
Guttmann
A
,
Harron
K
,
Moher
D
,
Petersen
I
,
Sorensen
HT
,
von elm
E
,
Langan
SM
:
The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement.
PLOS Med
2015
;
12
:
e1001885
17.
DN
,
Croxford
R
,
Chong
A
,
Austin
P
,
Tu
J
,
Laupacis
A
:
Canadian Institute for Health Information Discharge Abstract Database: A Validation Study ICES Investigative Report June 2006 Canadian Institute for Health Information Discharge Abstract Database.
2006
18.
Williams
J
,
Young
W
:
Appendix: A summary of studies of health care administrative databases in Canada
in
Patterns of Healthcare in Ontario: The ICES Practice Atlas
. Edited by
Goel
V
,
Williams
J
,
Anderson
G
,
Blackstein-Hirsch
P
,
Fooks
C
,
Naylor
C
.
Ottawa, Ontario
,
,
1996; 339–345
19.
Ackroyd-Stolarz
S
,
Bowles
S
,
Giffin
L
:
Validating administrative data for the detection of adverse events in older hospitalized patients.
Drug Healthc Patient Saf
2014
;
6
:
101
108
20.
Quan
H
,
Sundararajan
V
,
Halfon
P
,
Fong
A
,
Burnand
B
,
Luthi
JC
,
Saunders
LD
,
Beck
CA
,
Feasby
TA
,
Ghali
W
:
Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.
Med Care
2005
;
43
:
1130
39
21.
Austin
PC
:
Using the standardized difference to compare the prevalence of a binary variable between two groups in observational research.
Commun Stat Simul Comput
2009
;
38
:
1228
34
22.
Austin
PC
:
Statistical criteria for selecting the optimal number of untreated subjects matched to each treated subject when using many-to-one matching on the propensity score.
Am J Epidemiol
2010
;
172
:
1092
7
23.
Gayat
E
,
Thabut
G
,
Christie
JD
,
Mebazaa
A
,
Mary
JY
,
Porcher
R
:
Within-center matching performed better when using propensity score matching to analyze multicenter survival data: Empirical and Monte Carlo studies.
J Clin Epidemiol
2013
;
66
:
1029
37
24.
Ali
MS
,
Groenwold
RH
,
Belitser
SV
,
Pestman
WR
,
Hoes
AW
,
Roes
KC
,
Boer
,
Klungel
OH
:
Reporting of covariate selection and balance assessment in propensity score analysis is suboptimal: A systematic review.
J Clin Epidemiol
2015
;
68
:
112
21
25.
Austin
PC
,
Rothwell
DM
,
Tu
JV
:
A comparison of statistical modeling strategies for analyzing length of stay after cabg surgery.
Health Serv Outcomes Res Methodol
2002
;
3
:
107
133
26.
National Center for Health Statistics
:
National Hospital Discharge Survey
.
Atlanta, GA
,
2010
27.
Oh
J
Becker’s Hospital Review: Average Cost Per Inpatient Day Across 50 States in 2010. Available at: http://www.beckershospitalreview.com/lists/average-cost-per-inpatient-day-across-50-states-in-2010.html. Published 2012. Accessed February 1, 2016
28.
Qaisim
M
,
Andrews
R
:
Post-Surgical Readmissions among Patients Living in the Poorest Communities: HCUP Statistical Brief #142
Rockville, MD, 2009. Available at: http://www.hcup-us.ahrq.gov/reports/statbriefs/sb142.pdf. Accessed April 24, 2016
29.
Barbieri
A
,
Vanhaecht
K
,
Van Herck
P
,
Sermeus
W
,
Faggiano
F
,
Marchisio
S
,
Panella
M
:
Effects of clinical pathways in the joint replacement: A meta-analysis.
BMC Med
2009
;
7
:
32
30.
KS
,
Patorno
E
,
Huybrechts
KF
,
Liu
J
,
Rathmell
JP
,
Bateman
BT
:
Variations in the use of perioperative multimodal analgesic therapy.
Anesthesiology
2016
;
124
:
837
45
31.
Perlas
A
,
Kirkham
KR
,
Billing
R
,
Tse
C
,
Brull
R
,
Gandhi
R
,
Chan
VWS
:
The impact of analgesic modality on early ambulation following total knee arthroplasty.
Reg Anesth Pain Med
2013
;
38
:
334
339
32.
Marques
EM
,
Jones
HE
,
Elvers
KT
,
Pyke
M
,
Blom
AW
,
Beswick
:
Local anaesthetic infiltration for peri-operative pain control in total hip and knee replacement: Systematic review and meta-analyses of short- and long-term effectiveness.
BMC Musculoskelet Disord
2014
;
15
:
220
33.
Austin
PC
:
A tutorial and case study in propensity score analysis: An application to estimating the effect of in-hospital smoking cessation counseling on mortality.
Multivariate Behav Res
2011
;
46
:
119
51
34.
Nordström
P
,
Gustafson
Y
,
Michaëlsson
K
,
Nordström
A
:
Length of hospital stay after hip fracture and short term risk of death after discharge: A total cohort study in Sweden.
BMJ
2015
;
350
:
h696
35.
Memtsoudis
SG
,
Danninger
T
,
Rasul
R
,
Poeran
J
,
Gerner
P
,
Stundner
O
,
Mariano
ER
,
Mazumdar
M
:
Inpatient falls after total knee arthroplasty: The role of anesthesia type and peripheral nerve blocks.
Anesthesiology
2014
;
120
:
551
63
36.
Wasserstein
D
,
Farlinger
C
,
Brull
R
,
Mahomed
N
,
Gandhi
R
:
Advanced age, obesity and continuous femoral nerve blockade are independent risk factors for inpatient falls after primary total knee arthroplasty.
J Arthroplasty
2013
;
28
:
1121
4
37.
Ilfeld
BM
:
Single-injection and continuous femoral nerve blocks are associated with different risks of falling.
Anesthesiology
2014
;
121
:
668
9
38.
Bouaziz
H
,
Bondàr
A
,
Jochum
D
,
Fuzier
R
,
Paqueron
X
,
Ripart
J
,
Choquet
O
,
Belbachir
A
,
Fletcher
D
,
Estebe
JP
:
Regional anaesthesia practice for total knee arthroplasty: French national survey - 2008.
Ann Fr Anesth Reanim
2010
;
29
:
440
51

### Appendix

Fig. A1.

Propensity score distributions before (A) and after (B) matching. Closer overlap of distributions indicates the improved balance of covariates between peripheral nerve block (PNB) and no PNB groups.

Fig. A1.

Propensity score distributions before (A) and after (B) matching. Closer overlap of distributions indicates the improved balance of covariates between peripheral nerve block (PNB) and no PNB groups.

Close modal