Sage Journals: Discover world-class research

Abstract

Purpose

Joint arthroplasty has become increasingly more common in the United States, and it is important to examine the patient-based risk factors and surgical variables associated with hospital readmissions. The purpose of this study was to identify stratified rates and risk factors for readmission after upper extremity (shoulder, elbow, and wrist) and lower extremity (hip, knee, and ankle) arthroplasty.

Methods

All patients undergoing upper and lower extremity arthroplasty from 2008–2018 were identified using the National Surgical Quality Improvement Program dataset. Patient demographics, medical comorbidities and surgical characteristics were examined utilizing uni- and multi-variate analysis for significant predictors of 30-days hospital readmission.

Results

A total of 523,523 lower and 25,215 upper extremity arthroplasty patients were included in this study. A number of 22,183 (4.2%) lower and 1072 (4.4%) upper extremity arthroplasty patients were readmitted within 30 days of discharge. Significant risk factors for 30-days readmission after lower extremity arthroplasty included age, Body Mass Index (BMI), operative time, dependent functional status, American Society of Anesthesiologists (ASA) score ≥3, increased length of stay, and various medical comorbidities such as diabetes, tobacco dependency, and chronic obstructive pulmonary disease (COPD). An overweight BMI was associated with a lower odds of 30-days readmission when compared to a normal BMI for lower extremity arthroplasty. Analysis for upper extremity arthroplasty revealed similar findings of significant risk factors for 30-days hospital readmission, although diabetes mellitus was not found to be a significant risk factor.

Conclusion

Nearly one in 25 patients undergoing upper and lower extremity arthroplasty experiences hospital readmission within 30-days of index surgery. There are several modifiable risk factors for 30-days hospital readmission shared by both lower and upper extremity arthroplasty, including tobacco smoking, COPD, and hypertension. Optimization of these medical comorbidities may mitigate the risk short-term readmission following joint arthroplasty procedures and improve overall cost effectiveness of perioperative surgical care.

Keywords

Arthroplasty obesity diabetes readmission risk-factors

Introduction

Joint arthroplasty is becoming exceedingly common in the United States, with approximately 7 million Americans living with either a hip or knee replacement.¹ The rates of joint arthroplasty are expected to continue to increase in the coming years, with an over 100% increase projected in both total hip and total knee replacements in the next 10 years.^2,3 Similarly, there has been an exponential increase in the rate of shoulder and elbow arthroplasty that equals or even exceeds the recent increase seen in hip and knee replacements.^4,5

Just as the rates of upper and lower extremity arthroplasty have been rising, so have the rates of post-operative readmissions following these procedures. Zmistowski et al. found that 5.3% of patients undergoing hip or knee arthroplasty had an unplanned readmission within 90 days of discharge, whereas Mahoney et al. reported 90-days readmission rates for total shoulder arthroplasty to be 5.9%.^6,7 Hospital readmissions not only impact the quality of life of the patient but also consume valuable resources within the health care system. With the current focus on patient outcomes-based metrics and bundled payment models, readmission rates following arthroplasty have a profound effect on hospital quality ratings and reimbursement of hospitals and physicians.^8-10

By identifying risk factors for readmission, physicians can better collaborate between medical specialties to optimize patients for surgery and to mitigate existing modifiable peri-operative risk factors through patient-specific interventions. The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database collects patient data from many participating hospitals nationally. The database contains a large number of patients with various orthopaedic conditions¹¹ and collects data such as medical comorbidities, pre- and intra-operative surgical variables, and postoperative outcomes, including readmissions. Utilization of the NSQIP database has been shown to not only be associated with improved surgical outcomes, but also has been used to advance clinical standards of care.^12,13

The purpose of this study was to evaluate the readmission rates of patients undergoing upper and lower extremity arthroplasty, as well as to identify and analyze the risk factors for readmission. Although previous studies have evaluated the risk factors for post-arthroplasty readmission,^14-20 none have analyzed a population containing patient-based characteristics and surgical variables as large as the NSQIP dataset while encompassing comparison of upper and lower extremity arthroplasty.

Methods

NSQIP data from 2008–2018 were obtained, and patients were identified based on Current Procedural Terminology (CPT) code. CPT codes for upper joint arthroplasty included 23470 (shoulder hemiarthroplasty), 23472 (total shoulder arthroplasty), 25446 (total wrist arthroplasty), and 24363 (total elbow arthroplasty); those for lower joint arthroplasty included 27130 (hip arthroplasty), 27438 (patellofemoral arthroplasty), 27446 (unicompartmental knee arthroplasty), 27447 (total knee arthroplasty), and 27702 (total ankle arthroplasty). Surgical data, including American Society of Anesthesiologists (ASA) classification, type of anesthesia, operative time, and postoperative time to discharge were collected. Patient demographics and medical comorbidity data were also gathered.

Univariate logistic regression analysis was performed to determine the effect of different risk factors on postoperative hospital readmission. The independent variables with univariate analysis p-values of <0.2 were further analyzed with multivariate logistic regression. We discretized the continuous variables based on previous studies and reports to improve interpretation in our multivariate regression analysis. Body mass index (BMI) was categorized based on the WHO classification for weight status as follows: <18.5 kg/m² (underweight), 18.5 kg/m²–24.9 kg/m² (normal weight), 25 kg/m²–29.9 kg/m² (overweight), 30 kg/m²–34.9 kg/m² (Class I obesity), 35 kg/m²–39.9 kg/m² (Class II obesity), and >40 kg/m² (Class III obesity). Age variable was categorized based on a study by Fang et al.²¹ As follows: less 50 years of age, 51–60 years of age, 61–70 years of age, 71–80 years of age, 80 years of age or greater. Length of stay was also discretized to less than 2 days and 2 days or more. Operative time was categorized as: (1) operative time +/− one standard deviation from the mean; (2) operative time between +/−1 standard deviation AND +/− 2 standard deviations from the mean; and (3) operative time greater than +/−2 standard deviations from the mean. In order to be included within Multivariate analysis, variables must have been reported in at least 80% of the cohort. The performed surgical procedure was added to the multivariate analysis in order assess for the common effects associated with 30-days readmission among the upper extremity arthroplasty group and among the lower extremity arthroplasty group. Odds ratios (OR) with 95% confidence intervals (CI) are reported for both analyses. Odds ratios with CI not crossing 1.0 coupled with a p-value <0.05 were considered significant. The C-statistic was utilized to measure discriminative capacity, and the Hosmer and Lemeshow Goodness of Fit Test was employed to assess model calibration.

Results

Between 2008 and 2018, 523,523 patients undergoing lower extremity arthroplasty were identified from the NSQIP database. Of these, there were 22,183 readmissions (4.2%). A summary of the patient characteristics can be found in Table 1 and Table 2.

Table 1.

Summary statistics of patient population who underwent upper or lower extremity arthroplasty.

Upper extremity arthroplasty
Mean age (standard deviation)	68.55 years (10.29 years)
Mean BMI (standard deviation)	31.04 kg/m² (6.88 kg/m²)
Mean operative time (standard deviation)	111.81 min (46.89 min)
Percent female	56.10%
Lower extremity arthroplasty
Mean age (standard deviation)	66.11 years (10.27 years)
Mean BMI (standard deviation)	31.90 kg/m² (6.77 kg/m²)
Mean operative time (standard deviation)	92.23 min (38.14 min)
Percent female	59.10%

Table 2.

Summary statistics demonstrated sample size and 30-days readmission rates per procedure performed.

Procedure	Number	Number of 30-days readmission	Percent 30-days readmission, %
Total shoulder arthroplasty	21,755	901	4.14
Shoulder hemiarthroplasty	2840	128	4.51
Total elbow arthroplasty	553	37	6.69
Total wrist arthroplasty	67	6	8.96
Total hip arthroplasty	193,860	8554	4.41
Total knee arthroplasty	316,279	13,234	4.18
Uni-compartmental arthroplasty	10,907	323	2.96
Patellofemoral arthroplasty	1244	45	3.62
Total ankle arthroplasty	1233	27	2.19

Univariate analysis identified older age, male sex, increasing BMI, dependent functional status, ASA classification ≥3, specified medical comorbidities, longer operative time, and increased length of stay as factors associated with readmission in lower extremity arthroplasty (Table 3).

Table 3.

Results of univariate logistic analyses for the influence of risk factors on readmission for lower extremity joint arthroplasty.

Risk factor	Readmission
Risk factor	Or (95% CI)	p-value
Age (continuous)	1.024 (1.022, 1.025)	<0.0001
Female versus male	0.915 (0.891,0.940)	<0.0001
Body Mass index (kg/m²)	1.011 (1.009, 1.013)	<0.0001
Partially dependent versus independent functional status	0.840 (0.693, 1.018)	0.075
Totally dependent versus independent functional status	1.861 (1.514, 2.286)	<0.0001
ASA ≥3 (severe or life threatening disturbance) vs ≤ 2 (no or mild disturbance)	1.659 (1.615, 1.705)	<0.0001
Operative time (continuous)	1.002 (1.002, 1.002)	<0.0001
Length of stay (continuous)	1.014 (1.011, 1.017)	<0.0001
Medical Co-morbidities
Smoking (current smoker within 1 year)	0.862 (0.826,0.900)	<0.0001
All diabetes	1.37 (1.32, 1.42)	<0.001
Dyspnea at rest versus No dyspnea	2.755 (2.27, 3.34)	<0.0001
Dyspnea on exertion versus No dyspnea	1.705 (1.623, 1.792)	<0.0001
Chronic obstructive pulmonary disease	0.406 (0.386,0.427)	<0.0001
Hypertension	0.691 (0.671,0.712)	<0.0001
Bleeding disorder	0.503 (0.469,0.539)	<0.0001
Presence of preoperative open wound	0.428 (0.361,0.506)	0.0342
Steroid use for chronic condition	0.577 (0.544, 0.611)	<0.0001

Multivariate analyses for significant factors contributing to readmission are shown in (Table 4). Lower extremity arthroplasty patients who were between the ages 71 to 80 (OR: 1.476; 95% CI: 1.380, 1.578; p < 0.001) and 80 or greater (OR: 2.117; 95% CI: 1.964, 2.281; p < 0.001) had higher odds of 30-days readmission when compared to patients less than 50 years of age. Additionally, lower extremity arthroplasty patients who were overweight had lower odds of 30-days readmission (OR: 0.943; 95% CI: 0.900, 0.987; p = 0.011) when compared to patients of normal weight; whereas patients with class II obesity (OR: 1.097; 95% CI: 1.042, 1.155; p < 0.001) and class III obesity (OR: 1.281; 95% CI: 1.211, 1.355; p < 0.001) had increased odds for 30-days readmission. Patients who had an operative time between one and two standard deviations (OR: 1.051; 95% CI: 1.014, 1.088; p = 0.006), and two standard deviations (OR: 1.420; 95% CI: 1.331, 1.514; p < 0.001) outside of the sample mean operative time had an increased odds of being readmitted within 30 days when compared to lower extremity arthroplasty patients with operative times within one standard deviation of the mean.

Table 4.

Significant Results of Multivariate Logistic Analyses for the Influence of Risk Factors on Readmission for Lower Extremity Joint Arthroplasty. C statistic = 0.627.

Risk factor	Readmission
Risk factor	Or (95% CI)	p-value
Age 50 years of age or less	Ref	—
51–60 years of age	0.975 (0.911, 1.043)	0.460
61–70 years of age	1.056 (0.989, 1.127)	0.103
71–80 years of age	1.476 (1.380, 1.578)	<0.001
81 years or older	2.117 (1.964, 2.281)	<0.001
Female vs male	0.887 (0.862, 0.912)	<0.001
Body mass index 18.5 kg/m ² to 24.9 kg/m ²	Ref	—
Less than 18.5 kg/m²	1.060 (0.884, 1.272)	0.527
25.0 kg/m² to 29.9 kg/m²	0.943 (0.900, 0.987)	0.011
30.0 kg/m² to 34.9 kg/m²	1.018 (0.972, 1.067)	0.450
35.0 kg/m² to 40 kg/m²	1.097 (1.042, 1.155)	<0.001
Greater than 40 kg/m²	1.281 (1.211, 1.355)	<0.001
Optime (within one standard deviation from the mean) ^*	Ref	—
Optime (from one to two standard deviations from the mean)	1.051 (1.014, 1.088)	0.006
Optime (more than two standard deviation from the mean)	1.420 (1.331, 1.514)	<0.001
Length of stay less than 2 days	1.013 (0.978, 1.049)	0.463
Partially dependent vs independent functional status	1.658 (1.533, 1.794)	<0.001
Totally dependent vs independent functional status	1.547 (1.092, 2.191)	0.014
ASA ≥3 (severe or life-threatening disturbance) vs. ≤2 (no or mild disturbance)	1.302 (1.264, 1.342)	<0.0001
Medical Co-morbidities
Smoking (current smoker within 1 year)	1.209 (1.156, 1.265)	<0.0001
All diabetes	1.151 (1.111, 1.193)	<0.001
Dyspnea at rest versus No dyspnea	1.508 (1.235, 1.840)	<0.0001
Dyspnea on exertion versus No dyspnea	1.201 (1.139, 1.265)	<0.0001
Chronic obstructive pulmonary disease	1.817 (1.721, 1.919)	<0.0001
Hypertension	1.151 (1.115, 1.187)	<0.0001
Bleeding disorder	1.511 (1.408, 1.621)	<0.0001
Presence of preoperative open wound	1.599 (1.346, 1.900)	<0.001
Steroid use for chronic condition	1.562 (1.346, 1.900)	<0.0001
Procedure
Total knee arthroplasty	Ref	—
Patellofemoral arthroplasty	0.918 (0.6811.239)	0.576
Total ankle arthroplasty	0.500 (0.341, 0.734)	<0.001
Total hip arthroplasty	1.089 (1.057, 1.121)	<0.001
Uni-compartmental knee arthroplasty	0.771 (0.688, 0.863)	<0.001

^*Mean = 92.23 min, standard deviation = 38.14 min.

Other factors associated with 30-days readmission for lower extremity arthroplasty patients included: partially dependent functional status (OR 1.658 95% CI: 1.533, 1.794; p < 0.001), totally dependent functional status (OR 1.547 95% CI: (1.092, 2.191; p = 0.014), and ASA classification ≥3 (OR 1.302 (1.264, 1.342); p < 0.001). In descending severity of risk, medical comorbidities that were identified as factors for readmission include the following: chronic obstructive pulmonary disease (COPD), presence of pre-operative open wound, chronic steroid use, bleeding disorder, dyspnea at rest, smoking, dyspnea at exertion, diabetes mellitus, and hypertension (Table 4). Patients who underwent total ankle arthroplasty (OR: 0.500 95% CI: 0.341, 0.734; p=<0.001), and uni-compartmental knee arthroplasty (OR: 0.771 95% CI: 0.688, 0.863; p < 0.001) had lower odds of 30-days readmission when compared to patients who underwent total knee arthroplasty; whereas patients undergoing total hip arthroplasty had higher odds of 30-days readmission when compared to total knee arthroplasty patients (OR: 1.089 95% CI: 1.057, 1.121; p < 0.001).

Among upper extremity arthroplasty procedures, there were 25,215 patients identified within the NSQIP database between 2008 and 2018, including 1072 with subsequent 30-days readmission (4.4%). Univariate analysis identified increasing age, partially dependent and fully functional status, ASA classification ≥3, length of stay, and specified medical comorbidities as significant predictors for hospital readmission (Table 5).

Table 5.

Results of univariate logistic analyses for the influence of risk factors on readmission for upper extremity joint arthroplasty.

Risk factor	Readmission
Risk factor	Or (95% CI)	p-value
Age (continuous)	1.018 (1.010, 1.027)	<0.0001
Female versus male	1.032 (0.883, 1.21)	0.692
Body Mass index, kg/m² (continuous)	0.997 (0.986, 1.009)	0.663
Partially dependent versus independent functional status	3.43 (2.48, 4.63)	<0.0001
Totally dependent versus independent functional status	6.57 (2.18, 16.29)	0.0001
ASA ≥3 (severe or life threatening disturbance) vs ≤ 2 (no or mild disturbance)	1.84 (1.56, 2.17)	<0.0001
Operative time (continuous)	1.001 (0.999, 1.002)	0.195
Length of stay (continuous)	1.023 (1.02, 1.04)	0.003
Medical Co-morbidities
Smoking (current smoker within 1 year)	0.883 (0.734, 1.06)	0.189
All diabetes	1.26 (1.10, 1.56)	0.003
Dyspnea at rest versus No dyspnea	1.585 (0.692, 3.631)	0.276
Dyspnea on exertion versus No dyspnea	1.655 (1.348, 2.033)	<0.0001
Chronic obstructive pulmonary disease	0.498 (0.411,0.633)	<0.0001
Hypertension	0.699 (0.609,0.803)	<0.0001
Bleeding disorder	0.481 (0.363, 0.636)	<0.0001
Presence of preoperative open wound	0.461 (0.260,0.818)	0.008
Steroid use for chronic condition	0.699 (0.551,0.888)	0.003

Multivariate analysis showed that an age over 81 (OR 1.496 95% CI: 1.048, 2.136; p = 0.027) was associated with an increased risk for 30-days readmission when compared to patient under the age of 50. Furthermore, our regression analysis revealed that upper extremity operative time outside of two standard deviations from the sample mean was associated with increased odds for 30-days readmission (OR: 1.326 95% CI: 1.027, 1.807; p = 0.032). Other factors associated with increased odds ratio include: partially dependent functional status (OR 1.758 95% CI: 1.332, 2.320; p < 0.001), totally dependent functional status (OR 2.697 95% CI: 1.122, 6.481; p = 0.027), and ASA classification ≥3 (OR 1.232 95% CI: 1.078, 1.408; p < 0.001) (Table 6). Patients with a length of stay less than 2 days was associated with a decreased odds ratio (OR: 0.830 95% CI: 0.730, 0.943; p = 0.004) (Table 6). Medical comorbidities that were identified as risk factors for readmission include, in descending severity of risk: chronic obstructive pulmonary disease (COPD), bleeding disorder, chronic steroid use, and hypertension (Table 6). Patients who underwent total elbow arthroplasty (OR: 1.464 95% CI: 1.029, 2.085; p = 0.034) and total wrist arthroplasty (OR: 2.463 95% CI: 1.052, 5.765; p = 0.038) had greater odds of a 30-days readmission when compared to patients who underwent total shoulder arthroplasty.

Table 6.

Significant results of multivariate logistic analyses for the influence of risk factors on readmission for upper extremity joint arthroplasty. C-statistic = 0.623.

Risk factor	Readmission
Risk factor	Or (95% CI)	p-value
Age 50 years of age or less	Ref	—
51–60 years of age	0.847 (0.593, 1.209)	0.360
61–70 years of age	0.957 (0.687, 1.332)	0.793
71–80 years of age	1.168 (0.837, 1.629)	0.362
81 years or older	1.496 (1.048, 2.136)	0.027
Partially dependent versus independent functional status	1.758 (1.332, 2.320)	<0.001
Totally dependent versus independent functional status	2.697 (1.122, 6.481)	0.027
ASA ≥3 (severe or life-threatening disturbance) vs. ≤2 (no or mild disturbance)	1.232 (1.078, 1.408)	<0.0001
Optime (within one standard deviation from the mean) ^*	Ref	—
Optime (from one to two standard deviations from the mean)	0.941 (0.804, 1.101)	0.445
Optime (more than two standard deviation from the mean)	1.326 (1.027, 1.807)	0.032
Length of stay less than 2 days	0.830 (0.730, 0.943)	0.004
Medical Co-morbidities
Smoking (current smoker within 1 year)	1.181 (0.969, 1.441)	0.100
All diabetes	1.095 (0.937, 1.280)	0.254
Dyspnea at rest versus No dyspnea	0.855 (0.366,1999)	0.718
Dyspnea on exertion versus No dyspnea	1.197 (0.963, 1.488)	0.106
Chronic obstructive pulmonary disease	1.610 (1.307, 1.982)	<0.0001
Hypertension	1.216 (1.050, 1.408)	0.009
Bleeding disorder	1.608 (1.208, 2.140)	<0.0001
Presence of preoperative open wound	1.506 (0.839, 2.701)	0.170
Steroid use for chronic condition	1.246 (0.976, 1.591)	0.077
Procedure
Total shoulder arthroplasty	Ref	—
Shoulder hemiarthroplasty	1.060 (0.873, 1.287)	0.556
Total elbow arthroplasty	1.464 (1.029, 2.085)	0.034
Total wrist arthroplasty	2.463 (1.052, 5.765)	0.038

^*Mean = 111.81 min; standard deviation = 46.89 min.

Discussion

With the increasing emphasis on outcomes-driven ratings and reimbursement in the contemporary healthcare model, it is important for hospitals and physicians to identify the risk factors and potential mitigation strategies for readmissions. This study reveals that approximately one in 25 patients with upper or lower extremity arthroplasty will experience unplanned hospital readmission within 30-days of index surgery. Furthermore, the current results identify several modifiable risk factors for postoperative readmission rates, while also highlighting similarities and differences in these between lower and upper extremity arthroplasty.

For lower extremity arthroplasty procedures, age, sex, BMI, operative time, functional status, ASA Classification, length of stay, and specified medical comorbidities were identified as independent risk factors for readmission in our study. Previously, older age, male sex, higher BMI, and increased length of stay were found to be independently predictive of post-arthroplasty readmissions.^{7,16,18,22-26} This study found that a dependent functional status is an additional risk factor. Patients who are functionally dependent or admitted from a chronic care facility may be deconditioned or less mobile, potentially predisposing them to adverse clinical outcomes. A multidisciplinary care approach including discussion with patients and caregivers before and after surgery of their goals and anticipated post-operative rehabilitation plan may help reduce some unanticipated hospital readmissions.^27,28

Increased operative time was identified as an independent risk factor for readmission after lower and upper extremity arthroplasty. Longer operative time may be reflective of surgeon experience and/or volume, which have been previously shown to be risk factors.^18,29 Furthermore, operative time may also reflect the degree of surgical complexity which should be identified, discussed with the patient, and stratified in the outcomes-driven health care system.

The highest categories of BMI were identified as risk factors for readmission after lower extremity arthroplasty in the current study. However, there was no association between BMI and readmission for upper extremity arthroplasty. BMI has been previously identified as a risk factor in lower extremity arthroplasty for postoperative wound complications, infection, and readmissions,^30-33 but previous work in upper extremity arthroplasty have not found BMI to be a risk factor for readmission.^34,35 One explanation may be that higher BMI increases the risk of upper extremity arthroplasty failure from instability, which is a longer-term outcome that may not be represented in the 30-days readmission rate. In total shoulder arthroplasty, disproportionate truncal obesity and/or pannus formation alongside the increased extremity weight are thought to lead to an increased risk for implant loosening, instability or dislocation, and mechanical failure over time.^36-38 An interesting finding in our analysis was the protective setting of an overweight BMI, which was associate with a lower odds ratio of 30-days readmission compared to normal BMI in lower extremity arthroplasty. Previous studies have found decreased acute complication rates following total hip arthroplasty and have termed this the “obesity paradox”.^39,40 Our results assessing 30-days readmission rates in lower extremity arthroplasty show a similar finding, and further studies are needed to decipher the exact reasoning for this.

One possible explanation for the difference between risk factors for upper and lower extremity arthroplasty readmissions is the cause for readmission. Medical complications such as deep vein thrombosis or pneumonia cause the majority of readmissions after total shoulder arthroplasty, with surgical complications such as infection or dislocation responsible for a minority (18%–33%) of readmissions.^14,41 Interestingly we found that diabetes was a risk factor for readmission following lower extremity arthroplasty, but not upper extremity arthroplasty. This is consistent with other published studies which have shown diabetes as a risk factor for readmission following total hip and knee arthroplasty⁴² but not following total elbow or shoulder arthroplasty.^43,44 The exact reasoning for this finding is unclear and further studies are needed to better define the role of diabetes, perioperative glucose control, and target thresholds for hemoglobin A1c on readmission after joint arthroplasty.

Limitations of this study are primarily due to the selected information available through the NSQIP database. Data on the health and functional status among readmitted patients was not consistently reflected, as there may be some readmissions for rehabilitation given that dependent functional status was found to be independent risk factors. In turn, differences between the specific arthroplasty procedures in individual length of stay and rehabilitation, as well as those that deviate from the norm, may impact readmission and represent an area of future study. Additionally, the severity and treatment of patients’ disease and comorbidities are unknown. The current database only tracks readmissions within 30 days of arthroplasty, so readmissions at more extended timepoints were not accounted for. Lastly, some of the differences in readmission rates may be related to the sample size and statistical power, as lower extremity arthroplasty occurs at an order of magnitude greater than those of the upper extremity.

Conclusion

This study represents the latest comparative analysis of 30-days readmission rates and independent risk factors for readmission following upper and lower arthroplasty. Nearly one in 25 patients undergoing upper and lower extremity arthroplasty experiences hospital readmission within 30-days of index surgery. There are several modifiable risk factors for 30-days hospital readmission shared by both lower and upper extremity arthroplasty including COPD and hypertension. Optimization of these medical comorbidities may mitigate the risk short-term readmission following joint arthroplasty procedures regardless of the arthroplasty type and improve overall cost effectiveness of perioperative surgical care.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Donald J Scholten

References

Maradit Kremers

Larson

Crowson

, et al. Prevalence of total hip and knee replacement in the united states. J Bone Jt Surg Am 2015; 97: 1386–1397. DOI: 10.2106/JBJS.N.01141

Singh

Chen

, et al. Rates of total joint replacement in the united states: future projections to 2020-2040 using the national inpatient sample. J Rheumatol 2019; 46: 1134–1140. DOI: 10.3899/jrheum.170990.2019/04/17.

Sloan

Premkumar

Sheth

. Projected volume of primary total joint arthroplasty in the US, 2014 to 2030. J Bone Jt Surg Am 2018; 100: 1455–1460. DOI: 10.2106/JBJS.17.01617.2018/09/05.

Best

Aziz

Wilckens

, et al. Increasing incidence of primary reverse and anatomic total shoulder arthroplasty in the United States. J Shoulder Elbow Surg 2020; 30(5): 1159–1166. DOI: 10.1016/j.jse.2020.08.010.2020/08/29.

Day

Lau

Ong

, et al. Prevalence and projections of total shoulder and elbow arthroplasty in the United States to 2015. J Shoulder Elbow Surg 2010; 19: 1115–1120. DOI: 10.1016/j.jse.2010.02.009

Mahoney

Bosco

3rd Zuckerman

. Readmission after shoulder arthroplasty. J Shoulder Elbow Surg 2014; 23: 377–381. DOI: 10.1016/j.jse.2013.08.007

Zmistowski

Restrepo

Hess

, et al. Unplanned readmission after total joint arthroplasty: rates, reasons, and risk factors. J Bone Jt Surg Am 2013; 95: 1869–1876. DOI: 10.2106/JBJS.L.00679

Clement

Gray

Kheir

, et al.

Will medicare readmission penalties motivate hospitals to reduce arthroplasty readmissions?

J Arthroplasty 2016; 32(3): 709–713. DOI: 10.1016/j.arth.2016.08.031

Ban

Cohen

, et al. Evaluation of the propublica surgeon scorecard “adjusted complication rate” measure specifications. Ann Surg 2016; 264: 566–574. DOI: 10.1097/SLA.0000000000001858

10.

Graham

Prvu Bettger

Fisher

, et al. Duration to admission and hospital transfers affect facility rankings from the postacute 30-day rehospitalization quality measure. Health Serv Res 2016; 52(3): 1024–1039. DOI: 10.1111/1475-6773.12526

11.

Molina

Thakore

Blumer

, et al. Use of the national surgical quality improvement program in orthopaedic surgery. Clin Orthop Relat Res 2015; 473: 1574–1581. DOI: 10.1007/s11999-014-3597-7.2014/04/08.

12.

Hall

Hamilton

Richards

, et al. Does surgical quality improve in the American college of surgeons national surgical quality improvement program: an evaluation of all participating hospitals. Ann Surg 2009; 250: 363–376. DOI: 10.1097/SLA.0b013e3181b4148f

13.

Fuchshuber

Greif

Tidwell

, et al. The power of the national surgical quality improvement program--achieving a zero pneumonia rate in general surgery patients. Perm J 2012; 16: 39–45.

14.

Baker

Woods

, et al. Risk factors for early readmission after anatomical or reverse total shoulder arthroplasty. Am J Orthop (Belle Mead Nj) 2016; 45: E386–E392.

15.

Sibia

Mandelblatt

Callanan

, et al. Incidence, risk factors, and costs for hospital returns after total joint arthroplasties. J Arthroplasty 2016; 32(2): 381–385. DOI: 10.1016/j.arth.2016.08.003

16.

Schairer

Vail

Bozic

. What are the rates and causes of hospital readmission after total knee arthroplasty? Clin Orthop Relat Res 2014; 472: 181–187. DOI: 10.1007/s11999-013-3030-7

17.

Paxton

Torres

Love

, et al. Total joint replacement: a multiple risk factor analysis of physical activity level 1-2 years postoperatively. Acta Orthop 2016; 87(Suppl 1): 44–49. DOI: 10.1080/17453674.2016.1193663

18.

Paxton

Inacio

Singh

, et al.

Are there modifiable risk factors for hospital readmission after total hip arthroplasty in a US healthcare system?

Clin Orthop Relat Res 2015; 473: 3446–3455. DOI: 10.1007/s11999-015-4278-x

19.

Boraiah

Joo

Inneh

, et al. Management of modifiable risk factors prior to primary hip and knee arthroplasty: a readmission risk assessment tool. J Bone Jt Surg Am 2015; 97: 1921–1928. DOI: 10.2106/JBJS.N.01196

20.

Bovonratwet

Chen

Shen

, et al.

What are the reasons and risk factors for 30-day readmission after outpatient total hip arthroplasty?

J Arthroplasty 2020; 36(7S): S258–S263.e1. DOI: 10.1016/j.arth.2020.10.011.2020/11/10.

21.

Fang

Noiseux

Linson

, et al. The effect of advancing age on total joint replacement outcomes. Geriatr Orthop Surg Rehabil 2015; 6: 173–179. DOI: 10.1177/2151458515583515.2015/09/04.

22.

Avram

Petruccelli

Winemaker

, et al. Total joint arthroplasty readmission rates and reasons for 30-day hospital readmission. J Arthroplasty 2014; 29: 465–468. DOI: 10.1016/j.arth.2013.07.039

23.

Schairer

Sing

Vail

, et al. Causes and frequency of unplanned hospital readmission after total hip arthroplasty. Clin Orthop Relat Res 2014; 472: 464–470. DOI: 10.1007/s11999-013-3121-5

24.

Clement

Derman

Graham

, et al. Risk factors, causes, and the economic implications of unplanned readmissions following total hip arthroplasty. J Arthroplasty 2013; 28: 7–10. DOI: 10.1016/j.arth.2013.04.055

25.

Zhan

Kaczmarek

Loyo-Berrios

, et al. Incidence and short-term outcomes of primary and revision hip replacement in the United States. J Bone Jt Surg Am 2007; 89: 526–533. DOI: 10.2106/JBJS.F.00952

26.

Saucedo

Marecek

Wanke

, et al.

Understanding readmission after primary total hip and knee arthroplasty: who’s at risk?

J Arthroplasty 2014; 29: 256–260. DOI: 10.1016/j.arth.2013.06.003

27.

Stranges

Marshall

Walker

, et al. A multidisciplinary intervention for reducing readmissions among older adults in a patient-centered medical home. Am J Manag Care 2015; 21: 106–113.

28.

Bradley

Curry

Horwitz

, et al. Hospital strategies associated with 30-day readmission rates for patients with heart failure. Circ Cardiovasc Qual Outcomes 2013; 6: 444–450. DOI: 10.1161/CIRCOUTCOMES.111.000101

29.

Bozic

Maselli

Pekow

, et al. The influence of procedure volumes and standardization of care on quality and efficiency in total joint replacement surgery. J Bone Jt Surg Am 2010; 92: 2643–2652. DOI: 10.2106/JBJS.I.01477

30.

Eka

Chen

. Patient-related medical risk factors for periprosthetic joint infection of the hip and knee. Ann Transl Med 2015; 3: 233. DOI: 10.3978/j.issn.2305-5839.2015.09.26

31.

Kunutsor

Whitehouse

Blom

, et al. Patient-related risk factors for periprosthetic joint infection after total joint arthroplasty: a systematic review and meta-analysis. PLoS One 2016; 11: e0150866. DOI: 10.1371/journal.pone.0150866

32.

Namba

Inacio

Paxton

. Risk factors associated with deep surgical site infections after primary total knee arthroplasty: an analysis of 56,216 knees. J Bone Jt Surg Am 2013; 95: 775–782. DOI: 10.2106/JBJS.L.00211

33.

Pugely

Callaghan

Martin

, et al. Incidence of and risk factors for 30-day readmission following elective primary total joint arthroplasty: analysis from the ACS-NSQIP. J Arthroplasty 2013; 28: 1499–1504. DOI: 10.1016/j.arth.2013.06.032

34.

Richards

Inacio

Beckett

, et al. Patient and procedure-specific risk factors for deep infection after primary shoulder arthroplasty. Clin Orthop Relat Res 2014; 472: 2809–2815. DOI: 10.1007/s11999-014-3696-5

35.

Singh

Sperling

Schleck

, et al. Periprosthetic infections after total shoulder arthroplasty: a 33-year perspective. J Shoulder Elbow Surg 2012; 21: 1534–1541. DOI: 10.1016/j.jse.2012.01.006

36.

Gupta

Chalmers

Rahman

, et al. Reverse total shoulder arthroplasty in patients of varying body mass index. J Shoulder Elbow Surg 2014; 23: 35–42. DOI: 10.1016/j.jse.2013.07.043

37.

Werner

Burrus

Browne

, et al. Superobesity (body mass index >50 kg/m2) and complications after total shoulder arthroplasty: an incremental effect of increasing body mass index. J Shoulder Elbow Surg 2015; 24: 1868–1875. DOI: 10.1016/j.jse.2015.05.046

38.

Baghdadi

Veillette

Malone

, et al. Total elbow arthroplasty in obese patients. J Bone Jt Surg Am 2014; 96: e70. DOI: 10.2106/JBJS.M.00364

39.

Smith

Shahien

Chung

, et al. The obesity paradox: body mass index complication rates vary by gender and age among primary total hip arthroplasty patients. J Arthroplasty 2020; 35: 2658–2665. DOI: 10.1016/j.arth.2020.04.094 2020/06/03.

40.

Gurunathan

Anderson

Berry

, et al. Body mass index and in-hospital postoperative complications following primary total hip arthroplasty. Hip Int 2018; 28: 613–621. DOI: 10.1177/1120700017754058.2018/05/08.

41.

Schairer

Zhang

Feeley

. Hospital readmissions after primary shoulder arthroplasty. J Shoulder Elbow Surg 2014; 23: 1349–1355. DOI: 10.1016/j.jse.2013.12.004

42.

Middleton

Haas

, et al. Impact of diabetes on 90-day episodes of care after elective total joint arthroplasty among medicare beneficiaries. J Bone Jt Surg Am 2020; 102(24): 2157–2165. DOI: 10.2106/JBJS.20.00203.2020/10/24.

43.

Cutler

Collett

Farahani

, et al. Thirty-day readmissions and reoperations after total elbow arthroplasty: a national database study. J Shoulder Elbow Surg 2020; 30(2): e41–e49. DOI: 10.1016/j.jse.2020.06.033.2020/07/15.

44.

Boddapati

Dines

, et al. The impact of insulin dependence on short-term postoperative complications in diabetic patients undergoing total shoulder arthroplasty. J Shoulder Elbow Surg 2017; 26: 2091–2096. DOI: 10.1016/j.jse.2017.05.027.2017/07/26.

Shared and unique risk factors for readmission exist following upper and lower extremity arthroplasty in the 30-day postoperative period

Abstract

Purpose

Methods

Results

Conclusion

Keywords

Introduction

Methods

Results

Discussion

Conclusion

Footnotes

Declaration of conflicting interests

Funding

ORCID iD

References