The Risk Assessment and Prediction Tool (RAPT) after Hip and Knee Replacement: A Systematic Review

Predictors of Discharge Home Versus Inpatient Rehabilitation Following Total Hip and Knee Arthroplasty-Cohort Study

BACKGROUND

This study aims to identify the prevalence of inpatient rehabilitation (IPR) use in an Australian private total joint arthroplasty (TJA) cohort and to identify factors predictive of IPR discharge, including components of the Risk Assessment and Prediction Tool (RAPT).

METHODS

Primary TJA patients at a Sydney private hospital, between 2021 and 2022 were identified from an institutional arthroplasty database. Variables previously deemed as predictive factors for IPR facility discharge in the literature and components of RAPT were assessed utilising multivariable generalised linear model analysis.

RESULTS

Of the 733 total hip arthroplasty (THA) and 776 total knee arthroplasty (TKA) patients included, 46% of THA and 64% of TKA subjects transferred to IPR post-acutely. Bilateral procedure (OR 7.91, p < 0.001), living alone (OR 5.23, p < 0.001), older age groups (66-75 (OR 2.14, p = 0.001)); (> 75 (OR 5.02, p < 0.001)), poorer walking distance (1-2 blocks (OR 1.64, p = 0.023)); (housebound (OR 2.68, p = 0.009)), were significant predictors of IPR following THA. In the TKA cohort, the significant predictors of IPR discharge were female (OR 2.47, p < 0.001), older age (66-75 (OR 1.73, p = 0.021)); (> 75 (OR 4.23, p < 0.001)), bilateral procedure (OR 6.86, p < 0.001), obesity (OR 1.76, p = 0.006), living alone (OR 2.86, p = 0.001) and surgeon (surgeon 3 (OR 2.30, p = 0.024)); (surgeon 4 (OR 3.04, p = 0.003)); (surgeon 5 (OR 2.18, p = 0.046)).

CONCLUSION

The use of IPR following TJA was associated with some clinically justifiable factors, such as bilateral procedure, older age, and living alone. However, other variables may be driven by inappropriate and potentially modifiable societal expectations, such as being female, obesity, treating surgeon, and limited walking distance.

Risk assessment model used to predict discharge care after total hip and total knee arthroplasty: A population-based study

Background

Transfer to a post-acute care facility or hospital readmission after total joint arthroplasty represent additional costs and increased surgical and health care resource utilization. Accurate prediction of post-acute care factors could help providers to plan the patient's discharge destination and have a positive impact on postoperative outcomes and readmission rates.

Objective

To develop a risk assessment model to predict discharge care after total hip arthroplasty (THA) and total knee arthroplasty (TKA).

Design

A retrospective longitudinal observational study.

Settings

and participants: This study included 209 patients who underwent primary unilateral THA or TKA at a major academic medical center in Switzerland from January 2018 to December 2019.

Methods

A collection of computerized- and paper-recorded data identified the discharge destination, socio-demographic factors, comorbidities, and other factors related to the patient. Univariate and multivariate analyses were performed to describe the predictors of post-surgical discharge destinations.

Results

The characteristics associated with post-acute care after primary unilateral THA or TKA were the absence of a caregiver, advanced age, female gender, presence of walking aids, high ASA score, and comorbidity severity. A prediction model demonstrated that these six characteristics were associated 52 % with discharge to a post-acute care destination.

Conclusions

This study allowed us to identify predictors of discharge to a post-surgical destination. Predictive models can be efficiently used to better predict which patients are predisposed to post-acute care after hospital discharge. Further studies are needed to determine the optimal criteria for different destinations.

Sex Differences in Complications Following Total Hip Arthroplasty: A Population-Based Study

BACKGROUND

The relationship between sex and outcomes, especially complications, after total hip arthroplasty (THA) has not been well established. This study aimed to identify if patient biological sex significantly impacted complications after THA in Ontario, Canada.

METHODS

A population-based retrospective cohort study of patients undergoing primary THA in Ontario from April 1, 2015 to March 31, 2020 was conducted. The primary outcome was major surgical complications within a year postsurgery (a composite of revision, deep infection requiring surgery, and dislocation). Secondary outcomes included the individual component of the composite primary outcome and major medical complications within 30 days. Proportional hazards regression calculated the adjusted hazards ratio for major surgical complications in men relative to women, adjusting for age, comorbidities, neighborhood income quintile, surgeon and hospital volume, and year of surgery.

RESULTS

A total of 67,077 patients (median age 68 years; 54.1% women) from 61 hospitals were included; women were older with a higher prevalence of frailty. Women had a higher rate of major surgical complications within 1 year of surgery compared to men (2.9 versus 2.5%, adjusted odds ratio 1.19, 95% confidence interval 1.08 to 1.33, P = .0009). Conversely, men had a higher risk for medical complications within 30 days (6.3 versus 2.7%, P < .001).

CONCLUSIONS

Observable sex disparities exist in post-THA complications; women face surgical complications predominantly, while medical complications are more prevalent in men. These insights can shape preoperative patient consultations.

LEVEL OF EVIDENCE

Level III.

The Effect of Preoperative Information and Education on the Clinical Outcome of Total Hip Arthroplasty: A Prospective, Randomized Trial

Introduction Preoperative patient information and education is an essential aspect of modern surgical care, particularly for patients undergoing total hip arthroplasty (THA). This prospective, randomized trial aimed to assess the effects of structured preoperative education and information on clinical outcomes in patients undergoing THA. Materials and methods A total of 102 patients were randomized into two groups: the intervention group (n = 51) receiving standardized preoperative information and education, and the control group (n = 51) receiving standard preoperative care without a formal educational component. Postoperative outcomes, including functionality, mobility, length of hospital stay (LOS), patient satisfaction, health-related quality of life, anxiety, depression and fear for surgery, were compared between the two groups. Results Both groups were comparable in baseline characteristics, including age, sex, body mass index (BMI), smoking status and alcohol consumption. The mean age was 66.3 years, mean BMI was 29.05 and 70.6% of participants were female. Patients in the intervention group had a shorter mean hospital stay (mean 4.9 days vs. 6.2 days, p=0.031). Mean preoperative modified Harris Hip Score (mHHS) was similar between the two groups (p = 0.866). However, one month postoperatively, mHHS was significantly higher in the intervention group compared to controls (74.06 versus 67.81, p = 0.046). The absolute change in European Quality of Life 5 Dimensions 5 Level (EQ-5D-5L) Index and EQ-5D-5L Visual Analogue Scale (VAS) score before and after THA was statistically significant (p = 0.021 and p = 0.042). Preoperative and postoperative depression was significantly lower in the intervention group, one day preoperatively, one day before discharge and one month postoperatively, as shown by the Hospital Anxiety and Depression Scale (HADS) (p = 0.026, p = 0.027 and p = 0.018 respectively). Conclusions This prospective, randomized trial demonstrated that preoperative education and information significantly improve clinical outcomes, duration of hospitalization, health-related quality of life and postoperative anxiety in patients undergoing THA. These findings underline the importance of incorporating structured educational programs into preoperative care protocols prior to THA for enhancing patient recovery and optimizing postoperative results.

Applying models of care for total hip and knee arthroplasty: External validation of a published predictive model to identify extended stay risk prior to lower-limb arthroplasty

OBJECTIVE

This study aimed to externally validate a reported model for identifying patients requiring extended stay following lower limb arthroplasty in a new setting.

DESIGN

External validation of a previously reported prognostic model, using retrospective data.

SETTING

Medium-sized hospital orthopaedic department, Australia.

PARTICIPANTS

Electronic medical records were accessed for data collection between Sep-2019 and Feb-2020 and retrospective data extracted from 200 randomly selected total hip or knee arthroplasty patients.

INTERVENTION

Participants received total hip or knee replacement between 2-Feb-16 and 4-Apr-19. This study was a non-interventional retrospective study.

MAIN MEASURES

Model validation was assessed with discrimination, calibration on both original and adjusted forms of the candidate model. Decision curve analysis was conducted on the outputs of the adjusted model to determine net benefit at a predetermined decision threshold (0.5).

RESULTS

The original model performed poorly, grossly overestimating length of stay with mean calibration of -3.6 (95% confidence interval -3.9 to -3.2) and calibration slope of 0.52. Performance improved following adjustment of the model intercept and model coefficients (mean calibration 0.48, 95% confidence interval 0.16 to 0.80 and slope of 1.0), but remained poorly calibrated at low and medium risk threshold and net benefit was modest (three additional patients per hundred identified as at-risk) at the a-priori risk threshold.

CONCLUSIONS

External validation demonstrated poor performance when applied to a new patient population and would provide limited benefit for our institution. Implementation of predictive models for arthroplasty should include practical assessment of discrimination, calibration and net benefit at a clinically acceptable threshold.

Use of The Risk Assessment and Prediction Tool to Predict Same-day Discharge After Primary Hip and Knee Arthroplasty

INTRODUCTION

The Risk Assessment and Prediction Tool (RAPT) is a preoperative screening tool developed to predict discharge disposition after total hip arthroplasty (THA) and total knee arthroplasty (TKA), but its predictive value for same-day discharge (SDD) has not been investigated. The aims of this study were (1) to assess RAPT's ability to predict SDD after primary THA and TKA and (2) to determine a cutoff RAPT score that may recognize patients appropriate for SDD.

METHODS

Data were retrospectively collected from patients undergoing primary THA and TKA at a single tertiary care center between February 2020 and May 2021. A receiver operating characteristic curve was generated to choose a cutoff value to screen for SDD. Logistic regression analysis was done to identify factors including age, BMI, or RAPT score that may be associated with SDD.

RESULTS

Three hundred sixty-one patients with preoperative RAPT scores were included in the analysis of whom 147 (42.6%) underwent SDD. A cutoff of ≥9 was identified for TKA and ≥11 for THA. RAPT had a predictive accuracy of only 66.7% for SDD, whereas the discharge plan documented in the preoperative note was 91.7% accurate.

DISCUSSION

Although there is a positive association between RAPT and SDD, it is not a useful screening tool given its low predictive accuracy.

Factors affecting the length of hospital stay for total knee arthroplasty in Japan: a retrospective study using the diagnosis procedure combination database

BACKGROUND

We aimed to evaluate the length of hospital stay following total knee arthroplasty to determine the impact of relevant factors using data from the Diagnosis Procedure Combination database.

METHODS

This was a retrospective observational study. The study cohort included 5,831 patients who had osteoarthritis of the knee and had undergone total knee replacement between February 2018 and October 2022 at 38 hospitals.

RESULTS

Multivariate analysis showed that the factors influencing the length of stay included: age (p < 0.001), height (p < 0.001), weight (p = 0.049), body mass index (p = 0.008), Barthel index (p < 0.001), method of anesthesia (p < 0.001), bone transplant (p = 0.010), timing of postoperative rehabilitation (p < 0.001), atrial fibrillation (p < 0.001), chronic pain (p < 0.001), and number of institutionally treated cases (p < 0.001) (r = 0.451, p < 0.001).

CONCLUSIONS

Shorter or longer hospital stays were found to be associated with the patients' background characteristics and facility-specific factors; these can lead to more accurate estimates of the length of hospital stay and appropriate allocation of resources.

Machine Learning-Based Predictive Models for 90-Day Readmission of Total Joint Arthroplasty Using Comprehensive Electronic Health Records and Patient-Reported Outcome Measures

Background

The Centers for Medicare & Medicaid Services currently incentivizes hospitals to reduce postdischarge adverse events such as unplanned hospital readmissions for patients who underwent total joint arthroplasty (TJA). This study aimed to predict 90-day TJA readmissions from our comprehensive electronic health record data and routinely collected patient-reported outcome measures.

Methods

We retrospectively queried all TJA-related readmissions in our tertiary care center between 2016 and 2019. A total of 104-episode care characteristics and preoperative patient-reported outcome measures were used to develop several machine learning models for prediction performance evaluation and comparison. For interpretability, a logistic regression model was built to investigate the statistical significance, magnitudes, and directions of associations between risk factors and readmission.

Results

Given the significant imbalanced outcome (5.8% of patients were readmitted), our models robustly predicted the outcome, yielding areas under the receiver operating characteristic curves over 0.8, recalls over 0.5, and precisions over 0.5. In addition, the logistic regression model identified risk factors predicting readmission: diabetes, preadmission medication prescriptions (ie, nonsteroidal anti-inflammatory drug, corticosteroid, and narcotic), discharge to a skilled nursing facility, and postdischarge care behaviors within 90 days. Notably, low self-reported confidence to carry out social activities accurately predicted readmission.

Conclusions

A machine learning model can help identify patients who are at substantially increased risk of a readmission after TJA. This finding may allow for health-care providers to increase resources targeting these patients. In addition, a poor response to the "social activities" question may be a useful indicator that predicts a significant increased risk of readmission after TJA.

Preoperative Education Prior to Hip or Knee Arthroplasty Is Associated With Home Discharge but Not Reduced Length of Stay

Background

Increasing numbers of patients are undergoing total joint arthroplasty as a treatment for osteoarthritis, which can be an anxiety-provoking experience. Setting expectations through a preoperative physical therapy (pre-op PT) session can alleviate some of these stressors, potentially decrease hospital length of stay (LOS), and promote home discharge.

Purpose

We sought to determine whether attending a pre-op PT session is associated with decreased hospital LOS and home discharge in total hip arthroplasty (THA) and total knee arthroplasty (TKA) patients.

Methods

A retrospective cohort study was performed of 20,822 patients who underwent THA or TKA between January 2020 and December 2023. Pre-op PT attendance and covariates, including patient demographics and clinical data, were collected and analyzed for association with LOS and discharge disposition.

Results

Unadjusted univariate analysis revealed that THA and TKA patients who received pre-op PT had a significantly lower average LOS and were more likely to be discharged home. Our multivariate regression model showed that pre-op PT was not significantly associated with LOS in both groups but was significantly associated with home discharge among THA patients.

Conclusions

Our retrospective study of the effect of pre-op PT education on LOS and discharge disposition for elective THA and TKA patients found different results in univariate and multivariate analysis. Further study is needed to confirm the association found on multivariate analysis between pre-op PT and home discharge in THA patients.

Scaled TelePhysical Therapy Program a Promising Option for Post-acute Care of Lower-Extremity Arthroplasty Patients

Background

Post-acute care for orthopedic surgery patients continues to evolve with the reduction in hospital length of stay (LOS), shift to ambulatory surgery, increased number of surgeries, and focus on value-based care.

Purpose

We sought to examine outcomes of a cohort of lower-extremity arthroplasty patients receiving telephysical therapy (TelePT) according to hospital LOS, as a means of exploring the viability of TelePT as a value-based discharge option.

Methods

A retrospective review was conducted of patients who participated in our institution's HSS@Home TelePT program after undergoing primary unilateral hip or knee arthroplasty, unicondylar knee replacement, or hip resurfacing. Demographic data and outcomes such as hospital LOS, number of days between discharge and TelePT evaluation, number of TelePT visits, number of re-admissions, Hip dysfunction and Osteoarthritis Outcome (HOOS Jr.) or Knee injury and Osteoarthritis Outcome (KOOS Jr.) scores, and patient satisfaction scores were collected. Patients were divided into categories based on hospital LOS to help determine the versatility of program.

Results

In the 2814 patients included, we observed an average of 4.1 TelePT visits; 1% of patients were readmitted within 90 days, and 97% of patients were satisfied or highly satisfied. There was no difference in HOOS or KOOS Jr. scores at each follow-up time point, except for the 6-month HOOS Jr. scores.

Conclusion

This retrospective study suggests that TelePT may be a viable option for care of lower-extremity arthroplasty patients in the post-acute setting, regardless of hospital LOS. As a discharge option, it may meet the needs of select patients to fill a gap in providing value-based care.

RAPT and AM-PAC "6-Clicks": Do They Correlate on Predicting Discharge Destination After Total Joint Arthroplasty?

Background: The Risk Assessment and Prediction Tool (RAPT) and the Activity Measure for Post-Acute Care "6-Clicks" Mobility Score (AM-PAC) are validated discharge planning tools for patients undergoing total hip arthroplasty (THA) and total knee arthroplasty (TKA). Planning for discharge with these tools considers very different factors and it is important to determine if they relate. Purpose: We sought to determine whether the preoperative RAPT score would correlate with postoperative AM-PAC score for predicting discharge destination for THA and TKA populations. Secondarily, we sought to examine whether the AM-PAC and RAPT scores would remain statistically significant predictors of discharge destination despite covariates. Methods: A retrospective cohort study was performed for patients who underwent THA or TKA from January 2020 to December 2022 at a specialty orthopedic hospital. Primary variables included the RAPT score, the AM-PAC score, and discharge disposition. Correlation between AM-PAC and RAPT scores was tested using Pearson's correlation coefficient, and association between both scores and discharge destination was tested using chi-square tests and multivariable logistic regression. Results: Our comparison of AM-PAC scores and RAPT scores found a statistically significant, positive correlation in both THA and TKA patients. Regression analysis found that increased RAPT and AM-PAC scores resulted in higher odds of being discharged home for both populations, after adjusting for all other variables. In both cohorts, patients discharged to a facility were more likely to be female, be over the age of 70 years, have Medicare/Medicaid insurance, and have a higher number of preoperative social work visits or any incidence of an intraoperative or hospital complication. Conclusions: This retrospective study found that RAPT score correlated with AM-PAC score for predicting discharge destination for elective THA and TKA populations, suggesting that these scores may be predictors of home discharge destination even when accounting for covariates. Further study is recommended.

Identifying Preoperative Predictors for 24-Hour Discharge After Elective Hip and Knee Arthroplasties

Introduction The resumption of elective medical services post-pandemic has brought to the forefront the importance of outpatient arthroplasty services in promoting efficiency and mitigating hospital-acquired infections. This study aimed to identify preoperative factors that predict the success of outpatient lower limb arthroplasty surgeries. Methods Our investigation involved a retrospective review of 606 patients who underwent elective hip and knee arthroplasty. We documented variables such as the hospital length of stay, patient demographics (age and gender), Oxford Joint Scores, body mass index, socioeconomic status, American Society of Anaesthesiologists' (ASA) physical status classification, comorbid conditions, the Functional Comorbidity Index (FCI), preoperative blood test results, implant types, scheduling details of the surgery, and rates of readmission within 30 days post-surgery. A two-step analysis using univariate and multivariate regression models was performed to pinpoint preoperative indicators that could predict same-day discharge following arthroplasty. Results Forty-five patients (7.4%) were discharged within 24 hours of surgery. Early discharge did not correlate with higher rates of readmission within 30 days (p>0.05). Neither weekend nor afternoon surgeries significantly extended the length of stay beyond 24 hours (p>0.05). No significant differences in the prevalence of comorbidities, FCI scores, socioeconomic status, or preoperative blood test results were found when comparing patients discharged within 24 hours to those who stayed longer. Multivariate analysis revealed that patients younger than 65 years (relative risk (RR) 2.41; 95% confidence interval (CI) 1.02-5.74) and those receiving partial knee arthroplasty (RR 8.91; 95% CI 3.05-26.04) were more likely to be discharged within 24 hours. Conclusions Outpatient arthroplasty is a viable option, especially for individuals younger than 65 years undergoing partial knee arthroplasty, independent of other patient-related factors, comorbidities, and specifics of the hospital episode.

Identifying strategies that support equitable person-centred osteoarthritis care for diverse women: content analysis of guidelines

INTRODUCTION

Women are disproportionately impacted by osteoarthritis (OA) but less likely than men to access early diagnosis and management, or experience OA care tailored through person-centred approaches to their needs and preferences, particularly racialized women. One way to support clinicians in optimizing OA care is through clinical guidelines. We aimed to examine the content of OA guidelines for guidance on providing equitable, person-centred care to disadvantaged groups including women.

METHODS

We searched indexed databases and websites for English-language OA-relevant guidelines published in 2000 or later by non-profit organizations. We used manifest content analysis to extract data, and summary statistics and text to describe guideline characteristics, person-centred care (PCC) using a six-domain PCC framework, OA prevalence or barriers by intersectional factors, and strategies to improve equitable access to OA care.

RESULTS

We included 36 OA guidelines published from 2003 to 2021 in 8 regions or countries. Few (39%) development panels included patients. While most (81%) guidelines included at least one PCC domain, guidance was often brief or vague, few addressed exchange information, respond to emotions and manage uncertainty, and none referred to fostering a healing relationship. Few (39%) guidelines acknowledged or described greater prevalence of OA among particular groups; only 3 (8%) noted that socioeconomic status was a barrier to OA care, and only 2 (6%) offered guidance to clinicians on how to improve equitable access to OA care: assess acceptability, availability, accessibility, and affordability of self-management interventions; and employ risk assessment tools to identify patients without means to cope well at home after surgery.

CONCLUSIONS

This study revealed that OA guidelines do not support clinicians in caring for diverse persons with OA who face disadvantages due to intersectional factors that influence access to and quality of care. Developers could strengthen OA guidelines by incorporating guidance for PCC and for equity that could be drawn from existing frameworks and tools, and by including diverse persons with OA on guideline development panels. Future research is needed to identify multi-level (patient, clinician, system) strategies that could be implemented via guidelines or in other ways to improve equitable, person-centred OA care.

PATIENT OR PUBLIC CONTRIBUTION

This study was informed by a team of researchers, collaborators, and thirteen diverse women with lived experience, who contributed to planning, and data collection, analysis and interpretation by reviewing study materials and providing verbal (during meetings) and written (via email) feedback.

Preoperative Prediction and Risk Factor Identification of Hospital Length of Stay for Total Joint Arthroplasty Patients Using Machine Learning

Background

The aim of this study was to improve understanding of hospital length of stay (LOS) in patients undergoing total joint arthroplasty (TJA) in a high-efficiency, hospital-based pathway.

Methods

We retrospectively reviewed 1401 consecutive primary and revision TJA patients across 67 patient and preoperative care characteristics from 2016 to 2019 from the institutional electronic health records. A machine learning approach, testing multiple models, was used to assess predictors of LOS.

Results

The median LOS was 1 day; outpatients accounted for 16.5%, 1-day inpatient stays for 38.0%, 2-day stays for 26.4%, and 3-days or more for 19.1%. Patients characteristically fell into 1 of 3 broad categories that contained relatively similar characteristics: outpatient (0-day LOS), short stay (1- to 2-day LOS), and prolonged stay (3 days or greater). The random forest models suggested that a lower Risk Assessment and Prediction Tool score, unplanned admission or hospital transfer, and a medical history of cardiovascular disease were associated with an increased LOS. Documented narcotic use for surgery preparation prior to hospitalization and preoperative corticosteroid use were factors independently associated with a decreased LOS.

Conclusions

After TJA, most patients have either an outpatient or short-stay hospital episode. Patients who stay 2 days do not differ substantially from patients who stay 1 day, while there is a distinct group that requires prolonged admission. Our machine learning models support a better understanding of the patient factors associated with different hospital LOS categories for TJA, demonstrating the potential for improved health policy decisions and risk stratification for centers caring for complex patients.

Patient-rated satisfaction and improvement following hip and knee replacements: Development of prediction models

RATIONALE

Effective preoperative assessments of determinants of health status and function may improve postoperative outcomes.

AIMS AND OBJECTIVES

We developed risk scores of preoperative patient factors and patient-reported outcome measures (PROMs) as predictors of patient-rated satisfaction and improvement following hip and knee replacements.

PATIENTS AND METHODS

Prospectively collected National Health Service and independent sector patient data (n = 30,457), including patients' self-reported demographics, comorbidities, PROMs (Oxford Hip/Knee score (OHS/OKS) and European Quality of Life (EQ5D index and health-scale), were analysed. Outcomes were defined as patient-reported satisfaction and improvement following surgery at 7-month follow-up. Univariable and multivariable-adjusted logistic regressions were undertaken to build prediction models; model discrimination was evaluated with the concordance index (c-index) and nomograms were developed to allow the estimation of probabilities.

RESULTS

Of the 14,651 subjects with responses for satisfaction following hip replacements 564 (3.8%) reported dissatisfaction, and 1433 (9.2%) of the 15,560 following knee replacement reported dissatisfaction. A total of 14,662 had responses for perceived improvement following hip replacement (lack of improvement in 391; 2.7%) and 15,588 following knee replacement (lack of improvements in 1092; 7.0%). Patients reporting poor outcomes had worse preoperative PROMs. Several factors, including age, gender, patient comorbidities and EQ5D, were included in the final prediction models: C-indices of these models were 0.613 and 0.618 for dissatisfaction and lack of improvement, respectively, for hip replacement and 0.614 and 0.598, respectively, for knee replacement.

CONCLUSIONS

Using easily accessible preoperative patient factors, including PROMs, we developed models which may help predict dissatisfaction and lack of improvement following hip and knee replacements and facilitate risk stratification and decision-making processes.

Predictive Models for Length of Stay and Discharge Disposition in Elective Spine Surgery: Development, Validation, and Comparison to the ACS NSQIP Risk Calculator

STUDY DESIGN

A retrospective study at a single academic institution.

OBJECTIVE

The purpose of this study is to utilize machine learning to predict hospital length of stay (LOS) and discharge disposition following adult elective spine surgery, and to compare performance metrics of machine learning models to the American College of Surgeon's National Surgical Quality Improvement Program's (ACS NSQIP) prediction calculator.

SUMMARY OF BACKGROUND DATA

A total of 3678 adult patients undergoing elective spine surgery between 2014 and 2019, acquired from the electronic health record.

METHODS

Patients were divided into three stratified cohorts: cervical degenerative, lumbar degenerative, and adult spinal deformity groups. Predictive variables included demographics, body mass index, surgical region, surgical invasiveness, surgical approach, and comorbidities. Regression, classification trees, and least absolute shrinkage and selection operator (LASSO) were used to build predictive models. Validation of the models was conducted on 16% of patients (N=587), using area under the receiver operator curve (AUROC), sensitivity, specificity, and correlation. Patient data were manually entered into the ACS NSQIP online risk calculator to compare performance. Outcome variables were discharge disposition (home vs. rehabilitation) and LOS (days).

RESULTS

Of 3678 patients analyzed, 51.4% were male (n=1890) and 48.6% were female (n=1788). The average LOS was 3.66 days. In all, 78% were discharged home and 22% discharged to rehabilitation. Compared with NSQIP (Pearson R2 =0.16), the predictions of poisson regression ( R2 =0.29) and LASSO ( R2 =0.29) models were significantly more correlated with observed LOS ( P =0.025 and 0.004, respectively). Of the models generated to predict discharge location, logistic regression yielded an AUROC of 0.79, which was statistically equivalent to the AUROC of 0.75 for NSQIP ( P =0.135).

CONCLUSION

The predictive models developed in this study can enable accurate preoperative estimation of LOS and risk of rehabilitation discharge for adult patients undergoing elective spine surgery. The demonstrated models exhibited better performance than NSQIP for prediction of LOS and equivalent performance to NSQIP for prediction of discharge location.

Post-operative neurosurgery outcomes by race/ethnicity among enhanced recovery after surgery (ERAS) participants

OBJECTIVE

Prior work reveals that Enhanced Recovery After Surgery (ERAS) programs decrease opioid use, improve mobilization, and shorten length of stay (LOS) among patients undergoing spine surgery. The impact of ERAS on outcomes by race/ethnicity is unknown. This study examined outcomes by race/ethnicity among neurosurgical patients enrolled in an ERAS program.

METHODS

Patients undergoing elective spine or peripheral nerve surgeries at a multi-hospital university health system from April 2017 to November 2020 were enrolled in an ERAS program that involves preoperative, perioperative, and postoperative phases focused on improving outcomes through measures such as specialty consultations for co-morbidities, multimodal analgesia, early mobilization, and wound care education. The following outcomes for ERAS patients were compared by race/ethnicity: length of stay, discharge disposition, complications, readmission, pain level at discharge, and post-operative health rating. We estimated the association between race/ethnicity and the outcomes using linear and logistic regression models adjusting for age, sex, insurance, BMI, comorbid conditions, and surgery type.

RESULTS

Among participants (n = 3449), 2874 (83.3%) were White and 575 (16.7%) were Black, Indigenous, and people of color (BIPOC). BIPOC patients had significantly longer mean length of stay compared to White patients (3.8 vs. 3.4 days, p = 0.005) and were significantly more likely to be discharged to a rehab or subacute nursing facility compared to White patients (adjusted odds ratio (95% CI): 3.01 (2.26-4.01), p < 0.001). The complication rate did not significantly differ between BIPOC and White patients (13.7% vs. 15.5%, p = 0.29). BIPOC patients were not significantly more likely to be readmitted within 30 days compared to White patients in the adjusted model (adjusted odds ratio (95% CI): 1.30 (0.91-1.86), p = 0.15) CONCLUSION: BIPOC as compared to White ERAS participants in ERAS undergoing neurosurgical procedures had significantly longer hospital stays and were significantly less likely to be discharged home. ERAS protocols present an opportunity to provide consistent high quality post-operative care, however while there is evidence that it improves care in aggregate, our results suggest significant disparities in outcomes by patient race/ethnicity despite enrollment in ERAS. Future inquiry must identify contributors to these disparities in the recovery pathway.

Risk factors for extended length of stay and non-home discharge in adults treated with multi-level fusion for lumbar degenerative pathology and deformity

PURPOSE

To identify independent risk factors, including the Risk Assessment and Prediction Tool (RAPT) score, associated with extended length of stay (eLOS) and non-home discharge following elective multi-level instrumented spine fusion operations for diagnosis of adult spinal deformity (ASD) and lumbar degenerative pathology.

METHODS

Adults who underwent multi-level ([Formula: see text] segments) instrumented spine fusions for ASD and lumbar degenerative pathology at a single institution (2016-2021) were reviewed. Presence of a pre-operative RAPT score was used as an inclusion criterion. Excluded were patients who underwent non-elective operations, revisions, operations for trauma, malignancy, and/or infections. Outcomes were eLOS (> 7 days) and discharge location (home vs. non-home). Predictor variables included demographics, comorbidities, operative information, Surgical Invasiveness Index (SII), and RAPT score. Fisher's exact test was used for univariate analysis, and significant variables were implemented in multivariate binary logistic regression, with generation of 95% percent confidence intervals (CI), odds ratios (OR), and p-values.

RESULTS

Included for analysis were 355 patients. Post-operatively, 36.6% (n = 130) had eLOS and 53.2% (n = 189) had a non-home discharge. Risk factors significant for a non-home discharge were older age (> 70 years), SII > 36, pre-op RAPT < 10, DMII, diagnosis of depression or anxiety, and eLOS. Risk factors significant for an eLOS were SII > 20, RAPT < 6, and an ASA score of 3.

CONCLUSION

The RAPT score and SII were most important significant predictors of eLOS and non-home discharges following multi-level instrumented fusions for lumbar spinal pathology and deformity. Preoperative optimization of the RAPT's individual components may provide a useful strategy for decreasing LOS and modifying discharge disposition.

RAPT Scores Predict Inpatient Versus Outpatient Status and Readmission Rates After IPO Changes for Total Joint Arthroplasty: An Analysis of 12,348 Cases

BACKGROUND

Changes to Medicare's Inpatient Only List (IPO) and factors associated with the COVID pandemic have led to more total joint arthroplasty (TJA) patients to be designated as outpatient (OP). This potentially complicates postoperative care for patients with lower functional status and poor social support. These factors make the decision between OP versus inpatient (IP) designation particularly challenging for healthcare teams. The Risk Assessment and Prediction Tool (RAPT) was designed to indicate patient risk for needing posthospital discharge to facility and considers social and functional factors. The purpose of this study is to 1) evaluate the correlation of RAPT as a clinical tool to aid decision-making regarding OP versus IP for Total Hip and Knee Arthroplasty (THA and TKA), 2) assess the impact of recent changes to the IPO and the COVID pandemic on OP TJA readmission rates, and 3) determine whether 90-day readmissions are correlated with RAPT scores after OP TJA.

METHODS

We identified all elective TKA and THA patients from 2015 through 2021 in our electronic health record at our large, urban, academic health system. Fracture patients were excluded. For those patients with available RAPT scores, we determined OP and IP designations, with IP defined as those with length-of-stay 2 midnights or more. We performed subanalysis of OP between same-day and next-day discharge. RAPT scores and readmission rates were compared at time points related to changes in the IPO: before TKA removal in 2018 (period A), from 2018 until THA removal in 2020 (Period B), and after January 1, 2020, inclusive of impact from the COVID pandemic (Period C).

RESULTS

Reviewed were 11,819 elective TKAs and 10,212 elective THAs. RAPT scores were available for 6,759 TKA patients and 5,589 THA patients. For both TKA and THA, RAPT scores between IP, same-day, and next-day discharged OP were significantly different across all time periods (P < .001). The percentage of OP designation increased across all time periods for TKA and THA. Over these same time periods, mean RAPT scores decreased significantly for both OP TKA and OP THA (P < .01). Concurrent with these changes were significant increases in OP THA 90-day readmission rates across Periods A and B (P = .010) as well as A and C (P = .006). Readmitted OP TKA had significantly lower RAPT scores than OP TKA without readmission during Period B (P < .001). Readmitted OP THA had significantly lower RAPT scores than those without readmission for all periods (P < .05). To facilitate clinical utility, median RAPT scores were also analyzed, and showed that RAPT scores for OP THA patients with readmission were 1 to 2 points lower for all time periods.

CONCLUSION

RAPT scores correlate with IP versus OP status for both TKA and THA and vary significantly with same-day versus next-day discharge. OP TJA RAPT scores may also help predict readmission, and counsel some patients away from OP surgery. Average RAPT scores of 10, 9, and 8 appeared to be separators for same day, next day, and inpatient stay. Changes to the IPO and COVID pandemic correlate with decrease in RAPT scores for both TKA and THA patients within all designations. In addition, a shift toward lower RAPT for OP TJA correlates with increased 90-day readmission rates for OP TJA. Taken together, these results suggest that patients with poorer function and worse social support systems are increasingly being driven toward OP surgery by these changes, which may play a role in increasing readmission rates. Social support and functional factors should be considered for OP elective TKA and THA. Further, any OP TJA value-based payment system must account for these variables.

Same Day Joint Replacement Surgery: Patient Selection and Perioperative Management

Joint replacements are increasingly performed as outpatient surgeries. The push toward ambulatory joint arthroplasty is driven in part by the changing current health care economics and reimbursement models. Patients' selection and well-designed perioperative care pathways are critical for the success of these procedures. The rate of complications after outpatient joint arthroplasty is comparable to the rate of complications in the ambulatory setting. Patient education, adequate social support, multimodal analgesia, regional anesthesia are key ingredients to the ambulatory care pathway after joint arthroplasty. Motor sparing nerve blocks are often used in these settings. Implementation of the elements of fast protocols can result in overall improvement of outcome metrics for all patients undergoing joint arthroplasty, including reduced length of stay and increased rate of home discharge.

Barriers, enablers and acceptability of home-based care following elective total knee or hip replacement at a private hospital: A qualitative study of patient and caregiver perspectives

Background

To facilitate implementation of home-based care following an elective total knee or hip replacement in a private hospital, we explored patient and caregiver barriers and enablers and components of care that may increase its acceptability.

Method

Thirty-one patients (mean age 71 years, 77% female) and 14 caregivers (mean age 69 years, 57% female) were interviewed. All themes were developed using thematic analysis, then categorised as barriers or enablers to uptake of home-based care or acceptable components of care. Barrier and enabler themes were mapped to the Theoretical Domains Framework.

Results

Eight themes emerged as barriers or enablers: feeling unsafe versus confident; caregivers’ willingness to provide support and patients’ unwillingness to seek help; less support and opportunity to rest; positive feelings about home over the hospital; certainty about anticipated recovery; trusting specialist advice over family and friends; length of hospital stay; paying for health insurance. Five themes emerged as acceptable components: home visits prior to discharge; specific information about recovery at home; one-to-one physiotherapy and occupational therapy perceived as first-line care; medical, nursing and a 24/7 direct-line perceived as second-line care for complications; no one-size-fits-all model for domestic support. Theoretical domains relating to barriers included emotion (e.g., feeling unsafe), environmental context and resources (e.g., perceived lack of physiotherapy) and beliefs about consequences (e.g., unwillingness to burden their caregiver). Theoretical domains relating to enablers included beliefs about capabilities (e.g., feeling strong), skills (e.g., practising stairs), procedural knowledge (e.g., receiving advice about early mobility) and social influences (e.g., caregivers’ willingness to provide support).

Conclusions

Multiple factors, such as feeling unsafe and caregivers’ willingness to provide support, may influence implementation of home-based care from the perspectives of privately insured patients and caregivers. Our findings provide insights to inform design of suitable home-based care following joint replacement in a private setting.

Development of a Machine Learning Algorithm to Predict Nonroutine Discharge Following Unicompartmental Knee Arthroplasty

BACKGROUND

Reliable and effective prediction of discharge destination following unicompartmental knee arthroplasty (UKA) can optimize patient outcomes and system expenditure. The purpose of this study is to develop a machine learning algorithm that can predict nonhome discharge in patients undergoing UKA.

METHODS

A retrospective review of a prospectively collected national surgical outcomes database was performed to identify adult patients who underwent UKA from 2015 to 2019. Nonroutine discharge was defined as discharge to a location other than home. Five machine learning algorithms were developed to predict this outcome. Performance of the algorithms was assessed through discrimination, calibration, and decision curve analysis.

RESULTS

Overall, of the 7275 patients included, 263 (3.6) patients were unable to return home upon discharge following UKA. The factors determined most important for identification of candidates for nonroutine discharge were total hospital length of stay, preoperative hematocrit, body mass index, preoperative sodium, American Society of Anesthesiologists classification, gender, and functional status. The extreme boosted model achieved the best performance based on discrimination (area under the curve = 0.875), calibration, and decision curve analysis. This model was integrated into a web-based open access application able to provide both predictions and explanations.

CONCLUSION

The present model can, following appropriate external validation, be used to augment clinician decision-making in patients undergoing elective UKA. Patients with high preoperative probabilities of nonroutine discharge based on nonmodifiable risk factors should be counseled to start the insurance authorization process with case management to avoid unnecessary inpatient stay, and those with modifiable risk can attempt prehabilitation to optimize these parameters before surgery.

Predictive Value of the Risk Assessment and Prediction Tool (RAPT) Score for Primary Hip and Knee Arthroplasty Patients: A Single-Center Study

The Risk Assessment and Prediction Tool (RAPT) was developed to predict patient discharge destination for arthroplasty operations. However, since Enhanced Recovery After Surgery (ERAS) programs have been utilized in the UK, the RAPT score has not been validated for use. The aim of the current study was to evaluate the predictive validity of the RAPT score in an ERAS environment with short length of stay. Data were compiled from 545 patients receiving a primary elective total hip or total knee arthroplasty in a district general hospital over 12 months. RAPT scores, length of stay, and discharge destinations were recorded. Patients were classified as low, intermediate, or high risk as per their RAPT score. Length of stay was significantly different between groups (p = 0.008), with low-risk patients having shorter length of stay. However, RAPT scores did not predict discharge destination; the overall correct prediction was only 31.9%. Furthermore, the most likely discharge destination was directly home in ≤3 days in all groups (68.5%, 60.2%, and 40% for the low-, intermediate-, and high-risk groups, respectively). The RAPT score is not an adequate tool to predict the discharge disposition following primary total knee and hip replacement surgery in a UK hospital with a standardized modern ERAS program. Alternative predictive tools are required.

Targeted rehabilitation may improve patient flow and outcomes: development and implementation of a novel Proactive Rehabilitation Screening (PReS) service

Rehabilitation programmes can be delivered to patients receiving acute care (‘in-reach rehabilitation’) and/or those who have completed acute care but experience ongoing functional impairments (‘subacute rehabilitation’). Access to these programmes depends on a rehabilitation assessment, but there are concerns that referrals for this assessment are often triggered too late in the acute care journey. We describe a Proactive Rehabilitation Screening (PReS) process designed to systematically screen patients during an acute hospital admission, and identify early those who are likely to require specialist rehabilitation assessment and intervention. The process is based on review of patient medical records on day 5 after acute hospital admission, or day 3 after transfer from intensive care to an acute hospital ward. Screening involves brief review of documented care needs, pre-existing and new functional disabilities, the need for allied health interventions and non-medical factors delaying discharge. From May 2017 to February 2019, the novel screening process was implemented as part of a service redesign of the rehabilitation consultation service. Four thousand consecutive screens were performed at the study site. Of those ‘ruled in’ by screening as needing a rehabilitation assessment, 86.0% went on to receive inpatient rehabilitation interventions. Of those ‘ruled out’ by screening, 92.1% did not go on to receive a rehabilitation intervention, while 7.9% did receive some form of rehabilitation intervention. Of all patients accepted into a rehabilitation programme (n=516), PReS was able to identify 53.6% (n=282) of them before the acute care teams made a referral (based on traditional criteria). In conclusion, we have designed and implemented a systematic, PReS service in one metropolitan Australian hospital. The process described was found to be time efficient and feasible to implement in an acute hospital setting. Further, it appeared to identify the majority of patients who went on to receive formal inpatient rehabilitation interventions.

Assessment tools and factors used to predict discharge from acute general medical wards: a systematic review

PURPOSE

To identify assessment tools and patient factors statistically associated with discharge destination in general medical inpatients.

MATERIALS AND METHOD

A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. Four electronic databases were searched. Studies were eligible if they were a quantitative study design, had adult acute general medical inpatients and published in English. Outcomes of interest were tools or factors with statistical correlations with discharge destination (home, subacute or residential care). Articles were screened by two independent assessors. Data were extracted by one reviewer and independently checked by a second reviewer. Data were analysed/described descriptively.

RESULTS

Twenty-three studies were included. Twenty-three tools and 44 factors were identified, which spanned Health Condition, Body Structure and Function, Activity, Participation, Environment and Personal concepts of the World Health Organisation International Classification of Function, Disability and Health (WHO ICF).

CONCLUSIONS

The large number of tools and factors found and their distribution across several WHO ICF concepts exemplifies the complexities of predicting discharge. No single assessment tool that best predicts discharge destination was identified, but rather there were a variety of potential tools identified. Further research is needed to determine the psychometric properties of the identified assessment tools as well as additional predictors of subacute care (including rehabilitation). This is important as it may allow for timely clinical decision making.

TRIAL REGISTRATION

A priori, PROSPERO (CRD42017064209).IMPLICATIONS FOR REHABILITATIONThis systematic review identified a large number of assessment tools and patient factors associated with discharge destination (home, subacute and residential care) in general medical inpatients.All of the domains of the WHO ICF framework are associated with discharge destination and must be considered.Clinicians in the acute setting can use these findings to assist selection of assessment tools to identify patients likely to need rehabilitation or subacute care.Early identification of patients who are unable to return to their place of residence is essential as it allows for provision of early rehabilitation and subsequent discharge planning.

Modifying the RAPT Score to Reflect Discharge Destination in Current Practice

Background

The Risk Assessment Prediction Tool (RAPT) is a validated 6-question survey designed to predict primary total joint arthroplasty (TJA) patients’ discharge disposition. It is scored from 1 to 12 with patients stratified into high-, intermediate-, and low-risk groups. Given recent advancements in rapid-discharge protocols and increasing utilization of home services, the RAPT score may require modified scoring cutoffs.

Methods

A retrospective chart review of all patients undergoing primary TJA at a single academic center over 14 months was performed. The RAPT score was implemented during the sixth month. Patients undergoing revision TJA, complex TJA, and TJA after resection of malignancy were excluded. Outcomes before and after RAPT implementation were analyzed with additional subanalysis investigating of post-RAPT data.

Results

A total of 1264 patients (624 Pre-RAPT and 640 Post-RAPT) were evaluated. The post-RAPT group (245 total hip arthroplasty and 395 total knee arthroplasty) experienced significant decreases in mean hospital length of stay (2.22 days pre-RAPT to 1.82 days post-RAPT, P < .001) and the proportion of patients discharged to facility (21.8% pre-RAPT to 15.2% post-RAPT, P = .002). The modified system demonstrated the highest overall predictive accuracy at 92% and was found to be predictive of hospital length of stay.

Conclusion

Owing to the recent trends favoring in-home services over rehab facility after discharge, previously published RAPT scoring cutoffs are inaccurate for modern practice. Using mRAPT cutoffs maximizes the number of patients for whom a discharge prediction can be made, while maintaining excellent predictive accuracy.

Effect of Remote Monitoring on Discharge to Home, Return to Activity, and Rehospitalization After Hip and Knee Arthroplasty: A Randomized Clinical Trial

Importance

Hip and knee arthroplasty are the most common inpatient surgical procedures for Medicare beneficiaries in the US, with substantial variation in cost and quality. Whether remote monitoring incorporating insights from behavioral science might help improve outcomes and increase value of care remains unknown.

Objective

To evaluate the effect of activity monitoring and bidirectional text messaging on the rate of discharge to home and clinical outcomes in patients receiving hip or knee arthroplasty.

Design, Setting, and Participants

Randomized clinical trial conducted between February 7, 2018, and April 15, 2019. The setting was 2 urban hospitals at an academic health system. Participants were patients aged 18 to 85 years scheduled to undergo hip or knee arthroplasty with a Risk Assessment and Prediction Tool score of 6 to 8.

Interventions

Eligible patients were randomized evenly to receive usual care (n = 153) or remote monitoring (n = 147). Those in the intervention arm who agreed received a wearable activity monitor to track step count, messaging about postoperative goals and milestones, pain score tracking, and connection to clinicians as needed. Patients assigned to receive monitoring were further randomized evenly to remote monitoring alone or remote monitoring with gamification and social support. Remote monitoring was offered before surgery, began at hospital discharge, and continued for 45 days postdischarge.

Main Outcomes and Measures

The primary outcome was discharge status (home vs skilled nursing facility or inpatient rehabilitation). Prespecified secondary outcomes included change in average daily step count and rehospitalizations.

Results

A total of 242 patients were analyzed (124 usual care, 118 intervention); median age was 66 years (interquartile range, 58-73 years); 78.1% were women, 45.5% were White, 43.4% were Black; and 81.4% in the intervention arm agreed to receive monitoring. There was no significant difference in the rate of discharge to home between the usual care arm (57.3%; 95% CI, 48.5%-65.9%) and the intervention arm (56.8%; 95% CI, 47.9%-65.7%) and no significant increase in step count in those receiving remote monitoring plus gamification and social support compared with remote monitoring alone. There was a statistically significant reduction in rehospitalization rate in the intervention arm (3.4%; 95% CI, 0.1%-6.7%) compared with the usual care arm (12.2%; 95% CI, 6.4%-18.0%) (P = .01).

Conclusions and Relevance

In this study, the remote monitoring program did not increase rate of discharge to home after hip or knee arthroplasty, and gamification and social support did not increase activity levels. There was a significant reduction in rehospitalizations among those receiving the intervention, which may have resulted from goal setting and connection to the care team.

Trial Registration

ClinicalTrials.gov Identifier: NCT03435549.

Which Patient Factors Best Predict Discharge Destination After Primary Total Knee Arthroplasty? The ARISE Trial

BACKGROUND

The role of inpatient rehabilitation after total knee arthroplasty (TKA) remains uncertain, with evidence suggesting no better functional outcomes for those who discharge to rehabilitation to those who discharge home. The aim of this study is to develop and implement a pre-operative predictive tool, ARISE (Arthroplasty Rehabilitation Initial Screening Evaluation), that incorporated psychological, functional, and socio-demographic factors to determine discharge destination.

METHODS

One week prior to TKA, the ARISE tool was administered to 100 patients, in addition to an EQ-5D-5L survey and other demographic data being recorded. The primary outcome was discharge destination. An enhanced recovery pathway, which included an anesthetic protocol designed to optimize early mobilization, was utilized. Univariable and multivariable logistic regression analysis was performed to determine the likelihood of discharge destination.

RESULTS

Patients in the rehabilitation group were, on average, 4.5 years older than the home group (P = .036). After multivariable regression, ARISE questions were predictive of discharge destination related to beliefs around the superiority of inpatient rehabilitation (odds ratio = 9.9 [2.6-37.9]) and post-discharge level of support (odds ratio = 6.3 [1.5-26.8]). No question around self-reported physical function was predictive.

CONCLUSION

Pre-operative patient beliefs regarding rehabilitation and future home support are highly predictive of discharge destination after primary TKA. Pre-operative patient-reported functional status and demographic variables, with the exception of increasing age, were not shown to be predictive. Predicting those that are most likely to discharge to rehabilitation allows for early, targeted interventions to optimize resources and increase likelihood of home discharge.