Socio-demographic factors impact time to discharge following total knee arthroplasty

A balance focused biometric does not predict rehabilitation needs and outcomes following total knee arthroplasty

BACKGROUND

Both length of hospital stay and discharge to a skilled nursing facility are key drivers of total knee arthroplasty (TKA)-associated spending. Identifying patients who require increased postoperative care may improve expectation setting, discharge planning, and cost reduction. Balance deficits affect patients undergoing TKA and are critical to recovery. We aimed to assess whether a device that measures preoperative balance predicts patients' rehabilitation needs and outcomes after TKA.

METHODS

40 patients indicated for primary TKA were prospectively enrolled and followed for 12 months. Demographics, KOOS-JR, and PROMIS data were collected at baseline, 3-months, and 12-months. Single-leg balance and sway velocity were assessed preoperatively with a force plate (Sparta Science, Menlo Park, CA). The primary outcome was patients' discharge facility (home versus skilled nursing facility). Secondary outcomes included length of hospital stay, KOOS-JR scores, and PROMIS scores.

RESULTS

The mean preoperative sway velocity for the operative leg was 5.7 ± 2.7 cm/s, which did not differ from that of the non-operative leg (5.7 ± 2.6 cm/s, p = 1.00). Five patients (13%) were discharged to a skilled nursing facility and the mean length of hospital stay was 2.8 ± 1.5 days. Sway velocity was not associated with discharge to a skilled nursing facility (odds ratio, OR = 0.82, 95% CI = 0.27-2.11, p = 0.690) or longer length of hospital stay (b = -0.03, SE = 0.10, p = 0.738). An increased sway velocity was associated with change in PROMIS items from baseline to 3 months for global07 ("How would you rate your pain on average?" b = 1.17, SE = 0.46, p = 0.015) and pain21 ("What is your level of pain right now?" b = 0.39, SE = 0.17, p = 0.025) at 3-months.

CONCLUSION

Preoperative balance deficits were associated with postoperative improvements in pain and function after TKA, but a balance focused biometric that measured single-leg sway preoperatively did not predict discharge to a skilled nursing facility or length of hospital stay after TKA making their routine measurement cost-ineffective.

Associations of parecoxib and other variables with recovery and safety outcomes in total knee arthroplasty: insights from a retrospective cohort study

Background

Early mobilization post-total knee arthroplasty (TKA) significantly affects patient outcomes. While parecoxib is known to reduce postoperative pain and morphine use with a favorable safety profile, its impact on mobilization timing post-TKA remains uncertain. This retrospective study aims to assess parecoxib's influence on postoperative mobilization timing in TKA patients without compromising safety.

Methods

This study included unilateral TKA patients treated for primary knee osteoarthritis under general anesthesia. We divided the study period into two intervals, 2007-2012 and 2013-2018, to evaluate temporal differences. Both the control group and parecoxib group received standard postoperative oral analgesics and as-needed intramuscular morphine. The control group did not receive parecoxib, while the parecoxib group did. Primary outcomes compared postoperative complications and mobilization timing between groups, with secondary outcomes including length of hospital stay (LOS), Visual Analog Scale (VAS) scores for pain, as-needed morphine use, and postoperative nausea/vomiting.

Results

Parecoxib did not increase postoperative complications. Unmatched comparison with patients in controlled group found that patients in parecoxib group had significantly shortened mobilization time (2.2 ± 1.1 vs. 2.7 ± 1.6 days, P < 0.001) and LOS (6.7 ± 2.5 vs. 7.2 ± 2.1 days, P = 0.01). Multivariate analysis linked parecoxib use with faster mobilization (β = -0.365, P < 0.001) but not LOS. Males showed increased mobilization time and LOS compared to females during the period of 2007-2018, but gender had no significant association with LOS during the period of 2013-2018. The 2013-2018 period saw significant reductions in both mobilization time and LOS. Use of a tourniquet and local infiltration analgesia showed no significant impact. ASA classification 1-2 was positively associated with faster mobilization but not LOS. Longer operation times were linked to delayed mobilization and increased LOS.

Conclusion

In this study, intravenous parecoxib injection, female gender, and shorter OP time had consistent positive association with shorter time to mobilization after individual multivariate analysis in 2 different period. The use of parecoxib had consistent no significant association with LOS. Only shorter OP time was consistent positive associated with shorter LOS.

NAVIO RATKA shows similar rates of hemoglobin-drop, adverse events, readmission and early revision vs conventional TKA: a single centre retrospective cohort study

PURPOSE

Despite widespread adoption of NAVIO robotic-assisted total knee arthroplasty (NAVIO RATKA) in clinical practice, clinical outcome in terms of adverse events and complications remains unclear. The purpose of this study was to compare adverse events, length of stay, surgical time, hemoglobin drop, early readmission rate and revision rate between conventional TKA (CTKA) and NAVIO RATKA.

METHODS

This single-centre retrospective cohort analysis compared 230 NAVIO RATKA patients to 489 CTKA patients with a minimal follow-up of 12 months. Baseline demographic and comorbidity parameters were collected, as well as length of stay, revision rate and reason for revision, early readmission rate (< 6w) and reason for readmission, post-operative hemoglobin levels, adverse events, surgical time and operating room time. Data were compared using Mann-Whitney U test for continuous data without normal distribution and ordinal data, categorical variables were compared using the Chi-square or Fisher exact test.

RESULTS

There were no clinically relevant baseline demographic or comorbidity differences between groups. CTKA had shorter length of stay than NAVIO RATKA (5.0 days vs 5.4 days, p = 0.010) but trended towards a higher reoperation rate (4.1% vs 1.7%, p = .144, n.s). No differences were found in hemoglobin drop, readmission rate or overall incidence of adverse events, but CTKA showed more hematoma formation (1.6% vs 0%, p = .044) and higher incidence of periprosthetic joint infection (PJI) (1% vs 0%, p = n.s.), whilst NAVIO RATKA showed more periprosthetic fractures and persistent wound drainage (0.4% vs 2.2%, p = .038 and 0.6% vs 4.3%, p = .001, respectively). Surgical time remained significantly longer in NAVIO RATKA during all 230 cases (87 min vs 67.6 min) and showed a continuous downward trend.

CONCLUSIONS

This study further validates the usage of NAVIO RATKA as a safe method to perform TKA, with comparable short term outcomes to CTKA in terms of early revisions and adverse events. Surgeons should be mindful of the differing adverse event profile in NAVIO RATKA and adjust their patient selection accordingly to ensure optimal outcomes. In addition, surgeons using NAVIO RATKA should expect a linear learning curve and a surgical time exceeding that of CTKA.

LEVEL OF EVIDENCE

Level III (therapeutic retrospective cohort study).

Orthopaedic Nurse Navigators and Total Joint Arthroplasty Preoperative Optimization: Improving Patient Access to Musculoskeletal Care

Preoperative optimization programs for total joint arthroplasty identify and address risk factors to reduce postoperative complications, thereby improving patients' ability to be safe surgical candidates. This article introduces preoperative optimization programs and describes the role of orthopaedic nurse navigators. This foundation will be used to produce an article series with recommendations for optimization of several modifiable biopsychosocial factors. We consulted orthopaedic nurse navigators across the United States and conducted a literature review regarding preoperative optimization to establish the importance of nurse navigation in preoperative optimization. The responsibilities of nurse navigators, cited resources, and structure of preoperative optimization programs varied among institutions. Optimization programs relying on nurse navigators frequently demonstrated improved outcomes. Our discussions and literature review demonstrated the integral role of nurse navigators in preoperative optimization. We will discuss specific risk factors and how nurse navigators can manage them throughout this article series.

Influence of Demographic and Socioeconomic Factors on Hospital Distance for Total Knee Arthroplasty

Background

Disparities exist in access to and outcomes following total knee arthroplasty. However, there is a paucity of data examining the relationship between travel distance and these disparities.

Methods

We used the Healthcare Cost and Utilization Project, American Hospital Association, and UnitedStatesZipCodes.org Enterprise databases to gather patient demographic and postoperative outcomes data. We calculated the distance traveled between patient population-weighted zip code centroid points and the hospitals at which they received total knee arthroplasty. We then examined the association between travel distance and patient demographic characteristics as well as postoperative adverse outcomes.

Results

Among of cohort of 384,038 patients, white patients (16.58 miles) traveled farther on average than Black (10.05) or Hispanic patients (10.54) (P < .0001). Medicare and commercial insurance coverage were associated with greater travel distance (P < .0001). Fewer medical comorbidities (P < .001) and residence in the highest-income areas (P < .0001) were associated with increased travel distance. Differences in postoperative complication rates related to travel distance were not clinically significant.

Conclusions

Increased travel distance for total knee arthroplasty was associated with white race, commercial and Medicare insurance coverage, fewer medical comorbidities, and increased socioeconomic status. Future work is needed to determine the underlying causal mechanisms leading to these differences in access to specialized care.

In meeting the increasing demands for total knee arthroplasty, can we achieve high levels of quality care in a small community hospital? A mixed-methods study

Purpose

Small community hospitals (SCHs) help meet the demand for total knee arthroplasty (TKA). This mixed-methods study compares outcomes and analyses of environmental differences following TKA at a SCH and a tertiary care hospital (TCH).

Methods

Quantitative: A retrospective review of 352 propensity-matched primary TKA procedures at both a SCH and a TCH, based on age, body mass index, and American Society of Anesthesiologists class, was completed. Groups were compared by length of stay (LOS), 90-day emergency department visits, 90-day readmissions, reoperations, and mortality. Qualitative: Based on the Theoretical Domains Framework, seven prospective semistructured interviews were performed. Interview transcripts were coded and belief statements were generated and summarized by two reviewers. Discrepancies were resolved by a third reviewer.

Results

Quantitative: The average LOS for the SCH was significantly shorter than that for the TCH (2.0 ± 0.2 vs. 3.6 ± 2.7 days; p < 0.001), a difference that persisted following a subgroup analysis of ASA I/II patients (2.0 ± 0.2 vs. 3.2 ± 2.2; p < 0.001). There were no significant differences in other outcomes. Qualitative: The main themes that revolved around a higher case load for physiotherapy at the TCH resulted in patients waiting longer to be mobilized after surgery. Patient disposition also affected their discharge rates.

Conclusion

Given the increasing demand for TKA, the SCH represents a viable option to increase capacity, while reducing LOS. Future directions to reduce LOS include addressing social barriers to discharge and patient prioritization for assessment by allied health services. When TKA is performed by the same set of surgeons, the SCH provides quality care with a shorter LOS and comparable with urban hospitals, and this can be attributed to the differences in resource utilization in the two hospital settings.

Effect of Marital Status on Outcomes Following Total Joint Arthroplasty

INTRODUCTION

The purpose of this study is to investigate whether the specific socioeconomic factor such as marital status has any effect on clinical outcomes and patient-reported outcome measures (PROMs) after primary total hip (THA) and knee (TKA) arthroplasty.

MATERIALS AND METHODS

We retrospectively reviewed patients who underwent primary THA or TKA from January 2019 to August 2019 who answered all PROM questionnaires. Both THA and TKA patients were separated into two groups based on their marital status at the time of surgery (married vs. non-married). Demographics, clinical data, and PROMs (FJS-12, HOOS, JR, KOOS, JR, and VR-12 PCS&MCS) were collected at various time-periods. Demographic differences were assessed using chi-square and independent sample t tests. Clinical data and mean PROMs were compared using multilinear regressions while accounting for demographic differences.

RESULTS

This study included 389 patients who underwent primary THA and 193 that underwent primary TKA. In the THA cohort, 256 (66%) patients were married and 133 (34%) were non-married. In the TKA cohort, there were 117 (61%) married patients and 76 (39%) non-married patients. Length of stay was significantly shorter for married patients in both the THA (1.30 vs. 1.64; p = 0.002) and TKA (1.89 vs. 2.36; p = 0.024) cohorts. Surgical-time, all-cause emergency department visits, discharge disposition, and 90-day all-cause adverse events (readmissions/revisions) did not statistically differ between both cohorts. Both HOOS, JR and KOOS, JR score improvements from baseline to 1-year did not statistically differ for the THA and TKA cohorts, respectively. Although VR-12 PCS (p = 0.012) and MCS (p = 0.004) score improvement from baseline to 1-year statistically differed for the THA cohort, they did not for the TKA cohort.

CONCLUSION

Total joint arthroplasty may yield similar clinical benefits in all patients irrespective of their marital status. Although some PROMs statistically differed among married and non-married patients, the differences are likely not clinically significant. Surgeons should continue to assess levels of psychosocial support in their patients prior to undergoing TJA to optimize outcomes.

LEVEL OF EVIDENCE

III, Retrospective Cohort Study.

Taking the Long Way to Care: Who is Traveling Farthest to Undergo Elective Total Hip Arthroplasty?

Background

Disparities in access to total hip arthroplasty (THA) exist. The purpose of this study is to examine how distance traveled to undergo elective THA correlates with sociodemographic variables and postoperative outcomes.

Material and methods

The Healthcare Cost and Utilization Project New York and Florida state inpatient databases were used to identify patients who underwent elective THA between 2006 and 2014. Data from the American Hospital Association and United States Postal Service were used to calculate the distance patients traveled to receive THA, and only those who traveled more than 25 miles were included. We stratified patients into 4 groups based on their distance traveled (25-50 miles, 50.01-100 miles, 100.01-500 miles, and >500.01 miles) and compared demographic characteristics and postoperative outcomes between groups.

Results

Age, race, insurance provider, zip code income quartile, and Charlson Comorbidity Index scores were each significantly associated with travel distance (P < .001) among our cohort of 25,734 patients. Patients who were older, were white, had Medicare insurance coverage, lived in zip codes with a higher median household income, and had increased comorbidities were more likely to travel the farthest to receive care. There were minimal associations between travel distance and postoperative outcomes.

Conclusion

There may be specific demographic groups who either are forced to travel long distances to receive care or have the resources to seek out and travel to distant hospitals in an effort to receive optimal care. Understanding the interconnected relationships between demographic variables is necessary to address disparities in access to specialized orthopedic surgical care.

Demographics of Patients Traveling Notable Distances to Receive Total Knee Arthroplasty

Although disparities exist in patient access to and outcomes after total knee arthroplasty (TKA), there are limited data regarding the relationship between travel distance and patient demographics or postoperative complications.

Racial and Socioeconomic Differences in Distance Traveled for Elective Hip Arthroplasty

Introduction:

There are data that disparities exist in access to total hip arthroplasty (THA). However, to date, no study has examined the relationship between distance traveled to undergo THA and patient demographic characteristics, such as race, insurance provider, and income level as well as postoperative outcomes.

Methods:

Data from the Healthcare Cost and Utilization Project, American Hospital Association, and the United States Postal Service were used to calculate the geographic distance between 211,806 patients' population-weighted zip code centroid points to the coordinates of the hospitals at which they underwent THA. We then used Healthcare Cost and Utilization Project data to examine the relationships between travel distance and both patient demographic indicators and postoperative outcomes after THA.

Results:

White patients traveled farther on average to undergo THA as compared with their non-White counterparts (17.38 vs 13.05 miles) (P < 0.0001). Patients with commercial insurance (17.19 miles) and Medicare (16.65 miles) traveled farther on average to receive care than did patients with Medicaid insurance coverage (14.00 miles) (P = 0.0001). Patients residing in zip codes in the top income quartile traveled farther to receive care (18.73 miles) as compared with those in the lowest income quartile (15.31 miles) (P < 0.0001). No clinically significant association was found between travel distance and adverse postoperative outcomes after THA.

Discussion:

Race, insurance provider, and zip code income quartile are associated with differences in the distance traveled to undergo THA. These findings may be indicative of underlying disparities in access to care across patient populations.

A Novel Scoring System to Predict Length of Stay After Anterior Cervical Discectomy and Fusion

INTRODUCTION

The movement toward reducing healthcare expenditures has led to an increased volume of outpatient anterior cervical diskectomy and fusions (ACDFs). Appropriateness for outpatient surgery can be gauged based on the duration of recovery each patient will likely need.

METHODS

Patients undergoing 1- or 2-level ACDFs were retrospectively identified at a single Level I spine surgery referral institution. Length of stay (LOS) was categorized binarily as either less than two midnights or two or more midnights. The data were split into training (80%) and test (20%) sets. Two multivariate regressions and three machine learning models were developed to predict a probability of LOS ≥ 2 based on preoperative patient characteristics. Using each model, coefficients were computed for each risk factor based on the training data set and used to create a calculatable ACDF Predictive Scoring System (APSS). Performance of each APSS was then evaluated on a subsample of the data set withheld from training. Decision curve analysis was done to evaluate benefit across probability thresholds for the best performing model.

RESULTS

In the final analysis, 1,516 patients had a LOS <2 and 643 had a LOS ≥2. Patient characteristics used for predictive modeling were American Society of Anesthesiologists score, age, body mass index, sex, procedure type, history of chronic pulmonary disease, depression, diabetes, hypertension, and hypothyroidism. The best performing APSS was modeled after a lasso regression. When applied to the withheld test data set, the APSS-lasso had an area under the curve from the receiver operating characteristic curve of 0.68, with a specificity of 0.78 and a sensitivity of 0.49. The calculated APSS scores ranged between 0 and 45 and corresponded to a probability of LOS ≥2 between 4% and 97%.

CONCLUSION

Using classic statistics and machine learning, this scoring system provides a platform for stratifying patients undergoing ACDF into an inpatient or outpatient surgical setting.

Insurance Type and Marital Status Impact Hospital Length of Stay After Pancreatoduodenectomy

BACKGROUND

Recognition of the impact of social determinants on health care and surgical outcomes is imperative to improve patient care. This study aims to examine the impact social determinants have on hospital length of stay (LOS) after pancreatoduodenectomy (PD).

METHODS

Retrospective review of a prospective American College of Surgeons-National Surgical Quality Improvement Program database identified patients who underwent PD from 2013 to 2018. Patients were categorized by insurance type (public/private/multiple), and electronic medical record review was performed to obtain distance from home, marital status, and race. Public insurance included Medicare and Medicaid; multiple types were defined as public insurance supplemented by a private insurance. Univariable analysis was used to identify potential confounders. Significant differences (P < 0.05) were controlled for using multivariable regression models to examine the effect of variables on LOS.

RESULTS

About 813 PDs were included (n = 341 public; n = 238 private; and n = 234 multiple). Patients with public insurance had significantly longer LOS than patients with private on univariate (P < 0.001) and multivariable analyses (P = 0.021) (8 versus 7 d). Patients with multiple insurance types showed significantly increased LOS compared with patients with private on univariable (P < 0.001) and multivariable analyses (P = 0.006) (8 versus 7 d). Single patients had significantly longer LOS compared with married patients on univariable (P = 0.012) and multivariable analyses (P = 0.005) (8 versus 7 d). Distance from home, race, gender, or age did not have a significant impact on LOS.

CONCLUSIONS

Single patients and patients with public or multiple insurance types are more likely to have longer hospital LOS after PD. These findings will enable physicians to identify patients at risk and target them for enhanced recovery programming.

Quality of life outcomes in patients undergoing knee replacement surgery: longitudinal findings from the QPro-Gin study

Background

Many patients report postoperative pain, limited improvement in physical function and poor quality of life (QOL) after knee replacement surgery. Our study uses baseline predictors of change to investigate the QOL of patients with knee osteoarthritis 3-months after knee replacement surgery.

Methods

A prospective observational study was designed to evaluate patients (n = 132) scheduled for uni-compartmental or total knee replacement surgery who were assessed at baseline (preoperatively) and 3-months after. Physical and mental endpoints based on the component scores of the SF-12 and on the Western Ontario and McMaster Universities Arthritis (WOMAC) index were used to investigate patients’ QOL. Generalised estimating equation methodology was used to assess patients’ baseline characteristics (age, sex, education, body mass index (BMI), comorbidity, depressive symptoms, cognitive impairment, smoking/alcohol and type of surgery), the study endpoints and their changes over a 3-month post-surgery period. Stratified analyses by rehabilitation status after discharge were performed.

Results

Longitudinal data analysis showed that the baseline factors associated with improvement in general QOL at the 3-month post-surgery assessment were higher BMI, a high comorbidity, total (as opposed to unicompartmental) knee replacement and low education level. Data analysis of the patients who underwent rehabilitation after discharge revealed that the current smokers’ physical QOL worsened over time. The general QOL was unchanged over time in the presence of depressive symptomatology.

Conclusions

These findings underline the importance of using comprehensive assessment methods to identify factors affecting functionality and QOL, and developing interventions to improve the health/wellbeing of patients after knee replacement.

Enhanced Selection of Candidates for Same-Day and Outpatient Total Knee Arthroplasty

BACKGROUND

Medicare removed total knee arthroplasty (TKA) from its inpatient-only list and private insurers created ambulatory surgical codes; these changes bring about logistical challenges for TKA episode planning. We identified preoperatively determined factors associated with hospital length of stay for (1) same-day discharge (SDD) and (2) inpatient TKA defined by Medicare's 2-midnight rule benchmark.

METHODS

We retrospectively reviewed 325 consecutive unilateral primary TKAs performed on patients completing the Perioperative Surgical Home preoperative optimization pathway within a single hospital system. Stepwise logistic regression modeling was performed to identify preoperatively determined factors associated with (1) SDD and (2) inpatient TKA. We compared these models' ability to discern the length of stay category to the Risk Assessment and Prediction Tool (RAPT) score alone.

RESULTS

The cohort included 32 (10%) SDD, 189 (58%) next-day discharges, and 104 (32%) inpatients. Lower body mass index (BMI; odds ratio [OR], 0.92; 95% CI, 0.85-0.1.0; P = .04) and fewer self-reported allergies (OR, 0.66; 95% CI, 0.46-0.95; P = .03) were associated with SDD. The SDD model outperformed the RAPT alone (C-statistic, 0.73 vs 0.52; P < .01). Older age (OR, 0.96; P = .04), higher BMI (OR, 0.93; P 0.01), lower RAPT score (OR, 1.2; P = .04), and later surgery start time (OR, 0.80; P < .01) were associated with inpatient discharge. The inpatient model outperformed the RAPT alone (C-statistic, 0.74 vs 0.62; P < .01).

CONCLUSION

We identified preoperatively determined factors associated with (1) SDD as BMI and allergies and (2) inpatient TKA as age, BMI, RAPT score, and surgery start time. Hospitals, providers, patients, families, and payers can use this information for TKA episode planning.