Late-week surgery and discharge to specialty care associated with higher costs and longer lengths of stay after elective lumbar laminectomy

Determining the Impact of Preoperative Psychiatric Comorbidities on Readmission After Resection of Vestibular Schwannoma

OBJECTIVE

To determine the impact of comorbid depression on readmission after vestibular schwannoma resection.

STUDY DESIGN

Retrospective database analysis.

SETTING

National database of readmitted patients.

PATIENTS

The Nationwide Readmission Database (NRD) was retrospectively reviewed for patients with history of vestibular schwannoma, identified by International Classification of Disease, Ninth Revision (ICD-9) code 225.1 and ICD-10 code D33.3, who underwent surgical resection (ICD-9 04.01, ICD-10-PCS 00BN0ZZ) in 2020.

INTERVENTIONS

Therapeutic.

MAIN OUTCOME MEASURES

Need for rehabilitation, need for procedures, length of stay, cost of readmission, and insurance status.

RESULTS

A total of 1997 patients were readmitted after resection of vestibular schwannoma in 2020. Of these patients, 290 had history of a comorbid depressive disorder.A significantly higher proportion of patients with history of comorbid depression were transferred to a rehabilitation facility after readmission (11.30% versus 4.30%, p < 0.001). Length of stay (p = 0.227) and total readmission cost (p = 0.723) did not differ significantly, but a significantly lower proportion had private insurance (55.40% versus 64.40%, p = 0.027).

CONCLUSION

Depression is associated with higher utilization of postoperative rehabilitation services and higher rates of medical comorbidities, and should be considered during preoperative evaluation.

Does Surgical Day of Week Affect Patient Outcomes and Hospital Costs Following Lumbar Fusion?

Background As the population ages, surgical intervention for degenerative spine conditions is increasing, and this causes a commiserate increase in healthcare expenditures associated with these procedures. Little research has been done on the effect of early-week versus later-week surgeries on patient outcomes, cost, and length of stay (LOS) in patients undergoing lumbar fusion surgery. The purpose of this study is to compare LOS, patient outcomes, and hospital costs between patients having surgery early in the week and later in the week. Methods A retrospective review of 771 patients undergoing a one-, two-, or three-level lumbar fusion from December 2020 to December 2023 at a single institution was performed. Demographics, surgical details, postoperative outcomes and cost were compared between patients who had surgery on Monday, Tuesday, and Wednesday, to those having surgery Thursday or Friday. Univariate and multivariate analyses were performed to compare the groups. Results There were no differences in age, sex, BMI, race, American Society of Anesthesiology (ASA) scores, Charlson Comorbidity Index (CCI) scores, number of operative levels or inpatient/outpatient status between early- and late-week surgeries. Postoperatively the only significant difference was cost, late-week surgeries were, on average, $3,697 more expensive than early-week surgeries ($26,506 vs. $22,809; p<0.001). On multivariate analysis late-week surgeries were 2.47 times more likely to have a non-home discharge (OR: 2.47, 95% CI: 1.24 to 4.95; p=0.010) and 2.19 times more likely to have a 30-day readmission (OR: 2.19, 95% CI:1.01 to 4.74; p=0.044) Additionally, late-week surgeries were $2,041.55 (β:2,041.55, 95% CI: 804.72 to 3,278.38; p=0.001) more expensive than early-week surgeries. Conclusions At our institution, patients undergoing one- to three-level lumbar fusion surgery on Thursday or Friday had a higher risk of non-home discharge, 30-day readmission, and incurred higher cost than those having early-week surgery. Further research is needed to elucidate the reasons for these findings and to evaluate interventions aimed at improving outcomes for patients undergoing surgery later in the week.

Development and external validation of a predictive model for prolonged length of hospital stay in elderly patients undergoing lumbar fusion surgery: comparison of three predictive models

PURPOSE

This study aimed to develop a predictive model for prolonged length of hospital stay (pLOS) in elderly patients undergoing lumbar fusion surgery, utilizing multivariate logistic regression, single classification and regression tree (hereafter, "classification tree") and random forest machine-learning algorithms.

METHODS

This study was a retrospective review of a prospective Geriatric Lumbar Disease Database. The primary outcome measure was pLOS, which was defined as the LOS greater than the 75th percentile. All patients were grouped as pLOS group and non-pLOS. Three models (including logistic regression, single-classification tree and random forest algorithms) for predicting pLOS were developed using training dataset and internal validation using testing dataset. Finally, online tool based on our model was developed to assess its validity in the clinical setting (external validation).

RESULTS

The development set included 1025 patients (mean [SD] age, 72.8 [5.6] years; 632 [61.7%] female), and the external validation set included 175 patients (73.2 [5.9] years; 97[55.4%] female). Multivariate logistic analyses revealed that older age (odds ratio [OR] 1.06, p < 0.001), higher BMI (OR 1.08, p = 0.002), number of fused segments (OR 1.41, p < 0.001), longer operative time (OR 1.02, p < 0.001), and diabetes (OR 1.05, p = 0.046) were independent risk factors for pLOS in elderly patients undergoing lumbar fusion surgery. The single-classification tree revealed that operative time ≥ 232 min, delayed ambulation, and BMI ≥ 30 kg/m2 as particularly influential predictors for pLOS. A random forest model was developed using the remaining 14 variables. Intraoperative EBL, operative time, delayed ambulation, age, number of fused segments, BMI, and RBC count were the most significant variables in the final model. The predictive ability of our three models was comparable, with no significant differences in AUC (0.73 vs. 0.71 vs. 0.70, respectively). The logistic regression model had a higher net benefit for clinical intervention than the other models. The nomogram was developed, and the C-index of external validation for PLOS was 0.69 (95% CI, 0.65-0.76).

CONCLUSION

This investigation produced three predictive models for pLOS in elderly patients undergoing lumbar fusion surgery. The predictive ability of our three models was comparable. Logistic regression model had a higher net benefit for clinical intervention than the other models. Our predictive model could inform physicians about elderly patients with a high risk of pLOS after surgery.

Effect of Instrumented Spine Surgery on Length of Stay

INTRODUCTION

Total joint arthroplasty studies have identified that surgeries that take place later in the week have a longer length of stay compared with those earlier in the week. This has not been demonstrated in studies focused on anterior cervical diskectomy and fusions or minimally invasive lumbar laminectomies. All-inclusive instrumented spine surgeries, however, have not been analyzed. The purpose of this study was to determine whether day of surgery affects length of stay and whether there are predictive patient characteristics that affect length of stay in instrumented spine surgery.

METHODS

All instrumented spine surgeries in 2019 at a single academic tertiary center were retrospectively reviewed. Patients were categorized for surgical day and discharge disposition to home or a rehabilitation facility. Differences by patient characteristics in length of stay and discharge disposition were compared using Kruskal-Wallis and chi square tests along with multiple comparisons.

RESULTS

Seven hundred six patients were included in the analysis. Excluding Saturday, there were no differences in length of stay based on the day of surgery. Age older than 75 years, female, American Society of Anesthesiology (ASA) classification of 3 or 4, and an increased Charlson Comorbidity Index were all associated with a notable increase in length of stay. While most of the patients were discharged home, discharge to a rehabilitation facility stayed, on average, 4.7 days longer (6.8 days compared with 2.1 days, on average) and were associated with an age older than 66 years old, an ASA classification of 3 or 4, and a Charlson Comorbidity Index of 1 to 3.

CONCLUSIONS

Day of surgery does not affect length of stay in instrumented spine surgeries. Discharge to a rehabilitation facility, however, did increase the length of stay as did age older than 75 years, higher ASA classification, and increased Charlson Comorbidity Index classification.

Time of Discharge and 30-Day Re-Presentation to an Acute Care Setting After Elective Lumbar Decompression Surgery

BACKGROUND

Evidence regarding the consequence of efforts to increase patient throughput and decrease length of stay in the context of elective spine surgery is limited.

OBJECTIVE

To evaluate whether early time of discharge results in increased rates of hospital readmission or return to emergency department for patients admitted after elective, posterior, lumbar decompression surgery.

METHODS

We conducted a retrospective cohort study of 779 patients admitted to hospital after undergoing elective, posterior, lumbar decompression surgery. Multiple logistic regression evaluated the relationship between time of discharge and the primary outcome of return to acute care within 30 days, while controlling for sociodemographic, procedural, and discharge characteristics.

RESULTS

In multiple logistic regression, time of discharge earlier in the day was not associated with increased odds of return to acute care within 30 days (odds ratio [OR] 1.18, 95% CI 0.92-1.52, P = .19). Weekend discharge (OR 1.99, 95% CI 1.04-3.79, P = .04) increased the likelihood of return to acute care. Surgeon experience (<1 year of attending practice, OR 0.43, 95% CI 0.19-1.00, P = .05 and 2-5 years of attending practice, OR 0.50, 95% CI 0.25-1.01, P = .054), weekend discharge (OR 0.49, 95% CI 0.27-0.89, P = .02), and physical therapy evaluation (OR 0.20, 95% CI 0.12-0.33, P < .001) decreased the likelihood of discharge before noon.

CONCLUSION

Time of discharge is not associated with risk of readmission or presentation to the emergency department after elective lumbar decompression. Weekend discharge is independently associated with increased risk of readmission and decreased likelihood of prenoon discharge.

Robust prediction of nonhome discharge following elective anterior cervical discectomy and fusion using explainable machine learning

PURPOSE

Predict nonhome discharge (NHD) following elective anterior cervical discectomy and fusion (ACDF) using an explainable machine learning model.

METHODS

2227 patients undergoing elective ACDF from 2008 to 2019 were identified from a single institutional database. A machine learning model was trained on preoperative variables, including demographics, comorbidity indices, and levels fused. The validation technique was repeated stratified K-Fold cross validation with the area under the receiver operating curve (AUROC) statistic as the performance metric. Shapley Additive Explanation (SHAP) values were calculated to provide further explainability regarding the model's decision making.

RESULTS

The preoperative model performed with an AUROC of 0.83 ± 0.05. SHAP scores revealed the most pertinent risk factors to be age, medicare insurance, and American Society of Anesthesiology (ASA) score. Interaction analysis demonstrated that female patients over 65 with greater fusion levels were more likely to undergo NHD. Likewise, ASA demonstrated positive interaction effects with female sex, levels fused and BMI.

CONCLUSION

We validated an explainable machine learning model for the prediction of NHD using common preoperative variables. Adding transparency is a key step towards clinical application because it demonstrates that our model's "thinking" aligns with clinical reasoning. Interactive analysis demonstrated that those of age over 65, female sex, higher ASA score, and greater fusion levels were more predisposed to NHD. Age and ASA score were similar in their predictive ability. Machine learning may be used to predict NHD, and can assist surgeons with patient counseling or early discharge planning.

The Impact of Surgical Scheduling on Outcomes in Lumbar Laminectomy

Objective The purpose of this study was to determine whether surgical scheduling affected patient outcomes following lumbar laminectomy. Physician fatigue caused by prolonged work hours has been shown to worsen outcomes. Previous research has also established a relationship between surgical scheduling and outcomes. Methods This was a retrospective chart review of single-level lumbar laminectomy patients at the Penn State Milton S. Hershey Medical Center between 1992 and 2019. Patients who underwent a one-level laminectomy between 1992 and 2019 were included in the study. Patients with procedures defined as complex (>1 level, tumor or abscess removal, discectomy, implant removal) were excluded. The surgical complication rate [cerebrospinal fluid (CSF) leak, 30-day redo, 30-day ED visit, weakness, sensation loss, infection, urinary retention] was compared across surgical start times, day of the week, proximity to a holiday, and procedure length. Results Procedures that started between 9:01-11:00 were more likely to have a complication than those between 7:01-9:00 (p=0.04). For every 60-min increase in surgery length, odds of having a complication increased by 2.01 times (p=0.0041). Surgeries that started between 11:01-13:00 had a significantly longer median surgery length than those between 7:01-9:00. Conclusion The time of the day when the procedure was started was predictive of worse outcomes following laminectomy. This may be attributed to several factors, including fatigue and staff turnover. Additionally, increased surgical length was predictive of more complications. It remains unclear whether increased surgical time results from correction of noticed errors or a fatigue-related decline in speed and performance. These findings on one-level laminectomy warrant further investigations since they have implications for reducing systemic failures that impact patient outcomes.