Differences in Healthcare Resource Utilization After Surgery for Metastatic Spinal Column Tumors in Patients with a Concurrent Affective Disorder in the United States

Emotional distress and future healthcare utilization in oncology populations: A systematic review

OBJECTIVE

Emotional distress has been correlated with greater healthcare utilization and economic costs in cancer; however, the prospective relationship between positive distress screens and future healthcare utilization is less clear. Taken together, there is a critical need to synthesize studies examining the prospective relationship between emotional distress and future healthcare use to inform distress management protocols and motivate institutional resource allocation to distress management. The aim of the systematic review is to explore the relationship between emotional distress, measured via validated emotional distress questionnaires, and subsequent healthcare utilization in patients diagnosed with cancer.

METHODS

A systematic search of seven databases was conducted on 29 March 2022 and updated 3 August 2023. Eligibility criteria were: (1) peer-reviewed, (2) quantitative or mixed methods, (3) adults (≥18 years) diagnosed with cancer, (4) cancer distress questionnaire(s) completed prior to healthcare utilization, and (5) written in English. Exclusion criteria included: (1) non-emotional aspects of distress (i.e., spiritual or physical distress), (2) healthcare utilization characterized via economic or monetary variables, and (3) caregiver or non-cancer populations.

RESULTS

Nineteen peer-reviewed articles were included in the review. There was significant heterogeneity in emotional distress instruments and type of healthcare utilization used. Most studies examining general distress or anxiety found that increased distress was predictive of greater future healthcare utilization.

CONCLUSION

The results suggest that individuals with higher levels of general distress and anxiety are at increased risk for future healthcare utilization.

Influence of affective disorders on outcomes after suboccipital decompression for adult Chiari I malformation

INTRODUCTION

Affective disorders (AD) have been shown to influence patient outcomes and healthcare resource utilization across several pathologies, though this relationship has not been described in patients with Chiari I malformations (CM-I). The aim of this study was to determine the impact of comorbid AD on postoperative events and healthcare resource utilization in adults following suboccipital decompression for CM-I.

METHODS

A retrospective study was performed using the 2016-2019 National Inpatient Sample database. Adults who underwent suboccipital decompression for CM-I were identified using ICD-10-CM codes. Patients were stratified into two cohorts, those with AD and those without (No AD). Patient demographics, comorbidities, operative characteristics, perioperative adverse events (AEs), and healthcare resource utilization were assessed. Multivariate logistic regression analyses were used to identify independent predictors of prolonged length of stay (LOS), exorbitant admission costs, and non-routine discharge (NRD).

RESULTS

A total of 3985 patients were identified, of which 2780 (69.8%) were in the No AD cohort and 1205 (30.2%) were in the AD cohort. Patient demographics were similar, except for a greater proportion of Female patients than the No AD cohort (p = 0.004). Prevalence of some comorbidities varied between cohorts, including obesity (p = 0.030), ADHD (p < 0.001), GERD (p < 0.001), smoking (p < 0.001), and chronic pulmonary disease (p < 0.001). The AD cohort had a greater proportion of patients with 1-2 (p < 0.001) or ≥ 3 comorbidities (p < 0.001) compared to the No AD cohort. A greater proportion of patients in the AD cohort presented with headache compared to the No AD cohort (p = 0.003). Incidence of syringomyelia was greater in the No AD cohort (p = 0.002). A greater proportion of patients in the No AD cohort underwent duraplasty only (without cervical laminectomy) compared to the AD cohort (p = 0.021). Healthcare resource utilization was similar between cohorts, with no significant differences in mean LOS (No AD: 3.78 ± 3.51 days vs. 3.68 ± 2.71 days, p = 0.659), NRD (No AD: 3.8% vs. AD: 5.4%, p = 0.260), or mean admission costs (No AD: $20,254 ± 14,023 vs. AD: $29,897 ± 22,586, p = 0.284). On multivariate analysis, AD was not independently associated with extended LOS [OR (95%CI): 1.09 (0.72-1.65), p = 0.669], increased hospital costs [OR (95%CI): 0.98 (0.63-1.52), p = 0.930], or NRD [OR (95%CI): 1.39 (0.65-2.96), p = 0.302].

CONCLUSION

Our study suggests that the presence of an AD may not have as much of an impact on postoperative events and healthcare resource utilization in adult patients undergoing Chiari decompression. Additional studies may be warranted to identify other potential implications that AD may have in other aspects of healthcare in this patient population.

Depression Is Associated With Non-Home Discharge After Coronary Artery Bypass Graft

INTRODUCTION

Depression is disproportionately high in patients with coronary artery disease and has been associated with adverse outcomes following coronary artery bypass graft (CABG). One quality metric, non-home discharge (NHD), can have substantial implications for patients and health care resource utilization. Depression increases the risk of NHD after many operations, but it has not been studied after CABG. We hypothesized that a history of depression would be associated with an increased risk of NHD following CABG.

METHODS

CABG cases were identified from the 2018 National Inpatient Sample using ICD-10 codes. Depression, demographic data, comorbidities, length of stay (LOS), rate of NHD were analyzed using appropriate statistical tests where a P-value < 0.05 was defined as statistically significant. Adjusted multivariable logistic regression models were used to assess independent association between depression and NHD as well as LOS while controlling for confounders.

RESULTS

There were 31,309 patients, of which 2743 (8.8%) had depression. Depressed patients were younger, females, in a lower income quartile, and more medically complex. They also demonstrated more frequent NHD and prolonged LOS. After adjusted multivariable analysis, depressed patients had a 70% increased odds of NHD (adjusted odds ratio: 1.70 [1.52-1.89] P < 0.001) and a 24% increased odds of prolonged LOS (AOR: 1.24 [1.12-1.38] P < 0.001).

CONCLUSIONS

From a national sample, depressed patients were associated with more frequent NHD following CABG. To our knowledge, this is the first study to demonstrate this, and it highlights the need for improved preoperative identification in order to improve risk stratification and timely allocation of discharge services.

Machine learning-based algorithms to predict severe psychological distress among cancer patients with spinal metastatic disease

BACKGROUND CONTEXT

Metastatic spinal disease is an advanced stage of cancer patients and often suffer from terrible psychological health status; however, the ability to estimate the risk probability of this adverse outcome using current available data is very limited.

PURPOSE

The goal of this study was to propose a precise model based on machine learning techniques to predict psychological status among cancer patients with spinal metastatic disease.

STUDY DESIGN/SETTING

A prospective cohort study.

PATIENT SAMPLE

A total of 1043 cancer patients with spinal metastatic disease were included.

OUTCOME MEASURES

The main outcome was severe psychological distress.

METHODS

The total of patients was randomly divided into a training dataset and a testing dataset on a ratio of 9:1. Patients' demographics, lifestyle choices, cancer-related features, clinical manifestations, and treatments were collected as potential model predictors in the study. Five machine learning algorithms, including XGBoosting machine, random forest, gradient boosting machine, support vector machine, and ensemble prediction model, as well as a logistic regression model were employed to train and optimize models in the training set, and their predictive performance was assessed in the testing set.

RESULTS

Up to 21.48% of all patients who were recruited had severe psychological distress. Elderly patients (p<0.001), female (p =0.045), current smoking (p=0.002) or drinking (p=0.003), a lower level of education (p<0.001), a stronger spiritual desire (p<0.001), visceral metastasis (p=0.005), and a higher Eastern Cooperative Oncology Group (ECOG) score (p<0.001) were significantly associated with worse psychological health. With an area under the curve (AUC) of 0.865 (95% CI: 0.788-0.941) and an accuracy of up to 0.843, the gradient boosting machine algorithm performed best in the prediction of the outcome, followed by the XGBooting machine algorithm (AUC: 0.851, 95% CI: 0.768-0.934; Accuracy: 0.826) and ensemble prediction (AUC: 0.851, 95% CI: 0.770-0.932; Accuracy: 0.809) in the testing set. In contrast, the AUC of the logistic regression model was only 0.836 (95% CI: 0.756-0.916; Accuracy: 0.783).

CONCLUSIONS

Machine learning models have greater predictive power and can offer useful tools to identify individuals with spinal metastatic disease who are experiencing severe psychological distress.

Impact of Affective Disorders on Inpatient Opioid Consumption and Hospital Outcomes Following Open Posterior Spinal Fusion for Adult Spine Deformity

OBJECTIVE

Affective disorders (ADs) are common and have a profound impact on surgical recovery, though few have studied the impact of ADs on inpatient narcotic consumption. The aim of this study was to assess the impact of ADs on inpatient narcotic consumption and healthcare resource utilization in patients undergoing spinal fusion for adult spinal deformity.

METHODS

A retrospective cohort study was performed using the 2016-2017 Premier Healthcare Database. Adults who underwent adult spinal deformity surgery were identified using International Classification of Disease, Tenth Revision, codes. Patients were grouped based on comorbid diagnosis of an AD. Demographics, comorbidities, intraoperative variables, complications, length of stay, admission costs, and nonroutine discharge rates were assessed. Increased inpatient opioid use was categorized by morphine milligram equivalents consumption greater than the 75th percentile. Multivariate regression analysis was used to identify predictors of increased healthcare recourse utilization.

RESULTS

Of the 1831 study patients, 674 (36.8%) had an AD. A smaller proportion of patients in the AD cohort were 65+ years of age (P = 0.001), while a greater proportion of patients in the AD cohort identified as non-Hispanic White (P < 0.001). A greater proportion of patients in the AD cohort had increased morphine milligram equivalents consumption (P < 0.001). The AD cohort also had a longer mean length of stay (P < 0.001). A greater proportion of patients in the AD cohort had nonroutine discharges (P = 0.039) and unplanned 30-day readmission (P = 0.041). On multivariate analysis, AD was significantly associated with increased cost (odds ratio: 1.61, P < 0.001) and nonroutine discharge (odds ratio: 1.36, P = 0.035).

CONCLUSIONS

ADs may be associated with increased inpatient opioid consumption and healthcare resource utilization.