Fixed and Variable Relationship Models to Define the Volume-Value Relationship in Spinal Fusion Surgery: A Macroeconomic Analysis Using Evidence-Based Thresholds

An Employer-Provider Direct Payment Program Is Associated With Lower Episode Costs

Bundled payment has shown promise in reducing medical spending while maintaining quality. However, its impact among commercially insured populations has not been well studied. We examined the impacts on episode cost and patient cost sharing of a program that applies bundled payments for orthopedic and surgical procedures in a commercially insured population. The program we studied negotiates preferred prices for selected providers that cover the procedure and all related care within a thirty-day period after the procedure and waives cost sharing for patients who receive care from these providers. After implementation, episode prices for three selected surgical procedures declined by $4,229, a 10.7 percent relative reduction. Employers captured approximately 85 percent of the savings, or $3,582 per episode (a 9.5 percent relative decrease), and patient cost-sharing payments decreased by $498 per episode (a 27.7 percent relative decrease).

Comparison of Fusion Rate between Demineralized Bone Matrix versus Autograft in Lumbar Fusion : Meta-Analysis

The demineralized bone matrix (DBM) as the bone graft material to increase the fusion rate was widely used in spinal fusion. The current study aimed to compare the fusion rate of DBM to the fusion rate of autograft in lumbar spine fusion via meta-analysis of published literature. After systematic search, comparative studies were selected according to eligibility criteria. Checklist (risk of bias assessment tool for non-randomized study) was used to evaluate the risk of bias of the included nonrandomized controlled studies. The corresponding 95% confidence interval (95% CI) were calculated. We also used subgroup analysis to analyze the fusion rate of posterolateral lumbar fusion and lumbar interbody fusion. Eight studies were finally included in this meta-analysis. These eight studies included 581 patients. Among them, 337 patients underwent spinal fusion surgery using DBM (DBM group) and 204 patients underwent spinal fusion surgery with mainly autologous bone and without using DBM (control group). There was no significant differences of fusion rate between the two groups in posterolateral fusion analysis (risk ratio [RR], 1.03; 95% CI, 0.90–1.17; p=0.66) and interbody fusion analysis (RR, 1.13; 95% CI, 0.91–1.39; p=0.27). Based on the available evidence, the use of DBM with autograft in posterolateral lumbar spine fusion and lumbar interbody fusion showed a slightly higher fusion rate than that of autograft alone; however, there was no statistically different between two groups.

Defining the Volume-Outcome Relationship in Reverse Shoulder Arthroplasty: A Nationwide Analysis

BACKGROUND

As the utilization of reverse total shoulder arthroplasty (RSA) grows, it is increasingly important to examine the relationship between hospital volume and RSA outcomes. We hypothesized that hospitals that perform a higher volume of RSAs would have improved outcomes. We also performed stratum-specific likelihood ratio (SSLR) analysis with the aim of delineating concrete definitions of hospital volume for RSA.

METHODS

The Nationwide Readmissions Database was queried for patients who had undergone elective RSA from 2011 to 2015. Annual hospital volume and 90-day outcome data were collected, including readmission, revision, complications, hospital length of stay (LOS), supramedian cost, and discharge disposition. SSLR analysis was performed to determine hospital volume cutoffs associated with increased risks for adverse events. Cutoffs generated through SSLR analysis were confirmed via binomial logistic regression.

RESULTS

The proportion of patients receiving care at high-volume centers increased from 2011 to 2015. SSLR analysis produced hospital volume cutoffs for each outcome, with higher-volume centers showing improved outcomes. The volume cutoffs associated with the best rates of 90-day outcomes ranged from 54 to 70 RSAs/year, whereas cost and resource utilization cutoffs were higher, with the best outcomes in hospitals performing >100 RSAs/year. SSLR analysis of 90-day readmission produced 3 hospital volume categories (1 to 16, 17 to 69, and ≥70 RSAs/year), each significantly different from each other. These were similar to the strata for 90-day revision (1 to 16, 17 to 53, and ≥54 RSAs/year) and 90-day complications (1 to 9, 10 to 68, and ≥69 RSAs/year). SSLR analysis produced 6 hospital volume categories for cost of care over the median value (1 to 5, 6 to 25, 26 to 47, 48 to 71, 72 to 105, and ≥106 RSAs/year), 5 categories for an extended LOS (1 to 10, 11 to 25, 26 to 59, 60 to 105, and ≥106 RSAs/year), and 4 categories for non-home discharge (1 to 31, 32 to 71, 72 to 105, and ≥106 RSAs/year).

CONCLUSIONS

We have defined hospital surgical volumes that maximize outcomes after RSA, likely related to surgical experience, ancillary staff familiarity, and protocolized pathways. This information may be used in future policy decisions to consolidate complex procedures, such as RSA, at high-volume destinations, or to encourage lower-volume institutions to strategize an approach to function as a higher-volume center.

LEVEL OF EVIDENCE

Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Can a machine learning model accurately predict patient resource utilization following lumbar spinal fusion?

BACKGROUND CONTEXT

With the increasing emphasis on value-based healthcare in Centers for Medicare and Medicaid Services reimbursement structures, bundled payment models have been adopted for many orthopedic procedures. Immense variability of patients across hospitals and providers makes these models potentially less viable in spine surgery. Machine-learning models have been shown reliable at predicting patient-specific outcomes following lumbar spine surgery and could, therefore, be applied to developing stratified bundled payment schemes.

PURPOSE

(1) Can a Naïve Bayes machine-learning model accurately predict inpatient payments, length of stay (LOS), and discharge disposition, following dorsal and lumbar fusion? (2) Can such a model then be used to develop a risk-stratified payment scheme?

STUDY DESIGN

A Naïve Bayes machine-learning model was constructed using an administrative database.

PATIENT SAMPLE

Patients undergoing dorsal and lumbar fusion for nondeformity indications from 2009 through 2016 were included. Preoperative inputs included age group, gender, ethnicity, race, type of admission, All Patients Refined (APR) risk of mortality, APR severity of illness, and Clinical Classifications Software diagnosis code.

OUTCOME MEASURES

Predicted resource utilization outcomes included LOS, discharge disposition, and total inpatient payments. Model validation was addressed via reliability, model output quality, and decision speed, based on application of training and validation sets. Risk-stratified payment models were developed according to APR risk of mortality and severity of illness.

RESULTS

A Naïve Bayes machine-learning algorithm with adaptive boosting demonstrated high reliability and area under the receiver-operating characteristics curve of 0.880, 0.941, and 0.906 for cost, LOS, and discharge disposition, respectively. Patients with increased risk of mortality or severity of illness incurred costs resulting in greater inpatient payments in a patient-specific tiered bundled payment, reflecting increased risk on institutions caring for these patients. We found that a large range in expected payments due to individuals' preoperative comorbidities indicating an individualized risk-based model is warranted.

CONCLUSIONS

A Naïve Bayes machine-learning model was shown to have good-to-excellent reliability and responsiveness for cost, LOS, and discharge disposition. Based on APR risk of mortality and APR severity of illness, there was a significant difference in episode costs from lowest to highest risk strata. After using normalized model error to develop a risk-adjusted proposed payment plan, it was found that institutions incur significantly more financial risk in flat bundled payment models for patients with higher rates of comorbidities.

Optimizing the Volume-Value Relationship in Laminectomy: An Evidence-Based Analysis of Outcomes and Economies of Scale

STUDY DESIGN

Retrospective cohort study.

OBJECTIVE

The objective of the present study was to establish evidence-based volume thresholds for surgeons and hospitals predictive of enhanced value in the setting of laminectomy.

SUMMARY OF BACKGROUND DATA

Previous studies have attempted to characterize the relationship between volume and value; however, none to the authors' knowledge has employed an evidence-based approach to identify thresholds yielding enhanced value.

METHODS

In total, 67,758 patients from the New York Statewide Planning and Research Cooperative System database undergoing laminectomy in the period 2009 to 2015 were included. We used stratum-specific likelihood ratio analysis of receiver operating characteristic curves to establish volume thresholds predictive of increased length of stay (LOS) and cost for surgeons and hospitals.

RESULTS

Analysis of LOS by surgeon volume produced strata at: <17 (low), 17 to 40 (medium), 41 to 71 (high), and >71 (very high). Analysis of cost by surgeon volume produced strata at: <17 (low), 17 to 33 (medium), 34 to 86 (high), and >86 (very high). Analysis of LOS by hospital volume produced strata at: <43 (very low), 43 to 96 (low), 97 to 147 (medium), 148 to 172 (high), and >172 (very high). Analysis of cost by hospital volume produced strata at: <43 (very low), 43 to 82 (low), 83 to 115 (medium), 116 to 169 (high), and >169 (very high). LOS and cost decreased significantly (P < 0.05) in progressively higher volume categories for both surgeons and hospitals. For LOS, medium-volume surgeons handle the largest proportion of laminectomies (36%), whereas very high-volume hospitals handle the largest proportion (48%).

CONCLUSION

This study supports a direct volume-value relationship for surgeons and hospitals in the setting of laminectomy. These findings provide target-estimated thresholds for which hospitals and surgeons may receive meaningful return on investment in our increasingly value-based system. Further value-based optimization is possible in the finding that while the highest volume hospitals handle the largest proportion of laminectomies, the highest volume surgeons do not.

LEVEL OF EVIDENCE

3.