Real-World Clinical and Economic Outcomes Associated with Surgiflo® vs Floseal in Cardiovascular Surgeries in the US.

Background: Topical hemostatic agents are an option for controlling bleeding during cardiovascular surgery. Previous studies comparing topical hemostatic agents in cardiovascular surgery predate the 2012 reformulation of Surgiflo®, which had been re-engineered to increase paste viscosity and thus be more adherent to the bleeding surface. Objective: To compare clinical and economic outcomes in patients receiving the current formulation of Surgiflo vs Floseal during cardiovascular surgeries. Methodology: A retrospective analysis was conducted using the Premier Healthcare Database. Eligible patients had an inpatient cardiovascular surgery between 1/1/2013 and 6/1/2018, were ≥18 years old and received the current formulation of Surgiflo or Floseal during surgery. Propensity score matching was performed, with exact matching on the surgery year and surgery type (aortic, coronary artery bypass grafting, valve, or other). Descriptive analysis and generalized estimating equations models compared outcomes between the Surgiflo and Floseal groups. Results: The matched sample included 5768 patients in each group (mean age: 66.5 years; 66.3% male). In the matched sample, rates of any documented bleeding event were similar in Surgiflo and Floseal groups (6.9% vs 7.2%; P = 0.576). Differences in transfusion rates between patients receiving Surgiflo vs Floseal varied by operational definition and timing of measurement but did not differ by >2 percentage points. Compared to Floseal, patients who received Surgiflo experienced longer surgery duration (306.0 vs 299.4 minutes), lower hospitalization cost ($44,146 vs $46,812), and lower odds of readmission at 30, 60, and 90 days post-discharge (all P < 0.05). Inpatient mortality and LOS were comparable between Surgiflo and Floseal (all P > 0.05). Conclusion: In this large study of real-world clinical and economic outcomes after cardiovascular surgery involving the current formulation of Surgiflo vs Floseal, Surgiflo was associated with mostly similar clinical outcomes as compared with Floseal. Differences in selected economic/resource use outcomes were also observed, for which root-cause analysis in future research would be informative.

Effects of dose titration on adherence and treatment duration of pregabalin among patients with neuropathic pain: A MarketScan database study.

OBJECTIVE: To examine pregabalin dose titration and its impact on treatment adherence and duration in patients with neuropathic pain (NeP). METHODS: MarketScan database (2009-2014) was used to extract a cohort of incident adult pregabalin users with NeP who had at least 12 months of follow-up data. Any dose augmentation within 45 days following the first pregabalin claim was defined as dose titration. Adherence (measured by medication possession ratio/MPR) and persistence (measured as the duration of continuous treatment) were compared between the cohorts with and without dose titration. Logistic regressions and Cox proportional hazards models were used to identify the factors associated with adherence (MPR ≥ 0.8) and predictors of time to discontinuation. RESULTS: Among the 5,186 patients in the analysis, only 18% of patients had dose titration. Patients who had dose titration were approximately 2.6 times as likely to be adherent (MPR ≥ 0.8) (odds ratio = 2.59, P < 0.001) than those who did not have dose titration. Kaplan-Meier analysis shows that the time to discontinuation or switch was significantly longer among patients who had dose titration (4.99 vs. 4.04 months, P = 0.009). CONCLUSIONS: Dose titration was associated with improved treatment adherence and persistence among NeP patients receiving pregabalin. The findings will provide valuable evidence to increase physician awareness of dose recommendations in the prescribing information and to educate patients on the importance of titration and adherence.

Machine Learning for Precision Health Economics and Outcomes Research (P-HEOR): Conceptual Review of Applications and Next Steps.

Precision health economics and outcomes research (P-HEOR) integrates economic and clinical value assessment by explicitly discovering distinct clinical and health care utilization phenotypes among patients. Through a conceptualized example, the objective of this review is to highlight the capabilities and limitations of machine learning (ML) applications to P-HEOR and to contextualize the potential opportunities and challenges for the wide adoption of ML for health economics. We outline a P-HEOR conceptual framework extending the ML methodology to comparatively assess the economic value of treatment regimens. Latest methodology developments on bias and confounding control in ML applications to precision medicine are also summarized.