Data regarding the palliative needs of pediatric patients with central nervous system (CNS) cancer are scarce. We aimed to describe the attention provided by a pediatric palliative care (PPC) team to patients with CNS cancer and the differences in care compared to patients who did not receive PPC.

This retrospective study was based on the clinical records of deceased patients with CNS cancer attended by a PPC team over 10 years, analyzing their trajectory and provision of PPC, including medical, psychological, social, and nursing interventions. Furthermore, we compared the last month of life care of deceased patients with CNS cancer in the same institution, based on whether they were attended by the PPC team.

Of 71 patients, 59 received PPC, with a median of 1.6 months (Interquartile range: 0.6–5.2) from referral to death. Home hospitalization was provided to 84.8%, nursing interventions were registered in 89.8%, psychological characteristics in 84.7%, and social interventions in 88.1%. The most common symptoms were pain, dyspnea, and constipation. When comparing patients from the same hospital who received PPC (n = 36) with those who did not (n = 12), the former spent fewer days in the hospital in their last month and last week (p < 0.01) and were more likely to die at home (50% vs. 0%; p < 0.01).

Patients with CNS cancer show various medical, social, and psychological needs during end-of-life care. Providing specific PPC interventions decreased the number of days spent at the hospital and increased the rate of death at home.

We evaluated the early impact of a new hospital-based health technology assessment (HB-HTA) program, called Smart Innovation, at the University of Washington Medical Center (UWMC).

We compared the UWMC's utilization trends for two surgical procedures to control hospitals by evaluating the difference before and after adoption decisions: (i) a new filter for transcatheter aortic valve replacement (TAVR) procedures that treat aortic valve stenosis and (ii) microwave ablation (MWA) for treating hepatocellular carcinoma. We used descriptive statistics to assess the difference between the UWMC and controls for TAVR and MWA procedures and multivariate difference-in-differences (DID) analyses to test for statistical significance.

The UWMC experienced a 10 percent reduction in TAVR procedures compared with controls following the implementation of the TAVR Sentinel filter. The DID regression model indicated a 1.5 reduction in the number of TAVR procedures per quarter at the UWMC between the pre- and post period, which was not statistically significant (p-value: .87). The UWMC experienced a 51 percent reduction in utilization when compared with controls for MWA procedures in the pre- and post periods. The DID model for MWA indicated an 18.8 decrease in utilization per quarter during the study period for the UWMC, which was statistically significant (p-value: .0007). For MWA procedures, the UWMC experienced a $647,658 dollar reduction in total costs in the post period compared with controls.

When the UWMC used HB-HTA methods for technology adoption, there was a reduction in utilization and total costs when compared with controls; however, when the UWMC adopted a new technology without using HB-HTA methods, there was no difference in utilization.

We designed, developed, and implemented a new hospital-based health technology assessment (HB-HTA) program called Smart Innovation. Smart Innovation is a decision framework that reviews and makes technology adoption decisions. Smart Innovation was meant to replace the fragmented and complex process of procurement and adoption decisions at our institution. Because use of new medical technologies accounts for approximately 50 percent of the growth in healthcare spending, hospitals and integrated delivery systems are working to develop better processes and methods to sharpen their approach to adoption and management of high cost medical innovations.

The program has streamlined the decision-making process and added a robust evidence review for new medical technologies, aiming to balance efficiency with rigorous evidence standards. To promote system-wide adoption, the program engaged a broad representation of leaders, physicians, and administrators to gain support.

To date, Smart Innovation has conducted eleven HB-HTAs and made clinician-led adoption decisions that have resulted in over $5 million dollars in cost avoidance. These are comprised of five laboratory tests, three software-assisted systems, two surgical devices, and one capital purchase.

Smart Innovation has achieved cost savings, avoided uncertain or low-value technologies, and assisted in the implementation of new technologies that have strong evidence. The keys to its success have been the program's collaborative and efficient decision-making systems, partnerships with clinicians, executive support, and proactive role with vendors.