Needles in a Haystack: Finding Qualitative and Quantitative Collaborators in Academic Medical Centers.

Translational research is a data-driven process that involves transforming scientific laboratory- and clinic-based discoveries into products and activities with real-world impact to improve individual and population health. Successful execution of translational research requires collaboration between clinical and translational science researchers, who have expertise in a wide variety of domains across the field of medicine, and qualitative and quantitative scientists, who have specialized methodologic expertise across diverse methodologic domains. While many institutions are working to build networks of these specialists, a formalized process is needed to help researchers navigate the network to find the best match and to track the navigation process to evaluate an institution's unmet collaborative needs. In 2018, a novel analytic resource navigation process was developed at Duke University to connect potential collaborators, leverage resources, and foster a community of researchers and scientists. This analytic resource navigation process can be readily adopted by other academic medical centers. The process relies on navigators with broad qualitative and quantitative methodologic knowledge, strong communication and leadership skills, and extensive collaborative experience. The essential elements of the analytic resource navigation process are as follows: (1) strong institutional knowledge of methodologic expertise and access to analytic resources, (2) deep understanding of research needs and methodologic expertise, (3) education of researchers on the role of qualitative and quantitative scientists in the research project, and (4) ongoing evaluation of the analytic resource navigation process to inform improvements. Navigators help researchers determine the type of expertise needed, search the institution to find potential collaborators with that expertise, and document the process to evaluate unmet needs. Although the navigation process can create a basis for an effective solution, some challenges remain, such as having resources to train navigators, comprehensively identifying all potential collaborators, and keeping updated information about resources as methodologists join and leave the institution.

Health Care Economics of High-Frequency Spinal Cord Stimulation for Painful Diabetic Peripheral Neuropathy.

BACKGROUND: Painful diabetic peripheral neuropathy (pDPN) is a debilitating complication of long-term diabetes. High-frequency spinal cord stimulation (HF-SCS) was recently shown to be an effective treatment option, but the associated health care resource utilization (HCRU) on real-world patient populations with pDPN is unknown. METHODS: Using IBM MarketScan databases, we identified patients with HF-SCS implantation between January 2016 and December 2019 who had a diagnosis of diabetes or diabetic neuropathy within two years before implant. Cost data were collected for the six months before HF-SCS implantation (baseline) and for the periods of one, three, and six months post-implantation. The six-month explant rate was calculated. RESULTS: A total of 132 patients met inclusion criteria. The median total cost at baseline was $19 220 and was $1356 at one month post-implant, $4858 at three months post-implant, and $13 305 at six months post-implant. The median baseline out-of-pocket cost was $1477 and was $710 at six months post-implant. The average total cost reduction from baseline to six months post-implant was $5118 (P < .001), or $853 per month. The median device acquisition cost was $35 755. The explant rate within six months was 2.1%. CONCLUSIONS: High-frequency spinal cord stimulation significantly reduces total HCRU in patients with pDPN, and based on the average monthly cost reduction of $853, we estimate that the therapy recoups acquisition costs within 3.5 years. As policy increasingly focuses on value-based care, it will be critical to consider the cost and outcomes of innovative therapies.