INTRODUCTION: A shorter delay time from chronic pain diagnosis to spinal cord stimulation (SCS) implantation may make it more likely to achieve lasting therapeutic efficacy with SCS. The objective of this analysis was to determine the impact of pain-to-SCS time on patients' post-implant healthcare resource utilization (HCRU). METHODS: A retrospective observational study was performed using a real-world patient cohort derived from MarketScan(®) Commercial and Medicare Supplemental claims data bases from April 2008 through March 2013. The predictor variable was the time from the first diagnosis of chronic pain to permanent SCS implant. Using multivariable analysis, we studied the impact of pain-to-SCS time on HCRU in the first year post-implant. For some regression tests, patients were grouped into terciles by HCRU. RESULTS: A total of 762 patients met inclusion criteria, with a median pain-to-SCS time of 1.35 years (Q1: 0.8, Q3: 1.9). For every one-year increase in pain-to-SCS time, the odds increased by 33% for being in the high medical expenditures group (defined using the upper tercile: $4133 over above) over the low group (first lower: $603 or less). The odds increased by 39% for being in the high opioid prescriptions group (10-58 prescriptions) over the low group (0-1). The odds increased by 44% and 55%, respectively, for being in the high office visits (8-77) or hospitalizations (3-28) group over the low office visits (0-2) or hospitalizations (0) group. CONCLUSIONS: HCRU increased in the year following SCS implantation with longer pain-to-SCS time. These results suggest that considering SCS earlier in the care continuum for chronic pain may improve patient outcomes, with reductions in hospitalizations, clinic visits, and opioid usage.
INTRODUCTION: A shorter delay time from chronic pain diagnosis to spinal cord stimulation (SCS) implantation may make it more likely to achieve lasting therapeutic efficacy with SCS. The objective of this analysis was to determine the impact of pain-to-SCS time on patients' post-implant healthcare resource utilization (HCRU). METHODS: A retrospective observational study was performed using a real-world patient cohort derived from MarketScan(®) Commercial and Medicare Supplemental claims data bases from April 2008 through March 2013. The predictor variable was the time from the first diagnosis of chronic pain to permanent SCS implant. Using multivariable analysis, we studied the impact of pain-to-SCS time on HCRU in the first year post-implant. For some regression tests, patients were grouped into terciles by HCRU. RESULTS: A total of 762 patients met inclusion criteria, with a median pain-to-SCS time of 1.35 years (Q1: 0.8, Q3: 1.9). For every one-year increase in pain-to-SCS time, the odds increased by 33% for being in the high medical expenditures group (defined using the upper tercile: $4133 over above) over the low group (first lower: $603 or less). The odds increased by 39% for being in the high opioid prescriptions group (10-58 prescriptions) over the low group (0-1). The odds increased by 44% and 55%, respectively, for being in the high office visits (8-77) or hospitalizations (3-28) group over the low office visits (0-2) or hospitalizations (0) group. CONCLUSIONS: HCRU increased in the year following SCS implantation with longer pain-to-SCS time. These results suggest that considering SCS earlier in the care continuum for chronic pain may improve patient outcomes, with reductions in hospitalizations, clinic visits, and opioid usage.
Authors: Roger Chou; Judith A Turner; Emily B Devine; Ryan N Hansen; Sean D Sullivan; Ian Blazina; Tracy Dana; Christina Bougatsos; Richard A Deyo Journal: Ann Intern Med Date: 2015-02-17 Impact factor: 25.391
Authors: Shivanand P Lad; Paul S Kalanithi; Robert T Arrigo; Chirag G Patil; Jay K Nathan; Maxwell Boakye; Jaimie M Henderson Journal: Neuromodulation Date: 2010-10
Authors: Suneet Mittal; Dan L Musat; Michael H Hoskins; Julie B Prillinger; Gregory J Roberts; Yelena Nabutovsky; Faisal M Merchant Journal: J Am Heart Assoc Date: 2017-11-27 Impact factor: 5.501
Authors: Suneet Mittal; Dan L Musat; Michael H Hoskins; Julie B Prillinger; Gregory J Roberts; Yelena Nabutovsky; Faisal M Merchant Journal: J Interv Card Electrophysiol Date: 2018-02-28 Impact factor: 1.900