Does healthcare system device volume correlate with price paid for spinal implants: a cross-sectional analysis of a national purchasing database. Issue 4 (26th April 2022)

• Record Type: Journal Article
• Authors: Cahan, Eli; McFarlane, Kelly; Segovia, Nicole; Chawla, Amanda; Wall, James; Shea, Kevin
• Is Part Of: BMJ open. Volume 12:Issue 4(2022)
• Publication Date: 2022-04-26
• Subjects: Health policy -- supply chain -- health economics andorganisations -- quality improvement -- orthopaedicsurgery -- paediatrics; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2021-057547
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objectives: Amid continuously rising US healthcare costs, particularly for inpatient and surgical services, strategies to more effectively manage supply chain expenses are urgently necessary. Across industries, the 'economy of scale' principle indicates that larger purchasing volumes should correspond to lower prices due to 'bulk discounts'. Even as such advantages of scale have driven health system mergers in the USA, it is not clear whether they are being achieved, including for specialised products like surgical implants which may be more vulnerable to cost inefficiency. The objective of this observational cross-sectional study was to investigate whether purchasing volumes for spinal implants was correlated with price paid. Setting: USA. Participants: Market data based on pricing levels for spine implants were reviewed from industry implant price databases. Filters were applied to narrow the sample to include comparable institutions based on procedural volume, patient characteristics and geographical considerations. Information on the attributes of 619 health systems representing 12 471 provider locations was derived from national databases and analytics platforms. Primary outcome measure: Institution-specific price index paid for spinal implants, normalised to the national average price point achieved. Results: A Spearman's correlation test indicated a weak relationship between purchasing volume and price index paid (ρ=−0.35, p<0.001). Multivariable linear regression adjusting for institutional characteristics including type of hospital, accountable care organisation status, payer-mix, geography, number of staffed beds, number of affiliated physicians and volume of patient throughput also did not exhibit a statistically significant relationship between purchasing volume and price index performance (p=0.085). Conclusions: National supply chain data revealed that there was no significant relationship between purchasing volume and price paid by health systems for spinal implants. These findings suggest that factors other than purchasing or patient volume are responsible for setting prices paid by health systems to surgical vendors and/or larger healthcare systems are not negotiating in a way to consistently achieve optimal pricing.