Matthew J Lee1, Khalid M S Mohamed1, John C Kelly1, John G Galbraith1, John Street2, Brian J Lenehan1. 1. Department of Orthopaedic Surgery, Mid Western Orthopaedic Regional Hospital, University Hospital Limerick, Limerick, Ireland. 2. Department of Orthopaedic Surgery, Vancouver General Hospital, University of British Columbia, British Columbia, Canada.
Abstract
BACKGROUND: In Ireland, funding of joint arthroplasty procedures has moved to a pay-by-results national tariff system. Typically, adverse clinical events are recorded via retrospective chart-abstraction methods by administrative staff. Missed or undocumented events not only affect the quality of patient care but also may unrealistically skew budgetary decisions that impact fiscal viability of the service. Accurate recording confers clinical benefits and financial transparency. The aim of this study was to compare a prospectively implemented adverse events form with the current national retrospective chart-abstraction method in terms of pay-by-results financial implications. METHODS: An adverse events form adapted from a similar validated model was used to prospectively record complications in 51 patients undergoing total hip or knee arthroplasties. Results were compared with the same cohort using an existing data abstraction method. Both data sets were coded in accordance with current standards for case funding. RESULTS: Overall, 114 events were recorded during the study through prospective charting of adverse events, compared with 15 events documented by customary method (a significant discrepancy). Wound drainage (15.8%) was the most common complication, followed by anemia (7.9%), lower respiratory tract infections (7.9%), and cardiac events (7%). A total of €61,956 ($67,778) in missed funding was calculated as a result. CONCLUSION: This pilot study demonstrates the ability to improve capture of adverse events through use of a well-designed assessment form. Proper perioperative data handling is a critical aspect of financial subsidies, enabling optimal allocation of funds.
BACKGROUND: In Ireland, funding of joint arthroplasty procedures has moved to a pay-by-results national tariff system. Typically, adverse clinical events are recorded via retrospective chart-abstraction methods by administrative staff. Missed or undocumented events not only affect the quality of patient care but also may unrealistically skew budgetary decisions that impact fiscal viability of the service. Accurate recording confers clinical benefits and financial transparency. The aim of this study was to compare a prospectively implemented adverse events form with the current national retrospective chart-abstraction method in terms of pay-by-results financial implications. METHODS: An adverse events form adapted from a similar validated model was used to prospectively record complications in 51 patients undergoing total hip or knee arthroplasties. Results were compared with the same cohort using an existing data abstraction method. Both data sets were coded in accordance with current standards for case funding. RESULTS: Overall, 114 events were recorded during the study through prospective charting of adverse events, compared with 15 events documented by customary method (a significant discrepancy). Wound drainage (15.8%) was the most common complication, followed by anemia (7.9%), lower respiratory tract infections (7.9%), and cardiac events (7%). A total of €61,956 ($67,778) in missed funding was calculated as a result. CONCLUSION: This pilot study demonstrates the ability to improve capture of adverse events through use of a well-designed assessment form. Proper perioperative data handling is a critical aspect of financial subsidies, enabling optimal allocation of funds.
Authors: Daniel C Norvell; Jane B Shofer; Sigvard T Hansen; James Davitt; John G Anderson; Donald Bohay; J Chris Coetzee; John Maskill; Michael Brage; Michael Houghton; William R Ledoux; Bruce J Sangeorzan Journal: Foot Ankle Int Date: 2018-05-31 Impact factor: 2.827
Authors: Katie Garland; Brian P. Chen; Stephane Poitras; Eugene K. Wai; Stephen P. Kingwell; Darren M. Roffey; Paul E. Beaulé Journal: Can J Surg Date: 2020-01-22 Impact factor: 2.089