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1.
J Surg Orthop Adv ; 33(1): 14-16, 2024.
Article in English | MEDLINE | ID: mdl-38815072

ABSTRACT

The SARS-CoV-2 pandemic affected surgical management in Orthopaedics. This study explores the effect of COVID-19-positive patients on time to surgery from admission, total time spent in preoperative preparation, costs of orthopaedic care, and inpatient days in COVID-19-positive patients. The authors' case-matched study was based on the surgeon, procedure type, and patient demographics. The authors reviewed 58 cases, 23 males and 35 females. The results for the COVID-19-positive and -negative groups are time to admission (362.9; 388.4), time in preparation (127.8; 122.3), inpatient days to surgery (0.2; 0.2), and orthopaedic cost ($81,938; $86,352). With available numbers, no significant difference could be detected for inpatient days until surgery, any associated time to surgery, or orthopaedic costs for operating on COVID-19-positive patients during the pandemic. Perceived increased time and cost of care of COVID-19-positive patients were not proven in this study. (Journal of Surgical Orthopaedic Advances 33(1):014-016, 2024).


Subject(s)
COVID-19 , Elective Surgical Procedures , Orthopedic Procedures , Humans , COVID-19/epidemiology , Male , Orthopedic Procedures/economics , Orthopedic Procedures/statistics & numerical data , Female , Elective Surgical Procedures/economics , Case-Control Studies , Middle Aged , Adult , Aged , Length of Stay/statistics & numerical data , SARS-CoV-2 , Retrospective Studies , Time-to-Treatment , Pandemics
2.
Clin Chem ; 59(4): 649-57, 2013 Apr.
Article in English | MEDLINE | ID: mdl-23230323

ABSTRACT

BACKGROUND: Adverse outcomes associated with prescription drug use are common and costly. Many adverse outcomes can be avoided through pharmacogenomics: choosing and dosing of existing drugs according to a person's genomic variants. Finding and validating associations between outcomes and genomic variants and developing guidelines for avoiding drug-related adverse outcomes will require further research; however, no data-driven estimates yet exist for the time or money required for completing this research. METHODS: We identified examples of associations between adverse outcomes and genomic variants. We used these examples to estimate the time and money required to identify and confirm other associations, including the cost of failures, and to develop and validate pharmacogenomic dosing guidelines for them. We built a Monte Carlo model to estimate the time and financial costs required to cut the overall rate of drug-related adverse outcomes by meaningful amounts. We analyzed the model's predictions for a broad range of assumptions. RESULTS AND CONCLUSIONS: Our model projected that the development of guidelines capable of cutting overall drug-related adverse outcomes by 25%-50% with current approaches will require investment of single-digit billions of dollars and take 20 years. The model forecasts a pump-priming phase of 5-7 years, which would require expenditures of hundreds of millions of dollars, with little apparent return on investment. The single most important parameter was the extent to which genomic variants cause adverse outcomes. The size of the labor force was not a limiting factor. A "50 000 Pharmacogenomes Project" could speed progress. Our approach provides a template for other areas of genomic research.


Subject(s)
Evidence-Based Medicine , Genomics , Health Care Costs , Pharmacogenetics
3.
J Bone Joint Surg Am ; 99(1): 65-75, 2017 Jan 04.
Article in English | MEDLINE | ID: mdl-28060235

ABSTRACT

BACKGROUND: The decision between open reduction and internal fixation (ORIF) and arthroplasty for a displaced femoral neck fracture in a patient ≤65 years old can be challenging. Both options have potential drawbacks; if a fracture treated with ORIF fails to heal it may require a revision operation, whereas a relatively young patient who undergoes arthroplasty may need revision within his/her lifetime. The purpose of this study was to employ decision analysis modeling techniques to generate evidence-based treatment recommendations in this clinical scenario. METHODS: A Markov decision analytic model was created to simulate outcomes after ORIF, total hip arthroplasty (THA), or hemiarthroplasty in patients who had sustained a displaced femoral neck fracture between the ages of 40 and 65 years. The variables in the model were populated with values from studies with high-level evidence and from national registry data reported in the literature. The model was used to estimate the threshold age above which THA would be the superior strategy. Results were tested using sensitivity analysis and probabilistic statistical analysis. RESULTS: THA was found to be a cost-effective option for a displaced femoral neck fracture in an otherwise healthy patient who is >54 years old, a patient with mild comorbidity who is >47 years old, and a patient with multiple comorbidities who is >44 years old. The average clinical outcomes of THA and ORIF were similar for patients 40 to 65 years old, although ORIF had a wider variability in outcomes based on the success or failure of the initial fixation. For all ages and cases, hemiarthroplasty was associated with worse outcomes and higher costs. CONCLUSIONS: Compared with ORIF, primary THA can be a cost-effective treatment for displaced femoral neck fractures in patients 45 to 65 years of age, with the age cutoff favoring THA decreasing as the medical comorbidity and risk of ORIF fixation failure increase. Hemiarthroplasty has worse outcomes at higher costs and is not recommended in this age group. LEVEL OF EVIDENCE: Economic and decision analysis Level III. See Instructions for Authors for a complete description of levels of evidence.


Subject(s)
Arthroplasty, Replacement, Hip/economics , Femoral Neck Fractures/surgery , Fracture Fixation, Internal/economics , Hemiarthroplasty/economics , Adult , Aged , Cost-Benefit Analysis , Decision Support Techniques , Femoral Neck Fractures/economics , Humans , Markov Chains , Middle Aged , Quality of Life , Reoperation/economics , Treatment Outcome
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