Computers can undertake complex calculations and iterative actions much faster than humans so the mathematical calculation of the probabilities of diagnoses and outcomes (and their utilities) can be undertaken. Since we do not normally undertake these calculations, they add an extra dimension to clinical evaluation
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and can be used to shed light on the significance of features of the history, clinical examination and investigation. These methods have not been widely used in orthopaedics
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. Decision analysis has been reported in the diagnosis of disc herniation
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, mortality in trauma
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, resurfacing the patella in TKA
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, outcome of the contralateral side in Slipped Capital Femoral Epiphysis
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, acute Achilles Tendon rupture
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, open and arthroscopic Bankart repair
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, DDH
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, osteoporosis
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, and OA of the wrist
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. There is more extensive literature on the related technique of cost effectiveness, which has been recently reviewed by Brauer et al.
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h3 References
Bohren BF, Hadzikadic M, 1994. "Turning medical data into decision-support knowledge." Proc Annu Symp Comput Appl Med Care : 735-9 [PubMed]
Abstract:
Advances in information collection and analysis are reaching the point of providing physicians with the help of computer-based assistants. These systems will provide rapid second opinions to physicians in a clinical setting as well as assist them in the analysis of large sets of patient descriptions for research purposes. This paper presents INC2.5 as such a decision-support system. INC2.5 extracts information from databases of previously seen patients to build a decision tree which is used to predict the outcome of new patients on a chosen variable. The concept of matching new patients with the most similar previously seen patient, on which INC2.5 is based, can be easily understood by its users. Further adding to INC2.5's ease of use is its flexibility in allowing users to customize decision trees to their liking. In order to convey the uncertainty of the environment, INC2.5 presents all decisions with a confidence factor.
Sporer SM, Rosenberg AG, 2005. "Decision analysis in orthopaedics." Clin Orthop Relat Res (431): 250-6 [PubMed]
Abstract:
Orthopaedic surgeons are faced with an ever-growing amount of clinical information from which they are required to make treatment decisions. Many of these decisions can be approached with relative certainty. However, there are many situations where the optimal decision is less clear. These treatment decisions will have competing risks, benefits, or costs. Decision analysis is one method to critically evaluate alternative treatment options with multiple potential outcomes. This method of decision making can be extremely valuable because of the growing number of treatment alternatives, and to the ever-increasing complexity of medical scenarios.
Kocher MS, Henley MB, 2003. "It is money that matters: decision analysis and cost-effectiveness analysis." Clin Orthop Relat Res (413): 106-16 [PubMed]
Abstract:
Clinical decisions must be made, often under circumstances of uncertainty and limited resources. Decision analysis and cost-effectiveness analysis are methodologic tools that allow for quantitative analysis and the optimization of decision-making. These methods can be useful for decisions regarding individual patient evaluation and treatment options or in formulating healthcare policy. We overview the methodology of expected value decision analysis and of cost-effectiveness analysis, including cost-identification, cost-effectiveness, cost-benefit, and cost-utility analyses. Examples are provided of these methods and a user's guide to cost-effectiveness analysis is outlined.
Abstract:
A microcomputer was programmed to accept data on the history and physical findings of patients, with low-back pain, suspected of having a herniated lumbar intervertebral disc, then suggest a likely diagnosis, with probability, and make suggestions for further management. Formal decision analytic techniques were used to test for the threshold of diagnostic likelihood that would make the expected value of laminotomy for excision of a herniated disc greater than the expected value of non-surgical management. The program is recursive, using its results to update its data base, and become more "intelligent." In a blinded evaluation, an expert could not detect a significant difference between the output of the computer and the diagnoses and treatment plans of ten clinicians.
Hadzikadic M, Hakenewerth A, Bohren B, Norton J, Mehta B, Andrews C, 1996. "Concept formation vs. logistic regression: predicting death in trauma patients." Artif Intell Med 8 (5): 493-504 [PubMed]
Abstract:
This study compares two classification models used to predict survival of injured patients entering the emergency department. Concept formation is a machine learning technique that summarizes known examples cases in the form of a tree. After the tree is constructed, it can then be used to predict the classification of new cases. Logistic regression, on the other hand, is a statistical model that allows for a quantitative relationship for a dichotomous event with several independent variables. The outcome (dependent) variable must have only two choices, e.g. does or does not occur, alive or dead, etc. The result of this model is an equation which is then used to predict the probability of class membership of a new case. The two models were evaluated on a trauma registry database composed of information on all trauma patients admitted in 1992 to a Level I trauma center. A total of 2155 records. representing all trauma patients admitted for more than 24 h or who died in the Emergency Department, were grouped into two databases as follows: (1) discharge status of 'died' (containing 151 records), and (2) any discharge status other than 'died' (containing 2004 records). Both databases contained the same variables.
Zangger P, Detsky A, 2000. "Computer-assisted decision analysis in orthopedics: resurfacing the patella in total knee arthroplasty as an example." J Arthroplasty 15 (3): 283-8 [PubMed]
Abstract:
The purpose of the present study was to illustrate the use of computer-assisted decision analysis in making decisions in the field of orthopaedic surgery, using the choice between resurfacing and not resurfacing the patella in total knee arthroplasty as an example. We used a decision analysis technique based on probability theory and on Bayesian logic, with the help of an especially developed computer software. The process involves building a decision tree, searching for probabilities and utilities in the literature, folding back the tree to compute the baseline result, and running sensitivity analyses. Our literature search provided 26 useful articles, only 3 of which were randomized controlled trials. In the baseline analysis, both options were rated similarly, with resurfacing the patella faring slightly better. Sensitivity analyses revealed that not resurfacing becomes the procedure of choice if the probability of postoperative anterior knee pain with an unresurfaced patella falls below 14%, or if the probability of having pain with a resurfaced patella rises above 8% or if the utility of patellar implant failure falls below 80% of the utility of a perfect health state. Computer-assisted decision analysis is a promising, evidence-based tool to assist clinical decision making in orthopaedic surgery. However, its validity is limited by the poor quality of data found in the orthopaedic literature, especially the scarcity of randomized controlled trials.
Schultz WR, Weinstein JN, Weinstein SL, Smith BG, 2002. "Prophylactic pinning of the contralateral hip in slipped capital femoral epiphysis : evaluation of long-term outcome for the contralateral hip with use of decision analysis." J Bone Joint Surg Am 84-A (8): 1305-14 [PubMed]
Abstract:
BACKGROUND: The risk of a contralateral slip in patients who are first seen with a unilateral slipped capital femoral epiphysis has been reported to be 2335 times higher than the risk of an initial slip. The overall prevalence of bilaterality varies widely throughout the literature, with some reports indicating rates as high as 80%. This finding has led many authors to recommend prophylactic pinning of the contralateral asymptomatic hip in patients presenting with a unilateral slipped capital femoral epiphysis. METHODS: A decision analysis model with probabilities for the occurrence of contralateral slip and for the severity of slip at different intervals of follow-up was used in the present study. These probabilities were compared with those for various outcomes when the contralateral hip is prophylactically pinned. Scores representing long-term outcome, according to the Iowa hip-rating system, were used in the model as a measure of utility. The probabilities of contralateral slip and the rates of slip severity were taken from large retrospective series. All meaningful clinical scenarios with regard to long-term outcome for the hip were considered in the model. Variables of uncertainty were subjected to sensitivity analyses in order to explore the effect on outcome over the range of plausible values for variables of interest. RESULTS: The results showed a benefit in the long-term outcome for patients who had prophylactic pinning of the contralateral hip. The threshold level at which a benefit is obtained with prophylactic pinning is expressed according to the rates of sequential slip, rates of slips overlooked at follow-up, and complications associated with prophylactic pinning of the contralateral hip. CONCLUSIONS: The decision model shows that, when pooled data are used to predict probabilities of sequential slip, treatment of the contralateral hip with prophylactic pinning is beneficial to the long-term outcome for that hip. When considering prophylactic pinning of the contralateral hip, the clinician should use sound clinical judgment with respect to the age, sex, and endocrine status of the patient. Long-term follow-up studies are needed to establish the efficacy of prophylactic pinning, but the predictions in the present study, which are based on findings in the literature, support the safety of this procedure.
Kocher MS, Bishop J, Marshall R, Briggs KK, Hawkins RJ, 2002 Nov-Dec. "Operative versus nonoperative management of acute Achilles tendon rupture: expected-value decision analysis." Am J Sports Med 30 (6): 783-90 [PubMed]
Abstract:
BACKGROUND: The optimal management strategy for acute Achilles tendon rupture is controversial. PURPOSE: To determine the optimal management by using expected-value decision analysis. STUDY DESIGN: Cross-sectional study. METHODS: Outcome probabilities were determined from a systematic literature review, and patient-derived utility values were obtained from a visual analog scale questionnaire. A decision tree was constructed, and fold-back analysis was used to determine optimal treatment. Sensitivity analyses were used to determine the effect of varying outcome probabilities and utilities on decision-making. RESULTS: Outcome probabilities (expressed as operative; nonoperative) were as follows: well (0.762; 0.846), rerupture (0.022; 0.121), major complication (0.030; 0.025), moderate complication (0.075; 0.003), and mild complication (0.111; 0.005). Outcome utility values were well operative (7.9), well nonoperative (7.0), rerupture (2.6), major complication (1.0), moderate complication (3.5), and mild complication (4.7). Fold-back analysis revealed operative treatment as the optimal management strategy (6.89 versus 6.30). Threshold values were determined for the probability of a moderate complication from operative treatment (0.21) and the utility of rerupture (6.8). CONCLUSIONS: Operative management was the optimal strategy, given the outcome probabilities and patient utilities we studied. Nonoperative management was favored by increasing rates of operative complications; operative, by decreasing utility of rerupture. We advocate a model of doctor-patient shared decision-making in which both outcome probabilities and patient preferences are considered.
Kailes SB, Richmond JC, 2001. "Arthroscopic vs. open Bankart reconstruction: a comparison using expected value decision analysis." Knee Surg Sports Traumatol Arthrosc 9 (6): 379-85 [PubMed]
Abstract:
The reporting of midterm failure rates following arthroscopic shoulder stabilization for recurrent anterior instability of the glenohumeral joint has shown that the risk of failure may be higher with arthroscopic techniques than with traditional open methods. The use of expected value decision analysis offers an explicit, consistent, and structured means to assist the clinician in determining which stabilization technique to utilize. Decision analysis reveals that the surgical technique that is favored for a given patient depends on the value that the patient assigns to various potential outcomes following surgery, the perioperative morbidity of each of the two procedures, and the surgeon's probability of success with either technique
Roposch A, Wedge JH, Krahn MD, 2006. "The role of the ossific nucleus in the treatment of established hip dislocation." Clin Orthop Relat Res 449: 295-302 [PubMed]
Abstract:
Timing the reduction of a delayed presenting dislocated hip is controversial if the ossific nucleus of the proximal femoral epiphysis is absent. We formulated a decision model for management of 6- to 13-month-old infants based on two strategies: waiting for the ossific nucleus to appear before reducing the hip or immediate reduction. The model included the occurrence of long-term physical disability within a period of 20 years. A literature synthesis provided outcome probabilities. Outcome was measured by utilities derived by content experts. Waiting for the ossific nucleus was the preferred strategy with an expected value of 0.95 as opposed to 0.86 in the immediate reduction strategy. Sensitivity analyses showed the model was robust. Based on the results of decision analysis, reducing a dislocated hip in the presence of the ossific nucleus is likely to be the better strategy if avascular necrosis and long-term disability are considered. The difference between the two strategies is equivalent to one quality-adjusted life year, which is substantial. Level of Evidence: Economic and Decision Analyses, Level II-1. See the Guidelines for Authors for a complete description of levels of evidence.
Atik OS, Gunal I, Korkusuz F, 2006. "Burden of osteoporosis." Clin Orthop Relat Res 443: 19-24 [PubMed]
Abstract:
The number of the people with osteoporosis increases as the population ages. Increasing numbers of patients with osteoporotic fractures may have a serious economic impact on society and on the quality of life of the patient. We review some literature and provide expert opinion on the burden of osteoporosis. Awareness among clinicians and health care professionals on osteoporosis should be increased to overcome the burden of the disease. Although most of the osteoporotic fractures are treated by orthopaedic surgeons, many patients with these problems are not diagnosed appropriately and treated for probable osteoporosis. Appropriate diagnosis of the disease is essential to prevent osteoporotic fractures and related mortality and morbidity. Indirect costs and sociologic and psychological impact of fractures should be evaluated together with the direct costs of the disease. LEVEL OF EVIDENCE: Economic and decision analysis, level V (expert opinion). See the Guidelines for Authors for a complete description of the levels of evidence.
Graham B, Detsky AS, 2001. "The application of decision analysis to the surgical treatment of early osteoarthritis of the wrist." J Bone Joint Surg Br 83 (5): 650-4 [PubMed]
Abstract:
Osteoarthritis of the wrist is a complication of a number of common traumatic conditions. Arthrodesis of the radiocarpal joint, proximal row carpectomy and excision of the scaphoid, combined with midcarpal arthrodesis, have all been reported as surgical options. There have been no randomised studies comparing these procedures, and the feasibility of conducting this type of trial is limited. We used decision analysis to compare the three surgical techniques. The variables for the model used were based principally on data from the literature. Extensive sensitivity analyses were carried out to test the impact of the values given to these variables on the outcome of the model. The model indicated that the preferred treatment is proximal row carpectomy. Decision analysis allows a comparison between alternative treatments, when evidence from a randomised trial is lacking or unobtainable. The decision-analysis model may also provide insight into aspects of a problem which would be difficult, or impossible, to evaluate by a cohort study.
Brauer CA, Neumann PJ, Rosen AB, 2007. "Trends in cost effectiveness analyses in orthopaedic surgery." Clin Orthop Relat Res 457: 42-8 [PubMed]
Abstract:
Worldwide, programs dealing with musculoskeletal health are required to set priorities and allocate resources within the constraint of limited funding. There is increasing pressure for medical technology assessment, which traditionally has involved evaluating safety and effectiveness, to also include consideration of cost effectiveness. We updated our database of orthopaedic cost-effectiveness studies, critically reviewed their methods, and examined trends over time. Current analyses have numerous shortcomings, such as the inclusion of relatively few studies, inconsistent methodologic approaches, and lack of transparency. The wide variation in cost-effectiveness ratios observed among current interventions suggests efficiency can be improved. Despite reimbursement authorities in many other countries formally considering cost-effectiveness when determining coverage of new technologies, Medicare has been resistant to considering costs of treatments. Regardless of this policy deficiency, conducting cost-effectiveness analyses represents a prudent step forward in illuminating the tradeoffs involved in difficult resource allocation decisions, and there is an urgent need to consider economic impact in future studies using standardized and transparent methods.
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