The effectiveness of the program was measured as the estimated decrease in the incidence of future fractures. The predicted annual incidence of future hip fractures depends on the known relative risk of future fractures, which is based on the age and gender of the patients, the sites of the index fractures (wrist, hip, humerus, other), and the proportion of fractures attributable to osteoporosis. The age and gender-specific data on index fragility fractures were multiplied by the relative risk of future hip fracture to determine the probability of sustaining a future hip fracture. In the presence of a coordinator, the probability of future hip fracture was modified by the initiation of specific osteoporosis treatments and their known efficacies, adjusted by known ratios of patient adherence to care.
Costs and Resource Utilization
The analysis was performed from the perspective of hospital costs (Table IV). The cost of the coordinator, working part-time (50%), was C$27,000 per year (all values are given in year-2004 Canadian dollars), which includes 30% benefits. The mean cost per hip fracture treated was C$21,800 (median, C$13,829). These actual costs, which were obtained from the hospital (as opposed to being medical charges to an insurer), reflected ward costs, intensive care unit costs, perioperative costs, laboratory costs, imaging costs, catheter laboratory costs, ward and intensive care unit expendable costs, pharmacy costs, physiotherapy and allied health costs, and overhead costs. The total treatment costs for individual patients varied widely because of the clinical course, complications, and length of stay and ranged from C$3500 to C$183,000.
There were six key assumptions. First, it was assumed that future hip fracture costs would be attributed to one hospital facility. Second, it was assumed that patients who are not adherent with treatment receive no benefit (fracture risk reduction) from the treatment. Third, it was assumed that, in the absence of a coordinator, the proportion of patients who are treated for osteoporosis is calculated as the number of patients in the program population who had received osteoporosis treatment prior to the fracture, plus 20% of the remaining patients who are assumed would have been additionally treated for osteoporosis following the index fracture without a coordinator being present. This assumption was derived from the results of two studies20,21. In three urban fracture clinics, with similar demographics to the program population, 18% of the patients with fragility fractures underwent investigation for and received adequate treatment of osteoporosis one year following fracture20. In five fracture clinics in the same region, 17% of patients with fragility fractures were recommended one or more treatments for osteoporosis three to six months following a simple intervention, not managed by a dedicated coordinator, that consisted of informing the patients of their osteoporosis risk, recommending follow-up with their family physician, and sending a standardized letter to the physician21. Fourth, an adherence of 49%, based on a Canadian study of prescription drug use in 11,252 women for whom osteoporosis medication had been prescribed over a five-year period22, was assumed for patients who were lost to follow-up, who constituted 35% of all treated patients in the program population. Fifth, an adherence of 49%22 also was assumed for patients in the no-coordinator cohort who were treated for osteoporosis. Sixth, in the absence of information on treatments in the no-coordinator cohort, the same distribution of treatments and efficacy as in the coordinator cohort was assumed.
The base-case cost-effectiveness analysis compared the health outcomes and costs associated with the two strategies (“no coordinator” and “coordinator”). The incremental cost-effectiveness ratio (ICER) was calculated as follows:
Sensitivity analysis tested the stability of the conclusions over a range of structural assumptions, probability estimates, and outcome values23. Deterministic (one-way and multiway) sensitivity analyses and probabilistic sensitivity analysis (second-order Monte Carlo simulation) were performed (see Appendix).
In deterministic sensitivity analyses, the values of one or multiple variables in question were varied while the other probability and outcome values remained constant. All variables were tested with one-way sensitivity analysis over a range of plausible estimates.
Probabilistic sensitivity analysis modeled the uncertainty related to input variables by using probability distributions of their point estimates, consistent with the data types. For each simulation run, a value from the distribution of each variable was chosen at random, generating one set of outputs. This was repeated, such that a large number of iterations (10,000) generated a distribution of outcomes, effectiveness, and costs. Additional details on the probabilistic sensitivity analysis and the distributions chosen are available in the Appendix.
The base-case cost-effectiveness analysis showed that hiring a coordinator was estimated not only to be more effective in terms of a reduced incidence of subsequent hip fractures in the first year but also to be less costly (Table VI) and therefore constitutes a dominant strategy.
For a cohort of 500 patients managed by a part-time coordinator, the expected number of hip fractures was estimated to be reduced from thirty-four without the coordinator to thirty-one with the coordinator in the first year, which resulted in net hospital cost savings of C$48,950 after program costs.
Deterministic sensitivity analysis revealed that a coordinator led to cost savings in comparison with no coordinator under four conservative conditions: (1) if the cost per hip fracture was as low as C$8000, (2) if only 60% of patients initiated treatment and only 40% complied, (3) if treatment efficacy reduced the incidence of future hip fractures by no more than 10%, and (4) if as few as 350 patients were seen annually.
Probabilistic sensitivity analysis confirmed the robustness of the model. The results of the 10,000 iterations are shown in an incremental cost-effectiveness scatterplot (Fig. 2). Most simulations resulted in the “coordinator” strategy being more effective and less costly than the “no-coordinator” strategy, with most iteration results below a threshold cost of C$25,000. Probabilistic sensitivity analysis indicated a 90% probability that hiring a coordinator costs less than C$25,000 per hip fracture avoided.
The coordinator model of post-fracture osteoporosis care is an effective intervention8-12 that we have now demonstrated to be cost-effective in comparison with the no-coordinator model. Hiring a part-time coordinator to identify and manage patients who have fragility fractures was estimated, under very conservative assumptions, to increase the uptake of and adherence to treatment and hence to prevent subsequent hip fractures. The coordinator model resulted in a net hospital cost savings of C$48,950 in the first year following the incident fracture in comparison with the no-coordinator model. The probability that such an intervention is cost-effective, taking into account uncertainty related to input data, was calculated to be 90% at a threshold cost of C$25,000 per subsequent hip fracture avoided.
This intervention is suitable for environments in which large numbers of patients with fragility fractures can be accessed, including fracture clinics, orthopaedic and trauma units, and outpatient and inpatient rehabilitation facilities. It is also possible, although not yet proven, that this intervention model could be adapted for the large patient populations of health maintenance organizations, Medicare, and the United States Department of Veterans Affairs Health Administration, but this was not examined in our study nor has it been reported elsewhere. However, a different intervention consisting of health-care-provider and community education and a bone density testing program significantly reduced the incidence of hip fractures and increased osteoporosis treatment in all women over the age of fifty-five years who were enrolled in a health management program24. We therefore believe that the coordinator model should be further examined for its potential to be applied to high-risk patients, namely, those who have already sustained a fracture, in such organizations on a larger scale.
The present analysis includes only costs incurred in hospital. Hospital costs are tangible costs that can be accurately determined and tend to be similar in modern health-care jurisdictions. Drug costs, physician visits for long-term treatment, and nonhospital costs related to subsequent fractures (e.g., rehabilitation, loss of independence, assistive devices, transportation needs) were not included in the analysis. For example, it has been reported that 34% to 48% of surviving patients with an age of sixty-five years or more have not returned to independent living at one year following hip fracture25-28, generating substantial costs associated with chronic care. Such costs tend to vary across different locations or societies, and other costs, such as loss of employment and loss of productivity of the family member caring for a hip fracture patient, may be discretionary and subject to interpretation. Prevention of these latter costs would increase the beneficial economic impact of the coordinator program. Furthermore, future fractures involving sites other than the hip, which usually are treated without hospital admission and are associated with lesser costs, were not considered in the present study. Thus, the hospital cost perspective is likely to underestimate the overall cost savings to the health-care system associated with the coordinator model as compared with the no-coordinator model. As the cost analysis of this intervention based on hospital costs alone showed that a coordinator was associated with cost savings, the additional savings on full system costs will theoretically provide even further support for adopting a coordinator program for post-fracture osteoporosis care.
The present analysis was restricted to one year as most of the data were collected from the first year of the program. The benefits to patients and providers for the prevention of fractures that are expected to occur two, three, or more years after the index fracture were therefore not considered, and to this extent the value of the coordinator is again underestimated.
The present study had several strengths. First, the model was robust and was based on high-quality data. Values for adherence with care normally would be estimated, but in the present study they were drawn from published or program data. The risk of future hip fracture was drawn from the literature and was determined separately for each fracture site treated. The efficacy of care was based on the efficacy of drugs as reported in the literature19 and on real care that these patients received in the program8, and the efficacy of care in the absence of a coordinator was generated from meta-analyses of large trials. We determined the risk of future fracture from published data on large populations rather than using the known subsequent fractures in our own smaller population. Many conservative assumptions, which tended to underestimate the benefit of the coordinator model in comparison with the no-coordinator model, were made. For example, it was assumed that (1) in the absence of a coordinator, the proportion of patients who would be treated for osteoporosis included the number of patients in the program population who had received osteoporosis treatment prior to fracture plus an additional 20% of the remaining population (representing 44% of the patient population), (2) patients who were not adherent with treatment would have no fracture risk reduction from the treatment, and (3) the adherence rate would be 49% for patients who were lost to follow-up and for patients in the no-coordinator cohort. Despite these conservative assumptions, the coordinator strategy was cost-effective.
The proportion of patients receiving treatment prior to enrollment in the program (>30%) was higher than generally has been reported, possibly as a result of osteoporosis programs initiated in our area in the past ten years. Nevertheless, we used this high baseline level of treatment in the model, which would be a conservative assumption for other geographical locations. This resulted in a generous estimate of the proportion of patients who would be managed in the absence of a coordinator—approximately 44% of the program's total patient population. A more modest assumption based on typical follow-up rates reported in most published reviews6,7,20, i.e., that only 20% of patients would be managed in the absence of a coordinator, will result in further cost savings.
We used conservative estimates of the treatment efficacy of bisphosphonates19. This may also have underestimated the benefits of the coordinator. All patients in the study experienced a fragility fracture and thus constituted a high-risk population who might benefit from antiresorptive treatment. New treatments currently becoming available may have a higher efficacy29.
In systems in which various phases of management are captured by one payer, such as the United States Department of Veterans Affairs Health Administration, a large health-maintenance organization, or an environment with publicly funded care (i.e., Medicaid, individual Canadian provinces, certain countries with public health funding), the costs of the coordinator and the costs of future hip fractures are in the payer's budget, matching the assumptions of this analysis.
In conclusion, the present study indicates that the decision to employ a part-time coordinator to manage osteoporosis in patients with fragility fractures is likely to prevent subsequent hip fractures and thereby to be cost-effective from a hospital cost perspective when compared with the decision not to employ a coordinator.
The details of the probabilistic sensitivity analysis are available with the electronic versions of this article, on our web site at jbjs.org (go to the article citation and click on “Supplementary Material”) and on our quarterly CD-ROM (call our subscription department, at 781-449-9780, to order the CD-ROM).
NOTE: The authors thank Dagmar Gross for writing and editing assistance and Dr. Andreas Laupacis for reviewing the manuscript.
Disclosure: In support of their research for or preparation of this work, one or more of the authors received, in any one year, outside funding or grants in excess of $10,000 from an unrestricted research grant from Merck Frosst Canada, and a CIHR New Investigators Award. In addition, one of the authors became a salaried employee (with a salary in excess of $10,000), and continues to be an employee, of Amgen (Europe) GmbH in November 2004. No commercial entity paid or directed, or agreed to pay or direct, any benefits to any research fund, foundation, division, center, clinical practice, or other charitable or nonprofit organization with which the authors, or a member of their immediate families, are affiliated or associated.
A commentary is available with the electronic versions of this article, on our web site (www.jbjs.org) and on our quarterly CD-ROM (call our subscription department, at 781-449-9780, to order the CD-ROM).
Investigation performed at University Health Network and St. Michael's Hospital, Toronto, Ontario, Canada
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