A Coordinator Program in Post-Fracture Osteoporosis Management Improves Outcomes and Saves Costs

Sander, Beate MEcDev; Elliot-Gibson, Victoria MSc; Beaton, Dorcas E. PhD; Bogoch, Earl R. MD; Maetzel, Andreas MD, PhD

Journal of Bone & Joint Surgery - American Volume: 01 June 2008 - Volume 90 - Issue 6 - p 1197–1205
doi: 10.2106/JBJS.G.00980
Scientific Articles

Background: The orthopaedic unit at a university teaching hospital hired an osteoporosis coordinator to identify patients with a fragility fracture and to coordinate their education, assessment, referral, and treatment of underlying osteoporosis. We report the results of an analysis of the cost-effectiveness of the use of a coordinator (in comparison with the use of no coordinator) in avoiding future costs of subsequent hip fracture.

Methods: A one-year decision-analysis model was developed. The health outcome was subsequent hip fracture; only direct hospital costs were considered. With use of patient-level data from a previously described coordinator program and data from the literature, the expected annual incidence of subsequent hip fracture was calculated, on the basis of the type of index fracture (wrist, hip, humerus, other), attribution to osteoporosis, age, and gender. The rate of patient referral, the initiation of osteoporosis treatment, and adherence to therapy were modeled to modify the expected incidence of future hip fracture in the presence of a coordinator (with use of data from the program) and in the absence of a coordinator (with use of data from the literature). Sensitivity analysis modeling techniques were used to assess variable uncertainty and to evaluate coordinator cost-effectiveness.

Results: Deterministic cost-effectiveness analysis showed that a tertiary care center that hired an osteoporosis coordinator who manages 500 patients with fragility fractures annually could reduce the number of subsequent hip fractures from thirty-four to thirty-one in the first year, with a net hospital cost savings of C$48,950 (Canadian dollars in year-2004 values), with use of conservative assumptions. Probabilistic sensitivity analysis indicated a 90% probability that hiring a coordinator costs less than C$25,000 per hip fracture avoided. Hiring a coordinator is a cost-saving measure even when the coordinator manages as few as 350 patients annually. Greater savings are anticipated after the first year and when additional costs such as rehabilitation and dependency costs are considered.

Conclusions: Employment of an osteoporosis coordinator to manage outpatients and inpatients who have fragility fractures is predicted to reduce the incidence of future hip fractures and to save money (a dominant strategy). A probabilistic sensitivity analysis showed a high probability of cost-effectiveness of this intervention from the hospital cost perspective.

Level of Evidence: Economic and decision analysis, Level I. See Instructions to Authors for a complete description of levels of evidence.

1Division of Clinical Decision-Making and Health Care Research, University Health Network, 200 Elizabeth Street, EN 13-239, Toronto, ON M5G 2C4, Canada

2Li Ka Shing Knowledge Institute, Mobility Program Clinical Research Unit, St. Michael's Hospital, 30 Bond Street, Toronto, ON M5B 1W8, Canada

3Li Ka Shing Knowledge Institute, St. Michael's Hospital, 55 Queen Street East, Suite 800, Toronto, ON M5C 1R6, Canada. E-mail address: bogoche@smh.toronto.on.ca

4Amgen (Europe), Alpenquai 30, Lucerne 6002, Switzerland

Article Outline

Patients with fragility fractures who present to fracture clinics or are admitted urgently to orthopaedic wards can benefit from appropriate osteoporosis investigation and treatment to prevent subsequent fragility fractures, especially hip fractures1-5. Unfortunately, despite an increasing international orthopaedic focus on this issue, the rate of osteoporosis treatment for high-risk patients who have sustained a fragility fracture remains low in most locations6,7.

Coordinator programs have been demonstrated to be effective for initiating appropriate osteoporosis care for patients who have sustained a fragility fracture8-12 and for improving outcomes, with as many as 95% of patients having been appropriately diagnosed, treated, or referred for osteoporosis care8. Evidence also suggests that persistence with care in this model is satisfactory11,13,14. The coordinator model requires expenditure of funds for the coordinator's salary and related costs, and we sought to determine the extent to which these costs may be offset by the prevention of future hip fracture costs as a result of the initiation of appropriate osteoporosis care for high-risk patients who would have otherwise remained untreated.

The purpose of the present study was to determine the cost-effectiveness of the program by calculating the reduction in subsequent hip fractures and the cost savings that can reasonably be expected to result from the prevention of downstream hip fractures. The analysis is based on real data from a coordinator-facilitated program in the fracture clinic and inpatient orthopaedic unit of a large inner city university hospital and from Level-1 evidence from the literature and compares the costs of the coordinator program with the costs of having no coordinator. The analysis focuses exclusively on hip fractures (because they require hospitalization and have the greatest cost burden15) and on the avoidance of hospital costs (because such costs can be accurately determined, tend to be similar across different jurisdictions, and are less subject to interpretation).

Back to Top | Article Outline

Materials and Methods

Coordinator Program

In December 2002, a tertiary care, inner city, university hospital implemented an Osteoporosis Exemplary Care Program8. This coordinator-facilitated program created a clinical pathway for patients with fragility fractures to receive appropriate identification, education, assessment, referral, and treatment for suspected underlying osteoporosis. System modifications included coordination between the orthopaedic fracture clinic, inpatient ward, metabolic bone disease clinic, and nuclear medicine unit to provide comprehensive osteoporosis investigation and therapy for these patients. Barriers were addressed, and ongoing education of physicians, staff, and patients was undertaken to increase knowledge and awareness regarding fragility fractures and osteoporosis. The successful implementation and continuation of this program required a dedicated coordinator (V.E.-G.) with secure funding and full cooperation of orthopaedic surgeons, allied health practitioners (nurses, orthopaedic technologists, physical and occupational therapists, inpatient pharmacists, and discharge planners), administrative staff, and family physicians. The clinic structure and function were not altered to satisfy the program requirements.

Back to Top | Article Outline

Analytical Model

The target group for intervention comprised patients who had sustained a fragility fracture related to suspected underlying osteoporosis. The expected costs of future hip fractures that are predicted to occur in these patients, but that would be avoided with this program, were calculated from the perspective of hospital cost, with a time horizon of one year.

A decision-analysis model was developed with use of DATA software (TreeAge Software, Williamstown, Massachusetts) (Fig. 1). The decision tree showed the two alternative strategies: “coordinator” and “no coordinator.” The model then stratified the patients according to gender, age group, and type of index fracture (wrist, hip, humerus, other) as they were admitted to our program. A known proportion of patients then received osteoporosis treatment, to which an established proportion were adherent. Some patients experienced a subsequent hip fracture, whether or not they were previously managed for osteoporosis, on the basis of the reported efficacy of known treatments received, or may have died before experiencing any other fracture. Subsequent fractures were only modeled for osteoporotic fractures and included only hip fractures, as these are typically treated in hospital and generate major costs15.

The model structure and patient population were identical in both arms (coordinator, no coordinator). However, the probabilities of receiving treatment and adherence were known to be higher in the coordinator arm8.

Back to Top | Article Outline

Data

The model was based on patient-level data from the first year of the program and selected published data, as described below.

Back to Top | Article Outline

Probabilities

The characteristics of the patient population reflected the patient cohort from the first year of the program, during which 430 patients (276 outpatients and 154 inpatients) entered the study (Table I). The mean age (and standard deviation) was 71.3 ± 14.2 years, 77.4% of the patients were female, and osteoporosis was the most likely cause of the index fracture in 81.2% of the patients.

The relative risks of subsequent hip fracture according to the type of index fracture (Table II) were taken directly from the report by Robinson et al.16, who prospectively audited all inpatient and outpatient fracture-treatment events (n = 22,494) in a trauma unit in Edinburgh, Scotland, over a twelve-year period. That study comprised the largest population that has been followed to date, with a median age of seventy-four years and a female:male ratio of 3.75:1, which are similar to the mean age of seventy-one years and the female:male ratio of 3.4:1 in our program8. The background incidence of index fractures (Table III) was obtained directly from the report by Singer et al.17, which was a prospective study of the incidence of fractures (n = 15,293) in a catchment population of 595,600 in Edinburgh, Scotland. Data were reported according to five-year age-group categories and gender; thus, the incidence of hip fracture was selected for each gender and age group corresponding to our patient population (Table III). The proportion of fractures that were attributable to osteoporosis (Table III) was obtained directly from the report by Melton et al.18, in which a panel of experts was convened and a three-round Delphi process was applied to determine the proportion of osteoporosis-related fractures in the United States population according to fracture type and stratified according to age, racial group, and gender. Data were selected for the relevant fracture sites, gender, and age groups for a white population.

The probability of a patient receiving treatment for osteoporosis and patient adherence to treatment (Table IV) was obtained from patient-level data from our program (for the coordinator cohort) and from the report by Cranney et al.19 (for the no-coordinator cohort). The efficacy of individual treatments was obtained from the report by Cranney et al.19. The efficacy of treatment was expressed as a weighted average of all of the treatments received by patients in the program, which in most cases included calcium and vitamin-D supplements and in many cases included bisphosphonates (etidronate [which is approved in Canada for the treatment of osteoporosis], alendronate, and risedronate) (Table V). The weighted average of individual treatments was calculated on the basis of the proportion of patients who received the treatment, the compliance with treatment, and the efficacy of each treatment.

Back to Top | Article Outline

Health Outcome

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.

Back to Top | Article Outline

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.

Back to Top | Article Outline

Key Assumptions

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.

Back to Top | Article Outline

Analyses

Base-Case Analysis

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:

Back to Top | Article Outline

Sensitivity Analyses

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.

Back to Top | Article Outline

Results

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.

Back to Top | Article Outline

Discussion

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.

Back to Top | Article Outline

Appendix Cited Here...

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

1. Chrischilles EA, Dasbach EJ, Rubenstein LM, Cook JR, Tabor HK, Black DM; Fracture Intervention Trial Research Group. The effect of alendronate on fracture-related healthcare utilization and costs: the fracture intervention trial. Osteoporos Int. 2001;12:654-60.
2. Cree MW, Juby AG, Carriere KC. Mortality and morbidity associated with osteoporosis drug treatment following hip fracture. Osteoporos Int. 2003;14:722-7.
3. Harris ST, Watts NB, Genant HK, McKeever CD, Hangartner T, Keller M, Chesnut CH 3rd, Brown J, Eriksen EF, Hoseyni MS, Axelrod DW, Miller PD. Effects of risedronate treatment on vertebral and nonvertebral fractures in women with postmenopausal osteoporosis: a randomized controlled trial. Vertebral Efficacy With Risedronate Therapy (VERT) Study Group. JAMA. 1999;282:1344-52.
4. Johnell O, Jönsson B, Jönsson L, Black D. Cost effectiveness of alendronate (Fosamax) for the treatment of osteoporosis and prevention of fractures. Pharmacoeconomics. 2003;21:305-14.
5. Watts NB. Bisphosphonate treatment of osteoporosis. Clin Geriatr Med. 2003;19:395-414.
6. Elliot-Gibson V, Bogoch ER, Jamal SA, Beaton DE. Practice patterns in the diagnosis and treatment of osteoporosis after a fragility fracture: a systematic review. Osteoporos Int. 2004;15:767-78.
7. Giangregorio L, Papaioannou A, Cranney A, Zytaruk N, Adachi JD. Fragility fractures and the osteoporosis care gap: an international phenomenon. Semin Arthritis Rheum. 2006;35:293-305.
8. Bogoch ER, Elliot-Gibson V, Beaton DE, Jamal SA, Josse RG, Murray TM. Effective initiation of osteoporosis diagnosis and treatment for patients with a fragility fracture in an orthopaedic environment. J Bone Joint Surg Am. 2006;88:25-34.
9. Chevalley T, Hoffmeyer P, Bonjour JP, Rizzoli R. An osteoporosis clinical pathway for the medical management of patients with low-trauma fracture. Osteoporos Int. 2002;13:450-5.
10. Harrington JT, Barash HL, Day S, Lease J. Redesigning the care of fragility fracture patients to improve osteoporosis management: a health care improvement project. Arthritis Rheum. 2005;53:198-204.
11. Majumdar SR, Johnson JA, Lier DA, Russell AS, Hanley DA, Blitz S, Steiner IP, Maksymowych WP, Morrish DW, Holroyd BR, Rowe BH. Persistence, reproducibility, and cost-effectiveness of an intervention to improve the quality of osteoporosis care after a fracture of the wrist: results of a controlled trial. Osteoporos Int. 2007;18:261-70.
12. McLellan AR, Gallacher SJ, Fraser M, McQuillian C. The fracture liaison service: success of a program for the evaluation and management of patients with osteoporotic fracture. Osteoporos Int. 2003;14:1028-34.
13. Bogoch ER, Elliot-Gibson V, Beaton DE, Baburam A, Jamal SA, Josse RG, Murray TM. Adherence with osteoporosis assessment and treatment after fragility fracture in an inner city orthopaedic unit [abstract]. J Bone Miner Res. 2006;21 Suppl 1:S421.
14. Streeten EA, Mohamed A, Gandhi A, Orwig D, Sack P, Sterling R, Pellegrini VD Jr. The inpatient consultation approach to osteoporosis treatment in patients with a fracture: is automatic consultation needed? J Bone Joint Surg Am. 2006;88:1968-74.
15. Wiktorowicz ME, Goeree R, Papaioannou A, Adachi JD, Papadimitropoulos E. Economic implications of hip fracture: health service use, institutional care and cost in Canada. Osteoporos Int. 2001;12:271-8.
16. Robinson CM, Royds M, Abraham A, McQueen MM, Court-Brown CM, Christie J. Refractures in patients at least forty-five years old. A prospective analysis of twenty-two thousand and sixty patients. J Bone Joint Surg Am. 2002;84:1528-33.
17. Singer BR, McLauchlan GJ, Robinson CM, Christie J. Epidemiology of fractures in 15,000 adults: the influence of age and gender. J Bone Joint Surg Br. 1998;80:243-8.
18. Melton LJ 3rd, Thamer M, Ray NF, Chan JK, Chesnut CH 3rd, Einhorn TA, Johnston CC, Raisz LG, Silverman SL, Siris ES. Fractures attributable to osteoporosis: report from the National Osteoporosis Foundation. J Bone Miner Res. 1997;12:16-23.
19. Cranney A, Guyatt G, Griffith L, Wells G, Tugwell P, Rosen C; Osteoporosis Methodology Group and The Osteoporosis Research Advisory Group. Meta-analyses of therapies for postmenopausal osteoporosis. IX: Summary of meta-analyses of therapies for postmenopausal osteoporosis. Endocr Rev. 2002;23:570-8.
20. Hajcsar EE, Hawker G, Bogoch ER. Investigation and treatment of osteoporosis in patients with fragility fractures. CMAJ. 2000;163:819-22.
21. Hawker G, Ridout R, Ricupero M, Jaglal S, Bogoch E. The impact of a simple fracture clinic intervention in improving the diagnosis and treatment of osteoporosis in fragility fracture patients. Osteoporos Int. 2003;14:171-8.
22. Caro JJ, Ishak KJ, Huybrechts KF, Raggio G, Naujoks C. The impact of compliance with osteoporosis therapy on fracture rates in actual practice. Osteoporos Int. 2004;15:1003-8.
23. Hunink M, Glasziou PP, Siegel J, Weeks J, Pliskin J, Elstein A, Weinstein M. Decision making in health and medicine: integrating evidence and values. Cambridge, UK: Cambridge University Press; 2001.
24. Newman ED, Ayoub WT, Starkey RH, Diehl JM, Wood GC. Osteoporosis disease management in a rural health care population: hip fracture reduction and reduced costs in postmenopausal women after 5 years. Osteoporos Int. 2003;14:146-51.
25. Cooper C. The crippling consequences of fractures and their impact on quality of life. Am J Med. 1997;103:12S-19S.
26. Fierens J, Broos PL. Quality of life after hip fracture surgery in the elderly. Acta Chir Belg. 2006;106:393-6.
27. van Balen R, Steyerberg EW, Polder JJ, Ribbers TL, Habbema JD, Cools HJ. Hip fracture in elderly patients: outcomes for function, quality of life, and type of residence. Clin Orthop Relat Res. 2001;390:232-43.
28. Willig R, Keinänen-Kiukaaniemi S, Jalovaara P. Mortality and quality of life after trochanteric hip fracture. Public Health. 2001;115:323-7.
29. Black DM, Delmas PD, Eastell R, Reid IR, Boonen S, Cauley JA, Cosman F, Lakatos P, Leung PC, Man Z, Mautalen C, Mesenbrink P, Hu H, Caminis J, Tong K, Rosario-Jansen T, Krasnow J, Hue TF, Sellmeyer D, Eriksen EF, Cummings SR; HORIZON Pivotal Fracture Trial. Once-yearly zoledronic acid for treatment of postmenopausal osteoporosis. N Engl J Med. 2007;356:1809-22.
Copyright 2008 by The Journal of Bone and Joint Surgery, Incorporated