As in many other industrialized countries, osteoporosis prevalence is high in Canada, affecting more than one in five women over the age of 50 years.1 Osteoporosis is a major public health problem owing to its association with fragility fracture (low-energy fracture), particularly those of the spine, hip, humerus, and distal forearm.2 It is estimated that a 50-year-old woman has a 50% remaining lifetime risk of fragility fracture.3 Recently, it has been reported that approximately 81% of all fractures in women ≥50 years of age can be classified as fragility fractures and attributed to osteoporosis.4
Although hip fractures are well recognized for their disproportionate burden on individual health status and their substantial socioeconomic impact compared to other fragility fractures,5, 6 there is evidence suggesting that non-hip fractures also represent a significant burden, resulting in increased disability, impaired quality of life, decreased survival, and morbidity, as well as significant healthcare costs.7–15
Recent Canadian studies have observed a reduction in age-standardized rates of hip fracture in both sexes and of two major low-trauma fracture sites (forearm and humerus) in women.16, 17 With increased life expectancy, the population most at risk of fractures (i.e., those 65 years and older) is projected to grow from 14% in 2006 to 28% in 2056.18 Therefore, even under the assumption of declining rates, the absolute number of fragility fractures will continue to rise, imposing a heavy healthcare burden.
Details of direct medical resource utilization required for the treatment of fragility fractures by skeletal site may help to understand the impact of these fractures on the healthcare system. This information can be analyzed in conjunction with incidence data to project and estimate the healthcare resources needed and may help policy-makers to plan resource allocation and care organization to maintain and increase efficiency. The assessment of resource utilization beyond the initial treatment is essential to understand the care pathway related to different fractures and is the first step toward developing and implementing performance indicators.
The purposes of our study were to ascertain the burden of nonvertebral fragility fractures by analyzing direct medical resource utilization for their treatment in postmenopausal women in the year after fracture and to evaluate whether age is an independent determinant of medical resource utilization.
Materials and Methods
Study cohort and design
In this population-based, retrospective cohort study, all women aged 50 years or older who experienced incident nonvertebral osteoporotic fractures between January 1, 2004 and December 31, 2005 were identified in three of Quebec's largest provincial health regions (Montreal, Quebec City, and Mauricie). These three regions account for an estimated 42% of the population of women 50 years of age or older in the province of Quebec.19 This cohort of recently-fractured women was identified from a previous study that validated an algorithm for fracture case identification.20 Administrative databases of healthcare services (Régie de l'assurance maladie du Québec [RAMQ] physicians' fee-for-service claims and Med-Echo hospital discharge) delivered to the majority of residents in Quebec were considered to track fracture-related direct medical resource utilization in the year after fracture. RAMQ databases collect and store medical claims information from approximately 94% of Quebec-based physicians and on almost 98% of 7.5 million residents of the province.21 The data from both databases were linked by a unique personal identifier, creating a longitudinal cohort of health resource utilization for all fracture cases.
This project was approved by the Research Ethics Board of Centre Hospitalier Universitaire de Québec (CHUQ), and linkage with these administrative databases was approved by the Québec Commission d'Accès à l'Information, (http://www.cai.gouv.qc.ca).
In Canada, physician and hospital services provide to all citizens are covered by a universal health insurance plan. In Quebec, this plan is administered by the RAMQ, which maintains the computerized physician fee-for-service claims database containing information related to physician reimbursement. It includes: physicians' unique identification numbers, the patients' unique provincial health insurance numbers (NAM), medical service billing codes for the clinical services, dates and locations of the clinical services provided, and, optionally, diagnoses as per International Classification of Diseases, Ninth Revision, Clinically Modified (ICD-9-CM) codes, included in 91% of all RAMQ claims. The RAMQ also maintains the hospital discharge databases (Med-Echo), which include information on patient demographics, diagnosis and comorbidities at admission, treatment, and destination at discharge provided in general and acute care hospitals and rehabilitation facilities (not including long-term care). Diagnoses are coded using 16 diagnostic codes (ICD-9-CM) before April 1, 2006, and 25 diagnostic codes (International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada [ICD-10-CA]) thereafter. Some studies have shown that administrative healthcare databases have a high level of reliability and validity,22, 23 and their linkage provides a powerful resource when investigating health issues such as health resource utilization.24
Identification of incident fracture cases
An algorithm, developed using the physician fee-for-service claims database (RAMQ), identified all incident nonvertebral fracture cases during the period of interest.20 The algorithm is designed to first select all medical services claims potentially associated with fracture treatment: (1) claims with medical services billing codes definitively related to fracture care (i.e., open or closed reduction), or (2) claims with medical service billing codes not limited to fracture care (i.e., immobilization, consultation, principal or follow-up visit with an orthopedic surgeon [OS], emergency physician [EP], or general practitioner [GP]) if they were combined with ICD-9-CM diagnostic codes of fracture. The algorithm considered an incident fracture had occurred if there was at least one claim associated with (1) fracture treatment (open reduction, closed reduction, immobilization), (2) principal visit to an OS with at least one other claim, or (3) consultation with an OS with at least one other claim. The claim allowing fracture identification was referred to as the “index claim.” The validity of this algorithm has been evaluated and published.20
Fracture sites were defined by the specific medical service codes of the index claim related to the treatment of fracture or, if not specific to the treatment of fracture, to the ICD-9-CM codes. To establish the complete temporal sequence of medical care for each fracture, the algorithm identified any other claim (emergency room visit, follow-up visit, etc.) related to the same anatomical site. The date of the fracture corresponded to the date of the first claim in the temporal sequence of medical care. Finally, a 6-month period was established as “washout period” between two clinical sequences related to the same anatomical fracture to minimize potential misclassification of fracture follow-up as a new incident fracture.
In administrative databases, the lack of information on the circumstances surrounding the fracture event limits the ability to identify traumatic and pathological fractures. Because fragility fractures represent the vast majority of fractures in women aged 50 years or older (approximately 81% of this population),4 all fracture types (traumatic, nontraumatic, and pathological) were included in the analyses. Furthermore, both low- and high-energy trauma fractures have been proposed recently for inclusion as outcomes in osteoporosis studies because they are linked with decreased bone mineral density and result in increased risk of future fracture.25 Similarly, pathological fractures were not excluded because they represent a very small proportion, and their exclusion may lead to underestimation of the burden of osteoporotic fractures.25, 26 Women who had multiple fractures, either suffered at the same time or at different times during the assessment period, were eliminated from the analyses because it was often impossible to accurately ascertain the resources utilized for each fracture site independently. Fractures at the following sites were investigated in our study: hip, femur, pelvis, shoulder, humerus, forearm, elbow, wrist, tibia, fibula, foot, and ankle. Vertebra, sacrum, and coccyx fractures were not included in the analyses because sensitivity (Sn) of the algorithm was unacceptably low for the identification of these fractures.20 Furthermore, vertebral fractures are generally underreported in administrative databases.27 Rib and sternum fractures were excluded because there are very few specific medical service codes (open and closed reduction) and no immobilization related to the treatment of these fractures and codes related to surgeries at these sites may be used to treat patients after surgical intervention related to cardiovascular problems or likely define traumatic fracture rather than fragility fracture. Moreover, the majority of rib fractures do not require any medical care other than pain relief and are therefore not easily identifiable in administrative databases. Also, craniofacial, hand, finger, patella, and toe fractures were excluded because they are not typically associated with osteoporosis.28
Identification of healthcare resource utilization
To assess direct medical resource utilization for the treatment of each fracture, direct medical resources were identified in both physician fee-for-service claims (RAMQ) and hospital discharge (Med-Echo) databases. The records for each fracture case retained for analysis were followed forward in time between January 1, 2004 and December 31, 2007 and linked to create a longitudinal cohort of fracture cases for health resource utilization analysis.
To select claims in the physician fee-for-service claims database, all claims were screened to ensure they were relevant to fracture treatment. To prevent the addition of claims linked to subsequent or previous fracture type, claims were only retained if they were billed with medical service billing codes or ICD-9-CM diagnostic codes directly related to the original fracture site or a site considered to be affected by the original fracture (i.e., concomitant site).
To evaluate resource utilization related to hospitalization, all admissions in the hospital discharge database (Med-Echo) of patients included in the study cohort were screened and retained if related to fracture treatment and, for rehospitalization, if related to fracture treatment (rehabilitation) or complications. Each hospital admission was categorized by one of the clinical investigators (EB), a practicing orthopedic surgeon, according to one of the following criteria:
1.Hospital admission with primary diagnostic codes of fracture (same site, concomitant site, unspecified site, pathological fracture);
2.Hospital admission with procedure intervention codes of fracture repair (same site);
3.Hospital admission with primary diagnostic codes associated with fracture;
4.Hospital admission with primary diagnostic codes associated with fracture complication;
5.Hospital admission with secondary diagnostic codes of fracture (same site, concomitant site, unspecified site);
6.Hospital admission unrelated to fracture.
With the exception of unrelated hospital admissions (criteria 6), lists of the diagnostic codes and procedural intervention codes are presented in Supplemental Appendices 1 and 2. Hospital admission was considered as definitely related to fracture if it met any of the criteria numbered 1 to 3. Hospital admissions were considered as probably related to the fracture if they met criteria 4 and criteria 5 only if the admission date was within 14 days of the index fracture for hip/femur and 10 days for other sites. All other hospital admissions were assumed to be unrelated to the fracture and were not included in the study. Supplemental Appendix 3 details the selection of hospital admissions.
In this study, we considered hospitalization as initial hospital admission with any readmissions to another hospital within 1 day. Readmissions that occurred 2 or more days after discharge from a previous admission were considered as rehospitalizations. Hospitalizations and rehospitalizations that occurred more than 1 year after the index fracture were ignored.
Assessment of the direct medical resources utilization
For each fracture retained, our analysis provided an assessment of health service utilization at the population level. First, medical claims were used to describe all medical services related to fracture treatment and physician consultation. This information was also used to describe fracture treatment type, which had a direct impact on medical resource utilization. Fractures requiring surgery (open reduction) involved operating room utilization, which necessarily requires many medical resources and, most likely, hospitalization. Closed reduction of fracture requires more resources than a fractures treated by immobilization since such procedure are performed by OSs. Similarly, fractures requiring immobilization would likely involve cast room resources, thereby consuming more resources than fractures treated by conservative observational treatment (i.e., non–weight-bearing protected use or rest with follow-up visit with an OS without casting or immobilization). Therefore, in our analysis, the most resource-intensive fracture treatment was open reduction and internal fixation, followed by closed reduction, immobilization, and finally, conservative observational treatment. The proportions of fractures treated by each type of treatment were calculated according to this classification. Moreover, mean number of outpatient visits to an OS and mean numbers of inpatient and outpatient visits to other physicians were evaluated for each fracture site.
All hospitalizations included in the analysis were considered, to assess direct medical resource utilization for hospitalization. More specifically, the rate of fractures requiring at least one hospitalization directly related to their treatment was determined for each fracture site. The rate of hospitalization requiring at least one readmission to another hospital within 1 day and the rate of rehospitalization were also calculated. The lengths of stay at individual admission (LOS) and length of hospitalization (LOH) that included stays in several hospitals (initial hospital admission with all readmissions (for rehabilitation or complications postfracture) to another hospital within 1 day), are reported, in days, for the initial hospitalization and fracture-related rehospitalization. Furthermore, for long-term care (LTC) and non-LTC residents at initial admission, the destination at discharge (acute care, rehabilitation, local community health services center (CLSC), home, LTC, inpatient death) was ascertained from the last hospitalization related to fracture care.
Finally, to evaluate if patient age is an important determinant of healthcare resource utilization, all statistics on healthcare resource utilization were stratified by age group. The statistical significance of the age was analyzed by Pearson's chi-square test for dichotomous variables and by the Wilcoxon test for continuous variables.
All statistical analyses were undertaken with SAS software (version 9.1; SAS Institute, Cary, NC, USA).
During the study period (2004–2005), the algorithm identified 18,927 incident fractures (in 17,661 women). Vertebra, coccyx, and sacrum fractures (n = 286) were excluded because unacceptably low sensitivity was associated with the algorithm used for their identification. Knee fractures (n = 500) were not considered to be related to osteoporosis and were therefore excluded, and women who were less than 50 years old (n = 362) when their fracture occurred were also excluded. Finally, women with multiple fractures (n = 1186) (same or different events) were excluded because it was not possible to independently assess the individual health resources used for each of these fracture events. Therefore, data on 2334 women were removed from the analysis, resulting in 15,327 women aged 50 years or older with a single fracture event during the study period (Fig. 1).
Fifty-eight percent of these fractures occurred in women 70 years of age and older (Table 1). Moreover, during the study period, 9% (n = 1405) of women died and the majority of these deaths were observed for women with hip/femur and pelvis fracture (73.2%). The number of fractures by site and the median (quartiles 1–3 [Q1–Q3]) age of cases are reported in Table 1. In this cohort, hip/femur fractures represented 29.6% of all fracture, and non-hip fractures 70.4%. The most common fracture sites identified were the hip/femur (29.6%), wrist (20.6%), shoulder/humerus (17.0%), and ankle (12.0%). When all fracture groups were combined, median age (Q1–Q3) at fracture was 73 (range, 61–82) years. Median age at hip/femur fracture was approximately 10 years higher than median age at other peripheral fractures.
Table 1. Baseline Characteristics of the 15,327 Women Included in the Study
Number of fractures, n (%)
Number of fractures, n (%)
Age, median (Q1–Q3)
Q1 = quartile 1; Q3 = quartile 3.
A total of 100,923 medical service claims related to the treatment of these fractures were recorded in the physician fee-for-service claims database. This cohort accumulated 12,354 all-cause hospitalizations in the year after the fracture (Supplemental Appendix 3). Based on previously-described criteria, 8522 hospitalizations were considered definitely or probably related to fracture and were selected for analysis. Ninety-three percent of these hospitalizations were categorized as definitely related to fracture. In addition, 86% of these hospitalizations occurred within a window of 14 days from the fracture date for hip/femur fractures and 10 days for other nonvertebral fractures.
Tables 2 and 3 report direct medical resource utilization for fracture treatment and physician consultation. Globally, 43.6% of all claims were performed for hip/femur fractures treatment (Table 2). Because a large proportion of hip/femur fractures are treated with surgery (91.1%, Table 3), they required 72.1% of all clinical care related to surgery (open reduction). As expected, when hip/femur fractures were treated by surgery, the hospitalization rate was very high 98.3% (data not shown). Therefore, hip/femur fractures consumed a large proportion of medical consultations with an average of 2.0 outpatient visits to OSs, and 5.4 and 1.5 inpatient and emergency/outpatient visits with other physicians, respectively.
The most resource intensive treatment was an open reduction and internal fixation, followed by close reduction, casting or immobilization and finally observational conservative treatment.
Principal visit, consultation or follow-up visit with an orthopedic surgeon.
Principal visit, consultation or follow-up visit with general practitioner and other specialist.
1.8, 1.0 (1–2)
6.3, 3.0 (1–9)
4.7, 0 (0–7)
1.6, 1 (0–2)
2.0, 1.0 (1–2)
6.9, 3.0 (1–9)
5.4, 0 (0–6)
1.5, 1 (0–2)
2.4, 2.0 (1–3)
2.5, 1.0 (0–2)
1.2, 0 (0–0)
1.3, 1 (0–2)
2.2, 2.0 (1–3)
1.4, 1.0 (0–2)
0.2, 0 (0–0)
1.2, 1 (0–2)
2.4, 2.0 (1–3)
1.5, 1.0 (0–2)
0.3, 0 (0–0)
1.2, 1 (0–2)
2.6, 2.0 (1–4)
3.3, 1.0 (0–2)
2.2, 0 (0–0)
1.0, 1 (0–2)
1.7, 2.0 (1–2)
1.3, 1.0 (0–2)
0.2, 0 (0–0)
1.1, 1 (0–2)
2.6, 2.0 (1–3)
2.4, 1.0 (0–2)
1.1, 0 (0–0)
1.3, 1 (0–2)
For pelvic fractures, Tables 2 and 3 demonstrate that 2.4% of all claims were related to their treatment and 86.9% received conservative treatment (follow-up visit to an OS only). Despite the low rate of pelvic fractures treated by surgery (7.2%), they required a high rate of hospitalization (67.4%, Table 4), likely related to older age and functional impact of these fracture. Thus, these fractures accounted for a significant proportion of medical consultations with an average number of 1.8 outpatient visits to an OS, and 4.7 and 1.6 inpatient and emergency/outpatient visits with other physicians, respectively (Table 3).
Table 4. Health Resource Utilization Related to Hospitalization in the Year Following the Osteoporosis-Related Fracture
Pelvis (n = 291)
Hip/femur (n = 4536)
Shoulder/humerus (n = 2603)
Forearm/elbow (n = 1498)
Wrist (n = 3157)
Tibia/fibula (n = 638)
Foot (n = 769)
Ankle (n = 1835)
LOH = length of hospitalization that included stays in several hospitals (initial hospital admission with all readmission to another hospital within 1 day); LOS = length of stay at individual admission.
At least one hospitalization, n (%)
Number of hospitalizations, n
LOH, total days (%)
Mean LOH days (median)
Number of hospitalizations with at least 1 readmission, n (%)
Mean LOS days initial admission (median)
Mean LOS days all readmissions (median)
Number of rehospitalizations, n (%)
Mean LOH days initial hospitalization (median)
Mean LOH days first rehospitalization (median)
Mean LOH days second rehospitalization (median)
Non-hip and non-pelvic fractures accounted for a large proportion of medical consultations. Table 3 illustrates that several non-hip fractures had a high rate of clinical care related to surgery (tibia/fibula 40.1%, ankle 32.9%, shoulder/humerus 16.9%, forearm/elbow 13%, wrist 7.9, and foot 2.6%), requiring a total of 27.4% (open reduction). Forearm/elbow and wrist fractures had the highest rate of closed reduction (28.8% and 58.0%, respectively), which always involved an OS for the procedure. These fractures required a significant proportion of medical consultations, representing 74.6% of all consultations with an OS and 43.0% of all consultations with other physicians (Table 2). As with hip fractures, when other fractures were treated by surgery, the hospitalization rate was high, varying between 90% for foot and 99% for wrist fractures (data not shown). The average number of outpatient visits to an OS was approximately two visits, similar to that observed for hip/femur and pelvis fractures. Moreover, the average number of visits to other physicians varied between 3.3 (tibia/fibula) and 1.3 (foot) and were correlated with the rate of surgeries, due to the average number of inpatient visits. Therefore, the mean number of claims (Table 3) to treat these fractures was highly correlated with the proportion of fractures treated by surgery, thus requiring hospitalization.
Table 4 details health resource utilization related to hospitalization in the year after the fracture. As expected, the highest hospitalization rate was attributed to hip/femur fractures, with 95.4% of these fractures having at least one hospitalization related to their care. In terms of LOH, these fractures also had the highest resource utilization rate with a mean (median) LOH of 39.2 days (31 days), representing 73.2% of total LOH related to all fracture care. In addition, a significant proportion of hip/femur fractures (46.2%) required at least one re-admission to another hospital within 1 day. Mean (median) LOS was 18.4 days (11 days) for the initial hospital admission and a mean (median) total LOS was 45.1 days (38 days) for all readmissions were observed. Finally, 8.1% of all hospitalizations for hip/femur fractures corresponded to rehospitalization (rehabilitation or complications) and the LOH for these rehospitalizations was shorter in duration than the first hospitalization.
Pelvic fractures carried a high rate of medical resource use related to hospitalization, with 67.4% requiring at least one hospitalization. Mean (median) LOH was 34.2 days (26 days), and 40.6% of these hospitalizations involved at least one readmission to another hospital within 1 day. Mean LOS at initial hospital admission was shorter than for all readmissions. Mean (median) LOS at initial hospital admission was 18.9 days (13 days), and mean (median) LOS for all readmissions was 38.9 days (29 days). Globally, 5.3% of all hospitalizations related to pelvic fractures were rehospitalizations.
Non-hip and non-pelvic fractures (so-called peripheral fractures) accounted for a significant proportion of medical resources used, with 54.2% of tibia/fibula, 41.7% of ankle, 33.3% of wrist, and 30.7% of shoulder/humerus fractures needing at least one hospitalization for fracture care. Although somewhat shorter than for hip and pelvic fractures, mean (median) LOH at these sites was still considerable, with 26.3 days (9 days) for tibia/fibula, 16.6 days (3 days) for ankle, 8.0 days (1 day) for wrist, and 23.5 days (8 days) for shoulder/humerus fractures. Moreover, the rate of these fractures requiring at least one readmission to another hospital within 1 day varied between 12.1% and 29.4%. As with hip/femur and pelvic fractures, the mean LOS at initial admission was shorter than for all readmissions. Altogether, non-hip fractures involved 26.8% of total LOS for fracture care.
For all fractures, we observed that a large proportion (between 92% for hip/femur and 100% for foot) of all procedural intervention codes related to their treatment (reduction, fixation, etc.) was assigned during initial hospital admission (data not shown). This observation confirms that initial admissions correspond to the acute period of fracture care. Moreover, as described above, the high proportion of fractures requiring readmission to another hospital within 1 day of a previous admission suggests that after initial admission (acute care period), a significant proportion of fracture patients remain hospitalized to receive other care (inpatient rehabilitation).
Table 5 provides details of discharge destination for the last hospitalization related for fracture care in the year after fracture. Among all fracture patients with at least one hospitalization for fracture care (n = 7787), 5.2% (n = 407) were LTC residents at initial admission. Ninety percent of these LTC residents had hip/femur fractures. Among these LTC residents, 91% returned to LTC at last hospitalization and 6% died. Among non-LTC residents at initial admission, only 44.8% of hospitalized patients for hip/femur fracture returned home, 25.6% required rehabilitation or were referred to their CLSC, 18.2% needed LTC, and 10.8% died during hospitalization. Therefore, patients with hip/femur fractures use a significant proportion of health resources after hospitalization.
Table 5. Discharge Destination at Final Admission According to Resident Status at Initial Admission
All fractures (n = 15,327)
Pelvis (n = 291)
Hip/femur (n = 4536)
Shoulder/humerus (n = 2603)
Forearm/elbow (n = 1498)
Wrist (n = 3157)
Tibia/fibula (n = 638)
Foot (n = 769)
Ankle (n = 1835)
CLSC = community health services center; LTC = long term care.
At least one hospitalization, n
LTC resident at initial admission, n (%)
Rehabilitation or CLSC, n (%)
Return to LTC, n (%)
Inpatient death, n %
Non-LTC resident at initial admission, n (%)
Always in acute care at 12 month, n (%)
Rehabilitation or CLSC, n (%)
Home, n (%)
LTC, n (%)
Inpatient death, n (%)
Similarly, non-LTC residents hospitalized for pelvic fractures required a significant portion of medical resources after discharge, with only 53.9% returning home, 25.4% needing rehabilitation or referral to their CLSC, 10.9% admitted to LTC, and 9.3% dying during hospitalization. For other hospitalized peripheral fracture cases, between 10.1% (wrist) and 23.3% (tibia/fibula) required rehabilitation or were referred to their CLSC, and between 4.0% (wrist) and 8.1% (foot) were admitted for LTC. Therefore, a significant proportion of patients with peripheral fractures use medical resources after hospitalization.
Figure 2 discloses that the proportion of fractures treated with surgery increased significantly with age whereas less invasive (immobilization and conservative) treatments decreased. In contrast to hip/femur fractures, pelvic and tibia/fibula fractures were associated with a significant increment in the proportion of conservative treatment with age and a significant decline in the proportion of surgery (open reduction) and immobilization. For upper limb fractures, the proportion of closed reductions increased significantly with age, whereas the other types of treatment decreased or remained stable. For all fractures, Fig. 3 shows that the average number of visits to an OS fell slightly with age, whereas the average number of visits to other physicians, the proportion of fractures requiring hospitalization, and LOS increased significantly with age. Finally, Fig. 4 shows that during the last hospitalization for fracture care, the proportion of patients discharged to their home decreased significantly with age whereas the proportion of patients admitted for LTC or who died increased significantly with age. Therefore, patient age at time of fracture is an important determinant of health resource utilization, and is associated with increased admission for LTC and death.
Direct medical resource utilization for fracture treatments, physician consultations, and hospitalizations in the year after fragility fracture was assessed with administrative databases. As expected, hip/femur fractures represented the highest resource utilization rate because the majority of them required surgery and hospitalization. However, other peripheral fractures accounted for the significant use of clinical care related to surgeries, OS consultations, and hospitalizations. Even with pelvic fractures, which most of the time do not require surgical treatment, was associated with very significant resource utilization related to a high hospitalization rate. This study indicated that patient age was an important determinant of health resource utilization, associated with an increased number of visits to other physicians, hospitalizations, LOH, admissions to LTC, and death. As for hip fracture, there are published investigations providing detailed estimates of health resources utilization for non-hip nonvertebral fragility fractures. Any attempt to compare these studies is limited by differences in healthcare systems, populations, time periods studied, and type of data sources for estimating health service utilization.
In our study, the number of physician visits for fracture care was higher for hip and pelvic fractures compared to other peripheral fractures. This observation is related to the higher hospitalization rate associated with hip and pelvic fractures, which result in more inpatient physician visits. A study of Medicaid data (USA) reported approximately seven outpatient physician visits in the 6 months postfracture, a number that was constant across different fracture sites.29 In the year after fracture, a Canadian study disclosed an average of four general practitioner visits and one specialist visit for patients residing in the community. General practitioner visits averaged seven for patients transferred to LTC.30 However, these two studies considered all physician visits in the year following the fracture event, which differed from the study detailed here, in which only physician visits directly related to fracture care were included. Similar to our study, a recent work from the Global Longitudinal Study of Osteoporosis in Women (GLOW) study shows that women with hip fractures had the highest surgery rate (89%) with a surgery rate of less than 30% for other fracture sites.31
Results of the health services burden related to hospitalization in our investigation are similar in several aspects to those reported previously. For each fracture site, a significant proportion of patients had at least one acute hospitalization for fracture care in the year after fracture and the magnitude of these hospitalizations varied by fracture site. The proportion of patients with at least one hospitalization for fracture care ranged from 8.2% for foot fractures to 94.5% for hip/femur fractures. Variation among fracture types on medical resources use related to hospitalization and rehabilitation was also observed.29, 31 As suggested by Becker and colleagues,29 these variations between fracture sites reflect differences in fracture severity. In term of hospital and rehabilitation/nursing home days, a recent study reported that non-hip, non-spine fractures, due to their greater number, require significantly more healthcare resources than hip fractures with 2.9 times greater hospital days (3805 days for non-hip, non-spine versus 1306 days for hip fractures) and 3.1 times greater rehabilitation/nursing home days (5186 days for non-hip, non-spine versus 1650 days for hip fractures).31 Our data also revealed that the majority of procedural intervention codes related for fracture repair during hospitalization were assigned during initial admission. This observation indicates that a greater proportion of initial admissions corresponded to the acute care period. Moreover, the mean (median) LOS of 18.4 days (11 days) for hip/femur fractures at initial admission was similar to the mean acute care LOS of 16.7 days reported in 2005 by Med-Echo hospital discharge database in a Level I trauma center in Quebec, Canada.32 It was previously reported that a large proportion of patients hospitalized for fracture treatment also received inpatient postacute fracture care.29, 33 After initial admission a large proportion of the fracture cases were transferred to another hospital, suggesting that a significant proportion of postacute fracture care obtained rehabilitation and/or chronic care provided by another hospital. This observation is consistent with the Canadian context in which postfracture rehabilitation is considered to be an extension of acute care, whereas discharge to LTC occurs when patients fail to be autonomous.33 For LTC residents at the time of fracture, their place of residence remained largely unchanged among survivors, as reported.33 Moreover, among non-LTC residents, our descriptive analysis of discharge destination after final hospital admission indicated that a large proportion of fracture patients received postacute care services through LTC, rehabilitation care, or were referred to their CLSC, pointing to an important role of these services in fracture care. In this study, we observed that 18.2% of non-LTC patients with hip/femur fractures were transferred to LTC after hospitalization for fracture care. Another Canadian study found that 16.6% of community patients with hip fracture were admitted to LTC at hospital discharge.34
A Swiss study, comparing the total number of hospitalization days for osteoporosis and fragility fractures to those observed for other chronic diseases, reported that osteoporosis in women accounted for 1.5 times more hospital days than cardiovascular diseases, between 2.0 and 3.0 times more than chronic obstructive pulmonary disease and breast cancer, and 6.0 times more than diabetes.6 Moreover, in addition to the burden on health resources, the treatment of these osteoporosis-related fractures represents an economic burden to the healthcare system. Taking the same methodological approach, our earlier work estimated the average cost of treating acute fractures and postfracture complications in the year after fracture to be $46,664 (Canadian dollars [CND]) per hip/femur fracture, $5253 for wrist fracture and $10,410 for fractures of other peripheral sites.15
Major strengths of this study included the use of population-based administrative databases, providing global measurement of healthcare delivery at the population level and access to a large sample of fracture cases for each fracture site, allowing robust estimation. Moreover, in selecting only medical claims and hospitalizations for fracture care, medical resource utilization directly attributable to fracture care and representing actual utilization of care was assessed. In addition, a validated algorithm identified inpatient and outpatient fracture cases, thereby achieving a better understanding of the true burden related to fragility fractures especially those not leading to hospitalization. Finally, the ability to link the information on each fracture case from several databases allowed the assessment of fracture impact on health resource utilization across a continuum of clinical care.
This study had some limitations. First, we had no procedure for eliminating fractures related to motor vehicle accidents or malignancies. Nevertheless, studies have reported that the rate of motor vehicle accident- and malignancy-related fractures is low. Moreover, the Recognizing Osteoporosis and Its Consequences in Quebec (ROCQ) study, in a subset of the population included in these analyses, indicated that the majority of fractures (81%) occurring at an osteoporotic site were low-energy trauma fractures.4 Second, vertebral fractures were not considered in this investigation because of our inability to properly identify vertebral fractures in administrative databases. This limitation is not unusual, as approximately two-thirds of vertebral fractures do not come to clinical attention.27, 35, 36 For fractures identified according to our algorithm, we observed that 6% were recurrent fractures from a previous fracture. Among these recurrent fractures, less than 0.5% were excluded based on the 6-month washout period. Therefore, our sample may contain some duplicates of previous fractures. Furthermore, our investigation only included women from three health regions that represented 42% of the female population in the province of Quebec. It is possible that fractures and direct medical resource utilization differ in other regions in terms of the socioeconomic and regional aspects of medical care. It is also possible that the medical resource use reported in this study was not the same 5 years later. However, this is unlikely given that changes in medical practice often take more than 10 years to be implemented.37 Moreover, the results reported in our study are significant to describe the burden related to osteoporotic/fragility fracture and may provide a frame of reference for study assessing cost effectiveness of public health intervention for fracture prevention. This information can also guide policymakers who must assess the healthcare resources needed and assist them to plan resource allocation. Finally, administrative data analysis cannot overcome problems related to coding omissions or coding errors. The lack of clinical information on the subjects in the administrative database limits our ability to provide much in the way of description of the sample. Moreover, lack of information regarding transitions to LTC after the final discharge destination and treatment by home-based healthcare workers, physical therapists, or occupational therapists could also influence our results.
This study has implications for health service administrators responsible for coordinating and prioritizing healthcare delivery. Characterizing the healthcare resource utilization burden related to fragility fractures is a first step toward better understanding the determinants of fracture care. This information is essential for resource planning and organization of healthcare services and may also help to maintain and increase the efficiency of fracture care.
However, although the burden of osteoporosis-related fractures is high in terms of excess mortality,8, 12 levels of healthcare used,29 institutionalization,33 and their associated costs,15 under-recognition of osteoporosis and its consequences remains problematic4 despite the availability of effective therapy to reduce fracture risk. Therefore, effective public health interventions need to be introduced to improve the diagnosis and treatment of osteoporosis, particularly in high-risk groups (i.e., those with fragility fracture) to reduce their impact on the healthcare system.
All authors state that they have no conflicts of interest.
This study is part of the study Recognizing Osteoporosis and its Consequences in Québec (ROCQ), which has been made possible through the support of founding partners Merck Canada, sanofi-aventis Canada Inc., and Warner Chilcott, as well as major partner Amgen Canada Inc. and minor partners Eli Lilly Canada Inc. and Novartis Pharma Canada Inc. The funding source had no access to the data prior to publication, no input into the writing of the manuscript, and no input into the decision to publish the results.
Authors' roles: SJ designed the study, directed its implementation, acquired the data, analyzed and interpreted the data, and drafted the article. BC and EB contributed to the design, helped with its implementation, interpreted the data, and drafted the article. All others authors interpreted the data and reviewed the article critically for important intellectual content.