This bar graph represents the compliance with medications used for osteoporosis. The y-axis represents the proportion of the population in each category of compliance. The x-axis represents 60-day periods after date of osteoporosis medication initiation (index date). Four categories of compliance are graphed for each 60-day period after initiation. The black bar represents the proportion of patients who had filled prescriptions for any osteoporosis medication that covered greater than 66% of all days in the 60-day period, the dark gray bar represents patients with 34% to 66% of days with any osteoporosis medication, the light gray bar represents the patients with 1% to 33% of days, and the white bar represents the patients with no days of medication.
The Kaplan-Meier curves illustrate the proportion of patients who had 2 consecutive 60-day periods without any osteoporosis medication: all patients (A), patients stratified according to bone mineral density (BMD) testing (0, no testing; 1, testing) in the prior 12 months (B), and patients stratified according to age in years at the time of drug initiation (C).
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Solomon DH, Avorn J, Katz JN, et al. Compliance With Osteoporosis Medications. Arch Intern Med. 2005;165(20):2414–2419. doi:10.1001/archinte.165.20.2414
Long-term compliance with pharmacologic treatments for many asymptomatic conditions may be suboptimal, but little is known about compliance with medications used for osteoporosis. This study was undertaken to assess the level and determinants of compliance with drugs prescribed for osteoporosis.
This retrospective cohort study used pharmacy claims data from US Medicare and filled prescriptions from a state pharmaceutical benefits program. We included persons 65 years or older who initiated use of a medication for osteoporosis (alendronate sodium, calcitonin, hormone therapy, raloxifene hydrochloride, or risedronate) from January 1, 1996, through December 31, 2002. The outcome of interest was suboptimal medication compliance, defined as equal to or less than 66% of days with medication during a 60-day period.
One year after initiating treatment for osteoporosis, 45.2% of the 40 002 patients were not continuing to fill prescriptions. Five years after initiation, 52.1% of patients were not continuing to fill prescriptions for an osteoporosis medication. Several characteristics independently predicted compliance: female sex, younger age, fewer comorbid conditions, using fewer nonosteoporosis medications, bone mineral density testing before and after initiating a medication, a fracture before and after initiating a medication, and nursing home residence during the 12 months before initiating a medication. However, models adjusted for the significant patient variables explained only 6% of the variation in compliance.
Most patients who initiate a medication for osteoporosis do not continue to take it as prescribed. Although several patient characteristics significantly correlated with compliance, adjusted models explained little of the variation.
Several effective drug treatments for osteoporosis have become widely available during the past decade. Because patients with osteoporosis may have no symptoms from weakened bones until a fracture occurs, treatment for low bone mineral density (BMD) frequently begins during an asymptomatic phase of the condition. Data for several other chronic and largely asymptomatic conditions suggest that long-term medication compliance is often poor. Large community-based studies have shown that 40% to 60% of patients continue to take medications for hypercholesterolemia 1 year after initiation.1 Although prior research on osteoporosis treatment compliance has suggested that 60% to 80% of patients continue to receive therapy for at least 1 year, these studies were conducted in selected patient groups, several had relatively small samples, and some relied on patient self-report of medication use.2-4
We examined rates and predictors of compliance with medications for osteoporosis among a large population of unselected low- to moderate-income Medicare beneficiaries who all had a state-funded drug benefit requiring a minimal copayment. The cost of medications may be an important factor affecting noncompliance in other populations, but we were able to minimize this effect by studying compliance in a population with a drug benefit. We hypothesized that in addition to patient characteristics at the time of initiating treatment, time-varying factors, such as recent hospitalizations, fractures, or BMD testing, would influence long-term compliance. Although we are aware that some patients who discontinue their medications are actually being compliant with a physician’s request, the term compliance will be used to refer to long-term continuation with any osteoporosis medication.
The study database included all Medicare beneficiaries also eligible for a state-run drug benefits program in Pennsylvania—the Pharmaceutical Assistance Contract for the Elderly (PACE). Beneficiaries of PACE have annual incomes between $10 000 and $20 000 and are 65 years or older. The PACE drug benefit provides all outpatient drugs at a small copayment of $6 to $10. None of the medications for osteoporosis had prescribing restrictions.
We limited the study population to beneficiaries of PACE who had initiated use of a medication for osteoporosis from January 1, 1996, through December 31, 2002. These included bisphosphonates (alendronate sodium and risedronate), calcitonin, hormone therapy (except progesterone-only preparations and vaginal creams), and raloxifene hydrochloride. Teriparatide was not included because it became available only in late 2002. Because indications for medications were not identified in the database, some of the prescriptions for medications like hormone therapy were probably not explicitly used for osteoporosis but were included as such. All patients in this study were aged at least 65 years, so hormone therapy would not have been used for short-term menopausal symptoms. To reduce the chance that patients were obtaining medications through other means, we excluded patients who had not filled medications for any condition through PACE in each of the two 6-month intervals immediately preceding their initial osteoporosis prescription. Medication information from PACE consisted of the drug name, dosage, number of pills dispensed, and days’ supply. The study database included Medicare information on all inpatient and outpatient encounters, including diagnoses, procedures, and tests (without results). The study investigators have data use agreements in place with Medicare and PACE. To ensure patient confidentiality, all personal identifiers were removed from the study database after linkage was achieved. The institutional review board of Partners Healthcare, Boston, approved this research.
This retrospective analysis was designed as a cohort study of patients who initiated an osteoporosis medication from January 1996 through December 2002. We examined osteoporosis medication use in sequential 60-day periods starting with the initial prescription and the index date, and we followed the patients’ progress until they died or lost eligibility for PACE. Sixty days was chosen as the period to study because most prescriptions allow for a supply of 30 or 60 days, and the shorter 30-day period would be prone to less stable estimates. Within each 60-day period, we defined the proportion of days that osteoporosis medications were available to participants (days covered) on the basis of the day supply field. The days covered was calculated by summing the number of days when an osteoporosis medication was available and dividing by the period length of 60 days.
Because patients commonly have brief intervals between active prescriptions, we did not require them to fill medications to cover 100% of days in each interval. No data definitively establish the percentage of days required for an osteoporosis medication to be effective. However, results of 1 observational study suggested that patients reporting compliance for at least two thirds of days had better BMD than those reporting less; thus, we used greater than 66% of days covered as the primary threshold for compliance.3 Sensitivity analyses were used to explore alternative thresholds, such as greater than 50% and greater than 85% of days covered. Results for these alternative thresholds were similar to those of the primary analysis and are not included here. We also assessed several categories of compliance: no days with medications, 1% to 33% of days, 34% to 66% of days, and greater than 66% of days.
We had 2 objectives for developing multivariable models of compliance: (1) to examine predictors of compliance, and (2) to identify factors available from the baseline year that could be used to identify patients likely to be compliant. Results from the second set of analyses could help inform quality improvement interventions that might be initiated when drugs are started. Although these modeling exercises are closely related, different types of variables were entered into the models. For the first goal, we examined potential predictors of osteoporosis medication compliance in the 12 months before initiating treatment (baseline variables) and then since initiation of the osteoporosis medication (time-varying variables). For the second goal, we entered only baseline variables in the model. The baseline 12-month period extended back into 1995 for patients who initiated treatment in 1996.
Baseline variables included age; sex; race; annual income; marital status; nursing home residence; acute care hospitalization; fractures of the hip, wrist, humerus, or spine; BMD testing; number of physician visits; number of comorbid conditions (a comorbidity index)5; and total number of different nonosteoporosis medications used. For each 60-day period after initiation of a medication for osteoporosis, we repeated the assessment for the time-varying variables such as nursing home residence, acute care hospitalizations, fractures, and BMD testing.
We first calculated the proportion of days covered by an osteoporosis medication for each 60-day period after initiation of treatment. Kaplan-Meier survival curves were then constructed to estimate the distribution of time until a patient had 2 consecutive 60-day periods with no supply of any osteoporosis medication. The Kaplan-Meier curves were stratified on several key variables. Differences between the survival curves were evaluated by using a log-rank test.
Multivariable regression models were then constructed to assess variables associated with an increased likelihood of osteoporosis medication compliance. Our primary definition of medication compliance was a dichotomous categorization, and secondary analyses treated compliance as a continuous percentage. For the primary analyses, we initially dichotomized compliance as greater than 66% of days with any osteoporosis medication in a 60-day period. We constructed models for this dichotomous end point by using both a logarithmic and a logistic link function. The results were similar, and we display the results from the log-linear models, since the variables are interpretable as relative risks. All possible baseline and time-varying predictors were tested. Only the variables significant at P<.05 were retained for the final models. This process was repeated in a linear regression model with the percentage of days covered as the outcome, and predictors included baseline and time-varying patient-level variables. Because each participant contributed multiple periods, all analyses report standard errors that are estimated by using a generalized estimating equations approach for repeated measures data.6,7 Sensitivity analyses were used to test 120 days as the period length. There were no important differences between the 60-day and 120-day periods. All analyses were conducted using SAS version 8.02 (SAS Institute Inc, Cary, NC).
We identified 40 002 patients who initiated a medication used for osteoporosis from January 1996 through December 2002 (Table 1). The mean age of the treated population was 80 years. Most were white and female, reflecting the makeup of the underlying population enrolled in PACE. On the basis of information from the 12 months before initiating an osteoporosis drug, patients in the study sample had an average of 2 major comorbid conditions and used 9 different medications. About a third had an acute care hospitalization, and 12% had resided in a nursing home for at least part of the baseline year. Approximately one fifth had a fracture during the baseline year, and a similar proportion underwent BMD testing.
After initiation of 1 of the osteoporosis study medications, the percentage of days covered decreased rapidly during the first year (Figure 1). At the end of the first year of treatment, 45.2% of patients had discontinued osteoporosis treatment. This finding was demonstrated by at least 120 consecutive days without any filled prescriptions for osteoporosis. The proportion of patients filling their prescriptions did not change substantially after the first year. After 5 years of follow-up, 52.1% of patients were not continuing to fill prescriptions for an osteoporosis drug.
Kaplan-Meier curves suggest a similar trend of noncompliance with osteoporosis medications (Figure 2A). Those who underwent baseline BMD testing were more likely to remain compliant with osteoporosis medications than those who did not undergo BMD testing during the 12 months preceding medication initiation (Figure 2B). Compliance also differed significantly according to patient age, with the lowest compliance observed in patients 85 and older (Figure 2C).
In the multivariable models that included time-varying and baseline variables, several patient characteristics were associated independently with increased compliance (Table 2): female sex, BMD testing before and after initiating a medication, fracture before and after initiating a medication, and institutionalization in a nursing home before initiating a medication. Variables that reduced the likelihood of remaining compliant included being older, more comorbid conditions, more nonosteoporosis medications used, and institutionalization in a nursing home after initiating a medication. After controlling for these patient characteristics, patients who began taking raloxifene were more compliant than those who began taking a bisphosphonate; those who began taking hormone therapy or calcitonin were the least compliant. However, these multivariable models explained only 6% of the variation in compliance (R2 = 0.06).
The second set of models included only factors available at the time of initiating treatment (baseline variables). These models included virtually the same baseline variables as the previous set of models and produced similar point estimates (Table 2).
Finally, we examined models that considered the percentage of days covered with an osteoporosis medication in a 60-day period as a continuous end point (Table 3). The final set of variables in these models was similar to those in the models in which a dichotomous end point was used. However, these data can be interpreted directly with respect to increases in compliance. For example, women were compliant with osteoporosis medications for 3.3 days more than men in a given 60-day period.
In this study of unselected older adults, we found relatively low compliance with medications used for osteoporosis. After 1 year, 45.2% of patients were no longer still taking an osteoporosis medication; this increased to 52.1% after 5 years. Several characteristics of patients during the 12 months before their first prescription, as well as several variables since initiation, were associated with greater compliance. An adjusted model with many patient characteristics still had a relatively low ability to explain the variation in compliance. This finding suggests that other factors—patient beliefs or socioeconomic, physician-related, or health system issues—might be important correlates of osteoporosis medication compliance.
Prior research on compliance with osteoporosis medications is not entirely consistent with these findings. Authors of a large study from a health maintenance organization found that among women 45 years or older who had undergone BMD testing, 78% self-reported continuing osteoporosis medications 7 months after initiation.2 Treatment discontinuation was more common in women who reported bothersome adverse effects or did not think that their BMD test results showed osteoporosis. The much lower discontinuation rate in that study than what we observed may be related to several factors: drug use was measured by means of self-report; all women had undergone BMD testing at baseline; and the health maintenance organization population was younger and more likely to be health seeking, better educated, and more affluent. Authors of another study, also from a health maintenance organization, assessed compliance among women who had undergone BMD testing; they found that approximately 70% of respondents were compliant with osteoporosis medications.3
Our study differed in important ways from those in the literature. We included all older adults enrolled in a large drug benefits program for low- and moderate-income elderly patients in 1 US state. These persons are relatively frail and at high risk of future fractures, so they are an important group to study. The fact that all patients in the study had a drug benefit with minimal copayment limited our ability to study the effects of drug costs on compliance, even though economic issues may be an important correlate of long-term drug use, especially when the benefits of medication use may not be immediately obvious to patients. Although use of a large population of older adults is a potential strength of the study design, reliance on pharmacy claims has important limitations.
First, we were unable to assess the reasons for starting or stopping medications, so some of the prescriptions that we included as osteoporosis treatments were for other indications. Some of the hormone therapy noncompliance, as well as noncompliance with other medications, may have been at the advice of physicians on the basis of potential risks and/or adverse events. We attempted to deal with this limitation by considering patients who switched among treatments for osteoporosis as compliant. This categorization limited our ability to look at compliance with any given drug, but it did not lead to misclassification of a patient who switched medications as noncompliant. Nevertheless, some of the women who discontinued hormone therapy after the publication of the Women’s Health Initiative in July 2002 may have done so because of the lack of cardiovascular benefit.8 Because our study period was from January 1996 through December 2002, most of our follow-up occurred before the publication of the Women’s Health Initiative. Moreover, we found low rates of compliance no matter which medication was used at initiation.
Second, our pharmacy claims data did not include over-the-counter calcium and vitamin D supplement use. Patients who switch from a prescription medication to nonprescription calcium and/or vitamin D would be considered noncompliant. Although many consider these treatments suboptimal if a patient has confirmed osteoporosis, not all patients included in our cohort would be considered to have definite cases of osteoporosis.
Third, pharmacy claims data report only prescription filling, not actual medication use. We assumed that regular refilling of prescriptions is a good surrogate for long-term medication use, but it may not be. However, it is clear that patients who do not fill prescriptions consistently are likely to be noncompliant.
Finally, our data were limited to claims for procedures, diagnoses, and medications. We had no information about BMD test results. This limited our ability to determine the appropriateness of treatment. We chose the availability of medications on greater than 66% of days on the basis of 1 prior observational study that found this level to be a threshold for improved BMD.3 The results of our analyses were similar regardless of whether we used the alternative (50% or 85%) thresholds, but more work is necessary to determine whether intermittent use of these agents is effective. Moreover, the optimal duration of treatment is unclear.9,10
Our findings have several implications. Clinicians need to be aware that many patients initiating a medication used for osteoporosis do not continue to take these drugs long term, which limits the effectiveness of these treatments and suggests the need for interventions to improve compliance. Although the variables we identified do not explain much of the variation in compliance, some may provide valuable insights into improving long-term use of these medications. Several of the stronger correlates of long-term compliance included BMD testing at baseline and testing subsequent to initiation of treatment. It is unclear whether BMD testing motivates patients to remain compliant or whether it is a marker for patients and physicians who are concerned with osteoporosis and are more likely to remain compliant with medications. Another notable correlate of compliance was nursing home residence. Residence in a nursing home during the 12 months prior to initiating a treatment for osteoporosis was associated with an increase in compliance, but nursing home residence subsequent to initiation was associated with a reduced likelihood of persistent use. At first inspection, these findings seem contradictory. However, we think that certain physicians may be comfortable initiating osteoporosis medications on the basis of clinical indications. Other physicians, perhaps at different nursing homes, may think that treating osteoporosis is not worthwhile or is dangerous in frail recumbent residents of a nursing home. Thus, some patients transferred to their care may have their osteoporosis treatments discontinued. This finding warrants further analyses to determine how frequently medications for osteoporosis are discontinued in the nursing home setting and to develop strategies for improving osteoporosis treatment in this setting.
The low long-term compliance rates we observed highlight the need for improved strategies to ensure compliance with osteoporosis medications and/or medications that are easier to use. Patient reminder systems and improved physician-patient communication about compliance may help improve long-term use of these medications. New medications and new formulations of older medications requiring less frequent dosing also may help improve this discouraging picture. The promise of more effective medications for osteoporosis will not be realized until the health care system can effectively enhance long-term compliance with pharmacologic treatments. This issue looms large as the population ages and the number of persons at risk of osteoporosis grows.
Correspondence: Daniel H. Solomon, MD, MPH, Division of Pharmacoepidemiology, Brigham and Women’s Hospital, 1620 Tremont S, Suite 3030, Boston, MA 02120 (email@example.com).
Accepted for Publication: July 8, 2005.
Financial Disclosure: None.
Funding/Support: This study was supported by grants AR-48616, DK-02759, and AR-47782 from the National Institutes of Health, Bethesda, Md. Investigators are also supported by grants from the Arthritis Foundation, Atlanta, Ga, and its Engalitcheff Arthritis Outcomes Initiative. There was no pharmaceutical industry support for this study.