In the wake of what was the Food and Drug Administration’s (FDA’s) lowest new drug approval total in several years, the pharmaceutical industry is once again showing signs of life. The FDA’s Center for Drug Evaluation and Research approved a total of 21 new drugs in 2010; of these, 15 were new molecular entities (NMEs) and 6 were novel therapeutic Biologic License Applications (BLAs). As of July 20, 2011, the agency has approved 19 new drugs: 16 NMEs and 3 BLAs. Furthermore, of the 19 new drugs approved by the FDA this year, several have blockbuster sales potential, defined as a product that generates at least $1 billion in annual revenue for the manufacturer that produces it. These include new treatments for hepatitis C, lupus, and melanoma.

The new approvals of potential blockbusters represent a significant new source of revenue for pharmaceutical manufacturers, who will also experience a significant loss of income from blockbuster products expected to see generic competition for the fi rst time in 2011. The year has thus far seen the introduction of generic versions of Concerta and Levaquin. Before the year is out, generic versions of Lipitor and Zyprexa are expected.

New drug approvals are but 1 element—albeit a significant one&mdash;among many factors that impact drug spending via increased utilization. Other factors include new approved indications, reformulations, off-label drug use, changing demographics (eg, our aging population), pharmacy benefit designs, pharmaceutical promotional spending, new treatment guidelines, and the economy.

A full list of new drug approvals through July 20, 2011, can be found in the 

, including all NMEs and therapeutic BLAs approved by the Center for Drug Evaluation and Research. The most significant of these identified as having a strong potential impact on utilization, cost, and overall trend include the following:

Human Genome Sciences’ biologic Benlysta (belimumab), approved in March, is the fi rst new drug for lupus in more than 50 years.

 The company said Benlysta would cost (at launch) $443 for a 120-mg vial and $1477 for a 400-mg vial. The FDA puts the systemic lupus population at around 300,000 minimum.

Another biologic, Bristol-Myers Squibb’s injectable drug Yervoy (ipilimumab), was approved in March for late-stage or metastatic melanoma, and is the first drug shown to prolong the lives of patients with this form of advanced skin cancer. It will be priced at $30,000 per injection, for a total price of $120,000. Melanoma is the deadliest type of skin cancer, but the FDA has only approved 2 other drugs for advanced melanoma. The newer of those drugs was cleared more than 13 years ago. Neither drug has been shown to significantly extend patient lives.

The FDA approved 2 new hepatitis C treatments in May: Merck’s Victrelis (boceprevir) and Vertex Pharmaceuticals’ Incivek (teleprevir). Merck said the wholesale acquisition cost (WAC) for Victrelis will be $1100 per week,

 dosed for 24 to 44 weeks, whereas Vertex said Incivek would carry a price of $49,200 for a 12-week course of therapy. The WAC for Incivek will be only $800 higher for the course of therapy than the WAC for Victrelis when patients take that drug for 44 weeks. But for Victrelis patients who receive the drug for 24 weeks, the cost will be significantly lower than that for Incivek. The duration of treatment with Victrelis, however, is not determined until after starting treatment. Both agents produced a substantially greater sustained virological response rate compared with the existing standard of care.

On July 1, the FDA approved Johnson & Johnson/Bayer’s Xarelto (rivaroxaban) to prevent certain blood clots, known as venous thromboembolisms, in people undergoing knee- and hip-replacement surgery. Johnson & Johnson said Xarelto is the first new oral anticoagulant approved to prevent venous thromboembolisms in joint-replacement surgeries. An older drug used for this purpose, Lovenox (enoxaparin), is injected. A bigger market for Xarelto lies in its use to prevent strokes in people with atrial fibrillation. The companies have filed for approval to market Xarelto for this use, and a decision could come later this year from the FDA. Xarelto was launched shortly after approval with a WAC of $6.75 per unit.

Also in July, the FDA approved AstraZeneca’s Brilinta (ticagrelor) to reduce thrombotic events in patients with acute coronary syndrome, including unstable angina, and in patients with myocardial infarction who are candidates for stenting. Acute coronary syndrome includes a group of symptoms for any condition, such as unstable angina or heart attack, that could result from reduced blood flow to the heart. The FDA said Brilinta’s label will include a “boxed warning to healthcare professionals and patients warning that aspirin doses above 100 mg per day decrease the effectiveness of the medication.” A widely touted benefit of Brilinta is that its effect can be quickly switched off because it has a much shorter half life than either of the 2 approved antiplatelets, Plavix (clopidogrel) and Effient (prasugrel). A limitation of Brilinta’s pivotal trial program is that most of the patients came from Europe, the Middle East, or Africa. Only 11% of the patients were recruited in North America. In that cohort, Brilinta-treated patients were 27% more likely to suffer one of the end point events, although the difference fell short of statistical significance.

As new drugs become available, prescribing guidelines are updated and may impact utilization trends. An example of this is the updated protocol for treatment of atrial fibrillation published by the American College of Cardiology (ACC) and the American Heart Association (AHA). Pradaxa (dabigatran) capsules were approved by the FDA in October 2010 for prevention of stroke and systemic embolism in patients with atrial fibrillation, making it the first oral anticoagulant to enter the market since warfarin (Coumadin and generics) was approved in the 1950s. While Pradaxa is exponentially more expensive than generic warfarin, its competitive advantage and market positioning relate to superior efficacy; in a pivotal study used to support approval, Pradaxa patients had 34% fewer strokes and systemic embolisms than warfarin patients.

 While the approval of Pradaxa in October came too late for inclusion in the new ACC/AHA guidelines published in December,

 an additional update was published by the groups in February 2011 that said that Pradaxa can be used as an alternative to warfarin to prevent blood clots and stroke in certain atrial fibrillation patients.

Arguably, the most significant approvals for the year have already been made, based on the list of products that have a 2011 review goal date at the FDA. However, a number of other novel products are expected to receive a review at the agency before the end of the year, including:

Firazyr (icatibant), Shire’s hereditary angioedema (HAE) drug, won support from an FDA advisory committee for a claim to allow patients to self-inject the product, which would distinguish it from established treatments that must be delivered by a physician or infused in a clinical setting. Additionally, because HAE attacks are unpredictable, the ability to self-inject and receive the medication quickly is very important to patients. The HAE treatment population is small (an estimated 7000 Americans suffer from HAE), so Firazyr is likely to be costly if approved.

 (NOTE: Firazyr was approved by the FDA on August 25, 2011.)

Ruxolitinib, Incyte’s myelofibrosis (a disorder of the bone marrow) candidate, demonstrated superiority compared with the best available therapy with respect to reducing splenomegaly and alleviating symptoms in patients with myelofibrosis. Also, ruxolitinib treated patients saw a reduction in a variety of disease-related symptoms; patients receiving the existing standard of care did not.

Significant new drug approvals that could occur in 2012 include the following:

Apixaban, by Bristol-Myers Squibb/Pfizer, is from the same class of blood thinners as Xarelto. Although it will be the third new oral anticoagulant to reach the market (following Pradaxa and Xarelto), in certain clinical settings it has demonstrated superiority to warfarin on safety and efficacy, which could help it gain market share against established products. Xarelto was shown to be noninferior, not superior, to warfarin on efficacy and bleeding in a pivotal study. Pradaxa demonstrated superior efficacy compared with warfarin, but it had a comparable risk of bleeding. The projected 2012 market entry is based on the intent by Bristol-Myers Squibb/Pfizer to file for FDA approval in the third or fourth quarter,

Bydureon (exenatide) is Eli Lilly/Alkermes’ once-weekly subcutaneous injectable glucagon-like peptide-1 analog for type 2 diabetes. The companies recently said that they plan to resubmit Bydureon to the FDA in the third or fourth quarter after announcing that the drug met the primary end point of an FDA-mandated cardiovascular risk study. In a 3-year study, patients treated with Bydureon showed sustained decreases in blood sugar, weight loss, and improvements in blood pressure and cholesterol levels.

In 2012, the number and significance of the brand-name drugs losing marketing exclusivity via the so-called “patent cliff” will experience a maximum value in terms of sales dollars at risk, with first-generic entries projected for Actos, Diovan, Geodon, Lexapro, Plavix, Provigil, Seroquel, and Tricor. Before the year is out, generic versions of Lipitor and Zyprexa are expected.

 Approximately $25 billion in domestic brand sales are expected to be lost to generic drugs in 2011, according to IMS Health, which noted that the amount of brand sales lost to generic drugs in 2010, by comparison, was half that amount. The company has characterized the first-generic approvals in 2011 and 2012 as the largest generic opportunities ever, in terms of the protected brand sales that will be exposed to generic competition.18

Articles

The American Journal of Pharmacy Benefits

Approvals of potential blockbuster drugs represent a new source of revenue for pharmaceutical manufacturers, who will experience significant income loss from generic competition in 2011-2012.

New Drugs, First Generics, and the Near-Term Pipeline 2012

Schizophrenia is a chronic mental illness, characterized by episodes of relapse and control of symptoms, affecting both social and occupational functioning. Up to 80% of patients diagnosed with schizophrenia or schizoaffective disorder are nonadherent to oral antipsychotic medication, contributing to high relapse rates.

 Nonadherence to prescribed antipsychotics contributes to increased clinic and emergency department visits and psychiatric hospitalizations, resulting in increased healthcare expenditures.

 Typical long-acting injectable antipsychotics (eg, haloperidol and fluphenazine) were developed in the 1960s to improve adherence rates and decrease relapse.

 Risperidone long-acting injection (RLAI) therapy is the first atypical antipsychotic marketed in the United States and approved for the treatment of schizophrenia (2003) and for bipolar I disorder (2009). The unique drug delivery system releases medication over an extended period, allowing for dosing intervals every 2 weeks. Several pharmacoeconomic analyses have concluded that patients receiving RLAI have fewer hospitalizations compared with those receiving oral antipsychotic therapy or during the time period before initiation of RLAI, resulting in a reduction in total costs.

 Although there is a definitive relationship between RLAI adherence and reduced economic costs in the treatment of schizophrenia, adherence data in a naturalistic setting with RLAI is limited.

Medication adherence is affected by a multitude of individual and environmental factors. In schizophrenia, studies have demonstrated that medication adherence is infl uenced by global functioning level, substance abuse, level of social support, and quality of therapeutic alliances with healthcare professionals.

 The impact of discharge planning that occurs in the inpatient hospital setting in relationship to RLAI adherence in the outpatient setting is currently not defined. The objectives of this study are to (1) describe the adherence to RLAI following discharge from inpatient psychiatric hospitalization and (2) examine the predictors for outpatient RLAI adherence, especially factors related to discharge planning.

This is a retrospective study of patients receiving RLAI transitioning from an inpatient psychiatric state hospital to an outpatient community mental health center. Research was conducted at Western Missouri Mental Health Center (WMMHC) in Kansas City, Missouri, after approval from the University of Missouri-Kansas City Investigational Review Board and all outpatient sites included in the study. There are 6 outpatient community mental health centers in the surrounding Kansas City area; however, the majority of patients receiving inpatient psychiatric services at WMMHC receive outpatient psychiatric services from 2 of these facilities, Swope Health Services and Truman Medical Center Behavioral Health. Only individuals receiving outpatient psychiatric services from these 2 facilities were included in the study. All adult patients who received 

1 dose of RLAI during their inpatient stay and were discharged on RLAI from WMMHC to one of the community mental health centers listed above prior to June 30, 2008, were included in the study.

The primary end point is outpatient medication adherence to RLAI during the initial 3 months following discharge. The dates of RLAI administration at the community mental health center post-discharge were reviewed. Each patient should receive 6 doses of RLAI in total during the 3-month time frame, and the number of doses the patient actually obtained was used to assess adherence. A patient was considered as fully adherent if he or she obtained 6 doses.

Along with the number of doses obtained, the following variables were collected for each patient: age, gender, ethnicity, outpatient facility (Truman or Swope), length of stay since index admission, admission status (voluntary or involuntary), Axis I diagnosis, history of substance abuse, history of medication nonadherence, when RLAI was initiated (while inpatient or prior to admission), RLAI dose (25 mg, 37.5 mg, or 50 mg), discharge disposition (family, group home, self, or shelter), number of previous admissions, presence of a case manager, presence of a guardian, and establishment of an aftercare appointment within the time frame to receive the next RLAI dose. The last 3 variables reflected the degree of discharge planning. The data were collected using several different strategies. For Medicaid patients, a review of the Missouri Medicaid database was conducted. A manual review of institutional pharmacy and medical records was completed for all patients. Additionally, healthcare providers at the community mental health centers were contacted if needed.

Bivariate correlations were conducted for all variables. A linear regression analysis was performed where the number of doses obtained was the dependent variable. The independent variables included 2 groups of variables: (1) gender, outpatient facility, length of stay since index admission, and when RLAI was initiated, because their correlation coefficients with the dependent variable were not <0.2; and (2) presence of a case manager, presence of a guardian, and establishment of an aftercare appointment to assess the impact of discharge planning on adherence. In addition to these analyses, the reasons for discontinuation of RLAI and rate of rehospitalization were also explored.

A total of 126 patients were identified as being on RLAI during inpatient admission since the medication was approved in 2003; 73 patients were excluded due to various reasons which included: not referred to one of the included outpatient mental health facilities (n = 47), not discharged on RLAI (n = 10), and unable to access medical records (n = 16). A total of 53 patients met inclusion criteria and were included in the study. Patient characteristics are shown in 

. The majority of patients receiving RLAI were male (n = 40, 75%), African American (n = 36, 68%), had an Axis I diagnosis of paranoid schizophrenia (n = 37, 70%), and were involuntarily admitted (n = 32, 60%) to the inpatient psychiatric hospital due to acute psychosis. It is important to note our study population is reflective of people with serious and persistent mental illness from an urban setting.

Overall, 24% (13/53) of patients were considered fully adherent (6/6), as they received all 6 injections during the 3-month time frame, and 34% (18/53) were considered 80% adherent (5/6), as they received 

5 injections during the 3-month time frame. Sixty percent (32/53) of patients were initiated on RLAI and received their first injection while inpatient; more than half of these patients (19/32, 59%) did not follow up to receive even 1 injection in the outpatient setting. Out of the total number of patients included in the study, 40% (21/53) failed to receive a single dose of RLAI in the outpatient setting following discharge from the hospital; 19 of the 21 patients (90%) who failed to follow up were started on RLAI inpatient in an attempt to improve medication adherence in the outpatient setting.

The results of the regression are shown in 

. The regression model explained 11% of the variance in doses obtained. Among the independent variables, when RLAI was initiated was the strongest predictor for doses obtained (standardized beta = 0.34) and was the only significant predictor (

 <.05). Compared with patients who initiated RLAI while inpatient, patients who initiated RLAI before admission obtained approximately 2 more doses of RLAI, controlling for the other independent variables. None of the variables related to discharge planning, independently or collectively, were a significant predictor.

Documentation regarding reason for RLAI discontinuation was provided for only 15% (8/53) of patients and included patient refusal (n = 4), lack of follow-up (n = 3), and lack of efficacy (n = 1). A total of 15% of patients (8/53) included in the study were readmitted within 3 months of discharge. There is a possibility that patients were admitted to a hospital outside of our tracking ability via hospital records and the Medicaid database.

In this study, the rate of adherence to RLAI in the outpatient setting following discharge from inpatient psychiatric hospitalization was 24% or 34%, depending on the threshold set for adherence. That is, 24% of patients were considered adherent when the threshold was set to be 100% adherent, and 34% of patients were considered adherent when the threshold was set to be 80% adherent. Accordingly, the rate of nonadherence was 66% to 76%. This is comparable to nonadherence rates for oral antipsychotics found in the literature, though estimates of medication nonadherence vary significantly depending on each particular study’s definition of nonadherence, the study population, and methods for assessing adherence.

The use of long-acting injectable antipsychotics does not eliminate medication nonadherence but does address some of the issues associated with nonadherence, such as eliminating the need for daily dosing and identifying covert noncompliance.

 Most of the evidence for depot antipsychotics (eg, haloperidol, fluphenazine) indicates that their use is associated with increased medication adherence and a reduction in relapse rates.

 Low rates of discontinuation were found in RLAI randomized controlled trials.

One study reported a discontinuation rate of approximately 8% over 12 weeks

and another study reported a discontinuation rate of 35% over 12 months.

 The adherence rates derived from randomized controlled trials with strict inclusion and exclusion criteria may not be applicable to our study population.

The focus of most of the outcomes literature involving RLAI is the evaluation of healthcare resource utilization.

 In order to be included in these prospective and retrospective studies, patients had to have received a minimum number of injections, usually 

4 injections, in the outpatient setting. Many of these studies have shown improved medication adherence and reduced healthcare costs associated with RLAI compared with oral antipsychotic therapy or the time period prior to RLAI. But once again, these studies may not be reflective of RLAI in clinical practice as they do not include all patients initiated on RLAI (ie, those receiving <4 injections). Additionally, these studies were conducted in either a Veterans Affairs patient population or outside the United States, which may not be reflective of RLAI use in community mental health centers in the United States due to differences in healthcare access and delivery. European countries tend to mimic the Veterans Affairs closed system of care, in which there is potential for better follow-up and management of care.

There are limited data evaluating adherence to RLAI in a naturalistic setting. There are no published studies evaluating RLAI adherence following hospital discharge. It is a common occurrence for a long-acting injectable antipsychotic to be initiated in the inpatient setting with the intention that it will improve medication adherence in the outpatient setting following discharge. Evaluation of the effectiveness of this practice is needed to guide clinical practice.

Our study found that 40% (21/53) of the study population failed to receive RLAI in the outpatient setting following hospital discharge; 19 of these patients (90%, 19/21) were initiated on RLAI in the inpatient setting. This is in comparison with only 2 patients who were receiving RLAI prior to admission and failed to receive RLAI following hospitalization. The regression analysis identified RLAI initiation (inpatient or prior to admission) as a significant predictor for medication adherence. These findings question the effectiveness of the practice of initiating RLAI in the inpatient setting in an attempt to increase outpatient medication adherence. There are multiple factors which likely impact the effectiveness of such practice, including issues surrounding formulary guidelines, expense, lack of continuity in care between inpatient and outpatient settings, and poor medication reconciliation.

There are no published studies evaluating RLAI adherence during a 3-month time frame, regardless of whether initiation was in the inpatient or outpatient setting. The 3-month time frame following hospital discharge is critical because, during this vulnerable period, the patient may still be undergoing stabilization and, in some cases, is still being transitioned from oral risperidone to RLAI. Using strict criteria to define nonadherence (ie, received 6 doses of RLAI in a 3-month time frame), we found that 76% of patients were nonadherent to RLAI following hospital discharge, which is high by any standard. Using less stringent criteria, defining adherence as receiving >80% of medication (eg, 

5 RLAI doses in a 3-month time frame), nonadherence to RLAI therapy was found to be 66%, which still reflects a significant degree of nonadherence. Three studies have reported RLAI nonadherence rates at 6 months to be between 41% and 52.8%.

 Our rate of nonadherence to RLAI therapy at 3 months exceeds what has been reported in the literature for 6 months. Our 3-month nonadherence rate of 66% is more comparable to a 12-month discontinuation rate of 67.6%, which was reported in 1 study.

 This 12-month study included a description of the attrition rate, which was reported to be constant, suggesting a significantly lower nonadherence rate at 3 months than that reflected at 12 months. A comparison of our data with these previous studies is difficult as the time frames and patient populations are different. Our study included inpatients initiated or continued on RLAI then discharged to the outpatient setting, whereas other studies have included both inpatients and outpatients initiated on RLAI or outpatients only.

The nonadherence rate to RLAI observed in this study is higher than expected and may be due to several reasons attributed to our study population. As stated above, we included only patients with a recent inpatient psychiatric hospitalization. Our patient population may be less psychiatrically stable than other RLAI study populations. Although we did not evaluate treatment resistance, the fact that we included only those patients recently hospitalized may select for a more difficult-to-treat population compared with other studies. More than half of our study population was involuntarily admitted to the hospital, which is reflective of their lack of insight and resistance to treatment and likely carries over into the outpatient setting following hospital discharge. Additionally, the majority of our population were either actively abusing substances or had a history of substance dependence with alcohol, marijuana, or cocaine, a known barrier to medication adherence.

To our knowledge, there is only 1 other study evaluating factors or predictors associated with medication adherence in patients receiving RLAI.

 This study reported that continuation of RLAI at 6 months was more likely to occur in patients aged 

55 years and in those receiving RLAI 37.5 or 50 mg. The lack of association between discharge planning factors and RLAI adherence in our study may again be a reflection of our study population or could be attributed to the small sample size.

The rehospitalization rate in this study was 15%. The short duration of this study is optimal for evaluation of medication nonadherence during the transition from an inpatient to outpatient setting; however, it is insufficient in evaluating secondary outcomes, such as rehospitalization due to the occurrence of delayed relapse, which can occur several months following discontinuation of antipsychotic therapy.

Due to the retrospective nature of the study, many limitations exist which could potentially affect the outcome of the study. Although several databases were used for data collection to improve the accuracy of the data, relying on documentation for evidence of drug administration and other information is not optimal. Limiting data collection to 2 outpatient community mental health centers may reflect adherence rates that are affected by policies associated with the use of RLAI and clinicians’ perceptions of who is an appropriate candidate for RLAI treatment. The policies and clinicians’ perceptions at the 2 centers may differ from other community mental health centers. The small sample size may also have limited our ability to detect an association between discharge planning factors and medication adherence.

Notwithstanding these limitations, our study has several strengths. This was a retrospective study conducted as an evaluation of normal clinical practice. Thus, bias due to clinician awareness of the presence of a prospective study did not affect treatment decisions. We included patients consecutively and did not exclude patients for any clinical reasons (eg, treatment resistance, history of medication nonadherence, comorbid medical or psychiatric conditions, concomitant medications, etc), thus reflecting normal clinical practice. It is the only study to evaluate RLAI adherence at the 3-month time point following hospital discharge and the second study to assess predictors associated with RLAI adherence.

Our study found that patients who initiated RLAI prior to admission obtained more doses than those who initiated while inpatient. In addition, adherence to RLAI in the outpatient setting following discharge from inpatient psychiatric hospitalization was less than optimal and was extremely poor for those patients initiated on RLAI in the inpatient setting. This study emphasizes the continued need to discuss patient acceptance of risperidone with regard to route of administration in a collaborative setting. It also highlights the importance of communication, including accurate medication reconciliation, between inpatient and outpatient healthcare providers.

Adherence to risperidone long-acting injection (RLAI) therapy in the outpatient setting was poor. Degree of discharge planning from inpatient hospitalization was not associated with RLAI adherence.

Outpatient Adherence to Risperidone Long-Acting Injection Following Discharge From a State Psychiatric Hospital

In the United States, adjuvant chemotherapy with an anthracycline-based regimen is a widely used treatment for operable, invasive breast cancer. However, improved survival times in early-stage breast cancer patients are accompanied by concerns regarding the long-term toxicity of chemotherapeutic drugs, particularly anthracycline-associated cardiomyopathy.

Taxanes (eg, docetaxel) are among the most widely used therapies in the treatment of metastatic breast cancer.

 Recently, the effi cacy of these drugs has been demonstrated in the adjuvant setting. Results of the US Oncology Research trial 9735 (USOR 9735) demonstrated significant improvements in 7-year disease-free survival (DFS) (81% vs 75%; hazard ratio [HR] 0.74, 

 = .033) and overall survival (OS) (87% vs 82%; HR 0.69, 

= .032) for docetaxel and cyclophosphamide (TC) versus doxorubicin and cyclophosphamide (AC) in women with resected node-positive or high-risk nodenegative breast cancer (

The results of the USOR 9735, along with concerns about anthracycline-associated cardiac toxicity, may provide support for the selection of TC over AC for women with nodenegative and lower-risk, node-positive breast cancer. In the past, the evaluation of pharmaceuticals by managed care organizations for inclusion on the formulary had a primary focus on safety and effi cacy. With rising drug expenditures in the United States over the last decade, cost considerations have now become essential.

Accordingly, the objective of this analysis was to assess the cost-effectiveness of adjuvant TC therapy compared with standard AC therapy from the perspective of US managed care organizations.

The analysis was conducted using a lifetime decision model, developed in Microsoft Excel (Microsoft, Redmond, WA), simulating disease progression in early-stage breast cancer (

). The model followed a cohort of patients for their lifetimes.

One arm of the model considered adjuvant chemotherapy with TC, while the other considered adjuvant chemotherapy with AC. Over each 1-month cycle, patients either remained in the “alive” state or were transitioned to the “dead” state. These transitions were based on survival data reported in the USOR 9735.6 Costs and outcomes beyond 1 year were discounted at 3% annually.

Disease recurrence was modeled as an event rather than a health state, and it was assumed that patients who did experience recurrence could do so only once during the trial time period. This simplifying assumption was deemed reasonable given the relatively low recurrence rate during the trial period. Those experiencing a recurrence were attributed a utility decrement, representing quality of life (QoL) lost as well as the costs associated with that recurrence.

The base case estimates applied to a “typical” patient enrolled in the USOR 9735.

This prospective, phase III, randomized study evaluated TC or AC treatment in 1016 women with operable stage I to III breast cancer. These patients had undergone complete surgical excision of the primary tumor, had no evidence of metastatic disease, and were eligible for adjuvant chemotherapy. The median age of patients was 51 years; 84% were younger than age 65 years. The majority of patients (71%) had breast cancer that was estrogen receptor positive and/or progesterone receptor positive and 52% of patients were node positive.

Patient treatment in the USOR 9735 consisted of four 3-week cycles of either TC (75 mg/m

 of doxorubicin and 600 mg/m2 of cyclophosphamide). Accordingly, these were the therapy regimens evaluated in this analysis.

The long-term effectiveness for TC and AC was derived from USOR 9735 and extrapolated the potential clinical benefits and costs over the lifetime of a patient cohort. Survival over the first 7 years in our analysis followed that of patients in USOR 9735 and survival beyond 7 years matched that of the general population of US women aged 58 years (25.7 years at age 58). Given that the cycle duration of the model was 30 days to allow for the attribution of costs and utility, the OS curve was digitized using TechDig software (TechDig, Toronto, Ontario) to derive monthly transition probabilities. It was assumed that all patients alive and disease-free at 7 years, regardless of treatment, remained disease-free for the rest of their lives. This simplifying assumption was deemed reasonable given that 8-year data reported by Jones et al suggested a low risk of death or recurrence for TC patients after year 7, while the risk of death or recurrence for AC patients persisted beyond 7 years; thus, this simplifying assumption would bias the results against TC.

Disease recurrence was calculated as the inverse of the 7-year DFS curves from USOR 9735.

 The proportion of patients who died was removed to more accurately estimate recurrence and avoid double-counting death in the analysis. 

) provides the DFS curves from USOR 9735 along with the estimated recurrence curves. Recurrence was classified as either local recurrence or distant recurrence based on data from USOR 9735; 13.6% and 18.8% of TC patients and AC patients experienced local recurrence and 86.4% and 81.2% of TC and AC patients experienced distant recurrence, respectively.

Based on expert opinion, it was assumed that 25% of local recurrences were noninvasive and 75% were invasive.

Drug costs included only the cost of chemotherapy, assuming no drug wastage, a body surface area of 1.6 m

, and administration every 3 weeks for 4 cycles. Unit costs for the therapies were $16.732 per milligram for docetaxel, $0.466 per milligram for doxorubicin, and $0.0186 per milligram for cyclophosphamide. These drug costs were derived from Medicare Part B (October 2008) and were based on Biologics Average Sales Price plus a 6% markup (

Additional costs for the study were determined through analyses of the IMS LifeLink Health Plans Claims Database (PharMetrics)

 and Premier Perspective Comparative Database.

The IMS LifeLink Health Plan Claims Database includes longitudinal, integrated, patient-level medical and pharmaceutical claims comprising 4 billion patient observations from across the United States and more than 65 million patients from more than 95 health plans, including medical services and prescription drug information across the entire continuum of care. The Premier Perspective Comparative Database is a repository of hospital administrative data that includes approximately one-sixth of all hospitalizations in the United States. Service-level data that are recorded include charges for medications, procedures, and laboratory tests; characteristics of surgeons and hospitals are also available.

For costs associated with chemotherapy administration, the PharMetrics database was used to determine cost of administration per cycle. The sample included patients having a diagnosis of breast cancer (

] code 174) from January 2003 to December 2007, receiving at least 1 cycle of TC or AC following the first identified breast cancer diagnosis (assigned as the index diagnosis), and having mastectomy between index diagnosis and the first TC/AC use. The drug administration cost per cycle was determined separately for TC and AC cohorts and comprised physician visits, infusion procedure, equipment and solutions, growth factor, and other medications (ie, antinausea and antiemetic agents, agents to protect the heart).

Inpatient costs of treating grade 3 or 4 hematologic toxicities and fatal adverse events were derived from the Premier database from January 2004 to December 2007 for the events of anemia (

 code 478.0), and myelodysplastic syndrome (

Lastly, the cost of treating relapse (per episode) was estimated using the PharMetrics database. The sampled patients included those with a breast cancer diagnosis (January 2003 to December 2007) followed by a local recurrence (ie, 

 codes 196, 198.2, 198.81) or distant recurrence (ie, 

codes 197, 198, except 198.2, 198.81) after the index diagnosis. The costs of chemotherapy were assumed to be the same as in the adjuvant treatment setting. Other cost components of recurrence included diagnostic and staging, physician visits, surgery, and radiation.

Total local recurrence costs were composed of the weighted noninvasive (25%) and invasive (75%) costs. Treatment algorithms for local and distant recurrence were provided by expert opinion. For patients who experienced local invasive recurrence, it was assumed that 50% of patients would receive an additional course of chemotherapy, while 50% would not receive chemotherapy. For patients who received TC as adjuvant chemotherapy, it was assumed that 100% of patients would receive AC in postadjuvant treatment of local recurrence. For patients who received AC as adjuvant chemotherapy, it was assumed that 100% of patients would receive TC in postadjuvant treatment of local recurrence. For patients who experienced local noninvasive recurrence, it was assumed that patients would be treated with surgery. 

For patients with a distant recurrence who received adjuvant chemotherapy with TC, it was estimated that 50% of patients received a second course of TC, while 50% received a course of AC. For patients who received adjuvant chemotherapy with AC, it was estimated that 20% of patients received a second course of AC, while 80% received a course of TC. Following progression, 100% of patients, regardless of adjuvant chemotherapy, received approximately 6 cycles of chemotherapy with capecitabine. A total episode cost of distant recurrence utilized in the model was calculated by summing the cost within the first 6 months and the cost in the subsequent 6 months of recurrence.

Costs were inflated to 2008 dollars using the healthcare component of the Consumer Price Index and discounted at 3% per year.

As data specific to the US population were unavailable, the base utility value (0.79) for early breast cancer patients in remission (DFS) was obtained from a recent cost-effectiveness analysis by Wolowacz et al.

 This utility weight was calculated using the European Organisation for Research and Treatment of Cancer QoL questionnaire (QLQ-C030) on data collected in the BCIRG001 clinical trial.

Utility decrements for local (-0.09) and distant (-0.29) recurrence were also calculated based on the analysis by Wolowacz et al

by subtracting the respective utilities from the utility for remission. The QoL impact of recurrence was assumed to last for 1 year and the full utility decrement was applied in the first month of recurrence, in order to simplify the analysis structure. Overall survival was multiplied by health preference in order to obtain a quality-adjusted life-year (QALY). After 7 years, it was assumed that patient QoL would be comparable to that of women in the general population.

A series of 1-way sensitivity analyses were performed to explore the effect of changes in assumptions and data inputs on model outcomes (

The survival advantage associated with chemotherapy regimens may extend beyond the limited follow-up of clinical trials.

Therefore, we conducted 2 sensitivity analyses: (1) we assumed greater life expectancy in the TC arm equivalent to the mean difference in OS between the TC and AC arms within the clinical trial period (approximately 1.8 months) and (2) we assumed greater life expectancy in the TC arm equivalent to the difference in survival at the end of the 7-year trial period (approximately 22 months).

Several sensitivity analyses were conducted with respect to costs, inclusion of long-term fatal adverse events for AC, varying the utility decrements according to low

 ranges reported for local and distant recurrence, and varying the discount rate by 0% and 5%. Results for the base case and sensitivity analyses were presented as cost per life-year gained and cost per QALY gained in order to capture health-related QoL as well as OS.

Longer survival and fewer recurrences for patients receiving TC resulted in gains in both life-years and QALYs compared with those receiving AC (

). Base case results of the model suggested that the average TC patient was expected to live 18.95 years, which was 10.2 months (0.85 years) longer than the average AC patient. Following adjustment for QoL, the average TC patient was estimated to experience 14.87 QALYs vs the 14.20 QALYs experienced by AC patients.

Mean total lifetime disease-related costs were higher with TC compared with AC: treatment with TC was associated with a $5897 higher lifetime cost than AC, with a total per patient cost of $37,846. This cost difference was driven primarily by the higher drug acquisition costs associated with TC. Costs per life-year and per QALY gained (TC vs AC) were $8819 and $6985, respectively (Table 3).

Sensitivity analyses indicated that the results were most sensitive to changes in assumptions regarding the time horizon (date not shown). With a 7-year time horizon (ie, the time frame used in USOR 9735), the incremental cost per life-year gained remained under $50,000 ($45,037) and the incremental cost per QALY gained was very close to $50,000 ($53,983). In all remaining sensitivity analyses, cost per life-year gained remained between $3382 and $9367 and cost per QALY gained remained

The results of USOR 9735 demonstrated that compared with AC, adjuvant treatment with TC reduced the risk of recurrence and improved OS in patients with operable, invasive breast cancer. Grade 3 and 4 toxicities were comparable between the 2 groups with the exception of anemia, almost of all which occurred in older women receiving AC (5% vs 

1% in other groups) and febrile neutropenia, which was doubled in the TC group (5% vs 2.5%). There were 3 late deaths without relapse, probably related to treatment, and all occurred in the AC group. 

These findings prompted increased utilization of TC in early breast cancer treatment; however, the cost-effectiveness of this therapy in the United States remained unknown. Accordingly, the present economic evaluation was undertaken to determine the cost-effectiveness of TC compared with AC in this patient population. 

Results of the base case analysis demonstrated that treatment with TC compared with AC provided an increase of 0.85 year of life and 0.674 QALY per patient. These benefits were attained with a cost per life-year gained of $6985 and a cost per QALY gained of $8819 over a lifetime horizon. Overall, 1-way sensitivity analyses conducted on a variety of input parameters demonstrated the robustness of the base case results. Limitation of the time horizon to 7 years (the time frame of USOR 9735) resulted in an incremental cost per life-year of $45,037 and per QALY of $53,983; these values were below or close to the generally accepted threshold of $50,000 in the United States.

Strengths of the present analysis included the use of a simple, transparent analysis structure and the use of a gold standard, head-to-head, randomized controlled trial to provide the primary effectiveness inputs for the analysis. Furthermore, required assumptions were consistently biased against the new intervention, particularly assumptions regarding long-term survival. For the base case analysis, it was conservatively assumed that clinical benefits in terms of OS and recurrence did not extend beyond the end point of the clinical trial. Assuming no continued advantage for DFS and the same survival in both the TC and AC cohorts after the trial follow-up resulted in equivalent survival beyond 7 years. Since the recent Oxford overview (Early Breast Cancer Trialists’ Collaborative Group 2005) suggests that DFS and OS curves for alternative adjuvant regimens continue to diverge until at least 10 years after random assignment, it is likely that this analysis provided a conservative estimate of the longterm benefits of TC. The sensitivity analyses demonstrated that use of alternative assumptions (ie, extension of OS beyond 7 years) resulted in improved cost-effectiveness ratios, ranging from $3384 to $6574 for cost per life-year gained and $4296 to $8306 for cost per QALY gained.

Potential limitations of the present analysis included the inclusion of a single comparator, AC, without considering other regimens. However, trial-based cost-effectiveness analyses are often conducted, given that head-to-head, randomized controlled trial data provide the most direct evidence of the relative efficacy of comparator therapy. A second limitation would be the need for assumptions to be made when combining clinical data with data obtained outside of USOR 9735. For example, the availability of utility values for the calculation of QALYs in the United States was limited and varied considerably. Further, the data used for various cost inputs may not have been current, having been derived in some cases from database entries between 2003 and 2007. Overall, the analysis used the most up-to-date and accurate sources available. In addition, sensitivity analyses were conducted to address the impact of uncertainty about cost estimates on the costeffectiveness ratio, with the results being robust.

An analysis similar to the current cost-effectiveness evaluation of TC versus AC was recently conducted from the perspective of the Canadian publicly funded healthcare system.

 The results of this study also supported adoption of the TC regimen for the treatment of operable, invasive breast cancer, reporting comparable ratios of $6842 per life-year gained and $8251 per QALY gained over a lifetime horizon.

Our results were also consistent with a second Canadian cost-effectiveness analysis study, with recent findings presented by Younis et al at the 2008 San Antonio Breast Cancer Symposium.

 Also using data from USOR 9735, the authors found TC to be cost-effective compared with AC, with a cost per QALY of $16,753. Cost components and assumptions utilized in this Canadian analysis were similar to those used in our US analysis, with key differences being the inclusion of more than 1 opportunity for disease recurrence for each patient and use of a 10-year time horizon in the published Canadian analysis. Further economic evaluations specifically comparing these 2 chemotherapeutic regimens were not identified in the literature.

The similarity in results between the 2 published studies and this study suggests that country-specific differences in costing inputs and sources did not appear to impact the overall conclusions. Nevertheless, given the increasing emphasis on requirements for cost-effectiveness evaluations in the United States,

our study provided a unique comparative economic evaluation of these 2 chemotherapy regimens, applying US-specific resource utilization data obtained from nationwide, large representative databases.

Compared with doxorubicin plus cyclophosphamide, docetaxel plus cyclophosphamide was highly cost-effective for adjuvant treatment of operable breast cancer.

Cost-Effectiveness of Docetaxel-Cyclophosphamide Versus Doxorubicin-Cyclophosphamide for Breast Cancer

On September 12, 2009, The American Association of Diabetes Educators (AADE) hosted a “Taking Medication Symposium” in Chicago, Illinois. Fourteen invited participants examined diabetes self-management, attributes of diabetes education, and barriers to medication among people with diabetes. The symposium was designed to consider pre-set questions regarding how diabetes education can more effectively address barriers to medication use for diabetes and related conditions. The questions can be summarized as:

		What are the roles of healthcare providers in assisting people with diabetes relating to identification of strategies for taking prescribed medication and improving health?

		Within the context of medication adherence, what can be done to improve: a) clinical and b) behavioral assessments and interventions so that the best treatment and behavior change plans can be tailored for the individual living with diabetes?

		What are best practices for addressing barriers (including system barriers) to taking medication in relation to diabetes and its comorbid conditions?

		What can members of the diabetes care team do to enhance diabetes self-management education and training (DSME/T) and ongoing self-management support for people who are taking medication, with specific attention to populations with low literacy and low numeracy and other issues (eg, age-related, cultural, sociological)?

A Symposium Workgroup, comprising members of the AADE Research Committee, planned the symposium and established criteria for selecting a panel of academics and practitioners that would possess knowledge of diabetes, selfmanagement, and medications. Using the selection criteria, the workgroup searched the published literature and lists of conference speakers to identify potential attendees. Four multidisciplinary diabetes educators (nurse, dietitian, pharmacist, and behaviorist) who serve as members of the AADE Research or Professional Practice Committees were also invited. The Symposium Workgroup shaped the questions that would be addressed by the participant attendees and searched relevant literature to suggest a pre-reading list. A member of the AADE Research Committee served as the symposium chair; the event was facilitated by a professional moderator. These thought leaders (

) included 1 physician, 3 pharmacists, 1 advanced practice nurse, 1 registered dietitian, 1 public health nurse, 2 academic researchers, 1 pharmacy student, and 2 staff members from a national association. These participants came together to examine self-care behaviors for people with diabetes, attributes of diabetes education, and factors influencing and barriers to medication use. The discussants distilled findings from published literature with the aim of providing practical advice for healthcare practitioners regarding medication use for people with diabetes, so that the overall health of this population will be enhanced.

The Taking Medication Symposium marked the third in a series of symposia designed to focus on 7 specific self-care behaviors (healthy eating, being active, taking medication, monitoring, reducing risks, healthy coping, and problem solving), described as the AADE7 Self-Care Behavior Construct.

 The symposia series is designed to translate research findings from the literature into practice and develop recommendations for members of the diabetes care team to apply to practice.

The Taking Medication Symposium began with 2 presentations: 1) a review of the literature on taking medication, and 2) Internet-based support interventions in chronic disease self-management. Following these presentations, the panel engaged in a facilitated discussion of the questions that had been shaped by the participants prior to the discussion. The moderator synthesized the key messages throughout the event. Because all portions of the discussion were recorded, the authors were able to capture the richness of the discussion.

This report provides a summary of the panel’s discussion and highlights the key points, which apply to providers involved with diabetes care. It also links the Chronic Care Model with the multidisciplinary diabetes care team and the use of motivational interviewing skills and techniques to improve pharmacotherapy adherence.

 Motivational interviewing, for example, is one approach that is used to help people with diabetes become confident and motivated so that they can effectively make behavioral changes that are essential to the self-management of diabetes.

The Chronic Care Model underlies effective diabetes self-management because it places the patient at the center of the model and then intertwines the healthcare system, healthcare providers, and community to ensure that the needs of that patient are met.

 Likewise, Murray’s conceptual framework for studying medication adherence in older adults focuses on the relationship between environmental factors, patient characteristics, and medication adherence. This framework recognizes the importance of enabling resources (behavioral support), need, and outcomes, and thus has relevance for those engaged in diabetes self-management.

 While these models are relevant to the subject matter discussed in the Symposium, it was noted that there are few conceptual models that relate directly to diabetes self-management, behavior change, and medication use.

The symposium panel agreed that the field of diabetes education would best be advanced by discussing selfcare behaviors as a whole rather than separately. Indeed, what is known about diabetes self-management in general appears to also apply to taking medication. Rather than self-managing by performing each of the behaviors individually, people with diabetes make choices based on how these behaviors fit into their lifestyle. Therefore, taking medication is viewed as an integral part of the self-management continuum.

Pharmacologic therapy plays a vital role in the management of diabetes and is therefore a key element in the self-management of the disease.

Robust research provides clear evidence of the value of pharmacotherapy in achieving and maintaining glycemic control. Well-designed studies also document the benefits of medication in improving avoidable and costly microvascular and macrovascular outcomes of diabetes.

 Because of the efficacy of pharmacotherapy in lowering glycosylated hemoglobin (A1C) levels and keeping diabetes management on track, medication use has been identified by the AADE as one of the AADE7 Self-Care Behaviors.

 Together these behaviors form a framework for patient-centered diabetes management provided by a diabetes care team.

Recent pharmacologic advances have broadened the antihyperglycemic options available to persons with diabetes. However, despite this expansion in medication choices and the plethora of evidence supporting diabetes pharmacotherapy, adherence to prescribed drugs is often hindered by 1 or more barriers. Consequently, the control of diabetes is suboptimal in the United States.

Optimal diabetes control is individualized but most individuals are likely to benefit from lifestyle interventions and pharmacotherapy that aims to control A1C, blood pressure, and lipid levels. Ample literature exists on A1C control and its relationship to microvascular and macrovascular complications. In 2007, Qaseem et al published a guidance statement that built upon other organizations’ guidelines and an evaluation of the strengths and weaknesses of those guidelines. The authors used an accepted appraisal instrument to evaluate the guidelines and, based on the review, developed the following recommendations: 1) “To prevent microvascular complications of diabetes, the goal for glycemic control should be as low as is feasible without undue risk for adverse events or an unacceptable burden on patients. Treatment goals should be based on a discussion of the benefits and harms of specific levels of glycemic control with the patient. A hemoglobin A1C level <7% based on individualized assessment is a reasonable goal for many but not all patients;” and 2) “The goal for hemoglobin A1C level should be based on individualized assessment of risk for complications from diabetes, comorbidity, life expectancy, and patient preferences.” A third recommendation calls for additional research.

Three recent studies (Action to Control Cardiovascular Risk in Diabetes [ACCORD], Action in Diabetes and Vascular Disease: Preteraz and Diamicron MR Controlled Evaluation [ADVANCE], and Veterans Affairs Diabetes Trial [VADT]) have been undertaken to advance understanding of effective A1C target levels by comparing tight glycemic control with standard glycemic control. The ACCORD clinical trial, with 10,251 participants, examined an intensive blood sugar—lowering strategy. The trial ended in 2008 due to safety concerns. A data review found that patients who received intensive treatment to lower blood glucose were at higher risk for death; participants in the intensive blood sugar treatment group were transitioned to the standard treatment strategy.

The ADVANCE trial, with over 11,000 participants worldwide, demonstrated that “intensive glucose control with a gliclazide MR—based treatment regimen in people with type 2 diabetes reduces the combined risk of microvascular and macrovascular events, primarily through reductions in the risk of diabetic nephropathy.

 The ADVANCE data found that compared with standard treatment, intensively lowering A1C levels does not pose a greater risk to patients with type 2 diabetes. The VADT compared a group under intensive therapy (targeting A1C of <7%) with the group under standard therapy (A1C target of 8% to 9%) to assess macrovascular complications. The VADT participants were also treated with drugs and lifestyle therapies to control their blood pressure and blood lipid levels. The study found that while it is difficult to manage the therapy in an older population with long-term diabetes and chronic complications, it is possible to obtain significant improvement in glycemic levels and other risk factors of these individuals. However, the study also found that isolated glycemic control does not have significant effect in reducing cardiovascular events in people with long-standing type 2 diabetes.

It is not surprising that guidelines for A1C control differ slightly.

 The American Diabetes Association (ADA) 2010 clinical practice recommendations state, “Lowering A1C below or around 7% has been shown to reduce microvascular and neuropathic complications of type 1 and type 2 diabetes. Therefore, for microvascular disease prevention, the A1C goal for nonpregnant adults in general is <7%.” The ADA recommendations also note that less stringent A1C goals may be appropriate for patients with a history of severe hypoglycemia, limited life expectancy, advanced microvascular or macrovascular complications, and extensive comorbidities.

 The ADA also supports the use of diagnosing diabetes using A1C, for which the diagnostic criterion is 6.5%.

 The American Association of Clinical Endocrinologists (AACE) “recommends that people with type 2 diabetes reach an A1C goal of 6.5% or less.”

 Moreover, AACE and the American College of Endocrinologists (ACE) “do not endorse A1C criteria for pre-diabetes or for those at risk for diabetes. AACE/ACE support an A1C of 5.5% to 6.4% as a screening test for pre-diabetes if it leads to measurement of fasting glucose or a glucose tolerance test for diagnosis.”

Findings of the ACCORD, ADVANCE, and VADT studies provide a vital link between A1C control, selfmanagement, and medication taking. Clinical practice guidelines indicate the importance of pharmacologic therapy as a component of diabetes management, along with self-management education. In summary, pharmacologic therapy plays a vital role in the management of diabetes and is a key element of the self-management of the disease.

Several factors can impede medication adherence among persons with diabetes, and a link has been shown between poor medication adherence and suboptimal diabetes control.

Community pharmacists are in a prime position to help patients with medication adherence, as they see the patients more often than any other healthcare provider does. However, the current healthcare delivery system hinders optimal patient-centered care. Most community practice pharmacists do not have access to patients’ medical records. They may not even have complete prescription records, if patients filled medications at more than 1 pharmacy. This presents a challenge for pharmacists to provide a thorough medication review, adherence assessment, and optimal therapy management.

Many pharmacists work with people with diabetes and recognize 3 types of impediments to medication adherence:

1. Knowledge deficit (eg, patient lacks knowledge/understanding of the purpose of taking the medication, when to take the medication to get the best therapeutic effect with the fewest adverse effects [AEs], or how to use the medication correctly).

2. Practical (eg, financial constraints, busy schedule, poor health literacy, inability to see vial/syringe due to impaired eyesight).

3. Motivational (eg, cultural, family, and health beliefs).

A medication use systematic review examined the challenges and barriers to taking medication (adherence) for people with diabetes.

 Medication adherence is problematic in diabetes. The symposium participants concurred that few interventions on adherence in diabetes self-management have been rigorously studied, and assessment of medication adherence does not appear to be a standard practice. Diabetes medication adherence rates range from 31% to 87% in retrospective studies and from 53% to 98% in prospective studies.

 An 80% adherence rate translates into missing 1 of every 5 doses of a once-daily medication—or 1 to 2 doses per week.

Factors most frequently reported to hinder diabetes medication adherence are regimen complexity (eg, >1 diabetes medication, need to split tablets, need to mix products), dosing frequency greater than twice daily, remembering doses and refills, depression, and AEs or fear of them.

 Pharmacies may be able to improve medication adherence rates of oral antihyperglycemic agents by using refill reminders and unit-dose packaged medication.

 While more evidence is needed to support specific interventions for medication adherence, diabetes educators are in a key position to promote medication adherence.

Insulin use presents a unique set of challenges. According to an informal survey of diabetes educators in 2005, factors suggested as barriers to using insulin include patient resistance and fear, weight gain, inconvenience, physician resistance, inadequate support, cost, lack of access to medications, and confusion about medication use.

 In a survey of 1267 individuals with diabetes, 28% of people who were not taking insulin indicated an unwillingness to use insulin therapy.

most frequently cited reasons for wanting to avoid insulin therapy included the sense of personal failure (55%), pain of injection (51%), effect of insulin on increasing illness severity (47%), permanence of therapy (45%), restrictiveness (45%), and concern about problematic hypoglycemia (43%).

Integrate taking medication with self-care education.

It is important that people with diabetes develop knowledge and self-management skills related to medication use. “The goal is for the patient to be knowledgeable about each medication, including its action, side effects, efficacy, toxicity, prescribed dosage, appropriate timing and frequency of administration, effect of missed and delayed doses, and instructions for storage, travel and safety.”

 The diabetes care team therefore not only determines which medications a patient with diabetes requires, but also helps the patient understand how the medications work, how and when to take them, and how to problem solve in regard to medication use. Essentially, adherence can be achieved most effectively by integrating medication use into the patient’s overall understanding of the disease and self-management.

 Clinical and behavioral assessments, clinical interventions, and treatment plans for people with diabetes are most effective when they are customized for the needs and situations of the people with diabetes.

All members of the diabetes care team must consider the patient’s lifestyle and then tailor behavior change plans accordingly. It is also essential to consider where the patient is in the life cycle. Individualized plans begin by asking people with diabetes to describe how taking their medication fits into their lifestyle. An important element of this approach is the patient’s involvement in developing the plan, which increases the likelihood of the adherence. For this reason, a didactic approach to medication use should be avoided.

Various cultural, sociological, age-related, and other issues impact a person’s motivation, willingness, and ability to adhere to prescribed diabetes medications. Polonsky et al have found “psychological insulin resistance” to be common among a substantial number of people with diabetes who refuse insulin therapy once it is prescribed.

 In addition to fearing needles, many people with diabetes are fearful of taking insulin because they believe it signals a worsening of their disease and worry about developing a dependency on insulin once they begin therapy. The panelists noted that some providers create or exacerbate psychological insulin resistance by using insulin as a “threat,” indicating it will be needed if other interventions fail to achieve glucose control. Educating people with diabetes is essential to overcome the mind-set of psychological insulin resistance. Primary care providers can work in partnership with diabetes educators to assure that people with diabetes receive self-management education. All providers must convey the same messages to the patient and inform the patient that they are working as a team.

Age influences taking medication, with each stage in life posing a different set of potential barriers and challenges.

 Vision impairments and arthritis can make it difficult for elderly people with diabetes to self-administer insulin. Unique challenges also extend to younger individuals with diabetes. Adolescents often struggle with stigmas at school because of their need to take insulin. In addition, young women influenced by today’s “thin culture” may skip their insulin doses due to a fear of gaining weight. The symposium discussants noted that in families where English is the second language, younger family members are responsible for translating education to older adults with diabetes. Appropriate training and guidance needs to occur so that these younger individuals, some as young as middle-school age, are supported in their roles as translator and cultural advocate. It would therefore be helpful to implement educational interventions that focus on diabetes at schools.

Best practices for addressing barriers to taking medication begin with sound principles in communication.

To help overcome any knowledge deficit that may exist, the clinician must use terms that are comprehensible to people with diabetes, without speaking down to them.

 The use of understandable analogies is an excellent means for communicating technical information. As an example, A1C can be called a “detective” that provides a critical piece of information in the management of diabetes. To help people with diabetes identify strategies for taking their medication, a safe environment in which no judgments will be made about a patient’s behavior or situation is critical. The provider needs to facilitate an honest dialogue, asking the patient to relate any problem he or she foresees in taking the prescribed medication.

There is overlap across the roles of members of the diabetes care team in regard to taking medication.

It is often the diabetes educator who initiates discussion on concerns relating to taking medication. Educators would be better equipped to approach this topic if they understood that medication nonadherence is the norm rather than the exception among persons with diabetes. People with diabetes often wrestle with the effects of comorbidities as well as life challenges that may make them less likely to adhere to their pharmacotherapy. Instead of adhering, many people with diabetes make choices to “trade off” dealing with one challenge (eg, taking medication) for another. The history of healthcare suggests that nonadherence may constitute an adaptive characteristic of humans, suggesting differences in the underlying beliefs between those being treated and those providing the care. Diabetes educators have the competencies to provide individualized and culturally sensitive self-management education that aligns with the individual’s unique belief system; moreover, they can work with community health workers (CHWs) to overcome what might be called “the belief gap.”

As detailed in the Chronic Care Model, community resources should be involved in providing diabetes selfmanagement support. Medical assistants and CHWs can play a valuable role.

 Often these individuals hear about problems a patient is encountering before the provider learns of them; some people with diabetes wish to avoid “looking bad” in the eyes of the provider, but have no such qualms regarding community workers.

Effective and sustainable diabetes education teams are beginning to involve CHWs. As an example, a certified diabetes educator (CDE) serves as the education program supervisor, has the overall responsibility for the self-management education of the person with diabetes, and provides all the clinical self-management teaching. The CHW provides all the nonclinical instruction, serves as a bridge to the community, and adds cultural relevancy. While the “supervisor” reads the patient’s chart, the CHW provides training on community resources that are available to support people with diabetes and helps identify sources of affordable medications. The CHW also reminds participants what they were taught by the educator and provides them opportunities to restate and practice what they have been taught, assisting people with low literacy or language gaps by reading materials to them in their native language.

Tools to screen for medication adherence are emerging.

Participants in the panel explained that many pharmacists ask people with diabetes 3 primary questions about their understanding of the indications for the medications. The questions were developed by the Indian Health Service.

This paper considers opportunities and barriers relating to medication taking and self-management by people with diabetes and related conditions as discussed during an invitational symposium.

September/October 2011

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