Chris L. Bryson

Medication Adherence Its Importance in Cardiovascular Outcomes

Medication adherence usually refers to whether patients take their medications as prescribed (eg, twice daily), as well as whether they continue to take a prescribed medication. Medication nonadherence is a growing concern to clinicians, healthcare systems, and other stakeholders (eg, payers) because of mounting evidence that it is prevalent and associated with adverse outcomes and higher costs of care. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. The goals of the present report are to address (1) different methods of measuring adherence, (2) the prevalence of medication nonadherence, (3) the association between nonadherence and outcomes, (4) the reasons for nonadherence, and finally, (5) interventions to improve medication adherence.

Obesity and COPD: associated symptoms, health-related quality of life, and medication use.

Background: There is little data about the combined effects of COPD and obesity. We compared dyspnea, health-related quality of life (HRQoL), exacerbations, and inhaled medication use among patients who are overweight and obese to those of normal weight with COPD. Methods: We performed secondary data analysis on 364 Veterans with COPD. We categorized subjects by body mass index (BMI). We assessed dyspnea using the Medical Research Council (MRC) dyspnea scale and HRQoL using the St. Georges Respiratory Questionnaire. We identified treatment for an exacerbation and inhaled medication use in the past year. We used multiple logistic and linear regression models as appropriate, with adjustment for age, COPD severity, smoking status, and co-morbidities. Results: The majority of our population was male (n = 355, 98%) and either overweight (n = 115, 32%) or obese (n = 138, 38%). Obese and overweight subjects had better lung function (obese: mean FEV1 55.4% ±19.9% predicted, overweight: mean FEV1 50.0% ±20.4% predicted) than normal weight subjects (mean FEV1 44.2% ±19.4% predicted), yet obese subjects reported increased dyspnea [adjusted OR of MRC score ≥2 = 4.91 (95% CI 1.80, 13.39], poorer HRQoL, and were prescribed more inhaled medications than normal weight subjects. There was no difference in any outcome between overweight and normal weight patients. Conclusions: Despite having less severe lung disease, obese patients reported increased dyspnea and poorer HRQoL than normal weight patients. The greater number of inhaled medications prescribed for obese patients may represent overuse. Obese patients with COPD likely need alternative strategies for symptom control in addition to those currently recommended.

Alcohol Screening Scores and Medication Nonadherence

Context Is alcohol misuse associated with medication nonadherence? Contribution This study of primary care patients attending 7 Veterans Affairs clinics found a graded, linear decrease in adherence to statins and hypertension medications with increasing levels of alcohol misuse. Caution Alcohol misuse was measured with a brief screening questionnaire that was mailed to patients. Adherence was measured by pharmacy refills. Implication Alcohol misuse may be associated with increased risk for medication nonadherence. The Editors Daily medications are the cornerstone of chronic disease management. Medications to treat hypertension, hyperlipidemia, and diabetespotent risk factors for cardiovascular diseaseare common and are often prescribed for asymptomatic patients to prevent future disease. However, nonadherence to medications is common (1) and is associated with poor outcomes, increased health care costs (2, 3), and death (4). Many studies have examined patient characteristics associated with nonadherence, but most identified risk factors for nonadherence are not modifiable. Alcohol misuse is common, has been associated with medication nonadherence, and is modifiable (57). However, research on alcohol misuse and medication adherence has been largely limited to patients with HIV (811) and a few studies of diabetes (3, 12, 13). One recent study found both a temporal and a doseresponse relationship between alcohol consumption and medication adherence (8) but used a lengthy interview measure of alcohol use that is not practical for busy clinical settings. Therefore, it remains unclear whether brief validated alcohol screening questionnaires used in clinical practice could identify patients at risk for nonadherence due to alcohol misuse. We examined whether primary care outpatient scores on a brief, scaled, alcohol screening questionnairethe Alcohol Use Disorder Identification TestConsumption (AUDIT-C)were associated with medication nonadherence. Specifically, we evaluated the association between increasing scores on the AUDIT-C (score range, 0 to 12) and adherence to oral medications commonly used for hypertension, hyperlipidemia, and diabetes. We hypothesized that higher AUDIT-C scores would be associated with an increased risk for medication nonadherence. Methods Participants and Setting We used data collected from the Ambulatory Care Quality Improvement Project (ACQUIP) cohort in this study (14). In brief, ACQUIP enrolled 36821 active patients from the general internal medicine clinics of 7 Veterans Affairs (VA) medical centers nationwide, including facilities in Seattle, Washington; West Los Angeles, California; Birmingham, Alabama; Little Rock, Arkansas; San Francisco, California; Richmond, Virginia; and White River Junction, Vermont. The ACQUIP initially surveyed all VA sites and selected these 7 sites (from 60 respondents) on the basis of geographic diversity; well-established systems for assigning patients to firms; and an experienced, interested investigator to lead the study. The ACQUIP was a randomized trial testing the effect of an audit and feedback quality-improvement intervention; there was no detectable effect of the intervention on primary outcomes, including alcohol misuse (14). Patients were eligible for ACQUIP if they had at least 1 visit to a primary care facility in the past year and had a primary care provider. The ACQUIP sent questionnaires (ACQUIP Health Checklist) at enrollment (1997 to 2000), and the institutional review board considered participant response to the survey to be consent for study participation. The survey assessed demographic characteristics, alcohol misuse, other health behaviors, and psychiatric and medical conditions. Patients who did not respond were mailed up to 3 additional surveys. The date the survey was received by the study team was considered the index date for all participants. Survey data were linked to electronic records, including pharmacy, diagnosis, and death records. Participants who died during follow-up were excluded. The institutional review board at each participating VA site approved ACQUIP, and the University of Washington Division of Human Subjects approved the secondary analyses that we present in this article. Pharmacy Data and Medication Cohorts Pharmacy data were retrieved electronically as part of the ACQUIP protocol from December 1995 to May 2000. Each prescription filled generated 1 record containing the drug name, the quantity and date dispensed, and the number of days supplied. These data are nearly identical to national VA pharmacy data (15), which have been used in several studies of medication adherence and pharmacoepidemiology (16, 17). We identified 3 nonexclusive cohorts of patients with increasing medication regimen complexity: a statin cohort, consisting of all patients prescribed a statin medication for hypercholesterolemia; an oral hypoglycemic cohort, with all patients who were prescribed either a sulfonylurea or metformin for blood glucose control; and a hypertension treatment cohort, consisting of all patients with self-reported hypertension who were prescribed at least 1 of 6 classes of antihypertensive drugs (-blockers, angiotensin-converting enzyme inhibitors, -blockers, calcium-channel blockers, thiazide-type diuretics, or nonthiazide diuretics) and a group consisting of other antihypertension medications usually used as fourth- or fifth-line agents (such as hydralazine). We considered patients medication users and included them in 1 of the cohorts if they received both 1 or more fills of the drug class within 2 years before the index date and 1 or more fills in the year after the index date. We used these criteria to minimize potential dropout bias by ensuring that patients were still engaged in care and obtaining medications from the VA. We excluded glitazones and angiotensin-receptor blockers from analyses because few patients were prescribed these medications, which were on a restricted formulary at the time of the study. In addition, we excluded patients in the oral hypoglycemic cohort if they had an active prescription for insulin other than neutral protamine Hagedorn, in order to remove patients who transitioned from oral medication to insulin during the study. Alcohol Misuse and AUDIT-C We assessed alcohol misuse with the AUDIT-C from the ACQUIP Health Checklist. The AUDIT-C assesses frequency and typical quantity of drinking during the past year, as well as the frequency of heavy episodic drinking (6 drinks per occasion) by using 3 questions (18). Each of the 3 questions is scored 0 to 4, for a total combined score of 0 to 12. The AUDIT-C is reliable (19) and has been validated as a screening test for the spectrum of alcohol misuse, including risky drinking and alcohol-use disorders on the basis of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria (18, 20, 21). A score of 4 or more is considered positive for alcohol misuse in male VA patients, but the AUDIT-C score has also been shown to be a scaled measure of risk for alcohol-related symptoms (22) and medical complications often associated with alcohol misuse (2326). To provide adequate precision in estimates and allow comparison with previous analyses (23, 24), we grouped AUDIT-C scores into 5 categories: nondrinkers (score, 0); low-level alcohol use (score range, 1 to 3); and mild (score range, 4 to 5), moderate (score range, 6 to 7), and severe (score range, 8 to 12) alcohol misuse. Medication Adherence We created an individual measure of refill adherence, which was previously validated within the VA and ACQUIP, for each patient and medication class. This measure is similar to a medicationpossession ratio, and it accounts for overstocking and medication gaps, correlates better with physiologic outcomes when compared with previous measures, and is described in detail elsewhere (27). From this measure, we derived a proportion of days covered that reflected the number of days during the observation period that medication was available (17). We considered all medications within a medication type (statin, oral hypoglycemics, and antihypertensive medications) to be equivalent for purposes of adherence. We calculated adherence separately for 2 different periods: 90 days and 1 year starting from the index date. We assessed at 1 year because it is a traditional measurement of adherence (16, 17). We also assessed at 90 days because refill adherence for this period has been correlated with outcomes (27). On the basis of previous medication adherence literature (16, 17), we considered patients in all medication cohorts to be adherent if they had medication available for at least 80% of the observation period. In other words, for the 90-day observation period, nonadherent patients would not have medication available for at least 18 days; for the 1 year-period, they would be without medication for at least 73 days. When more than 1 medication was used (for example, for diabetes or hypertension), the proportions of days covered were averaged, and we considered patients to be adherent if they had at least 80% of the drug regimen for diabetes or hypertension available for the observation period. A person who met the definition of a user for 2 drug classes but only maintained complete fills of 1 drug with no fills of the other drug therefore would have an average adherence of 0.5 and would be considered nonadherent to the overall regimen. Covariates Race was based on a combination of self-report from the ACQUIP Health Checklist and the electronic record. We determined sex, education, and marital status from the ACQUIP Health Checklist. We calculated a drug count from the number of oral drugs that patients obtained during the year before the index date to adjust for total medication regimen complexity. We classified smoking status as current, former, or never. We assessed depression with the Mental Health Inventory (score range, 5 to 30); scores gre

A refill adherence algorithm for multiple short intervals to estimate refill compliance (ReComp)

Background: There are many measures of refill adherence available, but few have been designed or validated for use with repeated measures designs and short observation periods. Objective: To design a refill-based adherence algorithm suitable for short observation periods, and compare it to 2 reference measures. Methods: A single composite algorithm incorporating information on both medication gaps and oversupply was created. Electronic Veterans Affairs pharmacy data, clinical data, and laboratory data from routine clinical care were used to compare the new measure, ReComp, with standard reference measures of medication gaps (MEDOUT) and adherence or oversupply (MEDSUM) in 3 different repeated measures medication adherence-response analyses. These analyses examined the change in low density lipoprotein (LDL) with simvastatin use, blood pressure with antihypertensive use, and heart rate with β-blocker use for 30- and 90-day intervals. Measures were compared by regression based correlations (R2 values) and graphical comparisons of average medication adherence-response curves. Results: In each analysis, ReComp yielded a significantly higher R2 value and more expected adherence-response curve regardless of the length of the observation interval. For the 30-day intervals, the highest correlations were observed in the LDL-simvastatin analysis (ReComp R2 = 0.231; [95% CI, 0.222–0.239]; MEDSUM R2 = 0.054; [95% CI, 0.049–0.059]; MEDOUT R2 = 0.053; [95% CI, 0.048–0.058]). Conclusions: ReComp is better suited to shorter observation intervals with repeated measures than previously used measures.

Anginal symptoms consistently predict total mortality among outpatients with coronary artery disease

BACKGROUND Age, race, education, and diabetes have been associated with differences in anginal symptoms, treatments, and outcomes among outpatients with coronary artery disease (CAD), but there is little data on whether such characteristics affect relationships between anginal symptoms and mortality. METHODS Using a prospective cohort design, we examined associations of anginal symptoms, as assessed by the Seattle Angina Questionnaire, with total mortality among 8908 outpatients with CAD to investigate whether this relationship is influenced by patient demographic or clinical characteristics. Potential effect modification was primarily assessed for age, race, education, and diabetes, and secondarily assessed for smoking, prevalent congestive heart failure (CHF), myocardial infarction, and coronary revascularization. RESULTS Over 2 years mean follow-up, there were 896 deaths. After adjustment for potential confounders, persons reporting greater physical limitation due to angina had higher mortality: 27% higher with mild limitation (hazard ratio [HR] 1.27, 95% CI 0.98-1.64), 61% higher with moderate limitation (HR 1.61, 95% CI 1.27-2.05), and 2.5-fold higher with the greatest limitation (HR 2.55, 95% CI 1.97-3.30), compared with little or no limitation (P for trend <.001). Anginal instability was also independently predictive of mortality. There was little evidence that these relationships varied by age, race, education, diabetes, smoking, or presence of CHF, prior myocardial infarction, or prior coronary revascularization (P for each interaction >.28). Anginal symptoms predicted higher mortality risk comparable to a decade of age difference, presence of diabetes, or presence of CHF. CONCLUSIONS Among outpatients with CAD, self-reported anginal symptoms consistently predict mortality irrespective of differences in age, race, education, or clinical comorbidities.

Use of Outpatient Care in Veterans Health Administration and Medicare among Veterans Receiving Primary Care in Community-Based and Hospital Outpatient Clinics

OBJECTIVE To examine differences in use of Veterans Health Administration (VA) and Medicare outpatient services by VA primary care patients. DATA SOURCES/STUDY SETTING VA administrative and Medicare claims data from 2001 to 2004. STUDY DESIGN Retrospective cohort study of outpatient service use by 8,964 community-based and 6,556 hospital-based VA primary care patients. PRINCIPAL FINDINGS A significant proportion of VA patients used Medicare-reimbursed primary care (>30 percent) and specialty care (>60 percent), but not mental health care (3-4 percent). Community-based patients had 17 percent fewer VA primary care visits (p<.001), 9 percent more Medicare-reimbursed visits (p<.001), and 6 percent fewer total visits (p<.05) than hospital-based patients. Community-based patients had 22 percent fewer VA specialty care visits (p<.0001) and 21 percent more Medicare-reimbursed specialty care visits (p<.0001) than hospital-based patients, but no difference in total visits (p=.80). CONCLUSIONS Medicare-eligible VA primary care patients followed over 4 consecutive years used significant primary care and specialty care outside of VA. Community-based patients offset decreased VA use with increased service use paid by Medicare, suggesting that increasing access to VA primary care via community clinics may fragment veteran care in unintended ways. Coordination of care between VA and non-VA providers and health care systems is essential to improve the quality and continuity of care.

Alcohol Screening Results in Elderly Male Veterans: Association with Health Status and Mortality

Objectives: To evaluate the association between alcohol screening results and health status or mortality in elderly patients.

The Association of Inhaled Corticosteroid Use with Serum Glucose Concentration in a Large Cohort

BACKGROUND Inhaled corticosteroids (ICSs) are widely used in the treatment of obstructive lung disease. ICSs have been shown to be systemically absorbed. The association between ICS and serum glucose concentration is unknown. METHODS To explore the association of ICS dosing with serum glucose concentration, we used a prospective cohort study of US veterans enrolled in 7 primary care clinics between December 1996 and May 2001 with 1 or more glucose measurements while at least 80% adherent to ICS dosing. The association between ICS dose from pharmacy records standardized to daily triamcinolone equivalents and serum glucose concentration was examined with generalized estimating equations controlling for confounders, including systemic corticosteroid use. RESULTS Of the 1698 subjects who met inclusion criteria, 19% had self-reported diabetes. The mean daily dose of ICS in triamcinolone equivalents was 621 microg (standard deviation 555) and 610 microg (standard deviation 553) for subjects with and without diabetes, respectively. After controlling for systemic corticosteroid use and other potential confounders, no association between ICS and serum glucose was found for subjects without diabetes. However, among subjects with self-reported diabetes, every additional 100 microg of ICS dose was associated with an increased glucose concentration of 1.82 mg/dL (P value .007; 95% confidence interval [CI], 0.49-3.15). Subjects prescribed antiglycemic medications had an increase in serum glucose of 2.65 mg/dL (P value .003; 95% CI, 0.88-4.43) for every additional 100 microg ICS dose. CONCLUSION Among diabetic patients, ICS use is associated with an increased serum glucose concentration in a dose-response manner.

Appropriateness of Percutaneous Coronary Interventions in Washington State

Background— In anticipation of applying Appropriate Use Criteria for percutaneous coronary intervention (PCI) quality improvement, we determined the prevalence of appropriate, uncertain, and inappropriate PCIs stratified by indication for all PCIs performed in the state of Washington. Methods and Results— Within the Clinical Outcomes Assessment Program, we assigned appropriateness ratings to all PCIs performed in 2010 in accordance with published Appropriate Use Criteria. Of 13 291 PCIs, we successfully mapped the clinical scenario to the Appropriate Use Criteria in 9924 (75%) cases. Of the 3367 PCIs not classified, common failures to map to the criteria included nonacute PCI without prior noninvasive stress results (n = 1906; 57%) and unstable angina without high-risk features (n = 902; 27%). Of mapped PCIs, 8010 (71%) were for acute indications, with 7887 (98%) rated as appropriate, 39 (<1%) as uncertain, and 84 (1%) as inappropriate. Of 1914 mapped nonacute indications, 847 (44%) were rated as appropriate, 748 (39%) as uncertain, and 319 (17%) as inappropriate. Assuming results for noninvasive stress tests when data were missing, in the best-case scenario, 319 (8%) of nonacute PCIs were classified as inappropriate compared with 1459 (38%) in the worst-case scenario. Variation in inappropriate PCIs by facility was greatest for mapped nonacute indications (median = 14%; 25th to 75th percentiles = 9% to 24%) and nonacute indications with missing data precluding appropriateness classification (median = 54%; 25th to 75th percentiles = 35% to 66%). Conclusions— In a complete cohort of PCIs performed in Washington state, 1% of PCIs for acute indications and 17% of PCIs for nonacute indications were classified as inappropriate. Missing data on noninvasive stress tests present a challenge in the application of the criteria for quality improvement.

Adherence to Long-Acting Inhaled Therapies among Patients with Chronic Obstructive Pulmonary Disease (COPD)

Abstract Background: Long-acting inhaled medications are an important component of the treatment of patients with chronic obstructive pulmonary disease (COPD), yet few studies have examined the determinants of medication adherence among this patient population. Objective: We sought to identify factors associated with adherence to long-acting beta-agonists (LABA) and inhaled corticosteroids (ICS) among patients with COPD. Methods: We performed secondary analysis of baseline data collected in a randomized trial of 376 Veterans with spirometrically confirmed COPD. We used electronic pharmacy records to assess adherence, defined as a medication possession ratio of ≥0.80. We investigated the following exposures: patient characteristics, disease severity, medication regimen complexity, health behaviors, confidence in self-management, and perceptions of provider skill. We performed multivariable logistic regression, clustered by provider, to estimate associations. Results: Of the 167 patients prescribed LABA, 54% (n = 90) were adherent to therapy while only 40% (n = 74) of 184 the patients prescribed ICS were adherent. Higher adherence to LABA and ICS was associated with patient perception of their provider as being an “expert” in diagnosing and managing lung disease [For LABA: OR = 21.70 (95% CI 6.79, 69.37); For ICS OR = 7.93 (95% CI 1.71, 36.67)]. Factors associated with adherence to LABA, but not ICS, included: age, education, race, COPD severity, smoking status, and confidence in self-management. Conclusions: Adherence to long-acting inhaled medications among patients with COPD is poor, and determinants of adherence likely differ by medication class. Patient perception of clinician expertise in lung disease was the factor most highly associated with adherence to long-acting therapies.