Introduction 1 3 4 5 7 8 11 12 14 3 15 17 18 20 21 23 24 29 30 Methods Data sources 31 Study population 32 Outcomes: use of recommended medications after myocardial infarction From all filled prescriptions, we recorded out-of-hospital use of several medications between date of discharge and 120 days after MI admission: aspirin, beta-blockers, statins, and ACE inhibitors or ARBs. We also assessed the total number of distinct medications that patients received among statin, BB, and ACE inhibitor/ARB (minimum 0; maximum 3). Since aspirin was available for a price that was below the amount of the drug copayment (€4.35), it is possible that insurance claims data may lead to under-ascertainment of aspirin use. Thus, we decided to investigate aspirin separately, and only among patients who had their copayment waived based on income grounds. These indigent patients had a clear economic incentive to fill prescriptions for aspirin via the prescription route, thus generating a claim to the sickness fund. Covariates 2 Statistical analysis We plotted the unadjusted proportions of medication use for the overall population as well as by copayment status along with the corresponding 95% confidence intervals (CIs). We then used univariate and multivariate logistic regression to estimate the crude and multivariate adjusted odds of receiving a given study medication. Since none of our outcomes were rare, we were able to create full multivariate models that included all variables regardless of their statistical significance. In large datasets where outcomes are not rare, full multivariate models are superior to parsimonious models, because they provide better control for residual confounding compared to more restricted models. Odds ratios (OR) were presented with their 95% CIs. Additionally, we showed the population distribution of the number of different study drug classes received among statin, BB, and ACE inhibitor/ARB (minimum 0; maximum 3). Multivariate ordinal logistic regression and linear regression were used to model the associations between covariates and the number of drugs received. All analyses were conducted in the full final study population as well as after restriction to new users of each study drug, i.e. patients who had not received the respective study drug in the year prior to admission for MI. We used the SAS for Windows (release 9.2) software for all statistical analyses (The SAS Institute, Cary, NC). Results Study population P 1 1 Table 1 N Variable Count (%) or mean (±SD) Age 68.8 (±13.2)     <50 years 402 (9.8)     50–69 years 1,515 (36.9)     70–89 years 1,225 (29.8)     ≥90 years 963 (23.5) Male gender 2,442 (59.5) Length of stay 10.9 (±5.3) Days of hospitalization in prior year 6.7 (±14.7)     None 2,500 (60.9)     1–7 days 595 (14.5)     8–21 days 612 (14.9)     ≥21 days 398 (9.7) Copayment waived 654 (15.9%) Previous medication use     Alpha blocker 243 (5.9)     ACE-inhibitor or ARB 1,853 (45.1)     Beta-blocker 1,454 (35.4)     Calcium channel blocker 809 (19.7)     Other antihypertensive 734 (18.0)     Diuretic 927 (22.6)     Nitrate 1,032 (25.1)     Digitalis 347 (8.5)     Acetylsalicylic acid 1,169 (28.5)     Clopidogrel or Ticlopidine 385 (9.4)     Vitamin K-antagonist 249 (6.1)     Statin 1,043 (25.4)     Fibrate 116 (2.8)     Oral hypoglycemic  620 (15.1)     Insulin 265 (6.5)     Uric acid lowering drug 559 (13.6)     Pain medication 1,934 (47.1)     Gastroprotective drug 1,584 (38.6)     Asthma/COPD 610 (14.9)     Corticosteroid 379 (9.2)      Benzodiazepine or anxiolytic 491 (12.0)     Antidepressant 623 (15.2)     Antipsychotics 190 (4.6) Secondary prevention after myocardial infarction 1 P P P Fig. 1 Proportions of medication use after myocardial infarction  P P Independent predictors of study medication use 2 3 4 P 2 3 3 4 Table 2 Independent determinants of ACE-inhibitor or ARB use Variable N N OR 95% CI OR 95% CI Age <50 – Referent – Referent 50–69 1.19 0.96–1.49 1.23 0.96–1.58 70–89 1.48 1.19–1.85 1.54 1.19–2.00 ≥90 0.73 0.59–0.90 0.79 0.60–1.03 Male gender 1.07 0.91–1.25 1.19 0.98–1.44 Length of stay 1.02 1.00–1.03 1.03 1.01–1.05 Hospital days* 0 – Referent – Referent 1–7 0.68 0.56–0.84 0.62 0.49–0.80 8–21 0.79 0.63–0.99 0.68 0.51–0.91 >21 0.51 0.39–0.68 0.53 0.35–0.79 Copayment waived 1.35 1.10–1.67 1.34 1.03–1.74 Alpha-blocker 1.07 0.75–1.53 1.27 0.73–2.20 ACE-inhibitor or ARB 5.67 4.74–6.78 – – Beta-blocker 1.12 0.94–1.33 1.16 0.93–1.45 Calcium channel-blocker 1.35 1.10–1.66 1.34 1.01–1.79 Other anti-hypertensive agents 0.99 0.80–1.21 1.12 0.85–1.47 Diuretic 0.85 0.68–1.05 0.87 0.65–1.18 Nitrate 0.88 0.72–1.07 0.82 0.63–1.08 Digitalis 1.15 0.84–1.57 1.04 0.65–1.65 Aspirin 0.89 0.74–1.07 0.91 0.70–1.18 Clopidogrel 0.90 0.68–1.20 0.73 0.46–1.15 Vitamin K-antagonist 0.99 0.70–1.41 1.10 0.65–1.87 Statin 1.12 0.92–1.38 0.84 0.63–1.11 Fibrate 1.21 0.76–1.93 1.00 0.56–1.77 Oral antidiabetic 1.26 1.00–1.58 1.06 0.79–1.44 Insulin 1.02 0.73–1.44 1.20 0.68–2.10 Asthma/COPD 1.07 0.86–1.34 1.10 0.83–1.47 Benzodiazepines/anxiolytics 1.06 0.83–1.36 1.16 0.83–1.62 Antidepressants 0.87 0.70–1.09 0.85 0.64–1.13 Antipsychotics 0.64 0.45–0.91 0.65 0.41–1.04 P Table 3 Independent determinants of beta-blocker use Variable N N OR 95% CI OR 95% CI Age  <50 – Referent – Referent 50–69 1.25 0.98–1.60 1.21 0.93–1.59 70–89 1.05 0.83–1.33 1.14 0.87–1.47 ≥90 0.62 0.51–0.76 0.54 0.43–0.69 Male gender 1.14 0.97–1.35 1.19 0.98–1.43 Length of stay 1.00 0.98–1.01 1.00 0.98–1.01 Hospital days * 0 – Referent – Referent 1–7 0.92 0.74–1.15 0.85 0.66–1.08 8–21 0.77 0.61–0.96 0.78 0.60–1.02 >21 0.57 0.44–0.75 0.61 0.43–0.84 Copayment waived 1.09 0.89–1.35 1.19 0.93–1.53 Alpha-blocker 1.54 1.07–2.20 1.73 1.12–2.67 ACE-inhibitor or ARB 1.22 1.02–1.45 1.16 0.94–1.41 Beta-blocker 4.36 3.55–5.35 – – Calcium channel-blocker 1.29 1.05–1.59 1.49 1.16–1.90 Other anti-hypertensive agents 0.83 0.68–1.01 0.87 0.69–1.10 Diuretic 0.80 0.65–0.98 0.77 0.60–0.99 Nitrate 1.03 0.84–1.26 1.04 0.81–1.33 Digitalis 0.79 0.60–1.04 0.68 0.48–0.96 Aspirin 0.96 0.79–1.16 0.88 0.70–1.12 Clopidogrel 0.79 0.59–1.07 0.65 0.43–0.97 Vitamin K-antagonist 0.67 0.49–0.93 0.44 0.29–0.66 Statin 0.94 0.76–1.16 0.85 0.67–1.10 Fibrate 1.14 0.70–1.86 1.21 0.65–2.25 Oral antidiabetic 1.06 0.85–1.32 1.07 0.82–1.39 Insulin 0.72 0.53–0.98 0.78 0.52–1.16 Asthma/COPD 0.67 0.55–0.83 0.63 0.49–0.80 Benzodiazepines/anxiolytics 1.33 1.04–1.71 1.27 0.94–1.72 Antidepressants 0.88 0.71–1.09 0.96 0.74–1.24 Antipsychotics 0.71 0.51–1.00 0.74 0.50–1.09 P Table 4 Independent determinants of statin use Variable N N OR 95% CI OR 95% CI Age  <50 – Referent – Referent 50–69 1.38 1.09–1.76 1.40 1.09–1.81 70–89 1.08 0.86–1.36 1.09 0.85–1.39 ≥90 0.39 0.32–0.47 0.37 0.30–0.46 Male gender 1.10 0.94–1.29 1.13 0.95–1.35 Length of stay 0.98 0.97–0.99 0.99 0.97–1.00 Hospital days* 0 – Referent – Referent 1–7 0.88 0.71–1.09 0.82 0.66–1.04 8–21 0.68 0.55–0.85 0.68 0.53–0.87 >21 0.48 0.37–0.63 0.47 0.34–0.65 Copayment waived 1.09 0.89–1.34 1.07 0.85–1.34 Alpha-blocker 0.89 0.65–1.22 1.04 0.72–1.51 ACE-inhibitor or ARB 0.98 0.82–1.16 1.04 0.86–1.25 Beta-blocker 1.08 0.91–1.29 1.07 0.88–1.30 Calcium channel-blocker 1.01 0.83–1.23 0.98 0.79–1.23 Other anti-hypertensive agents 0.97 0.80–1.18 0.97 0.78–1.21 Diuretic 0.82 0.67–1.00 0.79 0.63–1.00 Nitrate 0.94 0.77–1.14 0.96 0.77–1.21 Digitalis 0.60 0.46–0.80 0.51 0.37–0.72 Aspirin 0.85 0.71–1.03 0.74 0.60–0.92 Clopidogrel 0.70 0.51–0.94 0.61 0.40–0.94 Vitamin K-antagonist 0.62 0.45–0.85 0.52 0.35–0.78 Statin 6.39 5.03–8.11 – – Fibrate 2.24 1.36–3.70 2.31 1.35–3.97 Oral antidiabetic 0.95 0.77–1.18 0.98 0.77–1.26 Insulin 0.76 0.56–1.04 0.71 0.48–1.05 Asthma/COPD 0.87 0.71–1.07 0.84 0.66–1.06 Benzodiazepines/anxiolytics 0.89 0.70–1.12 0.94 0.72–1.22 Antidepressants 1.13 0.91–1.40 1.08 0.85–1.39 Antipsychotics 0.48 0.34–0.68 0.53 0.36–0.79 P 2 4 Discussion In a large population-based study of patients who experienced an acute MI in Austria, we found that ambulatory use of several recommended medications after discharge was suboptimal. Within 120 days after their MI, only 74% patients received a BB, 67% a statin, and 67% filled a prescription for an ACE inhibitor or ARB. Only 41% of patients received all three interventions, while 25% of patients received only one of these beneficial drugs or even none at all. Underuse of these medications is unfortunate from both a patient’s and a societal perspective: while optimal secondary prevention including these drugs prolongs the expected lifespan of a patient after MI, use of these interventions constitutes an attractive allocation of scarce economic resources. Thus, considerable room for improvement is present in the care of patients after MI in Austria, and interventions ought to be targeted towards increasing the prescribing and use of these medications. 27 29 28 28 33 24 34 26 29 24 35 36 The number of hospital days in the year prior to MI was a strong negative predictor of medication use for all classes. This might reflect greater comorbidity or frailty in these patients, which both have been associated with lower use of and persistence with preventive medications. Similarly, patients receiving antipsychotic drugs had a lower likelihood to receive the study medications, likely indicating treatment bias regarding the mentally diseased. Beta-blocker use was significantly lower among patients who received any drugs for inhalation that are indicated in asthma or COPD, a plausible pattern, which may reflect presence of a relative contraindication or intolerance by the patient. Indeed, among patients without previous use of such asthma or COPD drugs (N = 3,495), BB use after MI was 75.4% (rather than 74.0% in the overall population), an only slightly higher proportion with respect to the goal of appropriately treating all patients free from contraindications. Statins were less likely to be used in patients who had previously used diuretics, digitalis, or coumadin, possibly indicating congestive heart failure or atrial fibrillation and thus, worse prognosis. 37 38 39 37 38 40 In summary, we provide evidence for underuse of several recommended medications after MI as recently as 2004 in the Austrian healthcare system. Our observations are in line with findings from other European and North American healthcare systems, despite the differences in data collection and time period studied. Educational efforts need to be directed at both physicians and patients, and the implementation of quality indicators should be considered. Maximizing secondary prevention after MI is highly desirable from an individual patient and the societal perspective.