Abstract
Background
Patients prescribed opioids often have chronic conditions that increase their risk of adverse cardiovascular outcomes, but little is known about the primary preventive cardiovascular care these patients receive.
Methods and Results
We analyzed data from the 2014 to 2016 National Ambulatory Medical Care Survey to evaluate physicians’ provision of primary preventive cardiovascular care to adults with and without opioid prescriptions. We included all visits made by adults 40 to 79 years old with at least 1 cardiovascular risk factor but no existing atherosclerotic cardiovascular disease. There were ≈32 million visits by adults who were prescribed opioids and ≈167 million visits by adults not prescribed opioids on an annual basis. The prevalence of primary preventive care was modest in patients with versus those without opioid prescriptions, respectively: (1) statins for patients with dyslipidemia (52.1% versus 46.3%); (2) statins for patients with diabetes mellitus (49.1% versus 37.9%); (3) antihypertensive agents for patients with hypertension (76.5% versus 65.8%); (4) diet/exercise counseling (40.5% versus 45.3%); and (5) smoking cessation therapy (25.3% versus 19.3%). In multivariate analyses, opioid use was associated with higher rates of statin therapy in patients with diabetes mellitus (adjusted relative risk [aRR], 1.25; 95% CI, 1.06–1.47; P=0.007) and antihypertensive medication in patients with hypertension (aRR 1.14; 95% CI, 1.06–1.22; P<0.001).
Conclusions
Overall adherence to guideline‐recommended primary preventive cardiovascular care during ambulatory visits was suboptimal. Findings show that patients prescribed opioids versus those without opioid prescriptions were more likely to receive statin therapy and antihypertensive agents in the setting of diabetes mellitus and hypertension, respectively. Ongoing efforts to bridge these gaps in primary prevention of cardiovascular disease remain a high priority.
Keywords: antihypertensives, cardiovascular outcomes, opioids, primary prevention, statins
Subject Categories: Quality and Outcomes, Primary Prevention, Cardiovascular Disease
Non‐standard Abbreviations and Acronyms
- ASCVD
atherosclerotic cardiovascular disease
- NAMCS
National Ambulatory Medical Care Survey
- NHAMCS
National Hospital Ambulatory Medical Care Survey
Clinical Perspective
What Is New?
In this retrospective study using the National Ambulatory Medical Care Survey database, the most underutilized primary preventive strategies were provision of statin therapy for patients with diabetes mellitus and provision of smoking cessation therapy.
Patients with opioid use compared with those without opioid use had higher rates of tobacco use and were more likely to receive primary preventive cardiovascular medications but not preventive lifestyle counseling.
What Are the Clinical Implications?
Greater clinician awareness of the overall underuse of primary preventive cardiovascular care among patients with opioid use may increase interest to more globally discuss primary preventive practices, not just in terms of the risks associated with initiating or continuing opioid therapy.
Patients prescribed opioids often have concurrent chronic conditions that increase their risk of adverse cardiovascular outcomes.1, 2 Several studies have also demonstrated that opioid use is independently associated with cardiovascular risk and death.3, 4, 5, 6, 7, 8, 9 One study of Medicare beneficiaries initiating therapy with analgesics showed that patients treated with opioids had higher rates of cardiovascular events compared with patients treated with nonselective nonsteroidal anti‐inflammatory drugs.6 Another study of Medicaid patients in Tennessee with chronic noncancer pain prescribed long‐acting opioids or alternative medications showed that opioids were associated with an increased risk of cardiovascular death.5 Other studies presented similar findings.4, 8
However, little is known about the rates of primary preventive cardiovascular care provided to patients prescribed opioids during ambulatory visits—and, to the best of our knowledge, no studies have examined this issue. Due to growing public and health policy concerns about opioid misuse, physicians’ efforts to mitigate opioid‐related risks and time constraints during ambulatory medical visits may be adversely affecting provision of optimal primary preventive cardiovascular care to patients using opioids. Although research on the effects of visit complexity on physician decision making has yielded mixed results,2, 10, 11, 12 the importance of examining this relationship is magnified due to the association of opioid use with adverse cardiovascular outcomes. In light of these risks, the aim of the present study was to compare physicians’ provision of guideline‐recommended care for primary prevention of cardiovascular disease among adults with and without opioid prescriptions.
Methods
The data and study materials are publicly available, and the analytic methods can be made available to other researchers upon request by contacting the corresponding author, for purposes of reproducing the results or replicating the procedure. The full data set is available at the National Ambulatory Medical Care Survey/National Hospital Ambulatory Medical Care Survey website (https://www.cdc.gov/nchs/ahcd/index.htm).
Data
We analyzed nationally representative, publicly available data from the National Ambulatory Medical Care Survey (NAMCS) for the years 2014 to 2016. The National Center for Health Statistics conducts the NAMCS in the United States on an annual basis. The survey is administered to non–federally employed, office‐based physicians, and it focuses on visits made to physician offices. Participating physicians are randomly assigned to a 1‐week reporting period in which data from ≈30 random patient visits are collected. Data are recorded in standardized electronic record formats and capture patient, provider, and visit characteristics.13 Data on community health centers (part of the NAMCS) and outpatient hospital departments (part of the National Hospital Ambulatory Medical Care Survey [NHAMCS]) were unavailable from 2014 to 2016. However, the majority of ambulatory care is performed in office‐based visits and captured by the NAMCS. (In recent years, 91% of visits occurred in NAMCS office visits rather than in NHAMCS hospital outpatient departments and, of NAMCS visits, 98% occurred outside of community health centers.14) 14
Physicians and staff members recorded up to 5 reasons for each visit, 5 diagnoses for each visit in addition to checkboxes that captured other major comorbid diagnoses, up to 30 medications, and health services provided during the visit. Diagnoses were coded by National Center for Health Statistics staff using the International Classification of Diseases, Ninth Revision―Clinical Modification (ICD‐9‐CM)15 Health services reported included diagnostic testing, procedures, and health education/counseling. Our study was exempt from institutional review board review.
Study Population
We included all office visits made by adults 40 to 79 years old with at least 1 cardiovascular risk factor (primary prevention), and excluded those with established atherosclerotic cardiovascular disease (ASCVD).13, 16 Cardiovascular risk factors were identified using visit diagnoses and patients’ chief complaints and included hypertension, diabetes mellitus, dyslipidemia, obesity/overweight, and cigarette smoking. Existing ASCVD included coronary artery disease, stroke, carotid stenosis, peripheral vascular disease, and abdominal aortic aneurysm.
We identified visits of patients prescribed opioids using Multum Lexicon drug codes and National Center for Health Statistics generic codes (Table S1), applying methods similar to those used in our earlier work.13, 16 We limited the sample to visits with physicians who usually provide preventive cardiovascular care, including primary care physicians (general and family medicine physicians and internists) and cardiologists. General and family medicine physicians and internists are also among the most frequent prescribers of opioids, as compared with other medical specialties.17
Primary Measures
We assessed 5 elements of primary cardiovascular prevention based on guidelines issued by the American Heart Association/American College of Cardiology, American Diabetes Association, and the US Preventive Services Task Force.18, 19, 20, 21, 22 These included: (1) statin therapy for adults with dyslipidemia; (2) statin therapy for adults with diabetes mellitus; (3) antihypertensive therapy for adults with hypertension; (4) diet, exercise, and weight‐loss counseling; and (5) smoking cessation counseling and/or therapy. Multum Lexicon drug codes and National Center for Health Statistics generic codes for preventive cardiovascular medications are listed in Table S2.
Other Measures
To further assess the association of opioid prescriptions with primary preventive cardiovascular care, we extracted information on patient age, sex, race/ethnicity (non‐Hispanic white, non‐Hispanic black, Hispanic, or other), insurance status (private, Medicare, Medicaid, self‐pay or no charge, and other or unknown), US census region (Northeast, Midwest, South, and West), urban or rural setting, and continuity of care. We considered a patient to have good continuity of care if he or she had been seen previously and had at least 1 visit to the practice during the preceding 12 months.23
Statistical Analysis
We estimated summary statistics for cardiovascular risk factors and sociodemographic characteristics among adults 40 to 79 years of age. To compare rates of primary preventive cardiovascular care among patients using or not using opioids, we estimated generalized linear models using a Poisson distribution and log link function. We employed Poisson regression because previous research has shown that it can be used to analyze binary data in a manner similar to logistic regression, with a time‐at‐risk value specified as 1 for each observation.24, 25, 26 The models adjusted for patients’ clinical and demographic characteristics, insurance, region, urban/rural setting, and physician specialty, similar to earlier studies using the NAMCS and/or analyzing cardiovascular outcomes. We report adjusted risk ratios (aRRs) and 95% CIs.
We performed sensitivity analyses that: (1) limited the sample of adults not using opioids to those with at least 1 medication listed in their medication list (to test the robustness of our study results); (2) limited the study sample to visits with physicians who reported being the patient's primary care physician (to maximize the accuracy of reported medications, because a patient's primary care physician is likely to be better informed about the patient's medications than physicians who do not identify as the patient's primary care physician); and (3) excluded patients with a diagnosis of cancer, because some of these patients may not be appropriate candidates for primary preventive cardiovascular care. In addition, we tested the validity of the Poisson regression models using multivariate linear probability models; these analyses yielded findings similar to our main results and are shown in Table S3.
All analyses accounted for the complex sampling design of the NAMCS and were performed using Stata version 14 (StataCorp, College Station, TX).27
Results
Among adults 40 to 79 years old and eligible for primary prevention of cardiovascular disease, there were ≈32 million visits annually by adults who were prescribed opioids and ≈167 million visits annually by adults not prescribed opioids from 2014 to 2016 (Table 1). Patients with opioid use compared with those without opioid use had higher rates of tobacco use (25.8% versus 14.8%, P<0.001); were more likely to be insured by Medicare (36.9% versus 29.2%, P<0.001) or Medicaid (10.0% versus 7.1%, P<0.001), or more likely to be uninsured (3.1% versus 2.2%, P=0.005), and had better continuity of care (90.5% versus 84.1%, P<0.001). Patients who were prescribed opioids were less likely to be seen by cardiologists (3.8% versus 7.3%, P<0.001) compared with patients not prescribed opioids.
Table 1.
United States Ambulatory Care Visits for Adults 40 to 79 Years Old, by Opioid Prescriptions, 2014–2016
| Characteristic | Adults 40–79 Years Old Prescribed an Opioid | Adults 40–79 Years Old Not Prescribed an Opioid | P Valuea | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Unweighted Visits, n | Annual Weighted Visits, n | % | SE | Unweighted Visits, n | Annual Weighted Visits, n | % | SE | ||
| All visits | 2262 | 32 347 000 | 100.0 | 0.0 | 11 102 | 167 100 000 | 100.0 | 0.0 | |
| Age, y | |||||||||
| 40 to 49 | 473 | 6 472 000 | 20.0 | 1.8 | 2439 | 36 642 000 | 21.9 | 1.2 | |
| 50 to 59 | 700 | 10 610 000 | 32.8 | 2.2 | 3240 | 50 055 000 | 30.0 | 0.8 | |
| 60 to 69 | 635 | 9 673 000 | 29.9 | 1.9 | 3263 | 48 685 000 | 29.1 | 0.8 | |
| 70 to 79 | 454 | 5 592 000 | 17.3 | 1.4 | 2160 | 31 704 000 | 19.0 | 0.9 | 0.873 |
| Sex | |||||||||
| Female | 1354 | 18 257 000 | 56.4 | 2.0 | 6300 | 94 943 000 | 56.8 | 1.1 | |
| Male | 908 | 14 090 000 | 43.6 | 2.0 | 4802 | 72 143 000 | 43.2 | 1.1 | 0.856 |
| Race/ethnicity | |||||||||
| Non‐Hispanic white | 1285 | 17 866 000 | 55.2 | 2.9 | 6423 | 87 974 000 | 52.7 | 2.3 | |
| Non‐Hispanic black | 225 | 3 108 000 | 9.6 | 1.2 | 1027 | 19 179 000 | 11.5 | 1.4 | 0.206 |
| Hispanic | 132 | 3 158 000 | 9.8 | 1.7 | 839 | 21 989 000 | 13.2 | 1.9 | 0.074 |
| Other/unknown | 620 | 8 215 000 | 25.4 | 2.9 | 2813 | 37 943 000 | 22.7 | 1.8 | 0.649 |
| Insurance | |||||||||
| Private | 864 | 12 841 000 | 39.7 | 1.6 | 5816 | 89 681 000 | 53.7 | 1.5 | |
| Medicare | 852 | 11 936 000 | 36.9 | 1.8 | 3266 | 48 757 000 | 29.2 | 1.3 | <0.001 |
| Medicaid | 218 | 3 243 000 | 10.0 | 1.5 | 699 | 11 887 000 | 7.1 | 0.8 | <0.001 |
| Other/unknown | 252 | 3 313 000 | 10.2 | 1.9 | 1002 | 13 029 000 | 7.8 | 1.3 | 0.002 |
| Uninsured | 76 | 1 015 000 | 3.1 | 0.6 | 319 | 3 732 000 | 2.2 | 0.3 | 0.005 |
| United States region | |||||||||
| Northeast | 236 | 5 129 000 | 15.9 | 3.1 | 1786 | 34 560 000 | 20.7 | 1.9 | |
| Midwest | 660 | 8 085 000 | 25.0 | 2.6 | 2926 | 33 473 000 | 20.0 | 1.7 | 0.035 |
| South | 809 | 12 000 000 | 37.1 | 3.2 | 4056 | 65 868 000 | 39.4 | 2.7 | 0.379 |
| West | 557 | 7 133 000 | 22.1 | 2.7 | 2334 | 33 185 000 | 19.9 | 2.3 | 0.139 |
| Setting | |||||||||
| Urban | 1894 | 27 664 000 | 85.5 | 2.5 | 9502 | 148 400 000 | 88.8 | 1.5 | |
| Rural | 368 | 4 683 000 | 14.5 | 2.5 | 1600 | 18 699 000 | 11.2 | 1.5 | 0.044 |
| Physician specialty | |||||||||
| General medicine/internist | 2105 | 31 110 000 | 96.2 | 0.8 | 9870 | 154 900 000 | 92.7 | 0.9 | |
| Cardiologist | 157 | 1 237 000 | 3.8 | 0.8 | 1232 | 12 186 000 | 7.3 | 0.9 | <0.001 |
| Chronic conditions | |||||||||
| Obese/overweight | 366 | 5 315 000 | 16.4 | 1.5 | 1537 | 23 477 000 | 14.1 | 0.8 | 0.120 |
| Dyslipidemia | 789 | 12 215 000 | 37.8 | 2.4 | 4410 | 68 800 000 | 41.2 | 1.4 | 0.172 |
| Diabetes mellitus | 558 | 7 922 000 | 24.5 | 1.7 | 2368 | 39 898 000 | 23.9 | 0.9 | 0.743 |
| Hypertension | 1207 | 16 806 000 | 52.0 | 2.0 | 5459 | 82 800 000 | 49.6 | 1.3 | 0.275 |
| Smoker | 566 | 8 360 000 | 25.8 | 2.0 | 1992 | 24 743 000 | 14.8 | 0.7 | <0.001 |
| Good continuity of care | 2019 | 29 265 000 | 90.5 | 1.3 | 9132 | 140 500 000 | 84.1 | 1.0 | <0.001 |
All analyses account for the complex sampling design of the National Ambulatory Medical Care Survey. SE indicates standard error.
Calculated with Wald chi‐square test from simple ordinal (age) or binomial/multinomial (sex, race/ethnicity, insurance, setting, risk factors, comorbid diseases) logistic regression models comparing patients with an opioid prescription versus patients without an opioid prescription.
Medications for Primary Prevention of Cardiovascular Disease
Rates of use of primary preventive cardiovascular medications were substantially lower than guideline recommendations overall. Among patients eligible for primary prevention—with and without opioid prescriptions―the prevalence of statin use for patients with dyslipidemia was 52.1% (95% CI, 44.5%–59.7%) and 46.3% (95% CI, 42.0%–50.6%); the prevalence of statin use for patients with diabetes mellitus was 49.1% (95% CI, 41.8%–56.4%) and 37.9% (95% CI, 32.6%–43.2%); and antihypertensive use for patients with hypertension was 76.5% (95% CI, 71.6%–81.4%) and 65.8% (95% CI, 62.5%–69.1%), respectively (Figure). Patients prescribed opioids were more likely to be prescribed statin therapy for ASCVD prevention in diabetes mellitus (aRR, 1.25; 95% CI, 1.06–1.47; P=0.007) and antihypertensive medications (aRR, 1.14; 95% CI, 1.06–1.22; P<0.001). Being seen by a cardiologist was not associated with improved primary preventive cardiovascular medication use (Table 2).
Figure 1. Prevalence of primary prevention of cardiovascular disease in adult patients 40 to 79 years old seeing physicians in ambulatory care visits in the United States, by opioid prescription (2014–2016).
ASCVD indicates atherosclerotic cardiovascular disease; DM, diabetes mellitus; and HTN, hypertension.
Table 2.
Adjusted Relative Risk of Primary Preventive Cardiovascular Medication Use in Adults 40–79 Years Old Seeing Physicians in United States Ambulatory Care Visits, 2014–2016
| Characteristics | Statin for Dyslipidemia | Statin for ASCVD Prevention in DM | Antihypertensive for Hypertension | |||
|---|---|---|---|---|---|---|
| Adjusted Relative Risk (95% CI) | P Value | Adjusted Relative Risk (95% CI) | P Value | Adjusted Relative Risk (95% CI) | P Value | |
| Prescribed an opioid | 1.11 (0.96–1.27) | 0.147 | 1.25 (1.06–1.47) | 0.007 | 1.14 (1.06–1.22) | <0.001 |
| Sex | ||||||
| Men | 1.00 | 1.00 | 1.00 | |||
| Female | 0.87 (0.79–0.97) | 0.011 | 0.86 (0.75–0.99) | 0.033 | 0.94 (0.89–1.00) | 0.070 |
| Race/ethnicity | ||||||
| White | 1.00 | 1.00 | 1.00 | |||
| Non‐Hispanic black | 0.96 (0.75–1.23) | 0.767 | 0.85 (0.65–1.11) | 0.227 | 1.01 (0.88–1.17) | 0.849 |
| Hispanic | 0.58 (0.44–0.78) | <0.001 | 0.52 (0.34–0.80) | 0.003 | 0.95 (0.85–1.05) | 0.276 |
| Other/unknown | 0.99 (0.84–1.17) | 0.938 | 1.10 (0.91–1.33) | 0.325 | 1.04 (0.94–1.16) | 0.436 |
| Age, y | ||||||
| 40–49 | 1.00 | 1.00 | 1.00 | |||
| 50–59 | 1.09 (0.88–1.35) | 0.431 | 1.13 (0.86–1.48) | 0.370 | 0.98 (0.88–1.09) | 0.723 |
| 60–69 | 1.12 (0.91–1.37) | 0.300 | 1.04 (0.76–1.42) | 0.829 | 1.04 (0.94–1.14) | 0.455 |
| 70–79 | 1.12 (0.90–1.40) | 0.318 | 1.17 (0.86–1.60) | 0.324 | 1.05 (0.91–1.20) | 0.507 |
| Insurance | ||||||
| Private | 1.00 | 1.00 | 1.00 | |||
| Medicare | 1.01 (0.89–1.15) | 0.834 | 1.06 (0.89–1.26) | 0.535 | 1.01 (0.94–1.08) | 0.735 |
| Medicaid | 0.95 (0.78–1.16) | 0.620 | 1.05 (0.82–1.34) | 0.723 | 0.91 (0.81–1.03) | 0.132 |
| Other/unknown | 0.96 (0.76–1.22) | 0.757 | 0.97 (0.70–1.35) | 0.862 | 1.05 (0.94–1.17) | 0.409 |
| Uninsured | 1.09 (0.71–1.68) | 0.701 | 1.24 (0.74–2.08) | 0.408 | 1.07 (0.90–1.28) | 0.426 |
| Urban or rural setting | ||||||
| Urban | 1.00 | 1.00 | 1.00 | |||
| Rural | 0.97 (0.77–1.23) | 0.820 | 0.85 (0.62–1.17) | 0.313 | 0.89 (0.73–1.08) | 0.225 |
| United States region | ||||||
| Northeast | 1.00 | 1.00 | 1.00 | |||
| Midwest | 1.23 (1.00–1.51) | 0.052 | 1.37 (1.06–1.78) | 0.017 | 1.13 (1.00–1.27) | 0.051 |
| South | 1.03 (0.82–1.29) | 0.808 | 1.19 (0.90–1.57) | 0.223 | 1.00 (0.88–1.13) | 0.998 |
| West | 1.05 (0.83–1.32) | 0.683 | 1.12 (0.84–1.51) | 0.435 | 1.07 (0.95–1.21) | 0.263 |
| Physician specialty | ||||||
| General medicine/internist | 1.00 | 1.00 | 1.00 | |||
| Cardiologist | 1.13 (0.94–1.35) | 0.191 | 1.02 (0.79–1.31) | 0.865 | 1.09 (0.97–1.22) | 0.160 |
| Chronic conditions | ||||||
| Obese/overweight | 1.08 (0.94–1.24) | 0.296 | 1.06 (0.91–1.24) | 0.451 | 1.16 (1.09–1.23) | <0.001 |
| Dyslipidemia | 1.00 (1.00–1.00) | 1.91 (1.57–2.32) | <0.001 | 1.03 (0.97–1.11) | 0.337 | |
| Diabetes mellitus | 1.16 (1.05–1.28) | 0.002 | 1.00 (1.00–1.00) | 1.03 (0.96–1.09) | 0.415 | |
| Hypertension | 1.35 (1.14–1.60) | <0.001 | 1.23 (0.98–1.54) | 0.072 | 1.00 (1.00–1.00) | |
| Smoker | 1.01 (0.90–1.13) | 0.902 | 1.06 (0.91–1.24) | 0.461 | 1.02 (0.95–1.09) | 0.554 |
| Good continuity of care | 1.14 (0.95–1.38) | 0.152 | 1.03 (0.84–1.26) | 0.776 | 1.16 (1.05–1.28) | 0.003 |
| Time trend | 0.98 (0.91–1.06) | 0.643 | 1.08 (0.97–1.19) | 0.150 | 0.94 (0.89–0.99) | 0.028 |
Reference groups include male sex, white race/ethnicity, age <45 years, private insurance, and urban setting. Other independent variables included in the regression models are obesity, smoker, dyslipidemia, diabetes mellitus, hypertension, cardiovascular disease, and a year‐based time trend. All analyses account for the complex sampling design of the National Ambulatory Medical Care Survey. ASCVD indicates atherosclerotic cardiovascular disease; and DM, diabetes mellitus.
Lifestyle Modification Counseling for Primary Prevention of Cardiovascular Disease
Physician rates of providing lifestyle counseling to adults with cardiovascular risk factors were modest. The proportion of visits during which diet/exercise counseling was provided was 40.5% (95% CI, 31.1%–49.9%) and 45.3% (95% CI, 38.8%–51.8%) in patients with versus without opioid prescriptions, respectively. The proportion of visits during which smoking cessation counseling or pharmacotherapy was provided was 25.3% (95% CI, 16.3%–34.3%) and 19.3% (95% CI, 15.4%–23.2%) in patients with versus without opioid prescriptions, respectively. Adjusted differences for diet/exercise counseling and smoking cessation therapy between patients with versus without opioid prescriptions were not significant (aRR for diet/exercise counseling, 0.88; 95% CI, 0.73–1.07; P=0.201; aRR for smoking cessation counseling/therapy, 1.05; 95% CI, 0.70–1.58; P=0.805). Being seen by a cardiologist was also not associated with improved lifestyle modification counseling (Table 3).
Table 3.
Adjusted Relative Risk of Preventive Cardiovascular Lifestyle Counseling in Adults 40–79 Years Old Seeing Physicians in United States Ambulatory Care Visits, 2014–2016
| Characteristics | Diet/Exercise Counseling | Smoking Cessation Counseling/Therapy* | ||
|---|---|---|---|---|
| Adjusted Relative Risk (95% CI) | P Value | Adjusted Relative Risk (95% CI) | P Value | |
| Prescribed an opioid | 0.88 (0.73–1.07) | 0.201 | 1.05 (0.70–1.58) | 0.805 |
| Sex | ||||
| Men | 1.00 | 1.00 | ||
| Female | 1.07 (0.90–1.27) | 0.432 | 1.00 (0.77–1.29) | 0.982 |
| Race/ethnicity | ||||
| White | 1.00 | 1.00 | ||
| Non‐Hispanic black | 1.17 (0.94–1.47) | 0.163 | 1.32 (0.82–2.10) | 0.251 |
| Hispanic | 1.38 (1.09–1.74) | 0.007 | 0.41 (0.22–0.75) | 0.004 |
| Other/unknown | 1.20 (0.94–1.54) | 0.149 | 1.06 (0.72–1.58) | 0.755 |
| Age, y | ||||
| 40–49 | 1.00 | 1.00 | ||
| 50–59 | 0.98 (0.78–1.24) | 0.893 | 1.28 (0.91–1.80) | 0.157 |
| 60–69 | 0.87 (0.71–1.06) | 0.162 | 0.97 (0.64–1.46) | 0.875 |
| 70–79 | 0.9 (0.6–1.1) | 0.252 | 0.6 (0.4–1.1) | 0.108 |
| Insurance | ||||
| Private | ||||
| Medicare | 1.04 (0.85–1.26) | 0.721 | 1.40 (1.00–1.95) | 0.050 |
| Medicaid | 0.71 (0.49–1.03) | 0.068 | 0.83 (0.49–1.41) | 0.487 |
| Other/unknown | 0.94 (0.71–1.25) | 0.683 | 1.02 (0.57–1.81) | 0.959 |
| Uninsured | 0.73 (0.37–1.47) | 0.384 | 0.76 (0.36–1.58) | 0.454 |
| Urban or rural setting | ||||
| Urban | 1.00 | 1.00 | ||
| Rural | 0.72 (0.47–1.11) | 0.142 | 0.90 (0.52–1.56) | 0.699 |
| United States region | ||||
| Northeast | 1.00 | 1.00 | ||
| Midwest | 0.94 (0.71–1.25) | 0.687 | 0.76 (0.47–1.23) | 0.267 |
| South | 1.19 (0.91–1.55) | 0.216 | 0.93 (0.57–1.50) | 0.768 |
| West | 0.82 (0.57–1.19) | 0.298 | 0.74 (0.43–1.25) | 0.262 |
| Physician specialty | ||||
| General medicine/internist | 1.00 | 1.00 | ||
| Cardiologist | 0.74 (0.54–1.02) | 0.064 | 0.75 (0.46–1.21) | 0.237 |
| Chronic conditions | ||||
| Obese/overweight | 1.00 (1.00–1.00) | 1.10 (0.77–1.58) | 0.589 | |
| Dyslipidemia | 1.27 (1.06–1.52) | 0.008 | 1.10 (0.81–1.51) | 0.535 |
| Diabetes mellitus | 1.12 (0.98–1.29) | 0.104 | 0.77 (0.53–1.12) | 0.178 |
| Hypertension | 1.10 (0.94–1.30) | 0.237 | 0.96 (0.74–1.26) | 0.777 |
| Smoker | 1.16 (0.96–1.39) | 0.117 | 1.00 (1.00–1.00) | |
| Good continuity of care | 1.0 (0.8–1.2) | 0.688 | 0.9 (0.6–1.3) | 0.531 |
| Time trend | 1.2 (1.1–1.3) | 0.002 | 1.6 (1.4–1.9) | <0.001 |
Medications for smoking cessation include nicotine replacement therapy, varenicline, and bupropion.
Sensitivity Analyses
On the basis of our results, we performed further analyses to determine whether our findings were robust to limiting the study population to patients who were taking at least 1 medication, because patients who are not taking any medications despite having cardiovascular risk factors may differ from other patients in ways that are meaningful but unobserved. This analysis reduced the annual number of patient visits among patients not prescribed opioids from 167 to 139 million (17% relative decrease), with ≈60% of the difference attributable to patients with cardiovascular risk factors. There was a significant attenuation of our main findings, indicating that our results were driven by patients with cardiovascular risk factors but not taking medications (Tables S4 and S5).
In another sensitivity analysis, we limited our study sample to visits with physicians who reported being the patient's primary care physician, because these physicians would be most likely to be well informed about their patient's medications. The results are shown in Tables S6 and S7 and are similar to our main findings. Excluding patients with a diagnosis of cancer also did not significantly affect our results (Tables S8 and S9). Results of a multivariate linear probability model sensitivity analysis are shown in Table S3 and are also similar to our main findings.
Discussion
Our findings indicate that the overall rates of primary preventive cardiovascular care were substantially lower than guideline recommendations. The 2 primary preventive strategies with the lowest adherence rates in our study were provision of statin therapy to patients with diabetes mellitus and provision of smoking cessation therapy or counseling. These findings were in the context of approximately a quarter of all ambulatory visits being made by patients with diabetes mellitus, and more than a quarter of all ambulatory visits by patients using opioids also involving tobacco use. Despite tobacco use being a major modifiable risk factor for ASCVD, we found that patients were only provided smoking cessation therapy in ≈25% of the visits made by patients with opioid prescriptions. These findings highlight major gaps in primary prevention, and also underscore the potential for primary care physicians and cardiologists to reduce cardiovascular risk in primary care populations with evidence‐based therapy. The practical implication of our findings for medical decision making is that clinicians can use clinical encounters related to pain management as an opportunity to more globally discuss preventive practices, not just in terms of the risks associated with initiating or continuing opioid therapy, but also in terms of preventing other adverse health events.
Although we hypothesized that increased physician attention on opioid therapy combined with limited time during ambulatory visits would hinder optimal primary preventive cardiovascular care, the opposite proved to be true. We suspect that the association we detected between opioid use and primary preventive cardiovascular medications may reflect a modest inclination on the part of physicians prescribing opioids toward more frequent prescribing overall (across multiple drug classes), or a modest inclination on the part of patients who were prescribed opioids to be more willing to use other medications, or both. In addition, patients prescribed opioids were more likely to have good continuity of care, and this may have contributed to improved primary preventive cardiovascular care in ways that our models did not capture. Our findings were partially attributable to patients who had cardiovascular risk factors but were not taking any medications.
To the best of our knowledge, consideration of increased cardiovascular risk among patients prescribed opioids is not widely recognized by physicians when deciding whether to initiate or continue opioid therapy. Although we found that these patients were more likely to receive certain primary preventive cardiovascular medications than patients not prescribed opioids, a substantial proportion of patients were still not receiving guideline‐recommended care. Greater clinician awareness of the possibility of increased adverse cardiovascular outcomes among patients treated with opioids may alter future opioid‐prescribing practices and increase interest in addressing cardiovascular risk factors as well as providing primary preventive cardiovascular care to these patients.
Our work has limitations, including the possibility of inaccurate documentation of cardiovascular risk factors and medications by physicians, absence of detailed information about blood pressure and cholesterol, and exclusion of adults with cardiovascular risk factors who did not receive care in ambulatory settings. In addition, we were unable to accurately determine indications for opioid use or duration of therapy, which may have increased the robustness and clinical utility of our findings. We were also unable to calculate oral morphine equivalents and determine the impact of dosing on our measures, as these data were unavailable. Furthermore, although we did obtain some sociodemographic measures, we did not have detailed information on income or educational level, both of which may influence opioid prescribing and physician decision making regarding preventive care.
The major policy implication of our work is that it reinforces the importance of national efforts to reduce cardiovascular risk, such as the Million Hearts initiative led by the Center for Medicare & Medicaid Services and the Centers for Disease Control and Prevention. Several studies have reported underuse of primary preventive cardiovascular medications, and our study highlights this underuse in patients prescribed opioids.28, 29, 30, 31, 32 On the basis of our most conservative analysis (the primary care physician analysis, because these physicians are most likely to have complete medication records), approximately one third of visits by patients with hypertension did not include antihypertensive therapy, and smoking cessation counseling/therapy was provided in <25% of visits. There are substantial opportunities to improve care and outcomes.
In conclusion, overall adherence to guideline‐recommended primary preventive cardiovascular care during ambulatory visits was suboptimal. Patients using opioids did not receive lower rates of primary prevention compared with patients not using opioids. Findings instead show that patients prescribed opioids were more likely to receive statin therapy and antihypertensives in the setting of diabetes mellitus and hypertension, respectively. Because of the potentially increased risk of adverse cardiovascular events associated with opioid therapy and the overall modest rates of primary prevention, ongoing efforts to bridge these gaps in primary prevention of cardiovascular disease remain a high priority.
Sources and Funding
J.A.L. is supported by National Institute on Drug Abuse (R01DA045688), the National Heart, Lung, and Blood Institute (U01HL142104); the National Institute on Minority Health and Health Disparities (R01MD011544); and the Robert Wood Johnson Foundation (72426).
Disclosures
None.
Supporting information
Tables S1–S9
(J Am Heart Assoc. 2020;9:e015961 DOI: 10.1161/JAHA.120.015961.)
For Sources of Funding and Disclosures, see page 8.
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Associated Data
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Supplementary Materials
Tables S1–S9