Safety Net Program to Improve Statin Initiation Among Adults With High Low-Density Lipoprotein Cholesterol.

INTRODUCTION: Despite their effectiveness in reducing low-density lipoprotein cholesterol and cardiovascular disease risk, high-intensity statins are underutilized among adults with low-density lipoprotein cholesterol ≥190 mg/dL. This study determined whether a safety net program (SureNet) facilitating medication and laboratory test orders improved statin initiation and laboratory test completions after (SureNet period: April 2019-September 2021) and before implementation (pre-SureNet period: January 2016-September 2018). METHODS: Kaiser Permanente Southern California members aged 20-60 years with low-density lipoprotein cholesterol ≥190 mg/dL and no statin use in previous 2-6 months were included in this retrospective cohort study. Statin orders within 14 days and statin fills, laboratory test completions, and improved low-density lipoprotein cholesterol within 180 days of the high low-density lipoprotein cholesterol (pre-SureNet) or outreach (SureNet period) were compared. Analyses were conducted in 2022. RESULTS: Overall, 3,534 and 3,555 adults were eligible for statin initiation during the pre-SureNet and SureNet periods, respectively. Overall, 759 (21.5%) and 976 (27.5%) had a statin approved by their physician during pre-SureNet and SureNet periods, respectively (p<0.001). After multivariable adjustment for demographics and clinical characteristics, adults during the SureNet period had a higher likelihood of receiving a statin order (prevalence ratio=1.36, 95% CI=1.25, 1.48), filling their statin (prevalence ratio=1.32, 95% CI=1.26, 1.38), completing their laboratories (prevalence ratio=1.41, 95% CI=1.26, 1.58), and improving low-density lipoprotein cholesterol (prevalence ratio=1.21, 95% CI=1.07, 1.37) than in pre-Surenet period. CONCLUSIONS: The SureNet program was able to improve prescription orders, fills, laboratory test completions, and lower low-density lipoprotein cholesterol. Optimizing both physician adherence to treatment guidelines; and patient adherence to the program may improve low-density lipoprotein cholesterol lowering.

Trends in Acute Myocardial Infarction by Race and Ethnicity.

Background Trends in acute myocardial infarction (AMI) incidence rates for diverse races/ethnicities are largely unknown, presenting barriers to understanding the role of race/ethnicity in AMI occurrence. Methods and Results We identified AMI hospitalizations for Kaiser Permanente Southern California members, aged ≥35 years, during 2000 to 2014 using discharge diagnostic codes. We excluded hospitalizations with missing race/ethnicity information. We calculated annual incidence rates (age and sex standardized to the 2010 US census population) for AMI, ST-segment-elevation myocardial infarction, and non-ST-segment-elevation myocardial infarction by race/ethnicity (Hispanic and non-Hispanic racial groups: Asian or Pacific Islander, black, and white). Using Poisson regression, we estimated annual percentage change in AMI, non-ST-segment-elevation myocardial infarction, and ST-segment-elevation myocardial infarction incidence by race/ethnicity and AMI incidence rate ratios between race/ethnicity pairs, adjusting for age and sex. We included 18 630 776 person-years of observation and identified 44 142 AMI hospitalizations. During 2000 to 2014, declines in AMI, non-ST-segment-elevation myocardial infarction, and ST-segment-elevation myocardial infarction were 48.7%, 34.2%, and 69.8%, respectively. Age- and sex-standardized AMI hospitalization rates/100 000 person-years declined for Hispanics (from 307 to 162), Asians or Pacific Islanders (from 271 to 158), blacks (from 347 to 199), and whites (from 376 to 189). Annual percentage changes ranged from -2.99% to -4.75%, except for blacks, whose annual percentage change was -5.32% during 2000 to 2009 and -1.03% during 2010 to 2014. Conclusions During 2000 to 2014, AMI, non-ST-segment-elevation myocardial infarction, and ST-segment-elevation myocardial infarction hospitalization incidence rates declined substantially for each race/ethnic group. Despite narrowing rates among races/ethnicities, differences persist. Understanding these differences can help identify unmet needs in AMI prevention and management to guide targeted interventions.

Sex-Specific Trends in Acute Myocardial Infarction Within an Integrated Healthcare Network, 2000 Through 2014.

BACKGROUND: In recent decades, the rates of incident acute myocardial infarction (AMI) have declined in the United States, yet disparities by sex remain. In an integrated healthcare delivery system, we examined temporal trends in incident AMI among women and men. METHODS: We identified hospitalized AMI among members ≥35 years of age in Kaiser Permanente Southern California. The first hospitalization for AMI overall, and for ST-segment-elevation MI and non-ST-segment-elevation MI was identified by International Classification of Diseases, Ninth Revision, Clinical Modification primary discharge diagnosis codes in each calendar year from 2000 through 2014. Age- and sex-standardized incidence rates per 100 000 person-years were calculated by using direct adjustment to the 2010 US Census population. Average annual percent changes (AAPCs) and period percent changes were calculated, and trend tests were conducted using Poisson regression. RESULTS: We identified 45 331 AMI hospitalizations between 2000 and 2014. Age- and sex-standardized incidence rates of AMI declined from 322.4 (95% CI, 311.0-333.9) in 2000 to 174.6 (95% CI, 168.2-181.0) in 2014, representing an AAPC of -4.4% (95% CI, -4.2 to -4.6) and a period percent change of -46.6%. The AAPC for AMI in women was -4.6% (95% CI, -4.1 to -5.2) between 2000 and 2009 and declined to -2.3% (95% CI, -1.2 to -3.4) between 2010 and 2014. The AAPC for AMI in men was stable over the study period (-4.7% [95% CI, -4.4 to -4.9]). The AAPC for ST-segment-elevation MI hospitalization overall was -8.3% (95% CI, -8.0% to -8.6%).The AAPC in ST-segment-elevation MI changed among women in 2009 (2000-2009: -10.2% [95% CI, -9.3 to -11.1] and in 2010-2014: -5.2% [95% CI, -3.1 to -7.3]) while remaining stable among men (-8.0% [95% CI, -7.6 to -8.4]). The AAPC for non-ST-segment-elevation MI hospitalization was smaller than for ST-segment-elevation MI among both women and men (-1.9% [95% CI, -1.5 to -2.3] and -2.8% [95% CI, -2.5 to -3.2], respectively). CONCLUSIONS: These results suggest that the incidence of hospitalized AMI declined between 2000 and 2014; however, declines in AMI have slowed among women in comparison with men in recent years. Determining unmet care needs among women may reduce these sex-based AMI disparities.

Trends in Lipid Screening Among Adults in an Integrated Health Care Delivery System, 2009-2015.

BACKGROUND: Lipid screening determines eligibility for statins and other cardiovascular risk reduction interventions. OBJECTIVE: To examine trends in lipid screening among adults aged ≥20 years in a large, multiethnic, integrated health care delivery system in southern California. METHODS: Temporal trends in lipid screening were examined from 2009 to 2015 with an index date of September 30 of each year. Lipid screening was defined as the proportion of eligible members each year who (a) had ever been screened among those aged 20-39 years and (b) had been screened in the previous 6 years for those aged ≥ 40 years. Trends were analyzed by age, gender, and the presence of atherosclerotic cardiovascular disease (ASCVD) or diabetes without ASCVD status. RESULTS: More than 2 million individuals were included each year: 5%-6% had ASCVD (includes those with diabetes), 7%-8% had diabetes without ASCVD, and 87% had neither condition. Among the entire population, lipid screening increased from 79.8% in 2009 to 82.6% in 2015 (P < 0.0001). Among those with ASCVD or diabetes, lipid screening was 99% across all years. Among those without ASCVD or DM, screening increased from 76.9% in 2009 to 80.0% in 2015 (P < 0.0001), with higher screening among women compared with men and lower screening among individuals younger than 55 years. CONCLUSIONS: Consistently high rates of lipid screening were observed among individuals with ASCVD or diabetes. In individuals without these conditions, screening increased over time. However, there is room to further increase screening rates in adults younger than 55 years. DISCLOSURES: This manuscript and research work was supported by a contractual agreement between the Southern California Permanente Medical Group and Regeneron Pharmaceuticals and Sanofi U.S. Researchers from Regeneron and Sanofi collaborated on the study design, interpretation of data, and writing of the manuscript. Ling Grant, Harrison, Chang, Hsu, Cheetham, Wei, and Reynolds are employed by Kaiser Permanente Southern California. Scott is employed by Southern California Permanente Medical Group. Boklage is employed by Regeneron, and Romo-LeTourneau is employed by Sanofi. Preliminary results from this study were presented at the American Heart Association Scientific Sessions; November 12-16, 2016; New Orleans, LA.

Trends in Statin Use 2009-2015 in a Large Integrated Health System: Pre- and Post-2013 ACC/AHA Guideline on Treatment of Blood Cholesterol.

PURPOSE: Implementation of the 2013 ACC/AHA cholesterol treatment guideline is likely to vary by statin benefit group. The aim of this study was to document trends in statin use before and after introduction of the ACC/AHA guideline. METHODS: We conducted a retrospective study with annual cohorts from 2009 to 2015 among members of Kaiser Permanente Southern California aged ≥ 21 years. Members were categorized into four mutually exclusive statin benefit groups: atherosclerotic cardiovascular disease (ASCVD), LDL-C ≥ 190 mg/dL in the last year, diabetes (aged 40-75 years), and 10-year ASCVD risk ≥ 7.5% (aged 40-75 years). RESULTS: The cohorts ranged from 1,993,755 members in 2009 to 2,440,429 in 2015. Approximately 5% of patients had ASCVD, 1% had LDL-C ≥ 190 mg/dL, 6% had diabetes, and 10% had a 10-year ASCVD risk ≥ 7.5% each year. Trends in statin use were stable for adults with ASCVD (2009 78%; 2015 80%), recent LDL-C ≥ 190 mg/dL (2009 45%; 2015 44%), and diabetes (2009 74%; 2015 73%), but increased for patients with 10-year ASCVD risk ≥ 7.5% (2009 36%; 2015 47%). High-intensity statin use also increased 142% and 54% among patients with LDL-C ≥ 190 mg/dL and those with ASCVD ≤ 75 years of age, respectively. Moderate-to-high intensity statin utilization increased over 50% among those with a 10-year ASCVD risk ≥ 7.5%. CONCLUSIONS: Statin use increased substantially among patients with 10-year ASCVD risk ≥ 7.5% and use of appropriate statin dosage increased in each of the four statin benefit groups between 2009 and 2015; however, there is room for improvement.

Unmet Patient Need in Statin Intolerance: the Clinical Characteristics and Management.

PURPOSE: A substantial percentage of patients report intolerance or side effects of statin treatment leading to treatment changes or discontinuation. The purpose of this study was to examine statin therapy changes and subsequent effects on low-density lipoprotein cholesterol (LDL-C) among patients with statin intolerance (SI). METHODS: We identified 45,037 adults from Kaiser Permanente Southern California with SI documented between 2006 and 2012. Changes in statin therapy in the year before and after the SI index date were examined. We categorized patients into those who initiated statin therapy, discontinued, up-titrated, down-titrated, or did not switch therapy. We calculated the percentage change in LDL-C from the year before to the year after SI, and the percentage of patients attaining LDL-C < 100 and < 70 mg/dL. RESULTS: In the year prior to the SI date, 77.8% of patients filled a statin prescription. Following SI, 44.6% had no treatment change, 25.5% discontinued, and 30.0% altered their statin therapy. Of those who altered statin therapy, 52.6% down-titrated and 17.2% up-titrated their dose. Rhabdomyolysis was documented in < 1% of the cohort. The largest changes in LDL-C were experienced by patients who were on a high-intensity statin then discontinued treatment (35.6% increase) and those who initiated a high-intensity statin (25.5% decrease). The proportion of patients achieving LDL-C < 100 mg/dL and LDL-C < 70 mg/dL was the lowest among those who discontinued therapy. CONCLUSIONS: Although adjustments to the statin dosage may be appropriate upon documentation of SI, many of these patients will have high LDL-C. Strategies for LDL-C reduction in patients with SI may be necessary.

All-Cause and Acute Pancreatitis Health Care Costs in Patients With Severe Hypertriglyceridemia.

OBJECTIVE: The aim of this study was to assess health care utilization and costs related to acute pancreatitis (AP) in patients with severe hypertriglyceridemia (sHTG) levels. METHODS: Patients with sHTG levels 1000 mg/dL or higher were identified from January 1, 2007, to June 30, 2013. The first identified incident triglyceride level was labeled as index date. All-cause, AP-related health care visits, and mean total all-cause costs in patients with and without AP were compared during 12 months postindex. A generalized linear model regression was used to compare costs while controlling for patient characteristics and comorbidities. RESULTS: Five thousand five hundred fifty sHTG patients were identified, and 5.4% of these patients developed AP during postindex. Patients with AP had significantly (P < 0.05) more all-cause outpatient visits, hospitalizations, longer length of stays during the hospital visits, and emergency department visits versus patients without AP. Mean (SD) unadjusted all-cause health care costs in the 12 months postindex were $25,343 ($33,139) for patients with AP compared with $15,195 ($24,040) for patients with no AP. The regression showed annual all-cause costs were 49.9% higher (P < 0.01) for patients with AP versus without AP. CONCLUSIONS: Patients who developed AP were associated with higher costs; managing patients with sHTG at risk of developing AP may help reduce unnecessary costs.

Severe hypertriglyceridemia and factors associated with acute pancreatitis in an integrated health care system.

OBJECTIVE: To evaluate patient characteristics, treatment patterns, comorbidities, and risk factors associated with the development of acute pancreatitis (AP) in patients with severe hypertriglyceridemia (HTG) in an integrated health care delivery system. METHODS: We identified a retrospective cohort of severe HTG patients with a fasting triglyceride level ≥ 1000 mg/dL during January 1, 2007 to June 30, 2013 (index date) in an integrated health care delivery system. Patients were aged ≥18 years on index date and had 12 months of continuous membership and drug eligibility before the index date and during postindex including index date. Baseline patient characteristics, comorbidities, and risk factors were evaluated during 12-month preindex. Outcomes such as development of AP, treatment patterns, adherence to index therapy, and change in triglyceride (TG) laboratory levels were evaluated during postindex. Descriptive statistics were used to identify differences between patients developing AP vs no development of AP. A stepwise multivariate logistic regression and backward elimination method were used to assess statistically significant predictive factors associated with development of AP vs no AP. RESULTS: We identified 5550 patients with severe HTG, and 5.4% of these patients developed AP during postindex. Patients were mostly male (≥70%) in both groups; however, younger in the AP group (45 years ± 10.6) vs no AP group (50 years ± 11.4) with P value < .0001. The AP group had higher baseline Charslon Comorbidity Index score, alcohol abuse history (42.2%), any pancreatitis history (51.5%), diabetes (47%), and hypertension (55%), vs the no AP group (P values < .05). Patients in the AP group had higher baseline mean TG levels (2148, SD ± 1578) vs the no AP group (1559, SD ± 861), P value < .0001. Over 50% of the patients were prescribed their index therapy by a primary care provider. Predictive factors associated with the development of AP included younger age, alcohol use, and prior history of any pancreatitis, hypertension, renal disease stage 4, and other prescriber specialty. From parameters estimates, for each 100 mg/dL unit of increase in the TG level above 1000 mg/dL, there was a 3 percent increase in risk of developing AP. CONCLUSIONS: Patients with severe HTG are at a higher risk of developing AP. A number of comorbidities, risk factors, and baseline TG levels are associated with an increased incidence of AP. Patients with severe HTG are underdiagnosed, undertreated and are nonadherent to their index lipid therapy. There is a need to better define optimal approaches to treating severe HTG so as to reduce the incidence of AP. Economic studies are also needed to evaluate the burden of AP on various health care systems.

Automated Outreach for Cardiovascular-Related Medication Refill Reminders.

The objective of this study was to evaluate the effectiveness of an automated telephone system reminding patients with hypertension and/or cardiovascular disease to obtain overdue medication refills. The authors compared the intervention with usual care among patients with an overdue prescription for a statin or lisinopril-hydrochlorothiazide (lisinopril-HCTZ). The primary outcome was refill rate at 2 weeks. Secondary outcomes included time to refill and change in low-density lipoprotein cholesterol and blood pressure. Significantly more patients who received a reminder call refilled their prescription compared with the usual-care group (statin cohort: 30.3% vs 24.9% [P<.0001]; lisinopril-HCTZ cohort: 30.7% vs 24.2% [P<.0001]). The median time to refill was shorter in patients receiving the reminder call (statin cohort: 29 vs 36 days [P<.0001]; lisinopril-HCTZ cohort: 24 vs 31 days [P<.0001]). There were no statistically significant differences in mean low-density lipoprotein cholesterol and blood pressure. These findings suggest the need for interventions that have a longer-term impact.

Adherence to statins and LDL-cholesterol goal attainment.

OBJECTIVES: To examine the relationship between low-density lipoprotein cholesterol (LDL-C) goal attainment and adherence to statin medications in patients with coronary artery disease (CAD). STUDY DESIGN: Cross-sectional study of CAD patients 18 years of age or older in an integrated healthcare system. METHODS: Patients dispensed 2 or more statin prescriptions between May 2009 and May 2010, were identified. Medication possession ratio (MPR) was calculated to estimate adherence. The LDL-C value closest to May 27, 2010, was used to determine goal. Adherence and LDL-C goal were defined as 80% or greater MPR and less than 100 mg/dL or less than 70 mg/dL, respectively. Electronic medical records were used to identify patient demographics and clinical information. Logistic regression was used to estimate the effect of these factors on goal attainment. RESULTS: A total of 67,100 CAD patients were identified. Overall, 85.8% had LDL-C less than 100 mg/dL, 32.4% had LDL less than 70 mg/dL, and 79.8% were adherent to their statin medication. Over 65% of patients not at LDL-C goal less than 100 mg/dL were adherent. Among patients with LDL-C less than 100 mg/dL, 17.9% were not adherent. Increasing medication adherence was associated with improved LDL-C levels. Adherence to statins, male sex, Asian and Hispanic race/ethnicity, a higher number of concurrent prescriptions, higher Charlson Comorbidity Index, and hypertension were associated with LDL-C goal attainment. CONCLUSIONS: Incorporating LDL-C levels and medication adherence at the point of care allows providers to focus interventions to address either adherence challenges or the need for medication titration in an effort to improve LDL-C goal attainment and ultimately reduce morbidity and mortality.

Leveraging the electronic medical record to implement an abdominal aortic aneurysm screening program.

OBJECTIVE: Screening for abdominal aortic aneurysms (AAAs) reduces aneurysm-related mortality and has been recommended by the U.S. Preventive Services Task Force and American Heart Association since 2005. Medicare has covered a one-time screening ultrasound for new male enrollees with a familial or smoking history since 2007. Nevertheless, in the U.S., screening has remained underutilized. Review of patients with ruptured AAA in our system in 2007 showed the majority were undiagnosed, yet met U.S. Preventive Services Task Force and American Heart Association screening guidelines. To reduce the number of preventable AAA ruptures and deaths in our patients, we implemented an AAA screening program using our electronic medical record (EMR). This study describes the design, implementation, and early results of that screening program. METHODS: Between March 2012 and June 2013, men aged 65 to 75 years with any history of smoking were targeted for screening. Medical records were reviewed electronically to exclude patients with abdominal imaging studies within 10 years that would have diagnosed an AAA. Best practice alerts (BPA) were created in the EMR so when an appropriate patient is seen, office staff and providers are prompted to order an aortic ultrasound. AAA was defined as aortic diameter ≥3.0 cm or greater, and ultrasound reports contained a standard template providing guidance for patient management when an aneurysm was identified. Newly identified AAAs were triaged for vascular surgery consultation or follow-up with their primary physician. The number of eligible patients, unscreened patients, and AAAs identified were tabulated by our Regional Outpatient Safety Net Program. RESULTS: In a population of 3.6 million, 55,610 patients initially met screening criteria, and 26,837 (48.26%) were excluded from the BPA because of prior abdominal imaging studies. After 15 months, there were 68,164 patients who met screening criteria, 54,356 (79.74%) of whom had undergone an abdominal imaging study. Thus, 27,519 patients underwent an imaging study after the BPA was activated. During the study period, 731 new AAAs were diagnosed, 165 over 4.0 cm in diameter. Screening rates have increased at all medical centers where the BPA was activated, and the percentage of unscreened patients has been reduced from 51.74% to 20.26% system-wide. CONCLUSIONS: In an integrated health care system using an EMR, AAA screening can be implemented with a dramatic reduction in unscreened patients. Further analysis is required to assess the impact of the screening program on AAA rupture rate and cost-effectiveness in our system.

Use of health information technology (HIT) to improve statin adherence and low-density lipoprotein cholesterol goal attainment in high-risk patients: proceedings from a workshop.

The workshop discussions focused on how low-density lipoprotein cholesterol (LDL-C) goal attainment can be enhanced with the use of health information technology (HIT) in different clinical settings. A gap is acknowledged in LDL-C goal attainment, but because of the passage of the American Recovery & Reinvestment Act and the Health Information Technology for Economic and Clinical Health Acts there is now reason for optimism that this gap can be narrowed. For HIT to be effectively used to achieve treatment goals, it must be implemented in a setting in which the health care team is fully committed to achieving these goals. Implementation of HIT alone has not resulted in reducing the gap. It is critical to build an effective management strategy into the HIT platform without increasing the overall work/time burden on staff. By enhancing communication between the health care team and the patient, more timely adjustments to treatment plans can be made with greater opportunity for LDL-C goal attainment and improved efficiency in the long run. Patients would be encouraged to take a more active role. Support tools are available. The National Lipid Association has developed a toolkit designed to improve patient compliance and could be modified for use in an HIT system. The importance of a collaborative approach between nongovernmental organizations such as the National Lipid Association, National Quality Forum, HIT partners, and other members of the health care industry offers the best opportunity for long-term success and the real possibility that such efforts could be applied to other chronic conditions, for example, diabetes and hypertension.

Primary nonadherence to statin therapy: patients' perceptions.

OBJECTIVES: To identify self-reported reasons for not filling a new prescription for statin therapy. STUDY DESIGN: A cross-sectional telephone survey. METHODS: Potential participants were identified from a randomized, controlled trial among Kaiser Permanente Southern California (KPSC) members aged >24 years with no record of redeeming a new statin medication, defined as primary nonadherence. Among 1158 eligible patients, 98 were randomly selected and participated in a semi-structured telephone interview that included questions on whether the respondent redeemed their statin prescription, why the patient may have chosen not to use a KPSC pharmacy, reasons for not filling the prescription, use of non-prescription products for elevated cholesterol levels, and questions to assess health literacy. RESULTS: At 12 weeks post-index prescription date, 75% of 98 respondents reported not filling their new statin prescription, 20% reported picking it up from a non-KPSC pharmacy, 4% had already picked up the prescription at a KPSC pharmacy, and 1% did not know if it had been filled. The 3 most commonly cited reasons for primary nonadherence were general concerns about taking the medication (63%), a decision to try lifestyle modifications (63%), and fear of side effects (53%). A substantial proportion (33%) of respondents reported inadequate health literacy. CONCLUSIONS: These data suggest the need for interventions that address patients' negative perceptions of statins while emphasizing the benefits of statin therapy for reducing cardiovascular morbidity and mortality in formats accessible to those with limited health literacy.

Primary nonadherence to statin medications in a managed care organization.

BACKGROUND: Primary nonadherence to a medication occurs when a drug is prescribed but the patient fails to pick the prescription up from the pharmacy. Managed care organizations that provide integrated care using electronic medical records (EMR) are an ideal setting to study primary nonadherence.  OBJECTIVE: To identify patient and provider characteristics that are significantly associated with primary nonadherence to statin medications compared with a population of patients who picked up their first statin order.   METHODS: This was a retrospective cohort study of patients with a new statin prescription. Patients with a new order for a statin prescription between December 1, 2009, and February 28, 2010, were eligible. A statin order was considered new if the patient had no statin prescriptions in the previous 12 months. Study participants were 24 years and older with 12 months of continuous membership prior to the statin order. Patients were defined as primary nonadherent if they did not pick up their new prescription within 90 days. Descriptive and multivariate (conditional logistic regression) analyses of patients who did and did not pick up their new statin prescriptions were performed using demographic and socioeconomic information, health care utilization, health conditions, medical benefits, and prescriber characteristics.   RESULTS: A total of 19,826 patients with a new statin order that met all of the inclusion and exclusion criteria was identified. Of these, 3,049 patients (15.4%) did not pick up their statin prescriptions within 90 days of the order date. Primary nonadherent patients tended to be younger (55 vs. 57 years, P less than 0.001) and healthier, with fewer comorbid conditions (Charlson Comorbidity Index ≥ 1, 42.2% vs. 52.3%, P less than 0.001), lower rates of hospitalizations (7.2% vs. 12.0%, P less than 0.001), fewer concurrent prescriptions (3 vs. 4, P less than 0.001) and fewer clinic (4 vs. 5, P less than 0.001) and emergency department visits (18.2% vs. 24.6%, P less than 0.001) in the prior year than adherent patients. Although the multivariate model agreed well with the observed data, the characteristics included had a poor ability to predict primary nonadherence (c-statistic = 0.603).   CONCLUSION: Primary nonadherence has been recognized as a significant problem for many years, and electronic health records are allowing researchers to investigate the extent of the problem. In this study, almost 1 in 6 patients (15.4%) failed to pick up their new statin order within 90 days. However, clinical and demographic information available in electronic health care data may not be useful in predicting primary nonadherence. New methods and interventions need to be developed to improve primary adherence.  

Automated outreach to increase primary adherence to cholesterol-lowering medications.

BACKGROUND: Primary nonadherence occurs when new prescriptions are not dispensed. Little is known about how to reduce primary nonadherence. We performed a randomized controlled trial to evaluate an automated system to decrease primary nonadherence to statins for lowering cholesterol. METHODS: Adult members of Kaiser Permanente Southern California with no history of statin use within the past year who did not fill a statin prescription after 1 to 2 weeks were passively enrolled. The intervention group received automated telephone calls followed 1 week later by letters for continued nonadherence; the control group received no outreach. The primary outcome was a statin dispensed up to 2 weeks after delivery of the letter. Secondary outcomes included refills at intervals up to 1 year. Intervention effectiveness was determined by intent-to-treat analysis and Fisher exact test. Subgroups were examined using logistic regression. RESULTS: There were 2606 participants in the intervention group and 2610 in the control group. Statins were dispensed to 42.3% of intervention participants and 26.0% of control participants (absolute difference, 16.3%; P < .001). The relative risk for the intervention vs control group was 1.63 (95% CI, 1.50-1.76). Intervention effectiveness varied slightly by age (P = .045) but was effective across all age strata. Differences in the frequency of statin dispensations persisted up to 1 year (P < .001). CONCLUSIONS: The intervention was effective in reducing primary nonadherence to statin medications. Because of low marginal costs for outreach, this strategy appears feasible for reducing primary nonadherence. This approach may generalize well to other medications and chronic conditions.