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To determine the optimal modes of delivery for interventions to improve adherence to cardiovascular medications.
We conducted systematic searches of English-language peer-reviewed publications in MEDLINE and EMBASE, 1966 through 12/31/2008. We selected randomized controlled trials of interventions to improve adherence to medications for preventing or treating cardiovascular disease or diabetes. Articles were classified based on mode of delivery of the main intervention as (1) person-independent interventions (mailed, faxed or hand-distributed; or delivered via electronic interface) or (2) person-dependent interventions (nonautomated phone calls, in-person interventions).
We identified 6550 articles; 168 were reviewed in full, 51 met inclusion criteria. Among person-independent interventions (56% successful), electronic interventions were most successful (67%). Among person-dependent interventions (52% successful), phone calls showed low success rates (38%). In-person interventions at hospital discharge were more effective (67%) than clinic interventions (47%). In-person pharmacist interventions were effective when held in a pharmacy (83% successful), less effective in clinics (38%).
Future medication adherence studies should explore new electronic approaches and in-person interventions at the site of medication distribution. Identifying times of increased patient receptivity to the adherence message such as hospital discharge will also be important.
Non-adherence to essential chronic medication therapy for cardiovascular disease and diabetes is common, leading to substantial morbidity, mortality, and health care costs1-3. Evidence-based efforts to improve adherence are needed. Previous studies have demonstrated the effectiveness of reduced dosing demands and complex, multi-factorial interventions4-5, but there is little evidence available comparing modes of delivery for adherence interventions.
Evidence-based information on modes of delivery would enhance the construction of adherence interventions in several domains: the communication channel (e.g. written, electronic, phone, in-person), the purveyor of information, (e.g. lay person, pharmacist, physician), and the optimal setting (hospital, home, pharmacy, clinic). The mode of delivery is closely linked to an intervention’s cost and therefore to its long-term viability. A careful consideration of the comparative efficacy and intensity of different approaches is therefore needed to develop evidence-based strategies.
We conducted a systematic review of interventions that seek to improve adherence to medications for cardiovascular disease and diabetes, a cardiovascular disease equivalent. We focused on the mechanism of information transfer to patients. By evaluating the effects of (1) the purveyor of information; (2) the channel of information; and (3) the setting of transfer, we offer to payors, providers and policymakers additional guidance on the development of adherence interventions.
We performed a systematic search of articles published in peer-reviewed health-care related journals between 1966 and December 31, 2008. The search was performed using MEDLINE and EMBASE, with the help of a professional librarian. We limited our search to randomized controlled trials.
We used search terms related to the type of study (randomized controlled trial), adherence (i.e., “adherence” OR “compliance” OR “medication adherence” or “treatment adherence”) prescription drugs (i.e., “drug,” OR “medication” OR “antihypertensive” OR “antihyperlipidemic” OR “hypoglycemic agents”) and cardiovascular disease and diabetes (myocardial infarction, coronary heart disease, heart failure; hypertension; hyperlipidemia; and diabetes.) Articles with at least 1 search term in 3 of the main categories (study type AND adherence AND either drug OR disease) met criteria for the title/abstract review (see Appendix).
Search terms and parameters were adjusted for both databases while maintaining a common overall architecture. Search results from MEDLINE and EMBASE were combined and screened for duplicate entries.
Studies were included if they reported the results of randomized controlled trials studying interventions to improve adherence to medications used for the prevention or treatment of cardiovascular disease or diabetes. Studies were limited to adult subjects (age ≥18) in either the outpatient setting or at the inpatient/outpatient transition. Data was gathered on outpatient adherence for all patients. Studies were excluded if they described an intervention characterized by regimen simplification (either unit-of-use packaging or changes in dose frequency or formulation), as they could not be placed into the study categorization, and previous studies have demonstrated their effectiveness4. Studies were excluded if they were written in a language other than English. Those with duration less than 24 weeks were excluded, since cardiovascular medications typically require long-term adherence.
After exclusions, 51 articles (see figure 1) were classified by the mode of delivery of the intervention. Person-independent interventions included (1) mailed, faxed or hand-distributed interventions and (2) interventions delivered via electronic system. Person-dependent interventions included (1) interventions delivered via non-automated phone calls and (2) in-person interventions (classified based on site of delivery, i.e. home, worksite, pharmacy, clinic, or hospital). Person-dependent interventions were further classified based on the level of training required of the person administering the intervention, i.e. (a) trained lay person; (b) nurse; (c) pharmacist; (d) physician; or (e) not specified.
For those studies that incorporated two or more modes of intervention, we assigned categories based on what appeared to be the main mode of intervention. Where categories appeared to be equivalent, we assigned priority in the following order: person-dependent (in person, followed by phone); person-independent (electronic system, followed by mailed, faxed or hand-distributed).
Data were extracted by 2 investigators (S.C. and W.S.) with disagreements resolved by consensus. We assessed a number of variables related to the organization and outcome of studies including: the study design, setting, characteristics of population studied, the number of participants, characteristics of intervention, methods used to measure medication adherence, clinical outcomes, and medication adherence outcomes. We report confidence intervals when available and p values when no confidence intervals are available.
Our search retrieved a total of 6550 articles, of which 168 were reviewed in full and 51 articles met inclusion criteria6-56 (see figure 1; Tables 1, ,2).2). The majority (55%) of interventions were aimed at subjects with hypertension. Other patient populations studied included those with diabetes (8%); coronary artery disease (8%); congestive heart failure (14%); dyslipidemia (10%); 6% of the studies evaluated patients with a mix of cardiovascular and noncardiovascular diseases.
There were three studies6-8 in which the main intervention was delivered via mail, fax or hand-distribution of paper or video information; one6 was successful. Smith followed 907 patients after discharge from a hospital stay for myocardial infarct; 2 letters sent to patients and to primary care providers describing the importance of beta-blocker use yielded improved adherence as measured by pharmacy claims data. Patients receiving mailings were 17% more likely to have 80% of days covered (RR 1.17; 95% CI 1.02-1.29). The two unsuccessful studies described direct patient mailings of written information on hypertension7 or video information on one of four medications (2 blood pressure agents, an antihyperlidemic, and transdermal estrogen)8; Takala defined adherent patients as those still under treatment after two years and Powell studied mean medication possession ratios.
There were 6 studies9-14 that examined a range of electronic interventions including use of electronic pill boxes with programmable reminders, automated phone calls with interactive components, computer-generated individualized interventions, and home automatic blood pressure monitoring. Overall, this group included more positive studies than the mailed/faxed/hand-delivered group (four out of six showed improved adherence).
Rosen14 studied 33 people with diabetes with baseline adherence < 80%. This study tested use of electronic pill caps with a time display and programmable beeper compared to electronic pill caps alone. Participants with programmable beeper pill caps showed improved adherence (80% intervention vs. 60% control, p=0.017).
Friedman10 and Piette13 studied the effect of automated phone calls. Friedman followed 299 hypertensive patients, randomizing patients to an interactive computer-based home telemonitoring system vs. usual care. Patients called in weekly, shared information by phone regarding automated blood pressures and adherence, and received targeted education and motivational counseling (all automated) with responses forwarded to doctors. Adherence, measured by pill count, was not significantly different between groups in unadjusted analysis; adjustment for age, sex, and baseline adherence yielded significant differences (17.7% adherence in intervention vs. 11.7% control, p=0.03). Piette randomized 280 patients to biweekly automated interactive phone calls with structured messages that were adjusted based on patient responses, followed by targeted nurse calls vs. usual care. Differences from Friedman’s intervention include outgoing calls to patients (Friedman required patients to call in) and limited non-automated phone follow-up. Piette found that intervention patients were “substantially less likely to report adherence problems” (based on self-report using modified Morisky scale) (p=0.003, no adherence percentages given) but did not provide baseline adherence (56% reported “any medication problem” at baseline).
Johnson11 followed 404 adults, describing the impact of a computer program designed to mimic the reasoning and problem-solving of humans based on an integrative model of behavioral change (the Transtheoretical Model) and incorporating an individualized computer-generated report mailed to patients. Johnson found an improvement in adherence at 18 months (OR 2.86, p<0.05). Emmett9 studied 217 patients newly diagnosed with hypertension who were randomized in a factorial manner to a computerized decision analysis intervention, mailed video and leaflet, both or neither. Neither the decision analysis nor the mailed video resulted in significant improvement. Marquez-Contreras12 examined use of home automatic blood pressure monitoring (along with a phone call with instructions on use) in 250 patients with uncontrolled or newly diagnosed hypertension. At the end of 6 months, 92% of the intervention group had adherence > 80% (assessed using electronic pill boxes) compared to 74% of the control group (p<0.05).
Eight studies described the use of non-automated phone calls to improve adherence. Calls were made by trained lay people15-16; nurses17; pharmacists18-19; or by a nonspecified caller20-22. Overall, five of these studies showed a nonsignificant improvement in adherence, one20 showed significant improvement but did not clearly define its adherence outcome measure, and two showed significant improvement with clearly defined outcomes.
Neither phone calls by trained lay people nor calls by a nurse yielded significant improvements in adherence. Pharmacist calls showed mixed results. Faulkner18 described twelve weeks of weekly phone calls from a pharmacist for patients after cardiac surgery or angioplasty, and found a significant improvement in adherence as measured by pharmacy refills (60% adherence for phone call group vs. 27% control at 2 years for lovastatin). Mehos19 evaluated the effect of monthly pharmacist phone calls in conjunction with home blood pressure monitoring in a group of hypertensive patients who all received direct clinical services from a pharmacist and found no significant improvement.
Three studies did not specify the identity of the caller. Antonicelli20 described a home telemonitoring intervention managed by a specialized congestive heart failure team that included doctors and nurses, without specifying the actual caller. The study reported significant improvement in adherence (91% intervention group vs. 46%, p<0.03), but did not adequately define how adherence was measured. Sclar21 used phone calls in which adherence was reinforced and monthly mailings delivered to patients with previously treated and newly-diagnosed hypertension, and found statistically significant improvements in both intervention groups (previously treated, 82% adherence intervention vs. 48% control; newly treated 93% vs. 52%; p<0.05 for both). Guthrie22 used phone reminders along with mailings to patients with elevated cholesterol and finds no significant difference in self-reported pravastatin use.
We identified 34 in-person interventions23-56 (see Table 2). These interventions included those conducted in the home23-26, at work-sites27-29, at pharmacies30-35, and at medical facilities36-56. Overall, in-person interventions were more likely (56%) than phone calls (38%) to show significant improvement.
Morisky25 examined the effect of a trained lay person, (a health educator) visiting the home of a patient in order to provide education to family members in addition to patients, and found a significant improvement in self-reported adherence scores. Saunders23 also incorporated trained lay person visits. This study sent reminder letters to patients with hypertension and used patient-recorded blood pressure and medication records, adding fieldworker home visits after 2 reminder letters went unanswered, but did not find significant improvement. Kirscht26 applied a factorial design to multiple educational and behavioral strategies (Table 2) and found a significant improvement in adherence among patients who received nurse-administered home visits aimed at a support person along with the patient (adherence 65% vs. control 55%, p<0.05). Johnson24 examined monthly home visits with or without home blood pressure monitoring (the training of the home visitor was not identified) and found no significant improvement. Both effective in-home interventions incorporated family member involvement, as compared to the two unsuccessful interventions.
The three work-site interventions provided hypertension care by a nurse27-28 or physician29; improvement was shown only in the study in which a nurse was acting with relative autonomy27. Logan27 examined the effect of hypertension care for 457 patients administered by a specially-trained nurse at the worksite. All aspects of blood pressure management were handled directly by the nurse, and the intervention demonstrated improved adherence (68% vs. 49% had at least 80% of medications consumed by pill count).
We identified 6 interventions30-35 that were conducted in pharmacies, all administered by pharmacists. All but one study in this group showed success at improving adherence. Although methods of measuring adherence differed between studies, the successful interventions improved adherence by 7% to 27% (Table 2). Interventions in this group were similar, involving an in-person meeting with a pharmacist in which patient-centered medication histories were obtained, medication knowledge was elicited and expanded upon, and disease and lifestyle teaching was conducted, sometimes with accompanying written information. All six studies lasted between 6 and 12 months.
Lee30 made use of blister packaging in addition to clinical pharmacist meeting and medication education for 159 patients with hypertension, hyperlipidemia, and other diseases, and found 96% adherence at 6 months in intervention patients compared to 69% in controls (p<0.001). Murray31 found an adherence improvement of 11 % (95% CI 5%, 17%) among 314 patients with hypertension over 12 months but noted that the difference declined to a nonsignificant level after the intervention was discontinued. Blenkinsopp32 followed 282 patients with hypertension from community pharmacies over 6 months (63% intervention vs. 50% control, p<0.05). Bouvy35 followed 152 patients with congestive heart failure, defining non-adherence as <80% of days without opening the electronic pill bottle, and found all patients in the intervention group took pills >80% of days, while 86% in the control reached that threshold (RR 0.5, CI 0.4-0.6). Vrijens33 followed 392 patients with hyperlipidemia and found that intervention patients at follow-up had higher adherence (96% vs. 89, p<0.001). Jaffray’s study34 of patients with coronary artery disease used a self-reported score to measure adherence (making a comparison to other studies difficult) and reported very high baseline and follow-up adherence scores. For this reason, the nonsignificant findings in this study may not be representative of the group of pharmacist interventions.
We identified 15 in-person studies36-50 that were conducted in a clinic setting. Among in-person clinic interventions conducted by a lay person or nurse36-39, 50% of studies showed significant improvement over control (Table 2). Whereas in-person pharmacist interventions showed high success rates when conducted in a pharmacy, in-person pharmacist interventions in clinics40-47 showed the lowest rate of success among clinic interventions (38% compared to 50-67% for other in-clinic interventions). All three successful clinic interventions 41, 46-47 were carried out at clinics that also had medication dispensing capabilities. The five unsuccessful clinic interventions40, 42-45 were carried out at primary care offices and neighborhood clinics that did not dispense medications.
Three in-person clinic interventions were carried out by physicians48-50. Although two of these studies were successful49-50, neither used a rigorous method of assessing adherence. Yilmaz49 studied the impact of verbal advice on statin benefits from an “expert physician”. At the end of the study there was an increased likelihood of being on continuous statin therapy (63% intervention vs. 46% control) but the authors do not define the outcome or the data source. Avanzini50 studied 1771 patients with hypertension, randomized to care by doctors who (1) had the opportunity to educate themselves extensively on hypertension and (2) then designed and implemented hypertension management guidelines compared to care by doctors without this experience. At follow-up, 4% of intervention vs. 10% of controls “admitted poor compliance” but the authors give no further information on how this outcome was calculated. Birtwhistle48 randomized patients with hypertension to every 3 vs. every 6 month physician follow-up and found no significant difference in adherence. In-person interventions for patients at the point of hospital discharge51-56 (67% successful) showed lower success rates than interventions carried out in a pharmacy (83%) but higher success than those carried out in a clinic setting (47%). However, while four out of six showed significant improvement in adherence52, 54-56, two of the successful studies had unclear definitions of adherence.
Of the six studies, four recruited in-hospital patients exclusively and followed them after discharge while two studies recruited patients from both in-hospital sites and outpatient clinics.
Tsuyuki51 found a non-significant effect of educational meetings with a research assistant prior to hospital discharge, accompanied by adherence aids, phone and mail follow-up. Krantz52 found a significantly higher rate of beta blocker utilization (96% intervention vs. 48% control) after predischarge nurse counseling and outpatient nurse follow-up, but the term “utilization” was not clearly defined. Two of the three pharmacist interventions54-55 showed significant improvement although Sadik54, who evaluated pharmacist education for congestive heart failure, did not clearly define the way self-reported adherence was calculated. Varma’s study55, a successful pharmacist intervention which defined adherence as 80-120% of all congestive heart failure drugs taken at 12 months, found a significant effect (77% intervention vs. 30% control). Edworthy56 followed 2643 cardiac patients after hospitalization, giving in-hospital counsel on medications and medical conditions by nurses and pharmacists along with video, printed material, and phone follow-up by both a nurse and a pharmacist. Significant improvement in adherence was seen for both beta-blocker (intervention 89% vs. control 80%, p<0.01) and lipid-lowering agents (intervention 83% vs. control 78%, p<0.05).
Our review of interventions to improve adherence to cardiovascular and diabetes medications yielded a highly diverse group of interventions. Several themes arose regarding the effectiveness of different approaches that may inform future intervention development.
Among person-independent interventions, those that used electronic interventions showed promise. Effective electronic interventions included those that were designed to be individualized using either computer-generated algorithms or hierarchically structured messages, and one study effectively combined hierarchical phone messages and targeted phone follow-up by a nurse. Home automatic blood pressure monitoring and programmable pill caps with reminder cues also demonstrated promising results. Adherence interventions delivered via paper or video showed minimal effectiveness unless targeted at a group (in this case hospitalized patients post-myocardial infarct) that was especially likely to be sensitive to the message.
Among person-dependent interventions, the results of phone call interventions were not encouraging. Only a minority were effective. These interventions targeted groups at a time in their lives when they should have been particularly sensitive to the message (e.g., immediately post bypass surgery, percutaneous intervention or hospitalization for congestive heart failure, or after a new diagnosis of hypertension).
In-person interventions yielded some interesting patterns. Home visits, an expensive intervention, were only effective in half the studies identified; both of the effective studies sought to target a family member as support person, while neither of the ineffective studies did so. The data on worksite interventions were limited and no recent studies were identified. Interventions carried out in the pharmacy (all by pharmacists) were almost uniformly effective and were a fairly homogenous group in both the nature of the services rendered and in duration of follow-up. Interestingly, when we looked at the group of interventions carried out in the clinic by pharmacists, only three out of eight were effective. All three of these were carried out in clinics that also had dispensing abilities and therefore may have been more similar to the group of in-person pharmacy interventions. Interventions that targeted patients at the point of hospital discharge were more effective than those that focused on clinic patients, though the lower number of in-person hospital studies should be noted (6 compared to 15 clinic studies).
Person-dependent administration of an adherence intervention can be costly, whether carried out by a lay person, nurse, pharmacist or physician. We found the success rate of person-dependent interventions comparable or lower than that of person-independent interventions. We interpret this result cautiously, given the presence of fewer person-independent interventions overall.
The wide heterogeneity of the adherence intervention studies we identified should prompt us to interpret all comparisons with caution. We included studies with differing populations (patients from different countries and with different cardiovascular diseases; nonadherent vs. all patients; hospitalized vs. outpatient) and we encountered a wide variety of study designs, including some with idiosyncracies that limited their generalizability. In addition, while a detailed discussion of comparative adherence measurement methods is outside the scope of this paper, we found inconsistencies in methods of adherence measurement across the studies reviewed, demonstrated most clearly in our tables. Direct comparison of the magnitude of intervention effect is complicated by this heterogeneity. While we were able to consider some aspects of healthcare setting in our analysis, stratification by health care facility size was not possible due to inconsistencies in reporting. Finally, although over 40% of studies identified showed no significant improvement, publication bias may also be playing a role in our findings.
We suggest that future research focus on (1) the life-events causing increased patient receptiveness to the adherence message (i.e. hospital stays, particularly after a serious cardiac event); (2) the psychological factors present during an acute illness and hospital stay as they relate to a patient’s willingness to modify adherence behavior; (3) in-person pharmacist counsel delivered at the site of medication dispensing (so that arriving for an appointment to discuss adherence can be combined with retrieving the medication); (4) new and innovative ways to take advantage of electronic technologies.
We saw few interventions that capitalized on lay-person social networks, either electronic or in-person. Research on adherence to other medically recommended behaviors including cancer screening has indicated that this may be a promising direction57, and the same may be true for medication adherence interventions.
In conclusion, among interventions to improve adherence to cardiovascular medications, electronic interventions, in-person pharmacist interventions held at a site of medication dispensing, and in-person interventions targeted to patients at the point of hospital discharge showed the highest rates of success. Future studies should explore new electronic approaches and in-person interventions at the site of medication distribution. A focus on identifying times of increased patient receptivity to the adherence message will also be important.
This work was supported by a research grant from CVS Caremark. Josh Liberman and Troy Brennan, both co-authors, are employees of CVS Caremark. All data analysis and evaluation took place at Brigham and Women’s Hospital. Dr. Shrank is supported by a career development award from the National Heart, Lung and Blood Institute (HL-090505).
(“compliance”[tiab] OR “patient compliance”[mesh] OR “patient adherence”[tw] OR “patients adherence”[tw] OR “patient compliance”[tw] OR “medication adherence”[tw] OR “medication compliance”[tw] OR “treatment compliance”[tw] OR “Treatment Refusal”[mesh] OR “patient dropouts”[mesh] OR “treatment refusal”[tw] OR “patient dropout”[tw] OR “patient dropouts”[tw] OR “patient dropped”[tw] OR “drug adherence”[tw] OR “drug compliance”[tw] OR “persistence”[tw] OR ((“compliance”[tw] OR “adherence”[tw]) NOT medline[sb])) AND (“drug therapy”[mesh] OR “drug therapy”[sh] OR “Pharmaceutical Services”[mesh] OR “Medication systems”[Mesh] OR “Drug Utilization Review”[mesh] OR “pharmacies”[mesh] OR “Pharmaceutical Preparations”[mesh] OR “prescription drugs”[tw] OR “prescription drug”[tw] OR “drug therapy”[tw] OR “drug treatment”[tw] OR ((“drug”[tw] OR “drugs”[tw] OR “medicine”[tw] OR “medicines”[tw] OR “medication”[tw] OR “medications”[tw]) NOT medline[sb]) OR “Cardiovascular Agents/therapeutic use”[Mesh] OR “Hypoglycemic Agents/therapeutic use”[Mesh] OR “Antihypertensive agents/therapeutic use”[Mesh] OR “Antilipemic Agents/therapeutic use”[Mesh]) AND (randomized controlled trial[pt] OR controlled clinical trial[pt] OR “randomized controlled trials as Topic”[MeSH Terms] OR “random allocation”[MeSH Terms] OR “single-blind method”[MeSH Terms] OR (“random allocation”[TIAB] NOT Medline[SB]) OR “random allocation”[MeSH Terms] OR “controlled”[TIAB] OR “Evaluation Studies as Topic”[Mesh] OR random*) AND ((“Cardiovascular Diseases”[Mesh] OR “Myocardial Revascularization”[Mesh] OR (“cardiovascular”[tw] NOT medline[sb]) OR “Heart failure”[tw] OR “Myocardial Failure”[tw] OR “Heart Decompensation”[tw] OR “Cardiac Failure”[tw] OR “Ischemic Heart Disease”[tw] OR “Ischemic Heart Diseases”[tw] OR “Myocardial Ischemia”[tw] OR “Myocardial Ischemias”[tw] OR “Coronary Disease”[tw] OR “Coronary Diseases”[tw] OR “Coronary Heart Disease”[tw] OR “Coronary Heart Diseases”[tw] OR “Platelet Aggregation Inhibitors”[Mesh] OR “Diuretics”[Mesh] OR “Diuretics”[Pharmacological Action] OR “Adrenergic beta-Antagonists”[Mesh] OR “Adrenergic beta-Antagonists”[Pharmacological Action] OR “Angiotensin-Converting Enzyme Inhibitors”[Mesh] OR “Angiotensin-Converting Enzyme Inhibitors “[Pharmacological Action] OR “Vasodilator Agents”[mesh] OR “Vasodilator Agents “[Pharmacological Action] OR “Cardiovascular Agents”[Mesh] OR “Cardiovascular Agents “[Pharmacological Action]) OR (“Diabetes Mellitus”[Mesh] OR “diabetes”[tw] OR “Insulin”[Mesh] OR “insulin”[tw] OR “hypoglycemic agents”[Mesh] OR “hypoglycemic agents”[pa] OR “hypoglycemic agent”[tw] OR “antidiabetic”[tw] OR “hypoglycemic drug”[tw] OR “hypoglycemic agents”[tw] OR “antidiabetics”[tw] OR “hypoglycemic drugs”[tw]) OR (“Antihypertensive agents”[Mesh] OR “Antihypertensive Agents”[pa] OR “hypertension”[MeSH Terms] OR “Blood Pressure”[Mesh] OR “high blood pressure”[tw] OR “high blood pressures”[tw] OR antihypertensive[tw] OR hypertension[tw]) OR (“Hyperlipidemias”[Mesh] OR “Antilipemic Agents”[Mesh] OR “Antilipemic Agents”[pa] OR “Hyperlipidemia”[tw] OR “Hyperlipemia”[tw] OR “Hyperlipemias”[tw] OR “Lipidemia”[tw] OR “Lipemia”[tw] OR “Lipemias”[tw] OR “Hyperlipidaemia”[tw] OR “Hyperlipaemia”[tw] OR “Hyperlipaemias”[tw] OR “Lipidaemia”[tw] OR “Lipaemia”[tw] OR “Lipaemias”[tw] OR “Hypercholesterolemias”[tw] OR “Hypercholesteremia”[tw] OR “Hypercholesteremias”[tw] OR “statin*”[tw] OR “Anticholesteremic”[tw] OR “antilipidemic”[tw] OR “antilipemic”[tw] OR “cholesterol lowering”[tw])) AND English[lang]