Patient-centered education in dyslipidemia management: a systematic review

We conducted a systematic review of the published literature in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines [14]. We searched the literature in 3 databases, namely PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Scopus, from inception to April 2021. Additional articles were sought by reviewing references of eligible studies and conducting a search on Google Scholar. Studies were identified with the following search terms: (“patient-centered education” OR synonyms) AND (“dyslipidemia” OR synonyms). We included both medical subject heading (MeSH) terms and free-text terms. Full search terms are shown in Table 1. A filter was applied to the searches on the databases to restrict retrieval of off-target articles, whereby non-English articles were excluded.

By adopting the population, interventions, comparisons, and outcomes (PICO) framework as a template, the inclusion and exclusion criteria presented in Table 2 were applied to set limits to the scope of the review. The population (P) aspect focused on patients with dyslipidemia, which commonly presents with CVD. The intervention (I) was PCE. In determining whether the interventions were patient-centered or not, the definition of patient-centered care by Robinson et al. [15] was adopted. They described the fundamental characteristics of patient-centered care, which are patient involvement in the care and individualization of patient care.

In terms of patient involvement, studies were only included when the authors clearly described active participation from the patients. Some studies described that the patients were actively involved in the care plan, while some studies also mentioned specifically the usage of shared decision-making (SDM). SDM is a method when the patients and health-care professionals make decisions together [17]. The SDM approach aims to ensure that decisions are made based on the patient’s. values and preferences.

Regarding individualization, the education provided in the study must be targeted according to patients’ specific needs. Garvey et al. [18] supported this fundamental characteristic of patient-centered care when describing that one of the goals of patient-centered care is the development of an individualized treatment plan. A study was also included in the review when the researchers used other established patient-centered approaches such as motivational interviewing (MI). Elwyn et al. [17] asserted that MI and SDM are patient-centered methods, and both have been associated with significant improvement in patient outcomes.

These interventions were compared against the usual care (C), such as a didactic or traditional form of education. Finally, the outcome (O) measure in this review is the cholesterol level or any other psychosocial, cognitive, or behavioral outcome reported in the studies. Articles retrieved from the database search were then exported to a reference managing software EndNote X9 (Clarivate), and duplicates were omitted. Because our focus was on randomized controlled trials (RCTs), only studies with the keyword “trial” were included using the smart screening tool in EndNote. The eligible studies underwent preliminary screening by 2 authors independently. The authors screened both titles and abstracts for potential relevance in line with the PICO criteria. Articles that met the predefined eligibility criteria were included for full-text screening and were assessed independently by the 2 authors. Any disagreements between the authors regarding study inclusion were resolved through discussion and consensus with the third author. The inclusion and exclusion criteria are listed in Table 2.

The key characteristics and pertinent information from the eligible studies were extracted and documented. The extracted information included author, year of publication, study location, study design, sample size, patient demographic, and study setting, which are summarized in Table 3. Other information collected were methods of intervention such as the health-care professionals involved, intervention duration, elements involved in the intervention group, and the underlying theories or models being used, summarized in Table 4. The key mechanisms were retrieved if no theories or models were presented by the studies. The outcomes of the intervention were also extracted and are summarized in Table 5. These included psychosocial, cognitive, or behavioral outcomes, cholesterol level, and cardiometabolic outcomes, such as blood pressure (BP), weight, body mass index (BMI), and glycated hemoglobin A (HbA1c). Low-density lipoprotein (LDL) reduction was also compared between the intervention and control groups and is reported in Table 5. For studies that did not measure LDL, the difference in total cholesterol (TC) or triglyceride (TG) level was extracted and reported. Significant information, such as P-value, odds ratio (OR), relative risk (RR), and confidence interval (CI), was also included whenever reported. All values were reported in the intervention group in comparison with the usual care. Other reported outcomes that did not fit any of the criteria mentioned earlier, but were relevant in dyslipidemia management, were also extracted and are described in Table 5.

The Critical Appraisal Skills Programme (CASP) [16]) for RCTs was adopted to evaluate the quality of the studies included. The CASP checklist consists of reviewing the RCT in terms of its basic study design (clarity of research question, appropriateness of randomization method), the methodology (blinding method, study groups), the results (effects of intervention being reported comprehensively, precision, benefits that the study brings), and in terms of the impact of the results to our targeted population. A score of 1 was assigned for each criterion if “yes” was the response, whereas a score of 0 was assigned if the response was “no” or “uncertain.” The review of quality assessment was conducted independently by 1 reviewer and was further assessed by a second reviewer to avoid the risk of bias. Any disagreements were resolved by consensus before finalizing the articles to be included in the study. The criteria assessments for all the included studies are summarized in Table 6.

Figure 1 shows the study selection flowchart. Study selection was based on the PRISMA guidelines [14]. We included 20 studies in this systematic review.

Figure 1.

Table 1 summarizes the findings from the 20 publications of the included studies. Fourteen studies were conducted in European countries, 2 studies were conducted in China, and 1 study each in Jordan, Japan, Hong Kong, and the Netherlands. The majority of studies used a 2-arm RCT, and 4 studies used a 3-arm RCT. The number of participants ranged from 62 to 4,105. The intervention’s duration of included studies ranged from 3 months to 48 months.

The details of interventions are described in Table 2. The interventions involved various health-care professionals, including nurses, pharmacists, physicians, dietitians, kinesiologists, nutritionists, psychologists, and internal medicine specialists. Most of the studies involved nurses in the interventions. Some studies involved single health-care professionals only [3, 19, 20, 30, 31, 33, 34], while others used the collaborative care concept, with ≥2 health-care professionals involved in the interventions. The most used theories in the interventions were the chronic care model, social learning theory, social cognitive theory, transtheoretical theory, health belief model, and MI.

All studies reported cardiometabolic outcomes, such as the BP reading, weight, BMI, or HbA1c, except for 4 studies that measured no cardiometabolic parameters [3, 19, 23, 33]. Most of the studies measured cardiovascular risk factors as one of their outcomes, as either primary or secondary outcomes. Cholesterol indices, namely, the TC, TG, LDL, and high-density lipoprotein (HDL) levels, were reported in 18 studies. Some studies also reported psychosocial and cognitive outcomes, such as perceptions of the quality of their chronic illness care [24], patient activation [19, 29], patient-centered care process [29], self-efficacy [34], perceived control and understanding [27], mental health status [6], and quality of life [35]. The majority of studies reported behavioral outcomes, such as consumption of heart-healthy food, physical activity, smoking status, reduction in saturated fat intake, and medication adherence [6, 20,21,22,23, 25, 27, 29, 31,32,33, 35, 36]. Details of the interventions’ impacts are described in Table 3.

Based on the studies reported, the findings on cholesterol levels comprised both positive and negative outcomes. Other outcomes measured, such as psychosocial or cognitive outcomes showed promising results in most studies. Improvement in cholesterol level was reported in 11 studies. Significant reductions in all cholesterol-related parameters (TC, LDL, and TG levels), but no significant change in HDL, were found by 2 studies [24, 31]. However, a few other studies [19, 26, 30,31,32,33, 36] reported any 1 of the cholesterol levels (TC/LDL/TG) as improving significantly. Only 1 study reported significant improvement in the HDL level [33]. Most studies reported positive outcomes in the aspect of psychosocial, cognitive, or behavioral outcomes. Significant improvements in other cardiometabolic markers, such as BP, weight, BMI, and HbA1c, were also reported [6, 20, 21, 22, 24, 27, 30, 31, 35].

Firstly, the desired outcome achieved might be due to the underlying theory used by the researchers. Studies that reported a significant improvement in cholesterol levels (TC/TC/LDL) used MI as one of the key concepts [6, 21, 24, 29, 30, 36]. MI is a communication style that uses specific techniques such as reflective listening, SDM, and eliciting change talk [37]. In addition, the PCE utilizing MI was able to significantly affect the smoking status, which was associated with an improvement in the CVD risk score. Besides smoking status, MI was also beneficial in improving behavioral outcomes, such as physical activity and self-monitoring [21]. Nevertheless, other studies using the MI technique showed no significant improvement in cholesterol levels but achieved significant improvement in psychosocial or cognitive outcomes, such as patient activation [29].

Many confounding factors contribute to the success of the MI intervention, such as health-care professionals’ skills, differences in participants’ characteristics, and time frame of the study. To conduct MI, health-care professionals need to be highly trained. This hypothesis is supported by a study conducted by Allen et al. [24], which suggested that use of MI coupled with appropriate training of health-care professionals would lead to the successful achievement of the desired outcomes. Their study found that using certified nurse practitioners and MI training was associated with significant improvement in psychosocial or cognitive outcomes, cholesterol levels, and measurements of SBP, DBP, and HbA1c [24]. Although MI is a proven and practical method in patient-centered care, as mentioned by Elwyn et al. [16], it is also important for future studies to emphasize the factors that may contribute to the success of the MI, such as the incorporation of health-care professionals’ training.

For behavioral outcomes, many studies reported positive findings in terms of physical activity [6, 21, 25, 27, 31], consumption of healthy foods [6, 20, 25, 31, 33], self-monitoring frequency [23], medication adherence [28, 30, 31], self-care activities [30], and smoking status [36]. Other studies [6, 22, 31, 32, 35] found no significant impact on the smoking status of the participants, except for 1 study by Daumit et al. [36]. This discrepancy may have occurred for a few reasons. A reason for the success of the intervention described by Daumit et al. [36] is the introduction of a point reward system. The investigators successfully educated the patients about smoking cessation, even though encouraging smokers to quit is extremely difficult. In the study, the participants were given points for attendance and behavioral change for smoking cessation. Finally, the points were exchanged with small reward items [36].

This proved that patients might be more motivated by a rapid reward system rather than the promising long-term rewards, such as their health outcomes. This hypothesis is supported by a study by Licthman et al. [38], who described that patients with dyslipidemia are less motivated to improve their cholesterol levels because of the asymptomatic nature of the disease. The motivation of patients with diabetes mellitus is different in that patients can quickly feel the changes in managing their symptoms [38]. Therefore, future studies should incorporate a rapid reward system as an alternative to boost patients’ motivation, especially in promoting behavioral change that demands a lot of effort and sacrifice.

Consumption of heart-healthy food may lead to significant improvement in HDL levels. However, none of the studies reported significant improvement in HDL levels, except 1 study [33]. It is important to note that improvement in HDL levels could not be achieved solely by taking a lipid-lowering therapy, unlike LDL levels, which decrease with the help of pharmacological treatment. By contrast, HDL level improvement requires a combination of aggressive behavioral interventions, such as a healthy lifestyle, diet, and exercise. The expected significant increment of HDL achieved by Mok et al. [33] was due to the aggressive dietary intervention of the nurses involved in the study. The nurses emphasized appropriate dietary intake and encouraged the patients to eat heart-healthy food. Consequently, there were significant differences in the consumption of saturated fats and healthy food choices. The importance of achieving desirable levels of HDL, TC, LDL, and TG should be emphasized.

Collaborative care is a method in which many experts collaborate to improve the quality of health care [39]. Health-care professionals from various disciplines work together as a single unit with centralized communication and coordination to potentially improve patient outcomes [40]. Of the 20 studies included, 12 used collaborative care methods. Goyer et al. [6] involved the highest number of health-care professionals: nutritionists, psychologists, kinesiologists, nurses, and physicians. This collaborative care approach resulted in significant improvement in the psychosocial or cognitive aspect of mental health status. In addition, the behavioral outcomes of calorie intake and physical activities showed significant improvement, together with TG and TC levels.

Ho et al. [28] conducted a study involving primary care clinicians and pharmacists to improve medication adherence among patients with acute coronary syndrome after hospital discharge. The pharmacists provided education and guided the patients to adhere to their medications. The primary care clinicians were then notified about their patients’ medication adherence status using a computerized medical record. The pharmacists’ contact number was also included so that they could be reached for any further questions or clarifications. After 12 months of such intervention, significant improvement in medication adherence was observed [28].

In terms of the pharmacists’ role, medication adherence is one of the crucial components in dyslipidemia management. Medication adherence is an outcome measured in some studies, but the methods of measuring adherence differ between studies. This difference in the method may result in outcome variability. Thus, it is rather challenging to make a generalized conclusion about medication adherence. Some studies used medication refill data from the pharmacy to measure medication adherence [28]. However, the record taken from the pharmacy refill data may be questionable as patients might not take the medication as prescribed, although they did not miss collecting the medications at the pharmacy [39].

Jarab et al. [30] measured medication adherence via self-reports from the patients, and significant improvement was observed. The authors reported that recall bias and social desirability might have occurred during the self-reporting [30]. Despite the disadvantage of self-reporting, Fortin et al. [21] mentioned that this technique is consistent with a patient-centered approach. Byrne et al. [27] measured medication adherence using a biochemical urine test and found no significant differences between groups. A biochemical urine test identifies the level of statin in the urine and is only applicable to test for atorvastatin [27].

Collectively, various methods of adherence measurement may affect the findings. To date, measuring medication adherence by using a biochemical urine test seems to be one of the alternatives. However, information regarding the cost and time constraints for implementing this method is scarce [27]. Various methods of measurement, such as self-reporting, records taken from pharmacy refill data, or biochemical urine tests, have their advantages and disadvantages. In highlighting the pharmacist’s role, future studies in measuring medication adherence should be conducted based on resource availability, drugs involved, and patients’ preferences.

The success of collaborative care in the interventions described earlier by 2 studies [6, 28] was associated with focused education content based on the health-care professionals’ expertise. The collaborative care or multidisciplinary approach should be extended to patients with CVD to optimize their care and risk reduction [6]. Future studies may consider the element of collaborative care to optimize the roles of different health-care professionals who have similar aims in improving patients’ overall clinical outcomes.

Duration of intervention can contribute to the efficacy of PCE. PCE has been used to reduce CVD risk among patients [36]. Significant improvement in smoking status was observed after 18 months. The effectiveness of the intervention, which leads to behavioral change, is possibly due to its longer duration. An individualized counseling session was conducted weekly or every 2 weeks. Systematic follow-ups played an important role in determining the effectiveness of the intervention. The time frame of the reported studies varies between 2 months and 4 years. In one of the studies reported by Maindal et al. [32], there was no significant difference in the CVD risk levels after 3 years of interventions. Although outcomes were measured after 3 years, there were no systematic follow-ups implemented before measuring the outcomes. Therefore, the authors [32] suggested providing gradual sessions at 1 month, 2 months, and 3 months after the core interventions.

Mok et al. [33] emphasized that systematic follow-ups are important. The authors highlighted that follow-ups conducted via telephone calls were a key component that led to significant positive dietary changes. The telephone calls were made fortnightly for the 2-month duration [33]. This assertion is supported by Jarab et al. [30], who found significant differences during the 6 months of their study duration. However, they were unsure of the impact of the intervention beyond that time [30]. Future studies should be conducted to explore the minimum duration of follow-up needed to sustain the desired outcomes. Systematic follow-ups, either face-to-face or by telephone calls, are crucial to ensure the effectiveness of the intervention.

The role of family members throughout the intervention period has been highlighted [31]. Recruitment of family members can encourage social support for the patients [41]. If there is no support available through a family, finding supporting individuals or groups is important for the patients to initiate behavioral change [41]. Dunbar et al. [42] asserted that social support is associated with better CVD outcomes. They indicated that family support is linked with the adoption and maintenance of healthy behaviors.

Kitko et al. [43] emphasized the role of caregivers in individuals with heart failure. They highlighted that many individuals with heart failure depend on support from their partners, families, friends, or neighbors to help them manage chronic diseases. Strom and Egede [44] also asserted that social support also significantly improves patients’ motivation. Therefore, the active involvement of family members or other individuals to provide social support to the patients throughout the intervention is strongly encouraged.

E-health has been discussed in the literature for more than a decade. E-health is an emerging field that refers to health services and information that are conveyed or enhanced through the Internet or related technologies [45]. Snyder et al. [46] mentioned that information technology is able to promote patient-centered care by providing a mechanism for the patient to share their information with health-care professionals. Wong et al. [47] reported that online counseling might serve as an alternative to reach those who remain untreated.

Moessner and Bauer [48] found that an Internet-based service reached a substantial proportion of individuals with eating disorders. More than half of the participants (57.3%) said that the Internet was their first choice for seeking professional assistance. The participants indicated that they would not have shown behavioral changes had it not been for the online services [48]. Many articles have explored online counseling for mental health patients, but limited research has been done on managing CVD patients.

Of the 20 articles included in this review, only 1 study described an e-health intervention [3]. Despite the promising outcomes of this intervention, Eaton et al. [3], who conducted a study on utilizing e-health or electronic devices to improve cholesterol management, did not find any significant improvement in any of the outcomes. The authors considered that the e-health tools might be improved in the future by making them more user-friendly. Before 2011, when the study was conducted, the patients might not have been familiar with technology and might have found it difficult to use, resulting in minimal benefits. Today, people are more familiar with technology, especially after the coronavirus disease-2019 (COVID-19) pandemic. O’Leary [49] found that there was a rapid demand for efforts to use technology to cope with the damage caused by COVID-19. This opportunity should be utilized by the health-care system, whereby online methods should be implemented as much as possible when appropriate. When more people are able to adapt to technology, the delivery of technology-assisted online counseling continues to grow [47]. Therefore, looking at the opportunity of available technology and readiness of patients, education using online platforms may produce a promising result. Online counseling may replace telephonic or face-to-face counseling for systematic follow-ups for patients with CVD and help particularly in managing their dyslipidemia. Online counseling also may enhance the patient–doctor relationship, which is a dimension in the patient-centeredness concept highlighted by Stewart et al. [12]. However, the performance of the utilized software and digitalized platforms should be carefully examined to ensure that they can achieve the objective of patient-centered care.