Address Medication Nonadherence Research Articles

'What Happened?': Perceptions of Patients with Hypertension of Conflicting Results between Self-Reported Medication Adherence and Chemical Adherence Testing: A Qualitative Study.

To explore the perceptions of outpatients with hypertension regarding the conflicting results between their self-reported medication adherence and chemical adherence testing. An exploratory generic qualitative study design with semi-structured interviews was conducted. Thirteen adult patients being treated with antihypertensives were interviewed. Patients had a negative chemical adherence test for at least one prescribed antihypertensive, while they reported to adhere to their medication. Audio-recorded interviews were thematically analyzed. Six themes emerged: (1) becoming frustrated with medication intake, (2) being uncomfortable with addressing medication nonadherence, (3) feeling ashamed and angry about their nonadherence, (4) feeling falsely accused of nonadherence, (5) experiencing results as a wakeup call and (6) wanting to be heard and listened to. Participants reacted differently to the adherence test results. Two distinct groups were identified among the participants: the first group felt shameful, disappointed, and angry at themselves for being nonadherent; the second group felt falsely accused and rejected the adherence test results. No differences between both groups were found in their reasons for becoming frustrated with medication intake and their behavior after the adherence test results. Patients felt that communication with clinicians is key in the treatment support of patients with hypertension. Clinicians need to consider the reasons for nonadherence and the different responses of patients to the chemical adherence test results in their support to optimize treatment for patients with hypertension.

Investigating medication adherence among Taiwanese patient with hypertension, hyperlipidemia, and diabetes: A pilot study using the Chinese version of a Two-Part Medication Nonadherence Scale and the NHI MediCloud system.

This pilot study aimed to investigate medication nonadherence among Taiwanese patients with diabetes, hypertension, and hyperlipidemia using the Chinese version of the Two-Part Medication Nonadherence Scale (C-TPMNS) and the National Health Insurance (NHI) Medicloud system. The study revealed insights into the factors contributing to nonadherence and the implications for improving patient adherence to medications for chronic conditions. However, the small sample size limits the generalizability of the findings. Additionally, the study identified the need for further research with larger and more diverse samples to validate the preliminary findings. The study conducted surveys individuals in central Taiwan who received three-high medications and those who returned expired medications from chain pharmacies. A structured questionnaire including the C-TPMNS was administered, and additional data on medical history and HbA1c, LDL, and blood pressure levels were collected from the NHI Medicloud system. Data analysis was performed using multiple ordered logistic regression and Wald test methods. Setting interpretation cutoff point to determine medication nonadherence. The study found that 25.8% of participants were non-adherent to prescribed medications. Non-adherent individuals had significantly higher systolic blood pressure (SBP ≥ 140 mmHg) than adherent participants. Non-adherence was also associated with factors such as lower education, single status, living alone, abnormal glucose postprandial concentration, and triglyceride levels. The C-TPMNS demonstrated good reliability (Cronbach's alpha = 0.816) and validity (area under the ROC curve = 0.72). The study highlighted the complexity of medication nonadherence with diverse determinants and emphasized the importance of tailored interventions. The findings underscored the need for region-specific research to comprehensively address medication nonadherence, especially focusing on adherence to medications for hypertension, hyperlipidemia, and diabetes. The study also identified the need for larger, more diverse studies to validate and expand upon the initial findings and emphasized the importance of pharmacist interventions and patient empowerment in managing chronic conditions and improving overall health outcomes.

Beneficial Effect of Remote Glucose Monitoring and Computerized Insulin Dose Adjustment Algorithms Independent of Insulin Dose Increases in Sizeable Minorities of Patients.

This article describes a program through which interactions every 2-3 weeks between patients and primary care clinicians (PCCs), with recommendations based on analysis of remote glucose monitoring by computerized insulin dose adjustment algorithms, significantly improved diabetes control. Insulin doses increased by 30% in the majority of patients. A sizeable minority (36%) had a decrease or no increase in insulin doses, but still showed an improvement in diabetes control. Frequent interactions allowed PCCs the opportunity to recognize and address medication nonadherence.

Telephone-based social health screening by pharmacists in the nonadherent Medicare population.

BACKGROUND: Unmet social health needs are associated with medication nonadherence. Although pharmacists are well positioned to address medication nonadherence, there is limited experience with screening for and addressing social health needs. OBJECTIVES: To compare the prevalence of social health needs among Medicare patients with higher vs lower social health risk using a predictive model. To also evaluate pre-post changes in medication adherence and health care use following a pharmacist-initiated social health screening. METHODS: A social health screening workflow was implemented into a routine pharmacist adherence program at an integrated health care delivery system. The social health screening was conducted during medication adherence outreach phone calls with Medicare members who were overdue for statin, blood pressure, or diabetes medications. We developed a social health need predictive algorithm to flag higher-risk patients and tested this algorithm against a random subset of lower-risk patients. Screening conversations were guided by a focus group that developed open-ended questions to identify social health needs. Comparisons in social health needs were made between higher- and lower-risk patients. Use and adherence outcomes were compared pre and post for patients who accepted a referral to social health resources and patients who declined a referral. RESULTS: 1,217 patients were contacted and screened for social health needs by pharmacists. Patients flagged by the social risk algorithm were more likely to report social health needs (28.7% vs 12.7% in the unflagged group; P < 0.01). Commonly reported needs included transportation (43%), finances (34%), caregiving (22%), mental health (11%), and food access (10%). 221 patients accepted a referral to a central resource website and call center that connected patients to local services. One year after screening dates, patients who did not accept a referral spent more time in the hospital (mean change +0.7 days, SD = 7.3, P < 0.01), had fewer primary care visits (mean change -0.5 visits, SD = 6.5, P < 0.01), and had a shorter length of membership (mean change -0.4 months, SD = 1.9, P < 0.01). Patients who accepted a referral had increased statin adherence (62.3% adherent pre vs 74.7% post, P = 0.02). CONCLUSIONS: We implemented a workflow for pharmacists to screen for social health needs. The social health need prediction model doubled the identification rate of patients who have needs. Intervening on social health needs during these calls may improve statin adherence and may have no adverse effect on health care utilization or health plan membership. DISCLOSURES: Social health risk predictive model development and validation was funded by the Agency for Healthcare Research and Quality (AHRQ R18HS027343).

Leveraging Electronic Health Record Technology and Team Care to Address Medication Adherence: Protocol for a Cluster Randomized Controlled Trial.

Low medication adherence is a common cause of high blood pressure but is often unrecognized in clinical practice. Electronic data linkages between electronic health records (EHRs) and pharmacies offer the opportunity to identify low medication adherence, which can be used for interventions at the point of care. We developed a multicomponent intervention that uses linked EHR and pharmacy data to automatically identify patients with elevated blood pressure and low medication adherence. The intervention then combines team-based care with EHR-based workflows to address medication nonadherence. This study aims to describe the design of the Leveraging EHR Technology and Team Care to Address Medication Adherence (TEAMLET) trial, which tests the effectiveness of a multicomponent intervention that leverages EHR-based data and team-based care on medication adherence among patients with hypertension. TEAMLET is a pragmatic, cluster randomized controlled trial in which 10 primary care practices will be randomized 1:1 to the multicomponent intervention or usual care. We will include all patients with hypertension and low medication adherence who are seen at enrolled practices. The primary outcome is medication adherence, as measured by the proportion of days covered, and the secondary outcome is clinic systolic blood pressure. We will also assess intervention implementation, including adoption, acceptability, fidelity, cost, and sustainability. As of May 2023, we have randomized 10 primary care practices into the study, with 5 practices assigned to each arm of the trial. The enrollment for the study commenced on October 5, 2022, and the trial is currently ongoing. We anticipate patient recruitment to go through the fall of 2023 and the primary outcomes to be assessed in the fall of 2024. The TEAMLET trial will evaluate the effectiveness of a multicomponent intervention that leverages EHR-based data and team-based care on medication adherence. If successful, the intervention could offer a scalable approach to address inadequate blood pressure control among millions of patients with hypertension. ClinicalTrials.gov NCT05349422; https://clinicaltrials.gov/ct2/show/NCT05349422. DERR1-10.2196/47930.

Pediatric subspecialty healthcare providers' views of recruitment during a randomized controlled trial of a mobile health intervention

BackgroundRandomized clinical trials (RCTs) enrolling pediatric populations often struggle with recruitment. Engaging healthcare providers in the recruitment process may increase patients' and caregivers' willingness to participate in research. The purpose of this study was to understand the perspectives of pediatric subspecialty healthcare providers considering recruiting patients to participate in an mobile health (mHealth) RCT. MethodsWe conducted 9 semi-structured interviews and 1 focus group with a total of N = 11 providers from various disciplines before the initiation of an mHealth RCT addressing medication nonadherence. Then, we conducted 5 follow-up interviews and 1 follow-up focus group with a total of 8 of these providers several months later. We used thematic analysis to generate themes describing providers' views of the RCT and patient recruitment. ResultsProviders indicated that they were willing to recruit for this study because they believed that the intervention sought to address a significant problem. They also thought it made sense to intervene using technology for this age group. However, many providers thought that certain patients (e.g., those with mild, shorter-lasting adherence difficulties) were the most appropriate to recruit. They described how keeping the trial front of mind facilitated recruitment, and they advised researchers to use strategies to promote their ongoing awareness of the study if conducting similar research in the future. ConclusionPediatric healthcare providers are important stakeholders in mHealth intervention research. Engaging them in participant recruitment is a complex endeavor that might promote patient enrollment, but their views of research and demanding clinical roles are important to understand when designing study procedures.

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Adherence patterns to oral hypoglycemic agents among primary care patients with type 2 diabetes

AimsTo examine patterns of adherence to oral hypoglycemic agents among primary care patients with type 2 diabetes mellitus and to assess whether these patterns were associated with baseline intervention allocation, sociodemographic characteristics, and clinical indicators. MethodsAdherence patterns were examined by Medication Event Monitoring System (MEMS) caps at baseline and 12 weeks. Participants (n = 72) were randomly allocated to a Patient Prioritized Planning (PPP) intervention or a control group. The PPP intervention employed a card-sort task to identify health-related priorities that included social determinants of health to address medication nonadherence. Next, a problem-solving process was used to address unmet needs involving referral to resources. Multinomial logistic regression examined patterns of adherence in relation to baseline intervention allocation, sociodemographic characteristics, and clinical indicators. ResultsThree patterns of adherence were found: adherent, increasing adherence, and nonadherent. Participants assigned to the PPP intervention were significantly more likely to have a pattern of improving adherence (Adjusted Odds Ratio (AOR)= 11.28, 95% confidence interval (CI)= 1.78, 71.60) and adherence (AOR=4.68, 95% CI=1.15, 19.02) than participants assigned to the control group. ConclusionPrimary care PPP interventions incorporating social determinants may be effective in fostering and improving patient adherence.

Feasibility of Exenatide, a GLP-1R Agonist, for Treating Cocaine Use Disorder: A Case Series Study.

Cocaine use remains a serious public health problem associated with a marked increase in overdose deaths in the past decade. No medications have yet been proven to be effective for the treatment of cocaine use disorder (CUD). Among the highly promising medications have been glucagon-like peptide 1 receptor agonists (GLP-1RA) that are currently used for the treatment of type 2 diabetes mellitus and weight management. Preclinically, GLP-1RAs have been shown to attenuate cocaine self-administration, however, this has not yet been demonstrated in a human laboratory study. The GLP-1RA extended-release exenatide is given as a once-weekly injection, which may be clinically advantageous for addressing medication nonadherence among individuals with CUD. Here, we assess feasibility and safety by reporting on 3 cases of patients with CUD who received 6 weeks of exenatide 2 mg subcutaneously once-weekly in an open-label fashion, along with standard individual drug counseling. We observed excellent attendance and compliance, along with positive end-of-study satisfaction ratings. The medication was well tolerated and without unexpected or severe adverse events. Results for cocaine use and related clinical effects were more mixed, yet encouraging. Future empirical testing of exenatide for treating CUD should utilize a randomized controlled trial design and longer treatment duration.

Medication Barriers and Adherence: Experiences of Pediatric Transplant Recipients.

This study examined associations between scores on the Adolescent Medication Barriers Scale (AMBS) and the Parent Medication Barriers Scale (PMBS), patient and family factors, and medication adherence outcomes. Patients and caregivers from a pediatric solid organ transplantation (SOT) program were recruited for participation. Pediatric SOT recipients ages 10 to 21 years were eligible for participation. Analyses included reliability analyses and regression modeling with posttransplant medication adherence measured by Medication Level Variability Index scores. Seventy-three patients and caregivers completed an AMBS or PMBS questionnaire. Patient-caregiver inter-rater reliability was poor to fair. Greater medication barriers were reported among younger and female patients and families with more children. AMBS scores predicted greater nonadherence, while the PMBS was not predictive of adherence. Results point to the difficulty of assessing barriers to medication adherence and the lack of agreement between adolescent patients and caregivers. AMBS scores were more closely aligned with medication nonadherence, whereas PMBS scores may have been more influenced by family social factors. Adolescent reports of medication barriers may offer multidisciplinary transplant teams greater clinical utility when addressing these challenges with patients. Transplant social workers and psychologists should engage adolescents and caregivers in efforts to address medication nonadherence.

Analysis approaches to address treatment nonadherence in pragmatic trials with point-treatment settings: a simulation study

BackgroundTwo-stage least square [2SLS] and two-stage residual inclusion [2SRI] are popularly used instrumental variable (IV) methods to address medication nonadherence in pragmatic trials with point treatment settings. These methods require assumptions, e.g., exclusion restriction, although they are known to handle unmeasured confounding. The newer IV-method, nonparametric causal bound [NPCB], showed promise in reducing uncertainty compared to usual IV-methods. The inverse probability-weighted per-protocol [IP-weighted PP] method is useful in the same setting but requires different assumptions, e.g., no unmeasured confounding. Although all of these methods are aimed to address the same nonadherence problem, comprehensive simulations to compare performances of them are absent in the literature.MethodsWe performed extensive simulations to compare the performances of the above methods in addressing nonadherence when: (1) exclusion restriction satisfied and no unmeasured confounding, (2) exclusion restriction is met but unmeasured confounding present, and (3) exclusion restriction is violated. Our simulations varied parameters such as, levels of adherence rates, unmeasured confounding, and exclusion restriction violations. Risk differences were estimated, and we compared performances in terms of bias, standard error (SE), mean squared error (MSE), and 95% confidence interval coverage probability.ResultsFor setting (1), 2SLS and 2SRI have small bias and nominal coverage. IP-weighted PP outperforms these IV-methods in terms of smaller MSE but produces high MSE when nonadherence is very high. For setting (2), IP-weighted-PP generally performs poorly compared to 2SLS and 2SRI in term of bias, and both-stages adjusted IV-methods improve precision than naive IV-methods. For setting (3), IV-methods perform worst in all scenarios, and IP-weighted-PP produces unbiased estimates and small MSE when confounders are adjusted. NPCB produces larger uncertainty bound width in almost all scenarios. We also analyze a two-arm trial to estimate vitamin-A supplementation effect on childhood mortality after addressing nonadherence.ConclusionsUnderstanding finite sample characteristics of these methods will guide future researchers in determining suitable analysis strategies. Since assumptions are different and often untestable for IP-weighted PP and IV methods, we suggest analyzing data using both IP-weighted PP and IV approaches in search of a robust conclusion.

Approach to a patient with hypertensive urgency in the primary care setting.

Patients who present to an outpatient office with hypertensive urgency-or severely elevated BP without evidence of acute target organ damage-can be safely treated in the ambulatory setting by initiating or reestablishing long-acting oral antihypertensive medications, addressing medication nonadherence, and reviewing precipitating factors.

A review of features and characteristics of smart medication adherence products

Background:Smart medication adherence products (smart MAPs) capture and transmit real-time medication intake by using various means of connectivity, allowing for remote monitoring. Numerous such products with different features are available to address medication nonadherence. A comparison of the features of these products is needed for clinical decision-making. Therefore, the objective of this review was to compare smart MAPs available for in-home use.Methods:We searched grey and published literature and videos to identify smart MAPs. To be considered smart, products required 2 features: connectivity (the ability for collected data to exist outside the physical device) and automaticity (the ability for data to be analyzed or processed automatically). Products were excluded if product descriptions were not available in English, not for in-home use and unable to dispense medications.Results:Of the 51 products identified, 38 commercially available and 13 prototypes met the definition. Of these, 75% (n = 38) contained alarms, 24% (n = 12) were unit-dose, 63% (n = 32) were multidose, 43% (n = 22) had locking features, 41% (n = 21) were portable and 88% (n = 45) sent notifications to patients. The cost of marketed products, excluding subscriptions, ranged from $10 to $1500 USD. Some products required a monthly (n = 16) or yearly (n = 1) subscription ranging from $10 to $100 USD.Discussion:There is a growing market of smart MAPs for in-home patient use with variable features. Clinicians can use these features to identify and recommend products according to the specific needs of their patients to address medication adherence. Can Pharm J (Ott) 2021;154:xx-xx.

Promoting a Shared Medication Adherence Practice: A Call to Action

Medication nonadherence exists among most patients and leads to increased morbidity, medical costs, and unnecessary hospitalizations. This study trained primary care staff at an urban Federally Qualified Health Center to address medication nonadherence. It included a single educational workshop that described medication nonadherence, demonstrated validated assessment tools to formulate evidence-based interventions, and incorporated motivational interviewing techniques. Evaluations conducted at pre-post training and at 4 weeks showed an increase in staff knowledge (29%), self-confidence (46%), and self-reported practice change (77%). Our findings suggest this training resulted in practice change through increased patient engagement, shared decision making, and strengthening patient-provider trust.

Medication nonadherence monitoring and management in adult kidney transplantation: A survey of practices and perceptions at US‐based transplant programs

AbstractIntroductionMedication nonadherence is a predominant contributor to graft loss, however little is known about currently utilized strategies by transplant centers to monitor or manage this issue.ObjectiveUtilizing standard surveying and analysis techniques, assess health care professionals' (HCPs) perceptions of the scope and scale of medication nonadherence and strategies used to manage this issue at US‐based transplant centers.MethodsA survey to gain insights into pre‐ and post‐transplant medication nonadherence screening, mitigation strategies and perceptions of HCPs regarding nonadherence was developed through an iterative process. This was followed by broad distribution to HCPs at US‐based adult kidney transplant centers. Standard descriptive and comparative statistics were utilized to assess responses and develop inferences and themes from participant responses.ResultsOne hundred and ninety HCPs from 99 centers responded; 56.5% felt medication nonadherence was a major contributor to post‐transplant rejection and graft loss, while 71.1% acknowledged not having a prospective medication nonadherence screening protocol. Of those centers with a protocol, screening declined over time (first post‐transplant month: 92.7%; after 1‐year: &lt;50%). Medication nonadherence management strategies also declined over time (initial transplant stay: 76%; after 1‐year: 6.5%). Few HCPs (24.1%) felt their centers had adequate resources to implement management strategies. Barriers to implement strategies included large patient volume (68.2%) and lack of a validated, easy to use, noninvasive medication nonadherence measure (65.9%).ConclusionWhile HCPs at US‐based adult kidney transplant programs feel that medication nonadherence is a significant issue, the use of systematic processes aimed at prospectively identifying and addressing medication nonadherence is uncommon. Opportunities exist to better address medication nonadherence in kidney transplantation, using feasible noninvasive monitoring and management strategies that align with current HCPs workflow and logistic constraints.

Mapping Modifiable Determinants of Medication Adherence in Bipolar Disorder (BD) to the Theoretical Domains Framework (TDF): A Systematic Review

Background: Around 40% of patients with bipolar disorder (BD) are non-adherent to prescribed medication leading to relapse, hospitalisation and increased risk of suicide. Lack of progress in addressing medication non-adherence may be partly attributable to the limited understanding of the modifiable determinants of adherence that should be targeted by interventions. We aimed to synthesise the modifiable determinants of medication adherence in BD and map them to the Theoretical Domains Framework (TDF). Method: We searched CINAHL, Cochrane Library, Embase, LILACS, Medline, PsychINFO, PubMed in Feb 2020 using search terms Treatment Adherence and Compliance, “Bipolar Disorder” and Psychotropic Drugs. We included qualitative and quantitative primary studies reporting modifiable determinants of medication adherence in BD. Two reviewers independently screened retrieved studies, extracted modifiable determinants of adherence and coded them to the TDF. The study protocol was registered with PROSPERO [CRD42018096306] and published in the BMJ Open [ http://dx.doi.org/10.1136/bmjopen-2018-026980 ]. Findings: We included 57 studies involving 32894 participants. A majority of studies (n=50) explored modifiable determinants from the perspectives of patients but none included carers. Clinicians reported a narrow range of modifiable determinants, eight themes of determinants mapped to seven TDF domains, compared to 33 themes reported by patient studies covering 11 TDF domains. The TDF domains represented in the greatest number of studies were ‘Environmental context and resources’ (67% of studies) and ‘Beliefs about consequences’ (62%). Examples of the determinants mapped to these domains include the experience of side effects (49% of studies) and beliefs about positive/negative effects of medication (36%). Only patient studies reported the ‘Memory, attention and decision process’ and ‘Emotion’ domains. These domains included modifiable determinants such as forgetfulness (31% of studies) and fear of addiction (20%). Interpretation: The review highlights that clinicians may be underappreciating the full range of modifiable determinants and thus may not be providing the adherence support reflective of patients’ need. Since each TDF domain has been linked to behavior change techniques (BCTs) this study provides foundation for the development of an adherence tool for clinicians to provide tailored BCTs to support adherence. Funding Statement: Asta Ratna Prajapati is funded by Health Education England / National Institute for Health Research (NIHR), (Clinical Doctoral Research Fellowship) (NIHR reference number: ICA-CDRF-2017-03-054) for this research project. Declaration of Interests: None.

A systematic overview of systematic reviews evaluating medication adherence interventions.

To systematically summarize evidence from multiple systematic reviews (SRs) examining interventions addressing medication nonadherence and to discern differences in effectiveness by intervention, patient, and study characteristics. MEDLINE, the Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects were searched for papers published from January 2004 to February 2017. English-language SRs examining benefits of medication adherence interventions were eligible. Inclusion was limited to adult patients prescribed medication for 1 of the following disease conditions: diabetes and prediabetes, heart conditions, hypertension and prehypertension, stroke, and cognitive impairment. Non-disease-specific SRs that considered medication adherence interventions for older adults, adults with chronic illness, and adults with known medication adherence problems were also included. Two researchers independently screened titles, abstracts, and full-text articles. They then extracted key variables from eligible SRs, reconciling discrepancies via discussion. A MeaSurement Tool to Assess systematic Reviews (AMSTAR) was used to assess SRs; those with scores below 8 were excluded. Conclusions regarding intervention effectiveness were extracted. Grades of Recommendation, Assessment, Development and Evaluation (GRADE) methodology was applied to assess evidence quality. Of 390 SRs, 25 met the inclusion criteria and assessed adherence as a primary outcome. Intervention types most consistently found to be effective were dose simplification, patient education, electronic reminders to patients, and reduced patient cost sharing or incentives. Of 50 conclusions drawn by the SRs, the underlying evidence was low or very low quality for 45 SRs. Despite an abundance of primary studies and despite only examining high-quality SRs, the vast majority of primary studies supporting SR authors' conclusions were of low or very low quality. Nonetheless, health system leaders seeking to improve medication adherence should prioritize interventions that have been studied and found to be effective at improving patient adherence, including dose simplification, education, reminders, and financial incentives.

Architecting Process of Care: A randomized controlled study evaluating the impact of providing nonadherence information and pharmacist assistance to physicians.

To test the impact of connecting physicians, pharmacists, and patients to address medication nonadherence, and to compare different physician choice architectures. The study was conducted with 90 physicians and 2602 of their patients on medications treating chronic illness. In this cluster randomized controlled trial, physicians were randomly assigned to an arm where the physician receives notification of patient nonadherence derived from real-time claims data, an arm where they receive this information and a pharmacist may contact patients either by default or by physician choice, and a control group. The primary outcome was resolving nonadherence within 30days. We also considered physician engagement outcomes including viewing information about nonadherence and utilizing a pharmacist. Physician engagement was constructed from metadata from the study website; adherence outcomes were constructed from medication claims. We see no differences between the treatment arms and control for the primary adherence outcome. The pharmacist intervention was 42 percentage points (95% CI: 28pp-56pp) more likely when it was triggered by default. Access to a pharmacist and real-time nonadherence information did not improve patient adherence. Physician process of care was sensitive to choice architecture.

The Prevalence of Nonadherence in Patients With Resistant Hypertension: A Systematic Review Protocol.

Background:Resistant hypertension, usually defined as blood pressure remaining above goal despite the concurrent use of 3 or more antihypertensive agents of different classes, is common (about 10% prevalence) and known to be a risk factor for cardiovascular events. These patients also undergo more screening intensity for secondary hypertension. However, not all patients with apparent treatment-resistant hypertension have true resistant hypertension, with some of them being nonadherent to prescribed pharmacotherapy. The prevalence of nonadherence varies from about 5% to 80% in the published literature. However, the relative contributions of intentional and nonintentional nonadherence are not well described. Nonintentional nonadherence refers to occasional forgetfulness and/or carelessness and can sometimes be related to an inability to follow instructions, because of either cognitive or physical limitations. Intentional nonadherence refers to an active process in which a patient may choose to alter the prescribed medication regimen by discontinuing medications, skipping doses, or modifying doses or dosing intervals.Objective:Our objective is to establish the overall prevalence of nonadherence in the apparent treatment-resistant hypertension population and evaluate the relative contributions of nonintentional and intentional nonadherence subtypes.Design:We will conduct a systematic review and meta-analysis.Setting:We will include observational studies and randomized controlled trials where adherence to antihypertensive medications is measured using a test of adherence, either direct or indirect.Patients:We will include adult human participants aged 18 years or older with a diagnosis of resistant hypertension.Measurements:Data extracted from individual studies will include title, first author, design, country, publication year, funding body, method of assessing adherence to antihypertensive medication, prevalence of medication nonadherence, definition of resistant hypertension, sample size, sex, mean age, and coexistent comorbidities.Methods:A librarian will search the databases Medline, EMBASE, Cochrane, CINAHL, and Web of Science for studies meeting criteria for inclusion. Two reviewers will independently screen the titles and abstracts retrieved and assess the methodological quality of eligible full-text articles using the Cochrane Risk of Bias tool for clinical trials and the Newcastle-Ottawa Scale for observational studies. Summary estimates of prevalence will be generated using pooled analysis using the random-effects method. Subgroup analyses, sensitivity analyses, and evaluation of publication bias will also be performed.Results:The outcomes of interest are the pooled prevalence of nonadherence to antihypertensive medication in apparent treatment-resistant hypertension and the prevalence of nonadherence based on different methods of assessing nonadherence (indirect vs direct), which will allow us to estimate the relative proportion of unintentional and intentional nonadherence subtypes in the overall phenomenon of medication nonadherence.Limitations:Possible limitations of this study include the finding of severe heterogeneity, the limitations of the literature search, publication bias, and the lack of granular data in the published studies for a study-level meta-analysis.Conclusions:This systematic review will provide a synthesis of current evidence on the prevalence of medication nonadherence in apparent treatment-resistant hypertension and on the relative contributions of nonintentional and intentional nonadherence subtypes. These findings will provide clinicians with a better understanding of the factors underlying treatment-resistant hypertension and will serve as a strong research base to guide future research on interventions to address medication nonadherence as well as the nonintentional and intentional subtypes.Trial registration:This protocol has been registered with PROSPERO. We will add registration details once available.

A perspective on nonadherence to drug therapy: psychological barriers and strategies to overcome nonadherence.

Medication adherence represents an inefficiency and ongoing challenge within medical care. The problem has been long-recognized – indeed, the research literature contains thousands of articles on the topic. Nonetheless, because of the complex nature of the problem, it still cannot be considered to be solved. Reasons for nonadherence are myriad but psychological barriers to adherence are most difficult to mitigate and, thus, are the focus of this paper. The present narrative review sketches a summary of theoretical models commonly utilized to understand and help address medication nonadherence; uses a patient-centered care approach to contextualize the problem of nonadherence to drug therapies; and then outlines a set of best-practice recommendations based on the extant data and framed from the perspective of the Information-Motivation-Strategy model.