Risk Factors For Medication Nonadherence Research Articles

Predicting psychosocial risk in pediatric kidney transplantation: An exploratory cluster analysis of a revised Pediatric Transplant Rating Instrument

The Pediatric Transplant Rating Instrument (P-TRI) is a 17-item scale developed to assess psychosocial risk factors for poor outcomes after solid organ transplantation. Research has identified the limitations of the original instrument and proposed revisions to improve clinical utility. This project examined patterns of risk in children being evaluated for kidney transplant using a revised P-TRI. A multidisciplinary kidney transplant team revised the P-TRI. A social worker and a psychologist collaboratively completed the modified instrument for 37 children after the psychosocial pretransplant evaluation. Electronic medical records were reviewed for transplant status (transplanted, active waitlist, inactive) 1 year later. Exploratory cluster analyses and chi-square tests examined patterns of risk and correlates with cluster membership. Three clusters were identified. The high-risk group (29.7%) had difficulties with medication and appointment adherence, strained relationships with the medical team, and the presence of parent psychiatric history. The medium-risk group (35.1%) had difficulties with parent knowledge, financial strain, and risk factors for medication nonadherence. The low-risk group (35.1%) demonstrated no difficulties with adherence or financial strain. Clusters were prospectively associated with transplant status, such that those in the high-risk group were less likely to be transplanted within 1 year post-evaluation. The revised P-TRI demonstrated good construct validity as risk level appeared to be associated with transplant listing status 1 year post-evaluation. These results suggest that standardized pretransplant psychosocial risk assessment tools may have value in optimizing transplant access if they can be paired with targeted, multidisciplinary interventions to address concerns early in the transplant process.

Medication Nonadherence: Implications for patient health outcomes in pharmacy practice

ABSTRACT
 Objectives: The primary objective of this review is (1) to better understand the prevalence and impact of medication nonadherence, (2) to identify risk factors for medication nonadherence, (3) to understand the association between nonadherence and its implications on patient health outcomes in pharmacy practice, and (4) to study interventions designed to improve patient adherence to prescribed medications for medical conditions, considering its impact on both medication adherence and patient health outcomes.
 
 Methods: Published journal articles were manually sorted. Additional references were obtained from citations within the retrieved articles. This review surveyed the findings of the identified articles with data extracted to presents various strategies and resources on medication nonadherence related to patients and healthcare providers. English languages were considered inclusion criteria in reviewing published articles related to medication nonadherence. This review also surveyed identified articles to determine both subjective and objective medication adherence measures.
 Key findings: The research in this field needs advances, including improved design of feasible long‐term interventions, objective adherence measures, and sufficient study power to detect improvements in patient health outcomes.
 
 Conclusion:
 Current methods of improving medication adherence for chronic health problems are mostly complex and ineffective so full benefits of treatment cannot be realized. To date, monitoring of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice.

Predicting medication nonadherence risk in the Chinese type 2 diabetes mellitus population - establishment of a new risk nomogram model: a retrospective study.

ObjectiveTo investigate the risk factors of medication nonadherence in patients with type 2 diabetes mellitus (T2DM) and to establish a risk nomogram model.MethodsThis retrospective study enrolled patients with T2DM, which were divided into two groups based on their scores on the Morisky Medication Adherence scale. Univariate and multivariate logistic regression analyses were used to screen for independent risk factors for medication nonadherence. A risk model was then established using a nomogram. The accuracy of the prediction model was evaluated using centrality measurement index and receiver operating characteristic curves. Internal verification was evaluated using bootstrapping validation.ResultsA total of 338 patients with T2DM who included in the analysis. Logistic regression analysis showed that the educational level, monthly per capita income, drug affordability, the number of drugs used, daily doses of drugs and the time spent taking medicine were all independent risk factors for medication nonadherence. Based on these six risk factors, a nomogram model was established to predict the risk of medication nonadherence, which was shown to be very reliable. Bootstrapping validated the nonadherence nomogram model for patients with T2DM.ConclusionsThis nomogram model could be used to evaluate the risks of drug nonadherence in patients with T2DM.

Oral therapy adherence and satisfaction in patients with multiple myeloma.

The transition to oral therapies in patients with multiple myeloma (MM) offers potential benefits to patients; however, they must self-manage their medication and adherence plays an important role in patient care. It has been shown that patient satisfaction with their medication has a strong positive correlation with adherence in chronic diseases. The aim of this study was to estimate adherence rate of oral antimyeloma therapies and to identify risk factors for medication non-adherence. This observational, prospective, and multicentre survey based on a self-report questionnaire enrolled MM patients with at least 3months of oral therapy. The 6-item Girerd scale and the medication possession ratio (MPR) were used for measuring medication adherence and the SATMED-Q® questionnaire was used for measuring satisfaction. An analysis of risk factors for non-adherence to oral therapy was performed using univariate analysis. A total of 101 patients participated in the survey, yielding a response rate of 87%. The prevalence of adherence to oral antimyeloma therapy was estimated at 51.5% using the Girerd questionnaire. According to the MPR, adherence was evaluated at 96% (i.e. MPR ≥ 0.80). Both methods combined, adherence was estimated at 50.5%. One risk factor for medication non-adherence was identified: Eastern Cooperative Oncology Group Performance Status > 2 (p = 0.007). One predictive factor for high medication adherence was identified: high satisfaction with treatment (p = 0.01). Identifying patients at higher risk for non-adherence allows clinical pharmacists to personalise therapeutic information and education and to improve the quality of healthcare overall.

Social Risk Factors for Medication Nonadherence: Findings from the CARDIA Study.

Objectives: Nonadherence to medications has been documented, but the combined effect of social risk factors on medication nonadherence has not been investigated. Methods: We conducted a cross-sectional analysis of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a population-based prospective cohort. The sample (N = 1506) included subjects who at Year 20 (2005-06) were taking prescription medications and completed a 4-item Medication Adherence Scale. Social risk factors were education of high school or less, annual household income <$25,000, high financial strain, high chronic stress, low social support, and high social strain. Results: In a fully adjusted logistic regression model, income <$25,000 (OR = 2.37 [95% CI 1.12-4.98], p < .05) and high chronic stress (OR = 2.07 [95% CI 1.09-3.94], p < .05) were significantly associated with medication nonadherence. Individuals with ≥3 social risk factors had >3 times higher odds of nonadherence than counterparts with no social risk factors (OR = 3.26 [95% CI 1.72-6.19], p < .001). Conclusion: Low income and chronic stress are associated with medication nonadherence, and the odds of nonadherence increase with the accumulation of social risk factors. Findings may be used to develop risk prediction tools to identify individuals who can benefit from adherence-promoting interventions.

Adherence of Geriatric Patients and Their Beliefs toward Their Medicines in the United Arab Emirates.

Introduction:Drug adherence is a major factor in determining health outcomes of geriatric patients and is a growing concern for health-care systems as the geriatric population shows a steep rise due to improved health-care services in the UAE.Aim:We aimed to evaluate the adherence and beliefs of geriatric patients in the UAE toward their medicines and to explore the factors affecting them.Methods:A cross-sectional study was performed including 163 geriatric patients. Surveys, direct observations, and interviews were used for primary data collection. Demographic data were computed using descriptive statistics method. The Statistical Package for the Social Sciences (SPSS) program, Version 19.0, SPSS Inc., Chicago, IL, USA, was used to analyze and code the raw data, whereas chi-squared test was used to analyze the responses. Secondary data were also collected.Results:The results indicated that patient factors and medication factors are the main risk factors for medication nonadherence among geriatric patients in the UAE. The study found that drug regimen (91.4%, N = 149), forgetfulness (87.1%, N = 142), time constraints (67.5%, N = 110), and cost (55.2%, N = 90) were the main key factors affecting medication adherence. Also, poor communication (12.9%), the lack of trust (16.6%), confidence (20.2%), and patient involvement (43.6%) were shown to influence adherence behaviors to medication. The main habits, attitudes, and beliefs that were found to affect patient’s adherence were follow-ups (73%), inadequate knowledge of medicine (60.1%), the lack of perceived benefits (18.4%), and limited knowledge on health conditions (19.6%). The study showed 161 patients among the total 163 participants forget taking their medications and others cease from taking their medications. To conclude, nonadherence to medications is a substantial problem among the elderly in the UAE.Conclusion:The study findings confirm the need for further research to examine the perspectives of at-risk population with a focus on knowledge, beliefs, and attitudes on medication nonadherence.

Risk Factors for Medication Nonadherence to Self-Injectable Biologic Therapy in Adult Patients With Inflammatory Bowel Disease.

In inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), nonadherence to biologic therapy increases risk of disease flare. The aim of this study was to identify risk factors for nonadherence. This was a single-center retrospective study evaluating patients with IBD treated at a tertiary care center and prescribed self-injectable biologic therapy using the center's specialty pharmacy. Adherence was defined using medication possession ratio (MPR). Nonadherence was defined as MPR <0.86. Four hundred sixty patients (n = 393 with CD and n = 67 with UC) were evaluated with mean MPR (interquartile range) equaling 0.89 (0.48-1). Overall, 69% of patients were adherent (defined as MPR ≥0.86), 66% of patients with CD and 87% of patients with UC. In univariate analysis, several factors increased risk of nonadherence: CD diagnosis, insurance type, psychiatric history, smoking, prior biologic use, and narcotic use (P < 0.05). In multivariable analysis, Medicaid insurance (odds ratio [OR], 5.5; 95% confidence interval [CI], 1.85-15.6) and CD diagnosis (OR, 2.8; 95% CI, 1.3-6.0) increased risk of nonadherence. In CD, as the number of risk factors increased (narcotic use, psychiatric history, prior biologic use, and smoking), the probability of nonadherence increased. Adherence was 72% in patients with 0-1 risk factors, decreasing to 62%, 61%, and 42% in patients with 2, 3, and 4 risk factors, respectively (P < 0.05). This study identified risk factors for nonadherence to biologic therapy. In patients with CD, the probability of nonadherence increased as the number of risk factors increased.

Risk Factors for Medication Non-Adherence to Biologic Therapy in Patients With Inflammatory Bowel Disease: A Retrospective Analysis

Introduction: In inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), adherence to biologic therapy is critical. Prior research has demonstrated that a medication possession ratio (MPR) of less than 0.86 significantly increases the risk of disease flare. (1) Further understanding of the risk factors for non-adherence is needed. Methods: We conducted a retrospective study to evaluate patients (pts) treated at a tertiary care IBD center prescribed injectable biologic therapy (adalimumab, certolizumab, golimumab, or ustekinumab) and followed by the center's specialty pharmacy (defined as at least 3 prescription claims). MPR was calculated as the sum of days' supply for all prescription claims divided by the total number of days (d) elapsed during the study period. Medication non-adherence was defined as MPR < 0.86. Wilcoxon test was used for continuous variables, Pearson testing for categorical variables in univariate analysis. Results: In this study, 460 pts (n=393 with CD and n=67 with UC) were evaluated. Table 1 summarizes patient characteristics. Median follow up was 921 d (range 232, 1414 d). The overall mean MPR was 0.89. In this cohort, 69% of pts were adherent (MPR > 0.86), 71% of pts with CD and 87% of pts with UC. Several risk factors were shown to increase the risk of non-adherence in univariate analysis including a diagnosis of CD, insurance type, psychiatric history, smoking, prior biologic use, and narcotic use (Table 2). Disease type and past surgical history in CD did not have an impact on adherence. Using multivariate analysis, insurance type (Medicaid) (OR 5.5, CI 1.85, 15.6) and diagnosis of CD (OR 2.8, CI 1.3, 6.0) increased the risk of noncompliance, but several risk factors trended toward significance. In pts with CD, as the number of risk factors present increased (narcotic use, psychiatric diagnosis history, prior biologic use, and smoking), the probability of non-adherence significantly increased. (Figure 2) Adherence was 77% and 73% in patients with 0 to 1 risk factors, decreasing to 65%, 61% and 37% in those with 2, 3, or 4 risk factors respectively (p < 0.05).570_B Figure 2. Risk Factors for non-adherence in pts with IBD on injectable biologic medicationConclusion: This study identified several risk factors for non-adherence to injectable biologic therapy. Additionally, as number of risk factors increased in pts with CD, the probability of adherence to therapy significantly decreased.570_A Figure 1. Patient Characteristics570_C Figure 3. The probability of adherence in pts with CD decreases as the number of risk factors increase (risk factors include prior biologic use, narcotic use, psychiatric history, and smoking; p < 0.05).

Meeting report: FDA public meeting on patient-focused drug development and medication adherence in solid organ transplant patients.

The Food and Drug Administration (FDA) held a public meeting and scientific workshop in September 2016 to obtain perspectives from solid organ transplant recipients, family caregivers, and other patient representatives. The morning sessions focused on the impact of organ transplantation on patients' daily lives and the spectrum of activities undertaken to maintain grafts. Participants described the physical, emotional, and social impacts of their transplant on daily life. They also discussed their posttransplant treatment regimens, including the most burdensome side effects and their hopes for future treatment. The afternoon scientific session consisted of presentations on prevalence and risk factors for medication nonadherence after transplantation in adults and children, and interventions to manage it. As new modalities of Immunosuppressive Drug Therapy are being developed, the patient perceptions and input must play larger roles if organ transplantation is to be truly successful.

Adherence to Antipsychotic Medication in Bipolar Disorder and Schizophrenic Patients: A Systematic Review.

Antipsychotics are the drugs prescribed to treat psychotic disorders; however, patients often fail to adhere to their treatment, and this has a severe negative effect on prognosis in these kinds of illnesses. Among the wide range of risk factors for treatment nonadherence, this systematic review covers those that are most important from the point of view of clinicians and patients and proposes guidelines for addressing them. Analyzing 38 studies conducted in a total of 51,796 patients, including patients with schizophrenia spectrum disorders and bipolar disorder, we found that younger age, substance abuse, poor insight, cognitive impairments, low level of education, minority ethnicity, poor therapeutic alliance, experience of barriers to care, high intensity of delusional symptoms and suspiciousness, and low socioeconomic status are the main risk factors for medication nonadherence in both types of disorder. In the future, prospective studies should be conducted on the use of personalized patient-tailored treatments, taking into account risk factors that may affect each individual, to assess the ability of such approaches to improve adherence and hence prognosis in these patients.

Current and remitted depression and anxiety disorders as risk factors for medication nonadherence.

To investigate the impact of current and remitted depression and anxiety disorders and sociodemographic and other related factors on medication nonadherence in a large cohort study. The Medication Adherence Rating Scale was used to assess medication nonadherence of 1,890 medication users in the 4-year follow-up assessment of the Netherlands Study of Depression and Anxiety, which was conducted between 2008 and 2011. Psychiatric diagnoses according to the DSM-IV, sociodemographic and clinical characteristics, and medication use were determined. Medication nonadherence was defined by the tendency to forget a dose, change the dose, stop for a while, skip 1 dose, or take a smaller dosage than prescribed. Overall medication nonadherence was 44%. In multivariate analyses, all current and remitted depression and anxiety diagnoses were risk factors for medication nonadherence as compared to subjects never having had a depressive or anxiety diagnosis (P < .05). Age (OR = 0.85, P < .001) and antidepressant use (OR = 0.66, P = .001) were associated with less medication nonadherence. Alcohol dependence (OR = 1.67, P = .05) and the number of dietary supplements (OR = 1.18, P = .02) proved risk factors for medication nonadherence. Associations of anxiety diagnosis with medication nonadherence were mainly driven by depression diagnosis. All current and remitted depression and anxiety disorders were risk factors for medication nonadherence. Since these disorders are highly comorbid with other medical conditions, health care workers should address medication nonadherence in patients with depression and/or anxiety disorders, even in those who are in symptomatic remission.

Perspectives on reasons of medication nonadherence in psychiatric patients.

PurposeThis study was carried out to evaluate factors resulting in medication nonadherence within 6 months before admission to the psychiatric service of our hospital for bipolar disorder, schizophrenia/schizoaffective disorder, depression, and other psychiatric diseases.Patients and methodsTwo hundred and three patients admitted to the Psychiatry Service of the Medical Faculty were included in this study. Sociodemographic parameters and clinical findings within 6 months before admission and patients’ views on reasons of medication nonadherence were examined.ResultsPatients were classified into four groups according to their diagnosis: bipolar disorder (n=68, 33.5%), schizophrenia/schizoaffective disorder (n=59, 29.1%), depression (n=39, 19.2%), and others (n=37, 18.2%). The ratio of medication nonadherence was higher in the bipolar disorder group when compared to the groups with schizophrenia/schizoaffective disorder, depression, and other disorders (12.1%, 18.2%, and 24.2% vs 45.5%); however, the ratio of medication nonadherence was similar in schizophrenia/schizoaffective disorder, depression, and the others group. In logistic regression analysis, irregular follow-up (odds ratio [OR]: 5.7; 95% confidence interval [CI]: 2.92–11.31) and diagnosis (OR: 1.5; 95% CI: 1.07–1.95) were determined to be important risk factors for medication nonadherence. The leading factors for medication nonadherence were: “not willing to use medication”, “not accepting the disease”, and “being disturbed by side effects” in the bipolar disorder group, “not accepting the disease” in the schizophrenia/schizoaffective disorder group, “feeling well” in the depression group, and “being disturbed by side effects” in the other diseases group.ConclusionMedication nonadherence is an important problem in psychiatric patients and should be dealt with by taking into account the diagnosis, attendance to follow-up appointments, and the patient’s attitude. Ensuring regular attendance to follow-up appointments, adjusting the management plan according to the diagnosis, and improving their thoughts about resistance to medication can be beneficial in terms of medication adherence.

Risk factors for medication nonadherence in older adults with cognitive impairment who live alone

The aim of this study was to prospectively examine the influence of cognitive, medical, behavioral, and social risk factors on medication nonadherence in community-dwelling older adults with cognitive impairment. A sample of 339 elderly participants with cognitive impairment, who lived alone and took at least one medication, underwent baseline assessment which included the five subscales of the Dementia Rating Scale (DRS), number of medications, retrospective medication nonadherence, amount of formal and informal assistance, functional impairment, depression, perception of social resources, comorbidity, and alcohol consumption. The outcome was medication nonadherence during the 12-month prospective period as reported by the participants' primary care physicians and caregivers at three-month intervals. Fifty-nine participants (17.4%) had, at least, one report of medication nonadherence. Logistic regression analyses indicated for every point increase on the DRS Conceptualization subscale (OR = 1.14; 95% CI = 1.02-1.27), there was a 14% increase in the odds of nonadherence. For every point increase on the DRS Memory subscale (OR = 0.89; 95% CI = 0.81-0.97) and DRS Initiation/Perseveration subscale (OR = 0.93; 95% CI = 0.87-1.00), there was an 11% decrease and 7% decrease in the odds, respectively. Having at least one previous occurrence of medication nonadherence (OR = 2.61; 95% CI = 1.18-5.62) and taking at least four medications (OR = 2.58; 95% CI = 1.31-5.29), both increased the odds by over 2.5-fold. Our unique finding that better conceptualization predicted nonadherence has important implications for healthcare providers' approaches to improve adherence in older adults with cognitive impairment. Replication in future studies is warranted.

Risk Factors for Medication Non-Adherence in an HIV Infected Population in the Dominican Republic

High levels of medication adherence are central to HIV treatment success. Barriers to medication adherence may differ by cultural setting. We aimed to determine risk factors for medication non-adherence in HIV infected individuals in the Dominican Republic. Adherence was measured in 300 individuals using a visual analog scale assessing the prior month and dichotomized at 95%. High levels of adherence were reported by 228 (76%). Risk factors for non-adherence included heavy alcohol use: 2.5 times odds (95% CI: 1.4-4.5), having children: 2.2 times higher odds (95% CI: 1.1-4.9) and perceptions of less social support related to adherence: 2 times higher odds (95% CI: 1.1-3.6). Culturally appropriate interventions are needed to address alcohol use, which is common in this setting. Parenting may represent a competing demand on time and resources and be an adherence barrier. Self-reported perceived lack of adherence support may be a useful marker for need for adherence interventions.

Medication Adherence: A Review of the Literature and Implications for Clinical Practice

Adherence is defined as the extent to which a patient's behavior coincides with medical or prescribed health advice. Adherence is considered non-judgmental and is preferred over the term "compliance," which carries negative connotations and suggests blame for the patient. A major challenge in the field of psychiatry has been to understand why patients may or may not adhere to medication and other treatment recommendations. A comprehensive review of the literature on medication adherence among patients with psychiatric illnesses was conducted with the following objectives: (1) to better understand the impact of medication nonadherence, (2) to identify risk factors for medication nonadherence, and (3) to study interventions designed to improve patient adherence. The authors initially searched the Ovid Medline electronic database using the key words "medication adherence" and "compliance" to identify all articles written in the English language published through early 2008. This produced over 2000 references. The search was then narrowed to publications specific to psychotropic medication. The ultimate goal of the review was to increase awareness of this critical issue and to discuss strategies that the psychiatric clinician can implement to address patient adherence to prescribed medications. The authors chose to include articles that were deemed to be clinically useful to the practicing clinician.Studies that have specifically investigated adherence to psychiatric medications vary in the definitions of adherence and methodology that were used, making interpretation of results across studies difficult. Psychoeducational interventions have long been the mainstay of treatment for adherence problems. However, there is growing evidence that other approaches such as cognitive-behavioral strategies and motivational interviewing may be effective. Based on a comprehensive literature review, the authors recommend the following strategies for addressing adherence problems: focus on strengthening the therapeutic alliance; devote time in treatment specifically to address medication adherence; assess patients' motivation to take prescribed medications; and identify and address potential barriers to treatment adherence.

Development of the ASK-20 Adherence Barrier Survey

ABSTRACTObjective: Poor medication adherence is widespread among patients with chronic conditions requiring long-term drug therapy. Medication adherence is determined by multiple patient-, context-, and therapy-dependent factors. This paper describes the development and initial validation of the ASK-20 survey, created to identify actionable risk factors for medication nonadherence and to improve communication about adherence.Methods: A pool of 30 items was generated through comprehensive literature review. Items were refined and the item pool was expanded through an expert panel review and patient focus groups to yield 47 candidate items, each with five response options ranging from either Strongly Agree to Strongly Disagree or from In the Last Week to Never. The pool of 47 candidate items was administered to a web-based sample of 605 patients taking medications and reporting a diagnosis of asthma, diabetes, or depression for psychometric testing and item reduction.Results: Eleven multi-item factor groupings with two additional unique items were identified on the basis of principal components analysis and interpretability. Twenty (20) items representing ten factor groupings were selected for the final instrument. Each of the final items was dichotomized as positive – indicating a barrier, or negative. Two summary scores – the sum of all positive barriers or Total Barrier Count (TBC) and the sum of raw item scores, the ASK-20 score – were calculated. Concurrent validity of the dichotomously scored individual items, the TBC and ASK-20 scores in relation to self-reported adherence was generally good. Cronbach's alpha coefficient was 0.77 for the TBC and 0.85 for the ASK-20 score.Conclusions: ASK-20 consists of 20 clinically actionable items representing multiple factors that affect medication adherence. The ASK-20 survey demonstrated satisfactory validity and internal consistency and may be used to identify actionable barriers to adherence across a spectrum of chronic diseases. Future research using more objective measures of adherence is warranted to confirm the exploratory validity and reliability of ASK-20 reported in this study.

Risk Factors for Medication Non-Adherence in Patients with First Episode Schizophrenia and Related Disorders; A Prospective Five Year Follow-Up

The goal of this study is to assess, prospectively, the relative contribution of baseline variables to long-term medication adherence in patients with a first episode of schizophrenia. Consecutively admitted patients suffering from a first episode of schizophrenia or related disorders were investigated. Subjective experience, attitudes towards treatment, insight, interaction with members of staff, involuntary admission, substance abuse, and severity of psychopathology were independently assessed at first admission and related to medication adherence during five year follow up. Standard multiple regression analysis revealed that hostility and uncooperativeness (p=0.007) and involuntary admission (p=0.02) were associated with the level of adherence during 5 year follow-up after admission. In first episode schizophrenia and related disorders, the initial interaction with staff and involuntary admission partly predicts long-term adherence to antipsychotic medication. Ameliorating these initial interactions might have long-term consequences on medication adherence. Involuntary admitted patients need intensive outpatient care.