Rates Of Medication Nonadherence Research Articles

Medication adherence and related psychosocial and clinical factors among schizophrenic patients: a cross - sectional analytical study in National Psychiatric Hospital 2, Vietnam

Background and Aims: Schizophrenia is a chronic and severe mental disorder. Treatment by antipsychotic medication is one of the main therapies to control the symptoms. Medication non/poor adherence is a one of the key factors leading to relapse and declined social and occupational function in patients. However, prevalence of schizophrenic patients with non/poor adherence to medication was quite high in previous studies. Therefore, this study aimed to identify the prevalence of medication non/poor adherence and its related psychosocial and clinical factors among schizophrenic patients. Subjects and Method: a cross - sectional analytical study of 126 schizophrenic patients at National Psychiatric Hospital 2 were conducted to evaluate the rate of medication non-adherence by Morisky Medication Adherence Scale 8 item (MMAS - 8). Data were collected on patients’ sociodemographic factors such as sex, age, marital and economic status, level of education and clinical factors including duration of schizophrenia, clinical symptoms evaluated by Positive and Negative syndrome scale (PANSS), type, and side effects of medication. Logistic regression was used to analyze the factors associated with medication non-adherence among schizophrenic patients. Results: Rate of poor medication adherence among participants was 78.57% by using MMAS – 8. The associated factors with poor medication adherence among schizophrenic patients were level of education under high school; unstable job/unemployment; poor insight about schizophrenia, poor family care/support, high scores of negative PANSS and general PANSS scale, duration of schizophrenia above 5 years, treated by typical antipsychotics and having more than two side effects of antipsychotics. Conclusion: The rate of poor medication adherence/ non - adherence among schizophrenic patients is high. Mental health staff should be aware of this risk and screening individuals for relevant risk factors is highly recommended Key words: medication adherence, schizophrenia, social - psycho - clinical factors.

Medication Adherence Among Patients With Kidney Disease: An Umbrella Review.

Chronic kidney disease (CKD) imposes a significant medication burden on patients due to the necessity of multiple treatments to slow disease progression, manage coexisting conditions, and address complications. The complex medication regimen, in turn, has implications for clinical and patient-centered outcomes. This umbrella review provides comprehensive evidence on extent of medication nonadherence among adults with CKD, as well as associated risk factors, outcomes, and the effectiveness of interventions by synthesizing evidence from published systematic reviews and/or meta-analyses. We identified 37 works that met our inclusion criteria. These reviews covered various aspects of treatment adherence in people with CKD, which can be categorized into four main themes: (i) prevalence of treatment nonadherence; (ii) factors associated with (non)adherent behaviors; (iii) outcomes associated with treatment (non)adherence; and (iv) interventions to improve treatment adherence or overall self-management practices. Approximately half of the included studies (15/34) focused on interventions aimed at improving medication adherence or overall CKD management, while outcomes associated with medication (non)adherence were relatively underexplored in the literature. The reported prevalence rates of medication nonadherence varied widely among reviews and stages of CKD. The determinants of adherence identified included socioeconomic variables, disease or clinical conditions, and psychosocial factors. Common interventions to improve adherence included nurse-led interventions, pharmaceutical services, and eHealth technologies, which had varying effects on medication adherence or dialysis sessions.

Patient-Reported Reasons for Antihypertensive Medication Change: A Quantitative Study Using Social Media.

Hypertension is the leading cause of heart disease in the world, and discontinuation or nonadherence of antihypertensive medication constitutes a significant global health concern. Patients with hypertension have high rates of medication nonadherence. Studies of reasons for nonadherence using traditional surveys are limited, can be expensive, and suffer from response, white-coat, and recall biases. Mining relevant posts by patients on social media is inexpensive and less impacted by the pressures and biases of formal surveys, which may provide direct insights into factors that lead to non-compliance with antihypertensive medication. This study examined medication ratings posted to WebMD, an online health forum that allows patients to post medication reviews. We used a previously developed natural language processing classifier to extract indications and reasons for changes in angiotensin receptor II blocker (ARB) and angiotensin-converting enzyme inhibitor (ACEI) treatments. After extraction, ratings were manually annotated and compared with data from the US Food and Drug administration (FDA) Adverse Events Reporting System (FAERS) public database. From a collection of 343,459 WebMD reviews, we automatically extracted 1867 posts mentioning changes in ACEIs or ARBs, and manually reviewed the 300 most recent posts regarding ACEI treatments and the 300 most recent posts regarding ARB treatments. After excluding posts that only mentioned a dose change or were a false-positive mention, 142 posts in the ARBs dataset and 187 posts in the ACEIs dataset remained. The majority of posts (97% ARBs, 91% ACEIs) indicated experiencing an adverse event as the reason for medication change. The most common adverse events reported mapped to the Medical Dictionary for Regulatory Activities were "musculoskeletal and connective tissue disorders" like muscle and joint pain for ARBs, and "respiratory, thoracic, and mediastinal disorders" like cough and shortness of breath for ACEIs. These categories also had the largest differences in percentage points, appearing more frequently on WebMD data than FDA data (p<0.001). Musculoskeletal and respiratory symptoms were the most commonly reported adverse effects in social media postings associated with drug discontinuation. Managing such symptoms is a potential target of interventions seeking to improve medication persistence.

Primary medication nonadherence rates to specialty disease-modifying antirheumatic drugs for rheumatoid arthritis within a health system specialty pharmacy.

BACKGROUND: Assessing primary medication nonadherence, the rate at which a medication is prescribed for a patient but is not obtained or replaced with an alternative medication within a reasonable time period, can provide a better understanding of the frequency and impact of these barriers to medication access. Previous literature has reported high rates of primary medication nonadherence, ranging from approximately 20% to 55% in patients with rheumatoid arthritis (RA) treated with specialty disease-modifying antirheumatic drugs (DMARDs). The high primary medication nonadherence rate may reflect the difficulties associated with obtaining specialty medications, such as high costs, extended prior authorizations, and pretreatment safety requirements. OBJECTIVE: To evaluate reasons for and rates of primary medication nonadherence to specialty DMARDs in patients with RA referred to an integrated health systems specialty pharmacy. METHODS: We conducted a retrospective cohort study examining eligible patients with a specialty DMARD referral from a health system rheumatology provider to the health system specialty pharmacy. Initially, pharmacy claims were used to identify primary medication nonadherence, defined as the lack of a fill event within 60 days following the medication referral for patients without a specialty DMARD claim in the 180 days prior. Referrals from July 1, 2020, to July 1, 2021, were eligible. Exclusion criteria included duplicate referrals, use for non-RA indications, switches to clinic-administered therapies, and alternate filling methods. Medical record reviews were conducted to confirm referral outcomes. Outcomes included rate of and reasons for primary medication nonadherence. RESULTS: We included 480 eligible patients, 100 of whom had no documented fill event. After medical record review, 27 patients were removed due to having a non-RA diagnosis and 65 patients were removed due to having alternative fill methods, most due to external prescription routing (83.1%). The final primary medication nonadherence rate was 2.1%. Out of the 8 cases of true primary medication nonadherence, 3 patients held specialty DMARD therapy because of other existing disease states, 3 patients were unreachable, and 2 patients were unable to afford medication. CONCLUSIONS: Rates of primary medication nonadherence to specialty DMARDs were low in patients with RA managed by a health system specialty pharmacy. A total of 8 primary medication nonadherence cases were related to safety concerns in non-RA diseases states, patient unreachability, and affordability. However, the limited number of primary medication nonadherence cases limits the generalizability of reasons for primary medication nonadherence found in this study. Key elements of the health systems specialty pharmacy model that likely contribute to low primary medication nonadherence include dedicated financial assistance navigation services, in-clinic pharmacist availability, and open communication between provider offices.

EPH150 A Survey of Prescription Abandonment and Primary Medication Nonadherence Rates: A Literature Review

Being adherent to medications is necessary for optimal therapeutic efficacy but nonadherence remains a significant public health issue. Primary medication nonadherence (PMN) is when a new prescription is filled and not picked up; prescription abandonment encompasses both new and refilled prescriptions. Previous research shows PMN rates of 3-10%, but currently, there isn’t a consensus to prescription abandonment rates despite interchangeable use of the terms. This research aims to quantify the rates of prescription abandonment in the literature.

Medication Adherence in Inflammatory Bowel Disease

Inflammatory bowel disease is a chronic idiopathic inflammatory condition with intestinal and extra-intestinal features. The key component of treating inflammatory bowel disease is medication. Patients, however, often don't take their medication as directed. Medication adherence is the act of taking a patient's prescribed medications as directed. Average medication non-adherence rates for chronic diseases are 50% in developed nations, and they are even lower in developing nations. Measuring medication adherence can be done in a variety of ways, including direct and indirect methods, each with advantages and disadvantages. The factors influencing medication adherence are multifactorial. Cost, Psychosocial-related and medication-related factors were more important determinants of adherence compared with demographic or clinical variables which will be looked at in this review. Additionally, this review talks about the negative clinical effects of non-adherence to drug therapy. Finally, this review explores different intervention strategies to improve adherence to medications. Keywords: [Inflammatory bowel disease, Medication adherence, Medication non adherence]

Challenges in the Long-term Management of Patients With Coccidioidal Meningitis: A Retrospective Analysis of Treatment and Outcomes.

Coccidioidal meningitis (CM) is the most severe form of disseminated coccidioidomycosis. Despite years of clinical experience, it remains a difficult condition to treat, often requiring surgical procedures, such as placement of a ventriculoperitoneal shunt, in addition to lifelong antifungal therapy. We performed a retrospective analysis of patients with CM seen in a large referral center in Central Valley, California, from 2010 to 2020. Data pertinent to CM were collected and analyzed. Among 133 patients with CM identified in the 10-year period, nonadherence to antifungal therapy was noted in 43% of patients. Of the 80 patients who underwent ventriculoperitoneal shunt placement for management of intracranial pressure, shunt failure requiring revision surgery occurred in 42 (52.5%). Rehospitalizations due to CM-related reasons occurred in 78 of 133 patients (59%). Twenty-three percent of patients (n = 29) died due to complications from CM, on an average 22 months after the diagnosis of CM. Encephalopathy at presentation was associated with a significantly higher risk of death. Patients with CM in central California are predominantly rural agricultural workers with elevated levels of poverty and low health literacy and many barriers to care, leading to high rates of medication nonadherence and loss to follow-up outpatient care. Management challenges are frequent, such as failure of antifungal therapy, high rates of rehospitalization, and the need for repeated shunt revision surgeries. In addition to the development of curative new antifungal agents, understanding the barriers to patient adherence to care and antifungal therapy and identifying means to overcome such barriers are of paramount importance.

The rate of medication nonadherence and influencing factors: A systematic Review

Lack of adherence to recommended therapy will reduce its effectiveness and can subsequently lead to disease progression, disabilities or even death. A vast number of research studies have emphasized the magnitude of medication nonadherence and its effect on treatment outcomes, patient’s health, healthcare providers and the associated costs; medication nonadherence remains a major concern that is believed to be widely practiced amongst medication taking patients. The current systemic review aims to cohere the available evidence regarding medication nonadherence rate, practices, and potential affecting factors and predictors. A search through different databases was conducted, including PubMed, Medline, and CINHAL for recently published research articles, within five years. The terms used for the search include medication nonadherence, medication nonadherence, factors affecting medication nonadherence and predictors of medication nonadherence. The search was limited to human subjects, English language journal articles and exclusion of review articles, case studies, and data from clinical trials as patient adherence is closely observed.&lt;br /&gt; The search resulted in 667 articles and only 65 articles were included and further screened. However, according to our exclusion criteria, 15 articles only were included in this review. The three most reported practices of medication nonadherence are prescription abandonment, nonconforming, and non-persistence. There are five reported factors that may lead to nonadherence practices such as socioeconomic-related factors, healthcare system-related factors, patient-related factors, disease-related factors, and therapy-related factors. In conclusion, medication nonadherence practice is a multi-dimensional phenomenon that requires a multi-targeted solution.

Resilience mediates the effects of self‐care activation and hope on medication adherence in heart failure patients

Medication adherence is important to heart failure (HF) self-care. However, the rate of medication nonadherence is approximately 50%. Evidence suggests that self-care activation and hope may be internal motivators for medication adherence. Empirical data on the association between self-care activation, hope, and medication adherence among people with HF is sparse, and the mechanism by which these factors influence medication adherence is unclear. The findings of prior research studies suggest that resilience may help to explain the relationship between self-care activation, hope, and medication adherence. The aim of this cross-sectional study was to investigate whether resilience mediated the effects of self-care activation and hope on medication adherence. A total of 174 adults with HF, between the ages of 19 and 92, completed the Patient Activation Measure, The Adult Hope Scale, the 14-item Resilience Scale, and the Domains of Subject Extent of Nonadherence Scale. Mediation analyses revealed that resilience fully mediated the effects of self-care activation and hope on medication adherence. Clinicians should consider the person related factors of self-care activation, hope, and resilience when promoting medication adherence in people with HF. Resilience may play an important role in improving medication adherence in HF patients. More research is needed to understand the connection between resilience, self-care activation, hope, and medication adherence.

Detecting medication non-adherence in schizophrenia: A comparison of different methods among outpatients from a North Indian center.

The rates of medication non-adherence among Indian patients with schizophrenia are high, and its detection poses problems. Comparisons of suitable measures to detect medication non-adherence in schizophrenia from Indian outpatient settings are scarce. This study compared simple and inexpensive methods of detecting medication non-adherence in schizophrenia among outpatients from a tertiary-care center in North India. A longitudinal comparison of two self-reports, the Morisky Medication Adherence Questionnaire and the Drug Attitude Inventory-10, clinicians' ratings employing the Compliance Rating Scale, and clinic-based pill counts was conducted among 70 outpatients with schizophrenia. The rates and detection of medication non-adherence, associations with determinants of treatment non-adherence, and agreement between measures were examined at intake and after six months of follow-up (n = 53). The self-reports had greater ability to detect medication adherence (specificity 41-65%; positive predictive values 25-51%; negative likelihood ratios 0.86-1.14) and moderate ability to detect medication non-adherence (sensitivity 27-65%; negative predictive values 49-69%; positive likelihood ratios 0.78-1.10). They yielded higher medication non-adherence rates, detected changes in medication non-adherence over time, and were associated with the other measures and the well-known correlates of medication non-adherence. Clinicians' ratings and pill counts had high sensitivity (56-90%) but low specificity (35-49%) to detect medication non-adherence. Self-reports are comparatively better screening options for detecting medication non-adherence among Indian outpatients with schizophrenia. However, the sequential use of different measures could lead to better recognition of medication non-adherence.

Pilot Intervention to Improve Medication Adherence Among Patients With Systemic Lupus Erythematosus Using Pharmacy Refill Data.

Despite high rates of medication nonadherence among patients with systemic lupus erythematosus (SLE), effective interventions to improve adherence in SLE are limited. We aimed to assess the feasibility of a pilot intervention and explore its effect on adherence. The intervention used pharmacy refill data to monitor nonadherence and prompt discussions surrounding SLE medications during clinic encounters. Over 12 weeks, the intervention was delivered through routine clinic visits by providers to patients with SLE who take SLE-specific medications. We measured acceptability, appropriateness, and feasibility using provider surveys. We also measured acceptability by patient surveys and feasibility by medical record documentation. We explored change in adherence by comparing percent of patients with medication possession ratio (MPR) ≥80% 3 months before and after the intervention visit using the McNemar's test. Six rheumatologists participated; 130 patients were included in the analysis (median age 43, 95% female, and 59% racial and ethnic minorities). Implementation of the intervention was documented in 89% of clinic notes. Provider surveys showed high scores for feasibility (4.7/5), acceptability (4.4/5), and appropriateness (4.6/5). Among patient surveys, the most common reactions to the intervention visit were feeling determined (32%), empowered (32%), and proud (19%). Proportion of patients with MPR ≥80% increased from 48% to 58% (P=0.03) after the intervention visit. Our intervention showed feasibility, acceptability, and appropriateness and led to a statistically significant improvement in adherence. Future work should refine the intervention, assess its efficacy in a controlled setting, and adapt its use among other clinic settings.

The Association Between Medication Non-Adherence and Early and Late Readmission Rates for Patients with Acute Coronary Syndrome

PurposeUnplanned hospital readmission forms costly, but preventable burdens on healthcare system. This study was designed to evaluate cardiovascular-related readmission rate after discharge of acute coronary syndrome (ACS) patients and its relationship with medication adherence at a university hospital, Saudi Arabia.MethodsA total of 370 consecutive patients presenting with ACS were involved. The inclusion criteria were clinical and coronary angiography diagnostic data of ACS. Exclusion criteria included heart valve disease, myocarditis, hepatic disease, and history of acute infection during the previous two weeks. Patients were divided into index admission group (n = 291) and unplanned readmission group (n = 79). Readmission and medication adherence rates were evaluated during 1–30, 31–180, 181–365, and 366–548 days post-ACS discharge. Medication adherence was estimated with a (yes/no) questionnaire.ResultsThe overall readmission rate was 21.4%; individual rates were 30.4%, 38.0%, 27.8%, and 3.8% and the overall medication adherence rate was 62.03%, while individual rates were 54.2%, 70.0%, 63.6%, and 33.3% during the four periods, respectively. There were strong correlations between medication non-adherence and readmission rates. Heart failure, ST-elevated myocardial infarction, unstable angina, cerebrovascular accident, and arrhythmia represented the top causes. Body mass index was higher in readmission group. There were significant correlations between smoking, hypertension, cerebrovascular accident, ischemic heart disease, previous stent, instent restenosis, and LDL-cholesterol as predictor factors and readmission rate.ConclusionThe cardiovascular-related unplanned readmission rate post-ACS discharge was 21.4%, and medication non-adherence rate was 37.97%. There were strong correlations between them in the time frames from 1-month to 1.5-year post-discharge. The individual rates decreased by time, but the first month showed lower rates than the following 5 months and this indicated the role of factors other than medication non-adherence in readmission. The rates are generally consistent with the international levels but utilizing technology can further improve medication adherence and reduce readmission rates.

Development of a Predictive Nomogram for Estimating Medication Nonadherence in Hemodialysis Patients.

BackgroundMedication compliance in hemodialysis patients affects the therapeutic effect of treatment and patient survival. Therefore, we aimed to explore the influencing factors of medication adherence in hemodialysis patients and develop a nomogram model to predict medication adherence.Material/MethodsData from questionnaires on medication adherence in hemodialysis patients were collected in Chengde from May 2020 to December 2020. The least absolute selection operator (LASSO) regression model and multivariable logistic regression analysis were used to analyze the risk factors for medication adherence in hemodialysis patients, and then a nomogram model was established. The bootstrap method was applied for internal validation. The concordance index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), decision curve analysis (DCA), calibration curve, net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index were used to evaluate the degree of differentiation and accuracy of the nomogram model, and clinical impact was used to investigate the potential clinical value of the nomogram model.ResultsIn total, 206 patients were included in this study, with a rate of medication nonadherence of 41.75%. Eight predictors were identified to build the nomogram model. The C-index, AUC, DCA, calibration curve, NRI, and IDI showed that the model had good discrimination and accuracy. The clinical impact plot showed that the nomogram of medication adherence in hemodialysis patients had clinical application value.ConclusionsWe developed and validated a nomogram model that is intuitive to apply for predicting medication adherence in hemodialysis patients.

Cannabis use and medication nonadherence in bipolar disorder: A nationwide inpatient sample database analysis

BackgroundMedication nonadherence among bipolar disorder (BD) is often linked with comorbid substance use disorders. This study aims to investigate cannabis use disorder (CUD) association with medication noncompliance in hospitalized BD patients. Methods: Using data on 266,303 BD hospitalizations between 2010 and 2014 from the US Nationwide Inpatient Sample database, we obtained medication noncompliance rates stratified by demographics and CUD. Logistic regression was used to evaluate factors associated with medication noncompliance. ResultsOverall mean age, the prevalence of CUD, and medication nonadherence were 41.58 (± 0.11) years, 15.0% and 16.1%, respectively. There were 56.6% females in the overall population. There was a significant difference in the characteristics of those in the medication nonadherence vs adherence groups, including age, sex, race, comorbid substance use, income, insurance type, hospital region, and hospital teaching status (p < 0.001). After adjusting for other variables using multivariate analysis, there remained a statistically significant association of medication nonadherence in BD hospitalization and CUD (OR 1.42, 95% CI 1.36–1.48). LimitationConfounding multiple substance use could not be accounted for, and the retrospective nature of the database which includes only inpatients is prone to possible selection and reporting bias. ConclusionCUD statistically predicts increased rates of medication nonadherence among patients with BD. Given the possible association of CUD with medication nonadherence among BD patients, collaborative work between general adult psychiatry and addiction services is imperative in improving the management outcome of patients with BD and comorbid CUD.

Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = −0.14; 95% confidence interval [CI]: −0.24 to −0.03; p value = 0.010) and MDD (β = −0.16; 95% CI: −0.27 to −0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34–1.93; p value = 2e−7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.

Clinicians' prescribing pattern, rate of patients' medication adherence and its determinants among adult hypertensive patients at Jimma University Medical Center: Prospective cohort study.

Many studies conducted in the past focused on patients' sociodemographic factors and medical profiles to identify the determinants of suboptimal blood pressure control. However, prescribing patterns and clinicians' adherence to guidelines are also important factors affecting the rate of blood pressure control. Therefore, this study aimed to determine clinicians' prescribing patterns, patients' medication adherence, and its determinants among hypertensive patients at Jimma University Medical Center. A general prospective cohort study was conducted among hypertensive patients who had regular follow-up at Jimma university ambulatory cardiac clinic from March 20, 2018, to June 20, 2018. Patients' specific data was collected with a face-to-face interview and from their medical charts. Clinicians' related data were collected through a self-administered questionnaire. Data were analyzed using SPSS version 21.0. Bivariate and multivariable logistic regression analyses were done to identify key independent variables influencing patients' adherence. P-Values of less than 0.05 were considered statically significant. From the total of 416 patients, 237(57.0%) of them were males with a mean age of 56.50 ± 11.96 years. Angiotensin-converting enzyme inhibitors were the most frequently prescribed class of antihypertensives, accounting for 261(63.7%) prescriptions. Combination therapy was used by the majority of patients, with 275 (66.1%) patients receiving two or more antihypertensive drugs. Patients' medication adherence was 46.6%, while clinicians' guideline adherence was 44.2%. Patients with merchant occupation (P = 0.020), physical inactivity (P = 0.033), and diabetes mellitus co-morbidity (P = 0.008) were significantly associated with a higher rate of medication non-adherence. The rate of medication adherence was poor among hypertensive patients. Physicians were not-adherent to standard treatment guideline. The most commonly prescribed class of drugs were angiotensin-converting enzyme inhibitors. Effective education should be given to patients to improve medication adherence. Prescribers should be trained on treatment guidelines regularly to keep them up-to-date with current trends of hypertension treatment and for better treatment outcomes.

Glaucoma Care of Incarcerated Patients at an Academic Institution: A Case-Control Study.

Purpose:To evaluate medication and follow-up adherence in incarcerated patients examined at an academic glaucoma clinic, in comparison to nonincarcerated controls.Methods:Retrospective, case-control study. Consecutive prisoners presenting for initial visits in the Glaucoma Clinic at the Illinois Eye and Ear Infirmary between December 2015 and December 2017 were included in the study. Nonincarcerated patients seen in the same Glaucoma Clinic with similar initial visit dates, age, race, sex, and disease severity were selected as controls. Glaucoma Clinic visits from each patient were reviewed until December 2018. Examination information, surgical intervention, follow-up and treatment recommendations, and patient-reported medication usage were recorded for each visit. Number of visits, loss to follow-up, follow-up delays, and medication nonadherence were studied as primary outcome measures.Results:Twenty-four prisoners and 24 nonincarcerated controls were included. Prisoners had an average of 2.46 ± 2.38 visits during the study period, compared to 5.04 ± 3.25 for controls (P = 0.001). Follow-up visits occurred more than 30 days after the recommended follow-up time in 57.4% (95% confidence interval [CI]: 44.2%–70.6%) of prisoners, compared to 17.9% (95% CI: 10.2%–25.6%) of controls (P < 0.00001). 70.8% of prisoners (95% CI: 66.3–74.5%) were lost to follow-up, compared to 29.2% of controls (95% CI: 25.5%–32.9%; P < 0.01). Medication nonadherence rates were similar between prisoners (13.6%; 95% CI: 12.1%–15.2%) and controls (12.0%; 95% CI: 11.4%–12.6%; P = 0.78).Conclusions:Glaucoma follow-up adherence was significantly worse in prisoners compared to a nonincarcerated control population. Further study into causative factors is needed.

Assessing Barriers to Medication Adherence in Pediatric and Adolescent and Young Adult (AYA) Patients on Anticoagulation

Background: Medication nonadherence rates as high as 50-75% have been widely reported in children and adolescents with chronic medical conditions. Anticoagulation nonadherence is associated with increased morbidity and mortality from hemorrhagic and thrombotic complications, reported mostly in older adult populations. As direct oral anticoagulant use increases, it is critical that pediatric clinicians understand the prevalence, adverse sequelae, and predictors of nonadherence for various anticoagulants prescribed for children and young adults to facilitate self-management in this population. To begin to address these critical knowledge gaps, this study explored the frequency of reported barriers to anticoagulation adherence and the relationship between reported barriers and adherence among a cohort of children and young adults who were prescribed anticoagulants through a pediatric thrombosis clinic. Methods: Data for this abstract were collected as part of a quality improvement (QI) initiative in the pediatric thrombosis clinic from May 2019 to November 2019. This QI initiative included the administration of a self-report measure which asked families to rate the presence/absence of 19 barriers to adherence and respond to two items assessing adherence ("How many anticoagulation doses did you/your child miss in the past 7 days?"; "Did you/your child miss any anticoagulation doses in the past month?"). Patients aged &amp;gt; 10 years (yr.) and/or their caregivers (for patients 0-17 yr.) visiting the clinic for anticoagulation follow-up completed the measure. With IRB approval, results from 161 anonymous measures from 130 families (n = 37 caregivers; n = 62 patients; n = 31 patient/caregiver dyads) were analyzed. Descriptive statistics were used to summarize the most frequent barriers, rates of adherence, and concordance of barriers within patient/caregiver dyads. Linear regression was used to explore relationships between barriers and adherence after controlling for medication administration type (injections versus oral). To ensure only one measure per family was included in this analysis, the regression was run on the subset of measures completed by caregivers of children &amp;lt; 18 yr. and patients ≥ 18 yr. (n = 105 [37 caregivers + 62 patients + 31 caregivers from patient/caregivers dyad = 130 families; 130 - 25 families with missing adherence data = 105 families]). Results: Of 161 reporters, 120 reported at least 1 barrier. The most common barriers were medication side effects (n = 44), alterations in lifestyle secondary to medication (n = 44) and forgetting to take the medications (n = 37). The distributions of barriers by reporter and medication type are illustrated in Figure 1. Of 31 dyads, 26 reported 1 or more barriers. Only 6 caregiver/child dyads reported the same set of barriers. The remaining 77% (n = 20) of caregivers endorsed different barriers than their children. On average, patients and caregivers reported 1.85 barriers (SD = 1.95, range 0 - 10) and that they/their child took 96% of prescribed doses (SD= 9%, range = 71 - 100%). The linear regression was significant (F(2, 102) = 4.19, p = 0.02, R2 = 0.08). After controlling for medication type (p = 0.06), a greater number of barriers was significantly associated with lower adherence (t = -2.63, p = 0.01). Every one unit increase in total barriers (1 additional barrier reported) was associated with a decrease of .26% in adherence. Discussion: Although self-reported adherence was high, 75% of patients and caregivers reported 1 or more barriers to adherence. A greater number of barriers is associated with lower adherence, regardless of medication route, suggesting that addressing reported barriers might improve adherence. The spectrum of reported barriers was diverse, differing even within patient and caregiver dyads. Therefore, it is important to evaluate both patients and caregivers to fully assess the burden of barriers. Future studies are needed to evaluate the impact of addressing barriers and the relationship between anticoagulation adherence, barriers, and health outcomes. Figure 1 Disclosures Luchtman-Jones: Corgenix: Other: Provided discounted kits for study; Accriva Diagnostics: Other: Provided kits for study.

M183. SINGLE-SESSION DANCE/MOVEMENT THERAPY FOR THOUGHT AND BEHAVIORAL DYSFUNCTION ASSOCIATED WITH ACUTE SCHIZOPHRENIA: A MIXED METHODS FEASIBILITY STUDY

BackgroundDance/movement therapy (DMT) interventions have been used to support people with schizophrenia; however, these typically include lengthier interventions. Current inpatient hospitalization lengths of stay do not offer the time needed to implement such interventions. The current treatment protocol for people in acute phases of schizophrenia is psychopharmacological; however, high rates of medication nonadherence and limited effects on negative symptomatology suggest the need for complementary psychosocial treatment options. The purpose of this study was to determine: feasibility of protocol completion, feasibility of measurement sensitivity, and the effects of a single-session DMT intervention compared to a single-session verbal treatment as usual (TAU) intervention.MethodsThis mixed methods feasibility study utilized a convergent mixed methods feasibility design. Qualitative and quantitative data were collected simultaneously in a single phase from the experimental and control groups. In this study, the quantitative strand was prioritized and constituted most of the data collection. A qualitative strand was added to enhance the understanding of participants’ experiences of the intervention and control conditions.Thirty-two participants were randomized to a 45-minute DMT session or a 45-minute verbal TAU session. Quantitative data were collected using the Brief Psychiatric Rating Scale, and qualitative data through semi-structured interviews.Resultsindicated that participants in the DMT intervention group had statistically significant symptom reduction versus those in the TAU group in overall BPRS scores (p < 0.001), Psychological Discomfort (p < 0.001), Negative Symptoms (p = 0.007), and Positive Symptoms (p = 0.003). No statistical significance was shown for Resistance. Qualitative findings substantiate the quantitative findings, however, show divergence regarding Resistance. Participants in the DMT group expressed feeling more in control, less angry, and motivated for continued treatment.DiscussionThese findings suggest that a single-session DMT intervention can alleviate symptoms associated with acute schizophrenia including affective regulation, and positive and negative symptomatology such as isolation, spontaneity, interpersonal skills, paranoia, and auditory hallucinations. Psychosocial interventions may be used in tandem with psychopharmacological interventions to support increased stabilization for patients experiencing acute phases of schizophrenia.

A Mobile App (mHeart) to Detect Medication Nonadherence in the Heart Transplant Population: Validation Study

BackgroundMedication nonadherence in heart transplant recipients (HTxR) is related to graft loss and death. mHeart is a mobile app that uses electronic patient-reported outcome measures (ePROMs) to identify and manage medication nonadherence in the outpatient heart transplant (HTx) population.ObjectiveThe study primarily aimed to validate mHeart to measure medication nonadherence in early stage HTxR by assessing the psychometric properties of ePROMs. The secondary aims were to (1) measure patient satisfaction with the mHeart tool and its usability and (2) explore the impact of a theory-based treatment on medication nonadherence rates to determine its scalability to larger research.MethodsA prospective study was conducted in the outpatient clinic of a tertiary hospital. All consecutive early stage HTxR (<1.5 years from HTx) were included. The ePROM psychometric properties assessed were validity, reliability, responsiveness, interpretability, and burden. ePROMs comprised the 4-item Morisky-Green-Levine questionnaire and an adapted version of the Haynes-Sackett questionnaire. The Simplified Medication Adherence Questionnaire (SMAQ) was also applied on-site. Three consecutive medication nonadherence assessments were performed by a transplant pharmacist. To improve medication nonadherence, theory-based interventions were delivered in a 1-month period. Patient satisfaction was assessed by a semiquantitative Web-based survey at the end of the study.ResultsWe included 31 early stage HTxR (age: mean 54 years, SD 12 years), and 71% (22/31) of them were men. The HTxR were taking a mean 13 (SD 4; range 7-18) drugs per day. A total of 42% (13/31) of patients were unaware of the consequences of medication nonadherence, and 39% (12/31) of patients were nonadherent to immunosuppressive treatment. The content validity measure showed excellent levels of expert panel agreement for the Haynes-Sacket (14/14, 100%) and Morisky-Green-Levine (13/14, 93%) questionnaires. SMAQ and Morisky-Green-Levine ePROMs showed similar measurement domains (convergent validity, phi=0.6, P<.001), which, as expected, differed from Haynes-Sackett ePROMs (divergent validity, phi=0.3, P=.12). Reliability assessment revealed a very strong association between ePROM and on-site PROMs (phi>0.7, P<.001). Reproducibility was moderate (Haynes-Sackett κ=0.6, P<.002) or poor (Morisky-Green-Levine κ=0.3, P=.11) because of unexpected improved medication adherence rates during the test-retest period. According to responsiveness, the theory-based multifaceted intervention program improved medication nonadherence by 16% to 26% (P<.05). A burden analysis showed that ePROMs could potentially overcome traditional on-site limitations (eg, automatic recording of ePROM responses in the hospital information system). The mean score for overall patient satisfaction with the mHeart approach was 9 (SD 2; score range: 0-10). All 100% (29/29) of patients surveyed reported that they would recommend the mHeart platform to other HTxR.ConclusionsePROMs adhered to the quality standards and successfully identified medication nonadherence in the HTx population, supporting their widespread use. The theory-based intervention program showed a promising improvement in medication adherence rates and produced excellent patient satisfaction and usability scores in HTxR.