Factors predicting self-reported medication low adherence in a large sample of adults in the US general population: a cross-sectional study

Cross-sectional analysis of factors associated with medication adherence in western Kenya

OBJECTIVES

Poor medication adherence in low-income and middle-income countries is a major cause of suboptimal hypertension and diabetes control. We aimed to identify key factors associated with medication adherence in western Kenya, with a focus on cost-related and economic wealth factors.

SETTING

We conducted a cross-sectional analysis of baseline data of participants enrolled in the Bridging Income Generation with Group Integrated Care study in western Kenya.

PARTICIPANTS

All participants were ≥35 years old with either diabetes or hypertension who had been prescribed medications in the past 3 months.

PRIMARY AND SECONDARY OUTCOME MEASURES

Baseline data included sociodemographic characteristics, wealth and economic status and medication adherence information. Predictors of medication adherence were separated into the five WHO dimensions of medication adherence: condition-related factors (comorbidities), patient-related factors (psychological factors, alcohol use), therapy-related factors (number of prescription medications), economic-related factors (monthly income, cost of transportation, monthly cost of medications) and health system-related factors (health insurance, time to travel to the health facility). A multivariable analysis, controlling for age and sex, was conducted to determine drivers of suboptimal medication adherence in each overarching category.

RESULTS

The analysis included 1496 participants (73.7% women) with a mean age of 60 years (range 35-97). The majority of participants had hypertension (69.2%), 8.8% had diabetes and 22.1% had both hypertension and diabetes. Suboptimal medication adherence was reported by 71.2% of participants. Economic factors were associated with medication adherence. In multivariable analysis that investigated specific subtypes of costs, transportation costs were found to be associated with worse medication adherence. In contrast, we found no evidence of association between monthly medication costs and medication adherence.

CONCLUSION

Suboptimal medication adherence is highly prevalent in Kenya, and primary-associated factors include costs, particularly indirect costs of transportation. Addressing all economic factors associated with medication adherence will be important to improve outcomes for non-communicable diseases.

TRIAL REGISTRATION NUMBER

NCT02501746.

Adherence and utilization of short-term antibiotics: Randomized controlled study

Enhancing adherence to medication has the potential to improve clinical outcomes and decrease healthcare cost. The role of clinical pharmacist-led education on adherence to short-term antibiotic has never been investigated in Jordan. This study aimed to evaluate the impact of an educational intervention on antibiotic short-term adherence and to assess the antibiotic utilization pattern. A prospective, single blinded, randomized controlled study was conducted in a tertiary referral hospital in Jordan. Adult patients diagnosed with acute infection and prescribed a short-term antibiotic course (< 30 day) were included in the study. Recruited patients were randomly allocated into control and intervention groups. Pharmaceutical education about the correct use of antibiotic/s was provided to the intervention group. The results showed that penicillins were the most prescribed antibiotics (38.7%) followed by fluoroquinolones (23.9%) and cephalosporines (20.9%). Patients in the intervention group were more likely to be adherent to the prescribed antibiotics compared to control group (OR = 1.445, 95CI% = 1.029-2.030, p = 0.033). Employed patients, less frequent administration of antibiotic, and searching information related to the prescribed antibiotics were factors associated with better adherence to short-term antibiotic (p<0.05). The most common reasons for non-adherence were feeling better and forgetfulness to take medication. These findings highlighted that pharmacist-led educational intervention significantly enhance adherence to prescribed short-term antibiotics which is a major drive to control antibiotic resistance. Initiatives should be adopted to include patient education as a regular element in the medication dispensing process. Clinical trial registration: The trial is registered at ClinicalTrials.gov (identifier: NCT05293977).

Heritable Risk and Protective Genetic Components of Glaucoma Medication Non-Adherence

Glaucoma is the leading cause of irreversible blindness, affecting 76 million globally. It is characterized by irreversible damage to the optic nerve. Pharmacotherapy manages intraocular pressure (IOP) and slows disease progression. However, non-adherence to glaucoma medications remains problematic, with 41–71% of patients being non-adherent to their prescribed medication. Despite substantial investment in research, clinical effort, and patient education protocols, non-adherence remains high. Therefore, we aimed to determine if there is a substantive genetic component behind patients’ glaucoma medication non-adherence. We assessed glaucoma medication non-adherence with prescription refill data from the Marshfield Clinic Healthcare System’s pharmacy dispensing database. Two standard measures were calculated: the medication possession ratio (MPR) and the proportion of days covered (PDC). Non-adherence on each metric was defined as less than 80% medication coverage over 12 months. Genotyping was done using the Illumina HumanCoreExome BeadChip in addition to exome sequencing on the 230 patients (1) to calculate the heritability of glaucoma medication non-adherence and (2) to identify SNPs and/or coding variants in genes associated with medication non-adherence. Ingenuity pathway analysis (IPA) was utilized to derive biological meaning from any significant genes in aggregate. Over 12 months, 59% of patients were found to be non-adherent as measured by the MPR80, and 67% were non-adherent as measured by the PDC80. Genome-wide complex trait analysis (GCTA) suggested that 57% (MPR80) and 48% (PDC80) of glaucoma medication non-adherence could be attributed to a genetic component. Missense mutations in TTC28, KIAA1731, ADAMTS5, OR2W3, OR10A6, SAXO2, KCTD18, CHCHD6, and UPK1A were all found to be significantly associated with glaucoma medication non-adherence by whole exome sequencing after Bonferroni correction (p < 10−3) (PDC80). While missense mutations in TINAG, CHCHD6, GSTZ1, and SEMA4G were found to be significantly associated with medication non-adherence by whole exome sequencing after Bonferroni correction (p < 10−3) (MPR80). The same coding SNP in CHCHD6 which functions in Alzheimer’s disease pathophysiology was significant by both measures and increased risk for glaucoma medication non-adherence by three-fold (95% CI, 1.62–5.8). Although our study was underpowered for genome-wide significance, SNP rs6474264 within ZMAT4 (p = 5.54 × 10–6) was found to be nominally significant, with a decreased risk for glaucoma medication non-adherence (OR, 0.22; 95% CI, 0.11–0.42)). IPA demonstrated significant overlap, utilizing, both standard measures including opioid signaling, drug metabolism, and synaptogenesis signaling. CREB signaling in neurons (which is associated with enhancing the baseline firing rate for the formation of long-term potentiation in nerve fibers) was shown to have protective associations. Our results suggest a substantial heritable genetic component to glaucoma medication non-adherence (47–58%). This finding is in line with genetic studies of other conditions with a psychiatric component (e.g., post-traumatic stress disorder (PTSD) or alcohol dependence). Our findings suggest both risk and protective statistically significant genes/pathways underlying glaucoma medication non-adherence for the first time. Further studies investigating more diverse populations with larger sample sizes are needed to validate these findings.

Effects of Adjuvant Medications on A1C, Body Mass Index, and Insulin Requirements among Patients with Type 1 Diabetes

Randomized controlled trials have demonstrated that noninsulin medications used to treat type 2 diabetes can improve health outcomes among patients with type 1 diabetes (T1D). This study assessed the effects of adjuvant diabetes medications on glycated hemoglobin (A1C), body mass index (BMI), or total daily insulin (TDI) among patients with T1D in a real-world setting. This was an analysis of the T1D Exchange Clinic Registry, using the study periods of 2010−2012, 2015−2016, and 2016−2017, to assess differences in A1C, BMI, and TDI between patients with and without adjuvant medications. The relationships between characteristics and A1C in 2015−2016 and 2016−2017 were determined. Analysis included 517 patients in the adjuvant medication cohort and 4968 in the insulin-only cohort. No significant improvement in A1C was observed. A significant difference in BMI and TDI between the insulin-only (median BMI: 25.5, 26.2, 26.4 and median TDI: 45, 44 units) and adjuvant medication cohorts (median BMI: 29.8, 30.5, 30.5 and median TDI: 51, 52 units) (p < 0.001) was observed. Patients with a continuous glucose monitor (CGM), higher education level, higher annual income, and older age were associated with lower A1C (p ≤ 0.001). Higher BMI and self-description as African American/Black were associated with higher A1C (p ≤ 0.01). Insulin pump use was associated with lower A1C (p < 0.01) in 2015−2016. Patients who used adjuvant medications did not demonstrate significant improvement in disease control. These data suggest that findings from well-designed research studies may not be consistently reproducible in real-world settings, due to patient-specific factors.

Primary medication nonadherence in a large primary care population: Observational study from Manitoba

OBJECTIVE

To analyze primary medication nonadherence across several prescription indications and test the predictors of drug nonadherence in an adult primary care population.

DESIGN

Retrospective observational study using primary care provider prescriptions linked to pharmacy-based dispensing data from 2012 to 2014.

SETTING

Manitoba.

PARTICIPANTS

Patients in the Manitoba Primary Care Research Network.

MAIN OUTCOME MEASURES

Prevalence of primary medication nonadherence by drug class. Multivariable logistic regression models were used to test the associations of patient demographic and clinical or provider characteristics with primary medication nonadherence. The C statistic was used to assess the models' discriminative performance.

RESULTS

A total of 91,660 unique prescriptions were assessed from a cohort of more than 200,000 patients. Primary medication nonadherence ranged from 13.7% (antidepressants) to 30.3% (antihypertensives). In conditions that typically present symptomatically (eg, infections, anxiety) nonadherence ranged from 13.7% to 17.5%. The range was 21.2% to 30.0% for medications related to asymptomatic conditions or those typically detected by screening. The discriminative performance of the models based on patient demographic, clinical, or provider characteristics was weak.

CONCLUSION

Primary medication nonadherence is common, occurring more often in asymptomatic conditions. The poor predictability of the models suggests that caution is required when considering characteristic-based interventions or prediction tools to improve primary medication nonadherence.

Alleviating time poverty among the working poor: a pre-registered longitudinal field experiment

Poverty entails more than a scarcity of material resources-it also involves a shortage of time. To examine the causal benefits of reducing time poverty, we conducted a longitudinal field experiment over six consecutive weeks in an urban slum in Kenya with a sample of working mothers, a population who is especially likely to experience severe time poverty. Participants received vouchers for services designed to reduce their burden of unpaid labor. We compared the effect of these vouchers against equivalently valued unconditional cash transfers (UCTs) and a neutral control condition. In contrast to our pre-registered hypotheses, a pre-registered Bayesian ANCOVA indicated that the time-saving, UCT, and control conditions led to similar increases in subjective well-being, reductions in perceived stress, and decreases in relationship conflict (Cohen's d's ranged from 0.25 to 0.85 during the treatment weeks and from 0.21 to 0.36 at the endline). Exploratory analyses revealed that the time-saving vouchers and UCTs produced these benefits through distinct psychological pathways. We conclude by discussing the implications of these results for economic development initiatives. PROTOCOL REGISTRATION: The Stage 1 protocol for this Registered Report was accepted in principle on 27/06/2019. The protocol, as accepted by Nature Human Behaviour, can be found at https://doi.org/10.6084/m9.figshare.c.4368455 .

Artificial Intelligence, Heuristic Biases, and the Optimization of Health Outcomes: Cautionary Optimism

The use of artificial intelligence (AI) and machine learning (ML) in clinical care offers great promise to improve patient health outcomes and reduce health inequity across patient populations. However, inherent biases in these applications, and the subsequent potential risk of harm can limit current use. Multi-modal workflows designed to minimize these limitations in the development, implementation, and evaluation of ML systems in real-world settings are needed to improve efficacy while reducing bias and the risk of potential harms. Comprehensive consideration of rapidly evolving AI technologies and the inherent risks of bias, the expanding volume and nature of data sources, and the evolving regulatory landscapes, can contribute meaningfully to the development of AI-enhanced clinical decision making and the reduction in health inequity.

Efficacy of Selective Laser Trabeculoplasty after iStent Implantation in Primary Open-Angle Glaucoma

iStent implantation is thought to augment the trabecular outflow channel in the anterior segment of the eye. We hypothesized that iStent with subsequent selective laser trabeculoplasty (SLT) would better control the intraocular pressure (IOP) compared to standalone SLT in patients with primary open-angle glaucoma (POAG). We, therefore, determined if the presence of an iStent combined with SLT was statistically associated with IOP lowering compared to standalone SLT. Through retrospective electronic medical record review, records of 824 eyes from 440 patients who received primary SLT without a history of iStent were considered. Additionally, 42 eyes from 28 patients who received SLT after combined phacoemulsification and iStent implantation that failed to control intraocular pressure (IOP) and/or the progression of the disease were retrospectively reviewed. IOP and number of medications, which were tracked in each patient for up to 12 months post laser, were also examined. Successful outcome was defined as a statistically significant reduction in IOP or number of medications at 6 months. As defined in univariate analysis (p ≤ 0.01), multivariate analysis included iStent, age, sex, race, and initial IOP as variables. IOP reduction was statistically associated with patients pre-SLT IOP (p < 0.001) but not with patients with iStent (p = 0.222). Medication reduction was statistically associated with the pre-SLT number of medications (p < 0.001) and iStent (p < 0.001). In eyes that received SLT, iStent was not statistically associated with a greater reduction in IOP compared to controls, but was associated with a higher reduction in the overall number of medications used 6 months after receiving SLT. The work presented should guide clinicians to consider SLT as an effective therapy after iStent implantation, in terms of glaucoma medication reduction in iStent patients, but clinicians should know that the presence of an iStent does not necessarily make subsequent SLT more effective at lowering IOP.

Older Adults' Socio-Demographic Determinants of Health Related to Promoting Health and Getting Preventive Health Care in Southern United States: A Secondary Analysis of a Survey Project Dataset

Background: This exploratory survey study examined the relationship between older adults’ five socio-demographic determinants (urban/rural residence, gender, age, marital status, and education) and their self-reported perception of importance, desire to perform, and ability to perform nine self-care behaviors related to promoting health and getting preventive health care. Methods: We reported a secondary analysis of a dataset from an exploratory survey project; we analyzed 2015–2016 retrospective data collected from a cross-sectional survey study, including 123 adults aged 65 years and older living in southern United States. Data were collected from the Patient Action Inventory for Self-Care and a demographic questionnaire and analyzed using binary and multiple logistic regression analyses. Results: Advancing age, marital separation, and holding less than a high school education were significantly associated with at least one of the unfavorable perceptions of the importance, the desire to perform, and the ability to perform three self-care behaviors. These three behaviors were: (1) creating habits that will improve health and prevent disease, (2) discussing the use of health screening tests with healthcare providers, and (3) joining in local health screening or wellness events. Gender and urban/rural residence were not significant. Conclusions: Comprehensive health care should include an individual’s socio-demographic context and self-care perception of importance, desire, and ability.

Predicting and improving patient-level antibiotic adherence

Low adherence to prescribed medications causes substantial health and economic burden. We analyzed primary data from electronic medical records of 250,000 random patients from Israel's Maccabi Healthcare services from 2007 to 2017 to predict whether a patient will purchase a prescribed antibiotic. We developed a decision model to evaluate whether an intervention to improve purchasing adherence is warranted for the patient, considering the cost of the intervention and the cost of non-adherence. The best performing prediction model achieved an average area under the receiver operating characteristic curve (AUC) of 0.684, with 82% accuracy in detecting individuals who had less than 50% chance of purchasing a prescribed drug. Using the decision model, an adherence intervention targeted to patients whose predicted purchasing probability is below a specified threshold can increase the number of prescriptions filled while generating significant savings compared to no intervention - on the order of 6.4% savings and 4.0% more prescriptions filled for our dataset. We conclude that analysis of large-scale patient data from electronic medical records can help predict the probability that a patient will purchase a prescribed antibiotic and can provide real-time predictions to physicians, who can then counsel the patient about medication importance. More broadly, in-depth analysis of patient-level data can help shape the next generation of personalized interventions.

Association Between Cost-Related Medication Nonadherence and Hypertension Management Among US Adults

BACKGROUND

Medication nonadherence is an important element of uncontrolled hypertension. Financial factors frequently contribute to nonadherence. The objective of this study was to examine the association between cost-related medication nonadherence (CRMN) and self-reported antihypertensive medication use and self-reported normal blood pressure among US adults with self-reported hypertension.

METHODS

Participants with self-reported hypertension from the 2017 National Health Interview Survey were included (n = 7,498). CRMN was defined using standard questions. Hypertension management included: (i) self-reported current antihypertensive medication use and (ii) self-reported normal blood pressure within the past 12 months. Adjusted prevalence and prevalence ratios of hypertension management indicators among those with and without CRMN were estimated.

RESULTS

Overall, 10.7% reported CRMN, 83.6% reported current antihypertensive medication use, and 67.4% reported normal blood pressure within past 12 months. Adjusted percentages of current antihypertensive medication use (88.6% vs. 82.9%, P < 0.001) and self-reported normal blood pressure (69.8% vs. 59.5%, P = 0.002) were higher among those without CRMN compared with those with CRMN. Adjusted prevalence ratios showed that, compared with those with CRMN, those without CRMN were more likely to report current antihypertensive medication use (odds ratio = 1.08, 95% confidence interval 1.04-1.12) and self-reported normal blood pressure (1.15 (1.07-1.23)).

CONCLUSIONS

Among US adults with self-reported hypertension, those without CRMN were more likely to report current antihypertensive medication use and normal blood pressure within the past 12 months. Financial barriers to medication adherence persist and impact hypertension management.

Primary medication non-adherence at Counties Manukau Health Emergency Department (CMH-ED), New Zealand: an observational study

OBJECTIVES

To measure primary medication non-adherence (failure to fill prescription medicines) in patients discharged from the emergency department (ED), and to determine whether sociodemographic factors, smoking status and access to a general practitioner affect prescription filling. Little is known about primary medication non-adherence in EDs, and less so in New Zealand (NZ). Identifying reasons for non-adherence will enable development of strategies to improve adherence and reduce morbimortality.

DESIGN AND SETTING

An observational study based on patient data from the ED of a large public hospital in South Auckland, NZ.

PARTICIPANTS

Data were collected from 1600 patients discharged between 28 April-6 May and 28 July-9 August 2014. Data were included if patients were residents within the Auckland Regional Public Health Service boundaries, admitted to ED and discharged with a prescription. Data were excluded if patients were admitted to another ward, transferred to another hospital or left the ED without seeing a doctor.

RESULTS

992 patients were included in the study, the majority were under 10 years (32.6%), of Pacific Island descent (42.8%), NZ-born (67.7%) and living in the most socioeconomically deprived areas (78.1%). Almost 50% of patients failed to fill all prescription medications. Simple linear regression analysis indicated that non-adherence was significant for those 10-24 years (n=236; adherence=47.2%; p<0.05), of NZ Māori ethnicity (n=175; 51.3%; p=0.01), unemployed (n=77; 46.8%; p<0.01), homemakers (n=66; 45.7%; p<0.01), students (n=228; 55.6%; p<0.05) and cigarette smokers (n=139; 50.3%; p<0.01). Following multivariable analysis, the strongest predictors for non-adherence were those aged between 10 and 17 years (n=116; p<0.01), the unemployed (n=77; p=0.01) and homemakers (n=66; p=0.01).

CONCLUSIONS

Age and occupation were the greater predictors of non-adherence; however, no other significant differences were found. Since this study, changes to prescription co-payments have been made. Further research is warranted to assess whether this change has more recently affected the rates of non-adherence.

Social support, social context and nonadherence to treatment in young senior patients with multimorbidity and polypharmacy followed-up in primary care. MULTIPAP Study

OBJECTIVE

To estimate the prevalence of nonadherence to treatment and its relationship with social support and social context in patients with multimorbidity and polypharmacy followed-up in primary care.

METHODS

This was an observational, descriptive, cross-sectional, multicenter study with an analytical approach. A total of 593 patients between 65-74 years of age with multimorbidity (≥3 diseases) and polypharmacy (≥5 drugs) during the last three months and agreed to participate in the MULTIPAP Study. The main variable was adherence (Morisky-Green). The predictors were social support (structural support and functional support (DUFSS)); sociodemographic variables; indicators of urban objective vulnerability; health-related quality of life (EQ-5D-5L-VAS & QALY); and clinical variables. Descriptive, bivariate and multivariate analyses with logistic regression models and robust estimators were performed.

RESULTS

Four out of ten patients were nonadherent, 47% had not completed primary education, 28.7% had an income ≤1050 €/month, 35% reported four or more IUVs, and the average perceived health-related quality of life (HRQOL) EQ-5D-5L-VAS was 65.5. The items that measure functional support, with significantly different means between nonadherent and adherent patients were receiving love and affection (-0.23; 95%CI: -0.40;-0.06), help when ill (-0.25; 95%CI: -0.42;-0.08), useful advice (-0.20; 95%CI: -0.37;-0.02), social invitations (-0.22; 95%CI:-0.44;-0.01), and recognition (-0.29; 95%CI:-0.50;-0.08). Factors associated with nonadherence were belonging to the medium vs. low tertile of functional support (0.62; 95%CI: 0.42;0.94), reporting less than four IUVs (0.69; 95%CI: 0.46;1.02) and higher HRQOL perception (0.98; 95%CI: 0.98;0.99).

CONCLUSIONS

Among patients 65-74 years of age with multimorbidity and polypharmacy, lower functional support was related to nonadherence to treatment. The nonadherence decreased in those patients with higher functional support, lower urban vulnerability and higher perceived health status according to the visual analog scale of health-related quality of life.

Optimization of Electronically Monitored Non-Adherence in Highly Adherent Renal Transplant Recipients by Reducing the Dosing Frequency - A Prospective Single-Center Observational Study

BACKGROUND

Non-adherence (NA) after renal transplantation poses a major risk for allograft rejection, graft loss, and patient mortality. Yet, there is still ambiguity about its etiology and its possible relationships with patient-related factors. In order to prevent poor outcomes after transplantation, it is crucial to gain a more refined understanding of potential determinants, to identify patients at risk, and to intervene accordingly. The objective of this study was to assess potential risk factors of NA by prospectively applying electronic monitoring.

MATERIALS AND METHODS

This was a single-center prospective observational study. Prior to study initiation, sociodemographic, biomedical, and psychosocial variables (depression, health-related quality of life, self-efficacy, social support, attachment, experiences and attitudes towards immunosuppressive medication, emotional responses after organ transplantation, satisfaction with information about immunosuppressive medication, and perceptions and beliefs about medications) were assessed. Thereafter, immunosuppressive adherence behavior was measured prospectively via electronic monitoring (EM, VAICA©) during a 3-month period to receive the percentage frequency of Taking and Timing Adherence (±2h, ±30min) for each patient. Focus of this study was the phase of medication implementation.

RESULTS

A total of 78 patients participated in our study (mean age 55.28, 56% male). We found rates of 99.39% for Taking Adherence, 98.34% for Timing Adherence ±2h, and 93.34% for Timing Adherence ±30min, respectively.  Multiple regression analyses revealed that the type of medication could significantly predict Taking Adherence. Patients receiving Advagraf© (once daily) depicted better Taking Adherence than patients receiving Prograf© (twice daily) (p=0.04). No associations were found for Timing Adherence (±2h, ±30min). Sociodemographic, biomedical, or psychosocial variables were not found to be associated with adherence behavior.

DISCUSSION

In highly adherent populations, only a few factors can be altered to improve adherence. Changing the immunosuppressive regimen from twice-daily to once-daily could be an option for optimizing adherence. However, risk factors for NA could be different in a less adherent population.

Self-Reported Nonadherence Associated with Pharmacy and Home Medication Management Inconvenience Factors in a US Adult Population

PURPOSE

Medication nonadherence is a significant and multidimensional problem contributing to an increased risk of morbidity and mortality. Inconveniences in pharmacy and home contexts may increase nonadherence. This research examined inconveniences in pharmacy and home contexts associated with self-reported nonadherence, controlling for demographic and medication-taking covariates.

METHODS

Data from 4682 individuals who reported self-managing medications in an online marketing survey between October and December 2017 were analyzed in this secondary analysis. Nonadherence was dichotomized using a single question about likelihood to take medications as prescribed (adherence=always; nonadherence=most of the time, some of the time, never). Multivariable logistic regression with backwards elimination was used to examine the pharmacy (use of home delivery, number prescriptions picked up and visits to pharmacy) and home context (method used to organize/manage medications, satisfaction, and bother with management) variables and the demographic (age, sex, race/ethnicity, education, income, insurance) and medication (number of oral medications, medication changes and frequency of taking) covariates associated with nonadherence.

RESULTS

Overall, 25.8% of the responses indicated nonadherence. Nonadherence was more likely for individuals making fewer separate pharmacy trips (OR 0.98; 95% CI 0.97-0.99); picking up fewer prescriptions (OR 0.96; 95% CI 0.93-0.99); never, rarely or sometimes using mail order compared with always (OR 1.71; 95% CI 1.30-2.26); not satisfied with managing medications (OR 2.13; 95% CI 1.42-3.19); and using pill pouches and being bothered by them (OR 8.28; 95% CI 1.83-37.31). Using pill pouches or a pillbox and not being bothered by them significantly decreased nonadherence likelihood. Younger and female respondents and those reporting medication changes in the last year were also more likely to report nonadherence.

CONCLUSION

Though reasons for nonadherence are multidimensional, this study suggests that inconveniences in both the pharmacy and home context are important. Improving adherence requires addressing issues of inconvenience across the care continuum.

Accuracy of Prescription Claims Data in Identifying Truly Nonadherent Patients

BACKGROUND

Administrative claims data are increasingly used to identify nonadherent patients. This necessitates a comprehensive review and assessment of their accuracy in identifying nonadherent patients.

OBJECTIVES

To (a) compare administrative claims-based measures of adherence with nonadherence verified by patient interview; (b) determine if and to what extent patients classified as nonadherent based on prescription claims differ from patients classified as nonadherent based on interventions designed to gather multiple types of medication lists to compare against the prescription fill history; and (c) assess the various patient-reported reasons for nonadherence.

METHODS

A cross-sectional study was used to identify patients from the Southern Piedmont Community Care Network of North Carolina who were enrolled with Medicaid between January 1, 2012, and May 31, 2013, and were using prescription medications for 1 or more chronic conditions. Patients with more than a 30-day gap in refill history were identified using prescription claims and were interviewed by pharmacists to assess the reasons for nonadherence. Based on the patient-reported reasons for a gap in refill, patients were classified as interview-verified nonadherent patients or interview-verified adherent patients. The positive predictive value of prescription claims in identifying nonadherent patients was calculated, and descriptive statistics were reported. Characteristics of interview-verified nonadherent patients were compared with adherent patients using t-tests and chi-square statistics.

RESULTS

1,425 patients representing 2,936 patient-class of medication combinations were included in the final analysis. 824 (28.07%) of the 2,936 records that were flagged as nonadherent using claims analysis were confirmed as adherent during patient interviews. The positive predictive value of claims records in identifying nonadherent patients was 0.72. The 2 most common reasons for patients to be misclassified as nonadherent in claims data following self-report were discontinuation of medication on prescribers' directions (21.93%) and having an alternate channel for receiving the medication (6.13%). Among interview-verified nonadherent patients, side effects, patient beliefs, education, and socioeconomic barriers were the most common patient-reported reasons for gaps in refill.

CONCLUSIONS

Prescription claims may underestimate adherence in patients. When interviewed directly by a pharmacist, most patients reported discontinuation of medication as per prescribers' directions. To determine the overall validity of prescription claims data, further analysis is required to assess its accuracy in identifying truly nonadherent patients among those who are identified as nonadherent by claims data.

DISCLOSURES

No outside funding supported this study. Glassberg and Wei were employees at Community Care of North Carolina when this research was conducted. Trygstad is an employee of Community Care of North Carolina; Robinson is an employee of Community Care of Southern Piedmont, a subsidiary of Community Care of North Carolina. The geographies, health care professionals, and subjects involved in the study were related to the care coordination work that Community Care of North Carolina was charged with implementing through its informatics and subject matter expertise assistance provided to these local entities to augment primary care activities. Farley has received funding from the Agency for Healthcare Research and Quality, Centers for Disease Control and Prevention, American College of Clinical Pharmacy, the National Institutes of Health, and Community Care of North Carolina and has also received consulting funds from UCB. The other authors have nothing additional to report.

Effects of Three Antecedents of Patient Compliance for Users of Peer-to-Peer Online Health Communities: Cross-Sectional Study

Background

Over the past 50 years, patient noncompliance has appeared as a major public health concern and focus of a great deal of research because it endangers patient recovery and imposes a considerable financial burden on health care systems. Meanwhile, online health communities (OHCs) are becoming more common and are commonly used by individuals with health problems, and they may have a role in facilitating compliance. Despite this growing popularity, little is known about patient compliance predictors for OHCs’ users.

Objective

This study aimed to investigate the extent to which participating in OHCs may trigger higher levels of compliance. It identified 3 interrelated predictors that may affect patient compliance: patient empowerment gained through peer-to-peer OHCs, satisfaction with the physician, and commitment to the physician.

Methods

A Web-based survey tested the conceptual model and assessed the effects of patient empowerment gained through OHCs on patient satisfaction and commitment to the physician, as well as the effects of these 3 predictors on patient compliance with the proposed treatment. Members of peer-to-peer OHCs were asked to answer an online questionnaire. A convenience sample of 420 patients experiencing chronic illness and using peer-to-peer OHCs was surveyed in August 2018 in Québec, Canada. A path analysis using structural equation modeling tested the proposed relationships between the predictors and their respective paths on patient compliance. The mediation effects of these predictor variables on patient compliance were estimated with the PROCESS macro in SPSS.

Results

The findings indicated that patient empowerment gained through OHCs was positively related to patient commitment to the physician (beta=.69; P<.001) and patient compliance with the proposed treatment (beta=.35; P<.001). Patient commitment also positively influenced patient compliance (beta=.74; P<.001). Patient empowerment did not exert a significant influence on patient satisfaction with the physician (beta=.02; P=.76), and satisfaction did not affect compliance (beta=−.07; P=.05); however, patient satisfaction was positively related to patient commitment to the physician (beta=.14; P<.01). The impact of empowerment on compliance was partially mediated by commitment to the physician (beta=.32; 95% CI 0.22-0.44) but not by satisfaction.

Conclusions

This study highlights the importance of peer-to-peer OHCs for two main reasons. The primary reason is that patient empowerment gained through peer-to-peer OHCs both directly and indirectly enhances patient compliance with the proposed treatment. The underlying mechanisms of these effects were shown. Second, commitment to the physician was found to play a more critical role than satisfaction with the physician in determining patient-physician relationship quality. Overall, our findings support the assumption that health care stakeholders should encourage the use of peer-to-peer OHCs to favor patient empowerment and patient commitment to the physician to increase patient compliance with the proposed treatment.

Personalized Care in the Prevention of Treatment-Related Cardiac Dysfunction in Female Cancer Survivors

Background: The American Cancer Society projects the number of U.S. cancer survivors to exceed 20 million individuals by 2026. However, approximately one in four cancer survivors report decreased quality of life due to physical dysfunction and disabling symptoms. Many effective anticancer treatments are now understood to be associated with cardiotoxicity, such that, for many survivors, the risk of death from cardiovascular disease now exceeds that of recurrent cancer. Materials and Methods: We undertook a Clinical Review of cancer treatment-related cardiac dysfunction (CTRCD) associated with standard treatment regimens with attention to risks experienced by female cancer patients and survivors. Results: Risks of standard (chemotherapy, radiotherapy) and targeted (antibodies, kinase inhibitors) in development of CTCRD in females are discussed. Multidisciplinary approaches in prevention are reviewed. Conclusions: Female cancer survivors with CTRCD represent an entirely new population at high risk of morbidity and mortality. Increased awareness of the short- and long-term effects of anti-cancer treatments is necessary for the community health care provider for early detection and CTRCD risk reduction.

Effects of a long-term smartphone-based self-monitoring intervention in patients with lipid metabolism disorders

The majority of lipid metabolism disorders can be managed well if patients adhere to their therapies. Self-monitoring can drive adherence with regards to medication intake, physical activities, and nutrition. Technical devices like smartphones can further support its users to achieve health-related goals. In a clinical trial, 100 patients with lipid metabolism disorders were asked to use a smartphone application over a duration of 12 months. Users of this app could set reminders to keep track of their medication and other disease-related variables, such as weight and cholesterol. More than half of all patients that started to use the app continued to use the app over the full 12 months. However, 43% of the patients that were asked to use the app stated that they never started to use the app. The reasons cited were lack of time, health problems, lack of motivation, and technical problems. The number of patients with high medication adherence increased significantly due to the use of the app. Health apps might benefit patients by enabling them to better manage chronic diseases, but successful digital health concepts will need to address efficient onboarding as well as long-term motivation.

Detection and Analysis of Drug Misuses. A Study Based on Social Media Messages

Drug misuse may happen when patients do not follow the prescriptions and do actions which lead to potentially harmful situations, such as intakes of incorrect dosage (overuse or underuse) or drug use for indications different from those prescribed. Although such situations are dangerous, patients usually do not report the misuse of drugs to their physicians. Hence, other sources of information are necessary for studying these issues. We assume that online health fora can provide such information and propose to exploit them. The general purpose of our work is the automatic detection and classification of drug misuses by analysing user-generated data in French social media. To this end, we propose a multi-step method, the main steps of which are: (1) indexing of messages with extended vocabulary adapted to social media writing; (2) creation of typology of drug misuses; and (3) automatic classification of messages according to whether they contain drug misuses or not. We present the results obtained at different steps and discuss them. The proposed method permit to detect the misuses with up to 0.773 F-measure.