Using Dispensing Data to Evaluate Adherence Implementation Rates in Community Pharmacy

Dispensation of outpatient hospital medicines by hospital only versus hospital-community pharmacies collaboration: a cross-sectional study and survey of patient's satisfaction

Goal

To describe the experience of a dispensing model of outpatient hospital medicines (OHM) via collaboration of hospital and community pharmacies, and to explore patient satisfaction with the strategy as compared with the hospital pharmacy only service.

Background

Patient satisfaction is an important component of the quality of health care.

Study

A new model of dispensing OHM was conducted in the Outpatients Unit of the Service of Hospital Pharmacy of Hospital del Mar, in Barcelona, Spain. Participants were patients on stable chronic treatment with clinical or social fragility, immunocompromised patients, and those whose residence was located at a distance from the hospital that justified drug delivery through the community pharmacy. A cross sectional study was done using an ad hoc 14-item questionnaire collecting demographic data, duration of treatment, usual mode of collecting medication, and the degree of satisfaction regarding waiting time for the collection of medication, attention received by professionals, information received on treatment, and confidentiality.

Results

The study population included a total of 4,057 patients (66.8% men) with a mean age of 53 (15.5) years, of whom 1,286 responded, with a response rate of 31.7%. Variables significantly associated with response to the survey were age over 44 years, particularly the age segment of 55-64 years (odds ratio [OR] 2.51) and receiving OHM via the community pharmacy (OR 12.76). Patients in the community pharmacy group (n = 927) as compared with those in the hospital pharmacy group (n = 359) showed significantly higher percentages of 'satisfied' and 'very satisfied' (p < 0.001) in the waiting time for the collection of OHM (88.1% vs. 66%), attention received by professionals (92.5% vs. 86.1%), and information received on treatment (79.4% vs. 77.4%). In relation to confidentiality, results obtained were similar in both pharmacy settings.

Conclusion

Dispensing OHM through the community pharmacy was a strategy associated with greater patient satisfaction as compared with OHM collection at the hospital pharmacy service, with greater accessibility, mainly due to close distance to the patient's home. The participation of community pharmacists could further optimize the care received by patients undergoing OHM treatment.

From non-adherence to adherence: Can innovative solutions resolve a longstanding problem?

Non-adherence to medication is a longstanding problem, profoundly affecting patient outcomes and sustainability of healthcare systems. Historically, non-adherence has been observed since the time of Hippocrates, however, when potent drugs became available in the midst of the 20th century, it became a pivotal concern. Despite numerous studies and interventions designed, medication adherence rates remain suboptimal, currently reaching about 50 % still, as described in WHO report two decades ago. What is worse, many healthcare professionals feel neither responsible nor able to change it. Enhancing adherence requires in-depth understanding of the concept, as many intuitive approaches fail to work. For example, contrary to expectations, patient education alone proves insufficient when addressing this issue. Both behavioural models and recent experience reflecting low acceptance of COVID-19 vaccinations strongly suggest that patients' decisions are driven by emotions, which often results in intentional non-adherence. Several technical innovations, such as smart inhalers and electronic pill dispensers, offer potential solutions. However, their effectiveness varies, and standardized certification procedures are lacking. Altogether, technical solutions do not eliminate the problem entirely. To move forward, social and health system innovation is equally needed. Multiple stakeholders could benefit from improved adherence, therefore their greater involvement is advisable to create an adherence-supporting environment. In conclusion, despite available evidence-based interventions, non-adherence remains a complex challenge. Technical and social innovations, combined with a shift in policy priorities, could lead to improved medication adherence and better patient outcomes. The global tide of non-communicable chronic conditions, and aging of societies urges us to take this problem seriously.

Impact of hospital pharmacist-delivered individualised pharmaceutical service intervention on clinical and patient-reported outcomes in patients with hypertension: a randomised controlled trial

OBJECTIVES

Patients with hypertension in Nepal are often known to have poor medication adherence and quality of life. This randomised controlled trial aimed to evaluate the impact of a hospital pharmacist-delivered individualised pharmaceutical service (P-DIPS) intervention on blood pressure, medication adherence and health-related quality of life (HRQoL) among patients with hypertension in a hospital setting in Nepal.

METHODS

In an open trial, 56 adult patients with hypertension who had been receiving antihypertensive medication for ≥6 months were randomly allocated to a control group (n=28) which received the usual care and an intervention group (n=28) which received a P-DIPS along with the usual care. The difference in blood pressure, medication adherence and HRQoL between the two groups at baseline, 2 and 4 months was compared using the Mann-Whitney U test, independent t-test or χ2 tests.

RESULTS

Participants were mostly ≥40 years (86%) and female (57%). There were no significant differences in the baseline characteristics between the control (C) and intervention (I) groups. At 2 months, the two groups had a significant improvement in the median (IQR) Morisky-Green-Levine (MGL) Medication Adherence Score (I=1 (2) vs C=2 (2); p<0.001) and the median (IQR) mental component of HRQoL (I=43.6 (9.5) vs C=37.5 (8.6); p=0.013). At 4 months, there were significant differences in the median (IQR) values of all the outcome measures between the groups (systolic blood pressure: I=125 (10) mmHg vs C=130 (15) mmHg, p=0.008; diastolic blood pressure: 80 (14) mmHg vs 90 (10) mmHg, p=0.012; MGL score: I=1 (1) vs C=2 (1), p<0.001; physical component of HRQoL: 45.0 (9.0) vs 40.3 (8.2), p=0.046; and mental component of HRQoL: 47.1 (11.1) vs 38.8 (8.5), p=0.003).

CONCLUSIONS

The findings suggest that a P-DIPS intervention in the hospital setting of Nepal has a significant potential to improve blood pressure, medication adherence and HRQoL in patients with hypertension.

Exploring patient medication adherence and data mining methods in clinical big data: A contemporary review

BACKGROUND

Increasingly, patient medication adherence data are being consolidated from claims databases and electronic health records (EHRs). Such databases offer an indirect avenue to gauge medication adherence in our data-rich healthcare milieu. The surge in data accessibility, coupled with the pressing need for its conversion to actionable insights, has spotlighted data mining, with machine learning (ML) emerging as a pivotal technique. Nonadherence poses heightened health risks and escalates medical costs. This paper elucidates the synergistic interaction between medical database mining for medication adherence and the role of ML in fostering knowledge discovery.

METHODS

We conducted a comprehensive review of EHR applications in the realm of medication adherence, leveraging ML techniques. We expounded on the evolution and structure of medical databases pertinent to medication adherence and harnessed both supervised and unsupervised ML paradigms to delve into adherence and its ramifications.

RESULTS

Our study underscores the applications of medical databases and ML, encompassing both supervised and unsupervised learning, for medication adherence in clinical big data. Databases like SEER and NHANES, often underutilized due to their intricacies, have gained prominence. Employing ML to excavate patient medication logs from these databases facilitates adherence analysis. Such findings are pivotal for clinical decision-making, risk stratification, and scholarly pursuits, aiming to elevate healthcare quality.

CONCLUSION

Advanced data mining in the era of big data has revolutionized medication adherence research, thereby enhancing patient care. Emphasizing bespoke interventions and research could herald transformative shifts in therapeutic modalities.

Recent Intimate Partner Violence and Oral Contraceptive Pill Adherence in a Cohort of Reproductive-Aged Women

Objective: Intimate partner violence (IPV) is an important public health problem that impacts reproductive decision-making. Although previous literature has reported a negative impact on contraceptive adherence overall, this study specifically aims to investigate the association between IPV and oral contraceptive pill (OCP) adherence. Methods: We analyzed baseline survey data from 373 OCP users participating in the MyNewOptions study. Recent IPV was defined as any positive response to HARK, a 4-question tool assessing emotional, sexual, and physical abuse in the past year, or self-report of sexual coercion in the past 6 months. High OCP adherence was defined by self-report of missing ≤1 pill per month, which was then corroborated by pharmacy claims data. Multivariable regression analyses were performed to assess the influence of recent IPV history and patient-level variables on OCP adherence. Results: Just over half of our participants were highly adherent to OCPs (53.6%), and approximately one-quarter reported recent IPV exposure (25.2%). Women with recent IPV were significantly less likely to be OCP adherent than those without IPV (adjusted odds ratio (AOR) 0.54, 95% confidence interval (CI): 0.32-0.92). Protestant religion was also associated with high OCP adherence (AOR 2.41, 95% CI: 1.24-4.65, compared with no religious affiliation), while younger age groups (18-25 and 26-33 years) were less likely to have high OCP adherence compared with the 34-40 age group (AOR 0.45, 95% CI: 0.20-1.00 and AOR 0.40, 95% CI: 0.18-0.91, respectively). Conclusion: Recent IPV exposure is associated with low OCP adherence among women of reproductive age. ClinicalTrials.gov identifier: NCT02100124.

Drug-related problems and satisfaction among patients receiving pharmacist-led consultations at the initiation of cardiovascular drugs

BACKGROUND

Drug-related problems (DRPs) lead to substantial morbidity and mortality and increase healthcare costs. Several interventions have been developed to reduce DRPs and improve the outcome of drug therapy.

OBJECTIVE

To investigate DRPs identified through a pharmacist-led intervention and to assess patient satisfaction with the intervention.

METHODS

Patients received two pharmacist consultations 1-2 weeks and 3-5 weeks after collecting a new cardiovascular medicine. Information about patient characteristics, beliefs about medicines (BMQ), DRPs, and patient evaluations were collected using questionnaires.

RESULTS

Pharmacists identified DRPs among 52.4% and 43.1% of the 633 patients at consultation 1 and 2, respectively. Of the DRPs reported in consultation 1, 43.7% were solved at consultation 2. Among patients with side effects, patients who received advice on managing these in consultation 1 where more likely to have solved problems at consultation 2 (61.2% vs. 42.6%, p = 0.008). Female gender, high BMQ concern and the number of new medicines were associated with DRPs. Patients were highly satisfied with the intervention. Predictors of satisfaction were female gender, older age, higher BMQ necessity, face-to-face consultations, longer duration of consultation 1, and solved problems in consultation 2.

CONCLUSIONS

The results indicate that the pharmacist-led follow-up intervention can aid early identification and solving of DRPs in patients prescribed new cardiovascular drugs. Knowledge of factors associated with DRPs and patients' satisfaction may allow further improvement of the intervention.

A Pharmacy-Based eHealth Intervention Promoting Correct Use of Medication in Patients With Asthma and COPD: Nonrandomized Pre-Post Study

BACKGROUND

Asthma and chronic obstructive pulmonary disease (COPD) affect millions of people worldwide. While medication can control and improve disease symptoms, incorrect use of medication is a common problem. The eHealth intervention SARA (Service Apothecary Respiratory Advice) aims to improve participants' correct use of inhalation medication by providing information and as-needed tailored follow-up support by a pharmacist.

OBJECTIVE

The primary aim of this study was to investigate the effect of SARA on exacerbation rates in participants with asthma and COPD. Secondary aims were to investigate its effects in terms of adherence to maintenance medication and antimycotic treatment.

METHODS

In this nonrandomized pre-post study, medication dispensing data from 382 Dutch community pharmacies were included. Exacerbation rates were assessed with dispensed short-course oral corticosteroids. Medication adherence between new and chronic users was assessed by calculating the proportion of days covered from dispensed inhalation maintenance medication. Antimycotic treatment was investigated from dispensed oral antimycotics in participants who were also dispensed inhaled corticosteroids (ICS). Outcomes were assessed 1 year before and 1 year after implementation of SARA and were compared between SARA participants and control participants. More specifically, for exacerbation rates and medication adherence, a difference score was calculated (ie, 1 year after SARA minus 1 year before SARA) and was subsequently compared between the study groups with independent-samples t tests. For antimycotics, the relative number of participants who were dispensed antimycotics was calculated and subsequently analyzed with a mixed-effects logistic regression.

RESULTS

The study population comprised 9452 participants, of whom 2400 (25.39%) were SARA participants. The mean age of the population was 60.8 (15.0) years, and approximately two-thirds (n=5677, 60.06%) were female. The results showed an increase in mean exacerbation rates over time for both study groups (SARA: 0.05; control: 0.15). However, this increase in exacerbation rates was significantly lower for SARA participants (t₉₄₅₀=3.10, 95% CI 0.04-0.16; P=.002; Cohen d=0.06). Chronic users of inhalation medication in both study groups showed an increase in mean medication adherence over time (SARA: 6.73; control: 4.48); however, this increase was significantly higher for SARA participants (t₅₈₈₆=-2.74, 95% CI -3.86 to -0.84; P=.01; Cohen d=-0.07). Among new users of inhalation medication, results showed no significant difference in medication adherence between SARA and control participants in the year after implementation of SARA (t₁₄₃₄=-1.85, 95% CI -5.60 to 0.16; P=.06; Cohen d=-0.10). Among ICS users, no significant differences between the study groups were found over time in terms of the proportion of participants who were dispensed antimycotics (t₅₆₅₄=0.29, 95% CI -0.40 to 0.54; P=.76; Cohen d=0).

CONCLUSIONS

This study provides preliminary evidence that the SARA eHealth intervention might have the potential to decrease exacerbation rates and improve medication adherence among patients with asthma and COPD.

Effectiveness of a Pharmacist-Led Web-Based Medication Adherence Tool With Patient-Centered Communication: Results of a Clustered Randomized Controlled Trial

Background

Growing numbers of people use medication for chronic conditions; nonadherence is common, leading to poor disease control. A web-based tool to identify an increased risk for nonadherence with related potential individual barriers might facilitate tailored interventions and improve adherence.

Objective

This study aims to assess the effectiveness of a newly developed tool aimed at improving medication adherence.

Methods

We performed a cluster randomized controlled trial in patients initiating cardiovascular or oral blood glucose–lowering medication. Participants were recruited from community pharmacies. They completed an online questionnaire comprising assessments of their risk for medication nonadherence and subsequently of barriers to adherence. In pharmacies belonging to the intervention group, individual barriers displayed in a graphical profile on a tablet were discussed by pharmacists and patients with high nonadherence risk in face-to-face meetings and shared with their general practitioners and practice nurses. Tailored interventions were initiated by pharmacists. Barriers of control patients were not presented nor discussed and these patients received usual care. The primary outcome was the effectiveness of the intervention on medication adherence at 8 months’ follow-up between patients with an increased nonadherence risk from the intervention and control groups, calculated from dispensing data.

Results

Data from 492 participants in 15 community pharmacies were available for analyses (intervention 253, 7 pharmacies; control 239, 8 pharmacies). The intervention had no effect on medication adherence (B=–0.01; 95% CI –0.59 to 0.57; P=.96), nor in the post hoc per-protocol analysis (B=0.19; 95% CI –0.50 to 0.89; P=.58).

Conclusions

This study showed no effectiveness of a risk stratification and tailored intervention addressing personal barriers for medication adherence. Various potential explanations for lack of effectiveness were identified. These explanations relate, for instance, to high medication adherence in the control group, study power, and fidelity. Process evaluation should elicit possible improvements and inform the redesign of intervention and implementation.

Trial Registration

The Netherlands National Trial Register NTR5186; https://tinyurl.com/5d8w99hk

Development and testing of a framework for defining a strategy to address medication adherence during patient encounters in community pharmacies

Background

Counseling patients on medication adherence could be ameliorated in pharmacy practice. There is a lack of simple and practical strategies to address medication adherence with patients in daily practice. The goal was to develop and test a framework that allows pharmacy teams to define and apply a strategy to address medication adherence in community pharmacies.

Methods

A framework based on the principles of social marketing was developed. It consisted of 3 items: the target patient (“Who”), the target plan (“How”), and the target goal (“How many”). To test the framework, each participating pharmacy team developed their strategy by defining the 3 items and applied them during one pilot day. A master student observed the encounters between patients and pharmacy team members and used a structured checklist to document the patient's characteristics, counseling content, and strategy use. Pharmacy teams answered a feedback questionnaire at the end of the pilot day.

Results

Ten pharmacy teams were included. During a brainstorming session that lasted on average 31 ± 8 min, unique strategies comprised 18 different target patients and 20 different target plans. The planned target goal was a mean of 31 patients (range: 1 to “all”). A total of 325 encounters were observed, of which 208 patients (64%) corresponded to the predefined target patients. Medication adherence was addressed with 73 patients (22.5%), and adherence counseling was performed with 50 patients (15%). The pharmacy teams accepted the framework and judged it feasible and adaptable to their needs.

Conclusion

The proposed framework represents a simple tool that enables pharmacy teams to develop a strategy for addressing medication adherence in community pharmacies. Its adoption by pharmacy teams occurred without additional training and its integration into daily practice without difficulties. A further study is now needed to investigate if pharmacy teams can successfully engage patients in discussion on medication adherence and ultimately propose targeted adherence interventions.

•

A 3-item framework to address medication adherence in pharmacies was introduced.

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The three framework was well received by the pharmacy teams.

•

The adoption of the 3-item framework by the pharmacy teams was simple and quick.

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The teams chose target patient not according to known factors for poor adherence

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Patients reacted mainly positively when asked about medication adherence

Effectiveness of a medication adherence management intervention in a community pharmacy setting: a cluster randomised controlled trial

BACKGROUND

Non-adherence to medications continues to be a burden worldwide, with significant negative consequences. Community pharmacist interventions seem to be effective at improving medication adherence. However, more evidence is needed regarding their impact on disease-specific outcomes. The aim was to evaluate the impact of a community pharmacist-led adherence management intervention on adherence and clinical outcomes in patients with hypertension, asthma and chronic obstructive pulmonary disease (COPD).

METHODS

A 6-month cluster randomised controlled trial was conducted in Spanish community pharmacies. Patients suffering from hypertension, asthma and COPD were recruited. Patients in the intervention group received a medication adherence management intervention and the control group received usual care. The intervention was based on theoretical frameworks for changing patient behaviour. Medication adherence, disease-specific outcomes (Asthma Control Questionnaire (ACQ) scores, Clinical COPD Questionnaire (CCQ) scores and blood pressure levels) and disease control were evaluated. A multilevel regression model was used to analyse the data.

RESULTS

Ninety-eight pharmacies and 1186 patients were recruited, with 1038 patients completing the study. Patients receiving the intervention had an OR of 5.12 (95% CI 3.20 to 8.20, p<0.05) of being adherent after the 6 months. At the end of the study, patients in the intervention group had lower diastolic blood pressure levels (mean difference (MD) -2.88, 95% CI -5.33 to -0.43, p=0.02), lower CCQ scores (MD -0.50, 95% CI -0.82 to -0.18, p<0.05) and lower ACQ scores (MD -0.28, 95% CI -0.56 to 0.00, p<0.05) when compared with the control group.

CONCLUSIONS

A community pharmacist-led medication adherence intervention was effective at improving medication adherence and clinical outcomes in patients suffering from hypertension, asthma and COPD. Future research should explore the implementation of these interventions in routine practice.

TRIAL REGISTRATION NUMBER

ACTRN12618000410257.

Delta T, a Useful Indicator for Pharmacy Dispensing Data to Monitor Medication Adherence

INTRODUCTION

Calculating patients' medication availability from dispensing or refill data is a common method to estimate adherence. The most often used measures, such as the medication possession ratio (MPR), average medication supplies over an arbitrary period. Averaging masks the variability of refill behavior over time.

GOAL

To derive a new absolute adherence estimate from dispensing data.

METHOD

Dispensing histories of patients with 19 refills of direct oral anticoagulants (DOAC) between 1 January 2008 and 31 December 2017 were extracted from 39 community pharmacies in Switzerland. The difference between the calculated and effective refill day (ΔT) was determined for each refill event. We graphed ΔT and its dichotomized version (dΔT) against the MPR, calculated mean ΔT and mean dΔT per refill, and applied cluster analysis.

RESULTS

We characterized 2204 refill events from 116 DOAC patients. MPR was high (0.975 ± 0.129) and showed a positive correlation with mean ΔT. Refills occurred on average 17.8 ± 27.9 days "too early", with a mean of 75.8 ± 20.2 refills being "on time". Four refill behavior patterns were identified including constant gaps within or at the end of the observation period, which were critical.

CONCLUSION

We introduce a new absolute adherence estimate ΔT that characterizes every refill event and shows that the refill behavior of DOAC patients is dynamic.

Association between gout and cardiovascular outcomes in adults with no history of cardiovascular disease: large data linkage study in New Zealand

Objective

To examine the association of gout with cardiovascular outcomes using linked administrative health data in Aotearoa New Zealand.

Design

Data linkage study.

Setting

National registries of pharmaceutical dispensing, hospital admission, and deaths linked to the Auckland/Northland regional repository of laboratory results to create a regional health contact population as of 31 December 2011.

Participants

942 416 residents of the Auckland/Northland region, aged 20-79 years with no history of cardiovascular disease.

Main outcome measures

Time to first fatal or non-fatal cardiovascular event, identified from national datasets on hospital admissions and mortality, between 1 January 2012 and 31 December 2016. Cardiovascular disease was broadly defined as comprising ischaemic heart disease, ischaemic or haemorrhagic stroke, transient ischaemic attack, peripheral vascular disease, and heart failure.

Interventions

A history of gout identified from a discharge diagnosis of gout from a public hospital admission or previous dispensing of gout specific drug treatments. The cohort was then linked to national hospital admissions and deaths through to 31 December 2016 (ie, 5 years' follow-up). Multivariable Cox proportional hazard models were constructed to assess the associations between gout, other risk factors, and cardiovascular outcomes.

Results

Of 942 416 people included in the study, 31 907 (3.4%) had gout (6261 women and 25 646 men). After adjustment for multiple risk factors for cardiovascular disease, gout was associated with increased cardiovascular events (adjusted hazard ratio 1.34 (95% confidence interval 1.23 to 1.45) in women; 1.18 (1.12 to 1.24) in men). For men with gout, there was an increased risk of cardiovascular disease in those who were not dispensed regular allopurinol (1.15 (1.05 to 1.25)) and those with a serum urate above the treatment target of 0.36 mmol/L (1.16 (1.04 to 1.30)). Risk of cardiovascular events was lower for men with gout who were not dispensed colchicine compared with those who were (0.84 (0.77 to 0.92)). These findings were not observed in women.

Conclusion

These results indicate that gout is associated with an increased risk of cardiovascular events. In men with gout without history of cardiovascular disease, the cardiovascular risk was lower in those regularly dispensed allopurinol and those with serum urate levels at the recommended treatment target. By contrast, colchicine dispensing was associated with an increased risk of cardiovascular events in men with gout without a cardiovascular history. The potential causal mechanisms of these associations require further exploration, including casual inference modelling in future studies.

Does a pharmacist-led medication use review improve medication adherence in polymedicated aged patients? Methodological choices matter!

RATIONALE, AIMS AND OBJECTIVES

The rise in chronic diseases urges for an identification of interventions that improve adherence. However, no golden standard exists for evaluating adherence in polymedicated patients. The objectives were to investigate the impact of a pharmacist-led medication use review (MUR) service on adherence implementation rates for chronic medication, and to evaluate the appropriateness of two adherence calculation approaches in this regard.

METHOD

Before-after study (SIMENON study) including ambulatory, aged, polymedicated patients. Refill data were used to calculate the proportion of days covered (PDC) per medication before and after the MUR. Adherence was assessed for chronic, solid, oral medication using a prescription-based and interval-based approach, and the performance of both approaches was compared.

RESULTS

Adherence was evaluated for 1483 medications from 316 patients. The median baseline PDC per medication was 0.95 (prescription-based method) and 0.91 (interval-based approach). Pearson correlation between both approaches was 0.616 (P < .0001). The prescription-based approach found less medication below the adherence threshold of 0.80 (319 medications; 21.5% vs 481 medications; 32.4%). Using the prescription-based approach, the proportion of non-adherent patients at baseline was 61.7% (195/316 patients), of which 54.9% (107/195 patients) was only non-adherent for one medication. Median PDC scores increased significantly from 0.95 to 0.99 and 0.91 to 0.99 with the prescription-based and interval-based approach respectively (both P < .0001). Only considering the 319 medications with baseline PDC scores <0.8 using the prescription-based approach, the median PDC scores significantly increased from 0.67 to 0.84 (P < .0001), with a median score improvement of 18.3%.

CONCLUSIONS

Although baseline adherence was high in this population of polymedicated aged patients, both calculation methods showed the MUR significantly improved adherence. The prescription-based approach was considered the most appropriate method. Based on these findings and literature evidence, it is recommended to implement the MUR service in Belgium and target non-adherent patients for maximal effect.

Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases

Artificial intelligence (AI) tools are increasingly being used within healthcare for various purposes, including helping patients to adhere to drug regimens. The aim of this narrative review was to describe: (1) studies on AI tools that can be used to measure and increase medication adherence in patients with non-communicable diseases (NCDs); (2) the benefits of using AI for these purposes; (3) challenges of the use of AI in healthcare; and (4) priorities for future research. We discuss the current AI technologies, including mobile phone applications, reminder systems, tools for patient empowerment, instruments that can be used in integrated care, and machine learning. The use of AI may be key to understanding the complex interplay of factors that underly medication non-adherence in NCD patients. AI-assisted interventions aiming to improve communication between patients and physicians, monitor drug consumption, empower patients, and ultimately, increase adherence levels may lead to better clinical outcomes and increase the quality of life of NCD patients. However, the use of AI in healthcare is challenged by numerous factors; the characteristics of users can impact the effectiveness of an AI tool, which may lead to further inequalities in healthcare, and there may be concerns that it could depersonalize medicine. The success and widespread use of AI technologies will depend on data storage capacity, processing power, and other infrastructure capacities within healthcare systems. Research is needed to evaluate the effectiveness of AI solutions in different patient groups and establish the barriers to widespread adoption, especially in light of the COVID-19 pandemic, which has led to a rapid increase in the use and development of digital health technologies.

Factors Associated with Medication Non-Adherence among Patients with Multimorbidity and Polypharmacy Admitted to an Intermediate Care Center

Identifying determinants of medication non-adherence in patients with multimorbidity would provide a step forward in developing patient-centered strategies to optimize their care. Medication appropriateness has been proposed to play a major role in medication non-adherence, reinforcing the importance of interdisciplinary medication review. This study examines factors associated with medication non-adherence among older patients with multimorbidity and polypharmacy. A cross-sectional study of non-institutionalized patients aged ≥65 years with ≥2 chronic conditions and ≥5 long-term medications admitted to an intermediate care center was performed. Ninety-three patients were included (mean age 83.0 ± 6.1 years). The prevalence of non-adherence based on patients' multiple discretized proportion of days covered was 79.6% (n = 74). According to multivariable analyses, individuals with a suboptimal self-report adherence (by using the Spanish-version Adherence to Refills and Medications Scale) were more likely to be non-adherent to medications (OR = 8.99, 95% CI 2.80-28.84, p < 0.001). Having ≥3 potentially inappropriate prescribing (OR = 3.90, 95% CI 0.95-15.99, p = 0.059) was barely below the level of significance. These two factors seem to capture most of the non-adherence determinants identified in bivariate analyses, including medication burden, medication appropriateness and patients' experiences related to medication management. Thus, the relationship between patients' self-reported adherence and medication appropriateness provides a basis to implement targeted strategies to improve effective prescribing in patients with multimorbidity.

The use of medication adherence guidelines in medication taking behaviour research

Medication nonadherence continues to be a serious issue in a range of long-term medical conditions and has been studied extensively over the past few decades. However, despite the plethora of research studies on medication adherence, poor methodological rigour in many studies has contributed to limited generalisability of the positive findings, limited impact on patients' medication adherence, and inability to compare between studies. This paper focuses on current guidelines designed specifically for research on medication adherence. It discusses key elements to consider during study design, selection of adherence measurements, and reporting on medication adherence research, to ensure a higher quality of research in medication adherence. Overall, there appears to be variations in adherence terminology reported in the literature despite improvements in defining medication taking behaviour and the availability of taxonomies. In addition, limited guidance exists on how best to measure adherence. Recommendations are provided on appropriate adherence measures for the adherence behaviour being investigated, including careful consideration of adherence concepts, validity of adherence instruments, appropriate instrument selection, definition of nonadherence threshold, and how to report medication adherence. Improving adherence research requires greater clarity and standardisation of descriptions of nonadherence behaviour, increased methodological rigour in study designs, better selection of adherence measurements, and comprehensive reporting.

Incessant threat of COVID-19 variants: Highlighting need for a mix of FDA-approved artificial intelligence tools and community pharmacy services

Seamless integration of artificial intelligence (AI) technology, especially FDA-approved AI tools, in community pharmacies can build increasingly effective and easy care pathways, thereby minimizing burden on healthcare system, and ensuring compliance to preventive measure through limiting hospital visits. In this regard, the WHO needs to enlist and provide guidance on most promising AI tools that can be implemented in community pharmacy settings.

Non-Adherence Tree Analysis (NATA)-An adherence improvement framework: A COVID-19 case study

Poor medication adherence is a global phenomenon that has received a significant amount of research attention yet remains largely unsolved. Medication non-adherence can blur drug efficacy results in clinical trials, lead to substantial financial losses, increase the risk of relapse and hospitalisation, or lead to death. The most common methods of measuring adherence are post-treatment measures; that is, adherence is usually measured after the treatment has begun. What the authors are proposing in this multidisciplinary study is a new technique for predicting the factors that are likely to cause non-adherence before or during medication treatment, illustrated in the context of potential non-adherence to COVID-19 antiviral medication. Fault Tree Analysis (FTA), allows system analysts to determine how combinations of simple faults of a system can propagate to cause a total system failure. Monte Carlo simulation is a mathematical algorithm that depends heavily on repeated random sampling to predict the behaviour of a system. In this study, the authors propose a new technique called Non-Adherence Tree Analysis (NATA), based on the FTA and Monte Carlo simulation techniques, to improve adherence. Firstly, the non-adherence factors of a medication treatment lifecycle are translated into what is referred to as a Non-Adherence Tree (NAT). Secondly, the NAT is coded into a format that is translated into the GoldSim software for performing dynamic system modelling and analysis using Monte Carlo. Finally, the GoldSim model is simulated and analysed to predict the behaviour of the NAT. NATA is dynamic and able to learn from emerging datasets to improve the accuracy of future predictions. It produces a framework for improving adherence by analysing social and non-social adherence barriers. Novel terminologies and mathematical expressions have been developed and applied to real-world scenarios. The results of the application of NATA using data from six previous studies in relation to antiviral medication demonstrate a predictive model which suggests that the biggest factor that could contribute to non-adherence to a COVID-19 antiviral treatment is a therapy-related factor (the side effects of the medication). This is closely followed by a condition-related factor (asymptomatic nature of the disease) then patient-related factors (forgetfulness and other causes). From the results, it appears that side effects, asymptomatic factors and forgetfulness contribute 32.44%, 22.67% and 18.22% respectively to discontinuation of medication treatment of COVID-19 antiviral medication treatment. With this information, clinicians can implement relevant interventions and measures and allocate resources appropriately to minimise non-adherence.

Adherence to thalidomide in patients with multiple myeloma: A cross-sectional study in a Brazilian metropolis

PURPOSE

The treatment of multiple myeloma (MM) has advanced with the introduction of immunomodulators (IMiDS). Thalidomide is the IMiD available in Brazil with free access to MM patients. Adherence to treatment with IMiDs is essential for a successful therapy. The study proposed to describe adherence to thalidomide treatment in patients diagnosed with MM in onco-hematological outpatient clinics.

METHODS

This is a cross-sectional study with patients over 18 years of age diagnosed with MM undergoing thalidomide treatment. Adherence was measured by the Proportion of Days Covered (PDC), which is an indirect method of measuring adherence that uses database-related medication dispensing information. Patients with PDC ≥90 were classified as adherent. The association between adherence and independent variables was assessed in univariate and multivariate analyses using logistic regression.

RESULTS

A total of 65 patients with a median age of 62.6 years were identified. The median PDC was 93.7%. The frequency of adherence to thalidomide was 56.9%. Adherence to thalidomide showed a negative association with hospitalization in the last 12 months (OR = 0.202; 95% CI = 0.060-0.687) and with higher schooling (OR =0.161; 95% CI = 0.039-0.667) and a positive association with higher income (OR = 5.115; 95% CI = 1.363-19.190).

CONCLUSION

Most patients from onco-hematological outpatient clinics in a metropolitan region of southeastern Brazil showed high adherence to thalidomide, which was independently associated with higher income, hospitalization, and higher schooling. More studies are required to understand better the determinants of adherence to thalidomide in the country.

Impact of a Multicomponent Digital Therapeutic Mobile App on Medication Adherence in Patients with Chronic Conditions: Retrospective Analysis

BACKGROUND

Strategies to improve medication adherence are widespread in the literature; however, their impact is limited in real practice. Few patients persistently engage long-term to improve health outcomes, even when they are aware of the consequences of poor adherence. Despite the potential of mobile phone apps as a tool to manage medication adherence, there is still limited evidence of the impact of these innovative interventions. Real-world evidence can assist in minimizing this evidence gap.

OBJECTIVE

The objective of this study was to analyze the impact over time of a previously implemented digital therapeutic mobile app on medication adherence rates in adults with any chronic condition.

METHODS

A retrospective observational study was performed to assess the adherence rates of patients with any chronic condition using Perx Health, a digital therapeutic that uses multiple components within a mobile health app to improve medication adherence. These components include gamification, dosage reminders, incentives, educational components, and social community components. Adherence was measured through mobile direct observation of therapy (MDOT) over 3-month and 6-month time periods. Implementation adherence, defined as the percentage of doses in which the correct dose of a medication was taken, was assessed across the study periods, in addition to timing adherence or percentage of doses taken at the appropriate time (±1 hour). The Friedman test was used to compare differences in adherence rates over time.

RESULTS

We analyzed 243 and 130 patients who used the app for 3 months and 6 months, respectively. The average age of the 243 patients was 43.8 years (SD 15.5), and 156 (64.2%) were female. The most common medications prescribed were varenicline, rosuvastatin, and cholecalciferol. The median implementation adherence was 96.6% (IQR 82.1%-100%) over 3 months and 96.8% (IQR 87.1%-100%) over 6 months. Nonsignificant differences in adherence rates over time were observed in the 6-month analysis (Fr(2)=4.314, P=.505) and 3-month analysis (Fr(2)=0.635, P=.728). Similarly, the timing adherence analysis revealed stable trends with no significant changes over time.

CONCLUSIONS

Retrospective analysis of users of a medication adherence management mobile app revealed a positive trend in maintaining optimal medication adherence over time. Mobile technology utilizing gamification, dosage reminders, incentives, education, and social community interventions appears to be a promising strategy to manage medication adherence in real practice.

Impact of Social Determinants of Health and Demographics on Refill Requests by Medicare Patients Using a Conversational Artificial Intelligence Text Messaging Solution: Cross-Sectional Study

Background

Nonadherence among patients with chronic disease continues to be a significant concern, and the use of text message refill reminders has been effective in improving adherence. However, questions remain about how differences in patient characteristics and demographics might influence the likelihood of refill using this channel.

Objective

The aim of this study was to evaluate the efficacy of an SMS-based refill reminder solution using conversational artificial intelligence (AI; an automated system that mimics human conversations) with a large Medicare patient population and to explore the association and impact of patient demographics (age, gender, race/ethnicity, language) and social determinants of health on successful engagement with the solution to improve refill adherence.

Methods

The study targeted 99,217 patients with chronic disease, median age of 71 years, for medication refill using the mPulse Mobile interactive SMS text messaging solution from December 2016 to February 2019. All patients were partially adherent or nonadherent Medicare Part D members of Kaiser Permanente, Southern California, a large integrated health plan. Patients received SMS reminders in English or Spanish and used simple numeric or text responses to validate their identity, view their medication, and complete a refill request. The refill requests were processed by Kaiser Permanente pharmacists and support staff, and refills were picked up at the pharmacy or mailed to patients. Descriptive statistics and predictive analytics were used to examine the patient population and their refill behavior. Qualitative text analysis was used to evaluate quality of conversational AI.

Results

Over the course of the study, 273,356 refill reminders requests were sent to 99,217 patients, resulting in 47,552 refill requests (17.40%). This was consistent with earlier pilot study findings. Of those who requested a refill, 54.81% (26,062/47,552) did so within 2 hours of the reminder. There was a strong inverse relationship (r10=−0.93) between social determinants of health and refill requests. Spanish speakers (5149/48,156, 10.69%) had significantly lower refill request rates compared with English speakers (42,389/225,060, 18.83%; X²₁ [n=273,216]=1829.2; P<.001). There were also significantly different rates of refill requests by age band (X²₆ [n=268,793]=1460.3; P<.001), with younger patients requesting refills at a higher rate. Finally, the vast majority (284,598/307,484, 92.23%) of patient responses were handled using conversational AI.

Conclusions

Multiple factors impacted refill request rates, including a strong association between social determinants of health and refill rates. The findings suggest that higher refill requests are linked to language, race/ethnicity, age, and social determinants of health, and that English speakers, whites, those younger than 75 years, and those with lower social determinants of health barriers are significantly more likely to request a refill via SMS. A neural network–based predictive model with an accuracy level of 78% was used to identify patients who might benefit from additional outreach to narrow identified gaps based on demographic and socioeconomic factors.

Pharmacist-led medication non-adherence intervention: reducing the economic burden placed on the Australian health care system

Background: Scarcity of prospective medication non-adherence cost measurements for the Australian population with no directly measured estimates makes determining the burden medication non-adherence places on the Australian health care system difficult. This study aims to indirectly estimate the national cost of medication non-adherence in Australia comparing the cost prior to and following a community pharmacy-led intervention. Methods: Retrospective observational study. A de-identified database of dispensing data from 20,335 patients (n=11,257 on rosuvastatin, n=6,797 on irbesartan and n=2,281 on desvenlafaxine) was analyzed and average adherence rate determined through calculation of PDC. Included patients received a pharmacist-led medication adherence intervention and had twelve months dispensing records; six months before and six months after the intervention. The national cost estimate of medication non-adherence in hypertension, dyslipidemia and depression pre- and post-intervention was determined through utilization of disease prevalence and comorbidity, non-adherence rates and per patient disease-specific adherence-related costs. Results: The total national cost of medication non-adherence across three prevalent conditions, hypertension, dyslipidemia and depression was $10.4 billion equating to $517 per adult. Following enrollment in the pharmacist-led intervention medication non-adherence costs per adult decreased $95 saving the Australian health care system and patients $1.9 billion annually. Conclusion: In the absence of a directly measured national cost of medication non-adherence, this estimate demonstrates that pharmacists are ideally placed to improve patient adherence and reduce financial burden placed on the health care system due to non-adherence. Funding of medication adherence programs should be considered by policy and decision makers to ease the current burden and improve patient health outcomes moving forward.