TEOS: A framework for constructing operational definitions of medication adherence based on Timelines-Events-Objectives-Sources

Evaluation of adherence to antipsychotics: A real-world data study using four different dosing assumptions

AIMS

This study aimed to assess the frequency of dosing inconsistencies in prescription data and the effect of four dosing assumption strategies on adherence estimates for antipsychotic treatment.

METHODS

A retrospective cohort, which linked prescription and dispensing data of adult patients with ≥1 antipsychotic prescription between 2015-2016 and followed up until 2019, in Catalonia (Spain). Four strategies were proposed for selecting the recommended dosing in overlapping prescription periods for the same patient and antipsychotic drug: (i) the minimum dosing prescribed; (ii) the dose corresponding to the latest prescription issued; (iii) the highest dosing prescribed; and (iv) all doses included in the overlapped period. For each strategy, one treatment episode per patient was selected, and the Continuous Medication Availability measure was used to assess adherence. Descriptive statistics were used to describe results by strategy.

RESULTS

Of the 277 324 prescriptions included, 76% overlapped with other prescriptions (40% with different recommended dosing instructions). The number and characteristics of patients and treatment episodes (18 292, 18 303, 18 339 and 18 536, respectively per strategy) were similar across strategies. Mean adherence was similar between strategies, ranging from 57 to 60%. However, the proportion of patients with adherence ≥90% was lower when selecting all doses (28%) compared with the other strategies (35%).

CONCLUSION

Despite the high prevalence of overlapping prescriptions, the strategies proposed did not show a major effect on the adherence estimates for antipsychotic treatment. Taking into consideration the particularities of antipsychotic prescription practices, selecting the highest dose in the overlapped period seemed to provide a more accurate adherence estimate.

Using a Semiautomated Procedure (CleanADHdata.R Script) to Clean Electronic Adherence Monitoring Data: Tutorial

BACKGROUND

Patient adherence to medications can be assessed using interactive digital health technologies such as electronic monitors (EMs). Changes in treatment regimens and deviations from EM use over time must be characterized to establish the actual level of medication adherence.

OBJECTIVE

We developed the computer script CleanADHdata.R to clean raw EM adherence data, and this tutorial is a guide for users.

METHODS

In addition to raw EM data, we collected adherence start and stop monitoring dates and identified the prescribed regimens, the expected number of EM openings per day based on the prescribed regimen, EM use deviations, and patients' demographic data. The script formats the data longitudinally and calculates each day's medication implementation.

RESULTS

We provided a simulated data set for 10 patients, for which 15 EMs were used over a median period of 187 (IQR 135-342) days. The median patient implementation before and after EM raw data cleaning was 83.3% (IQR 71.5%-93.9%) and 97.3% (IQR 95.8%-97.6%), respectively (Δ+14%). This difference is substantial enough to consider EM data cleaning to be capable of avoiding data misinterpretation and providing a cleaned data set for the adherence analysis in terms of implementation and persistence.

CONCLUSIONS

The CleanADHdata.R script is a semiautomated procedure that increases standardization and reproducibility. This script has broader applicability within the realm of digital health, as it can be used to clean adherence data collected with diverse digital technologies.

Nonadherence to antiseizure medications: what have we learned and what can be done next?

INTRODUCTION

Nonadherence to antiseizure medications (ASMs) is associated with increased mortality, morbidity, health care utilization, and costs.

AREAS COVERED

This article reviewed 18 randomized controlled trials published between Jan 2010 and Feb 2024 on Medication Adherence Enhancing Intervention (MAEI) for people with epilepsy. The adequacy of reporting intervention development process was assessed using the GUIDance for the rEporting of intervention Development (GUIDED). The adequacy of the intervention description was assessed using the Template for Intervention Description and Replication (TIDieR) checklist. The interventions were categorized as educational (n = 7), behavioral (n = 5), or mixed (n = 6). The impact of MAEIs on adherence is mixed with majority of studies either reporting no difference between intervention and control groups (n = 6) or improvement in the intervention group (n = 7). The shortcomings in the reporting of MAEIs development, MAEIs description, and MAEIs impact measurement were discussed.

EXPERT OPINION

Future research needs to accomplish the following tasks: 1) develop and test valid epilepsy-specific self-report measures for assessing adherence; 2) optimize intervention design; and 3) increase transparency in reporting all stages of research.

Medication adherence to inflammatory bowel disease medications in Aotearoa New Zealand and correlation with health outcomes: A nationwide database analysis

AIMS

Inflammatory bowel disease (IBD) management entails long-term medication therapy. Worse disease outcomes and reduced quality of life might arise from poor medication adherence (MA). This study is the first to investigate patients with IBD's adherence across Aotearoa New Zealand and its relationship with disease outcomes.

METHODS

Dispensing claims data (Pharmaceutical Collection) were used to calculate (3- and 5-year) adherence, using daily polypharmacy possession ratio. Using hospitalization data (National Minimum Dataset), the relationship between adherence and the numbers of hospitalizations and corticosteroid dispensings was investigated.

RESULTS

In total, 4654 patients (53% female; 55% Crohn's disease [CD], 45% ulcerative colitis [UC]; median age-at-first-dispensing, 43 years) and 3148 patients (54% female; 55% CD, 44% UC; median age-at-first-dispensing, 44 years) were in the 3- and 5-year cohorts, respectively. The 3- and 5-year cohorts had mean 4.6 and 4.2 IBD-related hospitalizations and 6.9 and 9.2 corticosteroid dispensings, respectively. Average adherence estimates were 77.4% (95% confidence interval: 76.9-78.0%) and 74.9% (95% confidence interval: 74.1-75.6%; 3 and 5 years), while 54% and 51% of patients, respectively, had good adherence (MA ≥ 80%). There was no correlation between adherence and the numbers of hospitalizations (Pearson's R = -.0007; P = .65 and R = -.04; P = .02 [3 and 5 years]) and corticosteroid dispensings (R = .08; P = <.0001 and R = .08; P = <.0001, respectively).

CONCLUSION

MA of Aotearoa New Zealand patients with IBD is moderately high but just over half of patients meet the adherent threshold. There was no correlation between adherence and hospitalizations or corticosteroid dispensings; hence, research into longitudinal adherence patterns and associated factors is needed.

Medication adherence and costs of medical care among patients with Parkinson's disease: an observational study using electronic medical records

BACKGROUND

Adherence to antiparkinsonian drugs (APDs) is critical for patients with Parkinson's disease (PD), for which medication is the main therapeutic strategy. Previous studies have focused on specific disorders in a single system when assessing clinical factors affecting adherence to PD treatment, and no international comparative data are available on the medical costs for Chinese patients with PD. The present study aimed to evaluate medication adherence and its associated factors among Chinese patients with PD using a systematic approach and to explore the impact of adequate medication adherence on direct medical costs.

METHODS

A retrospective analysis was conducted using the electronic medical records of patients with PD from a medical center in China. Patients with a minimum of two APD prescriptions from January 1, 2016 to August 15, 2018 were included. Medication possession ratio (MPR) and proportion of days covered were used to measure APD adherence. Multiple linear regression analysis was used to identify factors affecting APD adherence. Gamma regression analysis was used to explore the impact of APD adherence on direct medical costs.

RESULTS

In total, 1,712 patients were included in the study, and the mean MPR was 0.68 (± 0.25). Increased number of APDs and all medications, and higher daily levodopa-equivalent doses resulted in higher MPR (mean difference [MD] = 0.04 [0.03-0.05]; MD = 0.02 [0.01-0.03]; MD = 0.03 [0.01-0.04], respectively); combined digestive system diseases, epilepsy, or older age resulted in lower MPR (MD = -0.06 [-0.09 to -0.03]; MD = -0.07 [-0.14 to -0.01]; MD = -0.02 [-0.03 to -0.01], respectively). Higher APD adherence resulted in higher direct medical costs, including APD and other outpatient costs. For a 0.3 increase in MPR, the two costs increased by $34.42 ($25.43-$43.41) and $14.63 ($4.86-$24.39) per year, respectively.

CONCLUSIONS

APD adherence rate among Chinese patients with PD was moderate and related primarily to age, comorbidities, and healthcare costs. The factors should be considered when prescribing APDs.

Patient-Led Urate Self-Monitoring to Improve Clinical Outcomes in People With Gout: A Feasibility Study

OBJECTIVE

Self-monitored point-of-care urate-measuring devices are an underexplored strategy to improve adherence to urate-lowering therapy and clinical outcomes in gout. This study observed patient-led urate self-monitoring practice and assessed its influence on allopurinol adherence, urate control, and health-related quality of life.

METHODS

People with gout (n = 31) and prescribed allopurinol self-monitored their urate concentrations (HumaSens2.0plus) at baseline and thereafter monthly for 12 months (3 months per quarter). Adherence to allopurinol was measured using medication event monitoring technology (Medication Event Monitoring System cap). Time spent below the target urate concentration (<0.36 mmol/L) was determined. Health-related quality of life was measured using a survey (EuroQoL EQ-5D-5L). Gout flares were recorded. Two-tailed Spearman correlation and the Wilcoxon matched-pairs signed-rank test (P < 0.05) were used for statistical comparisons.

RESULTS

Most participants were male (94%) and had urate concentrations below the target (74%) at baseline. Overall, seven participants demonstrated repeated periods of "missed doses" (two or fewer allopurinol doses missed consecutively) and "drug holidays" (three or more missed doses). Most participants (94%) persisted with allopurinol. Time spent within the target urate concentration increased 1.3-fold (from 79% to 100%; P = 0.346), and the incidence of gout flares decreased 1.6-fold (from 8 to 5; P = 0.25) in the final quarter compared to that in the first quarter of the study. Health-related quality of life was reduced for participants reporting at least one gout flare (median utility values 0.9309 vs 0.9563, P = 0.04).

CONCLUSION

Patient-led urate self-monitoring may support the maintenance of allopurinol adherence and improve urate control, thus reducing the incidence of gout flares. Further research on patient-led urate self-monitoring in a randomized controlled study is warranted.

Immunosuppressant adherence in adult outpatient hematopoietic cell transplant recipients

INTRODUCTION

Medication nonadherence continues to be challenging for allogeneic hematopoietic cell transplant (HCT) recipients. The risk and severity of chronic graft-versus-host disease (GVHD) are associated with low immunosuppressant concentrations (which can be improved with model-informed precision dosing (MIPD)) and with immunosuppressant nonadherence (which can be improved with acceptable interventions).

METHODS

With the goals of improving adherence and achieving therapeutic concentrations of immunosuppressants to eliminate GVHD, we characterized the feasibility of using the Medication Event Monitoring (MEMS®) Cap in adult HCT recipients.

RESULTS

Of the 27 participants offered the MEMS® Cap at the time of hospital discharge, 7 (25.9%) used it, which is below our a priori threshold of 70%. These data suggest the MEMS® Cap is not feasible for HCT recipients. The MEMS® Cap data were available for a median of 35 days per participant per medication (range: 7-109 days). The average daily adherence per participant ranged from 0 to 100%; four participants had an average daily adherence of over 80%.

CONCLUSIONS

MIPD may be supported by MEMS® technology to provide the precise time of immunosuppressant self-administration. The MEMS® Cap was used by only a small percentage (25.9%) of HCT recipients in this pilot study. In accordance with larger studies using less accurate tools to evaluate adherence, immunosuppressant adherence varied from 0% to 100%. Future studies should establish the feasibility and clinical benefit of combining MIPD with newer technology, specifically the MEMS® Button, which can inform the oncology pharmacist of the time of immunosuppressant self-administration.

A framework for understanding sources of bias in medication adherence research

The sources of bias in medication adherence research have not been comprehensively explored. We aimed to identify biases expected to affect adherence research and to develop a framework for mapping these onto the phases of adherence (initiation, implementation and discontinuation). A literature search was conducted, key papers were reviewed and a Catalogue of Bias was consulted. The specific biases related to adherence measurement and metrics were mapped onto the phases of adherence using a tabular matrix. Twenty-three biases were identified, of which 11 were specifically relevant to adherence measures and metrics. The mapping framework showed differences in the numbers and types of biases associated with each measure and metric while highlighting those common to many adherence study designs (e.g., unacceptability bias and apprehension bias). The framework will inform the design of adherence studies and the development of risk of bias tools for adherence research.

Assessing disease activity of rheumatoid arthritis patients and drug-utilization patterns of biologic disease-modifying antirheumatic drugs in the Tuscany region, Italy

Introduction: The disease activity associated with the drug-utilization patterns of biologic Disease Modifying Anti-Rheumatic Drugs (DMARDs) is poorly investigated in real-world studies on rheumatoid arthritis (RA) patients. To investigate the relationship between biologic DMARD initiation/discontinuations in RA patients identified in the healthcare administrative databases of Tuscany and the Disease Activity Score 28 (DAS28) reported in the medical charts. Methods: This retrospective population-based study included RA's first-ever biologic DMARD users of the Pisa University Hospital from 2014 to 2016. Patients were followed up until 31 December 2019. We evaluated the DAS28 recorded before (T0) and after (T1) the biologic DMARD initiation and before (TD0) and after (TD1) discontinuations. Patients were classified as "off-target" (DAS28 > 3.2) or "in-target" (DAS28 ≤ 3.2). We described the disease activity trends at initiation and discontinuation. Results: Ninety-five users were included (73 women, mean age 59.6). Among 70 patients (74%) with at least three DAS28 measures, 28 (40.0%) were off-target at T0 and 38 (54.3%) in-target at T1. Thirty-three (47%) patients had at least one discontinuation, among those with at least three DAS28 assessments. In the disease activity trend, disease stability or improvement was observed in 28 out of 37 (75.7%) patients at initiation and in 24 out of 37 (64.9%) at discontinuation. Discussion: Biologic DMARD discontinuations identified in the healthcare administrative databasese of Tuscany are frequently observed in situations of controlled RA disease. Further studies are warranted to confirm that these events can be used in studies using healthcare administrative databases as proxies of treatment effectiveness.

Spanish translation of the ABC taxonomy for medication adherence

BACKGROUND

The Ascertaining Barriers to Compliance (ABC) taxonomy was developed aiming at systematizing definitions and operationalizations of medication adherence. Its translation is crucial to improve the generalizability, application and comparison of study findings.

OBJECTIVE

To provide a consensus translation of the ABC taxonomy from English to Spanish.

METHODS

A two-phased approach was used, according to the Preferred Methods for the Translation of the ABC Taxonomy for Medication Adherence. Two literature reviews were conducted: to identify Spanish synonyms and definitions of the ABC taxonomy, and to identify a panel of Spanish-speaking experts in medication adherence. A Delphi survey was designed based on the synonyms and definitions found. The experts previously identified were invited to participate in the Delphi. A consensus of ≥85% was established for the first round. A moderate consensus (50-75%), a consensus (75-95%) or a strong consensus (>95%) were considered to be necessary in the second round.

RESULTS

Forty potential synonyms of the ABC taxonomy terms were identified from a total of 270 papers. The response rate during the first Delphi round was 32% (63/197) and in the second round 86% (54/63). A strong consensus was reached for the term "inicio del tratamiento" (96%) and consensus for the term "implementación" (83%). A moderate consensus was obtained for "adherencia a la medicación" (70%), "interrupción del tratamiento" (52%), "manejo de la adherencia" (54%) and "disciplinas relacionadas con la adherencia" (74%). No consensus was reached for the term persistence. Five out of the seven definitions reached a consensus in the first round, and two definitions a moderate consensus after the second round.

CONCLUSION

The adoption of the Spanish taxonomy will increase transparency, comparability and transferability of results in the field of medication adherence. This may facilitate benchmarking of adherence strategies between Spanish-speaking researchers and practitioners, and other language speakers.

Prevalence and Patient-Level Correlates of Intentional Non-Adherence to Immunosuppressive Medication After Heart-Transplantation-Findings From the International BRIGHT Study

After heart transplantation (HTx), non-adherence to immunosuppressants (IS) is associated with poor outcomes; however, intentional non-adherence (INA) is poorly understood regarding its international variability in prevalence, contributing factors and impact on outcomes. We investigated (1) the prevalence and international variability of INA, (2) patient-level correlates of INA, and (3) relation of INA with clinical outcomes. Secondary analysis of data from the BRIGHT study-an international multi-center, cross-sectional survey examining multi-level factors of adherence in 1,397 adult HTx recipients. INA during the implementation phase, i.e., drug holiday and dose alteration, was measured using the Basel Assessment of Adherence to Immunosuppressive Medications Scale© (BAASIS©). Descriptive and inferential analysis was performed with data retrieved through patient interview, patient self-report and in clinical records. INA prevalence was 3.3% (n = 46/1,397)-drug holidays: 1.7% (n = 24); dose alteration: 1.4% (n = 20); both: 0.1% (n = 2). University-level education (OR = 2.46, CI = 1.04-5.83), insurance not covering IS costs (OR = 2.21, CI = 1.01-4.87) and barriers (OR = 4.90, CI = 2.73-8.80) were significantly associated with INA; however, clinical outcomes were not. Compared to other single-center studies, this sample's INA prevalence was low. More than accessibility or financial concerns, our analyses identified patient-level barriers as INA drivers. Addressing patients' IS-related barriers, should decrease INA.

Medication Adherence and Healthcare Costs in Chronically Ill Patients Using German Claims Data

BACKGROUND AND OBJECTIVE

Despite the importance of medication adherence for chronically ill patients and the vast literature on its relationship to costs, this field suffers from methodological limitations. These are caused, amongst others, by the lack of generalizability of data sources, varying definitions of adherence, costs, and model specification. We aim to address this with different modeling approaches and to contribute evidence on the research question.

METHODS

We extracted large cohorts of nine chronic diseases (n = 6747-402,898) from German claims data of stationary health insurances between 2012 and 2015 (t0-t3). Defined as the proportion of days covered by medication, we examined the relationship of adherence using several multiple regression models at baseline year t0 with annual total healthcare costs and four sub-categories. Models with concurrent, and differently time-lagged measurements of adherence and costs were compared. Exploratively, we applied non-linear models.

RESULTS

Overall, we found a positive association between the proportion of days covered by medication and total costs, a weak association with outpatient costs, positive with pharmacy costs, and frequently negative with inpatient costs. There were major differences by disease and its severity but little between years, provided adherence and costs were not measured concurrently. The fit of linear models was mainly not inferior to that of non-linear models.

CONCLUSIONS

The estimated effect on total costs differed from most other studies, which highlights concerns about generalizability, although effect estimates in sub-categories were as expected. Comparison of time lags indicates the importance of avoiding concurrent measurement. A non-linear relationship should be considered. These methodological approaches are valuable in future research on adherence and its consequences.

Primary nonadherence to drugs prescribed by general practitioners: A Dutch database study

AIM

Primary nonadherence (PNA) is defined as not filling the first prescription for a drug treatment. PNA can lead not only to poor patient outcomes but also to exposure misclassification in written prescription databases. This study aims to estimate PNA in primary care in the Netherlands and to investigate associated factors.

METHODS

Patients from the Nivel Primary Care Database (Nivel-PCD) who received a new prescription (>1 year not prescribed) from a general practitioner in 2012 were linked to pharmacy dispensing information of consenting pharmacies based on sex, year of birth, four-digit postal code and at least 50% matching Anatomical Therapeutic Classification codes. PNA was defined as not having a prescription dispensed within 30 days from the prescribing date. PNA was assessed overall and per drug class. The associations between PNA and several patient- and prescription-related characteristics were assessed using mixed-effects logistic regression models.

RESULTS

After matching 86 361 of 396 251 subjects (21.8%) in the Nivel-PCD records to the pharmacy records, this study included 65 877 subjects who received 181 939 new drug prescriptions. Overall, PNA was 11.5%. PNA was lowest for thyroid hormones (5.5%) and highest for proton pump inhibitors (12.8%). Several factors were associated with PNA, such as having comorbidities (odds ratio [OR] 1.46, 95% confidence interval [CI] 1.37-1.56 for >3 active diagnoses, compared to no active diagnoses) or reimbursement status (OR 2.78, 95% CI 2.65-2.92 for not reimbursed drugs compared to fully reimbursed drugs).

CONCLUSIONS

A total of 11.5% of newly prescribed drugs were not dispensed. This can lead to overestimation of the actual drug exposure status when using written prescription databases.

Patterns of statin adherence in primary cardiovascular disease prevention during the pandemic

Background: Study of medication adherence patterns can help identify patients who would benefit from effective interventions to improve adherence. Objectives: To identify and compare groups of statin users based on their adherence patterns before and during the COVID-19 pandemic, to characterize the profile of users in each group, and to analyze predictors of distinct adherence patterns. Methods: Participants of the CARhES (CArdiovascular Risk factors for HEalth Services research) cohort, comprising individuals aged >16 years, residing in Aragón (Spain), with hypertension, diabetes mellitus and/or dyslipidemia, took part in this observational longitudinal study. Individuals who began statin therapy during January-June 2019 were selected and followed up until June 2021. Those with a cardiovascular event before or during follow-up were excluded. Data were obtained from healthcare system data sources. Statin treatment adherence during the implementation phase was estimated bimonthly using the Continuous Medication Availability (CMA9) function in the AdhereR package. Group-based trajectory models were developed to group statin users according to their adherence pattern during July 2019-June 2021. Group characteristics were compared and predictors of each adherence pattern were analyzed using multinomial logistic regression. Results: Of 15,332 new statin users, 30.8% had a mean CMA9 ≥80% for the entire study period. Four distinct adherence patterns were identified: high adherence (37.2% of the study population); poor adherence (35.6%); occasional use (14.9%); and gradual decline (12.3%). The latter two groups included users who showed a change in adherence (increase or decrease) during the pandemic emergence. Users with suboptimal adherence were likely to be younger, not pensioners, not institutionalized, with low morbidity burden and a low number of comorbidities. Female sex and switching between statins of different intensity increased the likelihood of belonging to the occasional use group, in which improved adherence coincided with the pandemic. Conclusion: We identified four distinct adherence patterns in a population of new statin users; two of them modified their adherence during the pandemic. Characterization of these groups could enable more effective distribution of resources in future similar crisis and the routine implementation of patient-centered interventions to improve medication adherence.

Towards better reporting of the Proportion of Days Covered method in cardiovascular medication adherence: A scoping review and new tool TEN-SPIDERS

Although medication adherence is commonly measured in electronic datasets using the proportion of days covered (PDC), no standardized approach is used to calculate and report this measure. We conducted a scoping review to understand the approaches taken to calculate and report the PDC for cardiovascular medicines to develop improved guidance for researchers using this measure. After prespecifying methods in a registered protocol, we searched Ovid Medline, Embase, Scopus, CINAHL Plus and grey literature (1 July 2012 to 14 December 2020) for articles containing the terms “proportion of days covered” and “cardiovascular medicine”, or synonyms and subject headings. Of the 523 articles identified, 316 were reviewed in full and 76 were included (93% observational studies; 47% from the USA; 2 grey literature articles). In 45 articles (59%), the PDC was measured from the first dispensing/claim date. Good adherence was defined as 80% PDC in 61 articles, 56% of which contained a rationale for selecting this threshold. The following parameters, important for deriving the PDC, were often not reported/unclear: switching (53%), early refills (45%), in‐hospital supplies (45%), presupply (28%) and survival (7%). Of the 46 articles where dosing information was unavailable, 59% reported how doses were imputed. To improve the transparent and systematic reporting of the PDC, we propose the TEN‐SPIDERS tool, covering the following PDC parameters: Threshold, Eligibility criteria, Numerator and denominator, Survival, Presupply, In‐hospital supplies, Dosing, Early Refills, and Switching. Use of this tool will standardize reporting of the PDC to facilitate reliable comparisons of medication adherence estimates between studies.

Methodological considerations on estimating medication adherence from self-report, electronic monitoring, and electronic healthcare databases using the TEOS framework

AIM

Measuring adherence to medication is complex due to the diversity of contexts in which medications are prescribed, dispensed, and used. The Timelines-Events-Objectives-Sources (TEOS) framework outlined a process to operationalize adherence. We aimed to develop practical recommendations for quantification of medication adherence using self-report (SR), electronic monitoring (EM), and electronic healthcare databases (EHD) consistent with the TEOS framework for adherence operationalization.

METHODS

An adherence methodology working group of the International Society for Medication Adherence (ESPACOMP) analysed implications of the process of medication adherence for all data sources and discussed considerations specific to SR, ED, and EHD regarding the information available on the prescribing, dispensing, recommended and actual use timelines, the four events relevant for distinguishing the adherence phases, the study objectives commonly addressed with each type of data, and the potential sources of measurement error and quality criteria applicable.

RESULTS

Four key implications for medication adherence measurement are common to all data sources: adherence is a comparison between two series of events (recommended and actual use); it refers to one or more specific medication(s); it applies to regular repeated events coinciding with known recommended dosing; and it requires separate measurement of the three adherence phases for a complete picture of patients' adherence. We propose recommendations deriving from these statements, and aspects to be considered in study design when measuring adherence with SR, EM and EHD using the TEOS framework.

CONCLUSION

The quality of medication adherence estimates is the result of several design choices that may optimize the data available.

PrEP Use, Sexual Behaviour, and PrEP Adherence Among Men who have Sex with Men Living in Wales Prior to and During the COVID-19 Pandemic

We examined PrEP use, condomless anal sex (CAS), and PrEP adherence among men who have sex with men (MSM) attending sexual health clinics in Wales, UK. In addition, we explored the association between the introduction of measures to control transmission of SARS-CoV-2 on these outcomes. We conducted an ecological momentary assessment study of individuals in receipt of PrEP in Wales. Participants used an electronic medication cap to record PrEP use and completed weekly sexual behaviour surveys. We defined adherence to daily PrEP as the percentage of CAS episodes covered by daily PrEP (preceded by ≥ 3 days of PrEP and followed by ≥ 2 days). Sixty participants were recruited between September 2019 and January 2020. PrEP use data prior to the introduction of control measures were available over 5785 person-days (88%) and following their introduction 7537 person-days (80%). Data on CAS episodes were available for 5559 (85%) and 7354 (78%) person-days prior to and following control measures respectively. Prior to the introduction of control measures, PrEP was taken on 3791/5785 (66%) days, there were CAS episodes on 506/5559 (9%) days, and 207/406 (51%) of CAS episodes were covered by an adequate amount of daily PrEP. The introduction of pandemic-related control measures was associated with a reduction in PrEP use (OR 0.44, 95%CI 0.20–0.95), CAS (OR 0.35, 95%CI 0.17–0.69), and PrEP adherence (RR = 0.55, 95%CI 0.34–0.89) and this may have implications for the health and wellbeing of PrEP users and, in addition to disruption across sexual health services, may contribute to wider threats across the HIV prevention cascade.

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.

Trajectories of Adherence to Biologic Disease-Modifying Anti-Rheumatic Drugs in Tuscan Administrative Databases: The Pathfinder Study

Scanty information on clustering longitudinal real-world data is available in the medical literature about the adherence implementation phase in rheumatoid arthritis (RA). To identify and characterize trajectories by analyzing the implementation phase of adherence to biologic Disease-Modifying Anti-Rheumatic Drugs (DMARDs), we conducted a retrospective cohort drug-utilization study using Tuscan administrative databases. RA patients were identified by a validated algorithm, including the first biologic DMARD supply from 2010 to 2015, RA specialist visit in the year before or after the first supply date and RA diagnosis in the five years before or in the year after the first supply date. We observed users for three years or until death, neoplasia, or pregnancy. We evaluated adherence quarterly through the Medication Possession Ratio. Firstly, we identified adherence trajectories and described the baseline characteristics; then, we focused on the trajectory most populated to distinguish the related sub-trajectories. We identified 952 first ever-biologic DMARD users in RA (712 females, mean age 52.7 years old, standard deviation 18.8). The biologic DMARD mostly supplied was etanercept (387 users) followed by adalimumab (233). Among 935 users with at least 3 adherence values, we identified 49 fully-adherent users, 829 continuous users, and 57 early-discontinuing users. Significant differences were observed among the index drugs. After focusing on the continuous users, three sub-trajectories were identified: continuous-steady users (556), continuous-alternate users (207), and continuous-declining users (66). No relevant differences emerged at the baseline. The majority of first ever-biologic DMARD users showed a continuous adherence behavior in RA. The role of adherence potential predictors and the association with effectiveness and safety outcomes should be explored by further studies.

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.