Development and Validation of a Questionnaire to Measure Medication Adherence to Direct-Acting Agents in Patients with Hepatitis C

Patient-reported outcome measures to detect intentional, mixed, or unintentional non-adherence to medication: a systematic review

OBJECTIVE

To categorise patient-reported outcome measures (PROMs) into their propensity to detect intentional and/or unintentional non-adherence to medication, and synthesise their psychometric properties.

DESIGN

Systematic review and regression analysis.

ELIGIBILITY

Medication adherence levels studied at primary, secondary and tertiary care settings. Self-reported measures with scoring methods were included. Studies without proxy measures were excluded.

DATA SOURCES

Using detailed searches with key concepts including questionnaires, reliability and validity, and restricted to English, MEDLINE, EMBASE, CINAHL, International Pharmaceutical Abstracts, and Cochrane Library were searched until 01 March 2022. Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA-2020) checklist was used.

DATA ANALYSIS

Risk of bias was assessed via COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN-2018) guidelines. Narrative synthesis aided by graphical figures and statistical analyses.

OUTCOME MEASURES

Process domains [behaviour (e.g., self-efficacy), barrier (e.g., impaired dexterity) or belief (e.g., perception)], and overall outcome domains of either intentional (I), unintentional (UI), or mixed non-adherence.

RESULTS

Paper summarises evidence from 59 studies of PROMs, validated among patients aged 18-88 years in America, the United Kingdom, Europe, Middle East, and Australasia. PROMs detected outcome domains: intentional non-adherence, n=44 (I=491 criterion items), mixed intentionality, n=13 (I=79/UI=50), and unintentional, n=2 (UI=5). Process domains detected include belief (383 criterion items), barrier (192) and behaviour (165). Criterion validity assessment used proxy measures (biomarkers, e-monitors), and scoring was ordinal, dichotomised, or used Visual Analogue Scale. Heterogeneity was revealed across psychometric properties (consistency, construct, reliability, discrimination ability). Intentionality correlated positively with negative beliefs (r(57)=0.88) and barriers (r(57)=0.59). For every belief or barrier criterion-item, PROMs' aptitude to detect intentional non-adherence increased by β=0.79 and β=0.34 units, respectively (R2=0.94). Primary care versus specialised care predicted intentional non-adherence (OR 1.9; CI 1.01 to 2.66).

CONCLUSIONS

Ten PROMs had adequate psychometric properties. Of the ten, eight PROMs were able to detect total, and two PROMs were able to detect partial intentionality to medication default. Fortification of patients' knowledge and illness perception, as opposed to daily reminders alone, is most imperative at primary care levels.

Factors Associated with the Refusal of Direct-Acting Antiviral Agents for the Treatment of Hepatitis C in Taiwan

Background and Objectives: Direct-acting antiviral agents (DAA) are a safe and highly effective treatment for hepatitis C virus (HCV) infection. However, the uptake of DAA treatment remains a challenge. This study aims to examine the reasons for DAA refusal among HCV patients covered by the Taiwan National Health Insurance system. Materials and Methods: This retrospective observational study covered the period from January 2009 to December 2019 and was conducted at a single hepatitis treatment center in Taiwan. This study involved chart reviews and phone-based surveys to confirm treatment status and refusal causes. To confirm treatment status, subjects with HCV without treatment records were phone-contacted to confirm treatment status. Patients who did not receive treatment were invited back for treatment. If the patient refused, the reason for refusal was discussed. Results: A total of 3566 patients were confirmed with DAA treatment; 418 patients (179 patients who were lost to contact or refused the survey and 239 patients who completed the survey of DAA refusal) were included in the no-DAA-therapy group. Factors associated with receiving DAAs were hemoglobin levels, hepatitis B virus co-infection, and regular gastroenterology visits. Meanwhile, male sex, platelet levels, and primary care physician visits were associated with DAA refusal. The leading causes of treatment refusal were multiple comorbidities, low health literacy, restricted access to hospitals, nursing home residence, and old age. The rate of DAA refusal remains high (10%). Conclusions: The reasons for treatment refusal are multifactorial, and addressing them requires complex interventions.