British journal of clinical pharmacology · 2026
Standardization of measurement and reporting of medication adherence using the TEN-SPIDERS tool for claims data.
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Livori Adam C, Kuo Tzu-Yung, Ilomäki Jenni, Kilkenny Monique F, Talic Stella, Ademi Zanfina, Bell J Simon, Morton Jedidiah I, Dalli Lachlan L
Аннотация
AIM: The TEN-SPIDERS framework provides a structured approach to calculating and reporting the proportion of days covered (PDC) in medication adherence research, but gaps remain in operationalizing this framework into statistical code. We aimed to develop an open-source tool to standardize PDC calculation against parameters of the TEN-SPIDERS reporting framework.
METHODS: Phase 1 involved developing the Stata statistical tool to enable flexible adjustment of TEN-SPIDERS PDC parameters: threshold, eligibility, numerator, in-hospital stays, dose imputation, early refills and survival. The tool was developed to align with established data definitions, variable schemas and person-level record structures in linked Australian Pharmaceutical Benefits Scheme (PBS) datasets, with scope for interoperability across similar international systems. In Phase 2, PDC was estimated in a linked PBS dataset for survivors of myocardial infarction (37 919 statin users and 29 163 P2Y12 inhibitor users). The impact of different TEN-SPIDERS adjustments was evaluated against basic settings and a pre-existing Stata package (MedAdhere).
RESULTS: The TEN-SPIDERS tool was developed to support reproducible PDC calculations. While computation time was similar to the pre-existing MedAdhere package (116.5 vs. 100.2 s), the TEN-SPIDERS tool had greater flexibility to incorporate adjustments for different medication-taking situations. A bivariate comparison between different settings of TEN-SPIDERS highlighted a strong correlation (Pearson's r: >.9) with MedAdhere, with additional adjustments reducing Pearson's correlation from .987 to .921.
CONCLUSION: The TEN-SPIDERS tool provides a transparent, reproducible and efficient open-source method for medication adherence research within Australia, with potential applicability to similarly structured international datasets. Adoption of this tool will support global efforts for standardization in medication adherence research.
METHODS: Phase 1 involved developing the Stata statistical tool to enable flexible adjustment of TEN-SPIDERS PDC parameters: threshold, eligibility, numerator, in-hospital stays, dose imputation, early refills and survival. The tool was developed to align with established data definitions, variable schemas and person-level record structures in linked Australian Pharmaceutical Benefits Scheme (PBS) datasets, with scope for interoperability across similar international systems. In Phase 2, PDC was estimated in a linked PBS dataset for survivors of myocardial infarction (37 919 statin users and 29 163 P2Y12 inhibitor users). The impact of different TEN-SPIDERS adjustments was evaluated against basic settings and a pre-existing Stata package (MedAdhere).
RESULTS: The TEN-SPIDERS tool was developed to support reproducible PDC calculations. While computation time was similar to the pre-existing MedAdhere package (116.5 vs. 100.2 s), the TEN-SPIDERS tool had greater flexibility to incorporate adjustments for different medication-taking situations. A bivariate comparison between different settings of TEN-SPIDERS highlighted a strong correlation (Pearson's r: >.9) with MedAdhere, with additional adjustments reducing Pearson's correlation from .987 to .921.
CONCLUSION: The TEN-SPIDERS tool provides a transparent, reproducible and efficient open-source method for medication adherence research within Australia, with potential applicability to similarly structured international datasets. Adoption of this tool will support global efforts for standardization in medication adherence research.