How UnifiedACB handles conflicting drug scores

The project’s decision is to preserve the disagreement

When two sources publish different classifications for a medication, UnifiedACB keeps the observations separate. The interface is intended to make the disagreement understandable rather than conceal it behind a newly calculated value. This is an editorial and data-governance choice, not a claim that every source is equally informative for every clinical question.

The choice matters because a single cleaned-up number can hide whether the original issue involved different methods, different document versions or a questionable identity match. Once that detail is lost, readers cannot reconstruct why the sources differed.

What remains attached to a finding

The public observation file retains an observation identifier, medication concept, original source label, source-version identifier, value, evidence state and source locator. These fields allow the visible result to be traced back to the source record rather than to an undocumented site-level interpretation.

A preferred medication name supports navigation across records. It does not replace the literal source label. Likewise, a narrative explanation can describe why a difference matters, but it does not replace a source-native value in the evidence table.

Cross-scale differences are shown as cross-scale differences

The public paroxetine record contains BAAS 2019 value 3 and value 2 in several other identified public source versions. Those observations are retained as published source-specific entries. The project does not average them or label the most common category as a new UnifiedACB score.

A reader can investigate the methods behind the difference, compare source coverage and consider the clinical question. The site’s responsibility is to keep that investigation possible. A visually simpler consensus value would imply an adjudication that has not occurred.

Document-level anomalies receive their own explanation

The existing KABS notes distinguish several types of problem. The levodopa/decarboxylase inhibitor note identifies a difference between the medication-list supplement and a main-text validation table. The quinupramine note records main-text information without creating a missing list row. The doxepin and chlorpromazine notes identify omissions that cannot be repaired from category counts alone.

These four anomaly records communicate the source problem while preserving the public observations. They are not hidden corrections and do not imply that the reader should substitute a guessed value. Each note names the document-level boundary that a future adjudication would need to resolve.

What a defensible correction would contain

A proposed correction should identify the exact observation, the original publication or supplement, the relevant locator and the reason the current representation is wrong. An identity correction also needs to explain the mapping between the source label and medication concept. This is more specific than reporting that a number seems unexpected.

If a later source changes a classification, that creates a versioned finding. It should not silently rewrite the historical document’s value. If the website transcribed a source incorrectly, a correction should preserve the audit trail so the old representation and the reason for the change remain understandable.

What this approach gives the reader

The benefit is a record that can be questioned and checked. Readers can distinguish a published classification from a project note, a clinical criterion from a scale observation, and a true zero from an unavailable value. The remaining uncertainty is visible rather than compressed into a badge.

The next useful step is often a targeted source question: which version supplied this observation, does the source label match the product, or what evidence would resolve the discrepancy? UnifiedACB’s role is to support that inquiry while keeping the scientific record intact.

References

1. Vennard O, Stewart C, Tolia M, Soiza RL, Myint PK. Anticholinergic Medication Burden Scales: A Systematic Review. J Am Geriatr Soc. 2026;74(6):1771-1784. Source
2. Chew ML, et al. Anticholinergic activity of 107 medications commonly used by older adults. J Am Geriatr Soc. 2008;56:1333-1341. Source
3. Carnahan RM, et al. The Anticholinergic Drug Scale as a measure of drug-related anticholinergic burden: associations with serum anticholinergic activity. J Clin Pharmacol. 2006;46:1481-1486. Source
4. Rudolph JL, et al. The anticholinergic risk scale and anticholinergic adverse effects in older persons. Arch Intern Med. 2008;168:508-513. Source
5. Boustani M, et al. Impact of anticholinergics on the aging brain: a review and practical application. Aging Health. 2008;4:311-320. Source
6. Lisibach A, Benelli V, Ceppi MG, et al. Quality of anticholinergic burden scales and their impact on clinical outcomes: a systematic review. Eur J Clin Pharmacol. 2021;77(2):147-162. Source
7. UnifiedACB. Preserved public source-observation dataset, v3.0 RC12 final; inspected for this editorial revision. Source

Disclosure

Funding: None. Conflict of interest: None declared for the UnifiedACB educational project.

Educational evidence summary. This content does not provide patient-specific medical advice and does not replace clinical judgment, medication reconciliation, or prescribing guidance.