Original Articles

Correction for potentially inappropriate prescribing can increase specificity when using drug prescriptions as an adjunct to diagnostic codes to assess comorbidities in older patients


Abstract


Background: Comorbidities are a growing problem in older patients in many clinical settings, but electronic records may give an unsatisfactory picture of this complexity. Analysis of drug prescriptions can add further diagnostic information to that gathered from billing diagnostic codes, but the risk exhists that potentially inappropriate prescriptions may lead to over-estimating comorbidities.

Methods: We analysed the administrative records and drug prescriptions of the 304 patients discharged during 2016 from a neurological rehabilitation unit. International Classification of Diseases – 9th revision diagnostic codes were matched with prescriptions at discharge, coded according to the Anatomical Therapeutic Chemical classification. The codes of the prescriptions not explained by the diagnostic codes were recorded, grouped, corrected for potential inappropriate prescribing, and analysed.

Results: Of the 304 patients, 295 had at least one prescribed drug not inferable from their diagnostic codes. The mean number of these prescriptions was 3.5 ± 1.9 per patient, and that of prescriptions remaining after correction for potentially inappropriate prescribing was 2.0 ± 1.5. The more frequent groups of potentially inappropriate medications were anti-acids, psychotropic drugs, laxatives, potassium supplements, cardiovascular drugs and lipid modifying agents. Administrative databases underestimate the complexity of older patients in neurological rehabilitation wards. More reliable data can be obtained by adding the analysis of drug prescriptions, but correction for potentially inappropriate prescription seems necessary to avoid an over-estimation of comorbidities.


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DOI: https://doi.org/10.2427/13002

NBN: http://nbn.depositolegale.it/urn%3Anbn%3Ait%3Aprex-24624

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EBPH Epidemiology, Biostatistics and Public Health | ISSN 2282-0930

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.