The need for patient adherence standard measures for Big Data

Kardas, Przemyslaw ; Aguilar-Palacio, Isabel (Universidad de Zaragoza) ; Almada, Marta ; Cahir, Caitriona ; Costa, Elíseo ; Giardini, Anna ; Malo, Sara (Universidad de Zaragoza) ; Massot Mesquida, Mireia ; Menditto, Enrica ; Midão, Luis ; Parra-Calderón, Carlos Luis ; Pepiol Salom, Enrique ; Vrijens, Bernard

Resumen: Despite half a century of dedicated studies, medication adherence remains far from perfect, with many patients not taking their medications as prescribed. The magnitude of this problem is rising, jeopardizing the effectiveness of evidence-based therapies. An important reason for this is the unprecedented demographic change at the beginning of 21st century. Ageing leads to multimorbidity and complex therapeutic regimens that create fertile ground for non-adherence. As this scenario is a global problem, it needs a worldwide answer. Might this answer be provided, given the new opportunities created by the digitization of healthcare? Day by day health-related information is collected in electronic health records, pharmacy dispensing databases, health insurance systems and national health system records. These Big Data repositories offer a unique chance to study adherence both retrospectively and prospectively, at population level, as well as its related factors. In order to make the full use of this opportunity, there is a need to develop standardised measures of adherence, which can be applied globally to Big Data and will inform scientific research, clinical practice and public health. These standardized measures may also enable a better understanding of the relationship between adherence and clinical outcomes, and allow for fair benchmarking of effectiveness and cost-effectiveness of adherence-targeting interventions. Unfortunately, despite this obvious need, such standards are still lacking. Therefore, the aim of this paper is to call for producing a consensus on global standards for measuring adherence with Big Data. More specifically, sound standards of formatting, and analysing Big Data are needed in order to assess, uniformly present and compare patterns of medication adherence across studies. Wide use of these standards may improve adherence, and make healthcare systems more effective and sustainable.

Idioma: Inglés

DOI: 10.2196/18150

Año: 2020

Publicado en: Journal of Medical Internet Research 22, 8 (2020), e18150 [21 pp.]
ISSN: 1438-8871

Factor impacto JCR: 5.428 (2020)

Categ. JCR: MEDICAL INFORMATICS rank: 5 / 30 = 0.167 (2020) - Q1 - T1
Categ. JCR: HEALTH CARE SCIENCES & SERVICES rank: 10 / 108 = 0.093 (2020) - Q1 - T1

Factor impacto SCIMAGO: 1.446 - Health Informatics (Q1)

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Medic.Prevent.Salud Públ. (Dpto. Microb.Ped.Radio.Sal.Pú.)