A multistate model and an algorithm for measuring long-term adherence to medication: a case of diabetes mellitus type 2.
Value Health
; 17(2): 266-74, 2014 Mar.
Article
em En
| MEDLINE
| ID: mdl-24636386
ABSTRACT
OBJECTIVES:
To develop a multistate model and an algorithm for calculating long-term adherence to medication among patients with a chronic disease.METHODS:
We propose definitions of the different states of waiting, persistence, with sufficient supply to implement the prescribed dosing regimen, gaps, nonpersistence, and nonacceptance and an algorithm for transitions between states to describe long-term adherence to medication treatment. The model and algorithm are operationalized for use in a case with a retrospective cohort of patients with type 2 diabetes mellitus, with access to records of prescribed drugs from a Danish diabetes research hospital and records of filled prescriptions at Danish pharmacies from the Danish Health and Medicines Authority.RESULTS:
Calculations of long-term adherence to medication are shown for patients with type 2 diabetes mellitus on metformin and/or simvastatin. The study shows how the prevalence of patients waiting to initiate treatment, patients with supply to implement the prescribed dosing regimen, patients not accepting treatment, and patients discontinuing treatment varies over time.CONCLUSIONS:
The proposed multistate model and algorithm can easily be translated and used for the calculation of adherence to medication in any chronic disease. The model and algorithm take time into account, and thus, changes in incidence rates and prevalence of the different states over time can be estimated on several time scales (calendar time, age of the patient, and time since indication for medication).Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Diabetes Mellitus Tipo 2
/
Adesão à Medicação
/
Hipoglicemiantes
/
Metformina
/
Modelos Teóricos
Tipo de estudo:
Etiology_studies
/
Incidence_studies
/
Observational_studies
/
Prevalence_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
País/Região como assunto:
Europa
Idioma:
En
Revista:
Value Health
Assunto da revista:
FARMACOLOGIA
Ano de publicação:
2014
Tipo de documento:
Article