title: Multidimensional analysis of treatment adherence in patients with multiple chronic conditions. A cross-sectional study in a tertiary hospital.
abstract: OBJECTIVE
  Determine treatment adherence in patients with multiple chronic conditions (MCC).
  
  
  METHODS
  A random patient sample ≥ 15 years, discharged from hospital with ≥1 chronic conditions (CC) was interviewed after 6-12 months. Analysis included variables in 5 dimensions (WHO): socio-demographics, disease, treatment, patient and health system characteristics. Morisky-Green adherence questionnaire was used. High chronic treatment complexity was defined as: >3 pills/day, >6 inhalations/day, >1 injection/day, pharmacological treatment plus diet or self-monitoring techniques.
  
  
  RESULTS
  301 patients were interviewed (62 ± 15 years, 59% males). Despite good treatment information perception (79%), only 3% followed the patient education programme. Poor adherents (82%) were older (64 ± 14 years vs. 55 ± 16 years), had more CC (3.25 ± 2.02 vs. 2.62 ± 2.72), a higher frequency of hypertension (44% vs. 15%), ischaemic heart diseases: (21% vs. 4%), hyperlipidaemia (19% vs. 6%), more pills/day (5.78 ± 4.14 vs. 3.20 ± 4.70) and more complex treatments (95% vs. 70%) (p<0.05). On multivariate analysis number of CC [3.68 (0.75-18.15)], pills/day [2.23 (1.02-4.84)], treatment complexity [4.00 (1.45-11.04)], and hypertension [2.57 (1.06-6.25)] were predictive of poor adherence (OR 95% CI p<0.05).
  
  
  CONCLUSIONS
  The WHO conceptual framework allows the construction of poor adherence risk profiles in patients with MCC after hospital discharge.
  
  
  CONCLUSIONS
  Predictive variables of poor adherence could help clinicians detect patients with MCC most likely to present poor adherence.
authors.affiliation: Diabetes Unit, Hospital Clínic, Barcelona, Spain. mjansa@clinic.ub.es
authors.forename: Margarida
authors.initials: M
authors.lastname: Jansà
authors.forename: Carme
authors.initials: C
authors.lastname: Hernández
authors.forename: Mercè
authors.initials: M
authors.lastname: Vidal
authors.forename: Montse
authors.initials: M
authors.lastname: Nuñez
authors.forename: M Jesús
authors.initials: MJ
authors.lastname: Bertran
authors.forename: Sergi
authors.initials: S
authors.lastname: Sanz
authors.forename: Conxa
authors.initials: C
authors.lastname: Castell
authors.forename: Ginés
authors.initials: G
authors.lastname: Sanz
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease / Q000188:drug therapy*; D003430:Cross-Sectional Studies; D005260:Female; D006784:Hospitals, Teaching; D006801:Humans; D007407:Interviews as Topic; D008297:Male; D008875:Middle Aged; D010351:Patient Discharge / Q000706:statistics & numerical data*; D010353:Patient Education as Topic; D019338:Polypharmacy; D011446:Prospective Studies; D012646:Self Administration; D012959:Socioeconomic Factors; D013030:Spain; D011795:Surveys and Questionnaires; D014944:World Health Organization; D055815:Young Adult; D016903:Drug Monitoring