Multidrug and optimal heart failure therapy prescribing in older general practice populations : A clinical data linkage study

Objective: To investigate multidrug therapy in the cardiovascular disease (CVD) population and whether it was associated with suboptimal drug prescribing in heart failure (HF). Design: A population-based cross-sectional clinical data linkage study. Setting: The clinical database populations were registered with three general practices in North Staffordshire that are part of a research network. Participants: 3155 patients aged 50 years and over were selected on the basis of a CVD-related prescription and a CVD consultation code applied to their electronic medical record in a 2-year time period. All available diagnostic data were linked to all drugs prescribed data during this time period. Two study groups were: (1) HF and (2) non-HF CVD (reference group). Exposure: A standard drug formulary system was used to define four multidrug count categories based on the number of different British National Formulary drug chapters prescribed at the same time. Primary: and secondary outcome measures Optimal HF therapy was defined as the prescribing of ACE inhibitor (ACEi) or a combination of ACEi and β-blocker in the 2-year time window. An additional three specific CVD drug categories that are indicated in HF were also measured. Results: The HF group, compared with the reference group, had higher non-CVD multidrug therapy (26% with 7 or more counts compared with 14% in the non-HF CVD reference group). For the first-choice optimal drug treatment for HF with ACEi (64%) or ACEi and β-blocker combined therapy (23%), the multidrug-adjusted associations between the HF group and the reference group were OR 3.89; 95% CI 2.8 to 5.5 and 1.99; 1.4 to 2.9, respectively. These estimates were not influenced by adjustment for sociodemographic factors and multidrug counts. Conclusions: Multidrug therapy prescribing is much higher in the HF group than in a comparable CVD group but did not influence optimal drug prescribing.