Objective
Guidelines recommend non-invasive ischaemia testing (NIIT) for the majority of patients with suspected ischaemic heart disease in a non-emergency setting. A substantial number of these patients undergo diagnostic coronary angiography (CA) without therapeutic intervention inappropriately due to lacking preceding NIIT. The aim of this study was to evaluate the effect of voluntary healthcare models with limited access on the proportion of patients without NIIT prior to elective purely diagnostic CA.
DesignRetrospective cross-sectional analysis of insurance claims data from 2012 to 2015. Data included claims of basic and voluntary healthcare models from approximately 1.2 million patients enrolled with the Helsana Insurance Group. Voluntary healthcare models with limited health access are divided into gate keeping (GK) and managed care (MC) capitation models. Inclusion criteria: patients undergoing CA. Exclusion criteria: Patients<18 years, incomplete health insurance data coverage, acute cardiac ischaemia and emergency procedures, therapeutic CA (coronary angioplasty/stenting or coronary artery bypass grafting). The effect of voluntary healthcare models on the proportion of NIIT undertaken within 2 months before diagnostic CA was assessed by means of multiple logistic regression analysis, controlled for influencing factors.
Results9173 patients matched inclusion criteria. 33.2% (3044) did not receive NIIT before CA. Compared with basic healthcare models, MC was independently associated with a higher proportion of NIIT (p<0.001, OR 1.17, CI 1.045 to 1.312), when additionally controlled for demographics, insurance coverage, inpatient treatment, cardiovascular medication, chronic comorbidities, high-risk status (patients with therapeutic cardiac intervention 1 month after or 18 months prior to diagnostic CA). GK models showed no significant association with the rate of NIIT (p=0.07, OR 1.11, CI 0.991 to 1.253).
ConclusionsIn a non-GK healthcare system, voluntary MC healthcare models with capitation were associated with a reduced inappropriate use of diagnostic CA compared with GK or basic models.
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