TY - JOUR
T1 - Disease prevalence estimations based on contact registrations in general practice
AU - Hoogenveen, Rudolf
AU - Westert, Gert
AU - Dijkgraaf, Marcel
AU - Schellevis, François
AU - de Bakker, Dinny
PY - 2002
Y1 - 2002
N2 - This paper describes how to estimate the prevalence of chronic diseases in a population using data from contact registrations in general practice with a limited time length. Instead of using only total numbers of observed patients adjusted for the length of the observation period, we propose the use of (i) the time of the first contact of patients, (ii) the joint total numbers of patients and contacts, and (iii) the sets of patients in distinct time intervals, to generate prevalence rate estimates. The three new prevalence rate estimators have been developed assuming either a homogeneous or a parameterized heterogeneous patient population. Systematic and stochastic components of the estimators have been analysed by cross-validation for five chronic diseases using data from the Dutch 'Study on Chronic Conditions'. The results show that the first two estimators work well for diseases with a relatively structured visiting behaviour, such as hypertension and diabetes mellitus, assuming a time-constant contact rate and homogeneous patient population. For diseases such as ischaemic heart disease, chronic non-specific respiratory diseases and osteoarthritis, that do not satisfy these assumptions, the methods generally result in underestimations
AB - This paper describes how to estimate the prevalence of chronic diseases in a population using data from contact registrations in general practice with a limited time length. Instead of using only total numbers of observed patients adjusted for the length of the observation period, we propose the use of (i) the time of the first contact of patients, (ii) the joint total numbers of patients and contacts, and (iii) the sets of patients in distinct time intervals, to generate prevalence rate estimates. The three new prevalence rate estimators have been developed assuming either a homogeneous or a parameterized heterogeneous patient population. Systematic and stochastic components of the estimators have been analysed by cross-validation for five chronic diseases using data from the Dutch 'Study on Chronic Conditions'. The results show that the first two estimators work well for diseases with a relatively structured visiting behaviour, such as hypertension and diabetes mellitus, assuming a time-constant contact rate and homogeneous patient population. For diseases such as ischaemic heart disease, chronic non-specific respiratory diseases and osteoarthritis, that do not satisfy these assumptions, the methods generally result in underestimations
U2 - https://doi.org/10.1002/sim.1085
DO - https://doi.org/10.1002/sim.1085
M3 - Article
C2 - 12210638
SN - 0277-6715
VL - 21
SP - 2271
EP - 2285
JO - Statistics in medicine
JF - Statistics in medicine
IS - 15
ER -