Objectives:To investigate which symptoms are indicative of preclinical dementia in general practice and whether subjects with preclinical dementia have an increased contact frequency with their general practitioner (GP). Methods: Individuals with preclinical dementia (n = 75) and non-demented controls (n = 125) were selected from the Dutch GP registration network (RNH). Number of visits and odds ratio for the risk of subsequent dementia of various symptoms were analysed. Analyses were done separately for each 12-month period, in the 5 years prior to the diagnosis of dementia. Results: In the 5 years prior to diagnosis, subjects with preclinical dementia visited their GP more often than controls. Gait disturbances were the earliest predictor. Cognitive complaints were predictive for dementia in the 3 years before diagnosis. All other symptoms, except vascular symptoms, were predictive in the year prior to diagnosis. Sensitivity was highest for cognitive symptoms (0.58) and gait disturbances (0.47) in the year before diagnosis. Conclusion:Preclinical dementia is associated with an increased contact frequency between patient and GP at least 5 years prior to the diagnosis of dementia. Gait disturbances and cognitive complaints are the earliest symptoms of preclinical dementia.

BackgroundPhysicians are frequently confronted with complex health situations of patients, but knowledge of intensive forms of multimorbidity and their development during life is lacking.This study explores patterns and trajectories of chronic health problems of patients with multimorbidity particularly those with more than ten conditions and type and variety of organ systems involved in these patterns during life.MethodLife time prevalence patterns of chronic health problems were determined in patients with illness trajectories accumulating more than ten chronic health problems during life as registered by general practitioners in the South of the Netherlands in the Registration Network Family Practices (RNH).ResultsOverall 4,560 subjects (5%) were registered with more than ten chronic health problems during their life (MM11+), accounting for 61,653 (20%) of the 302,808 registered health problems in the population (N = 87,837 subjects). More than 30% accumulates 4 or more chronic health conditions (MM4-5: 4–5 conditions (N = 14,199; 16.2%); MM6-10: 6–10 conditions (N = 14,365; 16.4%).Gastro-intestinal, cardiovascular, locomotor, respiratory and metabolic conditions occur more frequently in the MM11+ patients than in the other patients, while the nature and variety of body systems involved in lifetime accumulation of chronic health problem clusters is both generic and specific. Regarding chronic conditions afflicting multiple sites throughout the body, the number of neoplasms seems low (N = 3,592; 5.8%), but 2,461 (49%) of the 4,560 subjects have registered at least one neoplasm condition during life. A similar pattern is noted for inflammation (N = 3,537, 78%), infection (N = 2,451, 54%) and injury (N = 3,401, 75%).ConclusionThere are many challenges facing multimorbidity research, including the implementation of a longitudinal, life-time approach from a family practice perspective. The present study, although exploratory by nature, shows that both general and specific mechanisms characterize the development of multimorbidity trajectories. A small proportion of patients has a high number of chronic health problems (MM11+) and keeps adding health problems during life. However, GP’s need to realise that more than one third of their patients accumulate four or more chronic health problems (MM4-5 and MM6-10) during life.

Background: Information on the incidence and prevalence of diseases is a core indicator for public health. There are several ways to estimate morbidity in a population (e.g., surveys, healthcare registers). In this paper, we focus on one particular source: general practice based registers. Dutch general practice is a potentially valid source because nearly all noninstitutionalized inhabitants are registered with a general practitioner (GP), and the GP fulfils the role as ''gatekeeper''. However, there are some unexplained differences among morbidity estimations calculated from the data of various general practice registration networks (GPRNs). Objective: To describe and categorize factors that may explain the differences in morbidity rates from different GPRNs, and to provide an overview of these factors in Dutch GPRNs. Results: Four categories of factors are distinguished: ''healthcare system'', ''methodological characteristics'', ''general practitioner'', and ''patient''. The overview of 11 Dutch GPRNs reveals considerable differences in factors.Conclusion: Differences in morbidity estimation depend on factors in the four categories. Most attention is dedicated to the factors in the ''methodology characteristics'' category, mainly because these factors can be directly influenced by the GPRN.

Objective After stratifying for age, sex and multimorbidity at baseline, our aim is to analyse time trends in incident multimorbidity and polypharmacy in the 15-year clinical trajectories of individual patients in a family medicine setting. Methods This study was carried out using data from the Registration Network Family Medicine in the South of the Netherlands. The clinical trajectories of 10037 subjects during the 15-year period (2000–2014) were analyzed in a repeated measurement of using a generalized estimating equations model as well as a multilevel random intercept model with repeated measurements to determine patterns of incident multimorbidity and polypharmacy. Hierarchical age-period-cohort models were used to generate age and cohort trajectories for comparison with prevalence trends in multimorbidity literature. Results Multimorbidity was more common in females than in males throughout the duration of the 15-year trajectory (females: 39.6%; males: 33.5%). With respective ratios of 11.7 and 5.9 between the end and the beginning of the 15-year period, the youngest female and male groups showed a substantial increase in multimorbidity prevalence. Ratios in the oldest female and male groups were 2.2 and 1.9 respectively. Females had higher levels of multimorbidity than males in the 0-24-year and 25-44-year age groups, but the levels converged to a prevalence of 92.2% in the oldest male and 90.7% in the oldest female group. Similar, albeit, moderate differences were found in polypharmacy patterns. Conclusions We sought to specify the progression of multimorbidity from an early age. As a result, our study adds to the multimorbidity literature by specifying changes in chronic disease accumulation with relation to polypharmacy, and by tracking differences in patient trajectories according to age and sex. Multimorbidity and polypharmacy are common and their prevalence is accelerating, with a relatively rapid increase in younger groups. From the point of view of family medicine, this underlines the need for a longitudinal approach and a life course perspective in patient care.

Since guidelines on antibiotic drug treatment often focus on appropriate first choice drugs, assessment of guideline adherence should only concentrate on the first drug prescribed, and not on subsequent antibiotics prescribed after failure of the first one.PurposeTo determine a valid cut-off point for a definition of “first” or “new” prescription in indicators for the assessment of the quality of antibiotic drug treatment on the basis of pharmaceutical data.MethodsThree possible definitions for the term “new prescription” were compared, based on three different periods of time, viz. more than 35, 28, or 21 days after starting a previous antibiotic. In an observational study, 1,225 antimicrobial prescriptions from the medical files of five family practices were audited (“clinical classification”) and compared with a classification based on the three definitions (“technical classification”). Agreement between these clinical and technical classifications was determined by calculating Cohen’s kappa. The technical classification was analyzed as a diagnostic test, using the clinical classification as the gold standard, and sensitivity, specificity, likelihood ratios, and post-test probabilities were calculated.ResultsDefining “new prescription” as “more than 35 days after a previous prescription was issued” resulted in a Cohen’s kappa of 0.93 (95% CI 0.92–0.98). The diagnostic value of this definition was extremely high, with a sensitivity of 0.976, specificity of 0.987, positive likelihood ratio of 77.7, and negative likelihood ratio of 0.02.ConclusionWe recommend using a cut-off value of 35 days since the last antimicrobial prescription as the definition of a “new prescription” when no diagnostic information is available, i.e., when using pharmaceutical data to assess the quality of antibiotic prescribing behavior.