What factors explain the differences in morbidity estimations among general practice registration networks in the Netherlands? A first analysis

Dungen, Catharina van den; Hoeymans, Nancy; Gijsen, R; Akker, Marjan van den; Boesten, Jos; Brouwer, Henk J.; Smeets, Hugo M.; Veen, Willem Jan van der; Verheij, Robert; Waal, Margot W. M. de; Schellevis, F.G.; Westert, Gert P.

doi:10.1080/13814780802436218

Cited by 28 publications

(23 citation statements)

References 17 publications

(15 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…GPs use the International Classification of Primary Care (ICPC) to code all diagnoses in the patient’s EHR [15], including those made by specialists after referral [16]. GPRNs collect and manage the EHR data of large numbers of associated general practices.…”

Section: Methodsmentioning

confidence: 99%

“…In two databases, new dementia cases were identified when the ICPC code P70 was entered on the problem list (RNUH-LEO and RNH). In the seven other databases, new dementia cases were identified when the ICPC code P70 was recorded in the episode list for a patient contact [16]. Within each database, coding and selection criteria were stable over the whole time frame of the study.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Dementia incidence trend over 1992-2014 in the Netherlands: Analysis of primary care data

et al. 2017

Self Cite

View full text Add to dashboard Cite

BackgroundRecent reports have suggested declining age-specific incidence rates of dementia in high-income countries over time. Improved education and cardiovascular health in early age have been suggested to be bringing about this effect. The aim of this study was to estimate the age-specific dementia incidence trend in primary care records from a large population in the Netherlands.Methods and findingsA dynamic cohort representative of the Dutch population was composed using primary care records from general practice registration networks (GPRNs) across the country. Data regarding dementia incidence were obtained using general-practitioner-recorded diagnosis of dementia within the electronic health records. Age-specific dementia incidence rates were calculated for all persons aged 60 y and over; negative binomial regression analysis was used to estimate the time trend. Nine out of eleven GPRNs provided data on more than 800,000 older people for the years 1992 to 2014, corresponding to over 4 million person-years and 23,186 incident dementia cases. The annual growth in dementia incidence rate was estimated to be 2.1% (95% CI 0.5% to 3.8%), and incidence rates were 1.08 (95% CI 1.04 to 1.13) times higher for women compared to men. Despite their relatively low numbers of person-years, the highest age groups contributed most to the increasing trend. There was no significant overall change in incidence rates since the start of a national dementia program in 2003 (−0.025; 95% CI −0.062 to 0.011). Increased awareness of dementia by patients and doctors in more recent years may have influenced dementia diagnosis by general practitioners in electronic health records, and needs to be taken into account when interpreting the data.ConclusionsWithin the clinical records of a large, representative sample of the Dutch population, we found no evidence for a declining incidence trend of dementia in the Netherlands. This could indicate true stability in incidence rates, or a balance between increased detection and a true reduction. Irrespective of the exact rates and mechanisms underlying these findings, they illustrate that the burden of work for physicians and nurses in general practice associated with newly diagnosed dementia has not been subject to substantial change in the past two decades. Hence, with the ageing of Western societies, we still need to anticipate a dramatic absolute increase in dementia occurrence over the years to come.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Dementia incidence trend over 1992-2014 in the Netherlands: Analysis of primary care data

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…Although more registration networks exist in the Netherlands [1], these five have been used for population health monitoring [6, 7]. Table 1 shows the full names, abbreviations, and some characteristics of these five networks in 2010.…”

Section: Methodsmentioning

confidence: 99%

“…In an earlier publication, we described these five networks in more detail [1]. Apart from incidence and prevalence rates, the networks also provided data on the number of patients that died.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Estimating incidence and prevalence rates of chronic diseases using disease modeling

Boshuizen¹,

Poos²,

Akker³

et al. 2017

Popul Health Metrics

Self Cite

View full text Add to dashboard Cite

BackgroundMorbidity estimates between different GP registration networks show large, unexplained variations. This research explores the potential of modeling differences between networks in distinguishing new (incident) cases from existing (prevalent) cases in obtaining more reliable estimates.MethodsData from five Dutch GP registration networks and data on four chronic diseases (chronic obstructive pulmonary disease [COPD], diabetes, heart failure, and osteoarthritis of the knee) were used. A joint model (DisMod model) was fitted using all information on morbidity (incidence and prevalence) and mortality in each network, including a factor for misclassification of prevalent cases as incident cases.ResultsThe observed estimates vary considerably between networks. Using disease modeling including a misclassification term improved the consistency between prevalence and incidence rates, but did not systematically decrease the variation between networks. Osteoarthritis of the knee showed large modeled misclassifications, especially in episode of care-based registries.ConclusionRegistries that code episodes of care rather than disease generally provide lower estimates of the prevalence of chronic diseases requiring low levels of health care such as osteoarthritis. For other diseases, modeling misclassification rates does not systematically decrease the variation between registration networks. Using disease modeling provides insight in the reliability of estimates.

show abstract

Acute niet-traumatische heupafwijkingen bij kinderen

Krul¹,

Wouden²,

Schellevis³

et al. 2010

HUWE

Self Cite

View full text Add to dashboard Cite

What factors explain the differences in morbidity estimations among general practice registration networks in the Netherlands? A first analysis

Cited by 28 publications

References 17 publications

Dementia incidence trend over 1992-2014 in the Netherlands: Analysis of primary care data

Dementia incidence trend over 1992-2014 in the Netherlands: Analysis of primary care data

Estimating incidence and prevalence rates of chronic diseases using disease modeling

Acute niet-traumatische heupafwijkingen bij kinderen

Contact Info

Product

Resources

About