Estimating incidence and prevalence rates of chronic diseases using disease modeling.
dc.contributor.author | Boshuizen, Hendrike C | |
dc.contributor.author | Poos, Marinus J J C | |
dc.contributor.author | van den Akker, Marjan | |
dc.contributor.author | van Boven, Kees | |
dc.contributor.author | Korevaar, Joke C | |
dc.contributor.author | de Waal, Margot W M | |
dc.contributor.author | Biermans, Marion C J | |
dc.contributor.author | Hoeymans, Nancy | |
dc.date.accessioned | 2018-02-07T08:11:03Z | |
dc.date.available | 2018-02-07T08:11:03Z | |
dc.date.issued | 2017-04-05 | |
dc.identifier.citation | Estimating incidence and prevalence rates of chronic diseases using disease modeling. 2017, 15 (1):13 Popul Health Metr | en |
dc.identifier.issn | 1478-7954 | |
dc.identifier.pmid | 28381229 | |
dc.identifier.doi | 10.1186/s12963-017-0130-8 | |
dc.identifier.uri | http://hdl.handle.net/10029/621348 | |
dc.description.abstract | Morbidity 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. | |
dc.language.iso | en | en |
dc.rights | Archived with thanks to Population health metrics | en |
dc.title | Estimating incidence and prevalence rates of chronic diseases using disease modeling. | en |
dc.type | Article | en |
dc.identifier.journal | Popul Health Metr 2017; 15(1):13 | en |
html.description.abstract | Morbidity 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. |