Bibtex export

 

@article{ Bödeker2010,
 title = {Prioritization of diseases for work-related health monitoring by multidimensional ranking},
 author = {Bödeker, Wolfgang and Klindworth, Heike},
 journal = {Journal of Public Health},
 number = {2},
 pages = {113-120},
 volume = {19},
 year = {2010},
 doi = {https://doi.org/10.1007/s10389-010-0370-6},
 urn = {https://nbn-resolving.org/urn:nbn:de:0168-ssoar-247807},
 abstract = {Aim: Although working life issues are subject to European health monitoring schemes, not many routine data sources include information on occupations or working conditions. Additional in-depth analysis is therefore necessary for diseases with high public health impact. The aim of this paper is to introduce a multidimensional ranking procedure for priority setting of diseases based on European and national data. Subject and methods: Multidimensional ranking was carried out on ten disease-specific indicators. First, suitable data sources were identified and information on indicators was retrieved. Second, the diseases were sorted by their ranks according to each indicator. Third, all ranks were added to a rank sum. Finally, the diseases were sorted by their rank sum. Results: Diseases of the circulatory system account for the highest rank sum. The high public health impact is visible in regard to most criteria, particularly to mortality, hospital discharges, and costs. Diseases of the digestive system rank second mainly because of high ranks for hospital discharges and costs. The third place is assigned to diseases of the musculoskeletal system. Conclusion: A multidimensional ranking procedure has advantages when used for priority setting of diseases. The procedure leads to an overall rank as a summary measure for the public health impact but information for each indicator is still retrieved. Furthermore, the procedure uses ranks and is therefore scale invariant. However, ranking procedures do not lead to a selection of diseases but a rank order. So, there is still a decision rule required to determine which diseases are selected e.g. for in-depth health reporting.},
 keywords = {retirement pension; Bundesrepublik Deutschland; EU; official statistics; Gesundheit; Pension; control; analysis; Gesundheitspolitik; Federal Republic of Germany; multidimensionale Skalierung; ranking; OECD; multidimensional scaling; Indikatorenbildung; health policy; decision making; Daten; EU; monitoring; insurance; WHO; Versicherung; Ranking; observation; Berichterstattung; data; mortality; amtliche Statistik; Beobachtung; Krankheit; Kontrolle; Überwachung; Sterblichkeit; construction of indicators; Entscheidungsfindung; WHO; Analyse; OECD; reporting; health; illness}}