INTRODUCTION: On-time identification of incident cancer patients is important in cancer research to ensure quality in cancer treatment and care. Nevertheless, the Danish Cancer Registry (DCR) is updated on an annual basis rather than continuously, and no standardised algorithm exists to enable sampling from administrative data which are updated on a monthly basis. The aim of this study was to develop and validate an algorithm for on-time sampling of incident cancer patients based on administrative data. MATERIAL AND METHODS: The study was based on registry and questionnaire data from incident cancer patients' general practitioners (GPs). An algorithm for on-time sampling of incident cancer patients was developed and validated in 2008 (12,747 patients) and further developed and validated in 2010 (7,996 patients). Questionnaire data from the GPs and data from the DCR were used as gold standards. The completeness over time of the 2010 cohort was evaluated. RESULTS: Further development of the 2008 algorithm into the 2010 algorithm increased its positive predictive value (PPV) to 95.0%. The PPV of a patient from the 2010 cohort being registered in the DCR was 97.4%. The 2010 algorithm displayed a completeness of 60% in the first month and 95% after four months. CONCLUSION: A valid and cost-saving algorithm for on-time sampling of incident cancer patients has been developed with great potential for research and quality assurance. FUNDING: This work was funded by the Danish Cancer Society and the Novo Nordisk Foundation. TRIAL REGISTRATION: not relevant.
INTRODUCTION: On-time identification of incident cancerpatients is important in cancer research to ensure quality in cancer treatment and care. Nevertheless, the Danish Cancer Registry (DCR) is updated on an annual basis rather than continuously, and no standardised algorithm exists to enable sampling from administrative data which are updated on a monthly basis. The aim of this study was to develop and validate an algorithm for on-time sampling of incident cancerpatients based on administrative data. MATERIAL AND METHODS: The study was based on registry and questionnaire data from incident cancerpatients' general practitioners (GPs). An algorithm for on-time sampling of incident cancerpatients was developed and validated in 2008 (12,747 patients) and further developed and validated in 2010 (7,996 patients). Questionnaire data from the GPs and data from the DCR were used as gold standards. The completeness over time of the 2010 cohort was evaluated. RESULTS: Further development of the 2008 algorithm into the 2010 algorithm increased its positive predictive value (PPV) to 95.0%. The PPV of a patient from the 2010 cohort being registered in the DCR was 97.4%. The 2010 algorithm displayed a completeness of 60% in the first month and 95% after four months. CONCLUSION: A valid and cost-saving algorithm for on-time sampling of incident cancerpatients has been developed with great potential for research and quality assurance. FUNDING: This work was funded by the Danish Cancer Society and the Novo Nordisk Foundation. TRIAL REGISTRATION: not relevant.
Authors: Henry Jensen; Marie Louise Tørring; Frede Olesen; Jens Overgaard; Morten Fenger-Grøn; Peter Vedsted Journal: BMC Cancer Date: 2015-04-23 Impact factor: 4.430
Authors: Louise Mahncke Guldbrandt; Morten Fenger-Grøn; Torben Riis Rasmussen; Henry Jensen; Peter Vedsted Journal: BMC Health Serv Res Date: 2015-01-22 Impact factor: 2.655
Authors: Louise Mahncke Guldbrandt; Morten Fenger-Grøn; Torben Riis Rasmussen; Finn Rasmussen; Peter Meldgaard; Peter Vedsted Journal: BMC Cancer Date: 2015-11-25 Impact factor: 4.430
Authors: Christiane Rudolph; Gitte Stentebjerg Petersen; Ron Pritzkuleit; Hans Storm; Alexander Katalinic Journal: BMC Health Serv Res Date: 2019-11-01 Impact factor: 2.655