BACKGROUND: The medical records of patients with cancer need to accurately record diagnoses for professionals to provide quality care. Aims. (i) To develop a methodology which identifies medical records of patients with a cancer diagnosis. (ii) To describe the effectiveness of search strategies to identify all patients in primary care with a cancer diagnosis compared with a diagnosis identified by a Cancer Registry. METHODS: The design of the study was a retrospective analysis of primary care medical records. Five general practices were recruited in the UK. The completeness and correctness of searches were measured and compared both within the practices and compared with a diagnosis identified by a Cancer Registry. RESULTS: One in five of all primary care patients with cancer was not identified when a search for all patients with cancer was conducted using electronic codes for malignancy. One in five patient records with an electronic code for a malignancy that was confirmed by registration with the Cancer Registry actually lacked the necessary documentation to verify the cancer type, date of diagnosis or any other aspect of the malignant condition. Overall, electronic codes for cancer in these medical records have a poor level of completeness (29.4%) and correctness (65.6%) when compared with the Cancer Registry. CONCLUSIONS: The electronic codes in five general practices were not able to identify all patients on the practice lists with a cancer diagnosis. Practices will only be able to comply with guidelines and meet quality targets if they can identify all of their current patients with a cancer diagnosis and will require information from a Cancer Registry in order to do this.
BACKGROUND: The medical records of patients with cancer need to accurately record diagnoses for professionals to provide quality care. Aims. (i) To develop a methodology which identifies medical records of patients with a cancer diagnosis. (ii) To describe the effectiveness of search strategies to identify all patients in primary care with a cancer diagnosis compared with a diagnosis identified by a Cancer Registry. METHODS: The design of the study was a retrospective analysis of primary care medical records. Five general practices were recruited in the UK. The completeness and correctness of searches were measured and compared both within the practices and compared with a diagnosis identified by a Cancer Registry. RESULTS: One in five of all primary care patients with cancer was not identified when a search for all patients with cancer was conducted using electronic codes for malignancy. One in five patient records with an electronic code for a malignancy that was confirmed by registration with the Cancer Registry actually lacked the necessary documentation to verify the cancer type, date of diagnosis or any other aspect of the malignant condition. Overall, electronic codes for cancer in these medical records have a poor level of completeness (29.4%) and correctness (65.6%) when compared with the Cancer Registry. CONCLUSIONS: The electronic codes in five general practices were not able to identify all patients on the practice lists with a cancer diagnosis. Practices will only be able to comply with guidelines and meet quality targets if they can identify all of their current patients with a cancer diagnosis and will require information from a Cancer Registry in order to do this.
Authors: Carriene Roorda; Annette J Berendsen; Feikje Groenhof; Klaas van der Meer; Geertruida H de Bock Journal: Support Care Cancer Date: 2012-10-04 Impact factor: 3.603
Authors: A Rosemary Tate; Alexander G R Martin; Tarita Murray-Thomas; Sarah R Anderson; Jackie A Cassell Journal: BMC Med Res Methodol Date: 2009-06-23 Impact factor: 4.615
Authors: Carriene Roorda; Geertruida H de Bock; Willem Jan van der Veen; Annemarie Lindeman; Liesbeth Jansen; Klaas van der Meer Journal: Support Care Cancer Date: 2011-03-25 Impact factor: 3.603
Authors: Barbara Iyen-Omofoman; Richard B Hubbard; Chris J P Smith; Emily Sparks; Emma Bradley; Alison Bourke; Laila J Tata Journal: BMC Public Health Date: 2011-11-10 Impact factor: 3.295
Authors: Amanda Nicholson; Elizabeth Ford; Kevin A Davies; Helen E Smith; Greta Rait; A Rosemary Tate; Irene Petersen; Jackie Cassell Journal: PLoS One Date: 2013-02-22 Impact factor: 3.240
Authors: Elizabeth Ford; Amanda Nicholson; Rob Koeling; A Tate; John Carroll; Lesley Axelrod; Helen E Smith; Greta Rait; Kevin A Davies; Irene Petersen; Tim Williams; Jackie A Cassell Journal: BMC Med Res Methodol Date: 2013-08-21 Impact factor: 4.615