AIMS: Clinical databases are regularly used for audit and research purposes. The accuracy of data input is critical to the value of these tools, but little is known about the factors which influence the completeness of data recording. The aim of this study was to evaluate the influences affecting completeness of data recording in computerized clinical databases of cancer treatment. METHODS: Data omission rates in three databases dealing with management of breast, colorectal and gastro-oesophageal cancers were calculated. The effects of (a) type of record; (b) nature of data and (c) training required to interpret data were evaluated by univariate and multivariate analyses. RESULTS: The overall data omission rate was 21.9% (upper GI 27.6%, breast 19.6%, colorectal 32.7%, P=0.13). For different categories of data, omission rates varied from 0% to 55%. Fields requiring a 'text field' or 'numerical' entry, or containing demographic data, data required for the process of care or data which required no interpretation were associated with low omission rates. Clinical data, and fields requiring a 'yes/no' response were associated with high omission rates (45 and 48% respectively). Clinical data and data relating to patient demographic details were independently associated with high and low omission rates respectively (odds ratios for significant missing data 86.9 and 1 respectively). CONCLUSION: Clinical data are poorly captured by current cancer surgery databases. Reasons for the poor completion of fields requiring input by clinical staff, particularly availability of time and training, and prioritization of work, should be addressed. Re-design of databases to ensure that data entry is simple and unambiguous may improve accuracy.
AIMS: Clinical databases are regularly used for audit and research purposes. The accuracy of data input is critical to the value of these tools, but little is known about the factors which influence the completeness of data recording. The aim of this study was to evaluate the influences affecting completeness of data recording in computerized clinical databases of cancer treatment. METHODS: Data omission rates in three databases dealing with management of breast, colorectal and gastro-oesophageal cancers were calculated. The effects of (a) type of record; (b) nature of data and (c) training required to interpret data were evaluated by univariate and multivariate analyses. RESULTS: The overall data omission rate was 21.9% (upper GI 27.6%, breast 19.6%, colorectal 32.7%, P=0.13). For different categories of data, omission rates varied from 0% to 55%. Fields requiring a 'text field' or 'numerical' entry, or containing demographic data, data required for the process of care or data which required no interpretation were associated with low omission rates. Clinical data, and fields requiring a 'yes/no' response were associated with high omission rates (45 and 48% respectively). Clinical data and data relating to patient demographic details were independently associated with high and low omission rates respectively (odds ratios for significant missing data 86.9 and 1 respectively). CONCLUSION: Clinical data are poorly captured by current cancer surgery databases. Reasons for the poor completion of fields requiring input by clinical staff, particularly availability of time and training, and prioritization of work, should be addressed. Re-design of databases to ensure that data entry is simple and unambiguous may improve accuracy.
Authors: Kristen M J Azar; Maria R Moreno; Eric C Wong; Jessica J Shin; Christy Soto; Latha P Palaniappan Journal: Health Serv Res Date: 2011-08-24 Impact factor: 3.402
Authors: Matthew K H Hong; Henry H I Yao; John S Pedersen; Justin S Peters; Anthony J Costello; Declan G Murphy; Christopher M Hovens; Niall M Corcoran Journal: BMJ Open Date: 2013-05-28 Impact factor: 2.692
Authors: Ali S Afshar; Yijun Li; Zixu Chen; Yuxuan Chen; Jae Hun Lee; Darius Irani; Aidan Crank; Digvijay Singh; Michael Kanter; Nauder Faraday; Hadi Kharrazi Journal: JAMIA Open Date: 2021-08-02