BACKGROUND: Although the majority of patient contact within the UK's National Health Service (NHS) occurs in primary care, relatively little is known about the safety of care in this setting compared to the safety of hospital care. Measurement methods to detect iatrogenic diseases in primary care require extensive development. Routinely collected data have been successfully applied to develop patient safety indicators in secondary care. Given the availability of electronic health data in primary care, we explored the potential to build adverse event screening tools using computerised medical record systems. OBJECTIVE: To identify the rate and types of adverse events that might be recorded in primary care through routinely collected data. The findings will inform the development of administrative data-based indicators to screen for patient harm arising from primary care contact. METHOD: Descriptive analyses were performed on data extracted from the clinical information management systems (CIMS) at NHS Brent. The data were explored according to age, sex and ethnicity of patients. Potential or actual adverse events were identified by mapping to three Read code chapters. RESULTS: Records from the calendar year 2007 were available for 69 682 registered patients from 25 practices, consisting of 680 866 consultations. A number of adverse events could be detected through terms contained in certain chapters of the Read code system. These events include injuries due to surgical and medical care (0.72 cases of per 1000 consultations) and adverse drug reactions (1.26 reactions per 1000 consultations). Patterns in the rate of harm among patients from different ethnic groups tended to reflect the proportion of the respective groups in the overall Brent population, with more injuries occurring among patients of white and Asian ethnicities. CONCLUSION: These findings suggest that there is scope to develop more accurate and reliable means of safety surveillance in general practice using data obtained from electronic patient records.
BACKGROUND: Although the majority of patient contact within the UK's National Health Service (NHS) occurs in primary care, relatively little is known about the safety of care in this setting compared to the safety of hospital care. Measurement methods to detect iatrogenic diseases in primary care require extensive development. Routinely collected data have been successfully applied to develop patient safety indicators in secondary care. Given the availability of electronic health data in primary care, we explored the potential to build adverse event screening tools using computerised medical record systems. OBJECTIVE: To identify the rate and types of adverse events that might be recorded in primary care through routinely collected data. The findings will inform the development of administrative data-based indicators to screen for patient harm arising from primary care contact. METHOD: Descriptive analyses were performed on data extracted from the clinical information management systems (CIMS) at NHS Brent. The data were explored according to age, sex and ethnicity of patients. Potential or actual adverse events were identified by mapping to three Read code chapters. RESULTS: Records from the calendar year 2007 were available for 69 682 registered patients from 25 practices, consisting of 680 866 consultations. A number of adverse events could be detected through terms contained in certain chapters of the Read code system. These events include injuries due to surgical and medical care (0.72 cases of per 1000 consultations) and adverse drug reactions (1.26 reactions per 1000 consultations). Patterns in the rate of harm among patients from different ethnic groups tended to reflect the proportion of the respective groups in the overall Brent population, with more injuries occurring among patients of white and Asian ethnicities. CONCLUSION: These findings suggest that there is scope to develop more accurate and reliable means of safety surveillance in general practice using data obtained from electronic patient records.
Authors: Widya N Insani; Cate Whittlesea; Hassan Alwafi; Kenneth K C Man; Sarah Chapman; Li Wei Journal: PLoS One Date: 2021-05-26 Impact factor: 3.240