Smoking status recording in GP electronic records: the unrealised potential

Vanessa Selak, Susan Wells, Robyn Whittaker, Alistair Stewart

Abstract


Objective To investigate the recording of smoking status and factors associated with the recording of smoking status in general practitioner (GP) electronic medical records (EMRs) in New Zealand, and the suitability of this source as a prevalence measure.
Setting General practices affiliated with an Auckland-based primary health organisation.
Population Patients registered with 84/107 (78.5%) eligible GPs who had used EMRs for at least a year and had PREDICT-CVD,a web-based cardiovascular disease risk assessment and management decision support program, integrated with their practice software.
Design Audit of EMRs using data from an evaluation of PREDICT-CVD.
Main outcome measures The proportion of EMRs audited (Maori, non-Maori) with smoking status
recorded and, among those with smoking status recorded,al so Read-coded, and factors associated with greater recording of smoking status.
Results Smoking status was recorded among 49.6% of Maori and 38.3% of non-Maori prior to the installation of PREDICT-CVD. Among those with smoking status recorded, smoking status was also Read-coded among 49.8% of Maori and 62.3% of non-Maori. Factors associated with greater recording of smoking status were installation of PREDICT-CVD, male sex, Maori ethnicity, cardio-vascular disease and diabetes. Age was also associated with the recording of smoking status.
Conclusion General practitioner electronic medical records in New Zealand are currently not a suitable source of smoking prevalence data, even if manually searched, as a large proportion of records did not have smoking status recorded. Such records are an even less suitable source of smoking prevalence if data extraction by remote querying (using Read codes) is relied upon. The potential to estimate the prevalence of smoking from GP records has not yet become a reality. Installation of electronic decision support systems, such as PREDICT-CVD, could improve the recording and Read-coding of smoking status, and thereby the availability and accessibility of these data.

Keywords


data collection; information systems; primary health care

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DOI: http://dx.doi.org/10.14236/jhi.v14i4.635

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