Literature DB >> 23972194

Adverse events recorded in English primary care: observational study using the General Practice Research Database.

Carmen Tsang1, Alex Bottle, Azeem Majeed, Paul Aylin.   

Abstract

BACKGROUND: More accurate and recent estimates of adverse events in primary care are necessary to assign resources for improvement of patient safety, while predictors must be identified to ameliorate patient risk. AIM: To determine the incidence of recorded iatrogenic harm in general practice and identify risk factors for these adverse events. DESIGN AND
SETTING: Cross-sectional sample of 74,763 patients at 457 English general practices between 1 January 1999 and 31 December 2008, obtained from the General Practice Research Database.
METHOD: Patient age at study entry, sex, ethnicity, deprivation, practice region, duration registered at practice, continuity of care, comorbidities, and health service use were extracted from the data. Adverse events were defined by Read Codes for complications of care (Chapters S, T, and U). Crude and adjusted analyses were performed by Poisson regression, using generalised estimating equations.
RESULTS: The incidence was 6.0 adverse events per 1000 person-years (95% confidence interval [CI] = 5.74 to 6.27), equivalent to eight adverse events per 10,000 consultations (n = 2,540,877). After adjustment, patients aged 65-84 years (risk ratio [RR] = 5.62, 95% CI = 4.58 to 6.91; P<0.001), with the most consultations (RR = 2.14, 95% CI = 1.60 to 2.86; P<0.001), five or more emergency admissions (RR = 2.08, 95% CI = 1.66 to 2.60; P<0.001), or the most diseases according to expanded diagnosis clusters (RR = 8.46, 95% CI = 5.68 to 12.6; P<0.001) were at greater risk of adverse events. Patients registered at their practice for the longest periods of time were less at risk of an adverse event (RR = 0.40, 95% CI = 0.35 to 0.47; P<0.001).
CONCLUSION: The low incidence of recorded adverse events is comparable with other studies. Temporal sequencing of risk factors and case ascertainment would benefit from data triangulation. Future studies may explore whether first adverse events predict future incidents.

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Year:  2013        PMID: 23972194      PMCID: PMC3722830          DOI: 10.3399/bjgp13X670660

Source DB:  PubMed          Journal:  Br J Gen Pract        ISSN: 0960-1643            Impact factor:   5.386


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