Skip to main content

Low rate of adverse events recorded in English primary care

A study by Dr Carmen Tsang and colleagues at Imperial College London has found a low incidence of patient safety incidents recorded in general practice. The research, which was published by the British Journal of General Practice, measured the extent of patient safety incidents recorded in 74 763 patients at 457 English general practices between 1999 and 2008, and the patient characteristics associated with these adverse events.

Older patients, those with more comorbid diseases or who had more previous emergency admissions to hospital were at greater risk of complications of care. Dr Carmen Tsang, lead author of the paper, says “Our finding of a low incidence of patient harm in general practice supports previously published studies. To better understand these adverse events, we must also examine the healthcare interactions from which they originate, and consider how to reduce the incidents that are potentially preventable”.

Outcomes following adverse events, including emergency admissions and death, are important because they may be preventable. The low rate of recording of adverse events in primary care may reflect under-recording of safety incidents occurring in this setting. Routine recording of adverse events, may be less frequent and less precise than recording of chronic diseases. The reasons for the low rate of adverse events detected needs to be better understood, particularly if this rate is an under-estimation of the true extent of iatrogenic patient harm in primary care.

Comments

Popular posts from this blog

What is the difference between primordial prevention and primary prevention?

Primordial prevention and primary prevention are both crucial strategies for promoting health, but they operate at different levels. Primordial prevention aims to address the root causes of health problems and improve the wider determinants of health. It focuses on preventing the emergence of risk factors in the first place by tackling the underlying social, economic, and environmental determinants of health. This involves broad, population-wide interventions such as: Policies that promote healthy food choices: Think about initiatives like taxing sugary drinks to discourage unhealthy consumption, or providing subsidies for fruits and vegetables to make them more accessible. Urban planning that prioritises well-being: This could include creating walkable neighborhoods with safe cycling routes, ensuring access to green spaces for recreation and relaxation, and designing communities that foster social connections. Social programs that address inequality: Initiatives aimed at reducing pov...

UK Covid-19 Inquiry - The Importance of a Strong Primary Healthcare System

In my witness statement for Module 10 of the UK Covid-19 Inquiry, I discuss the pandemic's impact through from the perspectives of  primary care and public health, drawing on my extensive experience as a senior academic at Imperial College London and as a practising GP and NHS Public Health Specialist.  I emphasise that the pandemic disproportionately affected people who were clinically vulnerable, the disabled, ethnic minority communities and those living in deprived areas. The pandemic highlighted how structural inequalities, multigenerational housing, and employment in high-risk frontline roles exacerbated health disparities.  My statement also critiques the weakening of public health infrastructure - particularly for the control of infectious diseases - and the lack of integrated health data systems to identify at-risk groups such as the clinically vulnerable. I also advocated for a more robust preventive healthcare model that prioritises community-based primary care ...

Relevance Over Recall: Rethinking How AI Uses Clinical Data

Our article in the Journal of the Royal Society of Medicine argues that safe and effective AI in healthcare must incorporate mechanisms that emulate human judgement - down-weighting old, inaccurate or superseded information and prioritising what is recent, clinically relevant and reaffirmed - so that AI supports, rather than disrupts, high-quality patient care.  Clinicians constantly revise, reinterpret and filter past information so that only what is relevant, accurate and timely shapes present-day management decisions; medical records function as dynamic “working tools” rather than fixed archives. By contrast, many AI systems lack this capacity for selective forgetting and often treat all historical data as equally meaningful.  This can lead to outdated or low-confidence diagnoses being repeatedly resurfaced, persistent labels influencing clinical expectations, and irrelevant, long-resolved events cluttering summaries and decision-support outputs. Such indiscriminate recall...