Frequent attendance at the emergency department is a symptom but not a disease

Mason, Suzanne

doi:10.1136/emermed-2014-203674

Cited by 13 publications

(12 citation statements)

References 15 publications

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“…Significantly, they are not mentioned in either the UK 2010 Drug and Alcohol Strategy (Home Office, 2010) or the 2012 Alcohol Strategy (HM Government, 2012). This dearth of information is compounded by variations in the number of attendances used to define somebody as a ''frequent attender'', with studies adopting 3-12 attendances across different time frames (LaCalle & Rabin, 2010;Mason, 2014). Evidence on whether and how people who frequently attend A&E because of alcohol differ from other sub groups of ''frequent attenders'' -such as those with mental health problems, chronic somatic diseases or medically unexplained symptoms -is also lacking (Scott, Strickland, Warner, & Dawson, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…One potential consequence of having limited information on the characteristics and needs of people who repeated attend A&E is the reification of assumptions and stereotypes about them (LaCalle & Rabin, 2010;Mason, 2014). Stereotypes occur as a consequence of social categorisation; the process whereby a person is seen as a member of a group based on common traits (Stangor, 2000;Tajfel & Forgas, 2000).…”

Section: Introductionmentioning

confidence: 99%

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Socio-demographic characteristics and stereotyping of people who frequently attend accident and emergency departments for alcohol-related reasons: Qualitative study

Neale

Parkman

Day

et al. 2016

Drugs: Education, Prevention and Policy

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Aims: To provide new insights into the socio-demographic characteristics of people who frequently attend Accident and Emergency (A&E) departments for alcohol-related reasons and to explore the findings with reference to stereotyping and prejudice. Methods: Semi-structured qualitative interviews with 30 individuals (18 males; 12 females; aged 20-68 years) recruited from six A&E departments across London, United Kingdom. Participants had all attended A&E 10 times within the last year or 5 times in the last three months for an alcohol-related condition. Detailed data relating to participants' socio-demographic characteristics were systematically coded and analysed. Findings: Participants reported many years of heavy drinking, and high levels of mental and physical ill health, unemployment, dependence on state benefits, housing problems and social isolation. Frequency of A&E attendances varied greatly by participant, patterns of drinking and other substance use were diverse, and the nature and extent of self-reported health and social problems were wide-ranging. Conclusions: Findings suggest that people who regularly attend A&E for alcohol-related reasons collectively experience multiple and complex needs, but individually have diverse patterns of drinking and other problems. Flexible person-centred systems could help to support this patient population, whilst avoidance of terminology that overstates group traits should help to minimise stigma.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Socio-demographic characteristics and stereotyping of people who frequently attend accident and emergency departments for alcohol-related reasons: Qualitative study

Neale

Parkman

Day

et al. 2016

Drugs: Education, Prevention and Policy

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“…There is a risk that frequent callers, once identified by ambulance services, are simply passed to another service10 so that budgetary rather than patient needs are met. As such, it must be remembered that many patients will be frequently calling ambulance services because they are not receiving adequate care, as opposed to calling for vexatious reasons 6.…”

Section: What Does Quality Mean To Frequent Callers?mentioning

confidence: 99%

Delivering clinical case management for frequent callers to ambulance services

Scott

2014

Emerg Med J

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Ambulance services in England are playing an increasing role in the provision of care. Their role has changed from one of picking up patients in the community and dropping them off at an emergency department (ED) to more advanced care models. These now include the provision of clinical advice over the telephone (hear and treat), the treatment of patients on-scene (see and treat) and the more traditional conveyance to the ED.1 These changes have been occurring during a prolonged period of increased demand on all areas of emergency care, including a 47% rise in ED attendance over 15 years.

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“…One aspect of healthcare which is well suited to being examined as a complex system is the use of urgent care [ 17 , 18 ]. Urgent care (emergency department (ED) and primary care out-of-hours (PCOOH) services) represents a relatively open system in which use is driven by patients rather than controlled by the service.…”

Section: Introductionmentioning

confidence: 99%

Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery

Burton

Elliott

Cochran

et al. 2018

BMC Med

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BackgroundThe science of complex systems has been proposed as a way of understanding health services and the demand for them, but there is little quantitative evidence to support this. We analysed patterns of healthcare use in different urgent care settings to see if they showed two characteristic statistical features of complex systems: heavy-tailed distributions (including the inverse power law) and generative burst patterns.MethodsWe conducted three linked studies. In study 1 we analysed the distribution of number of contacts per patient with an urgent care service in two settings: emergency department (ED) and primary care out-of-hours (PCOOH) services. We hypothesised that these distributions should be heavy-tailed (inverse power law or log-normal) in keeping with typical complex systems. In study 2 we analysed the distribution of bursts of contact with urgent care services by individuals: correlated bursts of activity occur in complex systems and represent a mechanism by which overall heavy-tailed distributions arise. In study 3 we replicated the approach of study 1 using data systematically identified from published sources.ResultsStudy 1 involved data from a PCOOH service in Scotland (725,000) adults, 1.1 million contacts) and an ED in New Zealand (60,000 adults, 98,000 contacts). The total number of contacts per individual in each dataset was statistically indistinguishable from an inverse power law (p > 0.05) above 4 contacts for the PCOOH data and 3 contacts for the ED data. Study 2 found the distribution of contact bursts closely followed a heavy-tailed distribution (p < 0.008), indicating the presence of correlated bursts. Study 3 identified data from 17 studies across 8 countries and found distributions similar to study 1 in all of them.ConclusionsUrgent healthcare use displays characteristic statistical features of large complex systems. These studies provide strong quantitative evidence that healthcare services behave as complex systems and have important implications for urgent care. Interventions to manage demand must address drivers for consultation across the whole system: focusing on only the highest users (in the tail of the distribution) will have limited impact on efficiency. Bursts of attendance — and ways to shorten them — represent promising targets for managing demand.

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Frequent attendance at the emergency department is a symptom but not a disease

Cited by 13 publications

References 15 publications

Socio-demographic characteristics and stereotyping of people who frequently attend accident and emergency departments for alcohol-related reasons: Qualitative study

Socio-demographic characteristics and stereotyping of people who frequently attend accident and emergency departments for alcohol-related reasons: Qualitative study

Delivering clinical case management for frequent callers to ambulance services

Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery

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