Readmission rates
BMJ 2013; 347 doi: https://doi.org/10.1136/bmj.f7478 (Published 16 December 2013) Cite this as: BMJ 2013;347:f7478
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Drozda's editorial article on readmission rates is disappointing as there was no mention of the impact of mental health on readmissions, despite established evidence concerning the significant negative impact of co-morbid mental illnesses, such as depression, on morbidity and mortality outcomes in disease such as stroke and myocardial infarction1.
Although the studies were US based, the editorial article relates to the UK and fails to mention the large investment in liaison psychiatry services across the UK following the RAID trial in Birmingham, where it was demonstrated that good liaison psychiatry services reduce both length of admission and readmission rates substantially 2.
Two thirds of older people in acute hospitals are estimated to have delirium, depression or dementia so this is a key area of need. One example of how readmission rates can be reduced can be found at the current time in County Durham and Darlington, where the liaison psychiatry service offers short term follow up at home for such patients to ensure the discharge is sucessful and readmission is avoided.
Part of the problem is that hospital doctors did not, in the Donze paper, record mental health problems as comorbidities, despite the significant impact they have on the physical health of their patients. Unless medicine moves from the mind body dualism concept proposed by Descartes in the 16th centuary, towards an integrative concept of mental and physical health, patients will continue to suffer significant morbidity and mortality unnecessarily.
The editorial concludes with calling for 'additional insights of the type provided by Donze and colleagues to provide the right answers for our patients'. Those insights will not provide the 'right answers' if mental health is not addressed within them.
1.Meijer A, Conradi HJ, Bos EH, Anselmino M, Carney RM, Denollet J, Doyle F, Freedland KE, Grace SL, Hosseini SH, Lane DA, Pilote L, Parakh K, Rafanelli C, Sato H, Steeds RP, Welin C, de Jonge P. Adjusted prognostic association of depression following myocardial infarction with mortality and cardiovascular events: individual patient data meta-analysis.
Br J Psychiatry. 2013 Aug;203(2):90-102
2.George Tadros, Rafik A. Salama, Paul Kingston, Nageen Mustafa, Eliza Johnson, Rachel Pannell, and Mahnaz Hashmi. Impact of an integrated rapid response psychiatric liaison team on quality improvement and cost savings: the Birmingham RAID model. The Psychiatrist Online January 2013 37:4-10
Competing interests: No competing interests
Drozda feels we are "edging slowly to a deeper understanding", but Oliver goes straight to the point - readmission rates can tell us nothing about quality!
Just like referral rates and prescribing rates used as performance indicators, the flawed premise is that rates are related to quality, when manifestly they are not. An average rate can easily conceal the worst quality in practice, but remains the fetish of performance monitors!! Rates are foisted upon us because they are easily obtained. What we really need are measures of appropriate readmission, quality assessments of indicated referral, measures of the value added by prescriptions, and in this readmissions study - measures of whether they achieved better outcomes than the alternatives available at the time!
Wasn't it Einstein who said "What counts doesn't matter, whilst what matters doesn't count"!
Will we ever learn ?
Competing interests: No competing interests
Using readmission as a marker of discharge failure shows unidimensional thought typical of many 'measurements' of quality.
Discharge from hospital should occur when the risks of being in the community (usually exaggerated) are less than those of remaining in hosopital (Usually ignored) and/or the benefits of discharge (often ignored) are greater than the benefits of remaining in hospital (usually overrated). As with all judgements, there is going to be some error.
If readmission becomes yet another stick to beat the medical profession with, and every readmission considered a failure, then doctors will 'play safe.' The obvious way to reduce the readmission rate is by increasing the length of stay. The hospital induced morbidity and negative effects on patients and families of this consequence will remain unmeasured.
I contest that a hospital with no readmissions is needlessy delaying discharge of a large number of patients. It seems sensible to ascertain what figure reflects a suitable balance for these conflicting requirements, likely to be a few percent of all admissions. Having readmission rates above, or equally importantly below, the expected level should precipitate a review of practice.
Competing interests: No competing interests
Editor
Both the articles on re-admission in this edition of BMJ are based on a flawed premise. That is that re-admissions are somehow a marker of the quality of care within the acute hospital. Of course, there are instances where patients are sent home unwell and prematurely or with complications of hospitalisation. But for the most part, re-admissions occur either because:
1. The patient suffers a new illness unrelated to the first admission.
2. They have a long term condition such as cardiac failure or COPD which relapses.
3. The hospital, wanting to respect the patient's wishes to go home rightly accepts a degree of risk (its not as if remaining in a hospital bed is risk free after all).
4. Even carefully made plans for discharge are ignored, bypassed or subverted - by worried relatives, care staff etc.
The notion that somehow hospitals are responsible for the majority of re-admissions is a demonstrable falsehood and the way re-admissions are framed in the articles is a result of the US health insurance industry in which providers can be penalised for "never events" (which re-admissions can never be). They are in reality a feature of how well whole health and social care systems function, the quality of primary care an the help seeking behaviour of the public. But the US spends twice what the UK does as a proportion of GDP on health care, for lower life expectancy, lower equity, higher rates of preventable death, higher health inequality and worse continuity and access to primary care. So what these papers have to teach us is not clear
David Oliver
Competing interests: No competing interests
Re: Readmission rates
Joseph P Drozda Jr’s editorial1 synthesises the findings of two linked studies on readmissions to hospital, and concludes that in spite of valuable studies such as these ‘our understanding of the causes of readmissions …… remains rudimentary’.
Both studies were carried out in the US, but this is not a uniquely American problem and it is important that we address these questions in the UK. Financial penalties for 30-day readmissions were proposed in the UK in 2010 and existing models that aimed to predict readmission within a year were revised to predict readmission within 30 days.2 The UK population is ageing and it is essential that the drivers of hospital admission and readmission are understood. This will only be achieved if further research on hospital admissions focuses on patients and their individual level risk factors: Drozda reminds us that ‘patients are readmitted and not diagnoses’.
The NHS routinely collects Hospital Episode Statistics (HES) and it is clear that admission and readmission rates both rise with age3;4. However these routine data do not allow investigation of what happens to individual patients - needed if the causes of admission and readmission are to be fully understood. The UK does however have a rich resource of cohort studies involving older people with detailed characterisation. We have therefore exploited data linkage technology to bring together data from the Hertfordshire Cohort Study (HCS)5 with HES data to identify the causes of admissions and readmissions among older people in the UK
The data comprise a comprehensive baseline (1999-2004) summary of the social, lifestyle and clinical status of 2997 community-dwelling men (n=1579) and women (n=1418) aged 59–73, routinely collected information about each hospital admission they experienced during the following decade and the date and cause of death for the 275 people who died.6
Our study has many strengths. First, admissions histories can be dovetailed with mortality records; Donzé et al7 do not appear to have considered deaths. Secondly, our database includes men and women who did not experience admission during follow-up; they are an important control group for comparison with individuals who did. Thirdly, a wide range of baseline data was collected prospectively by a team of research nurses and doctors according to strict research measurement protocols. Such data are not available from routine sources.
In response to Drozda Jr’s editorial we have conducted a preliminary analysis of readmissions among the men and women. We defined three binary outcome variables to classify whether or not a study participant was: ‘ever admitted or died’; ‘ever readmitted within 30 days or died’ and ‘ever readmitted as an emergency within 30 days or died’. We describe these variables and their associations with burden of co-morbidity at baseline as indicated by the number of systems medicated (identified by coding all prescription and over-the-counter medications taken by study participants according to the British National Formulary).
The cohort accumulated 8741 admissions during the follow-up period, although 829 individuals experienced none. The table shows that 1198 (75.9%) men and 989 (69.7%) women were ‘ever admitted or died’. 458 (29.0%) men and 289 (20.4%) women were ‘ever readmitted within 30 days or died’, of whom 313 men and 180 women were readmitted as emergencies.
The table shows that greater baseline burden of co-morbidity was strongly associated with higher proportions of men and women experiencing hospital admission; readmission within 30 days; and emergency readmission within 30 days, or death. For example, 48% of men and 45% of women who had four or more systems medicated experienced a readmission within 30 days or died; only 21% of men and 13% of women who had no systems medicated went on to experience a readmission within 30 days or death.
These simple analyses confirm the substantial burden of hospital admission and readmission even among young-old community-dwelling men and women. Moreover, they demonstrate the potential of the HCS database to identify important patient-level characteristics that are predictive of admission and readmission and to suggest avenues for intervention to reduce hospital admissions and improve care.
Drozda Jr has called for additional insights into the drivers of hospital readmission; using the wealth of data available in the HCS study we intend to provide them.
References
(1) Drozda Jr JP. Readmission rates. BMJ 2013;347:f7478.
(2) Billings J, Blunt I, Steventon A, Georghiou T, Lewis G, Bardsley M. Development of a predictive model to identify inpatients at risk of re-admission within 30 days of discharge. BMJ Open 2012;00:e001667.
(3) Office for National Statistics. General Lifestyle Survey - Health tables 2009 Table 7.28 Trends in inpatient stays in the 12 months before interview by sex and age, 1982 to 2009. 2011.
(4) Robinson P. Hospital readmissions and the 30 day threshold. 2010. CHKS.
(5) Syddall HE, Aihie Sayer A, Dennison EM, Martin HJ, Barker DJP, Cooper C. Cohort Profile: The Hertfordshire Cohort Study. Int J Epidemiol 2005:34,1234-1242.
(6) Simmonds SJ, Syddall HE, Walsh B, Evandrou M, Dennison EM, Cooper C et al. Understanding NHS hospital admissions in England: linkage of Hospital Episode Statistics to the Hertfordshire Cohort Study. Age Ageing. In press 2014.
(7) Donze J, Lipsitz S, Bates DW, Schnipper JL. Causes and patterns of readmissions in patients with common comorbidities: retrospective cohort study. BMJ 2013;347:f7171.
Competing interests: No competing interests