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The validity of readmission rate as a marker of the
quality of hospital care, and a recommendation for its definition
Juliet Rumball-Smith, Phil Hider
The need for quality assessment and improvement in the
health care system has gained increasing significance both internationally and
in New Zealand.1 Numerous criteria exist for
evaluating quality in hospital services, using various indicators, including
readmission rate. This rate reflects the impact hospital care has had on the
patient’s condition up to the point of discharge, and also represents the
efficiency of the service; inpatient hospital care being a primary source of
expense in the health system, and repeated admission representing a potential
source of wasted resources.2
Readmission rate is collected easily by hospital information
systems, and can readily be combined with information from other databases to
assess the potential impact of different variables, and control for
confounders.3 However, there is no agreed
definition of readmission rate in the literature, with researchers and states
employing multiple time periods, and failing to acknowledge subjects who died
following discharge.
MethodsA literature search was undertaken on the Medline
(1966–2008) and Embase (1988–2006) databases. Search terms included:
‘quality of health care’, ‘quality indicators, health
care’, ‘patient readmission’, ‘readmission’,
‘rehospitalisation’, ‘readmit$’, ‘new
zealand’. Searches were limited to English language material and articles
with abstracts available.
DiscussionQuality in health care—Quality in
health care may be defined as ‘the degree to which health services for
individuals and populations increase the likelihood of desired health outcomes
and are consistent with current professional
knowledge’.4p4 Campbell maintains that
quality can be viewed as having two simple domains, suggesting that quality of
care for an individual can be defined as ‘whether individuals can
access the health structures and processes of care which they need, and
whether the care received is
effective’.5
However, the emphasis placed on the quality of health care
by the medical profession, the consumer, and the state, is relatively recent.
Adverse events and incidents of ‘quality failure’ are now widely
publicised. Consumers may have higher expectations of the health care they
receive, and be less trusting of their provider to deliver error-free care.
Health care providers need to account for resources and ensure value and
efficiency of services. Funders also want to ensure that providers are meeting
their expectations, and are performing adequately compared to others.
Readmission rate as an indicator of the quality of
health care—Quality indicators are only one of the tools in the
‘quality toolbox’, but are indispensible in the assessment,
monitoring, and improvement of the quality of patient care. Quality indicators
explored in the literature include hospital multi-stay rate, length of inpatient
stay, hospital mortality rates, and complication
rates.6,7
The Maryland Hospital Association’s Quality Indicator
Project use over 15 measurable, discrete performance indicators upon which value
can be placed to describe quality.7 The wider
international community has embraced the concept of quality monitoring; hospital
accreditation programmes feature in over 36 countries using various indicators
to ensure a minimum standard of quality.8
Readmission rate has been used as a quality indicator in
various psychiatric, surgical and medical clinical
specialties.9–11 It is popular as a
quality indicator amongst researchers and management, for the following
reasons:
Validity
of readmission rate as an indicator of the quality of hospital
care—Are those who are readmitted more likely to have experienced
lower quality care? And conversely, are those who receive substandard care more
likely to be readmitted?
Ashton et al. performed a significant meta-analysis of 29
comparative studies, including both hospital chart and database analyses, and in
each study, process-of-care elements were examined in relation to 31-day
readmission rate. The authors classified the datasets according to these
elements, denoting the quality of care received as being either
‘substandard’, ‘normative’ or ‘exceptional’,
when compared to accepted clinical standards of care.
After review of 13 studies, an odds ratio of readmission of
1.24 (95%CI 0.99–1.57) was calculated for those patients who received
substandard as opposed to normative care. Sixteen studies were assessed to
calculate a summary odds ratio comparing care of relatively low quality
(‘substandard’ and ‘normative’ classification) relative
to care of higher quality (studies classified as ‘exceptional’) was
1.55 (1.25–1.92), representing an increased risk of early readmission of
between 25%–92% for those who experienced lower or normative quality of
care.
This article represents substantial evidence for the
validity of this indicator, yet is limited by the relatively few studies used to
develop the odds ratios. However, this reflects the criteria for inclusion
defined by the authors, such that the studies assessed were ostensibly
homogeneous and provided robust
results.16
Further information can be gained from cohort studies and
case-control studies. Weissman et al reviewed over 1700 admissions in a
case-control study, assessing the rate of 31-day readmission for patients
hospitalised with pneumonia and congestive heart failure in four states of the
US-trained physicians reviewed clinical records and compared the care delivered
to patients subjectively, and against explicit clinical criteria. They
discovered there were ‘significant but relatively small, differences in
initial quality of care between patients who subsequently experienced related
adverse readmissions and those who were not
readmitted’.19p500, findings that were
present after control for demographic and clinical variables, and hospital
characteristics. Ashton also performed a case-control study of over 2000
patients who had diabetes, obstructive lung disease or heart failure, reviewing
quality of inpatient care and 14-day readmission rate.
Chart review was used to ascertain quality of care,
according to specified process-of-care criteria. After adjustment for
demographic variables and clinical severity, they discovered a similar
significant association between substandard care and subsequent unplanned
readmission. This study was conducted within US Veterans Affairs Hospitals, and
as such may not be able to be generalised to patients who experience financial
restrictions in access to hospital
care.20
However, there are few studies that have examined the second
question, the issue of ‘false negatives’ in the calculation of
readmission rate. This proportion represents those that receive substandard
care, but due to other factors (such as death, or recovery) are not readmitted.
This data is very difficult to extract, as they do not enter again into the
hospital recording system, and it may be difficult to access information about
the health of those in the community. Although many studies ignore the
contribution of these false negatives to the validity of the readmission rate,
it must be acknowledged that the validity of the rate has not been proven in
this respect.21
There are other threats to the internal validity of this
rate. Given that the rate is made up of a numerator (those that are readmitted
to hospital within a given time period) and a denominator (total number of
patients discharged alive within a reference period), intervening variables,
confounders, demographic, and clinical factors may impact on both these
figures.
Intervening variables can be defined as those that are
‘interposed in time in the causal sequence between the proposed
independent and dependent
variables’.18p1539 The most significant
intervening variable for readmission rate is death in the community within the
reference period, as a result of substandard care.
The impact of this variable is two-fold. Firstly, these
patients are technically not eligible to be readmitted, so the overall
denominator used to calculate readmission rate is artificially inflated by these
absent subjects. Secondly, a patient that receives substandard care but dies in
hospital or the community, or has a longer initial admission due to this quality
breach, will not change the readmission rate despite substandard
care.13
A confounding factor is defined as ‘a third variable
that indirectly distorts the relationship between two other
variables’.22 The literature discusses
the following confounding factors with regards to readmission rate:
The external validity of a quality indicator
refers to its generalisability; its ability to yield comparable results over
time, and at homogeneous but differing institutions. The public acceptance of
the validity of readmission rate is demonstrated by its broad use. Governments
and private health purchasers such as US company Blue Cross Blue Shield use it
as an indicator of quality.31 The New Zealand
Ministry of Health has recently added readmission rate to its performance
monitoring project.32 However, while these
institutions may use the rate to detail trends over time and monitor progress,
there is limited external validity due to the multiple definitions of
readmission rate employed among institutions and researchers.
Definition of readmission rate‘Readmission’: Chambers and
Clarke define readmission as ‘the next subsequent admission of a patient
as an immediate (that is, emergency or unplanned) admission ... within a defined
interval of a previous (index) discharge taking place within a defined reference
period’.33p301 Ashton and Wray (1996)
recommend obtaining information on the frequency of death after discharge, and
state that the preferable outcome variable is “death at home or
readmission within n days”. If death is the worst possible result of poor
quality care, then those subjects who die within the time period should be
included as part of the readmission indicator. In practice, the number of these
patients is small and may change the overall indicator by a negligible amount
only. However, if they are not included in the analysis then the result may be
biased and produce an indicator that is an under-estimate. Accordingly, it is
advised that the indicator be revised to ‘readmission or deaths’ of
subjects within the specified time period.
Population: The rate is calculated by
dividing the numerator (‘readmissions’) by the ‘corresponding
number of patients discharged (alive) within the reference
period’.33p301
Time period: Researchers in quality have
employed various time periods over which readmission may occur, with intervals
of between 2 weeks and 12 months used.34 As
mentioned above, this variation threatens the external validity of this
indicator, and makes comparison between institutions and populations
difficult.
This author recommends the use of a 30-day time
period:
The
general consensus of the literature seems to be that a one-month time period
provides a logical balance.14 This assumption
is supported by another common indicator used to address inpatient quality,
30-day mortality rate.
ConclusionThis literature appraisal was intended to provide background
information on this indicator, as such this article does not offer the same
quality of information as a systematic review. However, the review notes that
‘readmission rate’ has some demonstrated internal validity and is
widely used in the measurement of the quality of hospital care. It is important
to recognise the limitations of this measure, and minimise the influence of
possible confounding variables by way of methodological and statistical
techniques. Similarly, the adoption of a consistent definition of this rate by
researchers will add to its external validity and improve its generalisability.
This author recommends the use of the following definition: ‘the number of
patients who experienced unintended, acute readmission or death within 30-days
of discharge from the index admission, divided by the total number of patients
discharged alive within the reference period’.
Competing interests: None known.
Author information:
Juliet M L Rumball-Smith, Research Fellow, Department of Public Health
and General Practice, University of Otago, Christchurch; Phil Hider, Senior
Lecturer, Department of Public Health and General Practice, University of Otago,
Christchurch
Correspondence: Dr. Juliet Rumball-Smith,
Research Fellow, Department of Public Health & General Practice, University
of Otago, Christchurch, PO Box 4345, Christchurch, New Zealand. Fax: +64 (0)3
3643697;
email: juliet.rumball-smith@otago.ac.nz Acknowledgements: The author acknowledges
the financial assistance of the Health Research Council of New Zealand and the
New Zealand College of Public Health Medicine; and supervisory support from Dr.
Patrick Graham, University of Otago, Christchurch.
References:
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