Derivation of a nomogram to estimate probability of revisit in at-risk older adults discharged from the emergency department
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- Arendts, G., Fitzhardinge, S., Pronk, K. et al. Intern Emerg Med (2013) 8: 249. doi:10.1007/s11739-012-0895-5
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Estimation of the risk of revisit to the emergency department (ED) soon after discharge in the older population may assist discharge planning and targeting of post discharge intervention in high risk patients. In this study we sought to derive a risk prediction calculator for this purpose. In a prospective observational study in two tertiary ED, we conducted a comprehensive assessment of people aged 65 and over, and followed them for a minimum of 28 days post discharge. Cox proportional hazard models relating any unplanned ED revisit in the follow up period to observed risk factors were used to compute a probability nomogram. From 1,439 patients, 189 (13.1 %) had at least one unplanned revisit within 28 days. Revisit probability was weighted towards chronic and difficult to modify risk factors such as depression, malignancy and cognitive impairment. We conclude that the risk of revisit post discharge is calculable using a probability nomogram. However, revisit is largely related to immutable factors reflecting chronic illness burden, and does not necessarily reflect poor ED care during the initial index presentation.
KeywordsEmergency departmentRevisitRisk assessmentDischarge planningAllied health personnel
When an older person is a patient at an emergency department (ED), and is discharged, the risk of revisit to the ED should form part of that discharge decision. Up to 20 % of patients aged 65 and over who are discharged home from the ED will have an unscheduled revisit to the ED within a month . Early revisit post discharge has been identified as a quality indicator of emergency care ; has negative consequences for patient outcomes and hospital occupancy; and is disproportionate in older people . Successful ED care for older people with complex needs should encompass not only management of the acute illness or injury necessitating ED attendance, but successful transition from ED to home . This presents a challenge to the traditional ED model of care, which by its nature is episodic and focussed on the acute presenting problem. An ED visit by an older person may be a sentinel marker of physical, functional and psychosocial decline, and while acute care in this population must be exemplary, high rates of early revisit post discharge could indicate suboptimal recognition of the at-risk patient. It would be especially important for ED care processes if the revisit risk was correlated with features of the acute care received on the first presentation.
With demographic change, the proportion of ED patients that are aged 65 and over is increasing . A number of centres now utilise specialist multidisciplinary geriatric teams within the ED in order to optimise care of older people, though the evidence in support of such teams is variable. Optimal care has many features including accurate diagnosis, recognition of concurrent geriatric syndromes, minimising iatrogenic illness and injury, avoiding unnecessary hospitalisation and organising safe discharge to reduce revisit risk [7–9]. To some extent, the latter two priorities are part of a spectrum of competing interests that presents a great challenge to emergency physicians. The decision to admit or discharge an older person is sometimes finely balanced, and represents a risk–benefit decision where the benefits of avoiding hospitalisation [10, 11] are pitted against the risks of discharge [12, 13].
To this end, a number of tools that enable prediction of discharge risk have been developed as a way of assisting with the discharge decision by identifying patients at increased risk of adverse event post discharge . The derivation of these tools has varied from study to study, but all have been based in part or fully on self reporting questionnaires in a convenience sample of respondents. Although the tools and their use in associated studies have sometimes been used to identify ‘high risk’ patients in a dichotomised fashion, none have been used to apply a risk-probability to an individual patient. If a robust tool could be developed to calculate the risk on any one individual revisiting an ED, it could assist physicians in cases where risk–benefit discharge decisions are being considered.
The aim of this study was to derive a risk probability calculator that could potentially be used to predict return visit risk in at risk older people discharged from the ED.
Variables collected from study patients during assessment
Demographic and acute presentation
Presence of co-morbidities
Allied health assessment
Post discharge referral
Medical services e.g. memory clinic
Hours/week of formal community help
Allied health services e.g. OT home visit
Hours/week of informal community help
Community services e.g. meals on wheels
Ischaemic heart disease
Government/social security services
Triage code in ED
Mode of transport to ED
ED length of stay
ICD10 discharge diagnosis
Number of ED visits in past year
Number of falls in past 6 months
Weight loss in past 6 months
Number of medications
The primary outcome measure was any unplanned ED revisit in the 28 days post discharge. All patients were followed up for a minimum of 28 days through established data processes , and, where necessary, telephone contact. A Cox proportional hazards model relating ED revisit to each of the predictive variables measured (Table 1) was constructed. Variables that were neither statistically significant predictors of revisit nor confounders of other variables were eliminated to reach a final best fit parsimonious model. Testing for interaction terms was conducted. We derived a probability nomogram by weighting individual risk factors on the basis of their hazard ratios estimated by the model, using methods described by Harrell et al. . A p value of 0.05 was used as the threshold for statistical significance. Data analysis was performed using Stata (StataCorp, TX, USA) and R (R Development, Vienna, Austria) software.
Summary of study population on arrival (n = 1,439 patients)
(n, % unless indicated)
Age (mean, SD)
Mode of arrival to ED
Australasian Triage Scale
4/5 (not urgent)
Most common individual presenting problems
Fall with no major injury
Atraumatic joint/back pain
At 28 days, 189 (13.1 %) of patients had made at least one unplanned ED revisit with another 20 (1.4 %) patients dying in the follow-up period. 88 (46.6 %) of revisits were clearly unrelated to the index presenting problem at enrolment, in the remaining cases the revisit was for the same problem or a problem that may have been related to the index attendance. Revisit rates at 3 and 90 days were 4.4 and 23.2 %, respectively.
Any revisit (n = 189)
No revisit (n = 1,250)
Age in years (median)
Non-urgent triage code for index visit
Ambulance transport for index visit
Index ED length of stay in hours (median)
Nil ED attendances in past year
Ischaemic heart disease
Living alone independently
No formal community help
No informal community help
Mobility safe unaided
Nil visual aids
Total urinary continence
Total faecal continence
Moderate to severe cognitive deficit
Nil falls in past 6 months
>5 kg weight loss in past 6 months
6 or more medications
Discharge referral to medical services
Discharge referral to allied health services
Discharge referral to community services
Discharge referral to government services
HR (95 % CI)
In this study of older adults that require comprehensive allied health assessment prior to ED discharge, we have found that the risk of ED revisit within 28 days of discharge is largely related to chronic immutable factors rather than characteristics associated with the index presentation. The implications of this for clinical ED practice are important. ED revisit by an older person may be considered a failure of discharge decision making or planning, but the factors that influence revisit are not strongly related to the acute presenting problem. ED care has a focus on acute illness and injury, but even exemplary initial acute care is unlikely to have a meaningful impact on the risk of revisit in some populations. A different approach is required.
The risk nomogram we have developed allows an estimation of the probability of revisit after discharge. This has some potential benefit over existing risk prediction tools. Knowing the estimated probability, and the factors that are contributing to that probability, could allow a stratified approach to post discharge care. At one end of the spectrum will be patients at low risk (<10 %) of revisit who could be discharged with standard procedures. At the other end, patients whose estimated probability is well in excess of the threshold seen in population based studies (30 % or more) could potentially benefit from closer discharge planning or post discharge intervention by a multidisciplinary service experienced in the care of older people with chronic illness, though the success rate of such programs on ED revisit is mixed [19–21].
The overall rate of 28 day revisit in our study population of 13 % is similar to that found in similar patient cohorts in other jurisdictions [1, 3, 12, 13]. There is no agreed figure for what constitutes an acceptable standard of revisit rate, but rates that are manifestly higher than the 10–25 % range found in the literature should raise alarm. This is where a risk probability calculator offers refinement to clinical practice, so that when a patient is identified who has a risk of revisit that is high, it might support targeted intervention of that patient and the identifiable risks post discharge.
Factors that particularly contribute to an increased probability of revisit in our study show similarities with those risk factors found by other researchers. The TRST tool includes five fields, three of which (polypharmacy, cognitive impairment and a history of recent hospital use) are similar to domains in our nomogram . Similarly the ISAR tool contains six fields, with the same three similar domains to those found in our study . The outcome measure in ISAR is a composite one of death, institutionalisation or functional decline rather than rehospitalisation.
Our study identifies the highest risk of revisit to be associated with patients with depression, which is not a feature of other risk tools. It is increasingly recognised that depression is common in older ED attendees, and that depression is significantly associated with health resource usage.Depression may be associated with social isolation, poor motivation and poor health literacy that may all contribute to contact with ED services. We find moderate cognitive impairment contributes more to risk than either normal cognition or profound impairment, it is possible that the latter is already recognised as having a need for services and support that slightly ameliorates the risk.
We emphasize again that the revisits of some older patients post discharge is inevitable, and does not represent a failure of ED care. As we have shown in this study, the patients at highest risk for revisit are those with factors that may be resistant to intervention, especially any intervention that can be meaningfully undertaken during the typically brief period of ED care.
There are limitations in the applicability of our nomogram. Firstly the nomogram was derived from a population that had already undergone a brief risk screen, and were referred to CCT for comprehensive assessment, in other words it is not necessarily applicable to all older patients being discharged from ED though it is likely that patients negative on a risk screen would also have a low predicted probability of revisit. Secondly, this paper reports the derivation of the nomogram, and it needs validation in a separate population. Thirdly and most importantly, knowing the estimated probability of revisit will not assist clinical practice if we are unable to successfully intervene in those patients at highest risk. Further studies to test whether this is possible are planned http://www.ANZCTR.org.au/ACTRN12612000798864.aspx.
In conclusion, from this large study of prospectively enrolled patients undergoing comprehensive allied health assessment prior to discharge we have developed a nomogram to estimate the probability of early revisit to the ED post discharge in patients aged 65 and over. This has the potential to refine clinical practice and enable targeted intervention of high risk patients in the post discharge period, though both of these assertions need to be tested in future trials.
CCT members at each site provided invaluable assistance with the study. Mr Michael Phillips and Ms Sally Burrows assisted with statistical analysis. The research was funded by a grant from the State Health Research Advisory Council of Western Australia.
Conflict of interest