Vivek Punjabi University of Missouri September 2014

Abstract
Background: Re-admissions back to the ICU is a growing problem in the United States which is of concern especially since these patients have higher in hospital mortality rates as well as longer inpatient length of stays. The objective of this study is to measure the incidence and determine the predictors of re-admissions to the Adult Intensive Care Unit.

Methods: Medline (1946-present) was searched using combinations of the following search terms ‘Intensive Care Units’ OR ’Critical Care’ AND ‘Patient re-admissions’. The searches were limited to abstracts in English language between 1990 and 2014. This search was then narrowed to ‘core clinical journals’ to increase the quality of the articles but this limitation cut the number of articles down to 2/3rd and even though these articles were saved under a separate folder, eventually all 91 articles were included in the final search. The term ‘Intensive Care Units’ were narrowed to include only ‘burn’, ‘coronary’ and ‘respiratory’ care units. The CINAHL and Cochrane Database search failed to reveal any relevant results.

Results: My search generated 33 articles and their review shed light on a few recurrent themes identified as being the reason for early re-admissions. Premature discharge, time gaps between reaching the wards and being seen, lack of attention by ward nurses, lack of experience of medical staff in the wards were some of the themes identified.

Conclusions: For a patient, coming back to the ICU is always a cause of concern for physicians, patients as well as their families. After reviewing a significant number of studies, we can see how certain factors have linear and non-linear relationships with readmissions to the ICU. We need more comprehensive studies to further determine ways to reduce these readmissions. In our review, ICU readmissions have not found to be a viable quality indicator of a hospital’s overall performance.

Keywords: Intensive Care Units, patient readmission, critical care

Introduction: Intensive Care Units are powerhouses of the hospitals accounting for anywhere between 25-40% of total expenditure of the hospitals while making up only 7-8% of total hospital beds. With advancing technology and the longer life expectancies of the elderly in a developed country like the United States, the utilization of Intensive Care beds has been at an all-time high. To add to this conundrum, there is increasing pressure being mounted by government-run and other managed care companies to discharge patients quicker from the ICU. Sometimes this leads to unsafe and untimely discharges leading to patient’s ‘bouncing back’ to the Intensive Care Unit within the course of the same admission. Some authors have named this the ‘quicker and sicker’ method of rushing patients out. In prior studies, many patient related characteristics including severity of illness, co morbidities, age etc. have been used to predict who will be re-admitted to the ICU. In addition, structural and workload factors such as patient census, number of open beds, demand for new beds to accommodate the inflow of patients etc. may also play a pivotal role in determining aggressiveness of discharges from the Intensive Care Units. Even though some re-admissions may occur due to reasons which could never have been anticipated, most readmissions are thought to have been avoidable. Since re-admitted patient’s come back sicker than they left, these readmissions lead to significant added expenses to the hospital and insurance companies. Hence, avoiding re-admissions to the Intensive Care Units may represent a useful quality indicator around which to target programs and interventions in an effort to improve overall hospital performance. By conducting this systematic review, we’re looking to determine the rates of re-admission to the ICU within the same hospital stay and determine factors leading to higher incidences of these as well as probable solutions tried at various institutions to deal with this problem. By analyzing what has been done, we hope to create our own alternative solution to this looming issue.

Methods
Data Sources:
Medline (1946-2014) was searched using combinations of the following search terms ‘Intensive Care Units’ OR ’Critical Care’ AND ‘Patient re-admissions’. The searches were limited to abstracts in English language between 1990 and 2014. This search was then narrowed to ‘core clinical journals’ to increase the quality of the articles but this limitation cut the number of articles down to 2/3rd and even though these articles were saved under a separate folder, eventually all 91 articles were included in the final search. The term ‘Intensive Care Units’ was narrowed to include only ‘burn’, ‘coronary’ and ‘respiratory’ care units. The CINAHL database was also searched to exclude the articles in MEDLINE and no search results relevant to the topic were found. Similarly, a Cochrane Database search failed to reveal any relevant results. Study Selection and Data Extraction
The abstracts of all 91 articles were reviewed and 38 articles were shortlisted to include only those studies that discussed re-admission to the Adult (Medical or Surgical) Intensive Care Units during the same hospital admission. In the initial short listing process, randomized control trials and retrospective chart review trials were included. The articles which were based solely on opinions were excluded. The studies that focused on only specific specialty patients were excluded and only those which studied the concept of a general ‘Intensive Care Unit’ were shortlisted. Amongst the shortlisted, five articles were further discarded either because they had poorly conducted research design or because they were done in foreign countries whose model could not be replicated in the USA. The remaining 33 articles were then sorted into 2 categories, firstly those that looked at re-admission rates and the probable cause and effect of re-admissions to the ICU and secondly those that looked at interventions to prevent or reduce these re-admissions. These two are not mutually exclusive.
Results
Study Selection
This author evaluated 33 studies for this systematic review, 27 of which looked at rates of re-admissions to the adult Intensive Care Units and tried to point out factors associated with these re-admissions. There were 19 studies which either proved or suggested interventions which may be useful in reducing the incidence of these re-admissions. Out of the studies analyzed, 15 were prospective studies, 2 were meta-analyses, 1 was a literature review and the remaining 15 were retrospective chart review cohort or case control studies.

Overall the systematic review, meta-analysis, prospective and retrospective studies scored between good to moderate on the quality assessment scale. The articles all rated between 1 to 3 when using the Agency for Health Care Policy and Research Evidence rating scale. When using the USPSTF scale, the level was evidence was I, II-1 or II-2, which indicate a good to decent level of evidence.

Incidence of re-admissions to the ICU:
Out of 27 studies that measured incidence rates of readmissions to their ICU, 23 of them defined ‘readmission’ as ‘re-entry to the ICU during the same hospital admission’, 3 of the studies used ‘re-entry within 72 hours of initial discharge’ and the remaining one study used defined it as ‘re-entry to the ICU within 48 hours of initial discharge’(2).

Incidence Rates:
The incidence of re-admissions to the ICU was in the range of 4-9% with an average of 5.6% when we used ‘same admission stay’ criteria. The same percentage went down as expected when the 72 and 48 hour criteria were used. These numbers were in range of 3.1-5.4% and 2.5-3.5% respectively and accounted for 20-30% of all ICU re-admissions. (12)
The studies above compared the number of readmitted patients to the group of at-risk patients who survive to first ICU discharge leaving out patients who died after they left the ICU. This was done in most studies so as not to increase the incidence of re-admissions by avoiding the recounting of patients who had more than one readmission.

Important Findings:
Patients were readmitted to the ICU either due to the same reason as the initial admit or secondary to a new clinical issue. New problems made up anywhere between 19-56% of readmissions while 34-52% of patients bounced back with the same original problem (12).

The most common reasons for being readmitted with the same initial diagnosis were related to pulmonary problems including pulmonary edema, aspiration pneumonia and inability to clear secretions effectively(8,10,12,24,25). Aspiration pneumonitis, pulmonary edema from cardiogenic or other causes and inadequate pulmonary toilet that developed on the general wards post ICU discharge were the main culprits. (12,24)
Patients who were discharged soon after extubation have had a higher incidence of returning to the ICU compared to controls that stayed longer in the ICU longer than 48 hours post extubation.
In the same above study, airway colonization with resistant organisms was also more prevalent in the readmitted group. The authors thought that the deleterious systemic effects of these infectious agents on the respiratory muscles could play a role in patients coming back to the ICU with respiratory distress. Lastly, this study showed that weakness and depression were the most common prevailing subjective finding in the readmitted group. However they were not able to predict whether the weakness was the same as during initial discharge or was it a new weakness due to some other new medical problem. It has however been proven that objective (and not subjective) weakness due to neuromuscular diseases and Critical illness neuro-myopathies lead to chronic diaphragmatic weakness which eventually leads to respiratory muscle fatigue, poor cough and clearance of secretions and eventually, readmission to the ICU. (3)

Another study found that patients who received sedation 24-48 hours prior to discharge and those who were malnourished (based on albumin and creatinine numbers) were at a higher risk of readmission (6)

Patients who were readmitted with a new problem came back in with mostly Gastrointestinal (bleeding from GI tract and bowel obstruction being the most common issues), Pulmonary and Cardiogenic (Acute MI, CHF exacerbation being the most common) problems. Other reasons included new or recurrent sepsis, accidental drug toxicities, acute encephalopathy, metabolic, electrolyte and renal issues.
Planned readmissions to the ICU such as those needed for pre or post-operative management were accounted for my most studies and omitted for accuracy reasons. One study (12) calculated this as 5-14% of all re-admissions to the ICU.

Patients who were re-admitted, not surprisingly performed much higher on severity of illness scores on readmission as compared to the same scores on initial admission. Most studies also found that they had longer length of ICU stays the second time around as compared to the first in 78% of cases. However one study found that the initial stay was 0.7% longer than the subsequent in their ICU (1, 12).
A Brazilian prospective study, using multiple regression analysis showed that higher Nursing Activities Score, Simplified Acute Physiology Score II and Logistic Organ Dysfunction Score were correlated with longer length of stays and when these patients were sent out despite of this, their chance of readmission was higher (16) [Note: The NAS is a tool to measure nursing workload ICU and the author of this study (16) mentions it to be twice as effective in measuring how nurses spend their time caring for critically ill patients than the TISS-28 which is another score primarily used in the European countries)

A few studies also looked at specific physiological, clinical and lab values that were most associated with higher degree of re-admission. These included, at discharge from the ICU, the presence of fever, PaO2 60mmHg, elevated respiratory rate>24breaths/min elevated heart rate > 104beats/min, age>65years, hematocrit 65
• More than two co-morbidities
• No mobilization in intensive care

None of these were statistically proven to accurately predict readmissions in these studies.

Longer initial ICU stays also put the patients at risk of nosocomial infections, lack of sleep, increased time spent on bed rest rather than moving around, worsening risk of encephalopathy and deep vein thrombosis. (1,12,14 ).

When looking at case-mix, medical ICUs (MICU) had higher number of readmissions than surgical Intensive Care Units (SICU)(12). When looking at hospital length of stay (LOS) parameters, readmitted patients had twice as long LOS as non- readmitted ones (1, 2).

One hospital started a targeted intervention program which included a focused transfer phone call to the accepting physician/nurses, charted care summaries and discharge checklists before a patient’s ICU discharge. These researchers (11) reported a favorable outcome with this intervention with reduced rate of readmission in their Surgical ICU.

Premature Discharges
Some studies speculate that the percentage of patient’s being readmitted within 24 hours of discharge with the same initial diagnosis could be a marker indicating a premature discharge. This number was between 20-30% re-admissions in studies (12)

Mortality
The risk of mortality was between 2-10 times higher in the re-admitted population compared to those discharged but not readmitted. However, when adjusted for illness severity, this number was found to still be 6-7 times higher in the readmitted group. These 2 studies (2,12) found that the patients readmitted with a new diagnosis had a higher mortality than those readmitted with the same initial diagnosis while other studies(22) found the exact opposite with same diagnosis being responsible for 54% and new diagnosis responsible for 35% of readmissions.
Despite many studies hinting at it, this review article did not find any direct or indirect connection between ICU readmissions and severity adjusted hospital mortality rates.
Finally, in one study (2), there was neither a direct nor indirect association between ICU readmission rate and severity-adjusted hospital mortality and length of stay during the initial ICU admission.
Time of Day/Week:
Some studies found a minor increase in the odds ratio of readmissions during the 6pm-6am period(2, 19) while some found that time of day of discharge form the ICU has no effect on readmission rates.
Another study(5,6) found that discharging patients over the weekend compared to the weekday had no effect on ICU readmissions.

Teaching Vs Non-Teaching
In one study(15) teaching and community hospitals had different rates of admissions with teaching hospitals generally performing worse than the latter (p = .001). In the case of non-teaching/community institutions, more readmissions were secondary to recurrence of the initial disease (56%) than to new complications (26%) when compared with readmission to teaching hospitals (39% and 50%, respectively).(15)

ICU Readmissions as a quality indicator :
The Society of Critical Care Medicine (SCCM) has recommended that ICU Readmission rates be used as a quality measure to assess optimal functioning of the ICU and thus the hospital as a whole(12). However there have been no good studies which prove that readmissions result from a poor quality of initial care or from pre-mature ICU discharge.
The study done by Cooper et al (1) surmised that ICU readmission did not correlate well as a quality indicator because when adjusted and non-adjusted readmission rates were looked at across a range of hospitals, the variation between the two rates were not significant enough.
Another study (12) looked at patients discharged from the hospital and re-admitted within 48 hours and found that unplanned hospital readmission may be an indicator for poor quality of care only when applied to specific medical and surgical diagnoses and not as a general measure of the overall quality of the hospital.

Discussion

The process of discharge making from the Intensive Care Unit has never been given much thought since, traditionally, physicians always discharge patients once they get better and once its determined that they can receive the same current level of care on the wards as they have been in the ICU. Patient or their family’s preference is rarely taken into consideration and even nursing and other ancillary staff have minimal say in who gets to stay and who leaves.

Major Findings:

The primary reason for conducting this study was to assess whether we can somewhat accurately pinpoint the primary reasons for ICU readmissions. Most studies found that it was the discharge acute physiology score (APS) and not the admission APS neither the difference between the admission and discharge APS that determined readmissions. This may indicate that despite subjective improvements in their condition, patients still might not be ready to move out pf the ICU as previously thought.

The Stability and Workload Index for Transfer (SWIFT) score (9,10) has been mentioned in two of the studies. This score, in short, measures the workload in the ICU. In these studies, this score has been shown to outperform models based on other severity of illness scales such as the APACHE II in predicting who will be readmitted to the ICU (5, 10)

Another study(18) found that days when the number of new patients admitted to the ICU were higher than normal, then the patients discharged on those days had a higher risk of readmission. A possible reason given by the authors for the same is the pressure on the staff to find beds for newer patients leading to subsequent premature discharges of older patients. Also, not being able to maintain nursing to patient ratios with new admissions, nurses may be forced to see more patients till re-enforcements arrive in the next shift. A subsequent study(19) supported this finding by pointing out that new patients needed a higher level of care (as indicated by higher TISS-28 scores) in the first few hours of their admissions.

The study by Rosenberg et.al (22) made other interesting observations. The concluded that when a patient was initially admitted to the ICU as a transfer from another hospital or as a transfer from the wards (rather than from the ER), they were more likely to be readmitted upon discharge. This, he attributed to the fact that these patients may have been non-responders to already started treatment and hence were more resistant to standard ICU treatment. These authors also found that if patient’s code statuses were changed to ‘DNR’ (Do Not Resuscitate) before transferring out, their chance of ‘bouncing back’ was reduced significantly. They also observed that patients were 4 times more likely to be made DNR during the 2nd admission to the ICU compared to the first which could be because by that time most physicians have sorted out the non-responders.

Transitions Programs:

Transition programs have been suggested as a means to smoothen the transition of patients out of the ICU. The 2 main components of Critical Care transition programs are as follows

1. ICU Liaison or Discharge Nurses:
This role has been developing in some ICUs since the past few years. This nurse is supposed to ensure that all practical and emotional needs of a patient are met during their transition to a step down unit or wards. This may also include but not be limited to providing clinical support and help to the staff that will be taking care of the patient and making them eventually step into the role of the transition nurse.

2. Step-down Units:
Step-down units are intermediary units which allow them to take care of patients with higher acuities by allowing for more nurses to patient ratios than on the wards but less than that in the ICU. This is a form of transition which eases the patients (usually those with higher nursing care demands) out of the unit.

Transitional care programs in some hospitals are not limited to inpatient care only but also include nurse liaisons/travel nurses who ensure that patient needs are met post discharge. This has been called the Critical Care Outreach team. (23,24)

Our review of certain articles (4, 23) found that these transitional programs or outreach teams, if structured the right way can play a phenomenal role in reducing patient readmission to the hospital and to the Intensive Care Unit, by up to as much as 6-7 % (23)

It is notable to mention that we also reviewed two studies [one performed in the UK and one in the USA(13, 24)]that did not reach statistical significance in favor of using outreach programs.

Costs:
Cost implications to the hospital from re-admissions were not looked at by any study probably because they are difficult to interpret. One way to generate a figure, in the opinion of this author, is to calculate the average cost/day per ICU stay for an average patient and then multiply it by the average number of additional ICU days. However, these readmitted patients are usually sicker than average and their stays may surmount to higher cost. Thus, looking at actual numbers per ICU may help it individually decide its own cost implications and developed mitigation programs in accordance.

ICU Readmissions as a quality indicator :
None of the studies reviewed could prove that ICU readmissions could directly be used as a quality indicator.
A quick return to the ICU may also indicate higher vigilance among physicians and higher aggressiveness of care which may actually be a good thing based on the perspective of the observer. More information in the form of robust controlled trials is necessary and in the meantime this appears to be only a crude indicator at best. The study by Rosenberg mentioned in the ‘results’ section above showed how readmissions were only specific when certain medical or surgical diagnoses were taken into account may also apply to ICU readmissions even though this was done looking at hospital readmissions. The two contrasting indicators, ‘Length of Stay’ and ‘ICU readmissions’, aim for different outcomes. One strives to move patients put of the ICU while the other indirectly hints at keeping patients in the ICU for a longer time. This further worsens the conundrum of using readmissions as a true quality indicator.

Mortality: The increased mortality in readmitted patients is explained by the simple fact that they probably are much sicker than all other patients based on their higher score on the severity of index scales (APACHE lll, SAPS-ll etc) (6). This may also indicate that these categories of patients were either not treated accurately or are non-responders to treatment. These non-responders are people who do not respond to the standard first line treatments available and their readmission to the ICU cannot be linked directly with poor quality of care.
Increased mortality figures in this category of patients also raise the question of premature discharges in these populations. This is difficult to quantify since in the present scenario, physicians, in consultation with the nurses (and sometime other ICU team members such as respiratory and physical therapists), make the conscious decision to send a patient out. There is no established score or protocolled check box method to identify the at risk patient. A few studies did attempt to establish their own scores but the successes achieved by one group did not hold water when tested by others.
These findings may suggest that either more robust studies are needed to prove an association between the above three parameters or that these parameters are not complementary to each other and that they may measure different facets of hospital performance.

Increasing ICU costs associated with increasing initial length of stay to allow for possible safer discharges are not appreciated by the policy makers and cost analysts in the hospitals. Moreover, decreasing ICU LOS is already an established and well looked at parameter for quality improvement in the ICU as shown in literature. Longer initial ICU stays also put the patients at risk of nosocomial infections, lack of sleep, increased time spent on bed rest rather than moving around, worsening risk of encephalopathy and deep vein thrombosis as mentioned above. (1,12,14 ) Thus, one can then argue about which one can be classified as the lesser evil.
This author believes that a physician, being the central decision making body in these scenarios, needs to put the patient’s safety first and not let pressures by administration or the increasing demand for ICU beds or nursing census deter him/her from keeping a patient in the ICU if so needed.
Another important question to ask is whether patients who stay in the ICU longer than average for their disease severity actually benefit from this or does it actually decrease the incidence of readmissions. This author did not find any studies which looks at this in detail.

Physiology:
As discussed before, suboptimal care for patients with higher severity of illness scores during admission may be a factor for early readmissions. As mentioned, a lot of the initial triggers for readmissions were pulmonary problems developing on the floors. This tells us that maybe these patients do not receive the same level of respiratory support as the ones in the ICU where the patient to respiratory therapist ratios are more favorable.
Physicians need to be aware of these hemodynamic changes and should set their discharge plans accordingly after optimizing patient safety.

This may suggest that aggressive respiratory care similar to the kind received in the ICU may need to be continued on the floors. However once the patient’s move out to the wards, the frequency and aggressiveness of care decreases since these patients are now seen to be out of the ‘crucial window’. On the general medical wards, nurse to patient ratios are lower than in the ICU and they may not be able to pay closer attention to these patients. The role of transition programs and more frequent transition from ICU to the step down units and then to the floors may be the answer to these problems.

Limitations:

This review looked at various studies each of which had significant limitations. Most studies looked at readmissions without bothering to determine the appropriateness of the readmissions. They did not they assess the quality of care these patients received in the wards. Even more so, most studies neglected to collect information on ICU census, nursing and physician workloads, presence of Intensivists versus hospitalists in the ICU and failed to mention if the ICUs were closed or open systems of care. These observations would have made it possible to compare similar ICUs with each other for a better and more comprehensive inference.
Another thing that has come into light is that clearly the sicker patients or patients with higher severity of index are more likely to get readmitted. This means that the ICUs dealing with sicker patients may get blamed for a higher rate of re-admission (5).
This has indirectly also been proven by noticing that incidence of readmission to the ICU is higher from the Step down Units (SDUs) rather than regular floors.

Future Research:

In our current healthcare system, the pressures from managed care to reduce ICU length of stays and reduced length of stays being looked at as a performance tool for Intensive care Units are forcing the hands of healthcare team members in the ICU to speed up the process and shorten the length of stay. This review clearly proves that the research out there isn’t exact and more in-depth studies need to be performed. New ICU predictive tools need to be devised and prospectively studied in multiple ICU settings and be validated using appropriate case mix indices. These studies should be subject to ongoing quality controls and utilization review processes.(12) Once established, these may serve as a guide to physicians in their discharge process.
Thus far, looking at severity of illness indices have shown the most promise to predict successfully whether someone is at a higher risk for readmission or not (1) ,For example, if the SAPS score were to be used as an indicator, the rate of improvement in a particular patient’s daily score could be used as a marker for a safer discharge.
Also, looking at other non-patient related parameters such as nursing workloads, effect of transition programs, bed census in the ICU and physician’s expectations from the ward teams when planning discharge for their patients and to what extent these expectations correlate with the facts, all need to be studied in depth.
This author would also like to see studies done which look at the difference between Intensivist’s decision making processes compared to any other physician’s though process. It would be interesting to see if being formally trained in critical care medicine plays any role at all in efficient discharge planning.

A good start may be directing efforts on preventing readmissions with the same initial diagnosis. Foreseeing new problems might be a bigger and tougher problem to deal with.

For all of these above mentioned studies, standardized definitions and precise descriptions need to be used as to what defines ICU readmissions. Elective planned re-admission need to be omitted. This author feels that readmissions should be defined based on whether a patient was readmitted to the ICU within the same hospital stay. Putting limit of 24-48 hours in defining the word ‘readmission’ creates false results and may paint a rosier picture than what exists. Similarly, when performing these studies, control groups should be clearly identified. Patients who were discharged from the ICU but expired while in the wards may need to be counted as potential discharge failures. Some studies have looked at this population in their studies already (12-27). Patients who have had multiple readmissions in to the ICU during the same hospital stays need to be looked at more carefully as these patients may hold the key to process changes that may need to be implemented sooner than later. Intensive Care Units may need to acquire level of treatment severity statuses (similar to level I-IV trauma centers) in order to compare them without any biases in prospective studies, for e.g., ICU’s providing comprehensive services who treat the sickest patients may be designated as ‘level 1’ centers and so on. Even within hospitals, patient’s readmitted to a different ICU than the one they were in before need to be taken into proper account.
On a cost –effectiveness scale, the cost of readmissions per year need to be weighed against the cost of additional initial ICU days expected. This may help to view readmission in a different light.

Conclusion:

For a patient, coming back to the ICU is always a cause of concern for physicians, patients as well as their families. After reviewing a significant number of studies, we can see how certain factors have linear and non-linear relationships with readmissions to the ICU. We need more comprehensive studies to further determine ways to reduce these readmissions. In our review, ICU readmissions have not found to be a viable quality indicator of a hospital’s overall performance.

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26. Brown, S. E., Ratcliffe, S. J., Kahn, J. M., & Halpern, S. D. (2012). The epidemiology of intensive care unit readmissions in the United States. American journal of respiratory and critical care medicine, 185(9), 955-964. 27. Utzolino, S., Kaffarnik, M., Keck, T., Berlet, M., & Hopt, U. T. (2010). Unplanned discharges from a surgical intensive care unit: Readmissions and mortality. Journal of critical care, 25(3), 375-381. 28. Ratcliffe, S. J., Halpern, S. D., & Brown, S. E. S. (2013). An Empirical Derivation Of The Optimal Time Interval For Defining Icu Readmissions. Am J Respir Crit Care Med, 187, A5290. 29. Kaben, A., Corrêa, F., Reinhart, K., Settmacher, U., Gummert, J., Kalff, R., & Sakr, Y. (2008). Readmission to a surgical intensive care unit: incidence, outcome and risk factors. Crit Care, 12(5), R123. 30. Lai, J. I., Lin, H. Y., Lai, Y. C., Lin, P. C., Chang, S. C., & Tang, G. J. (2012). Readmission to the intensive care unit: A population-based approach. Journal of the Formosan Medical Association, 111(9), 504-509. 31. Russell, S. (1999). Reducing readmissions to the intensive care unit. Heart & Lung: The Journal of Acute and Critical Care, 28(5), 365-372. 32. Chan, K. S., Tan, C. K., Fang, C. S., Tsai, C. L., Hou, C. C., Cheng, K. C., & Lee, M. C. (2009). Readmission to the intensive care unit: an indicator that reflects the potential risks of morbidity and mortality of surgical patients in the intensive care unit. Surgery today, 39(4), 295-299. 33. Lee, J. Y., Park, S. K., Kim, H. J., Hong, S. B., Lim, C. M., & Koh, Y. (2009). Outcome of early intensive care unit patients readmitted in the same hospitalization. Journal of critical care, 24(2), 267-272.

Appendix

Table. Measures of readmission to the ICU after initial discharge

|Author |Type of Study |Definition of |Intervention |Results | |
| | |Readmission | | |Inference |
|Cooper, G. S |Observational |Unplanned ICU |To determine variation in ICU |ICU readmissions occurred in 5.8%|Readmission rates were not associated |
|et al. (1999)| |re-admission |readmission rates across |patients who were initially |with severity-adjusted mortality or |
| | |within same |hospitals and associations of |classified as postoperative and |LOS |
| | |hospitalization |readmission rates with other |in 6.4% patients who were non | |
| | | |ICU-based measures of hospital |operative | |
| | | |performance. | | |
|Renton, J., |Retrospective |Readmissions |To determine the epidemiology, |Five initial diagnoses were |Many risk factors for |
|Pilcher et al|longitudinal |within 48 hours |in-hospital mortality, trends, |associated |increased ICU readmission were |
|(2011) | |of discharge. |patient characteristics and |with an odds ratio (OR) greater |identified in this study including ICU|
| | | |predictors of ICU readmissions |than 2 for readmission (p 0.001).|discharge between 6 p.m. and 6 |
| | | |in Australia |In-hospital mortality in |a.m.This was the only modifiable |
| | | | |readmitted patients was 20.7% |variable studied |
| | | | |compared with 4.4% in those not | |
| | | | |readmitted. | |
|Paratz, J., |Prospective |Unplanned ICU |To identify factors which place |The overall percentage of |A certain profile of patients has been|
|Thomas et al |Single Center |re-admission |patients at a higher risk of |patients who were re-admitted to |established who are at increased risk |
|(2005) | |within same |re-admission to intensive care. |intensive care compared with |of re-admission to intensive care. |
| | |hospitalization | |total admissions was 7.7%. |These patients could be provided with |
| | | | |Significant independent factors |increased intervention and |
| | | | |for re-admission were found to be|surveillance on discharge from |
| | | | |age >65 years , colonization |intensive care. |
| | | | |,Weakness, co-morbidities of | |
| | | | |cardiac and/or respiratory | |
| | | | |disease and depression | |
|Finfer, S et |Meta-analysis |N/A |To determine whether critical |Meta-analysis demonstrated a |Critical care transition programs |
|al. (2009) | | |care transition programs reduce |reduced risk of ICU readmission, |appear to reduce |
| | | |the risk of ICU readmission or |but no significant reduction in |the risk of ICU readmission in |
| | | |death, when compared with |hospital associated with a |patients discharged from ICU to |
| | | |standard care |critical care transition program.|a general hospital ward |
|Kramer, A. A |Retrospective |Unplanned ICU |To examine the association |The median unit readmission rate |Patients readmitted to ICUs have |
|et al. (2013)|cohort study |re-admission |between ICU readmission rates |was 5.9%. Across all admissions, |increased hospital mortality and |
| | |within same |and case-mix–adjusted outcomes. |hospital mortality for patients |lengths of stay. The use of |
| | |hospitalization | |with and without readmission was |readmission as a quality measure |
| | | | |21.3% vs. 3.6% |should only be implemented if patient |
| | | | | |case-mix is taken into account |
|Kramer, A. A |Retrospective |Unplanned ICU |To examine which patient |Patients who were readmitted had |Intensive care readmission is |
|et al. (2012)|cohort study |re-admission |characteristics increase the |a four-fold greater probability |associated with patient factors that |
| | |within same |risk for intensive care unit |of hospital mortality and a |reflect a greater severity and |
| | |hospitalization |readmission and assess the |2.5-fold increase in hospital |complexity of illness, resulting in a |
| | | |association of readmission with |stay compared to patients without|higher risk for hospital mortality and|
| | | |case-mix adjusted mortality and |readmission |a longer hospital stay. To improve |
| | | |resource use | |patient safety, physicians should |
| | | | | |consider these risk factors when |
| | | | | |making intensive care discharge |
| | | | | |decisions |
|Yoon KB et |Prospective |Unplanned ICU |To evaluate the effect of the |Re-admission rate in the |Re-admission rate was lower when |
|al. (2004) |Single Center |re-admission |intensivists' discharge |Intensivists group was lower at |Intensivists participated in the |
| | |within same |decision-making on readmission |3.9% compared to 6.5% in non |discharge decision-making, and that |
| | |hospitalization |to ICU |intensivist group |APACHE and MODS scores on the first |
| | | | | |discharge and readmission were |
| | | | | |significant prognostic factors in |
| | | | | |respect of the readmitted patients |
|Charles G |Retrospective |Unplanned ICU |To determine characteristics of |Variables that predicted |Pulmonary failure is the immediate |
|Durbin et al |case-control |re-admission |patients requiring readmission |readmission to the ICU were: |cause of readmission in more than half|
|(1993) |chart review |within same |to an intensive care unit |increased respiratory rate, lower|of the readmitted patients. Increased |
| | |hospitalization | |hematocrit value, positive fluid |respiratory rate correlates with ICU |
| | | | |balance, and positive blood. More|readmission. Intermediate care areas |
| | | | |than 30% of readmissions were for|for patients with poor pulmonary |
| | | | |a recurrence or worsening of the |function may help to avoid readmission|
| | | | |original problem |to an ICU, prevent death, and conserve|
| | | | | |hospital resources. |
|Kastrup, M et|Retrospective |Unplanned ICU |To validate a previously |The performance of the Stability |Based on the data from our patients, |
|al (2013) |chart analysis |re-admission |published numerical index named |and Workload Index for Transfer |the proposed Stability and Workload |
| | |within same |the Stability and Workload Index|score is poor with an area under |Index for Transfer score by Gajic et |
| | |hospitalization |for Transfer in a heterogeneous |the receiver |al is not ideal in aiding the |
| | | |group of ICU patients |operator curve of 0.581 |clinician in the decision, if a |
| | | | | |patient can |
| | | | | |be discharged safely from the ICU |
|Gajic, O et |Prospective |Re-admissions |To develop and validate a |Predictors of readmission |The Stability and Workload Index for |
|al (2006) |cohort study |within 7 days of |numerical index, named the |/unexpected death identified in a|Transfer score is derived from |
| | |ICU discharge |Stability and Workload Index for|logistic regression analysis were|information readily available at the |
| | | |Transfer, to predict ICU |ICU admission source, ICU length |time of ICU dismissal and acceptably |
| | | |readmission |of stay, and day of discharge |predicts ICU readmission |
| | | | |neurologic and respiratory | |
| | | | |impairment | |
|Heidi L. |Prospective |Unplanned ICU |To assess whether a focused |Readmission rates were 1.4%, 3.0%|A targeted interventionccan reduce the|
|Frankel et |Single Center |re-admission |transfer phone call, charted |and 1.2% in periods 1, 2, and 3, |rate of SICU readmission caused by |
|al.(2003) |Study |within same |care summary, and discharge |respectively |care inadequacies stemming from |
| | |hospitalization |checkup ameliorated the | |a resident reallocation strategy |
| | | |re-admission rates to the ICU | | |
|Rosenberg, A.|Systematic |N/A |To evaluate the causes, risk |Hospital death rates were 2- to |Unstable vital signs, respiratory and |
|L et al |Review | |factors, and mortality rates |10-times higher for readmitted |heart rate abnormalities, and the |
|(2000) | | |associated with |patients |presence of poor pulmonary function at|
| | | |unexpected readmission to |Respiratory and cardiac |time of ICU discharge appear to be the|
| | | |medical and surgical ICUs |conditions |most consistent predictors of ICU |
| | | | |were the most common (30 to 70%) |readmission. There were no consistent |
| | | | |precipitating cause of ICU |data supporting the use of |
| | | | |readmission |readmission rates as a measure of |
| | | | | |quality of care |
|Williams, T. |Prospective |Unplanned ICU |To evaluate the clinical |Readmissions during |No improvement in |
|A et al. |Single Center |re-admission |effectiveness of a critical care|the same hospital admission (5.6%|length of stay after admission to the |
|(2010) |Study |within same |nursing outreach service in |vs 5.4%, P= .83), and hospital |intensive care unit, readmission |
| | |hospitalization |facilitating discharge from the |survival |rate, or hospital mortality after a |
| | | |intensive care unit and |(P = .80) did not differ from |critical care nursing outreach service|
| | | |providing follow-up in general |before to after the intervention |was implemented |
| | | |care areas. | | |
|Brown, S. E |Retrospective |48- and |To determine incidence of ICU |(2%) were readmitted to the ICU |ICU readmission rates could be useful |
|et al (2012) |cohort study |120-hour ICU |readmissions in United |within 48 hours, and (3.7%) |for policy makers and |
| | |readmission |States hospitals, and describe |within 120 hours |investigations into their causes and |
| | | |the distribution of time between|Academic hospitals had higher |consequences. |
| | | |ICU discharges and readmissions |odds of 48- and 120-hour | |
| | | | |readmission than patients in | |
| | | | |community hospitals without | |
| | | | |residents | |
| | | | |Closed ICUs had the longest times| |
| | | | |to readmission. | |
|Utzolino, S |Retrospective |Re-admission |To evaluate reasons for |Readmission rate to the SICU was |Earlier-than-planned discharge from a |
|et al (2010) |cohort study |after discharge |re-admission to the SICU |8.3% (139/1675) in elective |SICU leads to a substantially higher |
| | | | |discharges, and 25.1% (110/439) |readmission rate |
| | | | |in unplanned discharges (P b | |
| | | | |.001); 50% (125/249) of all | |
| | | | |readmissions were for surgical | |
| | | | |complications. | |
| | | | |The mortality rate increased by | |
| | | | |4% in readmissions for each year | |
| | | | |of age | |
|Chrusch, C et|Prospective |Re-admissions |To determine whether a lack of |Increased patient occupancy |Overloading the capacity of an |
|al. (2009) |cohort study. |within 7 days of |intensive care unit beds was |within an intensive care unit is |intensive care unit to care for |
| | |ICU discharge |leading to premature patient |associated with an increased risk|critically ill patients may affect |
| | | |discharge from the intensive |of early death or intensive care |physician decision-making, |
| | | |care unit and subsequent early |unit readmission. |resulting in premature discharge from |
| | | |readmission or death | |the intensive care unit |
|Chen, L. M et|Multicenter, |Unplanned ICU |To determine the clinical |Patients with gastrointestinal |Patients with gastrointestinal (GI) |
|al (1998) |cohort study |re-admission |features and outcomes of |(GI) and neurologic diagnoses had|and neurologic diagnoses had the |
| | |within same |patients readmitted to the |the highest readmission rate. |highest readmission rate. |
| | |hospitalization |intensive care unit (ICU) during|Readmissions within 24 hrs |Readmissions within 24 hrs occurred in|
| | | |the same hospital stay and the |occurred in 27% of all |27% of all readmissions. |
| | | |causes for these readmissions |readmissions. |Patients requiring readmission had a |
| | | | |Patients requiring readmission |higher hospital mortality rate |
| | | | |had a | |
| | | | |higher hospital mortality rate | |
|Silva, M. C |Longitudinal |Unplanned ICU | |Higher Nursing Activities Score |The role of the nursing workload for |
|et al (2011) |prospective |re-admission |To identify the factors |at discharge decreased this risk |the death and ICU readmission outcome |
| |study |within same |associated with death and |of re-admission |evidences the importance of nurses’ |
| | |hospitalization |readmission into the Intensive | |work at these units. |
| | | |Care Unit. | | |
|Frost, S. A |Meta-analysis |Unplanned ICU |To assess the relationship |The risk of readmission to ICU |A relationship between increasing |
|et al. (2009)| |re-admission |between severity of illness in |increased by 43% with each |intensive care severity of illness and|
| | |within same |ICU patients and the risk of |standard deviation increase in |risk of readmission to ICU was found. |
| | |hospitalization |readmission to ICU during the |severity of illness score |The effect was the same regardless of |
| | | |same hospitalization. | |the time of measurement of severity of|
| | | | | |illness (at admission to ICU or the |
| | | | | |time of discharge from ICU). |
|Baker, D. R |Retrospective |Unplanned ICU |To determine whether high |The odds of readmission were |Days of high patient inflow volumes to|
|et al.(2009) |comparative |re-admission |patient inflow volumes |nearly five times higher on days |the unit were associated significantly|
| |analysis. |within 72 hours |to an intensive care unit are |when >10 patients were admitted |with subsequent unplanned readmissions|
| | | |associated with unplanned |compared with days with 48–60 hours. By contrast, ICU |measuring ICU readmissions |
| | | |readmission |discharge circumstances and ICU | |
| | | |as an ICU quality indicator |interventions (eg, mechanical | |
| | | | |ventilation) exhibited weaker | |
| | | | |relationships as intervals | |
| | | | |lengthened, with inflection | |
| | | | |points at 30–48 hours | |
|Kaben, A et |Prospective |Unplanned ICU |To investigate the incidence of,|Patients who were readmitted to |Readmission to the ICU was associated |
|al.(2008) |Single Center |re-admission |outcome from and possible risk |the ICU had a higher simplified |with a more than five-fold increase in|
| | |within same |factors for readmission to the |acute physiology II score and |hospital mortality. Older age, higher |
| | |hospitalization |surgical intensive care unit |sequential |maximum sequential organ |
| | | | |organ failure score. |failure score and higher C-reactive |
| | | | |In hospital mortality was |protein levels on the day of |
| | | | |significantly higher in patients |discharge to the hospital floor were |
| | | | |readmitted to the ICU than in |independently associated |
| | | | |other patients. |with a higher risk of readmission to |
| | | | |Age, maximum sequential organ |the ICU. |
| | | | |failure score and C-reactive | |
| | | | |protein | |
| | | | |levels on the day of discharge to| |
| | | | |the hospital floor were | |
| | | | |independently associated with a | |
| | | | |higher risk of readmission to the| |
| | | | |ICU. | |
|Lai, J. I et |Population-base|Readmission |To investigate possible risk |Age > 39 years old, female |Higher risk patients should be |
|al. (2012) |d study |within 1 year |factors for readmission to the |gender, ischemic heart disease, |assessed more carefully before |
| | | |intensive care unit |lung related disorders, |discharge or transfer from the |
| | | | |pneumonia, cerebrovascular |ICU to prevent readmission episodes. |
| | | | |disease, sepsis, heart failure, | |
| | | | |chronic liver disease, diabetes | |
| | | | |mellitus, and chronic | |
| | | | |obstructive pulmonary disease | |
| | | | |were identified as significant | |
| | | | |risk factors for readmission to | |
| | | | |the ICU. | |
|Kwok M. Ho et|Cohort study |Unplanned ICU |To assess the effect of |The number of Charlson |Comorbidity was a risk factor for late|
|al. (2009) | |re-admission |comorbidities on risk of |comorbidities was significantly |ICU readmission. Comorbidities could |
| | |within same |readmission to an intensive care|associated with late readmission |not account for the excess mortality |
| | |hospitalization |unit (ICU) and the excess |but not early readmission in the |associated with ICU readmissions. |
| | | |hospital mortality associated |multivariate analysis. | |
| | | |with ICU readmissions |Both early and late ICU | |
| | | | |readmissions were associated with| |
| | | | |an increased risk of hospital | |
| | | | |mortality after adjusting for | |
| | | | |age, admission source, type of | |
| | | | |admission, the APACHE predicted | |
| | | | |mortality, and the number of | |
| | | | |Charlson comorbidities. | |
|Russell, S. |Prospective |Unplanned ICU |To determine factors that |The study identified three main |Preliminary results indicate that the |
|(1999) | |re-admission |contributed to readmissions to |factors that contributed to |appointment of the follow-up nurse has|
| | |within same |the intensive care unit (ICU) |readmissions from the ward: |not only reduced the rate of |
| | |hospitalization |from the general wards |progression of the patient’s |readmissions to the ICU but also |
| | | | |illness, postoperative care |decreased the acuity levels of those |
| | | | |requirements, |readmitted. |
| | | | |and inadequate follow-up care on | |
| | | | |the general wards | |
|Metnitz, P. G|Prospective |Unplanned ICU |To evaluate |For mechanically ventilated |Patients with residual organ |
|et al. (2003)|multicenter |re-admission |risk factors in critically ill |patients, the time between |dysfunctions were associated with an |
| |cohort study |within same |patients |extubation and discharge was |increased risk of being readmitted. |
| | |hospitalization |who were readmitted to an |significantly shorter for |Optimizing organ functions in these |
| | | |intensive |readmitted than for |patients before discharge from the ICU|
| | | |care unit (ICU) during their |non-readmitted patients. |could result in reduced readmission |
| | | |hospital |On the day of their first ICU |rates |
| | | |stay. |discharge, readmitted patients | |
| | | | |were in greater need of organ | |
| | | | |support, with more patients still| |
| | | | |requiring ventilatory, | |
| | | | |cardiovascular and renal support | |
| | | | |than non-readmitted patients | |
|Lissauer, M. |Retrospective |Unplanned ICU |Defining predictors of ICU |Admission severity of illness was|Patients who require ICU readmission |
|E (2013) |cohort study |re-admission |Readmissions |significantly higher in the REA |have a different admission profile |
| | |within same | |group |than those who do not ‘‘bounce back.’’|
| | |hospitalization | |REA patients were more likely |Understanding these differences may |
| | | | |admitted to emergency, more |allow for quality improvement projects|
| | | | |likely to have a history of |such as instituting different |
| | | | |immunosuppression |discharge criteria for different |
| | | | |or higher Acute Physiology Score |patient populations. |
|Makris, N |Case-control |Unplanned |To identify patient, intensive |New onset respiratory compromise |Risk of readmission is associated with|
|(2010) |study |ICU readmission |care and ward-based risk factors|and sepsis were the most common |both patient and intensive care |
| | |within 72 hours |for early, unplanned readmission|cause of readmission. |factors. Physiological derangement on |
| | |of discharge |to the intensive care unit |Independent risk factors for |the ward predicts intensive care unit |
| | | | |readmission were chronic |readmission, however, clinical |
| | | | |respiratory disease, pre-existing|response to this appears suboptimal. |
| | | | |anxiety/depression , INR >1.3 , | |
| | | | |immobility , nasogastric | |
| | | | |nutrition, a white cell count | |
| | | | |>15×109/l and non-weekend | |
| | | | |intensive care unit discharge. | |
| | | | |Physiological derangement on the | |
| | | | |ward strongly predicted | |
| | | | |readmission | |
|Rosenberg, A.|Secondary |Readmissions |To determine the influence of |Hospital mortality was five |ICU readmissions may be more common |
|L (2001) |analysis of a |were classified |changes in acute |times higher (43% vs. 8%; p < |among patients who respond poorly to |
| |prospective |as to whether |physiology scores (APS) and |.0001), and length of stay was |treatment as measured by increased |
| |cohort study |they occurred |other patient characteristics on|two |severity of illness at first ICU |
| | |within 24, 48, |predicting intensive care unit |times longer (16 6 16 vs. 32 6 28|discharge and failure of prior therapy|
| | |72, or .72 hrs |(ICU) readmission |days; p < .001) in readmitted |at another |
| | |from the first | |patients. Mean discharge APS was |hospital or on a general medicine unit|
| | |ICU discharge | |significantly higher in the | |
| | | | |readmitted group compared with | |
| | | | |the not readmitted group (43 6 | |
| | | | |19 vs. 34 6 18; p > .01) | |
|Chan, K. S |Retrospective |Unplanned ICU |To investigate the |A total of 26.4% of the |The mortality of surgical patients |
|(2009) |cohort study |re-admission |characteristics and outcomes |readmission patients had an early|with ICU |
| | |within same |of surgical patients who were |readmission (