Abstract
Objective:
To compare the differences in characteristics and outcomes of cancer center patients with other subspecialty medical patients reviewed by rapid response teams.
Design:
A retrospective cohort study of hospitalized general medicine patients, subspecialty medicine patients, and oncology patients requiring rapid response team activation over a 2-year period from September 2009 to August 2011.
Patients:
Five hundred fifty-seven subspecialty medical patients required rapid response team intervention.
Setting:
A single academic medical center in the southeastern United States (800+ bed) with a dedicated 50-bed inpatient comprehensive cancer care center.
Interventions:
Data abstraction from computerized medical records and a hospital quality improvement rapid response database.
Measurements and Main Results:
Of the 557 patients, 135 were cancer center patients. Cancer center patients had a significantly higher Charlson Comorbidity Score (4.4 vs 2.9, < 0.001). Cancer center patients had a significantly longer hospitalization period prior to rapid response team activation (11.4 vs 6.1 d, p < 0.001). There was no significant difference between proportions of patients requiring ICU transfer between the two groups (odds ratio, 1.2; 95% CI, 0.8–1.8). Cancer center patients had a significantly higher in-hospital mortality compared with the other subspecialty medical patients (33% vs 18%; odds ratio, 2.2; 95% CI, 1.50–3.5). If the rapid response team event required an ICU transfer, this finding was more pronounced (56% vs 23%; odds ratio, 4.0; 95% CI, 2.0–7.8). The utilization of rapid response team resources during the 2-year period studied was also much higher for the oncology patients with 37.34 activations per 1,000 patient discharges compared with 20.86 per 1,000 patient discharges for the general medical patients.
Conclusions:
Oncology patients requiring rapid response team activation have a significantly higher in-hospital mortality rate, particularly if the rapid response team requires ICU transfer. Oncology patients also utilize rapid response team resources at a much higher rate.
Keywords: medical emergency teams, oncology patients, rapid response teams
Rapid response teams (RRTs) are widely used at many hospitals to recognize, assess, and triage deteriorating patients. As of 2011, approximately 3,700 U.S. hospitals had a rapid response system in place (1). A RRT consists of a team of nurses and physicians (2) with the goal of bringing critical care resources to an acutely deteriorating patient’s bedside (3).
Numerous studies have been conducted to determine the impact of rapid response systems. Multiple single-center studies have demonstrated decreases in both cardiac arrest and in-hospital mortality after the implementation of these systems (4–8). A reduction in out-of-ICU mortality has also been demonstrated (9). However, a meta-analysis of RRT studies demonstrated only weak evidence to support an overall reduction in in-hospital mortality (10). A large prospective study also did not demonstrate a significant difference in in-hospital mortality or ICU transfer rates (11). This suggests that further study of rapid response systems is warranted. Study of RRTs and their utilization by specific patient populations, such as the elderly, end-stage renal disease patients, and cancer patients, would also likely be helpful.
Of specific interest to this research group is the utilization of RRTs in the inpatient oncology population. There are currently 41 hospitals in the United States designated as Comprehensive Cancer Centers by the National Cancer Institute (12). Dedicated comprehensive cancer centers will likely continue to open at hospitals throughout the nation over the following years. Previous research has demonstrated that oncology patients have an inherently high acuity level (13, 14). To our knowledge, no one has conducted an analysis of RRT utilization and outcomes in a dedicated inpatient oncology population. An analysis of this sort is clinically relevant given the relatively high prevalence of cancer in the United States. Recent data indicate that the age-adjusted cancer prevalence is 533.8 per 100,000 (95% CI, 532.6–535.1) (15). Better knowledge of the differences in acuity between oncologic and other medical patients could facilitate appropriate RRT and ICU resource allocation planning for future and comprehensive cancer centers.
METHODS AND MATERIALS
Setting
We performed a retrospective study at a single academic medical center (800+ bed) in the southeastern United States during a 2-year study period from September 2009 through 2011 following the opening of a 50-bed dedicated inpatient comprehensive cancer care center in September 2009. Our institutional review board approved this study and waived the need for informed consent.
Patient Population
We included for review all consecutive RRT activations during the time period studied involving nonsurgical acute care patients. We excluded all RRT activations that occurred on intermediate care units, surgical floors, inpatient psychiatric, and inpatient rehabilitation units. The purpose of these criteria was to enable a direct comparison between the medical noncancer center population, including medical subspecialty and general medicine patients, and the comprehensive cancer center acute care population.
RRTs at our facility operate 24 hours a day and comprised a critical care nurse, respiratory therapist, and an ICU physician. The RRT program has been in effect since 2006.
Our overall goal was to compare the differences in characteristics and outcomes of comprehensive cancer center and medical noncancer center patients. Patients in the cancer center were identified as cancer center patients and patients on nonsurgical floors were identified as medical subspecialty patients. The primary outcome variable of interest was in-hospital mortality. Additional outcome variables of interest included requirement for ICU transfer and mortality if ICU transfer was required. Additional variables that were analyzed included the following: average hospital length of stay, average number of days between admission and RRT activation, and average duration of RRT event. RRT activation and nature of the event leading to the activation (alterations in heart rate, blood pressure, respiratory rate, or Sao2; altered mental status; staff concern; and other) were also analyzed. Data on baseline demographics, such as average age and gender, were collected. Furthermore, comorbidity data as defined by Charlson et al (14) were collected on the patients studied. These data were used to calculate a Charlson Comorbidity Score Index (14). The specific primary cancer diagnosis of the comprehensive cancer center patients was also identified.
Data on usage of palliative resources and advanced care planning decisions in the cancer center patients were additionally collected. For the purposes of this study, a code status change was defined as a change either from full code to do not resuscitate (DNR) or from DNR to comfort care only measures.
Concurrent hospital database information was accessed to obtain number of hospital admissions and deaths during the period under study. This enabled calculation of the rate of RRT activation per 1,000 patient, overall hospital mortality rates, and mortality rates for the medical subspecialty services for the period under study. Same day admissions were not included.
Statistical Methods
We analyzed data using descriptive statistics. Pearson chisquare test was used for bivariate analysis of categorical variables. Bivariate analysis of continuous variables was performed using Wilcoxon rank-sum test for nonnormally distributed variables, Student t test for normally distributed variables, and Welch test for normally distributed variables with unequal variance. Univariate and multivariate logistic regression were also used. Stata version 12.0 was used to conduct all analyses (Release 12, College Station, TX).
RESULTS
A total of 557 acute care medical subspecialty patients required RRT evaluation during the period under study. Of these 557 patients, 135 patients were in the comprehensive cancer center. The utilization of RRT resources during the 2-year period studied was higher for the comprehensive cancer center patients with 37.34 activations per 1,000 patient discharges compared with 20.86 per 1,000 patient discharges for the other subspecialty medical floor patients.
Table 1 presents the baseline demographic characteristics of the study patients. The cancer center group had a higher proportion of males, and they were younger. The cancer center group had a higher proportion of patients with metastatic solid tumors, leukemia or lymphoma, and neoplasia. The noncancer medical subspecialty floor patients had a significantly higher proportion of the following comorbid conditions: diabetes with end-organ dysfunction, moderate-to-severe renal failure, congestive heart failure, history of myocardial infarction, cerebrovascular disease, and dementia. There were no significant differences in the other comorbid conditions studied or in proportions of patients with multiple RRT events or ICU stay prior to RRT event. There was a significant difference in Charlson Comorbidity Scores in the two cohorts, with the cancer center patients having a higher score than the other medical subspecialty floor patients (4.5 vs 2.9, p < 0.001)(Table 1).
TABLE 1.
Patient Demographics and Comorbid Conditions
| Noncancer Center Patients (n = 422) | Cancer Center Patients (n = 135) | P | |
|---|---|---|---|
| Mean age (yr ± sd) | 60.1 ± 18.6 | 56.8 ± 13.5 | 0.03 |
| Male gender (n, % total) | 197 (46.7) | 81 (60.0) | 0.01 |
| Patients with multiple RRT events (n, % total) | 54 (12.8) | 19 (14.1) | 0.70 |
| Patients with ICU stay prior to RRT (n, % total) | 61 (14.5) | 17 (12.6) | 0.59 |
| Metastatic solid tumor (n, % total) | 25 (5.9) | 42 (31.1) | < 0.001 |
| Leukemia or lymphoma (n, % total) | 8 (1.9) | 73 (54.1) | < 0.001 |
| Neoplasia (n, % total) | 16 (3.8) | 15 (11.11) | < 0.01 |
| Diabetes (n, % total) | 71 (16.8) | 19 (14.1) | 0.45 |
| Diabetes with end-organ dysfunction (n, % total) | 71 (16.8) | 6 (4.4) | < 0.001 |
| Moderate-to-severe renal failure (n, % total) | 82 (19.4) | 8 (5.9) | < 0.001 |
| Congestive heart failure (n, % total) | 93 (22.0) | 13 (9.6) | < 0.01 |
| History of myocardial infarction (n, % total) | 64 (15.2) | 9 (6.7) | 0.01 |
| Cerebrovascular disease (n, % total) | 55 (13.0) | 9 (6.7) | 0.04 |
| Peripheral vascular disease (n, % total) | 35 (8.3) | 7 (5.2) | 0.23 |
| Chronic obstructive pulmonary disease (n, % total) | 99 (23.5) | 24 (17.8) | 0.17 |
| Peptic ulcer disease (n, % total) | 27 (6.4) | 6 (4.4) | 0.40 |
| Mild liver disease (n, % total) | 31 (7.4) | 5 (3.7) | 0.13 |
| Moderate-to-severe liver disease (n, % total) | 23 (5.5) | 5 (3.7) | 0.42 |
| Hemiplegia (n, % total) | 4 (1.0) | 2 (1.5) | 0.60 |
| AIDS (n, % total) | 13 (3.1) | 6 (4.4) | 0.45 |
| Dementia (n, % total) | 29 (6.8) | 1 (0.7) | 0.01 |
| Connective tissue disease (n, % total) | 45 (10.6) | 10 (7.4) | 0.27 |
| Weighted Charlson Comorbidity Score (score, 95% CI) | 2.9 (95 CI, 2.7–3.1) | 4.5 (95 CI, 3.9–4.8) | < 0.001 |
RRT = rapid response team.
The different physiologic and clinical triggers for RRT activation were analyzed, and there were no significant differences in the triggers between the two groups (Table 2). Furthermore, there was no difference in duration of time the RRT was at the bedside (Table 3). However, the cancer center group did have a significantly longer median duration of hospitalization prior to RRT activation (4 vs 2 d, p < 0.001). There was additionally a trend to longer hospitalization in the oncology cohort (p = 0.05) (Table 3). There was no significant difference in the proportion of patients requiring ICU transfer between the two groups (odds ratio [OR], 1.2; 95% CI, 0.8–1.9).
TABLE 2.
Comparison of Rapid Response Team Call and Trigger Characteristics
| Noncancer Center Patients (n = 422) | Cancer Center Patients (n = 135) | P | |
|---|---|---|---|
| RRT called due to heart rate change (n, % total) | 70 (22.4) | 28 (28.3) | 0.23 |
| RRT called due to blood pressure change (n, % total) | 68 (16.1) | 23 (17.0) | 0.80 |
| RRT called due to respiratory rate change (n, % total) | 33 (7.8) | 12 (8.9) | 0.69 |
| RRT called due to Sao2 change (n, % total) | 124 (29.4) | 43 (31.9) | 0.59 |
| RRT called due to altered mental status (n, % total) | 127 (30.1) | 39 (28.9) | 0.79 |
| RRT called due to staff concern (n, % total) | 85 (20.1) | 32 (23.7) | 0.38 |
| RRT called due to other reason (n, % total) | 97 (23.0) | 35 (25.9) | 0.48 |
RRT = rapid response team.
TABLE 3.
Duration of Rapid Response Calls and Hospitalization
| Noncancer Center Patients (n = 422) | Cancer Center Patients (n = 135) | P | |
|---|---|---|---|
| Duration of RRT (median minutes, IQR) | 34 (20–53) | 38 (23–60) | 0.19 |
| Duration between admission and RRT (median days, IQR) | 2 (1–6) | 4 (1–11) | < 0.001 |
| Duration of hospitalization (median days, IQR) | 9.5 (5–19) | 12 (6–27) | 0.05 |
RRT = rapid response team, IQR = interquartile range.
Within the comprehensive cancer center cohort, the primary oncologic diagnosis was identified. A large proportion had leukemia, lymphoma, myeloma, lung, breast, or colorectal primary sites (Table 4).
TABLE 4.
Cancer Demographics of Comprehensive Cancer Center Patients
| Cancer Type/Primary Location | No. of Patients (%) |
|---|---|
| Leukemia | 37 (37.4) |
| Lymphoma | 24 (17.8) |
| Myeloma | 14 (10.4) |
| Lung | 14 (10.4) |
| Breast | 8 (5.9) |
| Colorectal | 7 (5.2) |
| Liver | 3 (2.2) |
| Upper gastrointestinal (esophagus, stomach) | 2 (1.5) |
| Brain | 2 (1.5) |
| Prostate | 2 (1.5) |
| Other | 22 (16.3) |
Advanced care planning data for the comprehensive cancer center patients were collected. Of these patients, only 13 patients (9.6%) had a preexisting DNR order. Only four patients (1.5%) experienced a code status change during the event and 18 (13.3%) within 24 hours post RRT. Only two patients (1.5%) had palliative care involvement in the 24 hours prior to the RRT, and six patients (4.4%) had palliative care involvement within 24 hours post event (Table 5).
TABLE 5.
Advance Care Planning Characteristics
| Cancer Center Patients (n = 135) (%) | |
|---|---|
| Preexisting do not resuscitate | 13 (9.6) |
| Palliative care involvement in the preceding 24 hr | 2 (1.5) |
| Palliative care involvement within 24 hr post RRT | 6 (4.4) |
| Code status change during RRT | 4 (3.0) |
| Code status change in 24 hr post RRT | 18 (13.3) |
RRT = rapid response team.
Comprehensive cancer center patients requiring RRT activation had a significantly higher in-hospital mortality compared with the other medical subspecialty floor patients (33% vs 18%; OR, 2.3; 95% CI, 1.5–3.6). When adjusted for possible confounders including weighted Charlson comorbidity index as well as age and gender, mortality was still higher in the cancer center patients (OR, 1.9; 95% CI, 1.2–3.1). This finding was further magnified if the RRT event required an ICU transfer (56% vs 23%; OR, 4.0; 95% CI, 2.0–7.8) (Table 6).
TABLE 6.
ICU Transfer and Mortality Outcomes
| Noncancer Center Patients (n = 422) | Cancer Center Patients (n = 135) | P | Odds Ratio | |
|---|---|---|---|---|
| ICU transfer required (n, % total) | 142 (33.6) | 52 (38.5) | 0.301 | 1.2 (95% CI, 0.8–1.9) |
| Overall in-hospital mortality (n, % total) | 75 (17.8) | 45 (33.3) | < 0.001 | 2.3 (95% CI, 1.5–3.6) |
| Overall in-hospital mortality, adjusted for WCCI, age, and gender | 0.005 | 1.9 (95% CI, 1.2–3.1) | ||
| In-hospital mortality if ICU transfer required (n, % total) | 33 (23.2) | 29 (55.8) | < 0.001 | 4.2 (95% CI, 2.1–8.2) |
| In-hospital mortality if ICU transfer required, adjusted for WCCI, age, and gender | 0.001 | 3.3 (95% CI, 1.7–6.7) |
WCCI = Weighted Charlson Comorbidity Index.
During the time period of the study, overall hospital mortality was 26.0 per 1,000 patient admissions. Mortality on the nononcology medical subspecialty services was 26.2 per 1,000 patient admissions, whereas mortality on the medical oncology services was 48.2 per 1,000 patient admissions.
DISCUSSION
Major Findings
The results of this study are notable for a number of findings. Cancer center patients had a higher rate RRT activation than their general medicine counterparts. The study did not reveal a significant difference in rate of ICU transfer after an RRT event between the two groups. Despite this, there was a significantly higher in-hospital mortality rate in the cancer center patients both with and without requirement of ICU transfer. Not surprisingly, patients requiring RRT review had an overall higher hospital mortality than the general hospital population.
These findings confirm that comprehensive cancer center patients, particularly those who experience acute medical deterioration, have inherently higher mortality rates than their nononcology counterparts. Notably, the cancer center patients had a higher Charlson Comorbidity Index, which correlates with the higher mortality rates which are largely attributable to the higher mortality associated with a diagnosis of metastatic solid tumors, leukemia, or lymphoma. Conversely, it would seem intuitive that cancer center patients who require hospital admission would have an inherently higher acuity.
Cancer center patients also had a longer duration of hospitalization prior to medical emergency team activations. This could be a result of the fact that many oncology patients develop treatment-related complications and exposure to hospital-related infections in the setting of a compromised immune system.
Limitations
This study was conducted at a single academic center, and therefore, the results may not be reproducible in other centers. However, the findings are plausibly generalizable and not particularly surprising for any clinician who cares for these patients.
Implications
Taken as a whole, these data can help direct current resource allocation in the current care of inpatient oncology patients and future planning for comprehensive cancer centers. The higher RRT utilization rate suggests that more medical emergency team resources may be needed if a medical center has a comprehensive cancer center. A dedicated oncology RRT team would not be an unreasonable approach to address this issue.
Given the much higher mortality rate in cancer center patients that require RRT intervention, involvement of palliative care services when such an event occurs would be reasonable. Furthermore, if a cancer center patient deteriorates while in house and requires ICU transfer, it would be reasonable to advise patients and their families of the associated poorer outcomes and to address goals of care as warranted.
Areas for Future Research
Ultimately, a model that could help predict which oncology patients are unlikely to recover after in-house decompensation would be extremely useful. This would be a fruitful area for future research. Current and future comprehensive cancer centers, however, should be aware of the associated high mortality oncology patients who have an in-hospital decompensation and have appropriate palliative and ICU resources available.
CONCLUSION
Comprehensive cancer center patients who require RRT services have a significantly higher mortality rate and utilization of RRT resources. This should be taken into consideration by current and future comprehensive cancer centers. The increased RRT utilization suggests that increased RRT resources are necessary for the oncology population. The observation of increased mortality should help guide family counseling and involvement of palliative care services when appropriate in oncology patients who require RRT activation. A model that could predict which oncology patients were unlikely to recover after in-house deterioration would be helpful in guiding care.
Acknowledgments
Dr. Mayer is employed by UNC Health Care. Dr. Lin received support for article research from National Institutes of Health (NIH). His institution received grant support from the NIH(grant: UL1 TR000083). Dr. Chang’s institution received grant support from the NIH (Clinical trials for ARDS network and MIND-USA). The remaining authors have disclosed that they do not have any potential conflicts of interest.
Footnotes
See also p. 997.
REFERENCES
- 1.Jones DA, DeVita MA, Bellomo R: Rapid-response teams. N Engl J Med 2011; 365:139–146 [DOI] [PubMed] [Google Scholar]
- 2.Jacques T, Harrison GA, McLaws ML: Attitudes towards and evaluation of medical emergency teams: A survey of trainees in intensive care medicine. Anaesth Intensive Care 2008; 36:90–95 [DOI] [PubMed] [Google Scholar]
- 3.England K, Bion JF: Introduction of medical emergency teams in Australia and New Zealand: A multicentre study. Crit Care 2008; 12:151. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Bellomo R, Goldsmith D, Uchino S, et al. : A prospective before-and-after trial of a medical emergency team. Med J Aust 2003; 179:283–287 [DOI] [PubMed] [Google Scholar]
- 5.Chen J, Bellomo R, Flabouris A, et al. ; MERIT Study Investigators for the Simpson Centre; ANZICS Clinical Trials Group: The relationship between early emergency team calls and serious adverse events. Crit Care Med 2009; 37:148–153 [DOI] [PubMed] [Google Scholar]
- 6.Buist MD, Moore GE, Bernard SA, et al. : Effects of a medical emergency team on reduction of incidence of and mortality from unexpected cardiac arrests in hospital: Preliminary study. BMJ 2002; 324:387–390 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Jones D, Bellomo R, Bates S, et al. : Long term effect of a medical emergency team on cardiac arrests in a teaching hospital. Crit Care 2005; 9:R808–R815 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Sebat F, Musthafa AA, Johnson D, et al. : Effect of a rapid response system for patients in shock on time to treatment and mortality during 5 years. Crit Care Med 2007; 35:2568–2575 [DOI] [PubMed] [Google Scholar]
- 9.Beitler JR, Link N, Bails DB, et al. : Reduction in hospital-wide mortality after implementation of a rapid response team: A long-term cohort study. Crit Care 2011; 15:R269. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Winters BD, Pham JC, Hunt EA, et al. : Rapid response systems: A systematic review. Crit Care Med 2007; 35:1238–1243 [DOI] [PubMed] [Google Scholar]
- 11.The MERIT Study Investigators: Introduction of a medical emergency team (MET) system—A cluster-randomised controlled trial. Lancet 2005; 365:2091–2097 [DOI] [PubMed] [Google Scholar]
- 12.National Cancer Institute Office of Cancer Center: Cancer Centers List. Available at: http://cancercenters.cancer.gov/cancer_centers/cancer-centers-names4.html. Accessed June 20, 2012
- 13.Needham DM, Scales DC, Laupacis A, et al. : A systematic review of the Charlson comorbidity index using Canadian administrative databases: A perspective on risk adjustment in critical care research. J Crit Care 2005; 20:12–19 [DOI] [PubMed] [Google Scholar]
- 14.Charlson ME, Pompei P, Ales KL, et al. : A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 1987; 40:373–383 [DOI] [PubMed] [Google Scholar]
- 15.Atlanta U.S. Department of Health and Human Services. U.S. Cancer Statistics Working Group: United States Cancer Statistics: 1999–2005 Incidence and Mortality Web-Based Report. Available at: http://www.cdc.gov/uscs 2009. Accessed June 20, 2012 [Google Scholar]