INTRODUCTION
Intensive care unit (ICU) in South Africa (SA) is a scarce resource in both the public and private healthcare sectors. Only 23% of the public sector hospitals in the country have been shown to have ICU facilities. Furthermore, 86% of these beds are concentrated in the provinces of Gauteng, KwaZulu‐Natal and the Western Cape. The bed: population ratio in these provinces is 1:20,000 but ranges from 1:30,000 to 1:80,000 in other provinces. ICU beds only make up 1.7% of the total number of public sector hospital beds in SA.(1)
Given the limited availability of ICU beds together with the resource restrictions, doctors making admission decisions have a stressful task in correctly triaging patients. The process involves a preadmission evaluation of the patient to determine the severity of their condition and an evaluation as to whether the severity warrants ICU admission. The final decision is based on bed availability, survival prospects, and patient and family wishes. Grading systems such as the Acute Physiological and Chronic Health Evaluation (APACHE II) and Simplified Acute Physiology Score (SAPS) aim one to help formulate a clinical picture and categorise patients by severity; however, the final decision-making process is more complex. The South African Society of Anaesthesiologists has published critical care admission guidelines, but they are not evidence based. Nesibopho, an evidence-based initiative was founded in 2004 to improve the quality of care in ICU in SA. Nesibopho has a set of ICUs and high care admission guidelines that has been endorsed by the Critical Care Society of Southern Africa.(2)
Helen Joseph Hospital (HJH) is a tertiary referral centre in Johannesburg, affiliated to the University of the Witwatersrand. Critical care beds are a scarce resource at HJH, a situation prevalent in many other public hospitals. A limited number of beds serve a population with a large burden of disease. Medical practitioners request ICU beds for patients they deem to be in need of intensive care. However, the decision to admit patients to the ICU remains the responsibility of the ICU consultant on call. The profile of the number of admissions, refusals and reasons for admission or refusal has not been determined. Understanding the profile of bed requests, admissions, refusals and subsequent outcome is key to enhancing the appropriate use of this scarce resource.
METHOD
A contextual, prospective, descriptive research design was used in this study. Approval to conduct the study was obtained from the Human Research Ethics Committee (Medical) of the University of Witwatersrand. At the time of the study, there was no formal prognostic scoring system (such as APACHE or SAPS) or admission guidelines in place at HJH. The study involved analysing all the completed consultation forms for ICU beds requested at HJH. The sample size was realised by the number of ICU bed requests during the study months using a consecutive, convenience-sampling method. Forms that were illegible or incorrectly completed were excluded from the analysis. Data was collected from completed ICU consultation forms and follow-up data from ICU admission and discharge books. Data was collected during the winter month of August and the summer month of December 2012. All patients for whom ICU beds were requested were examined by ICU medical staff who then presented the clinical assessment to the consultant on call. The details of the consultation were documented on a standard hospital ICU consultation form and a copy of the form was retained in the ICU records.
Patients were grouped according to age (<60 years and >60 years) and the discipline that they were receiving treatment from (medical and surgical). The reasons for admission were mechanical ventilation, inotropic support or observation. Some patients were admitted for more than one reason; hence, the percentages do not total 100. A triad of reasons for refusal of admission to the ICU included patients being too ill, too well or no resources available. The no-resource-available group comprised a combination of ICU beds not available at the time of request and or lack of nursing staff to manage patients.
The data was analysed using Stata version 13.1. The findings are described and analysed using descriptive and inferential statistics. The Chi-square test was used to compare categorical variables, P‐values <0.05 were considered statistically significant. Logistic regression, odds ratio and median interquartile range (IQR) were also calculated.
RESULTS
A total number of 139 ICU bed requests were made during the 2 months reviewed. Of these, 49 patients were admitted to the ICU and 90 were denied admission. The median age of the study group was 44 years with an IQR 30–57.5 years. The demographics of the study cohort are described in Table 1 and the reasons for admission and refusal to ICU are shown in Table 2.
Demographics of patients for whom an ICU bed was requested
| Total | Admitted | Refusals | |||||
|---|---|---|---|---|---|---|---|
| Frequency | % | Frequency | % | Frequency | % | ||
| Total | 139 | 49 | 35.3 | 90 | 64.7 | ||
| Age | <60 | 110 | 79.14 | 40 | 81.6 | 70 | 77.8 |
| ≥60 | 29 | 20.86 | 9 | 18.4 | 20 | 22.2 | |
| Gender | Male | 84 | 60.4 | 29 | 59.2 | 55 | 61.1 |
| Female | 55 | 39.6 | 20 | 40.8 | 35 | 38.9 | |
| Season | Summer | 72 | 51.8 | 21 | 43.0 | 51 | 56.7 |
| Winter | 67 | 48.2 | 28 | 57.0 | 39 | 43.3 | |
| Discipline | Medical | 76 | 54.7 | 25 | 51.0 | 51 | 56.7 |
| Surgical | 63 | 45.3 | 24 | 49.0 | 39 | 43.3 | |
Reasons for admission and refusal
| Total admissions = 49 | |||
|---|---|---|---|
| Number | Percentage | ||
| Reason for admission | Mechanical ventilation | 42 | 85.7 |
| Inotropic support | 10 | 20.4 | |
| Observation | 12 | 24.5 | |
| Total refusals = 90 | |||
| Number | Percentage | ||
| Reason for refusal | Too ill | 37 | 41.1 |
| Too well | 27 | 30.0 | |
| Lack of resources | 26 | 28.9 | |
Those patients that were admitted to ICU and followed up for 30 days showed a 23.1% survival benefit over those not admitted to ICU. At a 30-day follow-up, 77.5% of those patients admitted to ICU were alive, compared to only 54.4% in the group who were refused admission to ICU (P = 0.007) (Table 3).
Comparison between ICU admission and outcome
| Demised | Alive | Total | |
|---|---|---|---|
| Refusals | 41 | 49 | 90 |
| Admitted | 11 | 38 | 49 |
| Total | 52 | 87 | 139 |
Chi square; P = 0.007.
Only one patient who was assessed as too ill for ICU admission survived to the 30-day follow-up and no patients who were deemed too well for ICU admission demised within the follow-up period.
The reason for ICU bed refusal together with outcomes is important as it highlights triage practice efficacy. A total of 90 patients for whom requests were made were refused admission to ICU. Of these, 41.1% of patients were assessed as too ill, 30% as too well and in 28.9% of patients, ICU admission refusal was due to a lack of resources (Table 4).
DISCUSSION
Triage is an important component of managing a successful ICU. Selecting the patients most likely to benefit from admission is difficult and hence many triage scoring systems have been developed.(3) Understanding the profile of bed requests, admissions, refusals and subsequent outcomes may enhance the appropriate use of this scarce resource.
The median age of patients for whom ICU bed requests at HJH in the current study was fairly young at 44 years. A study from Hong Kong (3) reported a median age of 61 years for patients admitted to ICU. Wunsch et al. (4) compared ICU admissions between the USA and the United Kingdom. They reported a mean age of patients in USA ICUs of 60.4 years and 57.4 years in the United Kingdom. Another study from the USA reported a mean age of ICU patients of 52 years.(5) Iapichino et al. (6) across seven developed countries reported a mean age of 59.1 years. All these studies emanated from developed countries and thus reflect an older ICU patient profile compared to the current study. The difference in age profile most likely could be explained by differing access to healthcare and different burden of diseases between developed and developing countries, with HJH having a younger population in need of critical care.
There are no local studies comparing ICU bed requests between winter and summer months. The expectation was that there would be more ICU requests during the winter months with an increase in medical admissions. In the current study, there was no difference in bed requests between the winter and summer months. Santana Cabrera et al. (7) in the Canary Islands reported that 79% of ICU admissions took place during winter; however, no difference was reported according to age, severity of illness or mortality rates. When comparing the discipline requesting the ICU bed with the season, in the current study, medical patients held the majority for both seasons. Simchen et al. (8) in Israel noted a 50% split between medical and surgical patients.
The most common reason cited for admission was the need for mechanical ventilation (85.7%). Patient observation was the second most common indication for admission (24.4%) followed by inotropic support at 20.4%. Patients may have had more than one reason for initial admission as critically ill patients often need multi-organ support. The most common reason internationally for admission to ICU has been cardiac and respiratory failure.(3,5,6,8,9) Bapoje et al. (5) in the USA reported respiratory failure as the most common reason for ICU admission at 27% and hypotension and heart failure accounted for 21% of the admissions. Iapichino et al. (6) reported respiratory involvement as the most common reason for admission at 38.3%, followed by cardiac involvement at 28.2%. These admission rates only represent the reason for admission and do not include patients who may have needed mechanical ventilation or inotropes after admission.
When assessing ICU bed access overall, a greater percentage of bed requests were bed denial. The rejection rate for ICU admission in this study was 64.7% which is much higher than the rejection rate in developed countries ranging from 17.2% to 38%.(3,6) The main reason for admission refusal in the current study was found to be patients too ill for ICU admission at 41%, followed by those judged to be too well (30%) and 29% of patients could not be admitted due to resource constraints. A study in seven developed countries (6) reported reasons for ICU refusal to be 23.9% in those assessed as too ill, 39.3% as too well and 15.1% related to insufficient resources. A study from Hong Kong found that 35% of patients were assessed as too ill and 21% as too well for ICU admission.(3) These comparisons suggest that the patient population for whom ICU beds are requested may be sicker at HJH; however, the lack of resources is of great concern as almost a third of the rejected patients were refused solely because of the lack of resources. This is almost double than that reported from developed countries.(6)
The 30-day outcome showed that almost 63% of patients in the study survived irrespective of admission to ICU. Interestingly, the patients admitted to ICU had a mortality rate of 22.5%, which is better than that reported by Joynt et al. (3) in Hong Kong who reported an ICU mortality rate of 37%. Moreover, there was an overall 23% survival benefit in those patients admitted to HJH ICU as compared to those who were refused admission. This could possibly suggest that admission criteria were too strict in that only relatively well patients were admitted in the current study. However, similar results to those in the current study were reported by Shmueli et al. (9) who demonstrated an overall 17.4% increased survival rate with ICU admission and Iapichino et al. (6) who reported a 27% reduction in mortality at 28 days with ICU admission.
Patients who were refused ICU admission due to lack of resources had a mortality rate of 19%, whereas the mortality rate for admitted patients was marginally higher at 22.4%. One would have expected a higher mortality in those refused admissions due to resource constraints. However, most of these patients would have still received critical care in the ward by means of mechanical ventilation where possible, inotropic support and increased monitoring by medical staff. Furthermore, aggregated data was collected anonymously from the ICU consultation forms; hence, ethical constraints prevented clinical data collection, which limits the comparison with regards to mortality.
Triage methods used by the ICU consultants at HJH at the time of the current study seemed to be accurate as only one (2.7%) patient was assessed as too ill for admission was alive at 30 days. Joynt et al. (3) noted a survival rate of 10% for the same group which is considerably higher. Patients assessed as too well for admission all survived to 30 days follow-up, again suggesting the triage efficacy of the ICU staff.
CONCLUSION
This study has shown that there is a high level of triage efficacy in the ICU at HJH. The allocation of beds between the disciplines is fairly equal, both with good survival benefits. The lack of ICU resources, either lack of ICU bed or nursing staff shortages, is an important limitation to access to ICU. The study also demonstrates a survival benefit with ICU admission. Thus strategies to improve ICU resources are suggested so that more patients can benefit from the survival benefit associated with ICU admission.
