Profile and length of stay of coronary artery bypass graft patients in the Cape metropolitan area.
In developed countries such the USA and Japan CABG surgery is one of the most common major operations. (6,7) In South Africa, where health care services are provided by both the public and private health sectors, (8) the burden of cardiothoracic surgery is largely borne by the private sector, which performs 860 operations per million annually as opposed to 59 per million in the public sector.8 Of our population of approximately 48 million, only 7.6 million (16% of the population) have access to medical aid. (9) The remaining 84% is solely dependent on the public health sector for specialised care such as cardiothoracic surgery. (8)
Only recently the former Minister of Health, Dr Tshabalala-Msimang, commented on the rising cost of health care, specifically in the private sector. She stated that there is little evidence that tariff increases have been accompanied by improvements in quality of care or health outcomes. (10)
According to Aggerwal et al., (11) 'the careful study of cardiac patients' demographics is essential as it impacts on patient management at every stage of care'. Physiotherapists in this country therefore need to know the possible implications of demographic differences with regard to provision of care. The purpose of this study was to establish (i) whether patients undergoing CABG surgery in Cape Town had a similar demographic profile (age, gender, race) and outcomes (mortality, incidence of postoperative pulmonary complications and LOS) to their international counterparts; and (ii) whether patient profile and outcomes were similar for the private and public health care sectors.
Setting and study design
This study was conducted in five of the six private hospitals that currently provide CABG surgery as well as the two state hospitals in the Cape metropolitan area. The sixth private hospital was not included in the study because it was not fully operational at the time of data collection. A multi-centre prospective cohort observational study design was used.
Sample and sampling procedure
All patients who underwent isolated (revascularisation only) elective or emergency CABG surgery in the seven hospitals during the period 15 August-15 November 2005 were included in the sample. Patients undergoing either elective or emergency surgery were identified prospectively from the patient register book or theatre list which is kept in the cardiothoracic intensive care unit.
A structured initial assessment (SIA) tool was developed by the researcher for the purpose of this study (appendix A). On the basis of the current literature, the following categories were included: demographic data (age, gender, race), pre-operative medical status (cardiac, renal and pulmonary status, level of activity), intra- and postoperative information (anaesthetic time, duration of intubation), and the outcome measures commonly used, such as postoperative pulmonary complications (PPCs) and LOS. A pilot study of the SIA tool was performed a month before the data collection period.
Theatre lists and patient register books were checked daily by qualified physiotherapists working at each of the seven hospitals to identify patients scheduled for CABG surgery. Once identified, patients were assessed by physiotherapists and the SIA tool was completed. In emergency cases all information was collected postoperatively by the same physiotherapists. Intra-operative information was collected by the attending physiotherapist postoperatively. Extubation times were obtained from patients' ICU flow charts. In the private hospitals, radiological reports were checked daily by the attending physiotherapist for the occurrence of PPCs and only the date of the initial occurrence was documented. In the absence of radiological reports, as in the state hospitals, an independent radiologist reported on the chest X-rays retrospectively. The completed SIA tool was collected from each hospital by the researcher on a weekly basis and cross-checked for any missing data. Data from completed SIA tools were then captured onto a spreadsheet.
Means and standard deviations were calculated using the Statistica and Microsoft Excel programmes where applicable. To determine relationships between different variables, the following statistical techniques were used:
* Analysis of variance (ANOVA) to determine possible differences in average measurements between various groups. In cases where it appeared that the ANOVA assumptions were violated, nonparametric bootstrap techniques were employed.
* Correlations to determine the relationships between pairs of measurements.
* Linear regression to determine the combined relationships between measurements, e.g. for age and pleural effusion and LOS.
* Logistic regression to determine the combined effects of measurements on a categorical variable.
* A p-value of [less than or equal to] 0.05 was used to indicate statistical significance.
* Probability calculations (odds ratios, ORs) were calculated and significant risk was identified by 95% confidence limits around ORs where neither 95% confidence limits encompass the value of 1.
Approval for the study was obtained through the Committee for Human Research, Stellenbosch University. All patient information obtained remained confidential.
A total of 254 patients were admitted to both private and state hospitals during the 3-month data collection period. More than 75% (N=187) of the data finally analysed were from private hospitals. A total of 9 patients were lost during the data collection period due to: (i) written consent not being obtained from 7 patients; (ii) the hospital records of 1 patient not being retrievable; and (iii) 1 patient refusing to participate in the study. Although 8 patients (private N=6, state N=2) died during the data collection period, their information was still used in the study as consent had been obtained prior to surgery. Therefore in total data for 245 patients were analysed.
Demographic and pre-operative medical status
The demographics of this population group, which included age, gender, race and body mass index (BMI), are depicted in Table I. Participants were predominantly male in both private and state hospitals. The mean age for the total sample was 60.9 ([+ or -] 10) years, and mean age differed minimally between hospital types (Table I). While differences in age and BMI between the private and state hospitals were not statistically significant, racial groups did vary between the institutions.
Mortality and postoperative pulmonary complications (PPCs)
The mortality rate was 3% (N=8). The incidences of the four most common PPCs after cardiac surgery (atelectasis, pleural effusion, pneumonia and pneumothorax) are depicted in Fig. 1. Only 35% (N=86) of the total sample did not develop any PPCs after surgery. PPCs were commonly reported within the first 3 days after surgery in both private and state hospitals.
The incidence of the four PPCs varied minimally between hospital types (Table II). Patients could present with more than one PPC; however, there was no statistical significance on the outcome of LOS (Fig. 2).
No correlation was found between the risk factors (age, gender, smoking history, time under anaesthesia and length of intubation) and occurrence of any of the four postoperative pulmonary complications. However, non-linear regression indicated that longer duration of anaesthesia tended to be associated with postoperative atelectasis, and increased age to be significant in prediction of pleural effusion.
Length of stay
The mean LOS for the total sample was 12.1 days ([+ or -] 5.5). Mean length of stay for state patients was 13.4 days ([+ or -] 7.1) and that for the private patients only 11.7 days ([+ or -] 4.8). Although there was a significant relationship between age and LOS in the private hospitals, the correlation (r=0.23) was not strong (Fig. 3).
The sample was divided into the group of participants staying for [greater than or equal to] 12 days and <12 days. Confidence intervals (95%) and ORs were calculated to ascertain whether the variables female gender, age and incidence of PPC were able to predict a LOS of more than 12 days (Table III).
With respect to gender, pre-operative risk factors and health behaviours, the current study sample was similar to that of international studies conducted on CABG surgery patients. (1-3,5,11-13) With regard to the outcomes of PPCs and mortality, the current study reported similar findings as well. (14-16) However, two distinct differences in the profile and outcome of the current study emerged, namely patients presenting for CABG surgery at a younger mean age and longer acute care LOS than in international studies. The mean age of 60.9 years reported in the current study is 10 years younger than that in international studies. (1,3,5,12,13) The older ages of populations in international studies have been attributed to an increase in the mean age in the elderly population in westernised countries. (1,3,5) The range of minimally invasive procedures and pharmacological techniques to delay surgical intervention developed over the past decade has also resulted in the population in international studies being older. Although these techniques are also widely used in South Africa, the ageing population has not increased to the same extent as in westernised countries.
[FIGURE 3 OMITTED]
The mean LOS in the current sample was more than double that reported in the current international literature. (17) In developed countries, such as the USA and Europe, patients undergoing CABG surgery have a postoperative LOS of only 4 days in acute care settings. (2,5,12,17,18) In the current study, age older than 60 years was the only predictor of a longer LOS (>12 days; OR 2.49 (significant), CI 1.33-4.65). Having age as the only predictor for a longer LOS could be attributed to the omission of variables such as APACHE score, bypass time, and previous myocardial infarction from the SIA tool.
Efficient use of health care resources is receiving increasing attention as health insurers constantly investigate ways to diminish the cost of expensive elective procedures such as CABG surgery. Postoperative LOS has long been identified as 'one of the chief drivers of hospital resource consumption by CABG surgery patients'. (17) When comparing LOS in the private and state hospitals, no statistically significant difference (p>0.05) was seen (11.7 v. 13.4 days). A possible reason for the seemingly longer LOS in state hospitals could be that some patients come from outlying areas or neighbouring provinces and need to wait for state transport before they can be discharged home. At the same time, the shorter LOS in the current international literature should be viewed in context as patients are likely to be discharged to a step-down facility rather than home. (5,19) According to Lazar et al., (19) patients who were discharged early (within 5 days) after CABG surgery spent on average an additional 10 days in step-down facilities. It must, however, be recognised that although step-down facilities allow for early discharge from acute care facilities, additional costs are still incurred. In the Cape metropolitan area there are only a few step-down facilities to which patients may be referred for prolonged care after CABG surgery. These facilities are exclusively private.
Reporting of PPCs after CABG surgery varies greatly between studies, with an incidence ranging between 6% and 88%. (15) This large range can be attributed in part to the variability of the PPCs reported after CABG surgery as well as variability in their definition. (15,20) The incidence and type of PPCs in the current study were no different to those in international studies, and did not negatively impact on the LOS or mortality rate of the sample. The question is therefore really whether the reporting of PPCs after CABG surgery is still valid or if we as therapists should be shifting our focus to a more holistic view using outcome measures such as health-related quality of life or functional capacity after CABG surgery.
The profile of CABG surgery patients in the Cape metropolitan area, while comparable to those in developed countries, none the less displayed two distinct differences, namely a younger population (<70 years of age) and a longer mean LOS, in both private and state hospitals. Although in the current study there were fewer admissions to state hospitals than to private hospitals, outcomes with regard to LOS and PPCs were similar, which may imply that management of CABG surgery patients in the two health care sectors in the Cape metropolitan area is comparable.
This study provides a very focused snapshot picture of the profile and outcome of patients admitted for CABG surgery in the South African context. It also raises interesting questions with regard to the postoperative management of these patients and the potential role of physiotherapy in reducing the LOS that need to be answered.
The author would like to thank Associate Professor J Jelsma (University of Cape Town) for assistance in data analysis and proofreading.
(1.) Fuster RG, Montero JA, Gill O, et al. Trends in coronary artery bypass surgery: Changing type of surgical patient. Rev Esp Cardiol 2005; 58(5): 512-522.
(2.) Abramov D, Tamariz MG, Fremes SE, et al. Trends in coronary artery bypass surgery results: A recent, 9-year study. Ann Thorac Surg 2000; 70: 84-90.
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Shamila Manie, MSc (Physiother), BSc (Physiother) School of Health and Rehabilitation Sciences, University of Cape Town
Susan Hanekom, BSc (Physiother), MSc (Physiother) Mary Faure, BA, MPhil, National Diploma (Physiother) Department of Physiotherapy, Stellenbosch University, Tygerberg, Western Cape
Table I. Demographic and pre-operative medical history Total sample (N=245) Private (N=187) % Age >70 yrs 52 43 23 <70 yrs 193 144 77 Mean age 60.9 ([+ or -] 10.0) 62.0 ([+ or -] 10.5) Gender Female 54 37 20 Male 191 150 80 Mean BMI 28.4 ([+ or -] 4.5) 28.4 ([+ or -] 4.4) Cardiac status Hypertension 165 115 62 Aortic stenosis 57 39 21 Unstable angina 189 147 79 Race White 169 153 82 Coloured 63 24 13 Black 9 7 4 Indian 4 3 2 Diabetic 68 50 27 Renal failure 9 4 2 Type of surgery Elective 187 145 77 Emergency 58 42 23 Health behaviour Smokers (yes) 157 113 61 Active life- 86 77 41 style (yes) Public (N=58) % Age >70 yrs 9 15 <70 yrs 49 85 Mean age 59.0 ([+ or -] 9.7) Gender Female 17 29 Male 41 71 Mean BMI 28.3 ([+ or -] 5.0) Cardiac status Hypertension 50 86 Aortic stenosis 18 31 Unstable angina 42 72 Race White 16 26 Coloured 39 67 Black 2 3 Indian 1 2 Diabetic 18 31 Renal failure 5 8 Type of surgery Elective 42 73 Emergency 16 27 Health behaviour Smokers (yes) 44 76 Active life- 9 16 style (yes) Table II. Incidence of PPCs (%): private v. state PPC Private State Pneumonia 12 <1 Atelectasis 46 48 Pleural effusion 30 43 Pneumothorax <1 <1 Table III. Odds ratios for LOS Variable OR Upper 95% CI Lower 95% CI Female gender 1.34 0.67 2.69 Age >60 2.49 * 1.33 * 4.65 * PPC 1.35 0.73 2.49 Female gender 1.39 0.59 3.23 & PPC * Significant values. Fig. 1. Incidence of PPCs (N=245). ATELECTASIS 47% PL. EFFUSION 34% PNEUMONIA 11% PNEUMOTHORAX 2% Note: Table made from bar graph. Fig. 2. Relationship between LOS and number of PPCs. 1 11.23 2 12.75 3 12.43 Note: Table made from line graph.
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|Author:||Manie, Shamila; Hanekom, Susan; Faure, Mary|
|Publication:||Southern African Journal of Critical Care|
|Article Type:||Clinical report|
|Date:||Dec 1, 2008|
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