This study investigated the prevalence of long ICU stay using admission data for SWS residents over three years. The study found the following: 1) ICU admission for patients with diabetes is greater if they are admitted to hospital. 2), Patients admitted to ICU for >48 hours have poorer outcomes and increased risk of death. 3) Cardiovascular disease is a risk factor for long stay in ICU in patients with and without diabetes, and nervous system disease and female sex are risk factors for those without diabetes. While other investigators have reported findings similar to ours13, 24, the present study provided a detailed assessment of the factors associated with long ICU stay among admitted adults in an Australian setting using a nationally representative database. These findings suggest that more interventions in primary care or outpatient care, including introducing integrated care systems25, may help improve diabetes care, avoid hospital admissions or shorten the patients’ stay in ICU, as noted previously26, 27.
The findings that long ICU stay was associated with increased risk of death in admission is contradictory to previous report of that the outcomes in people with long and short ICU stay in Saudi Arabia were similar13. Our findings must be interpreted in the proper context, keeping in mind that the definition of long ICU stay in the previous study was >14 days, involved only those in the medical/surgical ICU of a tertiary-care teaching hospital (not in primary care)13. In another study22 where prolonged stay was defined as >48 hrs in ICU, the authors found that 19% of patients who underwent coronary bypass surgery had a prolonged ICU stay and this was a risk factor for death and readmission. Although some studies have also used a different definition for prolonged ICU stay (range from 3 to 14 days), they included only surgical patients28, 29, people with diabetes complications30 or those with intracerebral haemorrhage25. The study conclusions were limited to a very small number of patients (<5% of the original population), but all of the studies agree that prolonged ICU stay was associated with higher mortality rate (range from 15–33%). Nevertheless, half of the patients in the present study were in ICU for >48hrs and the present findings suggest that this high-risk group is worth investing to reduce the cost of care. This information is useful as decisions about continuing or withholding aggressive intensive care management based on long ICU stay may yield better outcomes. Emphasis should also improve ICU efficiency for those with and without diabetes without compromising the level of care.
The study identified certain factors associated with long ICU stay among admitted people in SWS, which can help plan strategies to improve resource utilization. The presence of a circulatory system disease in people with and without diabetes increased the likelihood of long ICU stay. In addition, having a circulatory or nervous disease was associated with higher likelihood of having a long stay in ICU in people without diabetes. Since patients with comorbidities stay longer and utilize more resources13, 31, they constitute groups of patients worth investing in. It is also important that nurses recruited for ICU care have the proper background to care for patients with circulatory and nervous system diseases. It appears that patients admitted in the last year of this study (2016-2017) were less likely to stay longer than 48 hrs in ICU compared with those admitted in 2014-15 indicating some improvement in ICU care across SWS public hospitals.
The increased likelihood for ICU admission in people with diabetes compared with those without diabetes in Australia may reflect pre-existing comorbidity in people with diabetes. Among critically ill patients in India, 13.9% of the 1283 admissions in ICU over 4 years were established cases of diabetes, with 5.0% diagnosed as diabetes after admission. Past studies17, 32 have also reported significant interaction between pre-existing hyperglycaemia and the association between acute glycaemia and mortality among people with diabetes in ICU17. In-hospital control of glucose in people with diabetes receiving ICU care is associated with a reduced length of hospital stay and lower mortality rate32. These findings suggest that it is even more important to deal with diabetes management in primary care, help prevent hospital admission in the first place, and reduce the risk of ICU admissions and mortality.
The cost of hospital admission to patients may be a factor in the reduced risk of admissions in other countries, but in Australia, public hospitals do not charge for ICU care and hospital stay for Australian residents/citizens. Therefore, in this study, having private health insurance coverage does not appear to influence the length of stay in ICU and may not be a surrogate for socioeconomic status. In a study conducted in France among a low-income population with free access to health care, the researchers found higher hospitalisation and mortality rates for many diseases among people with access to free government health care than those without free access33. However, ICU care was not accessed.
ICUs admission is associated with greater utilization of hospital resources 13 and more in people with diabetes 34 with studies suggesting that this may be due the interaction between the longer LoS in hospital and the potential to receive emergency or intensive care during admission 34–36 . Lee et al 37 suggested that it cost the Australian government an average of A$5764 per admission to care for an individual with diabetes, and the cost increases by 1.3 times in people with diabetes who have both micro-and macrovascular complications. In this study, we found that people with diabetes needed more ICU care indicating the presence of complications. In a study using the Hospital Pricing Authority, researchers found that the Australian government spent about $210 per bed-hour or $5040 per bed-day for any individual who is admitted to ICU 8 . From this estimates to work out the cost per admitted patient in this study, we found that it cost about $5390 per year for those with diabetes and $5428 for those without diabetes in hospital across SWS with greater cost estimates when caring for those aged 45-54yrs. Although these are likely to be underestimated, because calculations were based on 2013 cost data, they did not consider the non-healthcare cost including costs of adverse events, glucose monitoring 37 and/or the impact of undiagnosed diabetes 34 both of which attract a higher cost; this group of patients with long-stay should be targeted for promotion of more optimal bed utilization by decreasing ICU length of stay. In the UK, the median cost per patient day in an ICU was estimated at US$1356 (range $1242–1745) 38 . A previous systematic review suggested that a regular source of primary care and a well-controlled HbA1c would reduce the likelihood of hospitalisation in people with diabetes 39 .
Strengths of this study include the provision of evidence of increased ICU care for general admissions of people with diabetes in Australia, and the large number of people included in the study as well as the use of place of residence rather than admitting hospital to define the population. The latter removes the bias associated with secondary/tertiary care centres, as well as including people admitted to hospitals outside the district. The main limitations of the study are due to the nature of the data being used (secondary data analysis). The dataset has the potential to be subject to coding errors at source, as with all administrative databases40. Although a previous study41 found good agreement between self-reported diabetes and coded diabetes, a much higher inpatient prevalence of diabetes was found in an audit of inpatients in Melbourne.42 Due to the higher length of stay for diabetes, the point prevalence will always be higher in hospital, but not as much when datasets like APDC look at all admissions. Data on the type of diabetes was not extracted, country of birth was used as ethnicity and indigeneity are not routinely available. Additionally, de-identified data did not allow for the identification of multiple admissions, and data were not available for one of the seven LGAs in the district. Nobody mass index or glucose data was used in this study, and socioeconomic status data were also not available.