Background
Current predictions indicate that by 2050, the percentage of the population that will be 80 years old or older will double, representing nearly 10% of the European and 8% of the North American population [
1]. Furthermore, female life expectancy is anticipated to break the 90-year barrier in several industrialised countries [
2]; the number of centenarians in the world is projected to increase rapidly from approximately 441,000 in 2013 to 3.4 million in 2050 and 20.1 million in 2100 [
3]. An important consequence of longer life expectancies is that this growth of the ageing population may result in increasing demand for critical care and affect the composition of the patient population cared for in ICUs. This will likely lead to an increase in the number of new critical care beds, which are particularly resource-consuming. Thus, the consequences of the increasingly ageing population on the public health system need to be adequately described and understood, especially concerning ICU hospitalisation.
Previous reports demonstrate that in Europe, elderly patients comprise 10–20% of all ICU admissions [
4‐
10]. Longitudinal studies further demonstrate that the proportion of patients admitted to the ICU who are elderly is increasing over time [
4]. Most studies considering ICU admission policies and their potential benefits have focused on the elderly as a single entity. We believe that the discussion should be disease specific. It is questionable to discuss hospital admission policies for patients based solely on their advanced age without considering the acute disease leading to ICU admission. Indeed, as critical care admissions for a particular diagnosis decline, those due to other diseases may replace them. These shifts in-hospital diagnoses may mask increases in the incidence of specific diseases. A recent retrospective study of a 7-year period (in the Netherlands) demonstrated a crude decrease in ICU and in-hospital mortality (4.6% and 9.7%, respectively) for patients 80 years and older [
11]. Interestingly, this decrease was not observed in all the subgroups studied. In particular, the ICU mortality in patients 80 and over who were admitted for a medical reason was constant during the study period, in contrast to the other admission subgroups. From our point of view, a focus on respiratory infections is of particular interest, because these infections are strongly associated with old age. Pneumonia was considered to be “the old man’s friend”, a terminal event leading to the rapid and relatively painless death of the elderly, avoiding “cold gradations of decay so distressing to himself and to his friends”, as described in 1898 by W. Osler [
12]. Today, pneumonia is still associated with considerable mortality (10% of in-hospital mortalities according to population-based studies [
13]), but it does not systematically sentence the elderly to death. Consequently, pneumonia and more generally acute respiratory infections (ARI) lead to the utilisation of substantial healthcare resources, in particular ICU hospitalisation for advanced monitoring and live support. We hypothesised that the increase in the percentage of ageing patients in the population is likely to inevitably increase hospital stays for ARI and the utilisation of ICU resources. The objective of our study was to describe and assess trends in demographics over a decade among elderly patients admitted to an ICU for ARI.
Discussion
This study of more than 3.8 million adult hospital stays in a French region provides a contemporary view of major epidemiological changes occurring over the last decade for patients hospitalised for ARI. We observed a rise in the number of ARI hospitalisations despite a statistically significant decline in the number of total hospitalisations (all indications combined) over the period. This substantial increase in the number of hospitalisations attributed to respiratory infections, together with an increasing demand for ICU services, led to a striking increase in the overall utilisation of ICU resources: 2038 ICU stays were recorded with ARI as the main diagnosis in 2015, compared with only 740 stays 10 years earlier (for a region of 2.5 million inhabitants). The hospitalisation of elderly patients in critical care services steadily increased for all age groups, but was greater for patients over 85 years old. Notably, ICU admissions for nonagenarians increased 5.8-fold during the decade with a marked decrease in mortality.
Respiratory infections occur mostly in elderly patients who are highly susceptible for reasons that are still poorly understood. Here, we confirmed an age-related increase in incidence, which reached 5% per year for patients over 90 years old. We did not define a cut-off value for “old” or “elderly”, because the demographic transition in Western countries is rapidly making previous definitions obsolete. Thus, the definition of an “elderly patient” is variable, and accurate comparisons between various studies are difficult. The age thresholds used in the literature to define a patient as “elderly” vary from 60 to 80 years [
18‐
21] and from 80 to 90 for “very elderly” [
11,
22,
23]. Indeed, the criteria to define an “elderly” patient are in constant flux and we preferred to use age groups instead.
Together with previous reports [
22,
24], our study further demonstrates how ARI in the elderly are increasingly becoming a major public health issue. This raises important questions for future work. An important one is whether this growth in ICU hospitalisations for elderly patients with ARI is necessary to meet the demands of an expanding population requiring intensive care or whether ICU beds are being oversupplied and filled with patients who might be cared for in less-intense settings at lower cost with similar outcomes [
25]. SAPS II scores and the rate of patients requiring invasive mechanical ventilation or vasopressor treatment were constant over the study period. Furthermore, the increase in ARI hospitalisations was not associated with a decrease in ICU length of stay or overall ICU case fatality rate (Fig.
5c). These results support the hypothesis that ICU admissions were driven by a real expansion of critically ill patients.
Above the individual consideration lies the societal question: how will funding agencies, policy makers and ICU caregivers face this increasing demand? Hospital stays for ARI have almost doubled over the last decade in the studied region, with a 2.7-fold increase for those in the ICU. Valley et al. [
26] reported that admission to the ICU for pneumonia patients older than 64 years was associated with reduced 30-day mortality with no significant cost increase. This finding may be now assessed and confirmed for patients 85 y/o or older, for whom we observed the most important changing trends in ICU hospitalisation for ARI. Finally, the observed heterogeneity regarding triage for elderly patients with ARI highlights the need to define clear criteria for ICU admission.
Our study should be interpreted in the context of several limitations. First, the use of administrative hospital databases introduced an inherent bias that should be taken into consideration. Strengths and limitations of using healthcare databases for epidemiological purposes have already been extensively discussed [
27‐
31]. Briefly, the PMSI (the national hospital healthcare database used here) was initially designed for billing purposes but now appears to be a powerful tool for epidemiological surveillance. However, one has to keep in mind that observed changes in disease patterns could be biased by variations in coding practices due to financial incentives for obtaining higher reimbursement rates [
32]. Hence, inter-rater reliability could represent an important limitation, particularly when a single code is used. To overcome this issue, we built our case definition using an algorithm based on different diagnosis codes and their positions, and taking the variability of the coding practices into consideration. The use of coding algorithms has been validated in numerous medical fields, especially in infectious diseases. We and others have previously demonstrated that the use of an appropriate algorithm provides a high positive predictive value for a case definition and an excellent negative predictive value [
30,
33]. Second, some concerning issues are not recorded in this database. For instance, increasing pollution over the past decade influences respiratory admissions; our study did not allow for testing correlations between pollution indexes and the increase in ARI hospitalisations. Similarly, some risk factors (i.e. smoking status) or protective factors (i.e. vaccination) could not be reliably studied. Third, this study population is representative of only one country, so the results may not be generalisable around the globe. Overall, the use of administrative hospital databases has strengths and weaknesses. But rather than opposing studies based on administrative data with studies based on clinical databases, future challenges will probably be to implement novel complementary strategies combining the advantages of both approaches. The major interest of this database is the exhaustive record of all patients hospitalised in the studied region during the 10-year period without initial selection bias, giving reliable information on care in real life. This could be considered a potent strategy to provide an early warning of the rise of hospitalisations for ARI. Results could be completed by more granular analyses focusing on clinical data to further decipher and explain these observations.
In conclusion, we observed a substantial increase in ARI diagnoses associated with hospitalisation between 2006 and 2015 with a growing demand for critical care services. Both the absolute number and the percentage of ICU admissions that were elderly increased over the last decade, driving an overall 2.7-fold increase in the number of ICU stays for ARI. Care delivered in the ICU contributes significantly to the expansion of healthcare spending. This work should guide physicians and healthcare administrators in their approach to policies concerning ICU admission and organisation, especially for the elderly.
Authors’ contributions
AG, LG-G and LL conceived and designed the study, analysed the data and wrote the first draft of the manuscript. LL, CH and CG performed the data retrieval. AG, LG-G, CH and CG performed the statistical analysis. YG, KMS, MS-T, PFD and ER made substantial contributions to the interpretation of data and were involved in drafting the manuscript and made critical revisions of the discussion section. All authors read and approved the final manuscript.