Abstract
Abstract
Objectives
Rural populations experience poorer health outcomes than urban counterparts globally. Limited studies have examined the impact of geographical location—specifically travel distance/time and rurality—on intensive care unit (ICU) outcomes. This scoping review aimed to map literature on geographical location and ICU outcomes to better inform policy and improve ICU access in underserved communities.
Design
Scoping review.
Data sources
MEDLINE, CINAHL and Embase were searched through to 8 May 2025. Grey literature was identified through ProQuest Dissertations and Theses Global, including dissertations, theses and conference proceedings.
Eligibility criteria for selecting studies
Studies examining the impact of geographical location (rurality and/or travel distance/time) on ICU outcomes in adult populations were included. No restrictions were placed on country, healthcare setting or date of publication. Peer-reviewed primary studies and grey literature were eligible; editorials, commentaries and reviews were excluded.
Data extraction and synthesis
Two reviewers independently extracted study characteristics, rurality definitions, travel distance/time measures and ICU outcomes using a standardised form and synthesised descriptively.
Results
23 articles and 1 conference abstract; all were retrospective studies. 23 studies reported on rurality with 20 specifying the definition used. Six studies reported travel distance/time, all detailing measurement methods. 12 studies mentioned baseline patient comorbidities, 18 reported ICU admissions and 4 hospital/ICU readmissions. More studies reported longer ICU length of stay and greater ICU intervention use among rural compared with urban/metropolitan patients, although mortality findings were inconsistent. Heterogeneity limited direct comparison. No clear association was found between travel distance/time and ICU outcomes.
Conclusions
Inconsistent rurality definitions complicated comparisons. The mapped literature reported longer ICU LOS and greater intervention use for rural compared with urban/metropolitan patients; however, mortality findings were inconsistent with no predictive pattern. No clear association was observed between travel distance/time and ICU outcomes. Future research should adopt standardised rurality definitions, account for preadmission health status and focus on condition specific contexts to inform policy.
Keywords: Intensive Care Units, Health Services Accessibility, Health Equity
STRENGTHS AND LIMITATIONS OF THIS STUDY.
The review followed the Preferred Reporting Items for Systematic Review and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline and the Arksey and O’Malley framework (with Levac’s refinement).
A comprehensive multidatabase and grey literature search was conducted, with independent duplicate screening and data extraction performed using Covidence following a pilot calibration.
Drawing on identified gaps in existing literature, we proposed a minimum reporting framework to standardise future research in this area.
The exclusion of records without English-language abstracts may have introduced language and geographical bias.
The disproportionate representation of Organisation for Economic Co-operation and Development (OECD)-member countries among included studies, reflecting limited available literature from other regions, may limit the generalisability of these findings to developing nations.
Introduction
Globally, health inequalities affect both developing and developed countries.1 2 Rural and remote populations carry a disproportionate burden of both chronic diseases (such as cardiovascular disease, diabetes and cancer) and non-chronic conditions (including trauma, poor dental health and mental health-related illness).3,6 In Australia, these disparities are particularly pronounced. Rural and remote areas account for 28% of the population and cover 98% of the country’s land mass.7 8 Residents of these areas experience poorer health outcomes than their urban counterparts, including higher rates of chronic disease, greater engagement in risky health behaviours and shorter overall life expectancy.7 9 10 Additionally, limited access to preventive healthcare services and the underutilisation of available resources contribute to these disparities.11,13 Notably, Aboriginal and Torres Strait Islander Australians (First Nations Peoples) are disproportionately admitted to intensive care units (ICUs), possibly because of limited access to primary care.14 Nonetheless, the evidence to date has not clarified whether these inequities are reflected in the patients admitted to ICUs.
ICUs are essential in managing critically ill patients, and markedly affect survival and long-term recovery.15 Over 200 000 adults are admitted to ICUs across Australia and New Zealand annually.16 Among these patients, 52% are admitted from operating theatres, 26% are admitted from emergency departments, 16% are admitted from hospital wards and 6% are admitted from other sources.16 The ICU mortality rates within Australia and New Zealand are 8% and 10%, respectively, both of which are below the global average of 13%.16 However, ICUs are concentrated in densely populated urban centres, thus leading to substantial access barriers for rural and remote populations.17 Studies to date have reported conflicting findings. Whereas the increase in mortality seen in rural populations might be expected to be reflected in the outcomes of critically ill patients, such evidence is lacking.18 Thus, a question arises as to whether geographical disparities persist in outcomes after patients reach the ICU.
Geographical location encompasses factors such as rurality of residence, distance to care and local socioeconomic conditions. Although the impact of socioeconomic status on ICU outcomes has been explored,19 minimal research has focused specifically on how other geographical factors influence ICU outcomes. Addressing this gap in the literature is critical, as delays in access and admission can significantly affect outcomes for time-sensitive ICU admissions, including stroke, sepsis, trauma and critically ill patients more broadly.20 21
Furthermore, ICU resources in rural areas, in contrast to urban areas, are often strained by lower staffing ratios, limited specialist availability and fewer high-dependency capabilities, such as access to mechanical ventilation.22 Despite an increasing body of evidence highlighting geographical disparities in healthcare,17 18 23 substantial gaps remain in understanding how these disparities affect ICU outcomes.
Existing studies have often been observational and context-specific, with inconsistent definitions of rurality, socioeconomic status and ICU resources, limiting comparability across settings. To address these gaps, a clearer understanding of how geographical location influences ICU outcomes is essential. This scoping review therefore aims to map and synthesise the available evidence for adults admitted to ICUs, focusing on geographical factors such as rurality and travel distance/time, within the ICU setting. By highlighting gaps in current knowledge, the review seeks to inform future policy and practice, including strategies for resource allocation, infrastructure planning and the development of solutions such as Tele-ICU systems, which have shown promise in enhancing care quality and reducing mortality in rural hospitals but remain inconsistently implemented.24
Study objectives
This scoping review was aimed at investigating how studies have explored the impact of geographical location on ICU outcomes in an adult population. This review also addressed the following seven aims:
Synthesise demographic and study level information for the included populations, including age and sex distribution, country and study design.
Explore how existing studies define rural/remote populations, and explain the differences between countries and the scales used.
Summarise how existing studies have reported travel distance/time.
Identify the pre-existing comorbidities or risk classification scales that have been reported.
Identify ICU admission rates (including likelihood of admission), inpatient mortality, ICU length of stay (LOS), ICU/hospital readmission rates and ICU interventions.
Summarise the reported differences in ICU outcomes between rural/remote and urban/metropolitan populations.
Assess whether travel distance or travel time to ICU is associated with differences in patient outcomes, separately from rural/urban classification where reported.
Materials and methods
Study methods
The scoping review followed the Preferred Reporting Items for Systematic Review and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, to ensure that the scoping review maintained rigour and replicability. Moreover, the methodological framework described by Arksey and O’Malley, and extended by Levac,25 was used. Critical appraisal was performed using the Scottish Intercollegiate Guidelines Network (SIGN) cohort study checklist.
Search strategy
An initial exploratory search in Google Scholar and PubMed was conducted to identify key terms related to geographical location, rural/remote populations, travel distance/time and ICU outcomes. This preliminary step helped refine the formal search strategy. The final search strategies were then designed by a senior medical librarian and implemented in MEDLINE (OVID), Embase (OVID) and CINAHL (EBSCO). Grey literature was identified through ProQuest Dissertations and Theses Global, including unpublished data, dissertations, theses and full-text conference proceedings. Additional references were retrieved by screening the bibliographies of relevant articles. The complete search strategies, including medical subject headings (MeSH) and text words for ICU, geographical location, rural/urban/suburban/remote populations and travel distance/time, are provided in online supplemental file 1.
Types of studies and eligibility criteria
This scoping review included primary empirical research studies, conference proceedings, theses and dissertations and abstracts, but excluded editorials. Studies in adult populations admitted to ICUs were included without restrictions on geographical setting or on publication date. Studies including paediatric patients were excluded. The eligibility criteria were as follows: included populations were patients admitted to ICUs, critical care units, coronary care units, or burn care units.
Studies were also required to contain at least one ICU-related outcome (eg, admission rates, mortality, length of stay and ICU interventions or readmissions), and to report relevant information on geographical location, including the following: identification of rural or remote populations (with or without the scale used for definition) in addition to a comparator group (eg, urban or metropolitan), and travel time or distance from a patient’s residential location (area or postcode) to the ICU facility. A summary of this criterion is described in table 1.
Table 1. Inclusion and exclusion criteria relating to population, context, concept and types of evidence included.
| Domain | Inclusion criteria | Exclusion criteria |
|---|---|---|
| Population | Human studies involving adult populations |
|
| Context | Adult patients admitted to ICUs, including any one of the following:
|
|
| Concept | Studies examining the geographical factors of patients, including:
|
|
| Types of evidence | Primary empirical studies, including:
|
|
ICU, intensive care unit.
Only records with English-language abstracts were eligible for screening. Where an English abstract met the eligibility criteria but the full text was not in English, the full text was translated and assessed. Although focusing solely on English-language sources might have introduced bias and affected the generalisability of the findings to non-English-speaking regions, we deemed this limitation acceptable, given that the review was scoping in nature and not intended to inform evidence-based practice.
Study selection and screening procedures
The review was conducted with the online systematic review platform Covidence. The screening process involved two stages. Initially, two study reviewers (JZ and CR) independently evaluated the titles and abstracts for eligibility. A pilot screening of the first 75 citations was undertaken to ensure consistency in applying the eligibility criteria. Inter-rater reliability was assessed with Cohen’s kappa statistic, interpreted as follows: ≤0 (no agreement), 0.01–0.20 (slight agreement), 0.21–0.40 (fair agreement), 0.41–0.60 (moderate agreement), 0.61–0.80 (substantial agreement) and 0.81–1.00 (near-perfect agreement).26 A threshold kappa value of ≥0.80 was considered acceptable. Discrepancies during screening were resolved through discussion or adjudication by a third reviewer (LW), if required. The data-charting form was refined according to any issues identified during this process.
Two reviewers (JZ and CR) then retrieved and independently screened the full-text articles of all relevant and potentially relevant studies, and a third reviewer (LW) resolved any discrepancies. Studies that did not meet the inclusion criteria were excluded. The reasons for exclusion at the full-text stage were documented and reported in the review. The study selection process, including the number of sources screened, assessed for eligibility and included in the review, was documented in a PRISMA flow diagram in accordance with PRISMA-ScR guidelines.27
Data extraction
Studies that met the inclusion criteria were organised into an Excel spreadsheet to ensure that all data were captured. This process was performed independently by two reviewers (JZ and CR), and any disagreements were resolved through consultation with a third reviewer (LW) when required.
Data presentation
The synthesis is presented in a descriptive format in tabular form. Data on ICU outcomes were stratified by key geographical factors, including rurality/remoteness and travel distance/time to ICU facilities, as well as by country, to highlight potential variations in clinical outcomes across population groups and settings. Common definitions of rurality and reported comorbidity scales are presented in tables.
Patient and public involvement
This review analysed existing research studies and did not involve patients or members of the public.
Results
The search yielded 8416 records for screening; an additional nine articles were obtained from reference list searching, and three were obtained from a systematic review.23 A total of 174 articles were eligible for full text screening, of which 24 were included in this scoping review. Figure 1 shows the PRISMA flow diagram of this search strategy. Pilot screening of the first 75 citations demonstrated 97.3% inter-rater agreement (73/75 citations concordant), with two discrepancies resolved through discussion. At the full-text screening stage, inter-rater agreement was near-perfect (Cohen’s κ=0.95), with two discrepancies resolved by a third reviewer (LW).
Figure 1. PRISMA flow diagram of study identification, screening and inclusion. ICU, intensive care unit; NICU, neonatal ICU; PICU, paediatric ICU; PRISMA, Preferred Reporting Items for Systematic Review and Meta-Analyses.
Study characteristics
All studies in this review were published in English between 2005 and 2025. Of the 24 studies, all were retrospective, including 23 full-text journal articles and 1 conference abstract. Of the 24 studies, 22 were conducted in Organisation for Economic Co-operation and Development (OECD) member countries: the USA (n=9), Australia (n=7), Canada (n=3), Finland (n=1), United Kingdom/Scotland (n=1) and Spain (n=1). Two studies were conducted in South Africa, the only non-OECD country in the included studies. OECD countries were defined according to the OECD membership list as of 2023, which includes 38 member countries.28 A summary of these characteristics can be seen in table 2, while ICU outcomes and relevant comorbidities reported by the publications are summarised in table 3.
Table 2. 
Characteristics of the publications included in this scoping review.
| Author | Country of study | No. patients | Male patients No. (%) | Retrospective study design? | Rural status classified | Scale/definition used for rurality? | Rurality determined by home residence? | Reported travel distance/time |
|---|---|---|---|---|---|---|---|---|
| Holladay Ford et al29 | USA | 92 975 | 47 689 (51.3) | Y | Y | N | Y | N |
| Nickel et al30 | USA | 214 955 | 106 276 (49.4) | Y | Y | Y | Y | N |
| Paynter et al31 | Australia | 3376 | 2457 (72.7) | Y | Y | Y | Y | Y |
| Aamodt et al32 | USA | 53 279 | 30 341 (57.0) | Y | Y | Y | Y | N |
| Greenhouse et al33 | USA | 220 848 | 198 919 (90.1) | Y | Y | Y | Y | N |
| Schroeder et al34 | USA | 1545 | 1292 (83.6) | Y | Y | Y | Y | N |
| Lee et al35 | South Africa | 323 | 201 (62) | Y | Y | Y | Y | N |
| Harrington et al36 | USA | 25 541 | 0 (0) | Y | Y | Y | Y | N |
| Cerni et al37 | Australia | 3546 | 2130 (60.1) | Y | Y | Y | Y | Y |
| Hamilton et al38 | USA | 155 | 74 (47.7) | Y | Y | Y | Y | N |
| Magallón-Botaya et al39 | Spain | 6286 | 2738 (43.6) | Y | Y | Y | Y | Y |
| Mann et al40 | Canada | 342 | 141 (41.2) | Y | Y | Y | Y | N |
| Kozakewich et al41 | USA | 35 618 | 18 722 (52.6) | Y | Y | Y | Y | N |
| Wong et al42 | Canada | 79 | 65 (82.3) | Y | Y | Y | Y | N |
| Aoyama et al43 | Canada | 3 157 248 | 0 (0) | Y | Y | N | Y | N |
| Raatiniemi et al44 | Finland | 472 | 330 (69.9) | Y | Y | Y | N | N |
| Shiraev and Condous45 | Australia | 532 | 373 (70.1) | Y | Y | Y | Y | N |
| Gessert et al46 | USA | 3710 | 877 (23.6) | Y | Y | Y | N | N |
| Paynter et al47 | Australia | 23 719 | 13 088 (55.2) | Y | Y | Y | Y | Y |
| Flabouris et al48 | Australia | 218 709 | 139 703 (63.9) | Y | Y | Y | Y | Y |
| Kong et al49 | South Africa | 102 | 94 (92) | Y | Y | Y | N | N |
| McGuffie et al50 | Scotland | 4636 | 2841 (61.3) | Y | Y | Y | N | N |
| Fatovich et al51 | Australia | 3333 | 2404 (72.1) | Y | Y | N | N | N |
| D’Arcy et al52 | Australia | 262 | 175 (66.8) | Y | N | N/A | N/A | Y |
N, no; N/A, not available; Y, yes.
Table 3. 
ICU outcomes and prior comorbidities reported by the included publications within this scoping review.
| Author | ICU admission | ICU mortality | Length of ICU stay | ICU interventions | ICU/hospital readmission | Relevant comorbidities mentioned? |
|---|---|---|---|---|---|---|
| Holladay Ford et al29 | Y | N | N | N | Y | N |
| Nickel et al30 | Y | Y | N | N | N | Y |
| Paynter et al31 | N | Y | N | N | N | Y |
| Aamodt et al32 | Y | N | N | Y | Y | N |
| Greenhouse et al33 | Y | N | N | N | N | N |
| Schroeder et al34 | Y | Y | Y | N | N | Y |
| Lee et al35 | Y | N | Y | Y | N | Y |
| Harrington et al36 | Y | Y | N | N | N | N |
| Cerni et al37 | Y | N | N | Y | N | Y |
| Hamilton et al38 | Y | Y | Y | Y | Y | Y |
| Magallón-Botaya et al39 | Y | N | N | N | N | N |
| Mann et al40 | Y | Y | Y | Y | N | Y |
| Kozakewich et al41 | N | N | Y | Y | Y | N |
| Wong et al42 | Y | Y | Y | N | N | Y |
| Aoyama et al43 | Y | N | N | N | N | N |
| Raatiniemi et al44 | Y | Y | Y | Y | N | Y |
| Shiraev and Condous45 | Y | N | N | N | N | N |
| Gessert et al46 | Y | N | N | N | N | N |
| Paynter et al47 | N | Y | N | N | N | N |
| Flabouris et al48 | N | Y | Y | N | N | Y |
| Kong et al49 | Y | N | N | N | N | N |
| McGuffie et al50 | N | N | Y | N | N | N |
| Fatovich et al51 | Y | N | Y | N | N | Y |
| D’Arcy et al52 | N | N | Y | Y | N | Y |
ICU, intensive care unit; N, no; Y, yes.
Risk of bias
Using the Scottish Intercollegiate Guidelines Network (SIGN) cohort study checklist, we classified the 24 retrospective studies29,52 as having acceptable methodological quality. Residual confounding was common, and no study was considered high quality. The conference abstract was included but provided limited methodological detail.
Patient characteristics
The 24 studies included 4 071 591 participants. Sex distribution was available for all 24 included studies. Two studies36 43 included female-only maternal/obstetric ICU cohorts, both reporting maternal ICU outcomes rather than neonatal admissions. Excluding these two female-only studies, the weighted proportion of male participants among the remaining 2229,3537mixed-sex studies was 64.2%.
Geographical location
23 studies29,51 reported a rural or remote group alongside a relevant comparator and subsequent ICU outcomes. 1829,4345 47 48 of those studies used patient residence to determine rurality or distance to ICU. Four studies4449,51 used trauma location, and one study used nursing home location to determine patient rurality.46 An evidence map of what geographical factors were reported alongside the various ICU outcomes is shown in figure 2. 20 studies30,4244 provided a scale indicating how rurality was determined. The commonly used rurality classifications with their defining characteristics are summarised in online supplemental file 2. All six studies31 37 39 47 48 52 reporting distance or travel time reported the scale/measuring system used. The frequently used urban-rural classification schemes53 54 55 56 57 58 59 60 are also presented in online supplemental file 2.
Figure 2. Evidence map displaying the number of studies reporting rurality/travel-related factors and ICU-related outcomes. ICU, intensive care unit; LOS, length of stay.
Types of ICU outcomes reported
18 studies2930 32,40 42 reported ICU admissions. 10 studies30 31 34 36 38 40 42 44 47 48 reported ICU mortality, and 11 studies3435 38 40,42 44 48 50 reported ICU LOS. Eight studies reported ICU interventions,32 35 37 38 40 41 44 52 with the reported interventions including mechanical ventilation,32 35 37 41 52 intubation,38 40 respiratory therapy,44 percutaneous endoscopic gastrostomy feeding32 and blood transfusion.32 Four studies reported hospital (n=3)29 38 41 and ICU (n=1)32 readmission rates. 12 studies30 31 34 35 37 38 40 42 44 48 51 52 reported baseline comorbidities and/or risk of death scale numbers.
Table 4 summarises outcomes between rural and non-rural patients. Table 5 summarises ICU outcomes among studies reporting comorbidity, illness-severity, or risk-adjustment measures. Table 6 summarises ICU outcomes for patients according to travel distance/times.
Table 4. ICU outcomes for rural patients compared with urban patients in OECD and non-OECD countries.
| Country of study | Author | ICU admission | ICU mortality | Length of ICU stay | ICU interventions | Hospital/ICU readmission |
|---|---|---|---|---|---|---|
| OECD member countries | ||||||
| USA | Holladay Ford et al29 | Less likely | N/A | N/A | N/A | More likely |
| Aamodt et al32 | Less likely | N/A | N/A | No difference | No difference | |
| Greenhouse et al33 | Less likely | N/A | N/A | N/A | N/A | |
| Harrington et al36 | More likely | Higher | N/A | N/A | N/A | |
| Kozakewich et al41 | N/A | N/A | Longer | Less MV time and use | No difference | |
| Gessert et al46 | Less likely | N/A | N/A | N/A | N/A | |
| Canada | Aoyama et al43 | More likely | N/A | N/A | N/A | N/A |
| Australia |
Shiraev and Condous45 | Less likely | N/A | N/A | N/A | N/A |
| Paynter et al47 | N/A | No difference | N/A | N/A | N/A | |
| Scotland | McGuffie et al50 | N/A | N/A | No difference | N/A | N/A |
| Spain | Magallón-Botaya et al39 | More likely | N/A | N/A | N/A | N/A |
| Non-OECD member countries | ||||||
| South Africa | Kong et al49 | No difference | N/A | N/A | N/A | N/A |
ICU, intensive care unit; MV, mechanical ventilation; N/A, not available; OECD, Organisation for Economic Co-operation and Development.
Table 5. ICU outcomes according to geographical location among studies reporting comorbidity, illness-severity, or risk-adjustment measures.
| Country of study | Author | Comorbidity, illness-severity, or risk- adjustment measure | ICU admission | ICU mortality | Length of ICU stay | ICU interventions | Hospital/ICU readmission |
|---|---|---|---|---|---|---|---|
| OECD member countries | |||||||
| USA | Nickel et al30 | APACHE II quartiles | More likely for rural and black patients | Higher for rural and black patients | N/A | N/A | N/A |
| Schroeder et al34 | Specific medical conditions | More admissions | No difference | Longer | N/A | N/A | |
| Hamilton et al38 | Specific medical conditions | No difference | No difference | No difference | No difference | No difference | |
| Canada | Wong et al42 | CCI | No difference | No difference | No difference | N/A | N/A |
| Mann et al40 | CCI | No difference | No difference | No difference | No difference | N/A | |
| Australia | D’Arcy et al52 | APACHE II and III | N/A | N/A | Shorter | No difference | N/A |
| Paynter et al31 | ANZROD score | N/A | No difference | N/A | N/A | N/A | |
| Cerni et al37 | CCI | More for large rural towns | N/A | N/A | More in smaller rural towns | N/A | |
| Flabouris et al48 | APACHE II | N/A | No difference | Longer | N/A | N/A | |
| Fatovich et al51 | TRISS | More admissions | N/A | Longer | N/A | N/A | |
| Finland | Raatiniemi et al44 | SAPS, SOFA and APACHE II | No difference | No difference | No difference | No difference | N/A |
| Non-OECD member countries | |||||||
| South Africa | Lee et al35 | CCI | More admissions | N/A | Longer | More interventions | N/A |
ANZROD, Australian and New Zealand Risk of Death; APACHE, Acute Physiology and Chronic Health Evaluation; CCI, Charlson Comorbidity Index; ICU, intensive care unit; N/A, not available; OECD, Organisation for Economic Co-operation and Development; SAPS, Simplified Acute Physiology Score; SOFA, Sequential Organ Failure Assessment; TRISS, Trauma and Injury Severity Score.
Table 6. ICU outcomes for patients according to travel distance/time and the corresponding measurement scales used.
| Country of study | Author | Distance categorisation | ICU admission | ICU mortality | ICU LOS | ICU interventions | Travel distance/time calculation method |
|---|---|---|---|---|---|---|---|
| Australia | Flabouris et al48 | 0–50 km, 50–300 km, 300–1500 km, or >1500 km | N/A | Higher risk when not admitted to ‘home ICU‘ | Longer LOS when not admitted to ‘home ICU‘ | N/A | Grouped distances into categories according to feasible choices of patient transport vehicles: road vehicle (0–50 km), helicopter (50–300 km), fixed-wing turbine propeller aircraft (300–1500 km) or jet aircraft (>1500 km) |
| Cerni et al37 | Travel time in 5-minute intervals up to 30 min | No impact | N/A | N/A | No impact on MV use | Estimated travel time from the patient’s residential postcode to the centre of the hospital postcode | |
| Paynter et al31 | Per km from ICU | N/A | No impact | N/A | N/A | From the centre of the patient’s postcode calculating the aerial straight line (shortest) distance to the treating hospital | |
| Paynter et al47 | Actual travel distance | N/A | Lower risk | N/A | N/A | Measured as the shortest distance from the centre of the patient’s postcode to the hospital | |
| D’Arcy et al52 | <50 km or >50 km | N/A | N/A | Shorter ICU stays | No impact on MV use | Distance from patient’s residential postcode to the treating ICU | |
| Spain | Magallón-Botaya et al39 | Travel time and distance | No impact | Higher risk | N/A | N/A | Distance and travel time from patient residence to hospital |
ICU, intensive care unit; LOS, length of stay; MV, mechanical ventilation; N/A, not available.
Classifications of rurality
Various measures were used to classify rurality across the included studies. Of the 23 studies29,51 reporting on rurality, 20 specified the classification system used.30,4244 These included three studies using population density, three using postal code-based classifications and two each using Rural–Urban Continuum Codes (RUCC), National Centre for Health Statistics classifications, US Census Bureau tracts and the Australian Statistical Geography Standard. One study each used the Modified Monash Model, the Accessibility/Remoteness Index of Australia (ARIA+) and Rural–Urban Commuting Area (RUCA) codes. Both South African studies35 49 defined rurality according to healthcare facility catchment areas, considering all regions outside Pietermaritzburg’s city limits as rural. One Australian study used a predefined list of rural and non-rural suburbs in New South Wales.45 Three studies29 43 51 did not specify the criteria used for rural classification. Despite the use of established classification systems, considerable inconsistency was observed in how rurality was defined across studies.
Among studies using population-based definitions, thresholds and metrics differed. McGuffie and colleagues50 defined rurality using a population density of 0.5 persons per acre or less, whereas Magallón-Botaya and colleagues39 applied a specific population guideline, defining rural areas as municipalities with fewer than 2000 residents. At the international level, the definitions also varied considerably though some consistency emerged. In the USA, RUCA codes were frequently employed, providing census tract-level classifications based on population density, urbanisation and commuting patterns. RUCC were also referenced; these codes enable county-level classification grounded in population size and proximity to metropolitan areas, thereby representing a broader and less granular framework than RUCA codes.
Greater consistency was noted among the five Australian studies, using the Australian Statistical Geography Standard – Remoteness Area classification. This system uses ARIA+, which quantifies remoteness according to road distance to population centres providing essential services, thereby offering a standardised geographical metric for defining rurality. Both studies by Paynter and colleagues31 47 used ARIA+index values, classifying remoteness across five categories ranging from major cities to very remote areas. Urban population centres were defined as having a population of at least 1000 residents.
Rural-urban/metropolitan differences
Regarding residence-based differences, the findings on ICU admissions and outcomes among rural residents compared with urban/metropolitan residents were mixed. Five studies29 32 33 45 46 reported lower ICU admission rates for rural patients compared with urban/metropolitan counterparts, three reported higher rates36 39 43 and one found no difference.49 ICU mortality was higher in rural cohorts compared with urban/metropolitan groups in one study,36 whereas one study found no difference.47 ICU LOS was longer in rural cohorts compared with urban/metropolitan groups in one study,41 whereas one study reported no difference.50 One study41 reported less use and time on ICU interventions (mechanical ventilation) among rural patients compared with urban/metropolitan patients, whereas one found no difference.32 Hospital or ICU readmission was more likely among rural patients compared with urban/metropolitan patients in one study,29 whereas two studies reported no significant difference between the two groups.32 41
Among the 12 studies reporting baseline comorbidities and/or illness-severity or risk-adjustment measures, 3 used APACHE II/III scores,30 48 52 1 used the ANZROD score,47 4 used the Charlson Comorbidity Index,35 37 40 42 2 considered specific medical conditions,34 38 1 used the Trauma and Injury Severity Score,51 and 1 applied the SAPS, SOFA, and APACHE II scores collectively.44 Regarding ICU admissions, five studies30 34 35 37 51 reported rural patients being admitted to ICU more often than urban/metropolitan patients (one study included rural and black patients), and four studies indicated no difference.38 40 42 44 Increased ICU mortality among rural patients compared with urban/metropolitan patients was noted in one study30 (also including black patients), whereas seven reported no difference.31 34 38 40 42 44 48 Four studies34 35 48 51 indicated rural patients had longer ICU stays than urban/metropolitan patients, one study52 indicated shorter stays for rural patients and four studies reported no difference.38 40 42 44 Greater use of ICU interventions by rural patients compared with urban/metropolitan patients was observed in two studies,35 37 whereas four studies38 40 44 52 reported no difference. One study indicated no significant difference in hospital or ICU readmissions between rural and urban/metropolitan patients.
Travel distance/time and ICU outcomes
Regarding access-based factors, of the six studies examining travel distance or time to the ICU, five31 39 47 48 52 reported distance and two37 39 reported travel time. Two studies48 52 categorised distance into intervals, whereas three studies31 39 47 assessed the straight-line distance from patient residential postcode to hospital. The two studies reporting travel time also performed stratification into time windows.37 39 Two studies37 39 found no impact of distance or time on ICU admission rates. Two studies39 48 reported that a longer travel distance from patient residence increased ICU mortality risk, although one study observed this finding only when patients were admitted to a facility other than their ‘home ICU’.48 One study31 indicated no effect of travel distance/time on patient mortality, whereas one study47 reported decreased mortality risk with increased travel distance. ICU LOS was longer when patients were admitted to non-home ICUs at greater distances in one study48 but was shorter in another study52 for patients residing more than 50 km away. Two studies37 52 indicated no difference in the use of ICU interventions (all mechanical ventilation) according to travel distance or time. No studies reported the effect of travel distance or time on hospital or ICU readmissions.
Discussion
Key findings
In this scoping review, we assessed the impact of geographical location on ICU outcomes in adults. Furthermore, we characterised the definitions and measures used for geographical location, including various classification systems of rurality/remoteness, measures of travel distance/time and reported ICU outcomes.
We observed marked heterogeneity in the definitions of rural/remoteness globally. Commonly used classifications in Australia included the ARIA+ and the Australian Statistical Geography Standard classification. In the USA, RUCA or RUCC were frequently referenced. In Canada, Census Agglomerations and Metropolitan Influence Zones were used. Globally, most studies provided a clear basis for their definitions and at least indicated whether population density or postcode-based classifications were used. Three studies lacked explicit criteria.29 43 51 Notably, even within the same country, the application of these scales varied considerably, thereby limiting the comparability of these metrics across studies.
Regarding ICU outcomes, neither travel distance/time nor patient rurality had a consistent impact on ICU admissions. Although a decreased likelihood of admission might be considered a positive outcome in the context of lessened disease severity, it might also represent an access barrier faced by rural/remote populations or populations requiring further travel to access care.61 This inherent limitation makes comparability across studies difficult, although this ICU outcome measure was the most commonly reported.
Regarding ICU mortality, rural residence was associated with poorer outcomes in several studies. This finding differs from Keeves et al, who found that, despite greater prehospital mortality in rural patients with trauma, rurality appears to be less relevant after hospital admission.23 Possible reasons for this finding might be that after ICU admission, patients generally receive specialised care with better staffing ratios,62 63 thus leading to comparable outcomes regardless of rural or urban residence. This finding suggests that disparities might exist primarily in the prehospital phase; consequently, further research on prehospital rural–urban health outcomes is warranted.
More studies also found that patients from rural residences have longer ICU LOS and more use of ICU interventions on average, compared with patients from urban/metropolitan areas. This finding was consistent with the existing literature reporting delayed presentation and greater disease severity among patients from lower socioeconomic backgrounds and from rural/remote communities compared with non-rural patients.64 65 Longer lengths of stay may also reflect clinician reluctance to discharge rural patients due to patients having to travel further to receive primary care. A notable finding was the limited number of studies reporting ICU outcomes beyond admission rates. In the literature, comparisons were often made according to the rurality of the treating hospital or ICU rather than that of the patient’s residence, thereby potentially overlooking prehospital factors influencing outcomes; hence, such studies were excluded from this review.
Establishing a definitive link between geographical location and ICU outcomes remains challenging, given the number of confounding variables. The interplay between geographical location and health outcomes is inherently influenced by social determinants of health,66 including socioeconomic status, environmental conditions, access to healthcare services, insurance status (in the case of traumatic injury) and risk-taking behaviours, all of which contribute to individuals’ health outcomes.67 Although some studies attempted to isolate rurality as the primary variable of interest by controlling for these factors, those that did not may have introduced residual confounding into their findings.
A critical methodological gap across the included studies was the failure to adequately report patient baseline comorbidity burden, with only half of the studies including any measure of preadmission comorbidity or illness severity. This is consequential given the well-established higher burden of chronic disease in rural populations, including greater rates of cardiovascular disease, diabetes and chronic respiratory conditions. Unadjusted comparisons of ICU mortality and length of stay between rural and urban patients therefore risk reflecting pre-existing differences in health status rather than any independent effect of geographical location. This confounding likely explains, at least in part, the inconsistent mortality findings observed across studies in this review.
Furthermore, the heterogeneity of populations studied and the limited literature available make defining the precise impact of geographical location on ICU outcomes challenging. Given classification systems, population thresholds, geographical units and travel metric methodologies all varied considerably with no consistent standard applied, we propose a minimum framework for future studies examining geographical location and ICU outcomes summarised in online supplemental file 3. Future research should prioritise standardised definitions of rurality and incorporate comprehensive assessments of social determinants of health to more accurately evaluate their collective influence on ICU outcomes.
Strengths and limitations
This scoping review represents a significant contribution to the literature by systematically mapping the current evidence regarding the influence of geographical location on ICU outcomes. One of the key strengths of our review is its comprehensive approach to identifying and synthesising the available data, thereby illuminating critical gaps in the operational definitions and conceptual frameworks used to assess the impact of travel distance and time on patient outcomes. By adopting a holistic perspective, our analysis integrates diverse findings to provide a more nuanced understanding of the complex associations between geographical factors and ICU results. Furthermore, this review not only identifies methodological and knowledge gaps within the existing research but also highlights promising opportunities for future investigations. In doing so, it enriches the broader pool of knowledge concerning geographical disparities in health outcomes and advances the field’s understanding of how location-based factors may influence critical care delivery and prognosis.
Several key limitations worth noting. Most included studies were conducted in high-income OECD nations, with only two studies from a single non-OECD country (South Africa) represented, which substantially limits the generalisability of findings. Healthcare organisation, referral pathways, prehospital care systems and ICU infrastructure vary considerably—both between and within these countries. This likely contributes to outcome variability beyond geographical distance alone. These structural differences mean that the observed associations between rurality, travel distance/time, and ICU outcomes may not translate to health systems with fundamentally different resources and configurations.
Similarly, the restriction to English-language publications likely introduced systematic geographical bias. Most studies included originated from high-income, English-speaking OECD nations with only one non-OECD country represented. This may carry significant implications as critical care disparities tend to be most pronounced in lower income settings, where ICU mortality rates are much greater—reaching up to 60.9% in Malawi and 38% in Ethiopia compared with approximately 8% in Australia and 10–29% the USA.1668,70 This is in addition to considerably larger ICU access gaps faced by non-OECD countries. Findings should hence be cautiously generalised beyond well-resourced high-income health systems and future reviews should include non-English sources and prioritise non-OECD regions to generate a more globally diverse evidence base.
Sources
The broad search strategy used to capture relevant literature might have led to the exclusion of relevant articles during title and abstract screening. Variability in rural definitions and outcome measures across studies poses challenges in drawing definitive conclusions. Three of the included studies33 38 39 were conducted during the COVID-19 pandemic and hence, shifts in presentation patterns, admission thresholds and ICU capacity during this period may hinder comparability with non-pandemic settings. Moreover, studies on COVID-19 admissions might be contradictory, given that living rurally might be considered ‘protective’ against disease transmission. Additionally, conditions such as trauma or stroke might exhibit different rural health outcomes from post-surgical admissions, thereby indicating the need for context-specific studies.
A key methodological decision in this revision was the exclusion of paediatric and neonatal populations. Disease severity scoring systems also differ, making meaningful comparisons with adult outcomes limited. Further, paediatric ICUs are predominantly located in centralised tertiary metropolitan centres, meaning the relationship to geography and ICU access is structurally different to adults. Neonatal ICU admissions were also excluded as they are sometimes used as proxies for maternal health outcomes and do not accurately reflect the broader social determinants of health affecting rural patients. This may lead to population bias due to a disproportionate focus on maternal health. Hence, exclusion of these demographics helped to sharpen the focus and validity of this review. Future literature should investigate specific differences in how rurality affects paediatric populations differently to adults.
Conclusions
This scoping review mapped the current literature on the impact of geographical location on ICU outcomes. The highly variable definitions of rurality complicated comparison across studies. Findings were inconsistent across studies; however, a greater proportion of studies reported longer ICU LOS and greater ICU intervention use among rural compared with urban/metropolitan patients. Mortality findings between rural and urban/metropolitan patients were inconsistent with no predictive pattern. We observed no clear impact of travel distance/time on ICU outcomes. Future research should aim to use more globally standardised definitions of rurality, to better consider preadmission health status and prehospital mortality outcomes and to focus more on context-related conditions. Greater understanding of geographical differences in health outcomes would better inform targeted healthcare policy for patients living in remote areas.
Supplementary material
Footnotes
Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2025-114956).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Not applicable.
Ethics approval: Not applicable.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Data availability statement
Data are available upon reasonable request.
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