Developing consensus-based indicators for intensive care unit capacity and capability in South Korea: a modified Delphi study

Jeehye Lee; Ho Kyung Sung; Min-hwan Oh; Jin Young Kim; KyoungHo Kim; Jae Young Moon

doi:10.4266/acc.000676

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Original Article Basic Science and Research Developing consensus-based indicators for intensive care unit capacity and capability in South Korea: a modified Delphi study: Acute and Critical Care 2026;41(2):282-294.
DOI: https://doi.org/10.4266/acc.000676
Published online: May 28, 2026

Jeehye Lee¹

, Ho Kyung Sung^2,3

, Min-hwan Oh⁴

, Jin Young Kim⁵

, KyoungHo Kim⁶

, Jae Young Moon⁷

¹Department of Preventive Medicine, Konkuk University College of Medicine, Chungju, Korea

²National Emergency Medical Center, National Medical Center, Seoul, Korea

³Public Health Research Institute, National Medical Center, Seoul, Korea

⁴Graduate School of Data Science, Seoul National University, Seoul, Korea

⁵Division of Respiratory Allergy and Critical Care Medicine, Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, Korea

⁶Division of Emergency and Critical Care Medicine, Department of Emergency Medicine, Chungnam National University Sejong Hospital, Sejong, Korea

⁷Department of Pulmonary and Critical Care Medicine, Chungnam National University Sejong Hospital, Sejong, Korea

Correspondence: Jae Young Moon Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Chungnam National University Sejong Hospital, Chungnam National University College of Medicine, 20, Bodeum 7-ro, Sejong 30099, Korea Tel: +82-42-280-7142 Fax: +82-42-257-5753 Email: diffable@hanmail.net

• Received: January 13, 2026 • Revised: March 16, 2026 • Accepted: March 25, 2026

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
KEY MESSAGES
NOTES
SUPPLEMENTARY MATERIALS
REFERENCES

Abstract

Background
Intensive care units (ICUs) are essential components of modern healthcare systems, but South Korea lacks capability-based standards for ICU classification. Critically ill patients are frequently assigned based on bed availability rather than clinical need, creating mismatches between patient acuity and ICU capability. The aim of this study was to develop consensus-based indicators for assessing ICU capacity and capability in South Korea.
Methods
A modified Delphi study was conducted with 24 multidisciplinary experts, including members of the Korean Society of Critical Care Medicine (SCCM) Standardization Committee. Based on a systematic review of international ICU frameworks (SCCM, European Society of Intensive Care Medicine, Australian and New Zealand Intensive Care Society), 42 candidate indicators across six domains were evaluated over three rounds (April–July 2025). Consensus was defined as a content validity ratio ≥ a preset critical threshold and ≥75% expert agreement.
Results
The response rates were 79.2%–91.7% across rounds. The final framework comprises 29 indicators across four domains: Capacity (staffing, facilities, bed management), Capability (life support, specialized care), Human resources (physician and allied health coverage), and Space and equipment infrastructure (monitoring and safety systems). The experts prioritized functional capabilities over structural metrics: nurse-to-bed ratios were rated more important than physician numbers, and 24/7 service availability was prioritized over personnel counts. Ward support, education, and research indicators did not reach consensus.
Conclusions
This study establishes the first expert consensus framework for ICU capability assessment in South Korea. The 29 indicators provide a foundation for a capability-oriented classification system that prioritizes patient safety and efficient resource allocation. Future research should validate these indicators against clinical outcomes and explore real-time ICU capacity monitoring strategies.
Key Words: consensus; critical care; Delphi technique; health resources; intensive care units; South Korea

INTRODUCTION

Intensive care units (ICUs) are essential components of modern healthcare systems that provide life-sustaining treatment for patients with acute, life-threatening conditions. Critical illness has been defined as a state characterized by vital organ dysfunction, a high risk of imminent death if care is not provided, and potential reversibility [1]. As a multidisciplinary and interprofessional specialty dedicated to the comprehensive management of such patients, critical care requires highly specialized personnel, advanced equipment, and substantial resources [2].

Many developed countries have established standards for ICUs, classify and manage them accordingly, and have quality management programs at the professional society or national level [3,4]. This is important because intensive care requires highly specialized professionals and multidisciplinary teams, as well as expensive equipment for life support [2,3], which makes geographic inequalities highly likely [5-7]. Moreover, for the reasons stated above, the inefficient use of intensive care resources can negatively affect not only hospitals but also the entire healthcare system. The importance of ICU capacity management was highlighted during the coronavirus disease 2019 (COVID-19) pandemic and other crises [8-12]. To respond effectively and efficiently to future public health crises, it is crucial to establish standards and manage the capacity of ICUs.

Korea currently has no capability-based standards for classifying ICUs [13,14]. In practice, critically ill patients enter a system in which the availability of a bed often outweighs the suitability of care, and there is no established mechanism to match patient acuity with ICU capability [15]. As a result, critically ill patients are frequently assigned according to bed availability rather than clinical need, and transfers depend on informal arrangements within the emergency network, rather than a defined critical-care system [16]. This can leave the most severely ill patients vulnerable to delays and mismatches between acuity and capability. To address this system-level gap, we used a modified Delphi process to identify consensus-based indicators that define ICU capability and can serve as the foundation for a future capability-oriented classification and transfer framework.

MATERIALS AND METHODS

This study was approved by the Institutional Review Board of Chungnam National University Sejong Hospital (No. CNUSH 2025-01-003-004). All participants provided informed consent and were assured of anonymity throughout the Delphi process.

Study Design and Rationale

This study used a modified Delphi [17-19] approach to develop consensus-based indicators for ICU capacity and capability in South Korea. We defined capacity as the quantitative ability to accommodate patients (e.g., beds, staffing, and equipment availability), and capability as the qualitative ability to deliver complex, resource-intensive critical care at an appropriate level of quality and timeliness. In short, capacity reflects how many patients can be admitted, and capability reflects what level of care can be provided.

The survey addressed two distinct research aims: (1) gathering expert opinion and consensus on ICU capability indicators, evaluated through Capacity and Capability domains; and (2) gathering expert opinion and consensus on ICU grading and classification criteria, evaluated through four additional domains—Human Resources, Space and Equipment Infrastructure, Ward Support Services, and Education, Training, Research, and Quality Management. In total, the initial item pool comprised 42 candidate indicators across those six domains. It should be noted that several indicators appear in both objectives—for example, multidisciplinary team composition and hemodynamic monitoring equipment feature in both the Capability domain and the Infrastructure domain—because the same clinical resource carries different evaluative meaning depending on whether it is assessed as a marker of inherent ICU capability or as a structural criterion for tiered classification. This deliberate overlap was retained to allow experts to evaluate each dimension independently.

A modified Delphi technique was selected instead of the classical Delphi for several methodological reasons. First, a pre-structured item list was generated through a systematic literature review of existing ICU classification frameworks (e.g., Society of Critical Care Medicine [SCCM], European Society of Intensive Care Medicine [ESICM], Australian and New Zealand Intensive Care Society [ANZICS]) [3,20-22], which prevented open-ended item generation and reduced participant burden while ensuring comprehensive coverage of evidence-based indicators. The literature review was conducted by a multidisciplinary team of four experts (two ICU specialists, one health policy expert, and one emergency medicine specialist) and produced the initial pool of 42 items. Second, the modified approach enabled broader interdisciplinary participation beyond traditional ICU specialists, incorporating perspectives from emergency medicine, hospital administration, and health policy experts. Key modifications included: (1) a predetermined 3-round design; (2) use of varying rating scales across rounds (5-point, 10-point, 5-point) to optimize discrimination; (3) iterative item refinement based on content validity ratio (CVR) thresholds; and (4) inclusion of reverse-phrased items in Round 3 to test response consistency.

Expert Panel

The panel contained 24 experts: 12 members from the Standardization Committee of the Korean Society of Critical Care Medicine and 12 external researchers. To ensure a multidisciplinary perspective, the panel contained specialists from pulmonology (n=11), anesthesiology (n=3), pediatrics (n=2), cardiovascular thoracic surgery (n=2), emergency medicine (n=1), general surgery (n=1), neurosurgery (n=1), infectious medicine (n=1), rehabilitation medicine (n=1), and critical care nursing (n=1). Panel size was determined based on methodological recommendations for multidisciplinary topics (15–30 participants).

Delphi Rounds

Three online survey rounds were conducted between April and July 2025. Table 1 summarizes the survey rounds and response rates. In Round 3, borderline items were stratified into two evaluation tracks. Items related to safety infrastructure and mandatory operational requirements (e.g., negative pressure rooms, bed count indicators) were assessed using a paired-item design, in which both a positively phrased and a reverse-phrased question were presented to verify internal consistency. The remaining items were re-evaluated using single positively phrased questions.

Consensus Criteria and Statistical Analysis

Consensus was defined a priori as satisfying both: (1) CVR ≥critical threshold for the panel size (0.455 for n=22; 0.429 for n=20; 0.417 for n=19), and (2) ≥75% of the experts rating the item as important/appropriate. For the paired items in Round 3, indicators were excluded if the CVR difference between phrasings exceeded 0.2 or showed logical contradictions (i.e., high agreement on both the positive and reverse statements). Descriptive statistics (means, medians, standard deviations, interquartile ranges) and CVR values were calculated for each item. Reliability was assessed using Cronbach's α for internal consistency. All analyses were performed using Microsoft Excel (Microsoft Corp.).

RESULTS

Twenty-four experts provided written consent and agreed to participate in the Delphi panel. The response rates were high across all three rounds: 22 experts (91.7%) in Round 1, 20 (83.3%) in Round 2, and 19 (79.2%) in Round 3 (Table 1, Figure 1).

Round 1

In Round 1, 42 candidate indicators were evaluated for importance using a 5-point Likert scale (n=22). Thirty-six indicators met the predefined consensus threshold (CVR ≥0.455 and ≥75% agreement). Items that failed to reach consensus included the presence of a physician on-call room and the absolute number of ICU beds, both of which were judged to insufficiently reflect ICU capability as standalone measures. Following a panel review of ambiguous responses, four items were excluded, two were revised, and four new items were added based on expert suggestions, resulting in a revised pool of 42 items carried forward to Round 2 (Table 2).

Round 2

In Round 2, 42 indicators were re-evaluated for appropriateness using a 10-point Likert scale (n=20). Seven indicators were redefined before this round to enhance their clarity and discriminability. For example, the item "number of ICU beds" was subdivided into the hospital-to-ICU bed ratio, ICU occupancy rate, and reserve staffing capacity, and one new item—personnel capable of performing emergency coronary artery bypass graft (CABG)—was introduced based on expert suggestion. Twenty-five indicators met the consensus threshold (CVR ≥0.429 and ≥75% rating 7–10). Nine indicators were excluded due to consistently low CVR values or redundancy. Eight indicators (Q6, Q7, Q13, Q20, Q36, Q37, Q38, Q40) showed borderline CVR values between the acceptance and rejection thresholds. Although those items did not meet the predefined consensus threshold, the research team determined that excluding them would create critical gaps in the assessment of safety infrastructure—areas directly linked to patient safety and minimum operational standards. In particular, the 2024 SCCM guidelines explicitly recommend single-patient rooms in ICU design [20]. These eight items were therefore carried forward to Round 3 for further validation (Table 2).

Round 3

In Round 3 (n=19), the eight borderline items were evaluated through two tracks. Three items were assessed using a paired-item design, and five were re-evaluated using single positively phrased questions. Those results are summarized in Table 3. All three paired items were rejected. The item "24/7 availability of emergency CABG" showed a logical inconsistency: the positive phrasing received high agreement (CVR 0.789), but the reverse phrasing ("not important") also showed substantial agreement (CVR 0.579), indicating that experts could not consistently determine its importance. "Negative pressure isolation room" was excluded due to unstable consensus, i.e., the CVR difference between the positive and reverse phrasings exceeded the acceptable threshold of 0.2. "Number of operational ICU beds" failed to meet the CVR threshold in both phrasings.

Of the five single items, four reached consensus and were accepted: "Central monitoring system" (CVR 0.895), "Single-bed ICU room with central monitoring station" (CVR 0.895), "Isolation bed proportion" (CVR 0.579) and "Hospital-to-ICU bed ratio" (CVR 0.474). One item, "Accredited training institution for critical care medicine," did not meet the CVR threshold (CVR 0.368) and was excluded.

Final Framework

The Delphi process yielded a final consensus-based framework of 29 indicators across four domains (Table 4). The Ward Support Services domain and the Education, Training, Research, and Quality Management domain did not achieve consensus on any of their candidate indicators and were therefore excluded from the final framework. The four retained domains—Capacity (12 indicators), Capability (6 indicators), Human Resources (3 indicators), and Space and Equipment Infrastructure (8 indicators)—constitute the final set of consensus-based indicators for ICU capability assessment in the Korean healthcare context.

DISCUSSION

The aim of this study was to develop consensus-based indicators for assessing ICU capacity and capability in South Korea through a three-round modified Delphi process [17-19]. The survey had two distinct research aims: (1) gathering expert consensus on ICU capability indicators, evaluated through Capacity and capability domains; and (2) gathering expert consensus on ICU grading and classification criteria, evaluated through four additional domains—Human resources, Space and equipment infrastructure, Ward support services, and Education, training, research, and quality management. Of the 42 candidate indicators evaluated across the six domains, which were informed by international frameworks such as SCCM, ESICM, and ANZICS [3,20-22], 29 ultimately reached consensus. The Ward support services and Education, training, research, and quality management domains failed to achieve agreement on any of their candidate indicators, resulting in a final four-domain framework: Capacity (12 indicators), Capability (6 indicators), Human resources (3 indicators), and Space and equipment infrastructure (8 indicators). This outcome reflects not merely a statistical finding but a substantive statement by Korean ICU experts about what constitutes the essential identity of an ICU in the current healthcare context.

To characterize the expert agreement beyond binary consensus classification, a post-hoc analysis classified all Round 2 indicators into four evidence-quality types based on their mean scores and CVR values (Supplementary Table 1). Type A (mean ≥8.5, CVR ≥0.9) represented strong, unambiguous consensus; type B (mean ≥8.0, CVR ≥0.5) represented stable moderate-to-high importance with sufficient agreement; type C (7.0≤ mean <8.0, CVR ≥0.5) represented moderate consensus; and type D (mean <7.0 or CVR <0.5) indicated low priority or insufficient agreement.

Fourteen indicators (33%) were classified as type A—the non-negotiable core of ICU capability in the view of Korean experts. These included all life support interventions (LSIs) (LSI provision: mean 9.55, CVR 1.000; 24/7 cardiovascular intervention: mean 9.55, CVR 1.000; 24/7 extracorporeal membrane oxygenation [ECMO]: mean 9.30, CVR 1.000; advanced critical care equipment: CVR 1.000), key staffing indicators (nurse-to-bed ratio: mean 9.45, CVR 0.900; daytime specialist coverage: mean 9.10, CVR 0.900; 24/7 specialist coverage: mean 8.75, CVR 0.900), and full-time intensivist staffing (mean 8.90, CVR 0.900). Six indicators (14%) were classified as type B, including nighttime physician coverage, multidisciplinary rounding, proportion of patients receiving LSI, other critical procedures, and hemodynamic monitoring indicators. Five indicators (12%) fell into type C, and the remaining 17 (40%) into type D.

A notable structural finding is the clear polarization between type A and type D: no indicator simultaneously received high mean scores and low CVR—that is, no indicator that was rated as highly important was deeply contested. When Korean experts agreed something was critical, they agreed strongly; disagreement was concentrated precisely among items considered less essential. The emergence of a distinct type B cluster—moderate-to-high importance with adequate consensus—provides a practical basis for a two-tier policy framework: type A indicators as mandatory minimum standards, and type B indicators as recommended standards for higher-tier ICU designations.

The distribution of the adopted and excluded domains reveals a consistent orientation among Korean experts toward functional capability over structural and institutional attributes. This stands in meaningful contrast to many international ICU frameworks. The SCCM, ESICM, and ANZICS standards incorporate structural indicators—dedicated physical layouts, education program accreditation, and research infrastructure—as integral components of ICU tiering [3,20-22]. Korean experts, by contrast, concentrated their strongest consensus on functional process indicators: 24/7 availability of cardiovascular interventions, LSI provision, and ECMO access—all of which reflect what an ICU can do for a patient at any given moment, rather than what it has in terms of physical infrastructure.

This functional orientation was also evident within the staffing domain. Experts rated the nurse-to-bed ratio (mean 9.45, CVR 1.000) more highly than absolute physician numbers, reflecting recognition that continuous 24-hour patient monitoring depends primarily on nursing presence. Physician staffing can demonstrate a threshold effect [23,24], whereas nursing workload increases proportionally with patient assignment. Because nurses provide continuous bedside care and monitoring, their staffing levels are closely linked to patient safety events. Accordingly, multiple observational studies have identified registered nurse staffing as one of the organizational factors most strongly associated with patient outcomes [25]. Furthermore, experts consistently prioritized the availability of interventions over the number of personnel capable of performing them—illustrated by the contrast between "24/7 cardiovascular intervention availability" (type A, CVR 1.000) and "number of surgeons capable of emergency CABG" (type D, CVR 0.200). The complete exclusion of the Education, training, research, and quality management domain—despite its prominence in international frameworks such as ESICM [21] and ANZICS [22]—suggests that Korean experts drew a deliberate boundary between clinical competence and institutional function. This implies a preference for a classification system in which non-university hospitals with strong clinical capability are not disadvantaged relative to academic centers.

Several indicators that failed to achieve final consensus merit specific discussion, as their exclusion carries substantive meaning. First, "negative pressure isolation rooms," despite initially appearing on the borderline, were excluded in Round 3 due to inconsistent paired-item responses—the CVR difference between the positive and reverse phrasings exceeded 0.2, indicating genuine expert uncertainty rather than clear rejection. Although the 2024 SCCM guidelines explicitly recommend single-patient rooms in ICU design [26], the broader question of mandatory infection control infrastructure remains unsettled in the Korean context and might warrant reconsideration as post-pandemic airborne precaution standards continue to evolve. Second, "24/7 emergency CABG availability" demonstrated a logical inconsistency in Round 3: experts gave high agreement to both the positive phrasing (CVR 0.789) and the reverse phrasing ("not important," CVR 0.579), revealing that although the capability is valued when present, it is not viewed as a universal prerequisite—reflecting a realistic appraisal of the current distribution of cardiac surgical capacity across Korean hospitals. Third, indicators related to ward support services—including rapid response systems led by critical care staff—did not reach consensus, suggesting that experts considered those dimensions to be important at the hospital level but insufficiently specific to the ICU environment to serve as defining capability criteria.

Outcome indicators, such as risk-adjusted mortality, were deliberately excluded from the framework. In the Korean context, the absence of a standardized national database for severity adjustment and the lack of a systematized inter-hospital transfer network render comparative outcome metrics unreliable at present. Beyond data infrastructure, risk-adjusted mortality indicators are inherently susceptible to selection bias, potentially penalizing high-acuity referral centers that disproportionately accept the most critically ill patients [27,28]. By prioritizing objective structural and process indicators—such as 24/7 staffing availability and life support capacity—this framework offers a more equitable and immediately actionable foundation for policy decisions. This can be interpreted as consistent with the World Federation of Intensive and Critical Care framework [2], which first defines ICU structural capability levels and then uses them for benchmarking and capacity planning

This study has several strengths. It represents the first consensus-based effort to develop ICU capability indicators in South Korea, and it is grounded in a multidisciplinary panel of 24 experts—including members of the Korean Society of Critical Care Medicine Standardization Committee—who provided high and sustained response rates across three rounds (79.2%–91.7%). The modified Delphi design incorporated methodological features that strengthen the rigor of the consensus process, including a pre-structured item pool derived from a systematic review of international frameworks [3,20-22], varying rating scales across rounds to optimize discrimination [17], and reverse-phrased items in Round 3 to verify internal consistency [18,19].

Several limitations also warrant acknowledgment. Nursing representation on the expert panel was small (n=1 critical care nurse), which might have introduced bias in the relative weighting of nursing-related indicators; however, the nurse-to-bed ratio emerged as one of the highest-rated measures overall. As a consensus-based study, the indicators require empirical validation against clinical outcomes such as mortality, length of ICU stay, and transfer efficiency before their adoption as formal regulatory standards [17]. This study also reflects the state of Korean ICU infrastructure as of 2025; evolving post-pandemic norms—particularly regarding infection control requirements—might shift expert consensus on currently excluded indicators in future iterations. Also, the composition of the expert panel might have introduced selection bias and limited representativeness because the results can be influenced by participants’ institutional characteristics, specialty background, and healthcare system context. Finally, the framework does not yet incorporate patient- and family-centered outcome perspectives, and they are an important dimension of ICU quality that future studies should address.

The 29 indicators identified in this study provide a practical foundation for constructing a capability-oriented ICU classification system in South Korea. International experience offers important lessons in this regard. Ontario, Canada, through Critical Care Services Ontario, demonstrates the value of a centralized, real-time capability network in which patient transfers are coordinated based on standardized tiering of staffing, life support equipment, and ventilation capacity [29,30]. The type A indicators identified in our study—particularly LSI provision, 24/7 cardiovascular and ECMO availability, and nurse-to-bed ratios—map directly onto the data fields required to build a monitoring infrastructure that connects institutional capability data to regional dashboards to enable transparent patient-acuity matching [31,32]. Conversely, Japan's experience illustrates the risks of linking ICU classification to reimbursement without functional oversight: a tiered fee structure based on staffing ratios incentivized increases in invasive procedures without corresponding improvements in mortality or occupancy rates [33,34]. South Korea, which shares a fee-for-service model with Japan, faces analogous risks if classification is tied to reimbursement prematurely or without functional validation. The indicators defined in this study should therefore be operationalized as a standardized data dictionary for a real-time ICU monitoring system—one that supports patient-acuity matching and transfer coordination at both the institutional and regional levels.

Future research should proceed in three directions. First, the indicators should be validated against clinical outcomes in a prospective cohort or registry-based study to confirm that higher capability scores correspond to improved patient survival, shorter ICU lengths of stay, and more efficient inter-hospital transfers [27,28]. Second, a pilot implementation in a defined geographic region—analogous to Ontario's provincial rollout [31,33]—would allow testing of the data dictionary, monitoring dashboard, and classification algorithm in real-world conditions before national adoption. Third, the framework should be revisited periodically as the Korean ICU infrastructure evolves: indicators currently in type D or excluded (such as negative pressure isolation and rapid response systems) might achieve stronger consensus as implementation conditions improve. Together, these steps would transform the present expert consensus into an operational classification system that can improve patient safety and resource efficiency in Korean critical care.

KEY MESSAGES

▪ This study establishes the first expert consensus framework for intensive care units (ICU) capability assessment in South Korea, comprising 29 indicators across four domains and providing an evidence base for moving beyond bed-count-based classification toward capability-oriented evaluation.

▪ Korean ICU experts consistently prioritized functional capabilities over structural metrics: 24/7 life support availability and nurse-to-bed ratios were rated as non-negotiable core standards, whereas indicators related to ward support services, education, and research functions did not reach consensus.

▪ The 29 consensus indicators could provide standardized data fields for constructing a regional and nationwide critical care resources monitoring system and enabling capability-based ICU matching and transferring models for critically ill patients.

NOTES

CONFLICT OF INTEREST

No potential conflict of interest relevant to this article was reported.

FUNDING

This research was supported by a grant from the Korean ARPA-H Project through the Korean Health Industry Development Institute, funded by the Ministry of Health & Welfare, Republic of Korea (RS-2024-00512375).

ACKNOWLEDGMENTS

None.

AUTHOR CONTRIBUTIONS

Conceptualization: HKS, JYM. Data curation: HKS. Formal analysis: HKS, JL. Methodology: HKS, JL. Visualization: HKS, JL. Methodology: HKS, JL. Visualization: HKS, JL. Funding acquisition: JYM. Writing - original draft: JL. Writing - review & editing: JL, HKS, MHO, JYK, KHK, JYM. All authors read and agreed to the published version of the manuscript.

SUPPLEMENTARY MATERIALS

Supplementary materials can be found via https://doi.org/10.4266/acc.000676.

Supplementary Table 1.

Post-hoc classification of Round 2 indicators by consensus type (type A–D^a))

acc-000676-Supplementary-Table-1.pdf

Figure 1.

Study flowchart.

Table 1.

Summary of Delphi survey rounds and response rates

Round	Participants (n/total)	Response rate (%)	Period	Rating scale	Purpose and criteria
1	22/24	91.7	Apr 10–14, 2025	5-Point Likert	Importance rating of 42 candidate indicators across 6 domains.
					Consensus: CVR ≥0.455 and ≥75% rating 4–5
					Outcome: 36 accepted; 4 excluded; 2 revised; 4 added
2	20/24	83.3	May 13–17, 2025	10-Point Likert	Appropriateness assessment of 42 indicators
					Consensus: CVR ≥0.429 and ≥75% rating 7–10
					Outcome: 25 accepted; 8 borderline (→ Round 3); 9 excluded
3	19/24	79.2	Jul 9–14, 2025	5-Point Likert	Validation of 8 borderline items: paired consistency check (3 items) and re-evaluation (5 items)
					Consensus: CVR ≥0.417
					Outcome: 4 accepted; 4 rejected; Final framework: 29 indicators across 4 domains

CVR critical thresholds: 0.455 (Round 1, n=22); 0.429 (Round 2, n=20); 0.417 (Round 3, n=19).

CVR: content validity ratio.

Table 2.

Candidate indicators evaluated across Delphi Rounds 1 and 2

No.	Round 1 indicator	Mean	CVR	No.	Round 2 Indicator (revised/added)	Mean	CVR	Round 2 outcome
Domain I: ICU capability indicators — Capacity
Staffing and personnel
1	Full-time intensivist staffing	4.64	0.909	1	Full-time intensivist staffing	8.90	0.900	Accepted
2	24/7 Coverage by intensivist	4.27	0.636	2	24/7 Coverage by intensivist	7.75	0.700	Accepted
3	Nighttime ICU physician coverage	4.09	0.636	3	Nighttime ICU physician coverage	8.10	0.800	Accepted
4	Nurse-to-bed ratio	4.59	1.000	4	Nurse-to-bed ratio	9.45	0.900	Accepted
5	Nursing staff with certified ICU training	4.14	0.727	5	Nursing staff with certified ICU training	7.75	0.600	Accepted
6	Physician assistant	2.95	–0.273	-	-	-	-	Rejected
Facilities & beds
7	Number of operational ICU beds	3.45	0.091	6	Operational ICU beds (revised)	7.45	0.300	Borderline
-	-	-	-	7	Ratio of ICU beds to total hospital beds (added)	7.45	0.400	Borderline
-	-	-	-	8	Appropriate ICU occupancy rate, 70%–85% (added)	7.95	0.500	Accepted
-	-	-	-	9	Reserve/surge personnel (added)	6.55	0.200	Rejected
8	Multidisciplinary ICU rounds	4.23	0.636	10	Multidisciplinary ICU rounds	8.30	0.800	Accepted
Equipment
9	Advanced equipment-II (ventilator, CRRT, ECMO, ultrasound, ABGA)	4.41	0.727	11	Advanced equipment-II	8.90	1.000	Accepted
10	Advanced equipment-I (hemodynamic monitor, HFNC, BiPAP, NIV, TTM)	4.32	0.909	12	Advanced equipment-I	9.25	1.000	Accepted
Design & policy
11	Single-bed isolation room ratio	4.23	0.545	13	Single-bed isolation room ratio	7.75	0.400	Borderline
12	Isolation room with anteroom/independent access	3.73	0.455	14	Isolation room with anteroom	6.95	0.200	Rejected
13	On-call room for physicians in ICU	3.45	0.000	-	-	-	-	Rejected
14	Admission/discharge policy → authority	3.95	0.364	15	Admission/discharge authority (revised)	7.45	0.500	Accepted
Domain I: ICU capability indicators — Capability
Life support
15	LSI availability (ventilator, CRRT, ECMO, HFNC/BiPAP, vasopressors, A-line)	4.82	1.000	16	LSI availability	9.55	1.000	Accepted
16	Proportion of patients receiving LSI	4.18	0.636	17	Proportion receiving LSI	8.05	0.700	Accepted
Specialized care
17	24/7 Cardiovascular intervention	4.55	1.000	18	24/7 Cardiovascular intervention	9.55	1.000	Accepted
18	24/7 ECMO	4.59	0.909	19	24/7 ECMO	9.30	1.000	Accepted
19	24/7 Open-heart surgery → emergency CABG	4.00	0.273	20	Emergency CABG 24/7 (revised)	7.30	0.400	Borderline
-	-	-	-	21	Number of CABG surgeons (added)	6.80	0.200	Rejected
20	Acute stroke treatment	4.36	0.727	22	Acute stroke treatment	8.55	1.000	Accepted
21	Organ transplant → brain-dead donor management	3.73	0.182	23	Brain-dead donor management (revised)	6.40	0.100	Rejected
22	Other LSI procedures (thrombolysis, echo, pacing, ablation, tracheostomy)	4.27	0.636	24	Other critical procedures	8.45	0.800	Accepted
Domain II: ICU classification criteria — Human resources
Physicians
23	24/7 on-call CCM subspecialist	4.50	0.818	25	24/7 On-call CCM subspecialist	8.75	0.900	Accepted
24	Daytime CCM subspecialist	4.82	0.909	26	Daytime CCM subspecialist	9.10	0.900	Accepted
Nursing & allied
25	24/7 nursing staff with certified ICU training	3.91	0.455	27	24/7 Specialized nurses	7.10	0.300	Rejected
26	Nurses with extra training/training programs	3.86	0.273	28	Nurse training programs (revised)	6.65	0.100	Rejected
27	Other interprofessional personnel (RT, PT, pharmacist, nutritionist)	4.14	0.636	29	Other interprofessional personnel	7.80	0.700	Accepted
Domain II: ICU classification criteria — Space, equipment & monitoring
Equipment & monitoring
28	Advanced hemodynamic monitoring equipment	4.45	0.818	30	Advanced hemodynamic monitoring	8.90	0.900	Accepted
29	Invasive BP monitoring & CVP	4.36	0.636	31	Invasive BP monitoring & CVP	8.45	0.700	Accepted
30	Noninvasive monitoring (SpO₂, ECG, urine output)	4.50	0.727	32	Noninvasive monitoring	8.45	0.800	Accepted
31	Advanced ventilator & hemodynamic support (CRRT, tracheostomy, ECMO)	4.64	0.909	33	Advanced organ support	9.30	1.000	Accepted
32	Basic mechanical ventilatory support, inotropes, intermittent RRT	4.64	0.909	34	Basic organ support	9.40	1.000	Accepted
33	Oxygen therapy & noninvasive support (HFNC, BiPAP/NIV)	4.59	0.909	35	Oxygen therapy & noninvasive support	9.25	1.000	Accepted
Space & safety infrastructure
34	Single-bed ICU room with central monitoring station	4.05	0.545	36	Single-bed ICU room (unchanged)	7.25	0.200	Borderline
35	Central monitoring station	4.27	0.636	37	Central monitoring station	7.70	0.400	Borderline
36	One or more negative pressure isolation room	4.05	0.545	38	Negative pressure room	7.25	0.300	Borderline
Domain II: ICU classification criteria — Ward support services
Critical care outreach
37	ICU outreach/rapid response system	4.00	0.364	39	Rapid response system (revised)	7.05	0.400	Rejected
Domain II: ICU classification criteria — Education, training, research & quality management
Education & research
38	CCM fellowship training institution	4.09	0.727	40	CCM fellowship training	7.30	0.400	Borderline
39	Residency training hospital	3.91	0.364	41	Residency training hospital	6.95	0.200	Rejected
40	Research support infrastructure	3.23	–0.273	42	Research support infrastructure	6.55	0.200	Rejected
Regional referral (rejected at Round 1)
41	Regional emergency medical center/trauma center	3.50	0.000	-	-	-	-	Rejected
42	Local emergency medical center	3.09	–0.273	-	-	-	-	Rejected

Round 1: 5-point Likert scale (n=22); CVR threshold 0.455. Round 2: 10-point Likert scale (n=20); CVR threshold 0.429. Accepted: met Round 2 consensus criteria; Borderline: carried forward to Round 3; Rejected: excluded; Added: new item after Round 1.

CVR: content validity ratio; ICU: intensive care unit; CRRT: continuous renal replacement therapy; ECMO: extracorporeal membrane oxygenation; ABGA: arterial blood gas analysis; HFNC: high-flow nasal cannula;

BiPAP: bilevel positive airway pressure; NIV: noninvasive ventilation; TTM: targeted temperature management; LSI: life support interventions; CCM: critical care medicine; RT: respiratory therapist; PT: physical therapist; BP: blood pressure; ECG: electrocardiography; RRT: renal replacement therapy.

Table 3.

Results of Delphi Round 3: consistency check and re-evaluation of borderline items

Analysis type	Item description	Question phrasing	Mean±SD	CVR	Decision	Rationale
1. Consistency check (paired items)	Emergency CABG (24/7 availability)	Positive	4.37±0.83	0.789	Reject	Inconsistent response: significant contradiction between positive and reverse items; high CVR on both phrasings indicates genuine ambiguity about mandatory status
	Emergency CABG (24/7 availability)	Reverse	4.00±1.20	0.579	Reject
	Negative pressure isolation room	Positive	4.26±0.81	0.579	Reject	Unstable consensus: CVR difference between phrasings >0.2, indicating genuine expert uncertainty
	Negative pressure isolation room	Reverse	3.90±1.15	0.368^a)	Reject
	Operational ICU beds (absolute number)	Positive	3.95±0.91	0.368^a)	Reject	Low consensus: failed to meet CVR threshold in both phrasings. Absolute bed count was consistently viewed as insufficient to capture ICU capability
	Operational ICU beds (absolute number)	Reverse	3.79±1.03	0.158^a)	Reject
2. Re-evaluation (single items)	Central monitoring system (standalone)	Positive	4.32±0.75	0.895	Accept	Met consensus: CVR >0.417 and agreement >75%.
	Hospital-to-ICU bed ratio	Positive	4.16±0.83	0.474	Accept	Met consensus: CVR threshold passed (0.474 >0.417).
	Isolation bed proportion	Positive	4.16±0.76	0.579	Accept	Met consensus: CVR threshold passed (0.579 >0.417).
	Training institution (accreditation)	Positive	3.79±0.79	0.368^a)	Reject	Low consensus: CVR below threshold (0.368 <0.417). Accreditation not considered a mandatory ICU capability criterion
	Single-bed ICU room (w/central monitor)	Positive	4.26±0.73	0.895	Accept	Met consensus: CVR >0.417 and agreement >75%.

Round 3: 5-point Likert scale (n=19); CVR critical threshold=0.417. Paired Items: tested with positive and reverse-phrased questions; CVR difference >0.2 considered inconsistent.

SD: standard deviation; CVR: content validity ratio; CABG: coronary artery bypass grafting; ICU: intensive care unit.

^a)Indicates CVR values below the critical threshold (0.417, n=19).

Table 4.

Final consensus-based framework for ICU capability assessment (29 indicators)

Domain	Category	Indicator	Mean±SD	CVR
Capacity (facilities & resources)	Staffing	1. Full-time intensivist staffing in ICU	8.90±1.68	0.900
		2. Nurse-to-bed ratio in ICU	9.45±1.19	0.900
		3. Nighttime ICU physician coverage	8.10±1.37	0.800
		4. Nursing staff with specialized/certified ICU training	7.75±1.62	0.600
		5. 24/7 Coverage by critical care medicine specialist	7.75±1.94	0.700
	Equipment	6. Advanced critical care equipment-I (hemodynamic monitor, HFNC, BiPAP, NIV, TTM)	9.25±0.91	1.000
	Equipment	7. Advanced critical care equipment-II (ventilator, portable ventilator, CRRT, ECMO, ultrasound, ABGA)	8.90±1.07	1.000
	Design & policy	8. Multidisciplinary ICU rounds (respiratory therapists, pharmacists, nutritionists, social workers)	8.30±1.22	0.800
		9. Appropriate ICU occupancy rate (optimal 70%–85%)	7.95±1.76	0.500
		10. Ratio of ICU beds to total hospital beds^a)	4.16±0.83	0.474
	Facilities & bed	11. Ratio of single-bed isolation rooms in ICU^a)	4.16±0.76	0.579
	Facilities & bed	12. Admission/discharge authority (managed by dedicated specialist)	7.45±1.88	0.500
Capability (service provision)	Life support	13. Availability of LSI (ventilator, CRRT, ECMO, HFNC/BiPAP, vasopressors, arterial line)	9.55±0.69	1.000
	Life support	14. Proportion of patients receiving LSI	8.05±1.47	0.700
	Specialized care	15. Cardiovascular intervention availability (24/7)	9.55±0.76	1.000
		16. ECMO availability (24/7)	9.30±0.87	1.000
		17. Acute stroke treatment (facilities & specialists)	8.55±1.00	1.000
		18. Other critical procedures (thrombolysis, thrombectomy, echocardiography, pacing, ablation, tracheostomy)	8.45±1.50	0.800
Human resources (workforce)	Physicians, nursing & allied	19. Daytime coverage by ICU-trained physicians	9.10±1.33	0.900
		20. 24/7 Or on-call coverage by ICU-trained physicians	8.75±1.25	0.900
		21. Other interprofessional personnel (respiratory therapists, physiotherapists, pharmacists, nutritionists)	7.80±1.44	0.700
Space & equipment (infrastructure)	Equipment & monitoring	22. Advanced organ & hemodynamic support (CRRT, tracheostomy, ECMO)	9.30±0.80	1.000
		23. Basic organ support (ventilators, inotropes, intermittent RRT)	9.40±0.75	1.000
		24. Oxygen therapy & noninvasive support (HFNC, BiPAP/NIV)	9.25±0.79	1.000
		25. Advanced hemodynamic monitoring (catheterization, ultrasound, cerebral/pulmonary monitoring)	8.90±1.17	0.900
		26. Invasive blood pressure monitoring & CVP	8.45±1.82	0.700
		27. Noninvasive monitoring (SpO₂, ECG, urine output)	8.45±1.50	0.800
	Safety & infra- structure	28. Single-bed ICU room with central monitoring station^a)	4.26±0.73	0.895
	Safety & infra- structure	29. Central monitoring station^a)	4.32±0.75	0.895

The mean±SD and CVR values are from Round 2 (10-point Likert scale, n=20), except where indicated. CVR critical thresholds: 0.429 (Round 2, n=20); 0.417 (Round 3, n=19).

ICU: intensive care unit; SD: standard deviation; CVR: content validity ratio; HFNC: high-flow nasal cannula; BiPAP: bilevel positive airway pressure; NIV: noninvasive ventilation; TTM: targeted temperature management; CRRT: continuous renal replacement therapy; ECMO: extracorporeal membrane oxygenation; ABGA: arterial blood gas analysis; LSI: life support interventions; RRT: renal replacement therapy; CVP: central venous pressure; ECG: electrocardiography.

^a)Were accepted in Round 3 (5-point Likert scale, n=19); values shown are Round 3 results.

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Developing consensus-based indicators for intensive care unit capacity and capability in South Korea: a modified Delphi study

Acute Crit Care. 2026;41(2):282-294. Published online May 28, 2026

DOI: https://doi.org/10.4266/acc.000676

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Figure

Developing consensus-based indicators for intensive care unit capacity and capability in South Korea: a modified Delphi study

Figure 1. Study flowchart.

Figure 1.

Developing consensus-based indicators for intensive care unit capacity and capability in South Korea: a modified Delphi study

Round	Participants (n/total)	Response rate (%)	Period	Rating scale	Purpose and criteria
1	22/24	91.7	Apr 10–14, 2025	5-Point Likert	Importance rating of 42 candidate indicators across 6 domains.
					Consensus: CVR ≥0.455 and ≥75% rating 4–5
					Outcome: 36 accepted; 4 excluded; 2 revised; 4 added
2	20/24	83.3	May 13–17, 2025	10-Point Likert	Appropriateness assessment of 42 indicators
					Consensus: CVR ≥0.429 and ≥75% rating 7–10
					Outcome: 25 accepted; 8 borderline (→ Round 3); 9 excluded
3	19/24	79.2	Jul 9–14, 2025	5-Point Likert	Validation of 8 borderline items: paired consistency check (3 items) and re-evaluation (5 items)
					Consensus: CVR ≥0.417
					Outcome: 4 accepted; 4 rejected; Final framework: 29 indicators across 4 domains

No.	Round 1 indicator	Mean	CVR	No.	Round 2 Indicator (revised/added)	Mean	CVR	Round 2 outcome
Domain I: ICU capability indicators — Capacity
Staffing and personnel
1	Full-time intensivist staffing	4.64	0.909	1	Full-time intensivist staffing	8.90	0.900	Accepted
2	24/7 Coverage by intensivist	4.27	0.636	2	24/7 Coverage by intensivist	7.75	0.700	Accepted
3	Nighttime ICU physician coverage	4.09	0.636	3	Nighttime ICU physician coverage	8.10	0.800	Accepted
4	Nurse-to-bed ratio	4.59	1.000	4	Nurse-to-bed ratio	9.45	0.900	Accepted
5	Nursing staff with certified ICU training	4.14	0.727	5	Nursing staff with certified ICU training	7.75	0.600	Accepted
6	Physician assistant	2.95	–0.273	-	-	-	-	Rejected
Facilities & beds
7	Number of operational ICU beds	3.45	0.091	6	Operational ICU beds (revised)	7.45	0.300	Borderline
-	-	-	-	7	Ratio of ICU beds to total hospital beds (added)	7.45	0.400	Borderline
-	-	-	-	8	Appropriate ICU occupancy rate, 70%–85% (added)	7.95	0.500	Accepted
-	-	-	-	9	Reserve/surge personnel (added)	6.55	0.200	Rejected
8	Multidisciplinary ICU rounds	4.23	0.636	10	Multidisciplinary ICU rounds	8.30	0.800	Accepted
Equipment
9	Advanced equipment-II (ventilator, CRRT, ECMO, ultrasound, ABGA)	4.41	0.727	11	Advanced equipment-II	8.90	1.000	Accepted
10	Advanced equipment-I (hemodynamic monitor, HFNC, BiPAP, NIV, TTM)	4.32	0.909	12	Advanced equipment-I	9.25	1.000	Accepted
Design & policy
11	Single-bed isolation room ratio	4.23	0.545	13	Single-bed isolation room ratio	7.75	0.400	Borderline
12	Isolation room with anteroom/independent access	3.73	0.455	14	Isolation room with anteroom	6.95	0.200	Rejected
13	On-call room for physicians in ICU	3.45	0.000	-	-	-	-	Rejected
14	Admission/discharge policy → authority	3.95	0.364	15	Admission/discharge authority (revised)	7.45	0.500	Accepted
Domain I: ICU capability indicators — Capability
Life support
15	LSI availability (ventilator, CRRT, ECMO, HFNC/BiPAP, vasopressors, A-line)	4.82	1.000	16	LSI availability	9.55	1.000	Accepted
16	Proportion of patients receiving LSI	4.18	0.636	17	Proportion receiving LSI	8.05	0.700	Accepted
Specialized care
17	24/7 Cardiovascular intervention	4.55	1.000	18	24/7 Cardiovascular intervention	9.55	1.000	Accepted
18	24/7 ECMO	4.59	0.909	19	24/7 ECMO	9.30	1.000	Accepted
19	24/7 Open-heart surgery → emergency CABG	4.00	0.273	20	Emergency CABG 24/7 (revised)	7.30	0.400	Borderline
-	-	-	-	21	Number of CABG surgeons (added)	6.80	0.200	Rejected
20	Acute stroke treatment	4.36	0.727	22	Acute stroke treatment	8.55	1.000	Accepted
21	Organ transplant → brain-dead donor management	3.73	0.182	23	Brain-dead donor management (revised)	6.40	0.100	Rejected
22	Other LSI procedures (thrombolysis, echo, pacing, ablation, tracheostomy)	4.27	0.636	24	Other critical procedures	8.45	0.800	Accepted
Domain II: ICU classification criteria — Human resources
Physicians
23	24/7 on-call CCM subspecialist	4.50	0.818	25	24/7 On-call CCM subspecialist	8.75	0.900	Accepted
24	Daytime CCM subspecialist	4.82	0.909	26	Daytime CCM subspecialist	9.10	0.900	Accepted
Nursing & allied
25	24/7 nursing staff with certified ICU training	3.91	0.455	27	24/7 Specialized nurses	7.10	0.300	Rejected
26	Nurses with extra training/training programs	3.86	0.273	28	Nurse training programs (revised)	6.65	0.100	Rejected
27	Other interprofessional personnel (RT, PT, pharmacist, nutritionist)	4.14	0.636	29	Other interprofessional personnel	7.80	0.700	Accepted
Domain II: ICU classification criteria — Space, equipment & monitoring
Equipment & monitoring
28	Advanced hemodynamic monitoring equipment	4.45	0.818	30	Advanced hemodynamic monitoring	8.90	0.900	Accepted
29	Invasive BP monitoring & CVP	4.36	0.636	31	Invasive BP monitoring & CVP	8.45	0.700	Accepted
30	Noninvasive monitoring (SpO₂, ECG, urine output)	4.50	0.727	32	Noninvasive monitoring	8.45	0.800	Accepted
31	Advanced ventilator & hemodynamic support (CRRT, tracheostomy, ECMO)	4.64	0.909	33	Advanced organ support	9.30	1.000	Accepted
32	Basic mechanical ventilatory support, inotropes, intermittent RRT	4.64	0.909	34	Basic organ support	9.40	1.000	Accepted
33	Oxygen therapy & noninvasive support (HFNC, BiPAP/NIV)	4.59	0.909	35	Oxygen therapy & noninvasive support	9.25	1.000	Accepted
Space & safety infrastructure
34	Single-bed ICU room with central monitoring station	4.05	0.545	36	Single-bed ICU room (unchanged)	7.25	0.200	Borderline
35	Central monitoring station	4.27	0.636	37	Central monitoring station	7.70	0.400	Borderline
36	One or more negative pressure isolation room	4.05	0.545	38	Negative pressure room	7.25	0.300	Borderline
Domain II: ICU classification criteria — Ward support services
Critical care outreach
37	ICU outreach/rapid response system	4.00	0.364	39	Rapid response system (revised)	7.05	0.400	Rejected
Domain II: ICU classification criteria — Education, training, research & quality management
Education & research
38	CCM fellowship training institution	4.09	0.727	40	CCM fellowship training	7.30	0.400	Borderline
39	Residency training hospital	3.91	0.364	41	Residency training hospital	6.95	0.200	Rejected
40	Research support infrastructure	3.23	–0.273	42	Research support infrastructure	6.55	0.200	Rejected
Regional referral (rejected at Round 1)
41	Regional emergency medical center/trauma center	3.50	0.000	-	-	-	-	Rejected
42	Local emergency medical center	3.09	–0.273	-	-	-	-	Rejected

Analysis type	Item description	Question phrasing	Mean±SD	CVR	Decision	Rationale
1. Consistency check (paired items)	Emergency CABG (24/7 availability)	Positive	4.37±0.83	0.789	Reject	Inconsistent response: significant contradiction between positive and reverse items; high CVR on both phrasings indicates genuine ambiguity about mandatory status
	Emergency CABG (24/7 availability)	Reverse	4.00±1.20	0.579	Reject
	Negative pressure isolation room	Positive	4.26±0.81	0.579	Reject	Unstable consensus: CVR difference between phrasings >0.2, indicating genuine expert uncertainty
	Negative pressure isolation room	Reverse	3.90±1.15	0.368^a)	Reject
	Operational ICU beds (absolute number)	Positive	3.95±0.91	0.368^a)	Reject	Low consensus: failed to meet CVR threshold in both phrasings. Absolute bed count was consistently viewed as insufficient to capture ICU capability
	Operational ICU beds (absolute number)	Reverse	3.79±1.03	0.158^a)	Reject
2. Re-evaluation (single items)	Central monitoring system (standalone)	Positive	4.32±0.75	0.895	Accept	Met consensus: CVR >0.417 and agreement >75%.
	Hospital-to-ICU bed ratio	Positive	4.16±0.83	0.474	Accept	Met consensus: CVR threshold passed (0.474 >0.417).
	Isolation bed proportion	Positive	4.16±0.76	0.579	Accept	Met consensus: CVR threshold passed (0.579 >0.417).
	Training institution (accreditation)	Positive	3.79±0.79	0.368^a)	Reject	Low consensus: CVR below threshold (0.368 <0.417). Accreditation not considered a mandatory ICU capability criterion
	Single-bed ICU room (w/central monitor)	Positive	4.26±0.73	0.895	Accept	Met consensus: CVR >0.417 and agreement >75%.

Domain	Category	Indicator	Mean±SD	CVR
Capacity (facilities & resources)	Staffing	1. Full-time intensivist staffing in ICU	8.90±1.68	0.900
		2. Nurse-to-bed ratio in ICU	9.45±1.19	0.900
		3. Nighttime ICU physician coverage	8.10±1.37	0.800
		4. Nursing staff with specialized/certified ICU training	7.75±1.62	0.600
		5. 24/7 Coverage by critical care medicine specialist	7.75±1.94	0.700
	Equipment	6. Advanced critical care equipment-I (hemodynamic monitor, HFNC, BiPAP, NIV, TTM)	9.25±0.91	1.000
	Equipment	7. Advanced critical care equipment-II (ventilator, portable ventilator, CRRT, ECMO, ultrasound, ABGA)	8.90±1.07	1.000
	Design & policy	8. Multidisciplinary ICU rounds (respiratory therapists, pharmacists, nutritionists, social workers)	8.30±1.22	0.800
		9. Appropriate ICU occupancy rate (optimal 70%–85%)	7.95±1.76	0.500
		10. Ratio of ICU beds to total hospital beds^a)	4.16±0.83	0.474
	Facilities & bed	11. Ratio of single-bed isolation rooms in ICU^a)	4.16±0.76	0.579
	Facilities & bed	12. Admission/discharge authority (managed by dedicated specialist)	7.45±1.88	0.500
Capability (service provision)	Life support	13. Availability of LSI (ventilator, CRRT, ECMO, HFNC/BiPAP, vasopressors, arterial line)	9.55±0.69	1.000
	Life support	14. Proportion of patients receiving LSI	8.05±1.47	0.700
	Specialized care	15. Cardiovascular intervention availability (24/7)	9.55±0.76	1.000
		16. ECMO availability (24/7)	9.30±0.87	1.000
		17. Acute stroke treatment (facilities & specialists)	8.55±1.00	1.000
		18. Other critical procedures (thrombolysis, thrombectomy, echocardiography, pacing, ablation, tracheostomy)	8.45±1.50	0.800
Human resources (workforce)	Physicians, nursing & allied	19. Daytime coverage by ICU-trained physicians	9.10±1.33	0.900
		20. 24/7 Or on-call coverage by ICU-trained physicians	8.75±1.25	0.900
		21. Other interprofessional personnel (respiratory therapists, physiotherapists, pharmacists, nutritionists)	7.80±1.44	0.700
Space & equipment (infrastructure)	Equipment & monitoring	22. Advanced organ & hemodynamic support (CRRT, tracheostomy, ECMO)	9.30±0.80	1.000
		23. Basic organ support (ventilators, inotropes, intermittent RRT)	9.40±0.75	1.000
		24. Oxygen therapy & noninvasive support (HFNC, BiPAP/NIV)	9.25±0.79	1.000
		25. Advanced hemodynamic monitoring (catheterization, ultrasound, cerebral/pulmonary monitoring)	8.90±1.17	0.900
		26. Invasive blood pressure monitoring & CVP	8.45±1.82	0.700
		27. Noninvasive monitoring (SpO₂, ECG, urine output)	8.45±1.50	0.800
	Safety & infra- structure	28. Single-bed ICU room with central monitoring station^a)	4.26±0.73	0.895
	Safety & infra- structure	29. Central monitoring station^a)	4.32±0.75	0.895

Table 1. Summary of Delphi survey rounds and response rates

CVR critical thresholds: 0.455 (Round 1, n=22); 0.429 (Round 2, n=20); 0.417 (Round 3, n=19).

CVR: content validity ratio.

Table 2. Candidate indicators evaluated across Delphi Rounds 1 and 2

Table 3. Results of Delphi Round 3: consistency check and re-evaluation of borderline items

Round 3: 5-point Likert scale (n=19); CVR critical threshold=0.417. Paired Items: tested with positive and reverse-phrased questions; CVR difference >0.2 considered inconsistent.

SD: standard deviation; CVR: content validity ratio; CABG: coronary artery bypass grafting; ICU: intensive care unit.

Indicates CVR values below the critical threshold (0.417, n=19).

Table 4. Final consensus-based framework for ICU capability assessment (29 indicators)

The mean±SD and CVR values are from Round 2 (10-point Likert scale, n=20), except where indicated. CVR critical thresholds: 0.429 (Round 2, n=20); 0.417 (Round 3, n=19).

Were accepted in Round 3 (5-point Likert scale, n=19); values shown are Round 3 results.