Appl Clin Inform 2024; 15(03): 414-427
DOI: 10.1055/a-2299-7643
Review Article

Centralized Multipatient Dashboards' Impact on Intensive Care Unit Clinician Performance and Satisfaction: A Systematic Review

Inna Strechen
1   Department of Anesthesiology and Perioperative Medicine, Division of Critical Care, Mayo Clinic, Rochester, Minnesota, United States
Svetlana Herasevich
1   Department of Anesthesiology and Perioperative Medicine, Division of Critical Care, Mayo Clinic, Rochester, Minnesota, United States
Amelia Barwise
2   Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States
Juan Garcia-Mendez
1   Department of Anesthesiology and Perioperative Medicine, Division of Critical Care, Mayo Clinic, Rochester, Minnesota, United States
Lucrezia Rovati
2   Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States
3   Department of Emergency Medicine, University of Milano-Bicocca, School of Medicine and Surgery, Milan, Italy
Brian Pickering
1   Department of Anesthesiology and Perioperative Medicine, Division of Critical Care, Mayo Clinic, Rochester, Minnesota, United States
Daniel Diedrich
1   Department of Anesthesiology and Perioperative Medicine, Division of Critical Care, Mayo Clinic, Rochester, Minnesota, United States
Vitaly Herasevich
1   Department of Anesthesiology and Perioperative Medicine, Division of Critical Care, Mayo Clinic, Rochester, Minnesota, United States
› Author Affiliations


Background Intensive care unit (ICU) clinicians encounter frequent challenges with managing vast amounts of fragmented data while caring for multiple critically ill patients simultaneously. This may lead to increased provider cognitive load that may jeopardize patient safety.

Objectives This systematic review assesses the impact of centralized multipatient dashboards on ICU clinician performance, perceptions regarding the use of these tools, and patient outcomes.

Methods A literature search was conducted on February 9, 2023, using the EBSCO CINAHL, Cochrane Central Register of Controlled Trials, Embase, IEEE Xplore, MEDLINE, Scopus, and Web of Science Core Collection databases. Eligible studies that included ICU clinicians as participants and tested the effect of dashboards designed for use by multiple users to manage multiple patients on user performance and/or satisfaction compared with the standard practice. We narratively synthesized eligible studies following the SWiM (Synthesis Without Meta-analysis) guidelines. Studies were grouped based on dashboard type and outcomes assessed.

Results The search yielded a total of 2,407 studies. Five studies met inclusion criteria and were included. Among these, three studies evaluated interactive displays in the ICU, one study assessed two dashboards in the pediatric ICU (PICU), and one study examined centralized monitor in the PICU. Most studies reported several positive outcomes, including reductions in data gathering time before rounds, a decrease in misrepresentations during multidisciplinary rounds, improved daily documentation compliance, faster decision-making, and user satisfaction. One study did not report any significant association.

Conclusion The multipatient dashboards were associated with improved ICU clinician performance and were positively perceived in most of the included studies. The risk of bias was high, and the certainty of evidence was very low, due to inconsistencies, imprecision, indirectness in the outcome measure, and methodological limitations. Designing and evaluating multipatient tools using robust research methodologies is an important focus for future research.

Protection of Human and Animal Subjects

Not applicable.

Publication History

Received: 22 January 2024

Accepted: 03 April 2024

Accepted Manuscript online:
04 April 2024

Article published online:
29 May 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

  • References

  • 1 Lindroth HL, Pinevich Y, Barwise AK. et al. Information and data visualization needs among direct care nurses in the intensive care unit. Appl Clin Inform 2022; 13 (05) 1207-1213
  • 2 Egan M. Clinical dashboards: impact on workflow, care quality, and patient safety. Crit Care Nurs Q 2006; 29 (04) 354-361
  • 3 Nijor S, Rallis G, Lad N, Gokcen E. Patient safety issues from information overload in electronic medical records. J Patient Saf 2022; 18 (06) e999-e1003
  • 4 Herasevich S, Pinevich Y, Lindroth HL, Herasevich V, Pickering BW, Barwise AK. Who needs clinician attention first? A qualitative study of critical care clinicians' needs that enable the prioritization of care for populations of acutely ill patients. Int J Med Inform 2023; 177: 105118
  • 5 Bauer DT, Guerlain S, Brown PJ. The design and evaluation of a graphical display for laboratory data. J Am Med Inform Assoc 2010; 17 (04) 416-424
  • 6 Pilcher DV, Hensman T, Bihari S. et al. Measuring the impact of ICU strain on mortality, after-hours discharge, discharge delay, interhospital transfer, and readmission in Australia with the activity index. Crit Care Med 2023; 51 (12) 1623-1637
  • 7 Görges M, Westenskow DR, Markewitz BA. Evaluation of an integrated intensive care unit monitoring display by critical care fellow physicians. J Clin Monit Comput 2012; 26 (06) 429-436
  • 8 Barwise A, Caples S, Jensen J, Pickering B, Herasevich V. Information needs for the rapid response team electronic clinical tool. BMC Med Inform Decis Mak 2017; 17 (01) 142
  • 9 Reese TJ, Kawamoto K, Del Fiol G. et al. Approaching the design of an information display to support critical care. 2017 IEEE International Conference on Healthcare Informatics (ICHI) 2017: 439-443
  • 10 Görges M, Kück K, Koch SH, Agutter J, Westenskow DR. A far-view intensive care unit monitoring display enables faster triage. Dimens Crit Care Nurs 2011; 30 (04) 206-217
  • 11 Alhmoud B, Melley D, Khan N, Bonicci T, Patel R, Banerjee A. Evaluating a novel, integrative dashboard for health professionals' performance in managing deteriorating patients: a quality improvement project. BMJ Open Qual 2022; 11 (04) 9
  • 12 Miller ME, Scholl G, Corby S, Mohan V, Gold JA. The impact of electronic health record-based simulation during intern boot camp: interventional study. JMIR Med Educ 2021; 7 (01) e25828
  • 13 Khairat SS, Dukkipati A, Lauria HA, Bice T, Travers D, Carson SS. The impact of visualization dashboards on quality of care and clinician satisfaction: integrative literature review. JMIR Human Factors 2018; 5 (02) e22
  • 14 Waller RG, Wright MC, Segall N. et al. Novel displays of patient information in critical care settings: a systematic review. J Am Med Inform Assoc 2019; 26 (05) 479-489
  • 15 Thomas MM, Kannampallil T, Abraham J, Marai GI. Echo: a large display interactive visualization of ICU data for effective care handoffs. 2017 IEEE Workshop Vis Anal Healthc VAHC (2017) 2017 October: 47-54
  • 16 Herasevich S, Pinevich Y, Lipatov K. et al. Evaluation of digital health strategy to support clinician-led critically ill patient population management: a randomized crossover study. Crit Care Explor 2023; 5 (05) e0909
  • 17 Herasevich S, Lipatov K, Pinevich Y. et al. The impact of health information technology for early detection of patient deterioration on mortality and length of stay in the hospital acute care setting: systematic review and meta-analysis. Crit Care Med 2022; 50 (08) 1198-1209
  • 18 Page MJ, McKenzie JE, Bossuyt PM. et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021; 372: n71
  • 19 Campbell M, McKenzie JE, Sowden A. et al. Synthesis without meta-analysis (SWiM) in systematic reviews: reporting guideline. BMJ 2020; 368: l6890
  • 20 Covidence systematic review software. Veritas Health Innovation, Melbourne, Australia. Accessed May 6, 2024 at
  • 21 Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ. et al., eds. Cochrane Handbook for Systematic Reviews of Interventions version 6.4 (updated August 2023). Cochrane 2023. Accessed at:
  • 22 Moher D, Liberati A, Tetzlaff J, Altman DG. PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 2009; 6 (07) e1000097
  • 23 Sterne JAC, Savović J, Page MJ. et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ 2019; 366: l4898
  • 24 Sterne JA, Hernán MA, Reeves BC. et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ 2016; 355: i4919
  • 25 Horsley T, Dingwall O, Sampson M. Checking reference lists to find additional studies for systematic reviews. Cochrane Database Syst Rev 2011; 2011 (08) MR000026
  • 26 Pageler NM, Longhurst CA, Wood M. et al. Use of electronic medical record-enhanced checklist and electronic dashboard to decrease CLABSIs. Pediatrics 2014; 133 (03) e738-e746
  • 27 Shaw SJ, Jacobs B, Stockwell DC, Futterman C, Spaeder MC. Effect of a real-time pediatric ICU safety bundle dashboard on quality improvement measures. Jt Comm J Qual Patient Saf 2015; 41 (09) 414-420
  • 28 Boudreault L, Hebert-Lavoie M, Ung K. et al. Situation awareness-oriented dashboard in ICUs in support of resource management in time of pandemics. IEEE J Transl Eng Health Med 2023; 11: 151-160
  • 29 Lai CH, Li KW, Hu FW. et al. Integration of an intensive care unit visualization dashboard (i-Dashboard) as a platform to facilitate multidisciplinary rounds: cluster-randomized controlled trial. J Med Internet Res 2022; 24 (05) e35981
  • 30 Lee K, Jung SY, Hwang H. et al. A novel concept for integrating and delivering health information using a comprehensive digital dashboard: an analysis of healthcare professionals' intention to adopt a new system and the trend of its real usage. Int J Med Inform 2017; 97: 98-108
  • 31 Pickering BW, Herasevich V, Ahmed A, Gajic O. Novel representation of clinical information in the ICU: developing user interfaces which reduce information overload. Appl Clin Inform 2010; 1 (02) 116-131
  • 32 Manor-Shulman O, Beyene J, Frndova H, Parshuram CS. Quantifying the volume of documented clinical information in critical illness. J Crit Care 2008; 23 (02) 245-250
  • 33 Pickering BW, Litell JM, Herasevich V, Gajic O. Clinical review: the hospital of the future - building intelligent environments to facilitate safe and effective acute care delivery. Crit Care 2012; 16 (02) 220
  • 34 Fareed N, Swoboda CM, Chen S, Potter E, Wu DTY, Sieck CJ. U.S. COVID-19 state government public dashboards: an expert review. Appl Clin Inform 2021; 12 (02) 208-221
  • 35 Mao Z, Liu C, Li Q, Cui Y, Zhou F. Intelligent intensive care unit: current and future trends. Intensive Care Res 2023; 3: 1-7
  • 36 Yoon JH, Pinsky MR, Clermont G. Artificial intelligence in critical care medicine. Crit Care 2022; 26 (01) 75
  • 37 Dowding D, Randell R, Gardner P. et al. Dashboards for improving patient care: review of the literature. Int J Med Inform 2015; 84 (02) 87-100
  • 38 Nelson O, Sturgis B, Gilbert K. et al. A visual analytics dashboard to summarize serial anesthesia records in pediatric radiation treatment. Appl Clin Inform 2019; 10 (04) 563-569
  • 39 Makic MBF, Stevens KR, Gritz RM. et al. Dashboard design to identify and balance competing risk of multiple hospital-acquired conditions. Appl Clin Inform 2022; 13 (03) 621-631
  • 40 Zaydfudim V, Dossett LA, Starmer JM. et al. Implementation of a real-time compliance dashboard to help reduce SICU ventilator-associated pneumonia with the ventilator bundle. Arch Surg 2009; 144 (07) 656-662
  • 41 Simpao AF, Ahumada LM, Larru Martinez B. et al. Design and implementation of a visual analytics electronic antibiogram within an electronic health record system at a tertiary pediatric hospital. Appl Clin Inform 2018; 9 (01) 37-45
  • 42 Lim HC, Austin JA, van der Vegt AH. et al. Toward a learning health care system: a systematic review and evidence-based conceptual framework for implementation of clinical analytics in a digital hospital. Appl Clin Inform 2022; 13 (02) 339-354
  • 43 Jambaulikar GD, Marshall A, Hasdianda MA. et al. Electronic paper displays in hospital operations: proposal for deployment and implementation. JMIR Form Res 2021; 5 (08) e30862
  • 44 Zoellner JM, Porter KJ. Chapter 6 - Translational research: concepts and methods in dissemination and implementation research. In: Coulston AM. et al, eds. Nutrition in the Prevention and Treatment of Disease, 4th ed. Academic Press; 2017: 125-143