Expanding Critical Care Delivery beyond the Intensive Care Unit: Determining the Design and Implementation Needs for a Tele-Critical Care Consultation Service

 

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Abstract

Background Unplanned intensive care unit (ICU) admissions from medical/surgical floors and increased boarding times of ICU patients in the emergency department (ED) are common; approximately half of these are associated with adverse events. We explore the potential role of a tele-critical care consult service (TC3) in managing critically ill patients outside of the ICU and potentially preventing low-acuity unplanned admissions and also investigate its design and implementation needs.

Methods We conducted a qualitative study involving general observations of the units, shadowing of clinicians during patient transfers, and interviews with clinicians from the ED, medical/surgical floor units and their ICU counterparts, tele-ICU, and the rapid response team at a large academic medical center in St. Louis, Missouri, United States. We used a hybrid thematic analysis approach supported by open and structured coding using the Consolidated Framework for Implementation Research (CFIR).

Results Over 165 hours of observations/shadowing and 26 clinician interviews were conducted. Our findings suggest that a tele-critical care consult (TC3) service can prevent avoidable, lower acuity ICU admissions by offering a second set of eyes via remote monitoring and providing guidance to bedside and rapid response teams in the care delivery of these patients on the floor/ED. CFIR-informed enablers impacting the successful implementation of the TC3 service included the optional and on-demand features of the TC3 service, around-the-clock availability, and continuous access to trained critical care clinicians for avoidable lower acuity (ALA) patients outside of the ICU, familiarity with tele-ICU staff, and a willingness to try alternative patient risk mitigation strategies for ALA patients (suggested by TC3), before transferring all unplanned admissions to ICUs. Conversely, the CFIR-informed barriers to implementation included a desire to uphold physician autonomy by floor/ED clinicians, potential role conflicts with rapid response teams, additional workload for floor/ED nurses, concerns about obstructing unavoidable, higher acuity admissions, and discomfort with audio-visual tools. To amplify these potential enablers and mitigate potential barriers to TC3 implementation, informed by this study, we propose two key characteristics—essential for extending the delivery of critical care services beyond the ICU—underlying a telemedicine critical care consultation model including its virtual footprint and on-demand and optional service features.

Conclusion Tele-critical care represents an innovative strategy for delivering safe and high-quality critical care services to lower acuity borderline patients outside the ICU setting.

Protection of Human and Animal Subjects

The Washington University Human Research Protections Office (IRB# 202205091) approved this study, and verbal consent was obtained from all participants.

Authors' Contributions

J.A., B.F., and C.P. led the conception and design of the study. M.K. and J.A. were involved in the data collection; J.A. and M.K. conducted independent data coding and analysis and drafted the manuscript. J.A., M.K., B.F., and C.P. participated in peer-debriefing sessions to discuss the results and their interpretations. All authors were involved in critically reviewing its content and editing the manuscript. All authors have provided their final approval of the version to be submitted.

Ethics Approval and Consent to Participate

The study was approved by the Washington University in St. Louis, Institutional Review Board (IRB # 202109011), and consents were obtained from all participants. Participants who completed interviews received compensation of $15 on a reloadable debit card.

Consent for Publication

All authors have approved the publication of this manuscript.

Availability of Data and Materials

The data that support the findings of this study are available on request from the corresponding author.

Publication History

Received: 21 July 2023

Accepted: 15 January 2024

Article published online:
06 March 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

• References

• 1 Barrett ML, Smith MW, Elixhauser A, Honigman LS, Pines JM. Utilization of Intensive Care Services,. 2011. : Statistical Brief #185. In: Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Rockville, MD:: Agency for Healthcare Research and Quality (US); ; 2006
  Google Scholar
• 2 Groeger JS, Guntupalli KK, Strosberg M. et al. Descriptive analysis of critical care units in the United States: patient characteristics and intensive care unit utilization. Crit Care Med 1993; 21 (02) 279-291
  CrossrefPubMedGoogle Scholar
• 3 Marquet K, Claes N, De Troy E. et al. One fourth of unplanned transfers to a higher level of care are associated with a highly preventable adverse event: a patient record review in six Belgian hospitals. Crit Care Med 2015; 43 (05) 1053-1061
  CrossrefPubMedGoogle Scholar
• 4 Mulvey HE, Haslam RD, Laytin AD, Diamond CA, Sims CA. Unplanned ICU admission is associated with worse clinical outcomes in geriatric trauma patients. J Surg Res 2020; 245: 13-21
  CrossrefPubMedGoogle Scholar
• 5 Rubano JA, Vosswinkel JA, McCormack JE, Huang EC, Shapiro MJ, Jawa RS. Unplanned intensive care unit admission following trauma. J Crit Care 2016; 33: 174-179
  CrossrefPubMedGoogle Scholar
• 6 Weissman GE, Kerlin MP, Yuan Y. et al. Potentially preventable intensive care unit admissions in the United States, 2006-2015. Ann Am Thorac Soc 2020; 17 (01) 81-88
  CrossrefPubMedGoogle Scholar
• 7 Kollef MH, Chen Y, Heard K. et al. A randomized trial of real-time automated clinical deterioration alerts sent to a rapid response team. J Hosp Med 2014; 9 (07) 424-429
  CrossrefPubMedGoogle Scholar
• 8 Smith RM, Conn AK. Prehospital care - scoop and run or stay and play?. Injury 2009; 40 (Suppl. 04) S23-S26
  CrossrefPubMedGoogle Scholar
• 9 Nirula R, Maier R, Moore E, Sperry J, Gentilello L. Scoop and run to the trauma center or stay and play at the local hospital: hospital transfer's effect on mortality. J Trauma 2010; 69 (03) 595-599 , discussion 599–601
  PubMedGoogle Scholar
• 10 Dacey MJ, Mirza ER, Wilcox V. et al. The effect of a rapid response team on major clinical outcome measures in a community hospital. Crit Care Med 2007; 35 (09) 2076-2082
  CrossrefPubMedGoogle Scholar
• 11 Sharek PJ, Parast LM, Leong K. et al. Effect of a rapid response team on hospital-wide mortality and code rates outside the ICU in a Children's Hospital. JAMA 2007; 298 (19) 2267-2274
  CrossrefPubMedGoogle Scholar
• 12 Jung B, Daurat A, De Jong A. et al. Rapid response team and hospital mortality in hospitalized patients. Intensive Care Med 2016; 42 (04) 494-504
  CrossrefPubMedGoogle Scholar
• 13 Karpman C, Keegan MT, Jensen JB, Bauer PR, Brown DR, Afessa B. The impact of rapid response team on outcome of patients transferred from the ward to the ICU: a single-center study. Crit Care Med 2013; 41 (10) 2284-2291
  CrossrefPubMedGoogle Scholar
• 14 Orosz J, Bailey M, Udy A, Pilcher D, Bellomo R, Jones D. Unplanned ICU admission from hospital wards after rapid response team review in Australia and New Zealand. Crit Care Med 2020; 48 (07) e550-e556
  CrossrefPubMedGoogle Scholar
• 15 Mullins PM, Goyal M, Pines JM. National growth in intensive care unit admissions from emergency departments in the United States from 2002 to 2009. Acad Emerg Med 2013; 20 (05) 479-486
  CrossrefPubMedGoogle Scholar
• 16 McGloin H, Adam SK, Singer M. Unexpected deaths and referrals to intensive care of patients on general wards. Are some cases potentially avoidable?. J R Coll Physicians Lond 1999; 33 (03) 255-259
  PubMedGoogle Scholar
• 17 Prints M, Fishbein D, Arnold R. et al. Understanding the perception of workload in the emergency department and its impact on medical decision making. Am J Emerg Med 2020; 38 (02) 397-399
  CrossrefPubMedGoogle Scholar
• 18 Pisani MA, D'Ambrosio C. Sleep and delirium in adults who are critically ill: a contemporary review. Chest 2020; 157 (04) 977-984
  CrossrefPubMedGoogle Scholar
• 19 Altman MT, Knauert MP, Pisani MA. Sleep disturbance after hospitalization and critical illness: a systematic review. Ann Am Thorac Soc 2017; 14 (09) 1457-1468
  CrossrefPubMedGoogle Scholar
• 20 Krewulak KD, Stelfox HT, Leigh JP, Ely EW, Fiest KM. Incidence and prevalence of delirium subtypes in an adult ICU: a systematic review and meta-analysis. Crit Care Med 2018; 46 (12) 2029-2035
  CrossrefPubMedGoogle Scholar
• 21 Soriano MC, Vaquero C, Ortiz-Fernández A, Caballero A, Blandino-Ortiz A, de Pablo R. Low incidence of co-infection, but high incidence of ICU-acquired infections in critically ill patients with COVID-19. J Infect 2021; 82 (02) e20-e21
  CrossrefPubMedGoogle Scholar
• 22 Al-Rajhi A, Mardini L, Jayaraman D. The impact of implementation of an ICU consult service on hospital-wide outcomes and ICU-specific outcomes. J Intensive Care Med 2016; 31 (07) 478-484
  CrossrefPubMedGoogle Scholar
• 23 Nguyen HB, Rivers EP, Havstad S. et al. Critical care in the emergency department: a physiologic assessment and outcome evaluation. Acad Emerg Med 2000; 7 (12) 1354-1361
  CrossrefPubMedGoogle Scholar
• 24 Churpek MM, Yuen TC, Winslow C, Meltzer DO, Kattan MW, Edelson DP. Multicenter comparison of machine learning methods and conventional regression for predicting clinical deterioration on the wards. Crit Care Med 2016; 44 (02) 368-374
  CrossrefPubMedGoogle Scholar
• 25 Brankovic A, Hassanzadeh H, Good N. et al. Explainable machine learning for real-time deterioration alert prediction to guide pre-emptive treatment. Sci Rep 2022; 12 (01) 11734
  CrossrefPubMedGoogle Scholar
• 26 Kahn JM, Cicero BD, Wallace DJ, Iwashyna TJ. Adoption of ICU telemedicine in the United States. Crit Care Med 2014; 42 (02) 362-368
  CrossrefPubMedGoogle Scholar
• 27 Kleinpell RM, Ely EW, Grabenkort R. Nurse practitioners and physician assistants in the intensive care unit: an evidence-based review. Crit Care Med 2008; 36 (10) 2888-2897
  CrossrefPubMedGoogle Scholar
• 28 Heisler M. Hospitalists and intensivists: partners in caring for the critically ill–the time has come. J Hosp Med 2010; 5 (01) 1-3
  CrossrefPubMedGoogle Scholar
• 29 Lilly CM, Cody S, Zhao H. et al; University of Massachusetts Memorial Critical Care Operations Group. Hospital mortality, length of stay, and preventable complications among critically ill patients before and after tele-ICU reengineering of critical care processes. JAMA 2011; 305 (21) 2175-2183
  CrossrefPubMedGoogle Scholar
• 30 Lilly CM, McLaughlin JM, Zhao H, Baker SP, Cody S, Irwin RS. UMass Memorial Critical Care Operations Group. A multicenter study of ICU telemedicine reengineering of adult critical care. Chest 2014; 145 (03) 500-507
  CrossrefPubMedGoogle Scholar
• 31 Fusaro MV, Becker C, Scurlock C. Evaluating tele-ICU implementation based on observed and predicted ICU mortality: a systematic review and meta-analysis. Crit Care Med 2019; 47 (04) 501-507
  CrossrefPubMedGoogle Scholar
• 32 Becker CD, Fusaro MV, Al Aseri Z, Millerman K, Scurlock C. Effects of telemedicine ICU intervention on care standardization and patient outcomes: an observational study. Crit Care Explor 2020; 2 (07) e0165
  CrossrefPubMedGoogle Scholar
• 33 Young LB, Chan PS, Lu X, Nallamothu BK, Sasson C, Cram PM. Impact of telemedicine intensive care unit coverage on patient outcomes: a systematic review and meta-analysis. Arch Intern Med 2011; 171 (06) 498-506
  CrossrefPubMedGoogle Scholar
• 34 Kahn JM, Le TQ, Barnato AE. et al. ICU telemedicine and critical care mortality: a national effectiveness study. Med Care 2016; 54 (03) 319-325
  CrossrefPubMedGoogle Scholar
• 35 Fusch PI, Ness LR. Are we there yet? Data saturation in qualitative research. Qual Rep 2015; 20 (09) 1408-1416
  PubMedGoogle Scholar
• 36 Hennink M, Kaiser BN. Sample sizes for saturation in qualitative research: a systematic review of empirical tests. Soc Sci Med 2022; 292: 114523
  CrossrefPubMedGoogle Scholar
• 37 Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci 2009; 4: 50
  CrossrefPubMedGoogle Scholar
• 38 Safaeinili N, Brown-Johnson C, Shaw JG, Mahoney M, Winget M. CFIR simplified: pragmatic application of and adaptations to the Consolidated Framework for Implementation Research (CFIR) for evaluation of a patient-centered care transformation within a learning health system. Learn Health Syst 2019; 4 (01) e10201
  CrossrefPubMedGoogle Scholar
• 39 Cypress BS. Rigor or reliability and validity in qualitative research: perspectives, strategies, reconceptualization, and recommendations. Dimens Crit Care Nurs 2017; 36 (04) 253-263
  CrossrefPubMedGoogle Scholar
• 40 Oye RK, Bellamy PE. Patterns of resource consumption in medical intensive care. Chest 1991; 99 (03) 685-689
  CrossrefPubMedGoogle Scholar
• 41 Kadar RB, Amici DR, Hesse K, Bonder A, Ries M. Impact of telemonitoring of critically ill emergency department patients awaiting ICU transfer. Crit Care Med 2019; 47 (09) 1201-1207
  CrossrefPubMedGoogle Scholar
• 42 Collins TA, Robertson MP, Sicoutris CP. et al. Telemedicine coverage for post-operative ICU patients. J Telemed Telecare 2017; 23 (02) 360-364
  CrossrefPubMedGoogle Scholar
• 43 Chandra S, Hertz C, Khurana H, Doerfler ME. Collaboration between tele-ICU programs has the potential to rapidly increase the availability of critical care physicians-our experience was during coronavirus disease 2019 nomenclature. Crit Care Explor 2021; 3 (03) e0363
  CrossrefPubMedGoogle Scholar
• 44 Gaieski DF, Carr B, Toolan M. et al. Can an end-to-end telesepsis solution improve the severe sepsis and septic shock management bundle-1 metrics for sepsis patients admitted from the emergency department to the hospital?. Crit Care Explor 2022; 4 (10) e0767
  CrossrefPubMedGoogle Scholar
• 45 Lee MS, Nambudiri VE. Electronic consultations (eConsults) for safe and equitable coordination of virtual outpatient specialty care. Appl Clin Inform 2020; 11 (05) 821-824
  Article in Thieme ConnectPubMedGoogle Scholar
• 46 Medford RJ, Granger M, Pickering M, Lehmann CU, Mayorga C, King H. Implementation of outpatient infectious diseases e-consults at a safety net healthcare system. Open Forum Infect Dis 2022; 9 (07) ofac341
  CrossrefPubMedGoogle Scholar

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