Advertisement

Journal of Medical Systems

, 41:171 | Cite as

Can a Novel ICU Data Display Positively Affect Patient Outcomes and Save Lives?

  • Natalia OlchanskiEmail author
  • Mikhail A. Dziadzko
  • Ing C. Tiong
  • Craig E. Daniels
  • Steve G. Peters
  • John C. O’Horo
  • Michelle N. Gong
Systems-Level Quality Improvement
Part of the following topical collections:
  1. Systems-Level Quality Improvement

Abstract

The aim of this study was to quantify the impact of ProCCESs AWARE, Ambient Clinical Analytics, Rochester, MN, a novel acute care electronic medical record interface, on a range of care process and patient health outcome metrics in intensive care units (ICUs). ProCCESs AWARE is a novel acute care EMR interface that contains built-in tools for error prevention, practice surveillance, decision support and reporting. We compared outcomes before and after AWARE implementation using a prospective cohort and a historical control. The study population included all critically ill adult patients (over 18 years old) admitted to four ICUs at Mayo Clinic, Rochester, MN, who stayed in hospital at least 24 h. The pre-AWARE cohort included 983 patients from 2010, and the post-AWARE cohort included 856 patients from 2014. We analyzed patient health outcomes, care process quality, and hospital charges. After adjusting for patient acuity and baseline demographics, overall in-hospital and ICU mortality odds ratios associated with AWARE intervention were 0.45 (95% confidence interval 0.30 to 0.70) and 0.38 (0.22, 0.66). ICU length of stay decreased by about 50%, hospital length of stay by 37%, and total charges for hospital stay by 30% in post AWARE cohort (by $43,745 after adjusting for patient acuity and demographics). Better organization of information in the ICU with systems like AWARE has the potential to improve important patient outcomes, such as mortality and length of stay, resulting in reductions in costs of care.

Keywords

EMR Quality ICU 

Notes

Compliance with Ethical Standards

The project described was supported by Grant Number 1C1CMS330964–01-00 from the U.S. Department of Health and Human Services, Centers for Medicare & Medicaid Services. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the U.S. Department of Health and Human Services or any of its agencies. The design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication were conducted by the awardee. Findings may or may not be consistent with or confirmed by the findings of the independent evaluation contractor.

NO and MAD have full access to all data in the study and take responsibility for the integrity and accuracy of the data analysis.

Conflict of Interest

All authors, Natalia Olchanski, Mikhail A. Dziadzko, Ing C. Tiong, Craig E. Daniels, Steve G. Peters, John C. O’Horo, MD, Michelle N. Gong, declare that he or she has no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

The Institutional Review Board reviewed and approved this minimal risk study, and granted a waiver of informed consent for data collection from all individual participants included in the study.

Supplementary material

10916_2017_810_Fig2_ESM.jpg (244 kb)
Figure S1

AWARE screenshot – global patient overview. Boxes represent patients and their geographical location in the ICU (GIF 682 kb)

10916_2017_810_MOESM1_ESM.tif (2.6 mb)
High Resolution Image (TIFF 2.60 mb)
10916_2017_810_Fig3_ESM.jpg (290 kb)
Figure S2

AWARE screenshot – single patient view. Boxes represent problem list, physiological systems parameters and ongoing interventions. (GIF 562 kb)

10916_2017_810_MOESM2_ESM.tif (2.5 mb)
High Resolution Image (TIFF 2.45 mb)
10916_2017_810_Fig4_ESM.jpg (77 kb)
Figure S3

Administrative AWARE usage chart. This bar-chart represents usage of AWARE in all ICU in numbers of session per period of time. The same view is available per single ICU. (GIF 216 kb)

10916_2017_810_MOESM3_ESM.tif (841 kb)
High Resolution Image (TIFF 841 kb)
10916_2017_810_Fig5_ESM.jpg (54 kb)
Figure S4

Administrative checklist compliance per ICU. This bar-chart represents check-list compliance per ICU per period of time. (GIF 175 kb)

10916_2017_810_MOESM4_ESM.tif (584 kb)
High Resolution Image (TIFF 584 kb)

References

  1. 1.
    Levinson D. Adverse events in hospitals: national incidence among Medicare beneficiaries.: US Dept of Health and Human Services, Office of Inspector General;2010.Google Scholar
  2. 2.
    Leventhal R. Research Shows Effectiveness of EMR in Positively Impacting Clinical Outcomes. Research Shows Effectiveness of EMR in Positively Impacting Clinical Outcomes. 2014. http://www.healthcare-informatics.com/news-item/research-shows-effectiveness-emr-positively-impacting-clinical-outcomes. Accessed 09/30/2015.
  3. 3.
    Thompson, G., O'Horo, J.C., Pickering, B.W., and Herasevich, V., Impact of the electronic medical record on mortality, length of stay, and cost in the hospital and ICU: A systematic review and Metaanalysis. Critical care medicine. 43(6):1276–1282, 2015.CrossRefPubMedGoogle Scholar
  4. 4.
    Han, Y.Y., Carcillo, J.A., Venkataraman, S.T., et al., Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics. 116(6):1506–1512, 2005.CrossRefPubMedGoogle Scholar
  5. 5.
    Manor-Shulman, O., Beyene, J., Frndova, H., and Parshuram, C.S., Quantifying the volume of documented clinical information in critical illness. J Crit Care. 23(2):245–250, 2008.CrossRefPubMedGoogle Scholar
  6. 6.
    Ahmed, A., Chandra, S., Herasevich, V., Gajic, O., and Pickering, B.W., The effect of two different electronic health record user interfaces on intensive care provider task load, errors of cognition, and performance. Crit Care Med. 2011, 2011.Google Scholar
  7. 7.
    Pickering, B.W., Dong, Y., Ahmed, A., et al., The implementation of clinician designed, human-centered electronic medical record viewer in the intensive care unit: A pilot step-wedge cluster randomized trial. Int J Med Inform. 84(5):299–307, 2015.CrossRefPubMedGoogle Scholar
  8. 8.
    Elkin, P.L., Mohr, D.N., Tuttle, M.S., et al., Standardized problem list generation, utilizing the Mayo canonical vocabulary embedded within the unified medical language system. Proc AMIA Annu Fall Symp.:500–504, 1997.Google Scholar
  9. 9.
    Thongprayoon, C., Harrison, A.M., O'Horo, J.C., Berrios, R.A., Pickering, B.W., and Herasevich, V., The effect of an electronic checklist on critical care provider workload, errors, and performance. J Intensive Care Med. 31(3):205–212, 2016.CrossRefPubMedGoogle Scholar
  10. 10.
    Herasevich, V., Pickering, B.W., Dong, Y., Peters, S.G., and Gajic, O., Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Mayo Clin Proc. 85(3):247–254, 2010.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Dziadzko, M.A.T.C., Ahmed, A., Tiong, I.C., Li, M., Brown, D.R., Pickering, B.W., and Herasevich, V., Automatic quality improvement reports in the intensive care unit: One step closer toward meaningful use. World J Crit Care Med. 5(2):165–170, 2016.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Lan, H., Thongprayoon, C., Ahmed, A., et al., Automating quality metrics in the era of electronic medical records: Digital signatures for ventilator bundle compliance. Biomed Res Int. 2015:396508, 2015.PubMedPubMedCentralGoogle Scholar
  13. 13.
    Magill, S.S., Klompas, M., Balk, R., et al., Executive summary: Developing a new, national approach to surveillance for ventilator-associated events. Ann Am Thorac Soc. 10(6):S220–S223, 2013.CrossRefPubMedGoogle Scholar
  14. 14.
    Klompas, M., Complications of mechanical ventilation--the CDC's new surveillance paradigm. N Engl J Med. 368(16):1472–1475, 2013.CrossRefPubMedGoogle Scholar
  15. 15.
    Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome, The acute respiratory distress syndrome network. N Engl J Med. 342(18):1301–1308, 2000.CrossRefGoogle Scholar
  16. 16.
    Kjonegaard, R., Fields, W., and King, M.L., Current practice in airway management: A descriptive evaluation. Am J Crit Care. 19(2):168–173, 2010 quiz 174.CrossRefPubMedGoogle Scholar
  17. 17.
    Sevilla Berrios RA, Kaur S, Erdogan A, et al. ProcessAWARE: Patient Outcomes and Resource Utilization Changes following Implementing an Electronic Rounding Checklist in the Intensive Care Unit AMIA 2014 proceedings. 2014:1580.Google Scholar
  18. 18.
    Erdogan A, Kaur S, Garcia Arguello LY, et al. Process Improvements from Implementing an Electronic Checklist and Rounds Choreography to the Intensive Care Unit AMIA 2014 proceedings. 2014:1379.Google Scholar
  19. 19.
    Thongprayoon, C., Harrison, A.M., O'Horo, J.C., Berrios, R.A., Pickering, B.W., and Herasevich, V., The effect of an electronic checklist on critical care provider workload, errors, and performance. J Intensive Care Med., 2014.Google Scholar
  20. 20.
    Shaw, S.J., Jacobs, B., Stockwell, D.C., Futterman, C., and Spaeder, M.C., Effect of a real-time pediatric ICU safety bundle dashboard on quality improvement measures. Jt Comm J Qual Patient Saf. 41(9):414–420, 2015.CrossRefPubMedGoogle Scholar
  21. 21.
    Lee, J., Kuo, Y.F., and Goodwin, J.S., The effect of electronic medical record adoption on outcomes in US hospitals. BMC Health Serv Res. 13:39, 2013.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Magill, S.S., Klompas, M., Balk, R., et al., Developing a new, national approach to surveillance for ventilator-associated events*. Crit Care Med:2013, 2013.Google Scholar
  23. 23.
    Dziadzko, M.A., Herasevich, V., Sen, A., Pickering, B.W., Knight, A.M., and Moreno Franco, P., User perception and experience of the introduction of a novel critical care patient viewer in the ICU setting. Int J Med Inform. 88:86–91, 2016.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.The Center for the Evaluation of Value and Risk in HealthInstitute for Clinical Research and Health Policy Studies, Tufts Medical CenterBostonUSA
  2. 2.Department of AnesthesiologyMayo ClinicRochesterUSA
  3. 3.Department of Information TechnologyMayo ClinicRochesterUSA
  4. 4.Department of Pulmonology and Critical Care MedicineMayo ClinicRochesterUSA
  5. 5.Department of Medicine, Division of Infectious DiseasesMayo ClinicRochesterUSA
  6. 6.Department of MedicineMontefiore Medical Center/Albert Einstein College of MedicineNew YorkUSA
  7. 7.Department of Epidemiology and Population HealthAlbert Einstein College of MedicineNew YorkUSA

Personalised recommendations