Appl Clin Inform 2014; 05(01): 58-72
DOI: 10.4338/ACI-2013-07-RA-0045
Research Article
Schattauer GmbH

Towards Prevention of Acute Syndromes

Electronic Identification of At-Risk Patients During Hospital Admission
A. Ahmed
1  Multidisciplinary Epidemiology and Translational Research in Intensive Care (M.E.T.R.I.C.), Mayo Clinic, Rochester
2  Institute for Health Informatics, University of Minnesota, Minneapolis
4  Department of Medicine, Division of Critical Care Medicine, Mayo Clinic
,
C. Thongprayoon
1  Multidisciplinary Epidemiology and Translational Research in Intensive Care (M.E.T.R.I.C.), Mayo Clinic, Rochester
4  Department of Medicine, Division of Critical Care Medicine, Mayo Clinic
,
B.W. Pickering
1  Multidisciplinary Epidemiology and Translational Research in Intensive Care (M.E.T.R.I.C.), Mayo Clinic, Rochester
3  Department of Anesthesiology, Division of Critical Care Medicine, Mayo Clinic
,
A. Akhoundi
1  Multidisciplinary Epidemiology and Translational Research in Intensive Care (M.E.T.R.I.C.), Mayo Clinic, Rochester
,
G. Wilson
1  Multidisciplinary Epidemiology and Translational Research in Intensive Care (M.E.T.R.I.C.), Mayo Clinic, Rochester
3  Department of Anesthesiology, Division of Critical Care Medicine, Mayo Clinic
,
D. Pieczkiewicz
2  Institute for Health Informatics, University of Minnesota, Minneapolis
,
V. Herasevich
1  Multidisciplinary Epidemiology and Translational Research in Intensive Care (M.E.T.R.I.C.), Mayo Clinic, Rochester
3  Department of Anesthesiology, Division of Critical Care Medicine, Mayo Clinic
› Author Affiliations
Further Information

Correspondence to:

Adil Ahmed MBBS
Division of Pulmonary and Critical Care Medicine,
200 First St. SW, Rochester, MN 55095

Publication History

received: 11 July 2013

accepted: 22 January 2013

Publication Date:
20 December 2017 (online)

 

Summary

Background: Identifying patients at risk for acute respiratory distress syndrome (ARDS) before their admission to intensive care is crucial to prevention and treatment. The objective of this study is to determine the performance of an automated algorithm for identifying selected ARDS predis-posing conditions at the time of hospital admission.

Methods: This secondary analysis of a prospective cohort study included 3,005 patients admitted to hospital between January 1 and December 31, 2010. The automated algorithm for five ARDS pre-disposing conditions (sepsis, pneumonia, aspiration, acute pancreatitis, and shock) was developed through a series of queries applied to institutional electronic medical record databases. The automated algorithm was derived and refined in a derivation cohort of 1,562 patients and subsequently validated in an independent cohort of 1,443 patients. The sensitivity, specificity, and positive and negative predictive values of an automated algorithm to identify ARDS risk factors were compared with another two independent data extraction strategies, including manual data extraction and ICD-9 code search. The reference standard was defined as the agreement between the ICD-9 code, automated and manual data extraction.

Results: Compared to the reference standard, the automated algorithm had higher sensitivity than manual data extraction for identifying a case of sepsis (95% vs. 56%), aspiration (63% vs. 42%), acute pancreatitis (100% vs. 70%), pneumonia (93% vs. 62%) and shock (77% vs. 41%) with similar specificity except for sepsis and pneumonia (90% vs. 98% for sepsis and 95% vs. 99% for pneumonia). The PPV for identifying these five acute conditions using the automated algorithm ranged from 65% for pneumonia to 91 % for acute pancreatitis, whereas the NPV for the automated algorithm ranged from 99% to 100%.

Conclusion: A rule-based electronic data extraction can reliably and accurately identify patients at risk of ARDS at the time of hospital admission.

Citation: Ahmed A, Thongprayoon C, Pickering BW, Akhoundi A, Wilson G, Pieczkiewicz D, Herasevich V. Towards prevention of acute syndromes: Electronic identification of at-risk patients during hospital admission. Appl Clin Inf 2014; 5: 58–72

http://dx.doi.org/10.4338/ACI-2013-07-RA-0045


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Conflicts of interest

The authors declare that they have no conflicts of interest in this project.


Correspondence to:

Adil Ahmed MBBS
Division of Pulmonary and Critical Care Medicine,
200 First St. SW, Rochester, MN 55095