Appl Clin Inform 2016; 07(02): 596-603
DOI: 10.4338/ACI-2015-12-RA-0183
Research Article
Schattauer GmbH

Derivation and validation of a search algorithm to retrospectively identify CRRT initiation in the ECMO patients

Pramod K. Guru
1   Department Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA
,
Tarun D. Singh
2   Department of Neurology, Division of Critical Care, Mayo Clinic, Rochester, MN, USA
,
Melissa Passe
3   Department of Anesthesia and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA
,
Kianoush B. Kashani
1   Department Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA
4   Department Medicine, Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
,
Gregory J Schears
3   Department of Anesthesia and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA
,
Rahul Kashyap
3   Department of Anesthesia and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA
› Author Affiliations
The study was supported by Mayo Clinic foundation funding through Critical Care research subcommittee.
Further Information

Publication History

received: 06 January 2016

accepted: 28 April 2016

Publication Date:
16 December 2017 (online)

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Summary

Background

The role of extracorporeal membrane oxygenation (ECMO) in refractory cardiorespiratory failure is gaining momentum with recent advancements in technology. However, the need for dialysis modes such as continuous renal replacement therapy (CRRT) has also increased in the management for acute kidney injury. Establishing the exact timing of CRRT initiation in these patients from the electronic medical record is vital for automated data extraction for research and quality improvement efforts.

Objectives

We aimed to derive and validate an automated Electronic Health Records (EHR) search strategy for CRRT initiation in patients receiving ECMO.

Methods

We screened 488 patients who received ECMO and a total of 213 patients underwent CRRT. We evaluated random 120 patients, 60 for derivation and 60 for validation cohorts. Following implementation of eligibility criteria, the algorithm was derived in 55 out of 120 ECMO/CRRT patients. The search algorithm was developed using first-time chart entry of ‘access pressure drop’ at CRRT initiation. The algorithm was then validated in an independent subset of 52 patients from the same time period. The overall agreement between electronic search algorithm and a comprehensive manual medical record review in the derivation and validation subsets, using ‘access pressure drop’ as the reference standard, was compared to assess CRRT initiation time.

Results

In the derivation subset (N=55), the automated electronic search strategy achieved an excellent agreement with manual search (D =0.99, 54 were identified electronically, and 55 upon manual review). There was no time difference observed in 49/54(89%) patients, while in the remaining 5 (9%) patients time difference was within 15 minutes. In the validation cohort (N=52), agreement was 100 % (D = 1.0, both methods identified 52 patients). Out of 52 patients, 47 (90%) had no time difference between the methods, for the remaining 5 (10%) patients, differences were within 15 minutes.

Conclusions

The use of an electronic search strategy resulted in determining an accurate CRRT initiation time among ECMO patients.