Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database

Renate Udo; Anke H Maitland-van der Zee; Toine C G Egberts; Johanna H den Breeijen; Hubert G M Leufkens; Wouter W van Solinge; Marie L De Bruin

doi:10.1002/pds.3824

Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database

Renate Udo, Anke H Maitland-van der Zee, Toine C G Egberts, Johanna H den Breeijen, Hubert G M Leufkens, Wouter W van Solinge, Marie L De Bruin

10 Citations (Scopus)

Abstract

PURPOSE: The development and validation of algorithms to identify cases of idiopathic acute liver injury (ALI) are essential to facilitate epidemiologic studies on drug-induced liver injury. The aim of this study is to determine the ability of diagnostic codes and laboratory measurements to identify idiopathic ALI cases.

METHODS: In this cross-sectional validation study, patients were selected from the hospital-based Utrecht Patient Oriented Database between 2008 and 2010. Patients were identified using (I) algorithms based on ICD-9-CM codes indicative of idiopathic ALI combined with sets of liver enzyme values (ALT > 2× upper limit of normal (ULN); AST > 1ULN + AP > 1ULN + bilirubin > 1ULN; ALT > 3ULN; ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN) and (II) algorithms based on solely liver enzyme values (ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN). Hospital medical records were reviewed to confirm final diagnosis. The positive predictive value (PPV) of each algorithm was calculated.

RESULTS: A total of 707 cases of ALI were identified. After medical review 194 (27%) patients had confirmed idiopathic ALI. The PPV for (I) algorithms with an ICD-9-CM code as well as abnormal tests ranged from 32% (13/41) to 48% (43/90) with the highest PPV found with ALT > 2ULN. The PPV for (II) algorithms with liver test abnormalities was maximally 26% (150/571).

CONCLUSIONS: The algorithm based on ICD-9-CM codes indicative of ALI combined with abnormal liver-related laboratory tests is the most efficient algorithm for identifying idiopathic ALI cases. However, cases were missed using this algorithm, because not all ALI cases had been assigned the relevant diagnostic codes in daily practice.

Original language	English
Journal	Pharmacoepidemiology and Drug Safety
Volume	25
Issue number	Suppl 1
Pages (from-to)	21-8
Number of pages	8
ISSN	1053-8569
DOIs	https://doi.org/10.1002/pds.3824
Publication status	Published - 1 Mar 2016
Externally published	Yes

Keywords

Journal Article
Research Support, Non-U.S. Gov't

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10.1002/pds.3824

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Udo, R., Maitland-van der Zee, A. H., Egberts, T. C. G., den Breeijen, J. H., Leufkens, H. G. M., van Solinge, W. W., & De Bruin, M. L. (2016). Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database. Pharmacoepidemiology and Drug Safety, 25 (Suppl 1), 21-8. https://doi.org/10.1002/pds.3824

Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database. / Udo, Renate; Maitland-van der Zee, Anke H; Egberts, Toine C G et al.

In: Pharmacoepidemiology and Drug Safety, Vol. 25 , No. Suppl 1, 01.03.2016, p. 21-8.

Research output: Contribution to journal › Journal article › Research › peer-review

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title = "Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database",

abstract = "PURPOSE: The development and validation of algorithms to identify cases of idiopathic acute liver injury (ALI) are essential to facilitate epidemiologic studies on drug-induced liver injury. The aim of this study is to determine the ability of diagnostic codes and laboratory measurements to identify idiopathic ALI cases.METHODS: In this cross-sectional validation study, patients were selected from the hospital-based Utrecht Patient Oriented Database between 2008 and 2010. Patients were identified using (I) algorithms based on ICD-9-CM codes indicative of idiopathic ALI combined with sets of liver enzyme values (ALT > 2× upper limit of normal (ULN); AST > 1ULN + AP > 1ULN + bilirubin > 1ULN; ALT > 3ULN; ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN) and (II) algorithms based on solely liver enzyme values (ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN). Hospital medical records were reviewed to confirm final diagnosis. The positive predictive value (PPV) of each algorithm was calculated.RESULTS: A total of 707 cases of ALI were identified. After medical review 194 (27%) patients had confirmed idiopathic ALI. The PPV for (I) algorithms with an ICD-9-CM code as well as abnormal tests ranged from 32% (13/41) to 48% (43/90) with the highest PPV found with ALT > 2ULN. The PPV for (II) algorithms with liver test abnormalities was maximally 26% (150/571).CONCLUSIONS: The algorithm based on ICD-9-CM codes indicative of ALI combined with abnormal liver-related laboratory tests is the most efficient algorithm for identifying idiopathic ALI cases. However, cases were missed using this algorithm, because not all ALI cases had been assigned the relevant diagnostic codes in daily practice.",

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author = "Renate Udo and {Maitland-van der Zee}, {Anke H} and Egberts, {Toine C G} and {den Breeijen}, {Johanna H} and Leufkens, {Hubert G M} and {van Solinge}, {Wouter W} and {De Bruin}, {Marie L}",

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doi = "10.1002/pds.3824",

language = "English",

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T1 - Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database

AU - Udo, Renate

AU - Maitland-van der Zee, Anke H

AU - Egberts, Toine C G

AU - den Breeijen, Johanna H

AU - Leufkens, Hubert G M

AU - van Solinge, Wouter W

AU - De Bruin, Marie L

PY - 2016/3/1

Y1 - 2016/3/1

N2 - PURPOSE: The development and validation of algorithms to identify cases of idiopathic acute liver injury (ALI) are essential to facilitate epidemiologic studies on drug-induced liver injury. The aim of this study is to determine the ability of diagnostic codes and laboratory measurements to identify idiopathic ALI cases.METHODS: In this cross-sectional validation study, patients were selected from the hospital-based Utrecht Patient Oriented Database between 2008 and 2010. Patients were identified using (I) algorithms based on ICD-9-CM codes indicative of idiopathic ALI combined with sets of liver enzyme values (ALT > 2× upper limit of normal (ULN); AST > 1ULN + AP > 1ULN + bilirubin > 1ULN; ALT > 3ULN; ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN) and (II) algorithms based on solely liver enzyme values (ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN). Hospital medical records were reviewed to confirm final diagnosis. The positive predictive value (PPV) of each algorithm was calculated.RESULTS: A total of 707 cases of ALI were identified. After medical review 194 (27%) patients had confirmed idiopathic ALI. The PPV for (I) algorithms with an ICD-9-CM code as well as abnormal tests ranged from 32% (13/41) to 48% (43/90) with the highest PPV found with ALT > 2ULN. The PPV for (II) algorithms with liver test abnormalities was maximally 26% (150/571).CONCLUSIONS: The algorithm based on ICD-9-CM codes indicative of ALI combined with abnormal liver-related laboratory tests is the most efficient algorithm for identifying idiopathic ALI cases. However, cases were missed using this algorithm, because not all ALI cases had been assigned the relevant diagnostic codes in daily practice.

AB - PURPOSE: The development and validation of algorithms to identify cases of idiopathic acute liver injury (ALI) are essential to facilitate epidemiologic studies on drug-induced liver injury. The aim of this study is to determine the ability of diagnostic codes and laboratory measurements to identify idiopathic ALI cases.METHODS: In this cross-sectional validation study, patients were selected from the hospital-based Utrecht Patient Oriented Database between 2008 and 2010. Patients were identified using (I) algorithms based on ICD-9-CM codes indicative of idiopathic ALI combined with sets of liver enzyme values (ALT > 2× upper limit of normal (ULN); AST > 1ULN + AP > 1ULN + bilirubin > 1ULN; ALT > 3ULN; ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN) and (II) algorithms based on solely liver enzyme values (ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN). Hospital medical records were reviewed to confirm final diagnosis. The positive predictive value (PPV) of each algorithm was calculated.RESULTS: A total of 707 cases of ALI were identified. After medical review 194 (27%) patients had confirmed idiopathic ALI. The PPV for (I) algorithms with an ICD-9-CM code as well as abnormal tests ranged from 32% (13/41) to 48% (43/90) with the highest PPV found with ALT > 2ULN. The PPV for (II) algorithms with liver test abnormalities was maximally 26% (150/571).CONCLUSIONS: The algorithm based on ICD-9-CM codes indicative of ALI combined with abnormal liver-related laboratory tests is the most efficient algorithm for identifying idiopathic ALI cases. However, cases were missed using this algorithm, because not all ALI cases had been assigned the relevant diagnostic codes in daily practice.

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KW - Research Support, Non-U.S. Gov't

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DO - 10.1002/pds.3824

M3 - Journal article

C2 - 26147715

SN - 1053-8569

VL - 25

SP - 21

EP - 28

JO - Pharmacoepidemiology and Drug Safety

JF - Pharmacoepidemiology and Drug Safety

IS - Suppl 1

ER -

Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database

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