Dataset Information

Process Variation Detection using Missing Data in a Multihospital Community Practice Anatomic Pathology Laboratory.

ABSTRACT:

Objectives

Barcode-driven workflows reduce patient identification errors. Missing process timestamp data frequently confound our health system's pending lists and appear as actions left undone. Anecdotally, it was noted that missing data could be found when there is procedure noncompliance. This project was developed to determine if missing timestamp data in the histology barcode drive workflow correlated with other process variations, procedure noncompliance, or is an indicator of workflows needing focus for improvement projects.

Materials and methods

Data extracts of timestamp data from January 1, 2018, to December 15, 2018 for the major histology process steps were analyzed for missing data. Case level analysis to determine the presence or absence of expected barcoding events was performed on 1031 surgical pathology cases to determine the cause of the missing data and determine if additional data variations or procedure noncompliance events were present. The data variations were classified according to a scheme defined in the study.

Results

Of 70,085, there were 7218 cases (10.3%) with missing process timestamp data. Missing histology process step data was associated with other additional data variations in case-level deep dives (P < 0.0001). Of the cases missing timestamp data in the initial review, 18.4% of the cases had no identifiable cause for the missing data (all expected events took place in the case-level deep dive).

Conclusions

Operationally, valuable information can be obtained by reviewing the types and causes of missing data in the anatomic pathology laboratory information system, but only in conjunction with user input and feedback.

SUBMITTER: Galliano GE

PROVIDER: S-EPMC6686573 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Process Variation Detection using Missing Data in a Multihospital Community Practice Anatomic Pathology Laboratory.

Galliano Gretchen E GE

Journal of pathology informatics 20190801

<h4>Objectives</h4>Barcode-driven workflows reduce patient identification errors. Missing process timestamp data frequently confound our health system's pending lists and appear as actions left undone. Anecdotally, it was noted that missing data could be found when there is procedure noncompliance. This project was developed to determine if missing timestamp data in the histology barcode drive workflow correlated with other process variations, procedure noncompliance, or is an indicator of workf ...[more]

PMID: 31463161

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Dataset Information

Process Variation Detection using Missing Data in a Multihospital Community Practice Anatomic Pathology Laboratory.

Objectives

Materials and methods

Results

Conclusions

Publications

Process Variation Detection using Missing Data in a Multihospital Community Practice Anatomic Pathology Laboratory.

Similar Datasets

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