Electronic versus manual data processing

Evaluating the use of electronic health records in out-of-hospital clinical research

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35 Citations (Scopus)

Abstract

Objectives: The objective was to compare case ascertainment, agreement, validity, and missing values for clinical research data obtained, processed, and linked electronically from electronic health records (EHR) compared to "manual" data processing and record abstraction in a cohort of out-of-hospital trauma patients. Methods: This was a secondary analysis of two sets of data collected for a prospective, population-based, out-of-hospital trauma cohort evaluated by 10 emergency medical services (EMS) agencies transporting to 16 hospitals, from January 1, 2006, through October 2, 2007. Eighteen clinical, operational, procedural, and outcome variables were collected and processed separately and independently using two parallel data processing strategies by personnel blinded to patients in the other group. The electronic approach included EHR data exports from EMS agencies, reformatting, and probabilistic linkage to outcomes from local trauma registries and state discharge databases. The manual data processing approach included chart matching, data abstraction, and data entry by a trained abstractor. Descriptive statistics, measures of agreement, and validity were used to compare the two approaches to data processing. Results: During the 21-month period, 418 patients underwent both data processing methods and formed the primary cohort. Agreement was good to excellent (kappa = 0.76 to 0.97; intraclass correlation coefficient [ICC] = 0.49 to 0.97), with exact agreement in 67% to 99% of cases and a median difference of zero for all continuous and ordinal variables. The proportions of missing out-of-hospital values were similar between the two approaches, although electronic processing generated more missing outcomes (87 of 418, 21%, 95% confidence interval [CI] = 17% to 25%) than the manual approach (11 of 418, 3%, 95% CI = 1% to 5%). Case ascertainment of eligible injured patients was greater using electronic methods (n = 3,008) compared to manual methods (n = 629). Conclusions: In this sample of out-of-hospital trauma patients, an all-electronic data processing strategy identified more patients and generated values with good agreement and validity compared to traditional data collection and processing methods.

Original languageEnglish (US)
Pages (from-to)217-227
Number of pages11
JournalAcademic Emergency Medicine
Volume19
Issue number2
DOIs
StatePublished - Feb 2012

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Electronic Health Records
Research
Wounds and Injuries
Emergency Medical Services
Confidence Intervals
Automatic Data Processing
Registries
Databases
Population

ASJC Scopus subject areas

  • Emergency Medicine

Cite this

@article{c508fdf4b7db4bd28d0d7cfe322b14ff,
title = "Electronic versus manual data processing: Evaluating the use of electronic health records in out-of-hospital clinical research",
abstract = "Objectives: The objective was to compare case ascertainment, agreement, validity, and missing values for clinical research data obtained, processed, and linked electronically from electronic health records (EHR) compared to {"}manual{"} data processing and record abstraction in a cohort of out-of-hospital trauma patients. Methods: This was a secondary analysis of two sets of data collected for a prospective, population-based, out-of-hospital trauma cohort evaluated by 10 emergency medical services (EMS) agencies transporting to 16 hospitals, from January 1, 2006, through October 2, 2007. Eighteen clinical, operational, procedural, and outcome variables were collected and processed separately and independently using two parallel data processing strategies by personnel blinded to patients in the other group. The electronic approach included EHR data exports from EMS agencies, reformatting, and probabilistic linkage to outcomes from local trauma registries and state discharge databases. The manual data processing approach included chart matching, data abstraction, and data entry by a trained abstractor. Descriptive statistics, measures of agreement, and validity were used to compare the two approaches to data processing. Results: During the 21-month period, 418 patients underwent both data processing methods and formed the primary cohort. Agreement was good to excellent (kappa = 0.76 to 0.97; intraclass correlation coefficient [ICC] = 0.49 to 0.97), with exact agreement in 67{\%} to 99{\%} of cases and a median difference of zero for all continuous and ordinal variables. The proportions of missing out-of-hospital values were similar between the two approaches, although electronic processing generated more missing outcomes (87 of 418, 21{\%}, 95{\%} confidence interval [CI] = 17{\%} to 25{\%}) than the manual approach (11 of 418, 3{\%}, 95{\%} CI = 1{\%} to 5{\%}). Case ascertainment of eligible injured patients was greater using electronic methods (n = 3,008) compared to manual methods (n = 629). Conclusions: In this sample of out-of-hospital trauma patients, an all-electronic data processing strategy identified more patients and generated values with good agreement and validity compared to traditional data collection and processing methods.",
author = "Craig Newgard and Dana Zive and Jonathan Jui and Cody Weathers and Daya, {Mohamud Ramzan}",
year = "2012",
month = "2",
doi = "10.1111/j.1553-2712.2011.01275.x",
language = "English (US)",
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pages = "217--227",
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AU - Weathers, Cody

AU - Daya, Mohamud Ramzan

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N2 - Objectives: The objective was to compare case ascertainment, agreement, validity, and missing values for clinical research data obtained, processed, and linked electronically from electronic health records (EHR) compared to "manual" data processing and record abstraction in a cohort of out-of-hospital trauma patients. Methods: This was a secondary analysis of two sets of data collected for a prospective, population-based, out-of-hospital trauma cohort evaluated by 10 emergency medical services (EMS) agencies transporting to 16 hospitals, from January 1, 2006, through October 2, 2007. Eighteen clinical, operational, procedural, and outcome variables were collected and processed separately and independently using two parallel data processing strategies by personnel blinded to patients in the other group. The electronic approach included EHR data exports from EMS agencies, reformatting, and probabilistic linkage to outcomes from local trauma registries and state discharge databases. The manual data processing approach included chart matching, data abstraction, and data entry by a trained abstractor. Descriptive statistics, measures of agreement, and validity were used to compare the two approaches to data processing. Results: During the 21-month period, 418 patients underwent both data processing methods and formed the primary cohort. Agreement was good to excellent (kappa = 0.76 to 0.97; intraclass correlation coefficient [ICC] = 0.49 to 0.97), with exact agreement in 67% to 99% of cases and a median difference of zero for all continuous and ordinal variables. The proportions of missing out-of-hospital values were similar between the two approaches, although electronic processing generated more missing outcomes (87 of 418, 21%, 95% confidence interval [CI] = 17% to 25%) than the manual approach (11 of 418, 3%, 95% CI = 1% to 5%). Case ascertainment of eligible injured patients was greater using electronic methods (n = 3,008) compared to manual methods (n = 629). Conclusions: In this sample of out-of-hospital trauma patients, an all-electronic data processing strategy identified more patients and generated values with good agreement and validity compared to traditional data collection and processing methods.

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