Objective: This study evaluated a computerized method for extracting numeric clinical measurements related to diabetes care from free text in electronic patient records (EPR) of general practitioners. Design and Measurements: Accuracy of this number-oriented approach was compared to manual chart abstraction. Audits measured performance in clinical practice for two commonly used electronic record systems. Results: Numeric measurements embedded within free text of the EPRs constituted 80% of relevant measurements. For 11 of 13 clinical measurements, the study extraction method was 94%-100% sensitive with a positive predictive value (PPV) of 85%-100%. Post-processing increased sensitivity several points and improved PPV to 100%. Application in...
ABSTRACT: BACKGROUND: Patient information, medical history, clinical outcomes and demographic inform...
Electronic Patient Records can be interfaced with medical decision support systems and quality of ca...
BACKGROUND: Electronic medical records contain valuable clinical information not readily available e...
Objective: This study evaluated a computerized method for extracting numeric clinical measurements r...
Item does not contain fulltextOBJECTIVE: Quality indicators for the treatment of type 2 diabetes are...
Objectives: To evaluate a semi-automatic data extraction from the electronic medical record (EMR) of...
AIMS: Type 2 diabetes mellitus is a worldwide cause of significant morbidity and mortality. The gene...
Contains fulltext : 172259.pdf (publisher's version ) (Open Access)BACKGROUND: Wit...
<p><b>OBJECTIVES: </b>To evaluate a semi-automatic data extraction from the electr...
Background The review of clinical data extraction from electronic records is increasingly being used...
Contains fulltext : 161049.pdf (publisher's version ) (Open Access)Background: Wit...
BACKGROUND: Electronic diabetes registers promote structured care and enable identification of undia...
Background: Electronic diabetes registers promote structured care and enable identification of undia...
Electronic medical records (EMRs) in primary care represent a longitudinal record of patient’s curre...
The most important information in Electronic Health Records is in free text form. The result is that...
ABSTRACT: BACKGROUND: Patient information, medical history, clinical outcomes and demographic inform...
Electronic Patient Records can be interfaced with medical decision support systems and quality of ca...
BACKGROUND: Electronic medical records contain valuable clinical information not readily available e...
Objective: This study evaluated a computerized method for extracting numeric clinical measurements r...
Item does not contain fulltextOBJECTIVE: Quality indicators for the treatment of type 2 diabetes are...
Objectives: To evaluate a semi-automatic data extraction from the electronic medical record (EMR) of...
AIMS: Type 2 diabetes mellitus is a worldwide cause of significant morbidity and mortality. The gene...
Contains fulltext : 172259.pdf (publisher's version ) (Open Access)BACKGROUND: Wit...
<p><b>OBJECTIVES: </b>To evaluate a semi-automatic data extraction from the electr...
Background The review of clinical data extraction from electronic records is increasingly being used...
Contains fulltext : 161049.pdf (publisher's version ) (Open Access)Background: Wit...
BACKGROUND: Electronic diabetes registers promote structured care and enable identification of undia...
Background: Electronic diabetes registers promote structured care and enable identification of undia...
Electronic medical records (EMRs) in primary care represent a longitudinal record of patient’s curre...
The most important information in Electronic Health Records is in free text form. The result is that...
ABSTRACT: BACKGROUND: Patient information, medical history, clinical outcomes and demographic inform...
Electronic Patient Records can be interfaced with medical decision support systems and quality of ca...
BACKGROUND: Electronic medical records contain valuable clinical information not readily available e...