Biomedical subjects

Adam B Wilcox

Publications and source records attributed to Adam B Wilcox.

6 recordsLinked to original sources

PubMed2006

Automated identification of adverse events related to central venous catheters.

Methods for surveillance of adverse events (AEs) in clinical settings are limited by cost, technology, and appropriate data availability. In this study, two methods for semi-automated review of text records within the Veterans Administration database are utilized to identify AEs related to the placement of central venous catheters (CVCs): a Natural Language Processing program and a phrase-matching algorithm. A sample of manually reviewed records were then compared to the results of both methods to assess sensitivity and specificity. The phrase-matching algorithm was found to be a sensitive but relatively non-specific method, whereas a natural language processing system was significantly more specific but less sensitive. Positive predictive values for each method estimated the CVC-associated AE rate at this institution to be 6.4 and 6.2%, respectively. Using both methods together results in acceptable sensitivity and specificity (72.0 and 80.1%, respectively). All methods including manual chart review are limited by incomplete or inaccurate clinician documentation. A secondary finding was related to the completeness of administrative data (ICD-9 and CPT codes) used to identify intensive care unit patients in whom a CVC was placed. Administrative data identified less than 11% of patients who had a CVC placed. This suggests that other methods, including automated methods such as phrase matching, may be more sensitive than administrative data in identifying patients with devices. Considerable potential exists for the use of such methods for the identification of patients at risk, AE surveillance, and prevention of AEs through decision support technologies.

Artificial Intelligence↗

PubMed2005

Physician use of electronic medical records: issues and successes with direct data entry and physician productivity.

At Intermountain Health Care, we evaluated whether physicians in an ambulatory setting will voluntarily choose to enter data directly into an electronic health record (EHR). In this paper we describe the benefits of an EHR, as they exist in the current IHC application and the ways in which we have sought to minimize obstacles to physician data entry. Currently, of 472 IHC employed physicians, 321 (68%) routinely enter some data directly into the EHR without coercion. Twenty-five percent (80/321) of the physicians use voice recognition for some data entry. Twelve of our 95 ambulatory clinics have voluntarily adopted measures to eliminate paper charts. Of the 212 physicians who entered data in 2004, sixty-nine physicians (22%) increased their level of data entry, while 12 (6%) decreased. We conclude that physicians will voluntarily adopt an EHR system, and will continue and even increase use after implementation barriers are addressed.

Ambulatory Care Information Systems↗

PubMed2005

Use and impact of a computer-generated patient summary worksheet for primary care.

Advanced clinical information systems have been proposed to improve patient care in terms of safety, effectiveness, and efficiency. In order to be effective, such systems require detailed patient-specific clinical information in a form easily reviewed by clinicians. We have developed a patient summary worksheet for use in outpatient clinics, which presents a structured overview of patient health information. The worksheet provides patient demographic information, specific problems and conditions, the patient's current medication profile, laboratory test results pertinent to patient problems, and disease-specific or preventive care actionable advisories. Usage has grown from a few hundred to over 25,000 unique patients per month during a two-year period. Diabetic patients for whom the worksheet is accessed are significantly more likely to be in compliance with accepted testing regimens for glycosolated hemoglobin (OR 1.47, 95% CI 1.28, 1.61).

Ambulatory Care Facilities↗

PubMed2005

The effect of longitudinal EMR access on laboratory ordering.

A longitudinal electronic medical record (EMR) allows physicians to access laboratory results in the context of the patient's medical history. Daily lab order volumes were tracked for physicians with access to an EMR and physicians with no EMR access to assess whether physicians with EMR access changed their lab order habits significantly more than a matched set of controls. This study shows that physicians will change their ordering habits in order to access the lab results in the context of an EMR.

Clinical Laboratory Information Systems↗

PubMed2003

The role of domain knowledge in automating medical text report classification.

OBJECTIVE: To analyze the effect of expert knowledge on the inductive learning process in creating classifiers for medical text reports. DESIGN: The authors converted medical text reports to a structured form through natural language processing. They then inductively created classifiers for medical text reports using varying degrees and types of expert knowledge and different inductive learning algorithms. The authors measured performance of the different classifiers as well as the costs to induce classifiers and acquire expert knowledge. MEASUREMENTS: The measurements used were classifier performance, training-set size efficiency, and classifier creation cost. RESULTS: Expert knowledge was shown to be the most significant factor affecting inductive learning performance, outweighing differences in learning algorithms. The use of expert knowledge can affect comparisons between learning algorithms. This expert knowledge may be obtained and represented separately as knowledge about the clinical task or about the data representation used. The benefit of the expert knowledge is more than that of inductive learning itself, with less cost to obtain. CONCLUSION: For medical text report classification, expert knowledge acquisition is more significant to performance and more cost-effective to obtain than knowledge discovery. Building classifiers should therefore focus more on acquiring knowledge from experts than trying to learn this knowledge inductively.

Algorithms↗

PubMed2002

Using natural language processing to analyze physician modifications to data entry templates.

Efficient data entry by clinicians remains a significant challenge for electronic medical records. Current approaches have largely focused on either structured data entry, which can be limiting in expressive power, or free-text entry, which restricts the use of the data for automated decision support. Text-based templates are a semi-structured data entry method that has been used to assist physicians in manually entering clinical notes, by allowing them to edit predefined example notes. We analyzed changes made to 18,726 sentences from text templates, using a natural language processor. The most common changes were addition or deletion of normal observations, or changes in certainty. We identified common modifications that could be captured in structured form by a graphical user interface.

Medical Records Systems, Computerized↗