Biomedical subjects

Pallav Sharda

Publications and source records attributed to Pallav Sharda.

3 recordsLinked to original sources

PubMed2005

Customizing clinical narratives for the electronic medical record interface using cognitive methods.

OBJECTIVE: As healthcare practice transitions from paper-based to computer-based records, there is increasing need to determine an effective electronic format for clinical narratives. Our research focuses on utilizing a cognitive science methodology to guide the conversion of medical texts to a more structured, user-customized presentation in the electronic medical record (EMR). DESIGN: We studied the use of discharge summaries by psychiatrists with varying expertise-experts, intermediates, and novices. Experts were given two hypothetical emergency care scenarios with narrative discharge summaries and asked to verbalize their clinical assessment. Based on the results, the narratives were presented in a more structured form. Intermediate and novice subjects received a narrative and a structured discharge summary, and were asked to verbalize their assessments of each. MEASUREMENTS: A qualitative comparison of the interview transcripts of all subjects was done by analysis of recall and inference made with respect to level of expertise. RESULTS: For intermediate and novice subjects, recall was greater with the structured form than with the narrative. Novices were also able to make more inferences (not always accurate) from the structured form than with the narrative. Errors occurred in assessments using the narrative form but not the structured form. CONCLUSIONS: Our cognitive methods to study discharge summary use enabled us to extract a conceptual representation of clinical narratives from end-users. This method allowed us to identify clinically relevant information that can be used to structure medical text for the EMR and potentially improve recall and reduce errors.

Cognitive Science↗

PubMed2003

Specifying design criteria for electronic medical record interface using cognitive framework.

As the healthcare industry transitions from paper to electronic medical records (EMRs), medical informatics researchers face the task of ensuring that the electronic presentation of the information remains usable and effective while capitalizing on the ability of EMRs to tailor information to different users. In our research, we focus on utilizing formal cognitive science methodology to guide the conversion of paper-based narrative discharge summaries to a more dynamic, structured electronic version. In this paper, we present the results of a cognitive analytic study (1) that determines a 'core' component in medical narratives and (2) that compares the use of structured and narrative texts by physicians with varying expertise. Specifically, we studied six psychiatrists at three levels of expertise- experts, intermediates, and novices. The subjects were given two clinical case scenarios with discharge summaries and asked to verbalize their thoughts as they read through the summaries. The interview transcripts were analyzed for recalls and inferences generated in the verbalization. Based on experts' verbalizations, the discharge summaries were organized into a more structured form and used in the interview of other subjects. Novice-level subjects had more recall with the structured than with the narrative format. More errors were also made in recall with the narrative than with the structured text. We discuss how these results are valuable in designing an EMR interface to reduce errors and to support users of different expertise.

Cognition↗

PubMed2003

An experimental system for comparing speed, accuracy, and completeness of physician data entry using electronic and paper methods.

Electronic medical record (EMR) systems have important potential advantages over traditional paper-based systems, but they require that physicians assume responsibility for data entry. However, little is known about the quality of physician data entry in electronic systems. This study describes a system for comparing the speed, accuracy, and completeness of examination data entry using electronic and paper methods. Data will be shown to demonstrate that this may be a simple, reproducible, and useful technique.

Humans↗