Biomedical subjects

Erik Korsten

Publications and source records attributed to Erik Korsten.

3 recordsLinked to original sources

PubMed2006

Towards patient-related information needs.

The quality of health care depends, among other factors, on the quality of a physician's domain knowledge. Since it is impossible to keep up with all new findings and developments, physicians usually have gaps in their domain knowledge. To handle exceptional cases, access to the full range of medical literature is required. The specific literature needed for appropriate treatment of the patient is described by a physician's information need. Physicians are often unaware of their information needs. To support them, this paper presents a first step towards automatically formulating patient-related information needs. We start investigating how we can model a physician's information needs in general. Then we propose an approach to instantiate the model into a representation of a physician's information needs using the patient data as stored in a medical record. Our experiments show that this approach is feasible. Since the number of formulated patient-related information needs is rather high, it has to be reduced. To reduce the number of formulated information needs we propose the use of additional knowledge. Four types of knowledge are discussed, viz. (a) knowledge about temporal aspects, (b) domain knowledge, (c) knowledge about a physician's specialism, and (d) a user model. Future research has to clarify which type of knowledge (or combination thereof) is most appropriate for our purpose. It is expected that the resultant set of information needs will have a manageable size and contributes to the quality of health care.

Humans↗

PubMed2005

Towards patient-related information needs.

The quality of health care depends, among others, on the quality of a physician's domain knowledge. Since it is impossible to keep up with all new findings and developments, physicians usually have gaps in their domain knowledge. To handle exceptional cases, access to the full range of medical literature is required. The specific literature needed for appropriate treatment of the patient is described by a physician's information need. Physicians are often unaware of their information needs. To support them, this paperThis research is part of the MIA project (Medical Information Agent), which is funded by NWO (grant number 634.000.021). aims at presenting a first step towards automatically formulating patient-related information needs. We start investigating how we can model a physician's information needs in general. Then we propose an approach to instantiate the model into a representation of a physician's information needs using the patient data as stored in a medical record. Our experiments show that this approach is feasible. Since the number of formulated patient-related information needs is rather high, we propose the use of filters. Future research will focus on the combination of personalization and filtering. It is expected that the resultant set of information needs will have a manageable size and contributes to the quality of health care.

Forecasting↗

PubMed2004

From patient data to information needs.

The goal of this paper is to contribute to the improvement of the quality of care. For physicians, it is a problem that they are often not aware of gaps in their knowledge and the corresponding information needs. Our research aim is to resolve this problem by formulating information needs automatically. Based on these information needs, patient-specific literature can be retrieved. As a first step, we investigate how to model a physician's information needs. Thereafter, we design and analyse an approach to instantiate the model with patient data, resulting in information-need templates that are able to represent patient-specific information needs. Our experiments show that a physician's information needs can be modelled adequately and can be substantiated into patient-specific information needs. Since the number of formulated information needs is rather high, future research will focus on methods that restrict the set of automatically formulated information needs to a more specialized set.

Information Storage and Retrieval↗