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Biomedical subjects

Floris Wiesman

Publications and source records attributed to Floris Wiesman.

4 recordsLinked to original sources

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↗

Avoiding literature overload in the medical domain.

The retrieval of patient-related literature is hampered by the large size of medical literature. Various computer systems have been developed to assist physicians during information retrieval. However, in general, physicians lack the time and skills required to employ such systems effectively. Our goal is to investigate to what extent a physician can be provided with patient-related literature without spending extra time and without acquiring additional skills. In previous research we developed a method to formulate a physician's patient-related information needs automatically, without requiring any interaction between the physician and the system. The formulated information needs can be used as a starting point for literature retrieval. As a result we found that the number of information needs formulated per physician was quite high and had to be reduced to avoid a literature overload. In this paper we present four types of knowledge that may be used to accomplish a reduction in the number of information needs. The usefulness of each of these knowledge types depends heavily on the specific cause underlying the multitude of information needs. To determine the nature of the cause, we performed an experimental analysis. The results of the analysis led us to conclude that the knowledge types can be ordered according to their appropriateness as follows: (1) knowledge concerning temporal aspects, (2) knowledge concerning a physician's specialism, (3) domain knowledge, and (4) a user model. Further research has to be performed, in particular on precisely assessing the performance of each type of knowledge within our domain.

Information Management↗

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↗

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↗