J. H. M. Zwetsloot-Schonk

Current Challenge in Consumer Health Informatics: Bridging the Gap between Access to Information and Information Understanding

The number of health-related websites has proliferated over the past few years. Health information consumers confront a myriad of health related resources on the internet that have varying levels of quality and are not always easy to comprehend. There is thus a need to help health information consumers to bridge the gap between access to information and information understanding–-i.e. to help consumers understand health related web-based resources so that they can act upon it. At the same time health information consumers are becoming not only more involved in their own health care but also more information technology minded. One way to address this issue is to provide consumers with tailored information that is contextualized and personalized e.g. directly relevant and easily comprehensible to the persons own health situation. This paper presents a current trend in Consumer Health Informatics which focuses on theory-based design and development of contextualized and personalized tools to allow the evolving consumer with varying backgrounds and interests to use online health information efficiently. The proposed approach uses a theoretical framework of communication in order to support the consumers capacity to understand health-related web-based resources.

Increased risk of second cancers in managing Hodgkin's disease: the 20-year Leiden experience

SummaryBetween January 1969 and December 1988, 482 patients were treated for Hodgkins disease at the Leiden University Hospital. All cases were routinely recorded in the Hospital Information System, which has an active annual follow-up. Of all patients, 57% remained relapse free. According to the kinds of treatment they received, the following major categories were established: radiotherapy only (28.2%), chemotherapy only (20.1%), only initial combination of radiotherapy and chemotherapy (34.2%), all other combinations of radio- and chemotherapy (15.4%), or not registered (2.1%). Twenty-seven second cancers were observed; six leukemias, five non-Hodgkin lymphomas, and 16 solid tumors. Of all solid tumors only nine occurred in relapse-free patients. The overall relative risk of second cancers increased with the duration of follow-up. Using general population incidence rates to calculate expected numbers, the risk for developing leukemia, non-Hodgkin lymphoma, and solid tumors was increased 36-fold, 31-fold, and 2.4-fold, respectively. The cumulative risk of developing a second cancer 10 years after diagnosis of Hodgkins disease was 7% for both the radiotherapy-only and the initial combination of radio- and chemotherapy group. It was 16% and 17% for the chemotherapy-only and the other combinations of radio- and chemotherapy group, respectively. Multivariate analysis (using the Cox regression model) show an increased risk of second cancers (RR=0.7) when a relapse of Hodgkins disease resulting in increasing cumulative therapy occurred. Age at diagnosis of Hodgkins disease was an important determinant for the risk of non-Hodgkin lymphoma and solid tumors. Cumulative chemotherapy intensity was an important factor in increasing leukemic risk in a dose-response fashion. Apart from this, the stage of Hodgkins disease, although closely related to the kind of therapy, seemed to have an independent effect on leukemic risk.

Use cases and DEMO: aligning functional features of ICT-infrastructure to business processes

OBJECTIVES The proper alignment of functional features of the ICT-infrastructure to business processes is a major challenge in health care organisations. This alignment takes into account that the organisational structure not only shapes the ICT-infrastructure, but that the inverse also holds. To solve the alignment problem, relevant features of the ICT-infrastructure should be derived from the organisational structure and the influence of this envisaged ICT to the work practices should be pointed out. The objective of our study was to develop a method to solve this alignment problem. METHODS In a previous study we demonstrated the appropriateness of the business process modelling methodology Dynamic Essential Modelling of Organizations (DEMO). A proven and widely used modelling language for expressing functional features is Unified Modelling Language (UML). In the context of a specific case study at the University Medical Centre Utrecht in the Netherlands we investigated if the combined use of DEMO and UML could solve the alignment problem. RESULTS AND CONCLUSION The study demonstrated that the DEMO models were suited as a starting point in deriving system functionality by using the use case concept of UML. Further, the case study demonstrated that in using this approach for the alignment problem, insight is gained into the mutual influence of ICT-infrastructure and organisation structure: (a) specification of independent, re-usable components-as a set of related functionalities-is realised, and (b) a helpful representation of the current and future work practice is provided for in relation to the envisaged ICT support.

Using hospital information systems for clinical epidemiological research

We address the question of how data collected during routine medical practice and stored in a hospital information system to support the various functions of the hospital can be used for clinical epidemiological research. The hospital information system HIS developed by BAZIS and implemented at the Leiden University Hospital is used as an example because the availability of data for clinical research is considered a potential benefit of the BAZIS-HIS. After a brief outline of the research area of clinical epidemiology and the BAZIS-HIS has been given, three different ways in which a hospital information system can be used in clinical epidemiology, are discussed: (1) as a sampling frame to select the study population; (2) to collect data from patients taking part in the study; (3) to register data specifically collected for the study. Whether or not the hospital information system is used in a particular study depends on the specific research question, the design of the study, the content of the database and the completeness and accuracy of the registration. We shall argue that retrieval facilities alone are not sufficient to support clinical research. To decide which items can best be used to select a study population, it is necessary to know how medical events take place in daily practice and how they are registered. Therefore when data stored in hospital information systems are used for epidemiological research, close collaboration is required between the clinical epidemiologists, the hospital administrative personnel and the data processing experts.

On the use of a hospital information system in evaluating clinical care: a case report

In this paper we describe, as an example, how we obtained the information needed to evaluate a newly introduced protocol for ordering X-rays for ankle trauma patients. Extensive use was made of available data and facilities of the hospital information system (HIS). Procedures for collecting the required additional data, which were not recorded in the HIS but were needed to evaluate the protocol, were embedded in the current medical and administrative routine of the emergency room. These additional data were also stored in the HIS. Periodically all data were downloaded to a personal computer to analyse the impact of using the protocol on quality of care and costs. In total 1241 patients entered the study, and for 1149 patients a complete dataset was obtained. The sensitivity and specificity of the protocol at the threshold value which was used during the initial study period was 0.77 and 0.80. The reduction in the number of ankle X-rays due to the protocol was significant when compared with a strategy of ordering an X-ray for every ankle trauma patient visiting the emergency room.

How to approach a hospital information system as sampling frame Selection of patients with a percutaneous renal biopsy

The paper describes the four steps that have to be taken in the process of using a hospital information system as sampling frame: step 1, description of the medical routine and registrations related to the study population; step 2, defining the design and criteria for selection; step 3, creating the datafile and step 4, validating the datafile. To illustrate these four steps a detailed description of the selection of patients with a percutaneous renal biopsy is given, using the central database of Leiden University Hospital. All registrations relating to patients undergoing a percutaneous renal biopsy in 1985 and 1986 were taken into account and combined in defining the design and criteria for selection. The selection resulted in 182 patient-records, of which 177 were compared with the medical file. Overall 150 percutaneous biopsies were confirmed. Hospital Information Systems are in principle useful as sampling frames for clinical research. However, to use these systems successfully in selecting a study population intensive mutual consultation between clinicians, clinical epidemiologists, database experts and administrative personnel is required.