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Assessing the feasibility of a mobile health-supported clinical decision support system for nutritional triage in
Jeroen S de Bruin1, Christian Schuh1, Walter Seeling1
1Section for Medical Expert and Knowledge-Based Systems, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria.
Background:
Nutritional screening procedures followed by regular nutrition monitoring for oncological outpatients are no standard practice in many European hospital wards and outpatient settings. As a result, early signs of malnutrition are missed and nutritional treatment is initiated when patients have already experienced severe weight loss.
Objective:
We report on a novel clinical decision support system (CDSS) for the global assessment and nutritional triage of the nutritional condition of oncology outpatients. The system combines clinical and laboratory data collected in the clinical setting with patient-generated data from a smartphone application for monitoring the patients' nutritional status. Our objective is to assess the feasibility of a CDSS that combines the aforementioned data sources and describe its integration into a hospital information system. Furthermore, we collected patients' opinions on the value of the system, and whether they would regard the system as a useful aid in coping with their condition.
Materials And Methods:
The system implements the Patient-Generated Subjective Global Assessment (PG-SGA) to monitor nutritional status in the outpatient setting. A smartphone application is used to collect patient-generated data by performing weekly mini-surveys on patients concerning their eating habits, weight, and overall well-being. Data are uploaded on completion of each mini-survey and stored on a secure server at the Medical University of Vienna (MUV). The data are then combined with relevant clinical information from the Vienna General Hospital (VGH) information system. The knowledge base for the CDSS is implemented in medical logic modules (MLMs) using Arden Syntax. A three-month pilot clinical trial was performed to test the feasibility of the system. Qualitative questionnaires were used to obtain the patients' opinions on the usability and personal value of the system during the four-week test period.
Results:
We used the existing separation between the scientific and clinical data domains in the secured network environment (SNE) at the MUV and VGH to our advantage by importing, storing, and processing both patient-generated and routine data in the scientific data domain. To limit exposure to the SNE, patient-generated data stored outside the SNE were imported to the scientific domain once a day. The CDSS created for nutritional assessment and triage comprised ten MLMs, each including either a sub-assessment or the final results of the PG-SGA. Finally, an interface created for the hospital information system showed the results directly in clinical routine. In all 22 patients completed the clinical study. The results of the questionnaires showed that 91% of the patients were generally happy with the usability of the system, 91% believed that the application was of additional value in detecting cancer-related malnutrition, and 82% found it helpful as a long-term monitoring tool.
Discussion And Conclusion:
Despite strict protection of the clinical data domain, a CDSS employing patient-generated data can be integrated into clinical routine. The CDSS discussed in this report combined the information entered into a smartphone application with clinical data in order to inform the physician of a patient's nutritional status and thus permit suitable and timely intervention. The initial results show that the smartphone application was well accepted by patients, who considered it useful, but not many oncological outpatients were willing to participate in the clinical study because they did not possess an Android phone or lacked smartphone expertise. Furthermore, the results indicate that patient-generated data could be employed to augment clinical data and calculate metrics such as the PG-SGA without excessive effort by using a secure intermediate location as the locus of data storage and processing.
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