Abstract
Medical information systems play a vital role in the everyday successful treatment of patients in hospitals, general practitioners’ offices, and beyond. From storing patient information in electronic health records to the recommendation of treatment options, and the warning on wrong prescriptions or dosages, the information systems provide a multitude of different features. These can be utilized in prospective, direct, and retrospective patient care. One especially important task is the prevention of drug interactions and their potential adverse drug reactions in polypharmacy patients. All of these tasks require a solid data basis and data integration processes to provide the latest recommendations and information to healthcare professionals. Where historically, single large databases such as ABDAmed on the German market provided all required information, newer systems use a multitude of different data sources of high quality. This chapter analyzes different examples of medical information systems, the underlying data integration, and how a solid integration workflow can elevate the potential of old and new healthcare information. The examples range from drug therapy safety systems using official healthcare database, over potentially inadequate medication systems, to molecular biological analysis tools. Finally, the chapter outlines an approach how new data integration efforts may bring all of these systems together for the prospect of patient treatment in a personalized manner.
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ABDATA Pharma-Daten-Service: Abdamed. https://abdata.de/datenangebot/abdamed/. Accessed: 2021-04-29
Alban S, Ulrich M, Arben S, Venus O, Ralf H (2017) Kalis—an ehealth system for biomedical risk analysis of drugs. Stud Health Technol Inform 236(Health Informatics Meets eHealth):128–135
American Chemical Society: Chemical abstracts service (CAS). https://www.cas.org. Accessed: 2021-04-29
BfArM: Verkehrsfähige arzneimittel im zuständigkeitsbereich des bfarm. https://www.bfarm.de/DE/Service/Statistiken/AM_statistik/statistik-verkf-am-zustBfArM.html. Updated: 2021-04-16
Boustani M, Baker MS, Campbell N, Munger S, Hui SL, Castelluccio P, Farber M, Guzman O, Ademuyiwa A, Miller D, Callahan C (2010) Impact and recognition of cognitive impairment among hospitalized elders. J Hosp Med 5(2):69–75
Chrischilles EA, VanGilder R, Wright K, Kelly M, Wallace RB (2009) Inappropriate medication use as a risk factor for self-reported adverse drug effects in older adults. J Am Geriatr Soc 57(6):1000–1006
Dippl H (2011) Hepatische cytochrom-wechselwirkungen von pharmakologischen substanzen—eine literaturrecherche für den zeitraum 2000–2008
Duerinckx AJ, Pisa EJ (1982) Filmless picture archiving and communication in diagnostic radiology. In: Duerinckx AJ (ed) 1st International conference and workshop on picture archiving and communication systems, vol 0318. International Society for Optics and Photonics, SPIE, New York, pp 9–18
FDA: FDA adverse event reporting system (FAERS). https://www.fda.gov. Accessed: 2021-04-29
Fick D (2001) Potentially inappropriate medication use in a medicare managed care population: association with higher costs and utilization. J Manag Care Pharm 7(5):407–413
Fiss T, Dreier A, Meinke C, van den Berg N, Ritter CA, Hoffmann W (2010) Frequency of inappropriate drugs in primary care: analysis of a sample of immobile patients who received periodic home visits. Age Ageing 40(1):66–73
German Federal Statistical Office: 14. koordinierte bevölkerungsvorausberechnung. https://service.destatis.de/bevoelkerungspyramide. Accessed: 2021-04-29
Grandt D, Lappe V, Schubert I (2018) BARMER Arzneimittelreport 2018 Schriftenreihe zur Gesundheitsanalyse. BARMER
Health Canada: Canada vigilance adverse reaction online database. https://www.canada.ca/en/health-canada/services/drugs-health-products/medeffect-canada/adverse-reaction-database.html. Accessed: 2021-04-29
Health Canada: Drug product database (DPD). https://health-products.canada.ca/dpd-bdpp/. Accessed: 2021-04-29
Hippe K, Kormeier B, Töpel T, Janowski SJ, Hofestädt R (2010) DAWIS-M.D.—A Data Warehouse System for Metabolic Data, pp 720–725. Ges. für Informatik
Holt S, Schmiedl S, ThĂĽrmann PA (2010) Potentially inappropriate medications in the elderly. Deutsches Aerzteblatt Online
International council for harmonisation of technical requirements for pharmaceuticals for human use (ICH): medical dictionary for regulatory activities (MEDDRA). https://www.meddra.org. Accessed: 2021-04-29
Kanehisa M (2000) KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28(1):27–30
Kim S, Chen J, Cheng T, Gindulyte A, He J, He S, Li Q, Shoemaker BA, Thiessen PA, Yu B, Zaslavsky L, Zhang J, Bolton EE (2020) PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res 49(D1):D1388–D1395
Knox C, Law V, Jewison T, Liu P, Ly S, Frolkis A, Pon A, Banco K, Mak C, Neveu V, Djoumbou Y, Eisner R, Guo AC, Wishart DS (2010) DrugBank 3.0: a comprehensive resource for omics’ research on drugs. Nucleic Acids Res 39(Database):D1035–D1041
Kuhn M, Campillos M, Letunic I, Jensen LJ, Bork P (2010) A side effect resource to capture phenotypic effects of drugs. Mol Syst Biol 6(1):343
Mann E., Böhmdorfer B, Frühwald T, Roller-Wirnsberger RE, Dovjak P, Dückelmann-Hofer C, Fischer P, Rabady S, Iglseder B (2011) Potentially inappropriate medication in geriatric patients: the Austrian consensus panel list. Wien Klin Wochenschr 124(5-6):160–169
Pazan F, Weiss C, Wehling M (2019) The FORTA (fit fOR the aged) list 2018: third version of a validated clinical tool for improved drug treatment in older people. Drugs Aging 36(5):481–484
Renom-Guiteras A, Meyer G, Thürmann PA (2015) The EU(7)-PIM list: a list of potentially inappropriate medications for older people consented by experts from seven European countries. Eur J Clin Pharmacol 71(7):861–875
Rote Liste® Service GmbH: Rote liste®. https://www.rote-liste.de. Accessed: 2021-04-29
Shoshi A, Hoppe T, Kormeier B, Ogultarhan V, Hofestädt R (2015) GraphSAW: a web-based system for graphical analysis of drug interactions and side effects using pharmaceutical and molecular data. BMC Med Inform Decis Mak 15(1):1–10
Töpel T, Kormeier B, Klassen A, Hofestädt R (2008) BioDWH: A data warehouse kit for life science data integration. J Integr Bioinform 5(2):49–57
Vidal MMI Germany GmbH: Gelbe liste®. https://www.gelbe-liste.de. Accessed: 2021-04-29
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Friedrichs, M. (2022). Data Integration Applications in Medical Information Systems. In: Chen, M., Hofestädt, R. (eds) Integrative Bioinformatics. Springer, Singapore. https://doi.org/10.1007/978-981-16-6795-4_11
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DOI: https://doi.org/10.1007/978-981-16-6795-4_11
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