Business Intelligence Applications in Health - Management and Clinical Areas
DOI:
https://doi.org/10.25746/ruiips.v10.i4.29103Keywords:
Health Information Technologies, Business Intelligence, Health, HealthcareAbstract
This article makes an integrative review of the state of the art in the application of Business Intelligence solutions in health care, both in the provision of care and in the management of healthcare institutions. To this end, a survey of scientific articles, published between 2018 and 2022, relating the terms of “Business Intelligence” and “Health” was carried out at b-On, with a result of 26 articles, 16 related to the provision of care and 11 associated with management. These showed the prevalence of solutions in a high number of clinical areas, such as cardiology, neurology, radiology, or pathology, and of management, from the scheduling of exams, human resources management or performance analysis, demonstrating the high potential of this type of solutions in the healthcare sector.
References
Abreu, J., Guimarães, T., Abelha, A., & Santos, M. F. (2022). Business Analytics Components for Public Health Institution - Clinical Decision Area. Procedia Computer Science, 198, 335–340. https://doi.org/10.1016/j.procs.2021.12.250
Andrade, J. R. M., & Blomberg, L. C. (2022). Business intelligence applied to the consumption of iodinated contrast agents in computed tomography scans. BMC Medical Informatics and Decision Making, 22(1). https://doi.org/10.1186/s12911-022-01814-9
Azevedo, J., Duarte, J., & Santos, M. F. (2022). Implementing a business intelligence cost accounting solution in a healthcare setting. Procedia Computer Science, 198, 329–334. https://doi.org/10.1016/j.procs.2021.12.249
Basile, L. J., Carbonara, N., Pellegrino, R., & Panniello, U. (2022). Business intelligence in the healthcare industry: The utilization of a data-driven approach to support clinical decision making. Technovation, 102482. https://doi.org/10.1016/j.technovation.2022.102482
Bréant, C., Succi, L., Cotten, M., Grimaud, S., Iavindrasana, J., Kindstrand, M., Mauvais, F., & RoriveFeytmans, B. (2020). Tools to measure, monitor, and analyse the performance of the Geneva university hospitals (HUG). Supply Chain Forum: An International Journal, 21(2), 117–131. https://doi.org/10.1080/16258312.2020.1780634
Chang, A. Y., Cowling, K., Micah, A. E., Chapin, A., Chen, C. S., Ikilezi, G., Sadat, N., Tsakalos, G., Wu, J., Younker, T., Zhao, Y., Zlavog, B. S., Abbafati, C., Ahmed, A. E., Alam, K., Alipour, V., Aljunid, S. M., Almalki, M. J., Alvis-Guzman, N., Dieleman, J. L. (2019). Past, present, and future of global health financing: a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995–2050. The Lancet, 393(10187), 2233–2260.
https://doi.org/10.1016/s0140-6736(19)30841-4
Cruz, M., Guimarães, T., Abelha, A., & Santos, M. F. (2022). Business Analytics Components for Public Health Institution -Nursing Decision Area. Procedia Computer Science, 198, 347–352. https://doi.org/10.1016/j.procs.2021.12.252
Definition of Analytics and Business Intelligence (ABI) - Gartner Information Technology Glossary. (n.d.). Gartner. Acedido em dezembro 18, 2022, https://www.gartner.com/en/informationtechnology/glossary/business-intelligence-bi
Degen, G.-A., Günther, V., Holm, J., Bürkle, T., & Sariyar, M. (2020). Using Business Intelligence Tools to Support Medical Validation of Laboratory Tests. Studies in Health Technology and Informatics, 270, 494–498. https://doi.org/10.3233/SHTI200209
Esteves, M., Abelha, A., & Machado, J. (2019a). The development of a pervasive Web application to alert patients based on business intelligence clinical indicators: a case study in a health institution. Wireless Networks, 28(3), 1279–1285. https://doi.org/10.1007/s11276-018-01911-6
Esteves, M., Esteves, M., Abelha, A., & Machado, J. (2019b). A Proof of Concept of a Mobile Health Application to Support Professionals in a Portuguese Nursing Home. Sensors, 19(18), 3951. https://doi.org/10.3390/s19183951
Fernandez, S., Jenkins, P., & Vieira, B. (2020, Julho 24). Europe’s digital migration during COVID-19: Getting past the broad trends and averages. McKinsey & Company. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/europes-digital-migration-duringcovid-19-getting-past-the-broad-trends-and-averages
Gaardboe, R., Nyvang, T., & Sandalgaard, N. (2017). Business Intelligence Success applied to Healthcare Information Systems. Procedia Computer Science, 121, 483–490. https://doi.org/10.1016/j.procs.2017.11.065
Gaardboe, R., Sandalgaard, N., & Nyvang, T. (2022). An assessment of business intelligence in public hospitals. International Journal of Information Systems and Project Management, 5(4), 5–18. https://doi.org/10.12821/ijispm050401
Longoni, C., Bonezzi, A. & Morewedge, C. (2020). Resistance to medical artificial intelligence is an attribute in a compensatory decision process: Response to pezzo and beckstead. Judgment and Decision Making. 15. 446-448.
Manyika, J., Ramaswamy, S., Khanna, S., Sarrazin, H., Pinkus, G., Sethupathy, G., & Yaffe, A. (2019, Fevereiro 13). Digital America: A tale of the haves and have-mores. McKinsey & Company. https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/digitalamerica-a-tale-of-the-haves-and-have-mores
Mekahlia, F. Z., Bouzama, M. Z., & Nechar, S. (2022). Impact of Vaccination on COVID-19 Spread in Real Time: Visualization and Analysis Tool. Ingénierie Des Systèmes D Information, 27(2), 293–301. https://doi.org/10.18280/isi.270213
Mettler, T., & Vimarlund, V. (2009). Understanding business intelligence in the context of healthcare. Health Informatics Journal, 15(3), 254–264. https://doi.org/10.1177/1460458209337446
Oliveira, D., Santos, A., Braga, D., Silva, I., Sousa, R., Abelha, A., & Machado, J. (2022). OpenEHR modelling applied to Complementary Diagnostics Requests. Procedia Computer Science, 210, 265–270.h https://doi.org/10.1016/j.procs.2022.10.148
Ovchinnikov, D. A., Potapov, I. V., Kurapeev, D. I., Vashenkov, V. V., & Konradi, A. O. (2021). Digitalizing quality of care control: a Business Intelligence system for COVID-19 inpatients. EUROPEAN JOURNAL OF PUBLIC HEALTH, 31, 190. Pasanisi, S., & Paiano, R. (2018). A Hybrid Information Mining Approach for Knowledge Discovery in Cardiovascular Disease (CVD). Information, 9(4), 90. https://doi.org/10.3390/info9040090
Pestana, M., Pereira, R., & Moro, S. (2020). Improving Health Care Management in Hospitals Through a Productivity Dashboard. Journal of Medical Systems, 44(4). https://doi.org/10.1007/s10916-020-01546-1
Rezaei-hachesu, P., Samad-Soltani, T., Yaghoubi, S., GhaziSaeedi, M., Mirnia, K., Masoumi-Asl, H., & Safdari, R. (2018). The design and evaluation of an antimicrobial resistance surveillance system for neonatal intensive care units in Iran. International Journal of Medical Informatics, 115, 24–34. https://doi.org/10.1016/j.ijmedinf.2018.04.007
Schulz, E. B., Phillips, F., & Waterbright, S. (2020). Case-mix adjusted postanaesthesia care unit length of stay and business intelligence dashboards for feedback to anaesthetists. British Journal of Anaesthesia, 125(6), 1079–1087. https://doi.org/10.1016/j.bja.2020.06.068
Silva, R., Parente, M. A., Evaristo, J. L., & Araújo , A. (2022). A Inserção Do Business Intelligence Na Gestão De Custos De Uma Rede De Clínicas Populares De Fortaleza. Administração de Empresas Em Revista, 1(27), 146–174.
Suter-Crazzolara, C. (2018). Better Patient Outcomes Through Mining of Biomedical Big Data. Frontiers in ICT, 5. https://doi.org/10.3389/fict.2018.00030
Teixeira, L., Cardoso, I., Oliveira e Sa, J., & Madeira, F. (2021). Are the Health Information Systems (HIS) ready for the digital transformation? Challenges and future perspectives for HIS in Portugal. AIS Electronic Library (AISeL). https://aisel.aisnet.org/capsi2021/34/
The rise of digital health technologies during the pandemic | Think Tank | European Parliament. (2021, Abril 14). Acedido em Dezembro 18, 2022, https://www.europarl.europa.eu/thinktank/en/document/EPRS_BRI(2021)690548
Torres, D. R., Cardoso, G. C. P., Abreu, D. M. F. D., Soranz, D. R., & Oliveira, E. A. D. (2021). Aplicabilidade e potencialidades no uso de ferramentas de Business Intelligence na Atenção Primária em Saúde. Ciência & Saúde Coletiva, 26(6), 2065–2074. https://doi.org/10.1590/1413-81232021266.03792021
Villar, A., Zarrabeitia, M. T., Fdez-Arroyabe, P., & Santurtún, A. (2018). Integrating and analyzing medical and environmental data using ETL and Business Intelligence tools. International Journal of Biometeorology, 62(6), 1085–1095. https://doi.org/10.1007/s00484-018-1511-9
Downloads
Published
How to Cite
License
Copyright (c) 2022 Filipe Madeira, João Madeira
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors publishing in this journal agree to the following terms:
Authors retain copyright and grant the journal the right of first publication, with the article simultaneously licensed under the Creative Commons Attribution License that allows sharing of the work with acknowledgement of authorship and initial publication in this journal.
Authors are permitted to enter into additional contracts separately for non-exclusive distribution of the version of the article published in this journal (e.g., publish in an institutional repository or as a book chapter), with acknowledgment of authorship and initial publication in this journal.
Authors have permission and are encouraged to publish and distribute their work online (e.g., in institutional repositories or on their personal webpage) at any point before or during the editorial process, as this may generate productive changes, as well as increase the impact and citation of the published work.
