CC BY 4.0 · Appl Clin Inform 2023; 14(01): 016-027
DOI: 10.1055/s-0042-1760081
Research Article

Ten Years of Medical Informatics and Standards Support for Clinical Research in an Infectious Diseases Network

Sara Mora
1   Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Genoa, Italy
,
Barbara Giannini
1   Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Genoa, Italy
,
Antonio Di Biagio
2   Infectious Diseases Unit, Policlinico San Martino Hospital, IRCCS for Oncology and Neuroscience, Genoa, Italy
3   Department of Infectious Disease, IRCCS AOU San Martino IST, (DISSAL), University of Genoa, Italy
,
Giovanni Cenderello
4   Infectious Diseases Unit, ASL-1 Imperiese, Sanremo, Imperia, Italy
,
Laura Ambra Nicolini
2   Infectious Diseases Unit, Policlinico San Martino Hospital, IRCCS for Oncology and Neuroscience, Genoa, Italy
,
Lucia Taramasso
2   Infectious Diseases Unit, Policlinico San Martino Hospital, IRCCS for Oncology and Neuroscience, Genoa, Italy
,
Chiara Dentone
2   Infectious Diseases Unit, Policlinico San Martino Hospital, IRCCS for Oncology and Neuroscience, Genoa, Italy
,
Matteo Bassetti
2   Infectious Diseases Unit, Policlinico San Martino Hospital, IRCCS for Oncology and Neuroscience, Genoa, Italy
3   Department of Infectious Disease, IRCCS AOU San Martino IST, (DISSAL), University of Genoa, Italy
,
Mauro Giacomini
1   Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Genoa, Italy
› Author Affiliations

Abstract

Background It is 30 years since evidence-based medicine became a great support for individual clinical expertise in daily practice and scientific research. Electronic systems can be used to achieve the goal of collecting data from heterogeneous datasets and to support multicenter clinical trials. The Ligurian Infectious Diseases Network (LIDN) is a web-based platform for data collection and reuse originating from a regional effort and involving many professionals from different fields.

Objectives The objective of this work is to present an integrated system of ad hoc interfaces and tools that we use to perform pseudonymous clinical data collection, both manually and automatically, to support clinical trials.

Methods The project comprehends different scenarios of data collection systems, according to the degree of information technology of the involved centers. To be compliant with national regulations, the last developed connection is based on the standard Clinical Document Architecture Release 2 by Health Level 7 guidelines, interoperability is supported by the involvement of a terminology service.

Results Since 2011, the LIDN platform has involved more than 8,000 patients from eight different hospitals, treated or under treatment for at least one infectious disease among human immunodeficiency virus (HIV), hepatitis C virus, severe acute respiratory syndrome coronavirus 2, and tuberculosis. Since 2013, systems for the automatic transfer of laboratory data have been updating patients' information for three centers, daily. Direct communication was set up between the LIDN architecture and three of the main national cohorts of HIV-infected patients.

Conclusion The LIDN was originally developed to support clinicians involved in the project in the management of data from HIV-infected patients through a web-based tool that could be easily used in primary-care units. Then, the developed system grew modularly to respond to the specific needs that arose over a time span of more than 10 years.

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by the Ligurian Institutional Review Board.




Publication History

Received: 11 May 2022

Accepted: 16 November 2022

Article published online:
11 January 2023

© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 
  • References

  • 1 Sackett DL. Evidence-based medicine. In: Seminars in Perinatology. Vol 21. The Netherlands: Elsevier; 1997: 3-5
  • 2 Fahey T, Griffiths S, Peters TJ. Evidence based purchasing: understanding results of clinical trials and systematic reviews. BMJ 1995;311(7012):1056–1059, discussion 1059–1060
  • 3 Kush RD, Warzel D, Kush MA. et al. FAIR data sharing: the roles of common data elements and harmonization. J Biomed Inform 2020; 107: 103421
  • 4 Giacomini M, Pastorino L, Soumetz FC. et al. Data modeling for tools and technologies for the analysis and synthesis of NANOstructures (TASNANO) Project. J Inf Technol Res 2009; 2 (03) 49-70
  • 5 Liu T, Lin Y, Wen X, Jorissen RN, Gilson MK. BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res 2007; 35 (Database issue): D198-D201
  • 6 Patel S, Lyons-Weiler J. caGEDA: a web application for the integrated analysis of global gene expression patterns in cancer. Appl Bioinformatics 2004; 3 (01) 49-62
  • 7 Izzo M, Mortola F, Arnulfo G, Fato MM, Varesio L. A digital repository with an extensible data model for biobanking and genomic analysis management. BMC Genomics 2014; 15 (03) 1-15
  • 8 Corradi L, Porro I, Schenone A. et al. A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience. BMC Med Inform Decis Mak 2012; 12 (01) 115
  • 9 El Emam K, Jonker E, Sampson M, Krleza-Jerić K, Neisa A. The use of electronic data capture tools in clinical trials: web-survey of 259 Canadian trials. J Med Internet Res 2009; 11 (01) e8
  • 10 Fenstermacher D, Street C, McSherry T, Nayak V, Overby C, Feldman M. The cancer biomedical informatics grid (caBIG TM). In: 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE; 2006:743–746
  • 11 Demotes-Mainard J, Kubiak C. A European perspective—the European clinical research infrastructures network. Ann Oncol 2011; 22 (Suppl. 07) vii44-vii49
  • 12 Dagliati A, Sacchi L, Bucalo M. et al. A data gathering framework to collect type 2 diabetes patients data. In: IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI). IEEE; 2014:244–247
  • 13 Crosswell LC, Thornton JM. ELIXIR: a distributed infrastructure for European biological data. Trends Biotechnol 2012; 30 (05) 241-242
  • 14 Gencturk M, Teoman A, Alvarez-Romero C. et al. End user evaluation of the FAIR4Health data curation tool. Stud Health Technol Inform 2021; 281: 8-12
  • 15 Giannini B, Riccardi N, Cenderello G, Di Biagio A, Dentone C, Giacomini M. From Liguria HIV web to Liguria infectious diseases network: how a digital platform improved doctors' work and patients' care. AIDS Res Hum Retroviruses 2018; 34 (03) 239-240
  • 16 Fraccaro P, Pupella V, Gazzarata R. et al. The Ligurian human immunodeficiency virus clinical network: a web tool to manage patients with human immunodeficiency virus in primary care and multicenter clinical trials. Med 2 0 2013; 2 (02) e5
  • 17 Rusconi S, Vitiello P, Adorni F. et al. Maraviroc as intensification strategy in HIV-1 positive patients with deficient immunological response: an Italian randomized clinical trial. PLoS One 2013; 8 (11) e80157
  • 18 Fraccaro P, Pupella V, Gazzarata R, Giacomini M. Reuse of clinical information: integrating primary care and clinical research through a bidirectional standard interface. In: IFMBE Proceedings. Vol 41. Springer Verlag; 2014:1274–1277
  • 19 Hammond KW, Helbig ST, Benson CC, Brathwaite-Sketoe BM. Are electronic medical records trustworthy? Observations on copying, pasting and duplication. AMIA Annu Symp Proc 2003; 2003: 269-273
  • 20 Kozak M, Krzanowski W, Cichocka I, Hartley J. The effects of data input errors on subsequent statistical inference. J Appl Stat 2015; 42 (09) 2030-2037
  • 21 Lai KH, Topaz M, Goss FR, Zhou L. Automated misspelling detection and correction in clinical free-text records. J Biomed Inform 2015; 55: 188-195
  • 22 ARCA (Antiretroviral Resistance Cohort Analysis). Accessed December 15, 2022 at: https://www.fondazioneicona.org/
  • 23 Fondazione ICONA Italian Cohort Naive Antiretrovirals.
  • 24 CISAI Coordinamento Italiano Studio Allergie e Infezioni da HIV. Accessed December 15, 2022 at: https://www.cisai.it/
  • 25 Cong G, Fan W, Geerts F, Jia X, Ma S. Improving data quality: consistency and accuracy. In: Proceedings of the 33rd International Conference on Very Large Data Bases, Vol. 7. Austria: University of Vienna; 2007: 315-326
  • 26 Mora S, Giacobbe DR, Russo C. et al. A wide database for future studies aimed at improving early recognition of Candidemia. Stud Health Technol Inform 2021; 281: 1081-1082
  • 27 Gazzarata R, Giannini B, Giacomini M. A SOA-based platform to support clinical data sharing. J Healthc Eng 2017; DOI: 10.1155/2017/2190679.
  • 28 Gazzarata R, Vergari F, Cinotti TS, Giacomini M. A standardized SOA for clinical data interchange in a cardiac telemonitoring environment. IEEE J Biomed Health Inform 2014; 18 (06) 1764-1774
  • 29 Bonetto M, Nicolo M, Gazzarata R. et al. I-Maculaweb: a tool to support data reuse in ophthalmology. IEEE J Transl Eng Health Med 2016; 4: 1-10
  • 30 General Regulation on Data Protection. Published 2016. Accessed December 5, 2022 at: https://www.garanteprivacy.it/web/guest/home/docweb/-/docweb-display/docweb/6264597
  • 31 Matsumura Y, Hattori A, Manabe S. et al. Interconnection of electronic medical record with clinical data management system by CDISC ODM. Stud Health Technol Inform 2014; 205: 868-872
  • 32 Lazarova E, Mora S, Maggi N. et al. An interoperable electronic health record system for clinical cardiology. Informatics (MDPI) 2022; 9 (02) 47
  • 33 President of the council of Ministers. Regulation on Electronic Health Records. Published 2015. Accessed December 05, 2022 at: https://www.agid.gov.it/sites/default/files/repository_files/linee_guida/dpcm_178_2015.pdf
  • 34 Gazzarata R, Eugenia Monteverde M, Vio E. et al. A terminology service compliant to CTS2 to manage semantics within the regional HIE. Eur J Biomed Inform (Praha) 2017; 13 (01) 43-50
  • 35 Iannacchero R, Mastrandrea C, Conforti D. Digital health and clinical decision support: the HealthSOAF project and the Calabria Headache Network. Confinia Cephalalgica 2018; 28: 25-31
  • 36 Ciampi M, Marangio F, Schmid G, Desira M, Esposito A, Sicuranza M. A Blockchain architecture for the Italian EHR system proof-of-familiarity: a privacy-preserved blockchain scheme for collaborative medical decision MD Mehedi Hassan Onik Dwarna: a blockchain solution for dynamic consent in biobanking A Blockchain Architecture for the Italian EHR System
  • 37 Ameri M, Cassola G, Cenderello G. et al. Quality of life among HIV patients: results from the Ianua Clinical Trial. Value Heal J Int Soc Pharmacoeconomics Outcomes Res 2015; 18 (07) A592
  • 38 Giannini B, Gazzarata R, Orcamo P. et al. IANUA: a regional project for the determination of costs in HIV-infected patients. Stud Health Technol Inform 2015; 210: 241-245
  • 39 Venturini A, Giannini B, Montefiori M. et al. Quality of life of people living with HIV, preliminary results from IANUA (Investigation on Antiretroviral Therapy) study. J Int AIDS Soc 2014; 17 (4, suppl 3): 19581
  • 40 Pupella V, Gazzarata R, Macrì M. et al. A tool for the evaluation of the cost effectiveness of AIDS therapies. In: IV Congresso Nazionale di Bioingegneria–GNB; 2014:2
  • 41 Mora S, Venturini A, Cenderello G, Fiorellino D, Pilotto A, Giacomini M. A web-based tool for a complete evaluation of fragility in senior HIV+ patients. Stud Health Technol Inform 2019; 261: 299-302
  • 42 Cenderello G, Artioli S, Viscoli C. et al. Budget impact analysis of sofosbuvir-based regimens for the treatment of HIV/HCV-coinfected patients in northern Italy: a multicenter regional simulation. Clinicoecon Outcomes Res 2015; 8: 15-21
  • 43 Taramasso L, Di Biagio A, Riccardi N. et al. Lipid profile changings after switching from rilpivirine/tenofovir disoproxil fumarate/emtricitabine to rilpivirine/tenofovir alafenamide/emtricitabine: different effects in patients with or without baseline hypercholesterolemia. PLoS One 2019; 14 (10) e0223181
  • 44 PNRR - Salute. Accessed December 5, 2022 at: https://www.pnrr.salute.gov.it/portale/pnrrsalute/dettaglioContenutiPNRRSalute.jsp?lingua=italiano&id=5879&area=PNRR-Salute&menu=investimenti
  • 45 Garcia KKS, Abrahão AA. Research development using REDCap software. Healthc Inform Res 2021; 27 (04) 341-349
  • 46 Blumenberg C, Barros AJD. Electronic data collection in epidemiological research. The use of REDCap in the Pelotas birth cohorts. Appl Clin Inform 2016; 7 (03) 672-681
  • 47 Zhang H, Dimitrov D, Simpson L. et al. A web-based, mobile-responsive application to screen health care workers for COVID-19 symptoms: rapid design, deployment, and usage. JMIR Form Res 2020; 4 (10) e19533
  • 48 Murphy SN, Mendis M, Hackett K. et al. Architecture of the open-source clinical research chart from Informatics for Integrating Biology and the Bedside. AMIA Annu Symp Proc 2007; 2007: 548-552
  • 49 Klann JG, Abend A, Raghavan VA, Mandl KD, Murphy SN. Data interchange using i2b2. J Amer Med Inform Assoc 2016; 23 (05) 909-915
  • 50 Abend A, Housman D, Johnson B. Integrating clinical data into the i2b2 repository. Summit On Translat Bioinforma 2009; 2009: 1-5
  • 51 Maier C, Christoph J, Schmidt D. et al. Experiences of transforming a complex nephrologic care and research database into i2b2 using the IDRT tools. J Healthc Eng 2019; 2019: 5640685
  • 52 Ganslandt T, Mate S, Helbing K, Sax U, Prokosch HU. Unlocking data for clinical research—the German i2b2 experience. Appl Clin Inform 2011; 2 (01) 116-127
  • 53 Mora S, Attene J, Gazzarata R. et al. A NLP pipeline for the automatic extraction of a complete microorganism's picture from microbiological notes. J Pers Med 2022; 12 (09) 1424
  • 54 Giannini B, Gazzarata R, Sticchi L, Giacomini M. A SOA-based solution to monitor vaccination coverage among HIV-infected patients in Liguria. Stud Health Technol Inform 2016; 228: 327-331
  • 55 Giannini B, Riccardi N, Di Biagio A, Cenderello G, Giacomini M. A web based tool to enhance monitoring and retention in care for tuberculosis affected patients. Stud Health Technol Inform 2017; 237: 204-208
  • 56 Nagy M, Radakovich N, Nazha A. Machine learning in oncology: what should clinicians know?. JCO Clin Cancer Inform 2020; 4: 799-810
  • 57 Peiffer-Smadja N, Rawson TM, Ahmad R. et al. Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Clin Microbiol Infect 2020; 26 (05) 584-595
  • 58 Fraccaro P, Nicolo M, Bonetto M. et al. Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach. BMC Ophthalmol 2015; 15 (01) 10