Skip to main content
SpringerLink
Log in

Development and Usability Assessment of a Semantically Validated Guideline-Based Patient-Oriented Gestational Diabetes Mobile App

  • Conference paper
  • First Online:
Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1297))

  • 395 Accesses

Abstract

Studies have shown the benefits of following Clinical Practice Guidelines (CPGs) in the daily practice of medicine. Nevertheless, the lack of digitalization of these guidelines makes their update and reliability to be a challenge. With the aim of overcoming these issues, Computer Interpretable Guidelines (CIGs) have been promoted to use in Clinical Decision Support Systems (CDSS). Moreover, the implementation of Semantic Web Technologies (SWTs) to formalize the guideline concepts is a powerful method to promote the standardization and interoperability of these systems. In this paper, the architecture of a CIG-based and semantically validated mobile CDSS is introduced. For that, the development of a patient-oriented mobile application for the management of gestational diabetes is described, and the design and results of its usability assessment are presented. This validation was carried out following the System Usability Scale (SUS) with some additional measurements, and results showed excellent usability scores.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.snomed.org/snomed-ct/five-step-briefing

  2. 2.

    https://loinc.org/

  3. 3.

    https://ncithesaurus-stage.nci.nih.gov/ncitbrowser/

  4. 4.

    https://eciemaps.mscbs.gob.es/

  5. 5.

    https://www.nlm.nih.gov/research/umls/

  6. 6.

    https://protegewiki.stanford.edu/wiki/ProtegeOWL_API

  7. 7.

    https://github.com/owlcs/owlapi/wiki

  8. 8.

    https://jena.apache.org/documentation/ontology/

  9. 9.

    http://rdf4j.org/

  10. 10.

    https://www.drools.org/

References

  1. Grimshaw, J.M., Russell, I.T.: Effect of clinical guidelines on medical practice: a systematic review of rigorous evaluations. The Lancet 342, 1317–1322 (1993). https://doi.org/10.1016/0140-6736(93)92244-N

    Article  Google Scholar 

  2. Latoszek-Berendsen, A., Tange, H., van den Herik, H.J., Hasman, A.: From clinical practice guidelines to computer-interpretable guidelines. A literature overview. Meth. Inf. Med. 49, 550–570 (2010). https://doi.org/10.3414/ME10-01-0056

    Article  Google Scholar 

  3. Artola, G., Torres, J., Larburu, N., Álvarez, R., Muro, N.: Development of a gestational diabetes computer interpretable guideline using semantic web technologies. In: Presented at the 11th International Conference on Knowledge Engineering and Ontology Development (2019). https://doi.org/10.5220/0008068001040114

  4. Kolias, V.D., Stoitsis, J., Golemati, S., Nikita, K.S.: Utilizing semantic web technologies in healthcare. In: Koutsouris, D.-D., Lazakidou, A.A. (eds.) Concepts and Trends in Healthcare Information Systems. AIS, vol. 16, pp. 9–19. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-06844-2_2

    Chapter  Google Scholar 

  5. Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Sci. Am. 1–5 (2001)

    Google Scholar 

  6. Sabou, M.: An introduction to semantic web technologies. Concepts and Trends in Healthcare Information Systems. AIS, vol. 16, pp. 53–81. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-41490-4_3

    Chapter  Google Scholar 

  7. Gruber, T.: A Translation Approach to Portable Ontology Specifications. Academic Press, New York (1993)

    Google Scholar 

  8. El-Sappagh, S., Kwak, D., Ali, F., Kwak, K.-S.: DMTO: a realistic ontology for standard diabetes mellitus treatment. J. Biomed. Semant. 9, 8 (2018). https://doi.org/10.1186/s13326-018-0176-y

    Article  Google Scholar 

  9. Musen, M.A.: The protégé project: a look back and a look forward. AI Matters. 1, 4–12 (2015). https://doi.org/10.1145/2757001.2757003

    Article  Google Scholar 

  10. Noy, N.F., McGuinness, D.L.: Ontology Development: A Guide to Creating Your First Ontology, vol. 25, March 2001

    Google Scholar 

  11. Kredo, T., Bernhardsson, S., Machingaidze, S., Young, T., Louw, Q., Ochodo, E., Grimmer, K.: Guide to clinical practice guidelines: the current state of play. Int. J. Qual. Health Care 28, 122–128 (2016). https://doi.org/10.1093/intqhc/mzv115

    Article  Google Scholar 

  12. Hu, S., Kirsner, R.S., Falanga, V., Phillips, T., Eaglstein, W.H.: Evaluation of Apligraf persistence and basement membrane restoration in donor site wounds: a pilot study. Wound Repair Regen. Off. Publ. Wound Heal. Soc. Eur. Tissue Repair Soc. 14, 427–433 (2006). https://doi.org/10.1111/j.1743-6109.2006.00148.x

  13. Huang, Z., ten Teije, A., van Harmelen, F., Aït-Mokhtar, S.: Semantic representation of evidence-based clinical guidelines. In: Miksch, S., Riaño, D., ten Teije, A. (eds.) KR4HC 2014. LNCS (LNAI), vol. 8903, pp. 78–94. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-13281-5_6

    Chapter  Google Scholar 

  14. Peleg, M., et al.: Comparing computer-interpretable guideline models: a case-study approach. J. Am. Med. Inform. Assoc. 10, 52–68 (2003). https://doi.org/10.1197/jamia.M1135

    Article  Google Scholar 

  15. Patel, V.L., Allen, V.G., Arocha, J.F., Shortliffe, E.H.: Representing clinical guidelines in GLIF. J. Am. Med. Inform. Assoc. JAMIA. 5, 467–483 (1998)

    Article  Google Scholar 

  16. Sutton, D.R., Fox, J.: The syntax and semantics of the PROforma guideline modeling language. J. Am. Med. Inform. Assoc. 10, 433–443 (2003). https://doi.org/10.1197/jamia.M1264

    Article  Google Scholar 

  17. Seyfang, A., Miksch, S., Marcos, M.: Combining diagnosis and treatment using asbru. Int. J. Med. Inf. 68, 49–57 (2002). https://doi.org/10.1016/S1386-5056(02)00064-3

    Article  Google Scholar 

  18. Tu, S.W., Musen, M.A.: Modeling data and knowledge in the EON guideline architecture. Stud. Health Technol. Inform. 84, 280–284 (2001)

    Google Scholar 

  19. Isern, D., Sánchez, D., Moreno, A.: Ontology-driven execution of clinical guidelines. Comput. Meth. Prog. Biomed. 107, 122–139 (2012). https://doi.org/10.1016/j.cmpb.2011.06.006

    Article  Google Scholar 

  20. Eccher, C., Seyfang, A., Ferro, A.: Implementation and evaluation of an Asbru-based decision support system for adjuvant treatment in breast cancer. Comput. Meth. Progr. Biomed. 117, 308–321 (2014). https://doi.org/10.1016/j.cmpb.2014.06.021

    Article  Google Scholar 

  21. Peleg, M., et al.: A computer-interpretable version of the AACE, AME, ETA medical guidelines for clinical practice for the diagnosis and management of thyroid nodules. Endocr. Pract. 20, 352–359 (2013). https://doi.org/10.4158/EP13271.OR

    Article  Google Scholar 

  22. Galopin, A., Bouaud, J., Pereira, S., Seroussi, B.: An ontology-based clinical decision support system for the management of patients with multiple chronic disorders. Stud. Health Technol. Inform. 216, 275–279 (2015)

    Google Scholar 

  23. Riaño, D., et al.: An ontology-based personalization of health-care knowledge to support clinical decisions for chronically ill patients. J. Biomed. Inform. 45, 429–446 (2012). https://doi.org/10.1016/j.jbi.2011.12.008

    Article  Google Scholar 

  24. Garg, A.X., et al.: Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 293, 1223–1238 (2005). https://doi.org/10.1001/jama.293.10.1223

    Article  Google Scholar 

  25. Peleg, M., et al.: MobiGuide: a personalized and patient-centric decision-support system and its evaluation in the atrial fibrillation and gestational diabetes domains. User Model. User-Adapted Interact. 27(2), 159–213 (2017). https://doi.org/10.1007/s11257-017-9190-5

    Article  Google Scholar 

  26. Miremberg, H., et al.: The impact of a daily smartphone-based feedback system among women with gestational diabetes on compliance, glycemic control, satisfaction, and pregnancy outcome: a randomized controlled trial. Am. J. Obstet. Gynecol. 218(453), e1–453.e7 (2018). https://doi.org/10.1016/j.ajog.2018.01.044

    Article  Google Scholar 

  27. Rehalia, A., Prasad, S.: Global harnessing of advanced mHealth for community mobilization. mHealth 2 (2016). https://doi.org/10.21037/mhealth.2016.03.02

  28. McKay, F.H., Cheng, C., Wright, A., Shill, J., Stephens, H., Uccellini, M.: Evaluating mobile phone applications for health behaviour change: A systematic review. J. Telemed. Telecare. 24, 22–30 (2018). https://doi.org/10.1177/1357633X16673538

    Article  Google Scholar 

  29. Boudreaux, E.D., Waring, M.E., Hayes, R.B., Sadasivam, R.S., Mullen, S., Pagoto, S.: Evaluating and selecting mobile health apps: strategies for healthcare providers and healthcare organizations. Transl. Behav. Med. 4(4), 363–371 (2014). https://doi.org/10.1007/s13142-014-0293-9

    Article  Google Scholar 

  30. Parmanto, B., Pramana, G., Yu, D.X., Fairman, A.D., Dicianno, B.E., McCue, M.P.: iMHere: a novel mHealth system for supporting self-care in management of complex and chronic conditions. JMIR MHealth UHealth. 1 (2013). https://doi.org/10.2196/mhealth.2391

  31. Seto, E., Leonard, K.J., Cafazzo, J.A., Barnsley, J., Masino, C., Ross, H.J.: Mobile phone-based telemonitoring for heart failure management: a randomized controlled trial. J. Med. Internet Res. 14 (2012). https://doi.org/10.2196/jmir.1909

  32. Seto, E., Leonard, K.J., Cafazzo, J.A., Barnsley, J., Masino, C., Ross, H.J.: Perceptions and experiences of heart failure patients and clinicians on the use of mobile phone-based telemonitoring. J. Med. Internet Res. 14 (2012). https://doi.org/10.2196/jmir.1912

  33. Fairman, A.D., Dicianno, B.E., Datt, N., Garver, A., Parmanto, B., McCue, M.: Outcomes of clinicians, caregivers, family members and adults with spina bifida regarding receptivity to use of the iMHere mHealth solution to promote wellness. Int. J. Telerehabilitation. 5, 3–16 (2013). https://doi.org/10.5195/ijt.2013.6116

    Article  Google Scholar 

  34. Boceta, J., Samper, D., de la Torre, A., Sánchez-de la Rosa, R., González, G.: Usability, acceptability, and usefulness of an mHealth app for diagnosing and monitoring patients with breakthrough cancer pain. JMIR Cancer 5 (2019). https://doi.org/10.2196/10187

  35. Zhou, L., Bao, J., Setiawan, I.M.A., Saptono, A., Parmanto, B.: The mHealth app usability questionnaire (MAUQ): development and validation study. JMIR MHealth UHealth 7 (2019). https://doi.org/10.2196/11500

  36. Brooke, J.: SUS: A “Quick and Dirty” Usability Scale. https://www.taylorfrancis.com/. Accessed 22 Jan 2020. https://doi.org/10.1201/9781498710411-35

  37. PSSUQ (Post-Study System Usability Questionnaire). https://uiuxtrend.com/pssuq-post-study-system-usability-questionnaire/. Accessed 22 Jan 2020

  38. American Diabetes Association: Classification and Diagnosis of Diabetes|Diabetes Care. https://doi.org/10.2337/dc16-S005

  39. Bellamy, L., Casas, J.-P., Hingorani, A.D., Williams, D.: Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. The Lancet 373, 1773–1779 (2009). https://doi.org/10.1016/S0140-6736(09)60731-5

    Article  Google Scholar 

  40. Chiefari, E., Arcidiacono, B., Foti, D., Brunetti, A.: Gestational diabetes mellitus: an updated overview. J. Endocrinol. Investigat. 40(9), 899–909 (2017). https://doi.org/10.1007/s40618-016-0607-5

    Article  Google Scholar 

  41. Queensland Gobernment: Guideline: Gestational diabetes mellitus, vol. 38, August 2015

    Google Scholar 

  42. Muro, N., et al.: Architecture for a multimodal and domain-independent clinical decision support system software development kit. In: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1399–1404 (2019). https://doi.org/10.1109/EMBC.2019.8856459

  43. Lewis, J.R., Sauro, J.: The factor structure of the system usability scale. In: Kurosu, M. (ed.) HCD 2009. LNCS, vol. 5619, pp. 94–103. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02806-9_12

    Chapter  Google Scholar 

  44. Tullis, T., Albert, B.: Chapter 6 - Self-reported metrics. In: Tullis, T., Albert, B. (eds.) Measuring the User Experience (Second Edition). pp. 121–161. Morgan Kaufmann, Boston (2013). https://doi.org/10.1016/B978-0-12-415781-1.00006-6

  45. Reichheld, F.: The Ultimate Question, with Fred Reichheld (2006). https://www.marketingprofs.com/marketing/online-seminars/71

Download references

Acknowledgments

This work has been developed under the research project DMG360 (2017-2018/Exp. number ZE-2017/00011, in collaboration with INIT Health, SL), which has been funded by the Department of Economic Development and Infrastructure of the Basque Government under the Hazitek program.

Author information

Authors and Affiliations

  1. Vicomtech Research Centre, Mikeletegi Pasalekua 57, 20009, San Sebastian, Spain

    Garazi Artola, Jordi Torres, Nekane Larburu, Roberto Álvarez & Naiara Muro

  2. Biodonostia Health Research Institute, P. Doctor Begiristain S/N, 20014, San Sebastian, Spain

    Nekane Larburu, Roberto Álvarez & Naiara Muro

Authors
  1. Garazi Artola
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jordi Torres
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nekane Larburu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Roberto Álvarez
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Naiara Muro
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Garazi Artola , Jordi Torres , Nekane Larburu , Roberto Álvarez or Naiara Muro .

Editor information

Editors and Affiliations

  1. Instituto de Telecomunicações, Lisbon, Portugal

    Ana Fred

  2. Federal University of Pernambuco, Recife, Brazil

    Ana Salgado

  3. University of Madeira, Funchal, Portugal

    David Aveiro

  4. Delft University of Technology, Delft, The Netherlands

    Jan Dietz

  5. Polytechnic Institute of Coimbra, Coimbra, Portugal

    Jorge Bernardino

  6. Polytechnic Institute of Setúbal, Setúbal, Portugal

    Joaquim Filipe

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Artola, G., Torres, J., Larburu, N., Álvarez, R., Muro, N. (2020). Development and Usability Assessment of a Semantically Validated Guideline-Based Patient-Oriented Gestational Diabetes Mobile App. In: Fred, A., Salgado, A., Aveiro, D., Dietz, J., Bernardino, J., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2019. Communications in Computer and Information Science, vol 1297. Springer, Cham. https://doi.org/10.1007/978-3-030-66196-0_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-66196-0_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-66195-3

  • Online ISBN: 978-3-030-66196-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation