Hemşirelik Bilişim Yetkinliklerinin Klinik Karar Verme Üzerindeki Etkisi: Bir Kamu Hastanesi Örneği

Year 2026, Volume: 11 Issue: 1, 62 - 70, 15.03.2026

Medine Sertkaya , Beratiye Öner

https://doi.org/10.26453/otjhs.1833728

https://izlik.org/JA67FT84SR

Abstract

Amaç: Bu çalışma, bir kamu hastanesinde çalışan hemşireler arasında bilişim yeterlilik düzeylerini ve klinik karar verme yaklaşımlarını incelemeyi ve demografik faktörlerin bu ilişkiyi etkileyip etkilemediğini araştırmayı amaçlamıştır. Materyal ve Metot: Kesitsel ve tanımlayıcı araştırma deseni kullanılmıştır. Veriler, Ocak ve Mart 2025 tarihleri arasında Ankara, Türkiye’de görev yapan 502 hemşireden toplanmıştır. Veriler, “Bilgi Teknolojileri Rehberliğinde Eğitim Reformu (TIGER) Girişimi Tabanlı Hemşirelik Bilişimi Yetkinlikleri Değerlendirme Aracı” ve “Hemşire Karar Verme Ölçeği” ile toplanmıştır. Veriler tanımlayıcı istatistikler, Ki-kare testi, Spearman korelasyonu ve Çoklu Regresyon analizleri değerlendirilmiştir. Bulgular: Katılımcıların yaş ortalaması 30,2 yıl olup, %73,3’ü kadın ve %87,4’ü lisans ve üzeri eğitime sahiptir. Hemşirelerin %64,9’u genel bilişim eğitimi almış, yalnızca %22,3’ü hemşirelik bilişimi üzerine özel eğitim almıştır. Genel olarak, bilişim yetkinliği “yetkin” düzeyde değerlendirilmiştir (X̄=2,37); en yüksek puan temel bilgisayar becerilerinde (2,64), en düşük puan klinik bilgi yönetiminde (2,25) bulunmuştur. Hemşirelerin yaklaşık %90’ı sezgisel karar verme eğilimindedir. Korelasyon analizinde bilişim yetkinlikleri ile karar verme arasında anlamlı ilişkiler bulunmuştur. Regresyon modelinde, temel bilgisayar becerileri (β=0,381) ve klinik bilgi yönetimi (β=0,377) karar verme puanlarını pozitif yönde yordarken, bilgi okuryazarlığı (β=–0,364) karar verme üzerinde negatif bir etki göstermiştir. Sonuç: Bu çalışmada yer alan hemşireler, orta düzeyde bilişim yeterliliğine (TIGER ortalama puanı=2,37) sahip olduklarını, nispeten daha güçlü temel bilgisayar becerilerine sahip olduklarını ancak klinik bilgi yönetimi ve bilgi okuryazarlığı puanlarının daha düşük olduğunu göstermiştir. Hemşire Karar Verme Ölçeği ortalama puanı (91), sezgisel karar vermenin baskın bir şekilde kullanıldığını göstermiştir. Bu bulgular, klinik kararları desteklemek için yapılandırılmış bilişim eğitimine ve kanıta dayalı sistem entegrasyonuna duyulan ihtiyacı vurgulamaktadır.

Keywords

Bilişim yetkinliği , hemşirelik , klinik karar verme , uygulama

Ethical Statement

Lokman Hekim Üniversitesi Bilimsel Araştırma Etik Kurulu'ndan etik onay alınmıştır (Tarih: 29.12.2024, karar no: 2024/277). Hastaneden de kurumsal izin alınmıştır (Tarih: 17.01.2025, karar no: E-97367300-514.01.02-265840504). Çalışma, Helsinki Bildirgesi'nin ilkelerine uygun olarak yürütülmüştür.

Supporting Institution

Araştırma ile ilgili herhangi bir proje ya da fon desteği alınmamıştır.

Project Number

-

Thanks

Tüm katılımcılara teşekkür ederiz.

The Impact of Nursing Informatics Competencies on Clinical Decision-Making: Evidence from a Public Hospital

https://izlik.org/JA67FT84SR

Abstract

Objective: This study aimed to examine the levels of informatics competency and clinical decision-making approaches among nurses working in a public hospital, and to explore whether demographic factors influence this relationship. Materials and Methods: A cross-sectional and descriptive design was employed. Data were collected from 502 nurses in Ankara, Türkiye, between January and March at 2025. Instruments included the “Technology Informatics Guiding Educational Reform (TIGER)-Based Nursing Informatics Competencies Assessment Tool" and the "Nurse Decision-Making Scale." Descriptive statistics, Chi-square tests, Spearman correlations, and Multiple Regression analyses were performed. Results: The mean age of nurses was 30.2 years; 73.3% were female, and 87.4% held at least a bachelor’s degree. While 64.9% had received general informatics training, only 22.3% had specific nursing informatics education. Overall, informatics competency was rated as “competent” (X̄=2.37), with the highest score in basic computer skills (2.64), and the lowest in clinical information management (2.25). Nearly 90% of the nurses exhibited intuitive decision-making tendencies. Correlation analysis revealed significant associations between informatics competencies and decision-making. In the regression model, basic computer skills (β=0.381) and clinical information management (β=0.377) positively predicted decision-making scores, whereas information literacy (β=–0.364) negatively influenced decision-making scores. Conclusion: Nurses in this study demonstrated moderate informatics competency (TIGER mean score=2.37), with relatively stronger basic computer skills but lower scores in clinical information management and information literacy. The mean Nurse Decision-Making Scale score (91) indicated a predominant use of intuitive decision-making. These findings highlight the need for structured informatics education and evidence-based system integration to support clinical decisions.

Keywords

Clinical decision-making , informatics competencies , nursing , practice

Ethical Statement

Ethical approval was obtained from the Lokman Hekim University Scientific Research Ethics Committee (Date: 29.12.2024, decision no: 2024/277). Institutional permission was also obtained from the hospital (Date: 17.01.2025, decision no: E-97367300-514.01.02-265840504). The study complied with the principles of the Declaration of Helsinki.

Supporting Institution

No financial support was received.

Project Number

-

Thanks

Thank you to all the participants.

References

• 1. Elsayed WA, Hussein FM, Othman WN. Relation between nursing informatics competency and nurses’ attitude toward evidence-based practice among qualified nurses at Mansoura Oncology Center. International Journal of Nursing Didactics. 2017;7(6):26-33. doi:10.15520/ijnd.2017.vol7.iss6.229.26-33
• 2. American Nurses Association. Nursing Informatics: Scope and Standards of Practice. 3th ed. Silver Spring, MD; 2022.
• 3. Technology Informatics Guiding Education Reform (TIGER). Informatics Competencies for Every Practicing Nurse: Recommendations From the TIGER Collaborative. Published 2014. https://www.tigersummit.com/uploads/3.Tiger.Report_Competencies_final.pdf Accessed March 12, 2025.
• 4. Hunter KM, McGonigle D, Hebda TL. TIGER-based measurement of nursing informatics competencies: The development and implementation of an online tool for self-assessment. Journal of Nursing Education and Practice. 2013;3(12):70-80. doi:10.5430/jnep.v3n12p70
• 5. Kaynar NS, Secginli S, West K. Psychometric testing of the Turkish version of the Technology Informatics Guiding Educational Reform–based assessment of nursing informatics competencies tool. CIN: Computers, Informatics, Nursing. 2020;38(11):572-578. doi:10.1097/CIN.0000000000000671
• 6. Yılmaz BO, Tozan H, Karadayı MA. Multi-criteria decision making (MCDM) applications in military healthcare field. Journal of Health Systems and Policies. 2020;2(2):149-181.
• 7. Bing‐Jonsson PC, Førsund LH, Hansen Stålesen J, et al. Lifelong learning in community healthcare: Testing competence after learning activities in a blended learning space. Scandinavian Journal of Caring Sciences. 2023;37(4):1057–1066. doi:10.1111/scs.13180
• 8. Quality and Safety Education for Nurses (QSEN). Graduate QSEN competencies. http://qsen.org/competencies/graduate-ksas/ 2022. Accessed April 19, 2025.
• 9. Eppler MJ, Mengis J. The Concept of Information Overload: A Review of Literature from Organization Science, Accounting, Marketing, MIS, and Related Disciplines. The Information Society. 2004;20(5):325–344. doi:10.1080/01972240490507974 Gungor S, Ozcan U. Decision theory and decision-making. European Journal of Science and Technology. 2022;(33):119-125. doi:10.31590/ejosat.1035682
• 10. Demir S, Yılmaz AA. Adaptation of the nursing decision making ınstrument to Turkish: A validity and reliability study. Journal of Health and Nursing Management. 2021;8(3):407-417. doi:10.54304/SHYD.2021.35693
• 11. Cetin S, Aydemir T. Clinical decision making in the light of philosophy and science. Journal of Anatolian Medical Research. 2019;4(3):116-122.
• 12. Chen SL, Hsu HY, Chang CF, Lin ECL. An exploration of the correlates of nurse practitioners’ clinical decision-making abilities. Journal of Clinical Nursing. 2016;25(7-8):1016-1024. doi:10.1111/jocn.13136
• 13. Nibbelink CW, Brewer BB. Decision-making in nursing practice: an integrative literature review. Journal of Clinical Nursing. 2018;27(5-6):917-928. doi:10.1111/jocn.14151
• 14. Ludin SM. Does good critical thinking equal effective decision-making among critical care nurses? A cross-sectional survey. Intensive and Critical Care Nursing. 2018;44:1-10. doi:10.1016/j.iccn.2017.06.002
• 15. Batran A, Al-Humran SM, Malak MZ, Ayed A. The relationship between nursing informatics competency and clinical decision-making among nurses in West Bank, Palestine. CIN: Computers, Informatics, Nursing. 2022;40(8):547-553. doi:10.1097/CIN.0000000000000890
• 16. Hants L, Bail K, Paterson C. Clinical decision-making and the nursing process in digital health systems: an integrated systematic review. Journal of Clinical Nursing. 2023;32(19-20):7010-7035. doi:10.1111/jocn.16823
• 17. Lauri S, Salanterä S. Developing an instrument to measure and describe clinical decision making in different nursing fields. Journal of Professional Nursing. 2002;18(2):93-100. doi:10.1053/jpnu.2002.32344
• 18. Ozbay I. Evaluation of nursing informatics competencies of Nurses. Istanbul University-Cerrahpaşa, Graduate Education Institute, Department of Public Health Nursing, Master Thesis. Istanbul, Turkiye. 2022.
• 19. Cetinkaya E. Nursing informatics competencies of nurse in charge, clinical training nurse and TEAM leaders working in private hospitals. Marmara University, Institute of Health Sciences, Department of Public Health Nursing, Master Thesis. Istanbul, Turkiye. 2023.
• 20. Faydaligul OD, Colakkol A. Information literacy education in nursing students. In: 6th International Symposium on Information Management in an Changing World. November 25-27, 2015, Guangzhou / China.
• 21. Soini UM, Andenæs R, Solberg MT. Oxygen treatment of ventilated critically ill children: nursing assessment and cognitive processes in clinical decision-making. Nordic Journal of Nursing Research. 2020;40(2):81-88. doi:10.1177/2057158519882263
• 22. Al-Qudah MM, Oweidat IA, Omar SA, et al. The relationship between nursing informatics competencies and clinical decision-making among registered nurses working at tertiary hospitals. Digit Health. 2025;11:20552076251346015. doi:10.1177/20552076251346015
• 23. Malik RM, Naveed MA, Rafique GM. Effect of ınformation literacy skills on clinical decision-making among nurses. Journal of Information Management and Practices. 2025;5(1):29–47.
• 24. Yıldız M, Yıldız M, Yıldırım MS, et al. Investigation of the relationship between TIGER-based nursing informatics competencies and digital literacy levels in nurses: Analysis with machine learning approach. Fenerbahce University Journal of Health Sciences. 2023;3(3):372-385. doi:10.56061/fbujohs.1252026
• 25. Rababa M, Al-Rawashdeh S. Critical care nurses' critical thinking and decision making related to pain management. Intensive and Critical Care Nursing. 2021;63:103000. doi:10.1016/j.iccn.2020.103000
• 26. Nair GG, Hellsten LAM, Stamler LL. Accumulation of content validation evidence for the critical thinking self-assessment scale. Journal of Nursing Measurement. 2017;25(1):156-170. doi:10.1891/1061-3749.25.1.156
• 27. Aslan Seki E. Digital skills in the 21st century: Understanding the impact of digital literacy on nurses. Research on Education and Psychology (REP). 2024;8(2):361–371. doi:10.54535/rep.1576624
• 28. Bakken S, Dreisbach C. Informatics and data science perspective on future of nursing 2020–2030: Charting a pathway to health equity. Nursing Outlook. 2022;70(6 Suppl 1):S77 S87. doi:10.1016/j.outlook.2022.04.004
• 29. Benner P. From novice to expert. The American Journal of Nursing. 1982;82(3):402–407. doi:10.2307/3462928