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The Role of Digital Health and Health Data in Providing Contemporary Healthcare
Study Course Description
Course Description Statuss:Approved
Course Description Version:1.00
Study Course Accepted:04.03.2024 11:36:14
Study Course Information | |||||||||
Course Code: | ISK_231 | LQF level: | All Levels | ||||||
Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
Branch of Science: | Computer sciences and informatics | Target Audience: | Medicine; Pharmacy; Medical Services; Health Management; Public Health | ||||||
Study Course Supervisor | |||||||||
Course Supervisor: | Ieva Bikava | ||||||||
Study Course Implementer | |||||||||
Structural Unit: | Department of Internal Diseases | ||||||||
The Head of Structural Unit: | |||||||||
Contacts: | Riga, 2 Hipokrata Street, iskrsu[pnkts]lv, +371 67042338 | ||||||||
Study Course Planning | |||||||||
Full-Time - Semester No.1 | |||||||||
Lectures (count) | 3 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 6 | ||||
Classes (count) | 4 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 8 | ||||
Total Contact Hours | 14 | ||||||||
Full-Time - Semester No.2 | |||||||||
Lectures (count) | 3 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 6 | ||||
Classes (count) | 4 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 8 | ||||
Total Contact Hours | 14 | ||||||||
Study course description | |||||||||
Preliminary Knowledge: | Not required. | ||||||||
Objective: | Provide insights into the wide range of Digital health tools, raise awareness of the role of health data in the provision and planning of comprehensive healthcare services, describe commonly used standards for data coding and data exchange, analyze commonly used information systems and various health registries. | ||||||||
Topic Layout (Full-Time) | |||||||||
No. | Topic | Type of Implementation | Number | Venue | |||||
1 | The role of health data in comprehensive healthcare. | Lectures | 1.00 | auditorium | |||||
Classes | 1.00 | auditorium | |||||||
2 | Overview of Digital Health. | Lectures | 1.00 | auditorium | |||||
Classes | 1.00 | auditorium | |||||||
3 | Health data systems and data sharing - EMR/EHR/PHR. | Lectures | 1.00 | auditorium | |||||
Classes | 1.00 | auditorium | |||||||
4 | Final seminar of the first part | Classes | 1.00 | auditorium | |||||
5 | Commonly used data coding and exchange standards - ICD-10/11; LOINC; ORPHA; NOMESCO; SNOMED-CT; HL7 CDA/FHIR. | Lectures | 1.00 | auditorium | |||||
Classes | 1.00 | auditorium | |||||||
6 | Health data in various registers - epidemiological/ statistical, disease, clinical, and patient registers. | Lectures | 1.00 | auditorium | |||||
Classes | 1.00 | auditorium | |||||||
7 | The benefits and challenges of digital health - data security and privacy, secondary use of data, development of innovations. | Lectures | 1.00 | auditorium | |||||
Classes | 1.00 | auditorium | |||||||
8 | Final seminar of the second part | Classes | 1.00 | auditorium | |||||
Assessment | |||||||||
Unaided Work: | - Acquisition of materials placed in e-studies (video lectures, articles, publications, databases). - Execution and submission of tests. In order to evaluate the quality of the study course as a whole, the student must fill out the study course evaluation questionnaire on the Student Portal. | ||||||||
Assessment Criteria: | - The assessment of the study course consists of the total assessment for the acquisition of each topic (maximum 1 points for each topic, summed up - 6 points). - Theoretical knowledge exam - in the form of a test (maximum 3 points). - Student's participation in the study process - active participation in discussions (maximum 1 point, in total for the entire study course). | ||||||||
Final Examination (Full-Time): | Exam | ||||||||
Final Examination (Part-Time): | |||||||||
Learning Outcomes | |||||||||
Knowledge: | - Characterize the role of health data in the health service delivery and planning process of modern healthcare; - Describe, classify and discuss various digital health tools, describe their application in various processes in the field of health; - Identify and classify commonly used information systems in health care, registers and explain their goals and objectives; - Recognise, name, and provide an overview of the most commonly used data coding and exchange standards in digital health; - Explain the challenges related to digital health data security, privacy, secondary data use, and the evolution of invocations. | ||||||||
Skills: | - Analyse and research, discuss and debate on various digital health tools and their applications to improve healthcare processes; - Distinguish the functionality of different information systems and registers, explain differences and the suitability of each solution for certain tasks; - Classify different standards used in digital health, discuss their use in a particular solution; - Assess data security and privacy challenges related to digital health, identify and justify selected risk mitigation measures. | ||||||||
Competencies: | - Recommend how to improve healthcare processes and facilitate access to services by introducing new digital health tools and approaches, as well as by improving or creating new information systems and registries; - To study, analyse and evaluate the challenges related to the changes, related to both - data security and privacy, as well as changes in existing processes and practices; - Evaluate, explain and justify the usable semantic and technical standards related to the changes to ensure interoperability with other systems. | ||||||||
Bibliography | |||||||||
No. | Reference | ||||||||
Required Reading | |||||||||
1 | Pacientu tiesību likums | ||||||||
2 | Ārstniecības likums | ||||||||
3 | Fizisko personu datu apstrādes likums | ||||||||
4 | Fizisko personu datu aizsardzības regula | ||||||||
5 | Butcher C., Hussain, W. Digital healthcare: the future. July, 2022. DOI: https://doi.org/10.7861/fhj.2022-0046 | ||||||||
6 | Sarwal D, Gupta V. (2023). Personal Health Record. NCBI Bookshelf. StatPearls Publishing. | ||||||||
7 | SOAP notes in Medical Record: Subjective, Objective, Assessment, Plan. ZeeMedicalBilling. | ||||||||
8 | Honavar SG. (2020). Electronic Medical Records - The good, the bad and the ugly. | ||||||||
9 | Evans RS. (2016). Electronic Health Records: Then, Now and in the Future. | ||||||||
10 | Baashar Y., et all. (2020). Customer relationship management systems (CRMS) in the healthcare environment: A systematic literature review. https://doi.org/10.1016/j.csi.2020.103442 | ||||||||
11 | Agency for Healthcare Research and Quality. Registries for Evaluating Patient Outcomes: A User’s Guide. (2020). 4th Edition. | ||||||||
12 | Eiropas komisija. Eiropas sadarbspējas satvars – Īstenošanas stratēģija. (2017). | ||||||||
13 | SNOMED CT Starter Guide. | ||||||||
Additional Reading | |||||||||
1 | Digitālās veselības stratēģija līdz 2029.gadam. Informatīvais ziņojums | ||||||||
2 | Delshad, S., Dontaraju, V. S., & Chengat, V. (2021). Artificial Intelligence-based application provides accurate medical triage advice when compared to consensus decisions of healthcare providers. Cureus. https://doi.org/10.7759/cureus.16956 | ||||||||
3 | Kourtis, L. C., Regele, O. B., Wright, J. M., & Jones, G. B. (2019). Digital biomarkers for alzheimer’s disease: The mobile/wearable devices opportunity. Npj Digital Medicine, 2(1). https://doi.org/10.1038/s41746-019-0084-2 | ||||||||
4 | MacIntyre, C. Raina, Lim, S., & Quigley, A. (2022). Preventing the next pandemic: Use of artificial intelligence for epidemic monitoring and Alerts. Cell Reports Medicine, 3(12), 100867. https://doi.org/10.1016/j.xcrm.2022.100867 | ||||||||
5 | Maples-Keller, J. L., Bunnell, B. E., Kim, S.-J., & Rothbaum, B. O. (2017). The use of virtual reality technology in the treatment of anxiety and other psychiatric disorders. Harvard Review of Psychiatry, 25(3), 103–113. https://doi.org/10.1097/hrp.0000000000000138 | ||||||||
6 | Molinaro, N., Schena, E., Silvestri, S., Bonotti, F., et all. (2022). Contactless vital signs monitoring from videos recorded with Digital Cameras: An overview. Frontiers in Physiology, 13. https://doi.org/10.3389/fphys.2022.801709 | ||||||||
7 | Rodrigues, J. J., De Rezende Segundo, D. B., Junqueira, et all. (2018). Enabling technologies for the internet of health things. IEEE Access, 6, 13129–13141. https://doi.org/10.1109/access.2017.2789329 | ||||||||
8 | Wright A, Sitting DF, McGowan J, et all. J Am Med Inform Assoc. DOI: 10.1136/amiajnl-2014-002776 | ||||||||
9 | Smak Gregoor, A. M., Sangers, T. E., Bakker, L. J., Hollestein, L., Uyl – de Groot, C. A., Nijsten, T., & Wakkee, M. (2023). An artificial intelligence based app for skin cancer detection evaluated in a population based setting. Npj Digital Medicine, 6(1). https://doi.org/10.1038/s41746-023-00831-w | ||||||||
10 | Bringing science to medicine: an interview with Larry Weed, inventor of the problem-oriented medical record. (2014). | ||||||||
11 | Donald C.J. et all. The Regenstrief Medical Record System: a quarter century experience. (1999). doi: 10.1016/s1386-5056(99)00009-x. | ||||||||
12 | Laugesen K, et all. (2021). Nordic Health Registry-Based Research: A Review of Health Care Systems and Key Registries. | ||||||||
13 | Using LOINC with SNOMED CT. |