1. Medical Informatics Workshop 2003-2013 Prognostic Matches and Mismatches HIS: Medical Knowledge and Decision Support (T20-T21) Casimir Kulikowski and Rainer Röhrig

2. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 T20: Medical Knowledge General Trend  “Knowledge about diseases will be current, comprehensive and internationally available via electronic media, including their availability to patients and their family members (consumers).” Partially true in terms of currency and international availability Not true in terms of comprehensiveness or access to patients and consumers, which depends on their resources and facilities for compiling search results over multiple, heterogeneous digital sources of varying degrees of reliability and interpretability.

3. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 T20: Medical Knowledge Availability and Accreditation  “This knowledge will be available in different qualities  Therefore, internationally accredited certification will be available for their contents (e.g. by specialty associations)” False (Mismatch) : very little knowledge can be certified easily or unambiguously without specification of the very particular queries that this knowledge answers. In Germany started a project to certify databases for CPOE – in first step without content

4. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 T20: Medical Knowledge Integration in Clinical Routines  “Knowledge Support will partially be integrated in clinical routines. This among others will result due to guidelines, or aggregated diagnostic or therapeutic knowledge in reference to evidence-based medicine” Largely False (Mismatch) : Procedures tend to have guidelines associated with them electronically in non-systematic, EMR-specific ways, and evidence-based medicine, while increasingly developed, has yet to find a standardized niche in routine healthcare practice (its use depends on the individual caregiver – at least in the US)

5. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 T20 Medical Knowledge P20.1 Web Acces  “Over 80% of polled/queried medical knowledge will result from electronic media (Over 95% from internet). Paper-based reference works will find seldom use.” Likely true (Match), but difficult to determine exactly depending on availability of web resources and level of education/expertise and facility with the web/internet (age and financial status) for caregivers and consumers (patients, families, etc) Half true (Match), More and more smartphone apps (from the internet) are used. The benefits of Apps are offline functionality and customization of knowledge (commentary)

6. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 T20 Medical Knowledge P20.2 Electronic availability  „Over 80% of the guidelines used in routinely in clinical work, will be available electronically“ True (Match)

7. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 T20 Medical Knowledge P20.3 Certification  Less than 10% of medical sites will be certified (a). Physicians will answer questions for more than 50% of certified sites (b) (a) True (Match) Very few internet sites are certified in any way – reliability is subjective and depends on authority/legitimacy of sources (ie NIH/NLM, WHO, professional organizations or societies) (b) Impossible to determine – probably false, since physician time is expensive and they are not usually hired by sites. ? Outlook: It it´s necessary to clarify the responsibility of information

8. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 T20 Medical Knowledge P20.4 EHRs and Guidelines Integrated  In over 10% of hospitals, over 30% of guidelines used in clinical routines will be integrated in application systems for EHRs. ? Very difficult to determine, since it depends on the country, health plan and insurance requirements, specific EHRs used in a hospital and adaptations to local environments. In the US and Germany this prediction is probably false.

9. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 T21 Decision Support Systems General statement  “DSSs will not yet have established themselves” True, they are rarely used in most institutions and practices  “Passive decision support functions (reference to next step in a therapy) will have further established themselves” False in the US and Germany for most institutions From todays point of view, for most guidelines we are not able to reference the next step in a therapy, we are only able to monitor the guideline adherance and give smart alerts.

10. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 T21 Decision Support P21.1 Professional Usage  “Health Care Professionals will actively seek assistance of DSSs in less than 10% of all diagnoses they make” True (Match) DSSs are rarely used in the USA and Germany – and physicians still consider they know most about the diagnostic possibilities for a patient – This, however, may change with results from translational medicine as the combinatorial explosion of genomic factors and their influences on phenotype in health and disease increases. Sidenote: There are positive examples for DSS (e.g. hemodynamics) – with interesting side effects (physicians believe the DSS and lose their skills in calculation and interpretation of values – and can´t controll it)

11. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 T21 Decision Support P21.2 DSS for Complex Treatments  “Over 10% of complex treatments in hospitals (chemotherapy, radiotherapy, surgery, etc) will be planned with the active assistance of systems offering DS functions” Probably true (Match) for technologically intensive and precise procedures like chemotherapy and radiotherapy. However, for surgeries it is likely False (Mismatch) except for those procedures that involve use of complex artificial components (like knee replacement surgery, etc)

12. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 Conclusion CDSS EHR / Patientinformation (Facts Data Base) Knowledge Base CDSS Inference machine HIS Clinician

13. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 Conclusion CDSS EHR / Patientinformation (Facts Data Base) Knowledge Base CDSS Inference machine HIS Clinician Increased numbers of guidelines, SOPs, …

14. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 Conclusion CDSS EHR / Patientinformation (Facts Data Base) Knowledge Base CDSS Inference machine HIS Clinician

15. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 Conclusion CDSS EHR / Patientinformation (Facts Data Base) Knowledge Base CDSS Inference machine HIS Clinician

16. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 Conclusion CDSS EHR / Patientinformation (Facts Data Base) Knowledge Base CDSS Inference machine HIS Clinician Smartphones

17. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 Conclusion CDSS EHR / Patientinformation (Facts Data Base) Knowledge Base CDSS Inference machine HIS Clinician Smartphones

18. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 Conclusion Dimensions of Ignorance KnowledgeLack of Knowledge knownknown knowledge - apparent ignorance known ignorance unknownunknown knowledgeunknown ignorance Wilkesmann & Jang: Dealing with Ignorance. Anästh & Intensivmed 2013;54(5): 246-252

19. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 Conclusion Dimensions of Ignorance KnowledgeLack of Knowledge knownknown knowledge - apparent ignorance known ignorance unknownunknown knowledgeunknown ignorance Wilkesmann & Jang: Dealing with Ignorance. Anästh & Intensivmed 2013;54(5): 246-252

20. 01001101011011100111000111101010101000101010100011100100101010001001001000111100010001000111100101010010100100111010101010101010110010010011010110111011011101110111000100101010010101010100101100111 1100100011110010101001010010011101010101010101010001001101001010101110010010010011100010010101001010101010010110011101110110101010001001110101010001001101010100010011010101000100110101010001001101010100010011 Conclusion Computerised Medical Decision Support Syntactic and Semantic Standards Structured Electronic Docoumentation Medical Informatics Edutcation IT-Risc Management Ethical Aspects and Privacy Protection Usability Clarified Responsabilities MDD / FDA Evidence Based Medicine IT-Infrastructure including Telemedicine Knowlegde Management

21. Medical Informatics Workshop 2003-2013 Prognostic Matches and Mismatches HIS: Medical Knowledge and Decision Support (T20-T21) Casimir Kulikowski and Rainer Röhrig