Dispelling the Myth of Interprofessional Practice Models in Health Informatics



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Transcription:

Dispelling the Myth of Interprofessional Practice Models in Health Informatics Margie Kennedy, PhD, RN, CPHIMS-CA, PMP, P2P Gevity Consulting Inc Canada 1 Objectives To challenge our assumptions and rhetoric around interprofessional collaboration To provoke expansion in our view of interprofessional collaboration in Health Informatics 2 1

HEALTHCARE IS INTIMATELY INTERPROFESSIONAL What does it mean to be intimately interprofessional? 3 Current Perceptions Collaborative practice happens when multiple health workers from different professional backgrounds work together with patients, families, carers and communities to deliver the highest quality of care. It allows health workers to engage any individual whose skills can help achieve local health goals (WHO, 2010) Practice includes both clinical and non-clinical healthrelated work, such as diagnosis, treatment, surveillance, health communications, management and sanitation engineering. Partnership between a team of health providers and a client in a participatory collaborative and coordinated approach to shared decision making around health and social issues (CIHC, 2013). 4 2

CMA Definition, 2007 5 Virani s Definition (2012) 6 3

Models of Interprofessional Care (Virani, 2012) 5 distinct models Interprofessional team model Nurse-led model Case management model Patient navigation model Shared care model 7 Framework for Action on Interprofessional Education & Collaborative Practice - WHO (2010) 8 4

MIND THE LEDGE 9 Where do existing models Fall off the Ledge? Variations in terminology Interprofessional vs collaborative Models all have a clinical view Applied only to direct care or education Traditional lens of who is involved Not one model mentioned: Health/clinical information management IT or HIM as a resource to support care Data quality (GIGO) Accuracy, timeliness, completeness, accessibility, or analytics to support practice decisions 10 5

As clinicians We are the self proclaimed experts What data we need What data we code How we should code it What the codes should be How data should be abstracted and distributed How data quality should be addressed We design to include other that can support the patientclinician relationship 11 Are clinicians really the right resources to be making all the decisions around health information management?? 12 6

Health Information Management Professionals (HIMs) Subject Matter Experts in their own right coding, abstracting, grouping and case weighting approaches. Stats Databases and programming Systems design Epidemiology and population health CDSS Systems integration Privacy & Security Clinical Systems Visual Design 13 HIMs Professional Practice Primary Care Research Patient Safety Telemedicine Principles in the EHR HIM Readiness Computer Assisted Coding Data Access, Use and Control for analytics Data standards, Quality, and interoperability Electronic Document Management Developing Data a Dictionary 14 7

Future Model for Interprofessional Care Clinical Provider Clinical Provider Client Clinical Provider HIM 15 Who needs to be driving this paradigm shift? CIO Accountable for the use and advancement of technology linked to organizational outcomes Time limited We have the opportunity to correct the current situation, engage HIMs, and improve information quality, accuracy, patient outcomes, and HI. 16 8

DISCUSSION THANK YOU 17 References: Canadian Interprofessional Health Collaborative (CIHC) (2010). A National interprofessional competency framework. University of British Columbia: Vancouver. Virani, T. (2012) Interprofessional collaborative teams. Ottawa: Canadian Health Services Research Foundation. Canadian Nurses Association (2014) Interprofessional Collaboration. Available: http://cna-aiic.ca/en/on-the-issues/bettercare/interprofessional-collaboration Bridges, D., Davidson, R., Odegard, P., Maki, I., & Tomowiak, J. (2011). Interprofessional collaboration: Three best practice models of interprofessional education, Med Educ Online, 16(10) 16i0.6035. doi: 10.3402/meo.v16i0.6035 18 9