eHealth2014 – June 3rd

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InterSystems – Population Health Management: The Health Informatics Platform for Analytics and Actions

Speaker: Dr. Qi Li, MD, MBA Physician Executive InterSystems Session’s Details: Around the world, healthcare systems share the goals of improving patient outcomes and caring for an entire population, while minimizing cost and risk. Traditionally, population health management has focused on statistical reporting and public health registries. However, healthcare now demands a health informatics platform that can dynamically stratify risks along the axes of outcomes, performance, and cost for effective population health management. This presentation will review how a health informatics platform is fundamental to a modern population health management strategy, and for engaging patients, connecting clinicians across the continuum of care, and using analytics to drive actions. (Source: ehealth2014 app)   PowerPoint Is not Available. Here is my personal notes from the actual session.
 

CS 23: EMRs: Driving Quality Improvements

CS23.1: From EMR to web to mobile app – iCHIP: Developing the complete health record solution for the  inherited blood disorder population

Speaker: Jack Michaan BC PBCO B.A.Sc., Electronics Engineering – Polytechnic School of the University of Sao Paulo, Brazil  Over 30 years experience in architecture and development of computer systems and databases. Over the past 10, actively working in the health sector developing the BC Central Transfusion Registry, Transparent Blood Inventory and many other health related systems for the BC PBCO/PHSA. Session’s Details: Caring for British Columbians with genetic bleeding and red cell disorders is complex and costly. Health care professionals and patients navigate numerous data systems to provide and receive care. Blood and blood product utilization for these patients is over $30 million (2012/13 in BC) with the majority used in a home environment. An accurate picture of home utilization is unknown making improved monitoring of usage necessary. The Inherited Coagulopathy and Hemoglobinopathy Information Portal (iCHIP) was developed by the BC Provincial Blood Coordinating Office (PBCO) as a unified and comprehensive data system to support health care delivery to these patients. This presentation describes the development of iCHIP and displays the capabilities of this innovative technology that melds health care delivery with e-health advancement (Electronic Medical Records to web-based tool to mobile application). Methodology/Approach iCHIP development required a comprehensive review of data systems the health care teams and patients were using. Working/focus groups identified the functionality required for a new system capable of replacing its predecessors. A prototype system enabled validation in a close to real world environment. The objectives of iCHIP are to: meet the demands of the health care team by reducing the duplication of manual data entry, improve access to longitudinal health information, provide patients with secure access to their health information and merge records of bleeding episodes with use of product at home and the hospital setting. As the existing data systems were not integrated, they were unable to capture comprehensive data on blood product utilization in real time by individual patient or patient population. With a small development team of four individuals and limited funding, iCHIP was created. Findings/Results Using many innovative technologies, meticulous software development practices and incorporating the latest security standards, iCHIP was developed as a multi-tier web application that is user-friendly, intuitive, robust and agile. iCHIP consists of two modules: Patient Home Module (PHM) and Clinic Module (CM). Both provide reports displaying graphics and adapt to the patient’s diagnosis type and treatment protocols. iCHIP PHM is a web and mobile-based application that makes it easy for patients to report clinical events, record use of blood products from their personal inventory, self-manage their care and receive notifications from their health care team. iCHIP CM is a web-based EMR tool that also provides the ability to view the data that patients input into the PHM in real-time. By using iCHIP, clinic staff can set the parameters for alerts regarding critical conditions associated with the care of the patient. Conclusions/Implications/Recommendations The development of iCHIP shows that a quality, modern, inventive product can be created with a small team, limited budget, and an aggressive timeframe. It improves patient health outcomes by providing real-time longitudinal care information, presenting detailed information on utilization of blood products and creating a platform for patients and their health care team to share clinical information. iCHIP has the capability to improve health care delivery for inherited blood disorder patients and the same model is suitable for use with other chronic disease populations.   PowerPoint Source: (eHealth-2014) It was a very interesting presentation. JAVA and Oracle database was used and the iCHIP software tracking system was accessible using computer and mobile devices.
 

 CS23.2: Using Data to Drive Quality Improvement and Decision Support

Speaker: Karl Langton Hamilton Family Health Team Karl Langton is the Health Informatics Coordinator with the Hamilton Family Health Team. He is also Assistant Professor with McMaster University’s Masters in eHealth Program, on the Program Advisory Committee for Conestoga College’s Health Informatics Program, Peer Leader with OntarioMD, member of the Quality Improvement Decision Support Specialist Steering Committee with AFHTO, and a performing musician. Session’s Details: The purpose of this initiative was to improve data quality in EMRs and get clinicians entering data in such a way that can yield accurate and meaningful ways. Additionally, this initiative was designed to track quality improvements over time through the visual generation of chronic disease graphs in order to provide metric-sensitive information that identifies populations at need or needing improvements in meeting disease-specific targets. Methodology/Approach There were five key stages to this initiative. The first was to introduce the chronic disease data quality initiative. This initiative was meant to provide practices with a visual representation of how well practices managed a specific chronic disease population. The second stage was to obtain meaningful data. This was done by extracting data from the EMR to create patient registries with metrics for each chronic condition. The third stage was to re-evaluate the chronic disease quality initiative with meaningful data. This allowed for proper data disciplining techniques to be implemented within practices in order for more accurate data representation as well as improvement management for specific chronic-disease populations. The fourth stage of this initiative was to track quality improvement over time in order to see how well our physicians and clinics were performing. The final stage of this initiative was to provide decision support to practices on how to better meet their chronic-disease specific targets. Findings/Results We found that it is difficult to get people to change their current methods of entering data. However, people see the positives in having clean data when they are able to see a tangible advantage. Visual representations not only provide individuals with this tangible advantage but also provide a graphic representation of performance measurements to spark better managed care. Conclusions/Implications/Recommendations Regardless of future automation, this initiative has taught us that data discipline will always be required as having clean data is the first step towards having meaningful results. For this initiative we hope to automate the process of data extraction and reporting and hope to deploy a functioning web-based platform to enhance our current chronic disease data quality package. PowerPoint Is not Available.
 

CS23.3: Measuring Maturity of Use and Changing Behaviors – What Can an EMR Dashboard Do?

Speaker: Catherine Hunter PwC Catherine Hunter is a Director in PwC’s Healthcare Consulting practice with an extensive background in ehealth. Her focus is in change management and the realization and evaluation of benefits associated with large scale changes in health care. Catherine has worked closely with management, staff and clinicians to achieve objectives through the definition and implementation of practical solutions, including IT and other strategic and process-focused initiatives. Catherine has recently worked extensively in primary care settings with EMR users, and brings additional experience with Canada Health Infoway, academic health science centers, community hospitals and provincial agencies. Session’s Details: In 2013, the Objective Data Dashboard (ODD) was developed and deployed to primary care physicians in BC to objectively assess maturity and clinical value of electronic medical record (EMR) use. The ODD is integrated into EMRs and tracks a set of indicators with structured data that measure maturity of EMR use at Clinical Value Level 3 and ensures that key aspects of patient information are recorded, reviewed and motivate any desired changes in behaviours in EMR use and clinical practice. Methodology/Approach Through a collaborative process with PITO and an advisory panel of primary care physicians, the functional requirements of the ODD and specific indicators and target values were identified in alignment with PITO’s Clinical Value Model at Level 3 maturity. Working closely with a selected EMR vendor, a pilot of the dashboard was implemented and evaluated to assess ease of use, functionality, suitability of indicators and changes in provider behaviours that resulted from dashboard use. With pilot feedback incorporated, the dashboard was developed by additional vendors and each were tested for conformance to requirements prior to broad implementation. Findings/Results Implementation has yielded positive results, with physicians finding the ODD to be a very intuitive and motivating tool to improve patient care and reporting around key indicators that are directly linked to maturity and clinical value of EMR use. The pilot has prompted early changes in behaviour among the small sample of users, with significant potential to improve practice and teaching over the longer term. Changes in behaviours were related to both data entry and practice itself, as the dashboard prompted focused efforts to address values of specific indicators. Physicians reference the dashboard as a means of understanding if their EMRs are tracking key data over time for the benefits of individual patient care and for broader population health management Conclusions/Implications/Recommendations Conclusions and recommendations include: [su_list]
  • The ODD measures structured data, and differentiates the existence of data and that data which is properly coded. In doing so, the dashboard is a precursor to effective quality indicators and interoperability.
  • The ODD affords physicians the opportunity for reflection and insights into their current practice, with the ability to make changes and use EMRs for improved clinical value. The establishment of appropriate indicators and their target values is an iterative process that requires clear definition and consideration of factors including practice patterns and patient populations.
[su_list] PowerPoint Source: (eHealth-2014)
 

CS30: Perspectives: Big Data and Health Analytics

CS30.1: Health Analytics: lessons learned from early adopters of data-driven decision-making in the health care sector

Speaker: Dr. Diane Gutiw Leidos Health (SAIC) Dr. Gutiw is a health informatics professional with Leidos Health (SAIC) and holds a Ph.D. in medical expert systems. Diane has led the architecture/design of jurisdictional EHR solutions, and is a interoperability, health data management and analytic strategy SME. Diane has over a decade experience with industry and academic research and the design of health analytics strategies for data-driven decision-making. Session’s Details: Despite the increase in automation and availability of digital health data in Canada, the delivery of quality healthcare continues to be challenged by inefficiencies. Inefficiencies have been tied to ineffective data gathering, sharing and use. In addition to the financial inefficiencies, clinical care continues to suffer as acute care facilities report numbers that range as high as 25% of patients reporting preventable clinical errors in some aspect of their care. Health care systems are undergoing transformations to improve access and quality of care, value for money, and the patient experience. Health Analytics has been identified as an enabler of these improvements with the potential to transform the cost, performance and delivery of care, and is gaining momentum as a key investment of health organizations. The purpose of this white paper presentation is to highlight existing academic studies, industry research and real case studies which cite the tangible benefits of adopting a data-driven approach for medical system decision-making. Methodology/Approach The approach taken in this analysis includes a combination of literature review and practical case studies to highlight the strategies and benefit realization from early adopters of health analytics across Canada and the United States. This white paper analysis synthesizes the reported strategic approaches to analytic program implementations, and cites the real benefits reported by these organizations. The outcome of this analysis is an early glimpse at best practices and lessons learned from early adopters of health analytic strategies. Findings/Results In summary, the findings of this analysis suggest that high-performing, data-driven organizations have taken a systematic and pragmatic approach to implementing health analytics. By focusing initially on quick wins in the areas of revenue cycle, and operational optimization, organizations are able to gain greater buy-in for increased investment to expand to clinical and research data analytic functions. The findings cite real case examples, and describe the triggers for engaging in health analytics for organizational decision-making, and identify specific opportunities where organizations have achieved real benefits from their analytic program and strategies. Some examples of almost immediate benefits include the use of analytics to reduce revenue leakage, identify and reduce fraud and target program improvements to better utilize healthcare resources as well as target readmission risks. The findings suggest that some longer term impacts resulting from the adoption of health analytics will be improved healthcare quality, improved chronic care, and patient empowerment. Conclusions/Implications/Recommendations The analysis concludes with a list of best practices and targeted benefits for organizations that are unsure where to start with the implementation of their analytic programs. By looking to high-performing organizations with an existing track record in the implementation of both big and small data analytic programs, new adopters will be able to leverage the lessons learned and take a pragmatic approach to implementing and benefiting from the increased use of their available data for strategic, predictive and prescriptive decision-making for more effective health care performance and improved quality of health care delivery and patient outcomes. PowerPoint Source: (eHealth-2014) My notes on this presentation.
 

CS30.2: Tensions between big data versus high quality clinical data: bridging the gap through clinical intelligence (CI)

Speakers: Dr. Margaret Kennedy Atlantic Branch Manager, Sr. Consultant & Clinical SME – Global Village Consulting, Inc. Margie is a seasoned clinician and informatics expert with extensive experience in stakeholder engagement, change management, deployment coordination, and strategic planning. She supports a variety of informatics projects across Canada, particularly for First Nations. Margie holds professional appointments in Canada and internationally, and is currently the Past President of the Canadian Nursing Informatics Association. Sally Remus Informatics, Nursing Practice & Education Consultant Sally is an accomplished healthcare executive who has diversified experiences as a clinician, nurse informatician and educator. Her current consulting work focuses in designing successful change leadership/management & education strategies that align with clinician stakeholder needs in deploying complex enabling technologies. Sally holds professional appointments at Canada Health Infoway and is the current Director, Member Services of the Canadian Nursing Informatics Association. Session’s Details: Recent reports and publications suggest that leading health care organizations recognize the value of “big data” and the necessity of health system transformation and sustainability. Despite compelling recommendations and a variety of expert panels, minimal or no uptake is demonstrated across any health system levels. There is a tension between the potential of “big data” and all the promised benefits of electronic health information and the associated harnessing of data, compared to the current state of information management and utilization supporting transformation. Clinical intelligence (CI) is a new field in healthcare, arising from both necessity and opportunity, to generate high quality, electronic data that will support knowledge driven care. A gap exists in this dynamic for informed and passionate leaders to advance the clinical intelligence agenda to achieve successful “big data” opportunities. The purpose of this concurrent session is to describe 1) the tension between the promises of big data, and the current state, 2) the recognition of clinical intelligence as the new business intelligence of health care and 3) the critical leadership of nurse informaticians in clinical intelligence. Methodology/Approach A scan 1 was conducted across professional and gray literature to collect evidence on the inclusion of nursing informatics competencies augmenting traditional leadership skills/knowledge (e.g., financial, human resources, clinical management, etc.) as a new essential skill set for all nurse executives. Additionally, the Canadian health care system was assessed on a jurisdictional and national basis to identify the existence of Chief Nursing Informatics Officer roles and applied nursing informatics (i.e., competencies) within practice settings. Further, the new COACH career matrix was applied to further identify the roles and opportunities for clinical leadership in health system transformation. Findings/Results While the concept of CI may seem futuristic, CI is being built today through the rapid deployment of HIT, especially electronic health records (EHR). Across the continuum of care, the majority of patient data is moved by nurses entering data into EHRs. As such, it is essential to understand the roles of Nursing Informaticians (NI) in the emerging field of CI.2 Canada and the clinical professions have been slow to recognize and embrace the concept of clinical intelligence and its potential role in supporting health system transformation. Healthcare leaders continuing with the status quo jeopardize the transformative eHealth practice agendas of achieving patient safety, quality care delivery, knowledge driven-care and sustainability. Alternatively, health systems that recognize the value of nursing informatics competencies and create new leadership roles with titles such as, Chief Nursing Informatics Executive (CNIE) or Chief Nursing Informatics Officer (CNIO) 3, 4,5,6,7 will be able to exploit and advance the development of clinical intelligence. Conclusions/Implications/Recommendations The ultimate benefit of the time, energy and cost of an EHR is clinical intelligence 8. Health systems must embrace a new way of operating in order to achieve the benefits that have been previously unattainable, despite massive investments in technology. Traditional perspectives and roles need to be reframed to align and exploit opportunities afforded by electronic health records and the essential informatics competencies and NI leadership roles. PowerPoint Source: (eHealth-2014) My notes on the session.
 

CS30.3: “Big Data, Big Challenges – Building Health & Business Analytics Capabilities”

Speaker: Philip Baker Fraser Health Philip Barker, B.Sc.[Pharmacology], M.H.S.A., CHE Vice President, Informatics & Transformation Support for Fraser Health Authority.  He has more than 25 years of health care management and consulting experience in public and private sectors. He leads the governance and strategic management of Fraser Health’s informatics and transformation services teams to support seamless care, greater clinical services integration and quality, enable evidence-based decision making and foster innovation and collaboration across the region and Lower Mainland. He previously served in senior leadership roles with IBM Canada, Simon Fraser Health Region, Fraser-Burrard Hospital Society, Calgary District Hospital Group and Saskatoon University Hospital. Philip currently serves on the Board of Directors of Health Improvement Action [IMPACT] BC. Session’s Details: As a member of Fraser Health’s senior executive team, Philip will share his views on drivers for change emanating from big data in an integrated healthcare delivery provider world. Whether driving quality improvement in access, patient experience, delivery system performance, point of care decision making or population health; big data demands new capacity and thinking to effect real change. In particular, the presentation will focus on transformation work associated with building organizational capabilities to keep pace with the big data analytics opportunities. Methodology/Approach In this concurrent session, the context and drivers for building a Health and Business Analytics (HBA) unit in an Integrated Health Care Delivery Organization will be described. The presentation proposes a null hypothesis as the basis for discussion: “The exponential proliferation of data and the accelerated development of “data” mining and analysis technology tools will rapidly outpace the capabilities of health care delivery systems, providers and stakeholders to effectively make sustainable differences in health and health care quality.” A review of this hypothesis will follow with a presentation of key organizational and informatics capabilities aimed at addressing these challenges. Findings/Results Organizational imperatives of integration, consolidation and standardization are foundational to the development of the analytics capabilities. Clinical program management capabilities, enterprise IM/IT business capabilities, enterprise architecture principles and IM/IT delivery strategies also impact the building of the Health and Business Analytics unit. The HBA unit development will be described based on previous organizational state, the vision and composition of the new unit, and the functions and staffing of the department. The Health & Business Analytics unit capabilities are contrasted to the COACH Professional Career matrix in terms of the core delivery functions: a) Information Delivery Services b) Operational Engineering and Analysis c) Operations and Data Management d) Data Warehousing/Business Intelligence Technology Three project vignettes will be presented where the HBA capabilities significantly contributed to meeting key organizational goals including: taking charge of hospital congestion; quality performance management; and enterprise data warehouse prioritization. Conclusions/Implications/Recommendations The conclusion will review the key success factors in developing the HBA capabilities. These include: engagement; analytics skills; data governance; COTS vs. Custom Design; information transparency and tool usability. The presentation will recommend that, in the world of big data, future capabilities are needed to a) establish data governance, b) use big data at point of care, and c) integrate big data solutions with point of service workflow. PowerPoint Source: (eHealth-2014) My notes on the presentation.