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Data Integration – The Key To Successfully Utilizing Information
 

Data Integration – The Key To Successfully Utilizing Information

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Examination of the value of data analytics and integration to support new care models such as ACOs and Patient-Centered Medical Homes. The EHR is necessary but not sufficient!

Examination of the value of data analytics and integration to support new care models such as ACOs and Patient-Centered Medical Homes. The EHR is necessary but not sufficient!

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  • Building the HIT Infrastructure for the Patient Centered Medical Home and Accountable Care OrganizationsThe EHR is necessary but not sufficientUnderstand the HIT implications of the new emerging care models. HIT not only closes critical gaps in how care is delivered but will be essential to enabling higher levels of competitive performance. The EHR is essential but must be optimized and integrated into a complete HIT “ecosystem” and transformed culture to deliver on its promise. Impact of current and expected government initiatives HIT requirements for the PCMH and ACOs Best practices for managing the data lifecycle Understand “Big Data” analytics Key strategies and tactics to implement the necessary HIT infrastructure
  • Define how to leverage and transformAccording to the U.S. Department of Health and Human Services, the current system, ICD-9-CM, does not provide the necessary detail for patients’ medical conditions or the procedures and services performed on hospitalized patients. ICD-9-CM is 30 years old, has outdated and obsolete terminology, uses outdated codes that produce inaccurate and limited data, and is inconsistent with current medical practice. It cannot accurately describe the diagnoses and inpatient procedures of care delivered in the 21st century. ICD-10-CM/PCS Incorporates much greater specificity and clinical information, which results in:Improved ability to measure health care servicesIncreased sensitivity when refining grouping and reimbursement methodologiesEnhanced ability to conduct public health surveillance; and decreased need to include supporting documentation with claimsIncludes updated medical terminology and classification of diseasesProvides codes to allow comparison of mortality and morbidity dataProvides better data for:Measuring care furnished to patientsDesigning payment systemsProcessing claimsMaking clinical decisionsTracking public healthIdentifying fraud and abusePerformance improvement plansConducting research In order for organizations to be successful with implementing ICD-10-CM/PCS and also meeting the criteria for meaningful use of electronic health records, physician documentation must be thorough. Clinical data documented through patient history and physical exams, clinical treatments, medication therapy, surgical procedures, and clinical outcomes should be documented thoroughly. Although Stage 1 of meaningful use calls for much less criteria than Stage 2 for physician documentation, the best practice should be to institute improved documentation now. The level of physician documentation influences quality measuring and reporting, what types of clinical information will be available when Health Information Exchange data is provided, and overall clinical performance improvement plans for the organization. So there is a direct link between improving physician documentation to prepare for ICD-10, meeting the criteria for the various stages of meaningful use, and measuring quality care for improvement purposes.

Data Integration – The Key To Successfully Utilizing Information Data Integration – The Key To Successfully Utilizing Information Presentation Transcript

  • Data Integration – The Key to SuccessfullyUtilizing Information for Point of Care and for Population Health Charles DeShazer, MD VP, Quality, Medical Informatics & Transformation Dean Health System
  • Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor – Data Integration & Distribution “Big Data” Analytics Key Strategies & Tactics
  • Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor – Data Integration & Distribution “Big Data” Analytics Key Strategies & Tactics
  • New Care Models Patient-Centered Medical Home  Health care model that aims to provide structured, proactive and coordinated care for patients. Accountable Care Organizations  Group of health care providers (e.g. primary care physicians, specialists and hospitals) that have entered into a formal arrangement to assume collective responsibility for the cost and quality of care of a specific group of patients and that receive financial incentives to improve the quality and efficiency of health care. Payment Driven Models  Bundled payments  Pay for Performance  Case rates  Capitation
  • ACO model represents a shift of COST RISK toProviders through payment mechanisms…
  • Population vs. Costs vs. Interventions Example of 100,000 People in a Population % of % of Cost Population Complex Case Management 1% 1000 25% Lives Disease/Demand14% 14,000 Lives Management 50%15% 15,000 Lives Health 15% Mgmt70% 70,000 Lives 10% Approximately 75% of costs are due to chronic co
  • Healthcare Information Technology (HIT)Requirements PCMH ACOs  Care Coordination  Cross Continuum  Chronic Disease Medical Management Management &  Member Engagement Complex Case  Clinical Information Management Exchange  Population Health  Quality & Performance Management (esp Reporting registries)  Predictive Modeling &  Patient Engagement & Analytics Activation  Administrative and  Evidence-based Financial Risk Medical Practice Management systems  Real-time connectivity
  • EHR is necessary but notsufficient In "Associations Between Structural Capabilities of Primary Care Practices and Performance on Selected Quality Measures," Mark Friedberg MD, and colleagues examine how a range of primary care practice attributes, including having an EMR, may impact physician performance on quality metrics. The research profiled 307 practices in Massachusetts across 2007. Across the practice characteristics and HEDIS metrics, the attributes correlated to a practices higher-quality performance on diabetes and prevention metrics included: having an EMR, frequent meetings to discuss practice quality performance, and physician awareness of patient experience. EMRs were specifically associated with higher performance on two diabetes metrics (eye exams and nephropathy monitoring) and three prevention metrics (breast cancer, colorectal cancer, and chlamydia). Key insight: The key transformative aspect of the EMRs role in the practice was shown to be providing information to support decision-making--not just serving as a repositoryFriedberg, M., et al, Annals of Internal Medicine, 2009; 151:456-463 for data.
  • Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor – Data Integration & Distribution “Big Data” Analytics Key Strategies & Tactics
  • Continued Evolution of the MedicalCare … Genomics New Technology Aging Population
  • Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor – Data Integration & Distribution “Big Data” Analytics Key Strategies & Tactics
  • Meaningful Use & ICD-10 Meaningful Use  Driving increased adoption of EHRs in-patient and ambulatory  Penalty starts if not “meaningful user” by 2015  Infrastructure for ONC vision and robust Clinical Decision Support (CDS) ICD-10  One of the most comprehensive regulatory changes in the history of healthcare in the US  Unlike MU, it is an unfunded regulatory event  Replaces 30 year old ICD-9-CM, which is outdated and lacks clinical granularity  Provides granularity to diagnostic information that should greatly enhance predictive models  Improved ability to specify and measure healthcare services  Enable better integration of predictive modeling and clinical decision support  Richer data structures for research
  • ICD-10 Asthma Codes More granular clinical information will enhance predictive models as well as enable real-time program referrals especially when followed serially and combined with other data.
  • Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor – Data Integration & Distribution “Big Data” Analytics Key Strategies & Tactics
  • Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor – Data Integration & Distribution “Big Data” Analytics Key Strategies & Tactics
  • Data Management LifecycleData Collection (QA) Data Extraction (ETL) •Avoid GIGO •Critical Integration Step • Collection workflows •Data Governance & • Clarity of where to enter Master Data Management data to be reportable •Data warehouse & marts • Coding consistency and • Single source of truth conventions (ICD-10) • Create Predictive & Analytic Models •Establish accountability •Leverage Analytics for and feedback mechanisms Insights that drive • Link with Lean efforts decisions and processes • Identify gaps and new •Testing and Validation requirements • Formatting for ACTION •Learn from reports & • Visualization of data change collection process • Delivery medium incl. CDSImprovement Initiatives Information Delivery
  • Key Technical Infrastructure to support thePCMHEHR is necessary but not sufficient. The next level of quality management willrequire an INTEGRATED Health Information Technology (HIT)“ecosystem” especially a robust analytic infrastructure. Standalone EHRmay not be able to provide all of these functions.Focus Area Key Technical InfrastructureCare Coordination HIE, Workflow Management, Shared Care Plan, Referral trackingChronic Condition Management CRM, Workflow Management, Shared Care& Complex Care Management Plan, Predictive Modeling, CDS, Telehealth, RegistriesPopulation Health Management CRM, HRA, Predictive Modeling, Workflow Management, CDS, Population analytics, RegistriesPatient Engagement & Activation CRM, Shared Decision Making, Telehealth, PHREvidence-Based Medicine CDS, Workflow Management, PopulationPractice analyticsReal-Time Connectivity HIE, Telehealth, mobile technology, unified messaging
  • CSC ACO Maturity Stages
  • Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor – Data Integration & Distribution “Big Data” Analytics Key Strategies & Tactics
  • “Big Data” Analytics Recent IDC research on digital data indicates that in 2010, the amount of digital information in the world reached beyond a zettabyte in size. Thats one trillion gigabytes of information. To put that in perspective, a blogger at Cisco Systems noted that a zettabyte is roughly the size of 125 billion 8GB iPods fully loaded. The increasing velocity, variety and complexity of data is overwhelming traditional datawarehouse tools, techniques and infrastructure. Healthcare has a particular need to manage data well as EHRs become common, use of devices increase, integration of multimedia and imaging becomes important, integration with social networking resources becomes useful and genomics data becomes essential for decision-making. New high performance hardware, software and techniques are emerging to address this issue called “Big Data” Analytics. Gartner contends that terms like "big data," "real-time data" and "linked data" signal a new era in which the economics of data (not the economics of applications, software or hardware) will drive competitive advantage. What does this mean? It doesnt matter which EHR you have from a competitive standpoint. Competitive advantage will come from (1) the quality of the data you collect, (2) how you integrate the data and provide analytics to drive insights and (3) how well you use these insights to drive customer experience/relationships and business results.
  • Overview Implications of New Emerging Care Models Implications of Medical Care Evolution Implications of Government Interventions Government Vision of HIT Critical Success Factor – Data Integration & Distribution “Big Data” Analytics Key Strategies & Tactics
  • Leverage Meaningful Use as a SpringboardCriteria OpportunityProblem List Define system-wide standards and policies, improve accuracy of documentation, infrastructure for CDS, use for shared care planAVS & PHR Enhance quality, consistency and usefulness of content (esp. for chronic condition management), fully operationalize PHR, enhance patient engagement, use for shared care plan, leverage to engage family & caregiversMedication List Improve medication reconciliation and management of transitions of care.Patient Lists & Enhance analytics, create robust registries andStructured Data dashboards, infrastructure for CDSClinical Decision Create governance structure, establish standards,Support focus them on key areas of improvement opportunity, avoid alert fatigueQuality Measures Expect to be held accountable for results, create
  • Key Tactics & Strategies Implement & Optimize your EHR Consider "Big Data" Analytics Develop an effective data governance and master data management strategy Develop your Clinical Analytics unit Enhance your CDS infrastructure Decide on and commit the organization to an improvement methodology, this is the cultural change tool Invest in workflow optimization (good use for Lean techniques) Docs should manage by exception Consider how you will create a “Shared Care Plan” (SCP) to ensure all providers and the patient are on the same page Create enterprise and community infrastructure for health information exchange and CRM at the ACO level 24 Develop approaches to activate consumer/patient & family