Data Integration Efforts and Challenges

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Data Integration Efforts and Challenges. Because Minds Matter: Collaborating to Strengthen Psychotropic Medication Management for Children and Youth in Foster Care August 27-28, 2012. Scott M. Bilder, Ph.D. Institute for Health, Health Care Policy, and Aging Research - PowerPoint PPT Presentation

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Data Integration Efforts and ChallengesScott M. Bilder, Ph.D.Institute for Health, Health Care Policy, and Aging ResearchRutgers, The State University of New Jersey(bilder@rci.rutgers.edu)

Because Minds Matter: Collaborating to Strengthen Psychotropic Medication Management for Children and Youth in Foster CareAugust 27-28, 2012MEDNETAHRQ-funded initiative involving Rutgers, Columbia, Academy Health, six states, and others to:Develop a set of measures for antipsychotic use patterns.Convene a cross-state network to review evidence, policies, and practices.Implement quality improvement programs in each state.Evaluate impact of efforts and share knowledge obtained.See aims in original Mednet application2MEDNET OrganizationMulti-state Steering Committee / Learning Workgroup.Workgroups (with representation from participating states).Metrics Workgroup.Foster Care Children Workgroup.Duals/Medicare Part D Data Workgroup.State-specific QI teams,including Project Leads, Data Leads, and Local Stakeholder Committees.

See aims in original Mednet application3Adapting Efforts to Foster Care ContextMaintain existing relationships while developing new collaborations with child welfare stakeholders.Broaden and diversify focus:Shared (core) issues.State-specific issues.Identify appropriate data systems and experts.Create and/or adapt quality metrics.

See aims in original Mednet application4Data IssuesIdentifying and tracking youth across time and data systems.Keeping up with status/eligibility changes.Identifying health services not captured in claims data.Establishing sufficient look-back periods for treatment initiators.Establishing common data structures to support analysis and reporting.

See aims in original Mednet application5Data IntegrationData SourcesMedicaid FFS ClaimsMedicaid Eligibility FilesMedicare(A, B, D)Medicaid Encounter DataState Mental Health Agency DataMental Health Carveouts

State Childrens Services DataData UsersProviders andPrescribersConsumersMentalHealthClinicsStateMedicaidAgenciesState MentalHealthAgenciesStateChildrensServicesDATA INTEGRATIONSee aims in original Mednet application6Data IntegrationMultiple data silos are structured differently.Often the data are structured to support very specific applications.Narrative data present additional complications.Data integration must happen at several levels:Linkable databases.Task-specific analytic files.

On final point we have to be careful when we combine data that were developed with the expectation that they would be kept in a silo.7Data IntegrationFull-scale integration of multiple data sources is often impractical given:Different organization.Different production schedules.The sheer number of data elements.We have found it useful to define a common data framework.Using only those data elements that are needed.Focusing programming efforts.Focusing documentation efforts.

On final point we have to be careful when we combine data that were developed with the expectation that they would be kept in a silo.8Privacy and ComplianceDifferent data sources present unique threats to privacy, and accompanying:Request processes and agreements.Person identifiers.Physical security requirements.Ongoing privacy review.Data that we are used to handling in isolation may require additional efforts at privacy protection when combined.

On final point we have to be careful when we combine data that were developed with the expectation that they would be kept in a silo.9Metric DevelopmentPolypharmacyAdherenceExcessive doseCardiometabolically challenging antipsychoticsMetabolic/lipid monitoring

Psychotropics in very young childrenDiagnoses consistent with psychotropic treatmentServices consistent with psychotropic treatment

10Metric DevelopmentMetrics committee identifies needs with input from all stakeholders.Initial discussions within metrics committee result in a draft conceptual summary. Programming code is developed and results of applying metric are evaluated.Conceptual summary is presented to stakeholder committee.Metrics committee revisits evidence base on a regular basis.1. Metrics committee includes quality measurement people, data experts (state and academic), clinicians, and pharmacists.2. Draft conceptual summary is usually accompanied by several rounds of preliminary analyses.3. Conceptual summary and programming code are subject to revision.11Initiative Under DevelopmentDevelop partnerships to assist states in effectively utilizing systems for psychotropic medication monitoring and mental health quality improvement for foster care youth.Facilitate knowledge sharing and integration.Provide technical assistance.Initiative Under DevelopmentDevelop, customize, and disseminate evidence on treatment effectiveness, processes, and quality management to states.Monitor evidence base.Create topic and technical briefs.Provide participating states with customized products adapted to child welfare context.Conduct webinars, panel discussions, to bring together multiple stakeholder perspectives.Initiative Under DevelopmentImprove the informatics foundation for bringing together multiple data sources.Develop and/or adapt health care quality metrics to foster care context.Identify and share best practices for linking data across and within state systems.Develop a core multistate data model.Implement a shared computing and documentation infrastructure.Collaborate with states and others to design and conduct studies that make the most use of enhanced, linked databases.