data integration efforts and challenges
DESCRIPTION
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 PresentationTRANSCRIPT
Data Integration Efforts and Challenges
Scott M. Bilder, Ph.D.Institute for Health, Health Care Policy, and Aging
ResearchRutgers, The State University of New Jersey
Because Minds Matter: Collaborating to Strengthen Psychotropic Medication Management for Children
and Youth in Foster CareAugust 27-28, 2012
MEDNETo AHRQ-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.
MEDNET Organizationo Multi-state Steering Committee /
Learning Workgroup.o Workgroups (with representation
from participating states).• Metrics Workgroup.• Foster Care Children Workgroup.• Duals/Medicare Part D Data Workgroup.
o State-specific QI teams,including Project Leads, Data Leads, and Local Stakeholder Committees.
Adapting Efforts to Foster Care Context
o Maintain existing relationships while developing new collaborations with child welfare stakeholders.
o Broaden and diversify focus:• Shared (core) issues.• State-specific issues.
o Identify appropriate data systems and experts.
o Create and/or adapt quality metrics.
Data Issueso Identifying and tracking youth across
time and data systems.o Keeping up with status/eligibility
changes.o Identifying health services not captured
in claims data.o Establishing sufficient look-back periods
for treatment initiators.o Establishing common data structures to
support analysis and reporting.
Data Integration
Data Sources
Medicaid FFS Claims
Medicaid
Eligibility Files Medicare
(A, B, D)
Medicaid
Encounter Data
State Mental Health Agency
Data
Mental Health
Carveouts
State Childrens’ Services
Data
Data UsersProviders
andPrescribersConsumers
MentalHealthClinics
StateMedicaidAgencies
State MentalHealth
AgenciesState
Children’sServices
DATA INTEGRATION
Data Integrationo Multiple data silos are structured
differently.o Often the data are structured to support
very specific applications.o Narrative data present additional
complications.o Data integration must happen at several
levels:• Linkable databases.• Task-specific analytic files.
Data Integrationo Full-scale integration of multiple data
sources is often impractical given:• Different organization.• Different production schedules.• The sheer number of data elements.
o 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.
Privacy and Complianceo Different data sources present unique
threats to privacy, and accompanying:• Request processes and agreements.• Person identifiers.• Physical security requirements.• Ongoing privacy review.
o Data that we are used to handling in isolation may require additional efforts at privacy protection when combined.
Metric Developmento Polypharmacyo Adherenceo Excessive doseo Cardiometabolica
lly challenging antipsychotics
o Metabolic/lipid monitoring
o Psychotropics in very young children
o Diagnoses consistent with psychotropic treatment
o Services consistent with psychotropic treatment
Metric Developmento Metrics committee identifies needs with
input from all stakeholders.o Initial discussions within metrics committee
result in a draft conceptual summary. o Programming code is developed and results
of applying metric are evaluated.o Conceptual summary is presented to
stakeholder committee.o Metrics committee revisits evidence base on
a regular basis.
Initiative Under Development
o Develop 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 Development
o Develop, 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 Development
o Improve 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.