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Novel Data Sources for Quality Improvement

This Thursday I gave a presentation to the National Committee on
Vital and Health Statistics (NCVHS) about measuring quality using
“traditional” and emerging, novel sources of healthcare data.

My
definition of traditional data sources that are currently used to
measure quality includes administrative claims data aggregated from
hospital-based claims databses (for example, BIDMC has an Oracle
respository called Casemix), payer-based databases (all have a claims
warehouse to support disease management), physician organizations (Beth
Israel Deaconess Physicians Organization has worked with Heathcare Data Services to create all payer business intelligence tools ) and health data consortia (such as the Massachusetts Health Data Consortium offers de-identified aggregated claims to enable institutional comparisons)”

New
sources of data for quality analysis go beyond administrative data and
include EHR, PHR, and Healthcare Information Exchange resources. Here
are a few examples:

*At BIDMC all our laboratory, radiology,
pharmacy and care process data is available in business intelligence
datamarts. We use these internally for scorecards, benchmarking and
workflow improvement projects.

*Massachusetts has a long history
of payer/provider collaboration, such as NEHEN. Recently, the Eastern
Massachusetts Healthcare Initiative (EMHI) has developed a new set of
clinical data exchange use cases to support regional payer/provider
collaboration. One of those use cases is the automated exchange of
quality data via a secure publish/subscribe web service that eliminates
the need for providers to create bulk data extracts for payer quality
measures.

*The Massachusetts eHealth Collaborative has created a
quality data warehouse for its 600 participating clinicians. This
warehouse is so good that the BIDMC Physicians Organization (BIDPO) has
elected to use it for aggregating the quality measure data on its
physicians.

*Surescripts/Rx Hub provides national medication list data that is helpful for clinical care and quality measurement

*Commercial
labs such as Quest and LabCorps are implementing HITSP standards for
lab transactions which include the data elements needed for
biosurveillance, public health reporting and quality analysis.

*The Social Security Administration’s Megahit pilot
demonstrated automated submission of electronic medical records between
hospitals and the SSA with patient consent to improve turn around time
for disability claims adjudication.

*The Centers for Disease
Control has implemented Biosense, an automated surveillance system for
detecting variations in disease frequency using de-identified emergency
department and hospital data.

*The Massachusetts Medical Society
is working with the Massachusetts eHealth Collaborative (MAeHC) to
pilot quality scorecards for its members using the MAeHC quality
warehouse.

*Departments of Public Health in Massachusetts
receive automated data feeds from local hospitals to enable early
detection of outbreaks

*The AEGIS system
developed by Children’s hospital uses automated data feeds from
Massachusetts hospitals to create real time influenza prevalence maps

*A new generation of consumer healthcare devices from the Continua Alliance enables remote monitoring of patients in the home, transmitting data to EHRs and PHRs.

*Personal
Health Records includes those tethered to an EHR, those sponsored by
employers, hosted by health plans and vendor-based systems such as
Microsoft HealthVault and Google Health enable patients to aggregate,
enter, and manage their own data. PHRs may be an appropriate way to
measure quality by asking the patients to subscribe/contribute their
data to quality measurement organizations. The trusted third party
model in Google enables patients to share data with their consent. Some
patients may feel altruistic enough to contribute their data for
quality measurement.

*Google Trends
shows search term trends over time. This can be used to quantify
searches on symptoms such as flu-related illnesses, providing early
detection of changes in the frequency of users searching for
fever/cough/flu etc. It would be interesting to track the Google trend
for searches on Chest Pain/Heart attack before and after the
introduction of Vioxx as measure of pharmaco-vigilence.

*As part
of the Clinical and Translational Science Awards, all Harvard Medical
School affiliates must work together as single virtual unit, sharing
data for clnical research. SHRINE
is an innovative, web-services based federated data mining tool that
enables clinical research among all the data at all Harvard hospitals
with appropriate privacy protection and IRB oversight.

All of
these new approaches go behind claims data to provide novel indicators
that can be used to measure quality. I predict that all these novel
sources of data will become increasingly important as stimulus funds
become available and clinicians are incentivized based on quality, not
quantity, of care delivered.

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I don’t know that I’d call the electronic medical records transfers to and from Social Security a megahit, but Astrue has done a great job with Social Security Disability so far. Still a long way to go.