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Making Music with Data

March 30, 2009
by Brian Wells
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Knowing your CDA score can help harmonize disparate data pools that arise from mergers and consolidations

Mergers, acquisitions and consolidations regularly introduce new challenges for healthcare managers and administrators - a pattern we're likely to see increase in our present economic climate. For example, merging and consolidating hospitals often use different information systems and data vocabularies for key markers such as providers, allergies, and drug formularies. As a result, many medical centers must shoehorn differently organized data into a common warehouse, as well as combine dissimilar information systems into coherent, manageable wholes. We, at Penn Medicine, were one of them.

Brian Wells

Brian Wells


Penn Medicine, based in Philadelphia, is made up of the University of Pennsylvania School of Medicine and the University of Pennsylvania Health System, (UPHS) which includes three hospitals - the Hospital of the University of Pennsylvania, Pennsylvania Hospital and Penn Presbyterian Medical Center.

In the past year, following a series of network expansions and additions, we faced the need to assimilate separate information systems. Our first step was to determine what we called our clinical data aggregation (CDA) score (see page 50). A CDA score helps establish baseline knowledge across the health system as a first step toward harmonizing disparate data pools. CDA score assessments can also yield information to help correct source-system errors, maintain vocabulary server mappings, and monitor workflow process changes to ensure data quality and completeness.

The Penn Medicine experience

At Penn Medicine, we embarked on the creation of an aggregated data warehouse - we called it Penn Data Store - in 2007. Our goal? A single data repository with all patient, administrative, financial, and supply chain data mapped to a standard data model and vocabulary. We created a number of objectives in support of the goal in areas such as research, finance and patient care.

At the outset, we focused on clinical data sources because of their wide applicability and key to improving patient outcomes. For example, knowing the average length of stay for a given diagnosis is necessary for reducing it. However, determining why lengths of stay are high requires data on such measures as drug administration timing, infections and patient falls. Such data is generally only available in clinical systems or paper charts.

Based on our experience, we came up with five questions to consider when developing or refining your own plans for a unified clinical data warehouse, questions that can be clarified through an assessment of your CDA score.

1. Which patient data are housed on common electronic systems by function across entities?

Most major medical centers have many parts: hospitals, specialized centers, physician practices, home health agencies, etc. A given patient may have critical data stored in four or five places on four or five systems. Getting convenient access to this data is crucial. The obvious solution is common EMRs across all entities, yet even that is not enough. Data models, field values, and patient identification techniques also need to be the same even if a common EMR is in use. Your CDA score can identify gaps in these areas.

2. Which administrative and clinical vocabularies are consistent across systems and entities?

While data can be mapped from source-system values to data-warehouse values, this process slows down the ability to provide near real-time data in the warehouse and requires constant vigilance over the mapping process to ensure consiste ncy. Switching context between the warehouse and real-time systems also creates room for error and misinterpretation. This section of your CDA score can help direct efforts in rectifying divergence in your administrative and clinical vocabularies.

Clinical Data Aggregation (CDA) scoring tool

Average Score

0%

Dimension

Significance

Percentage Calculated Score

Percentage of Patients on Electronic Common Clinical Systems by Function across entities

0%

Patient Registration

1

0%

Patient Scheduling

2

0%

Inpatient CPOE

1

0%

Inpatient EMR

1

0%

Outpatient EMR

1

0%

LAB

2

0%

Radiology

2

0%

Pharmacy

1

0%

Emergency Room

2

0%

Operating Room

3

0%

Anesthesia

3

0%

Infection Control

3

0%

Patient tracking

3

0%

Percentage of consistent vocabularies in administrative and clinical systems

0%

Race

1

0%

Religion

3

0%

Gender

1

0%

Marital Status

2

0%

Pages

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