Profitability By [Fill in the Blank] Using the MEDITECH DR and SQL Analysis Services to Quantify...
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![Page 1: Profitability By [Fill in the Blank] Using the MEDITECH DR and SQL Analysis Services to Quantify Profitability By Glen R. DAbate Acmeware, Inc.](https://reader036.fdocuments.us/reader036/viewer/2022070305/551436b05503466d1a8b52ee/html5/thumbnails/1.jpg)
Profitability By [Fill in the Blank]
Using the MEDITECH DR and SQL Analysis Services to Quantify
ProfitabilityBy Glen R. D’Abate Acmeware, Inc.
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Objective
To develop a SQL Query Analyzer-based On-Line Analytical Processing (OLAP) Cube that will provide information about profitability measures across a wide variety healthcare business parameters
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Project Design Environment MEDITECH Data Repository MAGIC 4.9 on SQL
Server 2000 MEDITECH ADM, ABS, B/AR, & CA Applications Cost Accounting data could be provided by a
third party with minor modifications SQL Server Analysis Services Implemented on
DR Server Internet Explorer 6.0 used to browse the OLAP
cube on an ASP.NET web page that resides on Internet Information Server (Web-Server)
We could also use Microsoft Excel to browse cube
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Project Design Strategy Identify OLAP Measures Identify OLAP Dimensions Build SQL Server View with Fact Table
Containing Measures and Foreign Keys to Dimensions
Build SQL Server Views for Dimension Tables
Construct OLAP Cube and Process it Deploy Cube to Web Page
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OLAP Measures A set of values that are based on a
column in the cube's fact table and are typically numeric
In our cube: Count of Visits Receipt Total Cost Total Charge Total Expected Reimbursement Profitability (Calculated Total) Expected Profitability (Calculated Total)
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OLAP Dimensions The ways by which would like to break out and
view the measures “slice and dice” Dimensions often correspond to MEDITECH
dictionaries Time Dimension are treated special in Analysis
Services and can be defined with a hierarchy (i.e., Year / Quarter / Month / Day)
Dimensions can have a hierarchy (i.e., MDC -> DRG, ProvderGroup -> Provider, InsuranceGroup -> Insurance)
Dimension are limited to 64K entries at any hierarchical level. As a results, to use AccountNumber, we must associate it in a DischargeDate -> AccountNumber hierarchy
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Dimensions In This Project: Admission (Inpatients) or Service (Outpatients)
Date Transaction Procedure Charge Category Diagnosis Discharge Disposition Discharge (Inpatients) or Service (Outpatients)
Date AccountNumber Facility Final DRG Financial Class Insurance Location Patient Status Attending Provider ServiceThere are dozens of other potential dimension fields that could have been selected for this project
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Fact Table The central table in the OLAP schema that
contain the numerical Measures and Foreign Keys relating facts to the Dimension tables
A SQL Server View is used to bring together data from multiple tables in the DR to a single Fact table
All columns in the Fact table should have data values. NULL data must be substituted with a value (“<U>”)
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DR Tables used in Fact Table BarVisits (demographics) BarVisitProvider (Attending Provider) AbsDrgData (Final DRG) BarChargeTransactions (Charges, Charge
Category, Transaction Procedure) BarCollectionTransactions (Receipts) CaStandardCosts (Costs) BarInsuranceLedger (Expected
Reimbursement)
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Fact Table View (Foreign Keys)
If there is any chance that a NULL value could be present, replace it with ‘<U>’
Append leading zeros to DRGs to display in a more typical form
Use only left component of the diagnosis
For dates, use an integer identifier in dimension and fact tables
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Fact Table View (Measures)
UNION
UNION
Expected Reimbursement is at the Visit level, not the Transaction Level
Receipts and Adjustments come from Collection Transactions
Charges come from Charge Transactions
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Dimension Table ViewExample Dimension View for the Location Dimension
Use the MIS Dictionary with Locations
The LocationID and Name are concatenated together when more detail is required in the cube
‘<U>’ is included via a UNION in all dimension to account for any NULL values
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SQL Analysis Manager
Dimension are defined in a wizard using the Views that were set up in SQL Server
Data Source Links to DR ‘livedb’
Profitability Cube Defined
Once SQL Views are defined, SQL Analysis Manager is used to construct the Profitability cube and related components
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OLAP Cube Components
Data Source Fact Table Dimension Tables Measures Calculated Measures Design Storage Schema
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Select the DR Server
Select Security Profile
Select Cube Database
Tool for Building Cubes
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Entering a Cube using the Cube Editor
Fact Table
Dimension TablesAnalysis Services has useful Wizards that assist in configuring the cube
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Measures are available from the Fact table (View) and are inserted into the cube definition
Adding Measures to the Cube
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EXPECTED REIMBURSEMENT – COSTS
COSTS
How to compute Profitability?
RECEIPTS – COSTS
COSTS
Expected Profitability?
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Adding Calculated Members
Formula expression for Profitability added to Cube
All Cube data and many pre-defined functions are available in the Calculated Member Builder
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Cube Design Storage Options
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Browsing Data in the Cube Editor
The Analysis Server provides a rudimentary browser to give a quick ‘reality check’ that the cube is compiling correctly
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Deploying the Cube in Visual Studio
It is also possible to deploy cubes using SQL Server Reporting Services, albeit a bit cumbersome
Visual Studio .NET solution. Originally deployed as Visual InterDev 6.0 Solution
ActiveX Control – Pivot Table 10. 0 Office Component
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Web Page with Cube on Internet Information Server
Visual Studio .NET project is deployed to an instance of IIS
This example includes the Active Server Page (ASP) with the Profitability Cube ActiveX control within a Web Application (AcmeView) that has other OLAP Cubes
AcmeView Web Application in IIS
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Browsing the Cube using IE