Aggregating Data to Enhance Decision Making

Posted by Cross Current on June 13, 2017

One of the most compelling reasons for implementing business intelligence is to support decision making with data aggregated from multiple sources.  Advances in cloud computing and technical capabilities means it is more affordable than ever to provide operational insights not offered by legacy solutions.     

Legacy application vendors have resisted importing external data to support analytics because it is difficult to manage and is outside the scope of their domain expertise.  The good news is many analytics companies specialize in aggregating and transforming data from many systems to meet specific organizational goals.  These companies identify the data needed to solve a problem and construct a data model to support it. 

In a healthcare practice, practice management systems focus on revenue and billing performance.  but don’t take into account patient satisfaction, patient outcomes, or efficiency metrics based on payroll data.

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 Office Manager KPI Workbook by Cross Current

Here is an example of a Business Intelligence tool designed to manage orthopaedic office manager performance.   This workbook designed in Tableau, measures performance based on a combination of weighted factors for managing employee efficiency, physical therapy overhead, patient experience, and exam room utilization.  Data sources include:  payroll, patient satisfaction, and practice management.   

The workbook incorporates algorithms to compute weighted scores to identify benchmarks for performance which could be used for employee bonuses and identify trends in overall organizational performance. 

Other examples in orthopaedics include: 

  • Correlating patient experience data with wait times sourced from practice management.
  • Correlating computed surgical conversion rates with likelihood to recommend scores.
  • Correlating patient outcomes data to revenue data sourced from practice management systems.
  • Correlating and trending marketing investments with revenue data.
  • Supporting Dashboard with data and KPIs sourced from Financial. Billing, Scheduling, EHR, Patient Satisfaction, and Patient Reported Outcomes
 

Key Points to Consider When Implementing 

  1. Choose off-the-shelf solutions to deliver value quickly.  A number of healthcare analytics firms are dedicated to delivering off the shelf analytic tools and delivering the data extraction and data transformation to support them.  For smaller and mid-sized practices, outsourcing offers lower deployment costs and shorter timelines to deliver value quickly with less impact on existing operations.
  2. Focus on culture and establishing baseline metrics to drive practice performance.   In the example we discussed earlier,  the practice identified 4 key efficiency metrics to define office manager success (versus the typical volume and revenue driven metrics in the past.)  
  3.  Establish baselines for performance to promote organizational objectives and uncover new insights.  Use Ad Hoc capabilities (offered with business intelligence tools like Tableau)  to drill down and customize analyses to identify root cause.  
  4. Define metrics that can be controlled by the manager, employee or physician.  Explain to staff how these metrics were defined and why they are important to the organization
  5. Prepare and Plan for potential obstacles:
  • Getting access to the data - Can you get the data from your vendor in a format that will support your BI strategy.  Most analytic vendors can let you know of these issues up front.
  • Transforming the Data - Can you automate the extraction and transformation of data easily and accurately, particularly if buying an analytics tool.  This is generally the most difficult step in implementing analytics.
  • Manipulating the Data - Does your solution offer flexibility for the end user to filter, sort, and manipulate the analyses.  Likewise, are capabilities available to perform Ad Hoc analyses with the extracted data.
  • Validating the Data - Identify Source Documents to validate the data.  Make sure you can drill down to the source data to validate the findings.

To compete in today’s healthcare environment, practices need advanced business intelligence tools that cross all their data sources.  Off-the-shelf solutions exist today to shortcut the technical hurdles that once made this a costly and time consuming process.  Practice executives should focus their efforts on building a culture by developing performance models that provide staff with performance benchmarks and data to provide insights into best practice behaviors.  

As more practices learn the skills in using their data, building superior capabilities will become a decisive competitive asset.

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Topics: business intelligence

Written by Cross Current