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Customer Story

Data Strategy Eases Data Integration After Mergers & Acquisitions

About

The healthcare provider has recently grown through a series of mergers and acquisitions to include services across three separate lines of business—Personal Care Services, Home Health, and Hospice—but under one umbrella of complete care. This puts them in a unique position to provide continuity of care to patients who over time require increasing help and service. It also puts them in the position to grow the business and reach more patients across the country.

Goals

With recent acquisitions, as well as the company’s continued expected growth, comes the inheritance of disparate systems, data, and technologies—each with their own set of best practices, terms and definitions, and processes. As a result, their analytics ecosystem was disjointed and not providing them with the insights they needed.

Their goal was to implement an enterprise data and analytics solution that would provide their separate lines of business with a common, combined set of data and tools to provide critical care to their patients.

They engaged with Analytics8 to modernize their data architecture and implement a data strategy that will grow with the business and its data and analytics needs.

Solution

We conducted a data and analytics strategy assessment of the company’s business, data processes, and technology stack and developed a data strategy roadmap outlining how to integrate data from the healthcare provider’s multiple systems into a cloud-based platform to allow for unified analysis across the company.

The modern data architecture included Snowflake, Fivetran, and dbt, offering a simplified user interface with minimal maintenance requirements; a flexible and collaborative data transformation platform, and automation—all things the healthcare provider needs as they scale and grow their business.

We also created standardized data definitions, as well as the framework for a data governance program so that users across the company define metrics and KPIs the same way and use terms consistently—something that will assist in troubleshooting and problem-solving during analysis.

Results

The modern data architecture we designed and built allows the healthcare provider to move from untrustworthy data and scattered analysis to being able to draw insights from a unified dataset about all its patients and employees. They can now:

  • Spend less time manually manipulating data and focus instead on drawing insights regarding employee headcount, pay and overtime rate, as well as turnover and retention metrics—information that will lead to making better decisions around employee hiring, compensation, and retention across the board so that they can provide the care patients depend on when they need it.
  • Combine disparate data sources into single unified tables and view employee data for the last 13 months across all acquisitions/business units in one unified view.
  • Provide access to trustworthy data across the organization as users can see data lineage and better understand the relationship between data sources and tables. This is especially helpful for non-data engineering users such as BI developers so that they can understand the data they are using in the dashboards that they are building.

This information will allow the healthcare provider to continue to deliver excellent care to patients as the company grows and expands its reach.

Get started with a data analytics consultation

Talk to an expert who will review your data struggles and help map out steps to achieve data-driven decision making.

Rooted in helping individuals, this company provides post-acute healthcare services for more than 200,000 patients, across 31 states, each year. With more than 50 years of industry experience to draw from, the company is focused on reimagining the way care is provided and prioritizing patients and their needs.

Talk with a data expert

Schedule a meeting with one of our data analytics experts who will review your data struggles and map out steps to achieve data-driven decision making.

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