Data Due Diligence in Strategic Acquisitions, Mergers and Partnerships

The healthcare industry continues to turn out a steady number of conventional and unconventional partnerships, mergers and acquisitions in response to an ever-shifting, increasingly competitive market. Under pressure to transform the way they do business, leaders are turning to new affiliations to scale operations, increase access to technology and attract patients and employees.

With every deal comes the complex and difficult task of evaluating potential business partners. In the due diligence process, ample resources are devoted to analyzing finances, operations, regulatory issues and the compatibility of mission, vision and culture.

The area most organizations fail to fully scrutinize and plan for is data. In most cases, data integration planning is handled after the acquisition when it should be accounted for in the pre-acquisition phases of a deal.

In a Huron survey of healthcare executives, merger and acquisition (M&A) activity and industry consolidation, along with data concerns, topped the list of trends impacting healthcare leaders. In the next three to five years, leaders will heavily prioritize building data structures for better decision making.

Similarly, a survey of ambulatory healthcare leaders revealed that data is the leading concern as organizations acquire assets such as large physician group practices, urgent care centers and clinics that they need to move care outside the hospital.

Like many other industries, the exploding potential of data in healthcare is the source of tremendous opportunity and challenge. This becomes even more true as organizations consolidate and bring their data — for better or worse — with them.

When an organization acquires another entity, they are getting more than a facility and patient care setting. They are acquiring significant data resources (e.g., electronic health records, facility and professional billing, admissions and discharges, human resources and enterprise systems data) that should be treated like an asset and planned for accordingly.

Organizations are aware that data is critical, yet healthcare information technology is the area where organizations often end up the least prepared in acquisitions or integrations. An appropriate data plan upon acquisition will lead organizations further down the path to becoming a consumer-centric, digitally enabled health system.

Below are four important questions that leaders should answer in pre-integration planning:

How will data and information be distributed across the network?

Disparate underlying platforms will present a challenge as organizations transition and merge. A significant amount of pre-integration planning should be focused on how data will be presented in a consistent platform and distributed to as many people as possible. To achieve that, cloud migration should be part of any data integration strategy. Cloud migration prevents overstressing existing physical infrastructures. Acquisitions leave organizations open to increased security threats or cyberattacks. Cloud technology helps safeguard organizations during a time of transition. In addition to moving new data assets to the cloud, organizations have to move quickly to fold new facilities into their cybersecurity and analytics program.

Healthcare systems should have a facility technology plan in place that outlines how they will support their view of a digital health system, and how they will achieve the largest possible digital footprint at the lowest cost.

How seamlessly information is distributed to those who need it will also determine how well an organization is able to build a data-focused culture that will ultimately drive consistency of care and quality of clinical outcomes enterprisewide.

What approach will be taken to integrate disparate systems?

Post-acquisition, there are three basic approaches to unite data: connect systems, merge systems or play a “wait-and-see” game where entities continue operating independently with their disparate systems. Focus should be on connecting systems as a steppingstone to merging.

Organizations need a master data management system, which provides a way to feed data through the health system. Then, they can begin establishing consistency and create a data model that works across enterprise resource planning (ERP) systems, electronic health records (EHRs) and customer relationship management (CRM) systems. Without data due diligence and consistency in the data models, an organization cannot present a consistent experience to patients.

Can the data be trusted?

Bad data is costly and unsafe in an industry increasingly focused on leveraging the power of applications such as predictive analytics and artificial intelligence. Data in both the source and target systems needs to be profiled carefully to ensure that it meets established business rules.

Organizational data maturity progresses from siloed data to departmental data and finally to enterprisewide data efficacy. Often organizations purchase facilities with much lower levels of data maturity than their own and, therefore, should have a lower level of trust in the acquired data. An additional layer of scrutiny should be applied to acquired data to determine what will be brought into or excluded from the enterprisewide data system.

Is a firm data governance plan in place?

The data governance model or plan is critical to data quality and to creating a technical infrastructure that can scale adequately. Every step of a digital and data integration road map should point back to governance. Prioritize the creation of a data governance team that will regulate where and how data can flow through the organization. That team should include physician champions or end-user clinicians in addition to finance, IT and administration. The data governance team must have a clear charter that outlines its scope of authority as well as the expectations placed on each member.

Data is one of the largest but often underanalyzed assets that accompanies healthcare mergers, acquisitions and partnerships. Planning fully for data integration in the due diligence phase of a deal is critical to realizing value faster and achieving an organization’s M&A goals.