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Connected Care and Analytics

Connected Care and Analytics

Healthcare delivery is rapidly reincarnate due to changes in laws, regulations, and reimbursement mechanisms. In order to survive and succeed in this stormy environment, hospitals and healthcare networks are turning to healthcare analytics to convert raw clinical and financial data into actionable knowledge they can use to improve performance, care—and the bottom line.

The WRC healthcare analytics approach leverages enterprise-level, vendor-neutral data sources to identify short- and long-term opportunities to help:

  1. Integrate and improve financial and clinical outcomes
  2. Eliminate data silage
  3. Divide knowledge across the organizations

Massive transformation changes in the healthcare industry are prompting many hospitals and networks to accept a healthcare analytics approach to ensure their survival and growth. Investment in information technology and business intelligence tools is an important first step in this process. How ever, cultivation the true value of healthcare’s massive data assets requires a change in perspective, behavior, and, most importantly, organizational culture. To succeed, organizations need to create a healthcare analytics culture that merges information technology, information management, and information behaviors at every level across the enterprise.

The shear to a healthcare analytics culture:

  1. Reduces data silage and data ownership
  2. Creates an atmosphere of inquisitiveness and collaboration
  3. Permit organizations to see beyond what has already happened and begin to forecast next

Data Analysis and Governance Is NOT only an IT Project

One of the most features of a healthcare analytics culture is that data management isn’t an IT liability, but rather an enterprise-wide one. While IT may play a pivotal role, it can’t be gearing the initiative by itself.

Chilmark Research estimates that 70% of analytics projects fail. Managing analytics like an IT project with a start, middle, and end can play a significant role in these failures. This approach focuses on technology without understanding its application and can result in:

  1. Deficient engagement of end users
  2. Insubstantial project expectations
  3. Insufficient approaches to quantify costs and performance
  4. Методы управления, которые плохо подходят для культивирования аналитики

 

An analytics culture doesn’t have a limited ending. It continues to change to keep focus on:

  1. Enterprise-level governance with sponsorship and oversight
  2. Defined outcomes accomplishment
  3. Solution adoption versus software go-live
  4. Converting planning
  5. Customer advocacy

Additionally, the most highly skilled of IT resources may lack the context and nuance needed to validate and steward clinical data. For this reason, clinicians, quality experts, and finance professionals need to have a voice in defining data standards.

In a healthcare analytics culture, responsibly for validating clinical and financial data is assigned to the stakeholders with the skillsets and expertise needed to ensure the organization uses the right information in the right context. Involving key leaders and staff members in analytics journey creates accountability and drives the cultural change needed to unite enterprise.