By M. Evan Hétu, senior vice president, data & analytics at Altegra Health
Although more than half of hospitals have invested in at least basic electronic health record (EHR) technology, [1] we, in the US, are in the infancy of leveraging this data to improve care quality and reduce costs. Accessing this EHR information for analysis and delivering meaningful reports to providers and administrators is still not a reality for many organizations.
Some EHR vendors offer analytics tools; however, choosing analytics technology tethered to one EHR system may pose interoperability challenges if the organization needs an enterprise-wide view of their performance or a continuum-wide view of their patients’ care. Similarly, in an era where organizations must accept more financial risk, the chosen technology must also be able to analyze different sets of financial and claims information in addition to clinical data from EHRs. The plethora of data—and limited internal resources to manage it—means choosing the right data analytics partnership will be essential to obtaining immediate, actionable information, as well as confidently setting long-term data analytics goals. Yet, with dozens of vendors to choose from in the data analytics space, picking the right partner takes careful consideration.
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By M. Evan Hétu, senior vice president, data & analytics at Altegra Health
Although more than half of hospitals have invested in at least basic electronic health record (EHR) technology, [1] we, in the US, are in the infancy of leveraging this data to improve care quality and reduce costs. Accessing this EHR information for analysis and delivering meaningful reports to providers and administrators is still not a reality for many organizations.
Some EHR vendors offer analytics tools; however, choosing analytics technology tethered to one EHR system may pose interoperability challenges if the organization needs an enterprise-wide view of their performance or a continuum-wide view of their patients’ care. Similarly, in an era where organizations must accept more financial risk, the chosen technology must also be able to analyze different sets of financial and claims information in addition to clinical data from EHRs. The plethora of data—and limited internal resources to manage it—means choosing the right data analytics partnership will be essential to obtaining immediate, actionable information, as well as confidently setting long-term data analytics goals. Yet, with dozens of vendors to choose from in the data analytics space, picking the right partner takes careful consideration.
To find the ideal vendor for an organization, leaders should ask the following five questions of the prospective companies to ensure that the firm chosen will enable their organizations to perform the data analysis needed to help providers improve clinical quality and the overall organization to better control costs:
- How will the technology help us meet our specific program goals? Asking this question means organizations will need to perform some internal due diligence to determine their specific clinical and financial goals, which may vary depending on the relevant health insurer program. There are countless commercial and government accountable care and other types of programs that financially reward organizations for achieving certain clinical quality metrics and/or controlling costs. While many programs include similar care quality or financial metric requirements, determining the precise data points will be crucial so the vendor can locate this data in the organization’s information systems and demonstrate how the firm’s technology can extract and deliver the analysis to the organization.
- How can your technology help us manage our risk? Effectively managing high-risk patients is essential for succeeding in any clinical quality improvement or risk-based payment program. The data analytics vendor chosen should prove how it can delve into an organization’s clinical, financial and demographic data to create timely reports listing these high-risk patients and deliver insight such as clinical care gaps and who is most likely to respond to a clinical outreach and which intervention would be most effective. This type of predictive analytics capability requires leveraging sophisticated algorithms unavailable from many vendors.
- How will the technology integrate with our current systems? Healthcare organizations operate using many different information technology systems from numerous vendors, even within the same facility. Each software system, whether in the hospital, outpatient clinic or rehabilitation facility, captures patient data that could be beneficial for the organization in improving care quality metrics. A single vendor that can integrate data from these disparate systems is essential for the most accurate and comprehensive analytics.
- How can we verify accuracy? Data transparency should be required from any data analytics vendor because the reports generated from the technology will likely be used to adjust physician behaviors. If physicians are skeptical about the data source or accuracy of their performance reports, then modifying their behavior becomes much more challenging. Clearly demonstrating to physicians that the analysis is based on data from their charts, as well as claims and other data subsets that originated from their department or clinic, will be much more effective in facilitating collaboration and trust.
- How can this analysis be accessed at the point-of-care? Likewise, physicians will need clinical quality reports on-demand to support clinical decision making while the patients are in the exam room. The data analytics technology should display this timely information to providers in a meaningful, actionable format directly in an EHR as a suggestion for treatment or reminder for services. This analysis would include not only the information from the physician’s chart, but also data extracted from other providers, such as discharge summary data from a hospital. Analysis based on data captured from the continuum of care offers physicians greater confidence in forming their diagnosis and treatment plan decisions.
Applying the knowledge
Choosing a data analytics vendor and implementing the firm’s software is just the beginning. The insight delivered by this technology may compel the organization to undergo challenging enterprise-wide initiatives to improve care quality and operational efficiency. The right data analytics technology, however, should make this process easier for the organization by helping them track their progress toward the finish line.
About the author:
M. Evan Hétu is senior vice president, data & analytics Altegra Health
[1] Julia Adler-Milstein, Catherine M. DesRoches, Michael F. Furukawa, Chantal Worzala, Dustin Charles, Peter Kralovec, Samantha Stalley, and Ashish K. Jha. “More Than Half of US Hospitals Have At Least A Basic EHR, But Stage 2 Criteria Remain Challenging For Most.” Health Affairs August 7, 2014. Online. http://content.healthaffairs.org/content/early/2014/08/05/hlthaff.2014.0453