Tag Archives: EMR
A lesson learned from other industries, like retail and financial services, is that while analytics and data warehouses are critical components to delivering big results from data — neither is easy. Gartner reported that 80% of data warehousing initiatives fail to meet expectations, often running over budget and failing to deliver a ROI.
- Executives are often frustrated because responses to their requests for new reports and edited reports take too long
- Misunderstood requirements and costly rework are the result of a lack of collaboration between stakeholders and IT
- BI consumers lose confidence in data; they don’t trust it because they lack transparency into its lineage and don’t understand why it appears differently after being aggregated with data from other applications
Expecting value from data without making a commiserate investment in data results in unmet expectations. Accessing data is hard, each request requires new effort, establishing enterprise standards for data quality are an enormous effort and transforming data to fit into a heterogeneous intelligence environment is complicated and time consuming.
Introducing multiple sources of data across organizational boundaries creates a need for an environment that supports effective collaboration between stakeholders and the information technology team implementing solutions to manage data. To be genuinely useful, data must be verifiable and trustworthy since only then will stakeholders have the confidence to make data-driven decisions. To realize the value of data, from Epic and beyond, IT leaders must implement business intelligence and data warehousing best practices that:
- bring data together across applications including clinical and financial data
- foster collaboration between clinicians, IT and business stakeholders
- establish trust and confidence in business intelligence and decision making.
EMR vendors have long encouraged that their EMR and business intelligence capabilities negate the need to have a plan to integrate data or implement a separate data warehousing and business intelligence. This philosophy begs the question – how can one transactional clinical application support the intelligence needs of an enterprise? Consider customer relationship management data for feeding customer driven marketing initiatives, time tracking data full of valuable employee utilization stats, payer claims data and newly acquired practices running an EMR independent of Epic… just to name a few.
With the recognition that an EMR accounts for only a fraction of the data needed for reliable and comprehensive business intelligence comes requirements to reconcile terminology and data quality standards across an increasingly large set of trading partners and stakeholders, to access data from other sources (like payroll, CRM and claims) and to migrate clinical data from legacy applications.
In fact, business intelligence and analytics are dependent on data from across the enterprise. Most clinical and financial decisions are dependent on data; great potential lies within data – making it a valuable asset. This is not a new idea. What is a newer concept is what it means to really elevate data to the status of an asset. Unlocking the potential of data as an asset requires that healthcare organizations begin to think about and invest in data in new ways; making investments beyond traditional infrastructure like databases and data storage. Healthcare organizations must make investments in the ongoing management and improvement of the data itself as they do with any other asset, like talent, buildings or their EMR – for example understanding its quality and allocating people and systems to managing it. Moving faster in this competitive climate and delivering differentiated results requires it.
Check back next week for Part II which explores treating data as an asset further.
All the talk about whether or not healthcare organizations will adopt cloud solutions is much ado about nothing – the simple fact is that they already have adopted cloud solutions and the trend will only accelerate.
The typical hospital IT department is buried under the burden of supporting hundreds of legacy and departmental systems, the multi-year implementation of at least one if not more enterprise electronic health record applications to meet the requirements of meaningful use, all the while contending with a conversion to ICD10 and a litany of other never-ending regulatory and compliance mandates. And this is happening in an economic climate of decreasing reimbursements and flat or declining IT budgets. (more…)
I had the privilege to be invited to testify to the Health I.T. Policy Committee workgroup on the topic of data quality back in November. I’ve been an advocate for the work of the committee for years and am constantly impressed with the considerable insight and genuine passion they bring to their work. The opportunity to testify, however, was my first opportunity to actually participate in the policy-making process and it certainly was both a learning opportunity for me, as well as a chance to share my thoughts on the important topic of data quality. (more…)
The widespread adoption of electronic health records (EHRs) is a key objective of the Health Information Technology for Economic and Clinical Health (HITECH) Act, enacted as part of the American Recovery and Reinvestment Act of 2009. With the pervasive use of EHRs, an enormous volume of clinical data will be readily accessible that has previously been locked away in paper charts. The potential value of this data to yield insights into what works in healthcare, and what doesn’t work, dwarfs the benefits of simply replacing a paper chart with an electronic system. There’s appropriate enthusiasm that this data is going to be a veritable goldmine for enterprise data warehousing, business intelligence, and comparative effectiveness research. However, there are other, equally valuable, uses for this data to enhance clinical decision-making and improve the value of healthcare spending. Simply having instant access to large volumes of data that span thousands or tens-of-thousands of physicians, hundreds-of-thousands of patients and millions of encounters, offers an unparalleled opportunity to increase the quality and lower the cost of healthcare. (more…)
I’ve been advocating for years that replacing the paper chart with an electronic system is not the value of the EHR, but rather collecting data that can be used to understand and improve care. So I was very pleased to see Dr. John Showalter’s blog address this very issue – making a compelling case with real-world examples where wisdom derived from data has made demonstrable improvements in healthcare quality and corresponding reductions in cost. (more…)
Richard Cramer, Chief Healthcare Strategist for Informatica shares some views on Electronic Health Record (EHR) adoption, including HITECH and Meaningful Use pressures. He also talks about the challenges that the future holds for EHRs.
Visit Informatica’s Healthcare pages for more on EMRs.
I had the good fortune to work in the information services department at UMass Memorial Healthcare for several years prior to joining Informatica. It was pretty clear when I was there that the investments UMass Memorial was making in information systems was the future direction of healthcare everywhere, and that the lessons being learned there had applicability across the broader healthcare market. Since joining Informatica, I have had the opportunity to meet with a wide cross section of our healthcare customers and prospects, and I can confirm that this is in-fact absolutely true. A good case in point is the recent discussion I had with Karen Marhefka, Associate CIO at UMass Memorial, about the challenges of poor data quality and the adverse impact this can have on migrating existing data to new applications. (more…)
Richard Cramer, Chief Healthcare Strategist at Informatica talks about protecting healthcare data in non-production testing environments.
Reposted with permission
Shahid Shah’s healthcare IT, EMR, EHR, PHR, medical content, and document management advisory service. Enjoy.
Join me for a free webinar on “Understanding the Escalating Data Challenges of Meaningful Use” on Thursday, April 7th
I’ve been doing a good deal of coaching and consulting on what Meaningful Use really means to technology professionals lately so I was pleased to accept an invitation by Informatica to lead a webinar on that subject for a data management audience.
Data management professionals and the executives that they report to have now had enough time to learn how difficult meeting the escalating requirements for MU actually is; most are reporting that it’s been more work than they thought. Gone are the days when health systems thought they could just install a certified EHR and they would be able to meet the MU goals. Everyone now understands that even if they’re able to collect the measures required in the first phase of MU, the escalating data challenges of later phases will be more difficult. (more…)