The New Approach to Healthcare Enterprise Information Management – EHR, EMR, EIM

The lack of a healthcare specific, compliant, cost-effective approach to Enterprise Information Management (aka EIM) is the #1 reason integration, data quality, reporting and performance management initiatives fail in healthcare organizations. How can you build a house without plumbing? Conversely, the organizations that successfully deploy the same initiatives point to full Healthcare centric EIM as the Top reason they were successful (February, 2009 – AHA). The cost of EIM can be staggering – preventing many healthcare organizations from leveraging enterprise information when strategically planning for the entire system. If this is prohibitive for large and medium organizations, how are smaller organizations going to be able to leverage technology that can access vital information inside of their own company if cost prevents consideration?

The Basics –

What is Enterprise Information Management?

Enterprise Information Management means the organization has access to 100% of its data, the data can be exchanged between groups/applications/databases, information is verified and cleansed, and a master data management method is applied. Outliers to EIM are data warehouses, such as an EHR data warehouse, Business Intelligence and Performance Management. Here is a roadmap, in layman terminology, that healthcare organizations follow to determine their EIM requirements.

Fact #1: Every healthcare entity, agency, campus or non-profit knows what software it utilizes for its business operations. The applications may be in silos, not accessible by other groups or departments, sometimes within the team that is responsible for it. If information were needed from groups across the enterprise, it has to be requested, in business terminology, of the host group, who would then go to the source of information (the aforementioned software and/or database), retrieve what is needed and submit it to the requestor – hopefully, in a format the requestor can work with (i.e., excel for further analysis as opposed to a document or PDF).

Fact #2: Because business terminology can be different WITHIN an organization, there will be further “translating” required when incorporating information that is gathered from the different software packages. This can be a nightmare. The gathering of information, converting it into a different format, translating it into common business terminology and then preparing it for consumption is a lengthy, expensive process – which takes us to Fact #3.

Fact #3: Consumers of the gathered information (management, analysts, etc) have to change the type of information required – one-off report requests that are continuously revised so they can change their dimensional view (like rotating the rows of a Rubik’s cube to only get one color grouped, then deciding instead of lining up red, they would really like green to be grouped first). In many cases, this will start the gathering process all over again because the original set of information is missing needed data. It also requires the attention of those that understand this information – typically a highly valued Subject Matter Expert from each silo – time-consuming and costly distractions that impact the requestor as well as the information owner’s group.

Fact#4: While large organizations can cope with this costly method in order to gather enough information to make effective and strategic business decisions, the amount of time and money is a barrier for smaller or cash strapped institutions, freezing needed data in its silo.

Fact #5: If information were accessible (with security and access controls, preventing unauthorized and inappropriate access), time frames for analysis improve, results are timely, strategic planning is effective and costs in time and money are significantly reduced.

Integration (with cleansing the data, aka Data Quality) should not be a foreign concept to the mid and smaller organizations. Price has been the overriding factor that prevents these tiers from leveraging enterprise information. A “glass ceiling”, solely based on being limited from technology because of price tag, bars the consideration of EIM. This is the fault of technology vendors. Business Intelligence, Performance Management and Data Integration providers have unknowingly created class warfare between the Large and SMB healthcare organizations. Data Integration is the biggest culprit in this situation. The cost of integration in the typical BI deployment is usually four times the cost of the BI portion. It is easy for the BI providers to tantalize their prospects with functionality and reasonable cost. But, when integration comes into play, reluctance on price introduces itself into the scenario. No action has become the norm at this point.

What are the Financial Implications for a Healthcare Organization by maintaining the status quo?

Fraud detection is the focal point for CMS in their EHR requirements of healthcare organizations, Let’s take a deeper, more meaningful look at the impact of EHR. Integration, a prominent component of Enterprise Information Management in the New Approach, brings data from all silos of the organization, allowing a Data Quality component to verify and cleanse it. The next step would be to either send it back to its originating source in an accurate state and/or put it into a repository where it will be accessible to auditing (think CMS Sanctions Auditors), Business Intelligence solutions, and Electronic Health Records applications. With instantly accessible EHRs, hospitals and their outlying practices can verify patients with payors, retrieve medical histories for diagnosis and treatment decisions, and update/add patient related information. What impact to treatment does a review of a new patient’s history have for both patient and practice? Here are some elements to consider:

1. Diagnosis and treatments that are based on previous patient dispositions – reducing recovery time, eliminating Medicare/Medicaid/Payor denials (based on their interpretation as to fault of the practitioner in original treatment or error incurring additional treatment).

2. Instant fraud detection of patients seeking treatment for the same malady across the practices within the organization. Prescription abuse and Medicare fraud saves money not only for the payors, but the healthcare organization as well.

3. The Association of Fraud Examiners states that 9% of a Hospital’s revenue each year is actually lost to fraud.

One overlooked but common impact is in the cost of managing patient records. Thousands of file folders in storage with new instances being added each time a new patient enters into the system. Millions of pieces of paper capturing patient information, payer data, charts, billing statements, and various items such as photo copies of patient IDs, are all stored in those folders. The folders are then stored in vast filing cabinets – constantly being accessed by filing clerks, nurses, practitioners and assorted staff. Contents of the files being misplaced or filed incorrectly. Hundreds, if not thousands, of square feet being consumed for storage. The AHA projects that an enterprise leveraging Electronic Health Records will recover no less than 15,000 square feet of usable space. That space can be used for additional services, opening up new channels of revenue. The justification is easy: how much would it cost the hospital to build out 15,000 square feet for a new service? The average cost to build space utilized for Health Services is $65 per square foot, or $975,000 total. An EIM solution through the New Approach would be less than 20% of that. Not only has the EIM solution reduced dollars lost to fraud, lowered the days for payor encounters to be paid, increased cash on hand, but it will also open up new services for the patient community and revenue back to the healthcare organization.

Electronic data is costly in its own way. Bad aka “Dirty” data has enormous impact. Data can be corrupted by error in data entry, systems maintenance, database platform changes or upgrades, feeds or exchanges of data in an incompatible format, changes in front end applications and fraud, such as identity theft. The impact of bad data has a cause and effect relationship that is pervasive in the financial landscape:

1. Bad data can result in payor denials. Mismatched member identification, missing DRG codes, empty fields where data is expected are examples of immediate denials of claims. The delay lowers the amount of Cash on Hand as well as extends the cycle of submitted claim to remittance by at least 30 days.

2. Bad data masks fraud. A reversal of digits in a social security number, a claim filed as one person for the treatment of another family member, medical histories that do not reflect all diagnosis and treatments because the patient could not be identified. Fraud has the greatest impact on cost of delivering healthcare in the United States. Ultimately, the health system has to absorb this cost – reducing profitability and limiting growth.

3. Bad data results in non-compliance. CMS has already begun the architecture and deployment of Sanctions Data Exchanges. These exchanges are a network of data repositories that are used to connect to health healthcare system, retrieve CMS related data, and store it for auditing. The retrieval will only be limited to the patient encounters that show a potential for denial or fraud, so the repository will not be a store of all Medicare and Medicaid patient encounters. But, the exchange has to be able to read the data in its provider data source in order for CMS to apply certain conditions against the information it is reading. What happens when the information is incomplete or wrong? The healthcare system is held accountable for the encounters it cannot read. That means automatic and unrecoverable denials of claims PRIOR to an audit, regardless of claim legitimacy.

The Price Fix by Big Box Healthcare Technology Firms

Are the major healthcare software and technology vendors (Big Box) price gouging? Probably not. They are a victim of their own solution strategies. Through acquired and some organic growth (McKesson, Eclipsys, Cerner, etc), they find their EIM solutions lose their agnostic approach. This is bad…very bad for health systems of all sizes. With very few exceptions, the vast majority of healthcare organizations DO NOT BUY all applications and modules from a single stack player. How could they? Healthcare systems grow similarly – some organic, some through acquisition. When a hospital organization finds over the course of time, an application that is reliable, such as a billing system, there is tremendous reluctance to remove a proven solution that everyone knows how to use. Because the major technology providers in the healthcare space act as a “One Stop Shop”, they spend most of their time working on integrating in their own product suite with little to no regard to other applications. Subsequently, they find themselves trapped: they have to position all products/modules to maintain the accessibility and integrity of their data. This is problematic for the hospital that is trying to solve one problem but then must purchase additional solutions to apply to areas that are not broken, just to be able to integrate information. That is like going to the hardware store for a screwdriver and coming back with a 112 piece tool set with a rolling, 4 foot cart built for NASCAR. You will probably never use 90+% of those tools and will no longer be able to park in your own garage because the new tool box takes up too much space!

IT resources – including people – must be utilized. In today’s economy, leveraging internal IT staff to administer a solution post-deployment is a given. If those IT resources do not feel comfortable in supporting the integration plan, then status quo will be justified. This is the “anti” approach to providing solutions in the healthcare industry: the sales leaders from Big Box technology firms want their sales people in front of the business side of the organization and to stop selling to IT. While this is a common sense approach, the economy in 2010 mandates that IT has to at least validate their ability to administer new technology solutions. The prospect of long-term professional consulting engagements to follow post installation has been shrinking at the same rate as healthcare organizations profit margins

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