healthcare executive search

 The possible lack of a healthcare specific, compliant, cost-effective way of Enterprise Information Management (aka EIM) could be the #1 reason integration, data quality, reporting and performance management initiatives fail in healthcare organizations. How will you build a house without plumbing? Conversely, the organizations that successfully deploy exactly the same initiatives indicate full Healthcare centric EIM whilst the Top reason they certainly were successful (February, 2009 - AHA). The expense of EIM can be staggering - preventing many healthcare organizations from leveraging enterprise information when strategically planning for the whole system. If that is prohibitive for big and medium organizations, how are smaller organizations planning to have the ability to leverage technology that could access vital information within their particular company if cost prevents consideration?

The Basics -healthcare executive search

What is Enterprise Information Management?

Enterprise Information Management means the corporation has access to 100% of its data, the information 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 for instance an EHR data warehouse, Business Intelligence and Performance Management. Listed here is a roadmap, in layman terminology, that healthcare organizations follow to find out 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 maintain silos, not accessible by other groups or departments, sometimes within the team that's responsible for it. If information were needed from groups across the enterprise, it must be requested, in operation terminology, of the host group, who'd then visit the foundation 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 use (i.e., excel for further analysis in place of a document or PDF).

Fact #2: Because business terminology can differ WITHIN an organization, you will have further "translating" required when incorporating information that's gathered from the various software packages. This can be quite a nightmare. The gathering of information, converting it right into a different format, translating it into common business terminology and then preparing it for consumption is a long, expensive process - which takes us to Fact #3.

Fact #3: Consumers of the gathered information (management, analysts, etc) have to alter the type of information required - one-off report requests which 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 rather than lining up red, they would really like green to be grouped first). Oftentimes, this may start the gathering process yet again because the original set of information is missing needed data. It also requires the interest of those who appreciate this information - typically a highly valued Subject Matter Expert from each silo - time-consuming and costly distractions that impact the requestor along with the info owner's group.

Fact#4: While large organizations can cope with this specific costly method in order to gather enough information to create effective and strategic business decisions, the quantity of time and money is just 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 beneficial and costs with time and money are significantly reduced.

Integration (with cleansing the information, aka Data Quality) should not be considered 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 predicated on being limited from technology because of price tag, bars the consideration of EIM. Here is the fault of technology vendors. Business Intelligence, Performance Management and Data Integration providers have unknowingly created class warfare involving the Large and SMB healthcare organizations. Data Integration is the greatest culprit in this situation. The expense of integration in the typical BI deployment is generally four times the price of the BI portion. It is easy for the BI providers to tantalize their prospects with functionality and reasonable cost. But, when integration is necessary, reluctance on price introduces itself to the scenario. No action has become the norm only at that point.

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

Fraud detection could be the focal point for CMS within their EHR requirements of healthcare organizations, Let's take a deeper, more meaningful consider the impact of EHR. Integration, a prominent component of Enterprise Information Management in the New Approach, brings data from all silos of the corporation, allowing a Data Quality element of verify and cleanse it. The next phase would be to either send it back again to its originating source in a precise state and/or use it right into a repository where it is going to 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? Below are a few elements to consider:

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

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

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

One overlooked but common impact is in the price of managing patient records. Thousands of file folders in storage with new instances being added everytime a new patient enters to the system. Millions of bits of paper capturing patient information, payer data, charts, billing statements, and various items such as for instance 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 utilized for extra services, setting up new channels of revenue. The justification is easy: how much would it cost a healthcare facility to build out 15,000 square feet for a new service? The typical 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 significantly less than 20% of that. Not just has got the EIM solution reduced dollars lost to fraud, lowered the occasions for payor encounters to be paid, increased cash readily available, but it will also open up new services for the patient community and revenue back again 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 within an incompatible format, changes in-front end applications and fraud, such as for instance identity theft. The impact of bad data has a cause and effect relationship that's pervasive in the financial landscape: healthcare executive search

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 quantity of Cash on Hand along with extends the cycle of submitted claim to remittance by at least 30 days.