Tag Archives: data integration

Integrating Group Life and Voluntary Benefits

Group and voluntary benefits providers vary in a hundred different ways. If you are a supplementary benefits provider that only provides one product to the group market, your data integration issues with multiple brokers and employers may still be complex. The more products you sell into the group and voluntary space, the more difficult your data integration will be.

Let’s say that your organization carries group life, voluntary supplemental life, dependent life, LTC and AD&D products. Without modernization, it is likely that your organization will have several hurdles to surmount. The first is to develop one consolidated repository from all of the data that is likely held on multiple systems. The second is to make that set of data available to the many different people and institutions that have a vested interest in access. On the flip side, insurers need to be able to receive data efficiently, as well. Carriers must be able to import data received from various benefit partners into their source systems through a single point of entry. Without this, entry or import issues could lead to benefit integrity issues, where data is are correct on one platform but incorrect on another. These types of basic data errors will quickly erode relationships with employees and benefit partners.

One way to help alleviate potential data issues is for insurers to focus on providing simple products with simple rate structures. Focus on guaranteed issue limits. Anything that has to be approved or underwritten after payroll deductions begin will cause deduction and billing issues. An exception could be made if an insurer is able to provide automated underwriting decisions at the point of sale.

The data requirements for employers and enrollment partners vary widely (in part because no standards exist), which places more of the data integration responsibility on individual carriers to interact with individual employers or benefits companies. So, the easier it is for your IT teams or vendor partners to make those connections, the better off you are likely to be when it comes time for an employer to renew their contracts. It makes sense to pursue a course that keeps your systems agile.

What about a fresh start?

When it makes sense, we regularly recommend that, instead of attempting to migrate current and past business to a new platform, insurers start fresh with a new system dedicated solely to the one program. If an insurer is moving into a new market or launching new products, why not learn from past system issues and product issues and embrace a clean slate, eliminating the need to translate and carry cumbersome legacy programming into a new environment? Start with a brand new set of products and filings, a brand new marketing plan…perhaps even a brand new name to signify the difference.

Within group and voluntary benefits, this approach makes its case when looking at just a few of the benefits, including simplified testing, fewer resources required to launch, less expense, less risk to the old system and old data and dramatically increased flexibility in data usage, capability development and integration points. Managers who touch the system are far more likely to trust the data they see, reducing a “checks and balances” approach to billing, reconciling, correspondence and a dozen other areas where the need for clean data and quick visualization are essential.

We’ll discuss more about data strategies in the coming months, including ways you can build effective technology bridges and keep a high level of data integrity.

7 Ways Your Data Can Hurt You

Your data could be your most valuable asset, and participants in the workers’ compensation industry have loads available because they have been collecting and storing data for decades. Yet few analyze data to improve processes and outcomes or to take action in a timely way.

Analytics (data analysis) is crucial to all businesses today to gain insights into product and service quality and business profitability, and to measure value contributed. But processes need to be examined regarding how data is collected, analyzed and reported. Begin by examining these seven ways data can hurt or help.

1. Data silos

Data silos are common in workers’ compensation. Individual data sets are used within organizations and by their vendors to document claim activity. Without interoperability (the ability of a system to work with other systems without special effort on the part of the user) or data integration, the silos naturally fragment the data, making it difficult to gain full understanding of the claim and its multiple issues. A comprehensive view of a claim includes all its associated data.

2. Unstructured data

Unstructured documentation, in the form of notes, leaves valuable information on the table. Notes sections of systems contain important information that cannot be readily integrated into the business intelligence. The cure is to incorporate data elements such as drop-down lists to describe events, facts and actions taken. Such data elements provide claim knowledge and can be monitored and measured.

3. Errors and omissions

Manual data entry is tedious work and often results in skipped data fields and erroneous content. When users are unsure of what should be entered into a data field, they might make up the input or simply skip the task. Management has a responsibility to hold data entry people accountable for what they add to the system. It matters.

Errors and omissions can also occur when data is extracted by an OCR methodology. Optical character recognition is the recognition of printed or written text characters by a computer. Interpretation should be reviewed regularly for accuracy and to be sure the entire scope of content is being retrieved and added to the data set. Changing business needs may result in new data requirements.

4. Human factors

Other human factors also affect data quality. One is intimidation by IT (information technology). Usually this is not intended, but remember that people in IT are not claims adjusters or case managers. The things of interest and concern to them can be completely different, and they use different language to describe those things.

People in business units often have difficulty describing to IT what they need or want. When IT says a request will be difficult or time-consuming, the best response is to persist.

5. Timeliness

There needs to be timely appropriate reporting of critical information found in current data. The data can often reveal important facts that can be reported automatically and acted upon quickly to minimize damage. Systems should be used to continually monitor the data and report, thereby gaining workflow efficiencies. Time is of the essence.

6. Data fraud

Fraud finds its way into workers’ compensation in many ways, even into its data. The most common data fraud is found in billing—overbilling, misrepresenting diagnoses to justify procedures and duplicate billing are a few of the methods. Bill review companies endeavor to uncover these hoaxes.

Another, less obvious means of fraud is through confusion. A provider may use multiple tax IDs or NPIs (national provider numbers) to obscure the fact that a whole set of bills are coming from the same individual or group. The system will consider the multiple identities as different and not capture the culprit. Providers can achieve the same result by using different names and addresses on bills. Analysis of provider performance is made difficult or impossible when the provider cannot be accurately identified.

7. Data as a work-in-process tool

Data can be used as a work-in-process tool for decision support, workflow analysis, quality measurement and cost assessment, among other initiatives. Timely, actionable information can be applied to work flow and to services to optimize quality performance and cost control.

Accurate and efficient claims data management is critical to quality, outcome and cost management. When data accuracy and integrity is overlooked as an important management responsibility, it will hurt the organization.

Even More Tips For Building A Workers Compensation Medical Provider "A" Team

Fact
Significant dollars can be saved by getting injured workers to the best doctor. Evidence supporting this fact is the mounting Workers' Comp industry research clearly stating treatment by well-informed and well-intentioned medical doctors results in lower costs and better outcomes.

Belaboring A Point
As repeatedly stated in this series, many doctors in networks are not well-informed or well-intentioned regarding management of Workers' Comp claimants. As a consequence of their involvement, claim results are lacking, costs are high, and outcomes are precarious. This series of articles, “Tips for Building a WC Medical Provider A Team,” is intended to describe how to identify doctors who know the ropes in Workers' Comp using indicators in the data.1

Beyond the indicators discussed in the previous articles in this series, additional salient data elements are available in the data to broaden the scope of medical management evaluation. What makes this approach so feasible is that solid knowledge of who demonstrates best practices is revealed in the data. However, to find that knowledge, some operational processes and the data itself need refinement. Access to the data and its quality must be addressed.

Getting To The Knowledge In The Data
Regrettably, access to the data by the right persons is often a problem. Those who know best what to look for, the business and clinical professionals, cannot use current data in a practical, work-in-progress manner. The reasons are many.

First, relevant data resides in separate databases that must be integrated to understand all activity in a claim. Moreover, in most organizations, provider records are simply inaccurate and incomplete. Until now, the need for them was for reimbursement purposes only, not performance evaluation. Yet another problem is that provider records are frequently duplicated in the data, making it difficult to accurately evaluate individual medical providers' treatment process and results.

Data Silos
Critical data for analyzing medical provider performance is still fragmented in most payer organizations. While people have long complained about data silos in Workers' Comp, little has been done to correct the problem. If anything, data sources have increased. Pharmacy databases have been added, for instance. Yet the databases are not integrated on the claim level, thereby portraying the claim as a whole. Data silos too often lead those who are attempting to evaluate provider performance to rely on a single data source.

Single Source Analysis
Relying on one source of provider performance data is foolhardy. Nevertheless, bill review data is often used, but by itself is inadequate to tell the whole story. Claims level data is also critical to weigh return to work data, indemnity payments, and legal involvement associated with claims and ultimately, to individual doctors. None of these data items are found in bill review data, yet these are essential to complete analysis of provider performance. Because in Workers' Comp, doctors drive the non-medical claim costs as well as the direct medical costs, these data items are essential to evaluating the quality of their performance.

Data Quality
The problem of data quality can be even stickier. Traditionally, medical provider records are kept in the claims database, along with records of other vendors for payment purposes. All that is needed for bill payment is a name, address, and tax ID. Unfortunately, the same provider is frequently added to the database when a new bill is received. This outdated database management practice leads to slightly different records added for the same provider.

Data Optimization
To evaluate medical provider performance, more information about individual providers is needed such as accurate physical addresses. PO Boxes will suffice for mailing checks, but injured workers cannot be sent there for treatment.

Merge Duplicate Records
Tax ID's are still important for reimbursement and 1099 purposes, but often multiple doctors are represented by one Tax ID. To evaluate provider performance, individuals must be differentiated in the data. State medical license numbers and NPI (National Provider Identification) numbers are needed. Frankly, some doctors deliberately obfuscate the data by operating under multiple Tax ID's and multiple NPI numbers. Consequently, provider records must be merged, scrubbed, and optimized before any analysis can begin.

What To Do
For most organizations, choosing best practice providers by analyzing the data is challenged by the shortage of accurate and complete data. Therefore, those wanting to control costs by choosing the best providers should obtain provider performance analysis and scoring from a specialty third party, one that is expert in data integration from multiple sources, as well as provider data scrubbing and optimization.

When behaviors of doctors are analyzed using clean, integrated data, the well-informed and well-intentioned in Workers' Comp will rise to the surface.

1 Tips for Building a Medical Provider “A” Team and More Tips for Building a WC Medical Provider “A Team”