Tag Archives: medical management

How to Monetize Medical Management

Over the past 25 years, the workers’ comp industry has collected vast amounts of data, and organizations within the industry have easy access to this valuable asset. Their challenge now is to profit from it.

Experts say medical costs now amount to 60% of claim costs in workers’ comp. If true, organizations should be charging ahead to find ways to optimize medical loss management and monetize their data for profit.

See also: Intelligent WC Medical Management  

The first step toward monetizing medical data is to integrate it from disparate data silos. All bill review, claims system, pharmacy (PBM) and other relevant data should be integrated at the claim level to gain a full picture of individual claims. Once integrated, predictive analytics methodologies can be applied to convert the data to usable information.

You need to analyze historic data using predictive analytics to discover conditions that are cost drivers or cost accelerators. What conditions or combinations initiate or perpetuate high-cost situations? Where are the gaps in timing in operational flow? What actions encourage positive or negative claim resolution? And the information must be made actionable.

Predictive analytics has determined the comorbidity of diabetes adds complexity and cost to claims, so an alert can be generated, and key Information conveyed to appropriate persons.

Based on predictive analytics, the probable ultimate medical costs for the claim are portrayed for the claims rep along with other key information regarding the claim in question. The claims rep adjusts medical reserves accordingly and moves on. Time is saved, and accuracy is optimized.

At the same time, the predictive analytics-informed system automatically notifies the nurse case manager based on the organization’s referral protocol. The claims rep is informed of the referral but is not required to take action.

Similar claim information is presented to the nurse case manager for quick review, thereby integrating and coordinating claims and nurse case management initiatives.

Data is made intelligent and can be monetized through predictive analytics combined with a timely information delivery system. Searching for decision-support information takes time and is inefficient. Manually entering data is time-consuming, annoying and often inaccurate. On the other hand, intelligent information delivered appropriately is monetized as claim stakeholders make informed decisions quickly, effortlessly and accurately without need for data gathering and data entry.

Projected probable ultimate claim cost with comprehensive supportive information displayed for claims reps does not require data search or data entry. Even less-experienced adjusters are accurate and efficient. Accuracy and efficiency is optimized, productivity is increased and profitability follows. Moreover, early intervention through timely alerts allows for action before further damage is incurred.

Medical loss management is also monetized by the ability to objectively measure claim cost savings. Having projected the ultimate medical costs for a claim, quantifiable cost savings are available at claim closure due to coordinated medical management initiatives. Monetization is realized through client satisfaction, customer loyalty and client retention. Moreover, the story is proof of value serving the organization’s strategic competitive advantage.

See also: Proof of Value for Medical Management  

Organizations that monetize their data have greater returns, including return on investment. The intelligent medical management system is monetized internally and externally, thereby paying for itself. Such statements are familiar as sales platitudes, but with intelligent medical management, positive results are objectively measured. Savings are greater than the cost.

Intelligent WC Medical Management

Technology in workers’ comp is hardly new, but new ways to infuse technology and predictive analytics into the claims and medical management processes can significantly improve accuracy, efficiency, outcomes and, importantly, profitability. Well-designed technology that streamlines operational flow, provides key knowledge to the right stakeholders at the right time, promotes efficiency and generates measurable savings is formidable. The system is intelligent and includes these key components:

  1. Predictive analytics
  2. Data monitoring
  3. Knowledge for decision support

Predictive analytics

Predictive analytics is the foundation for creating an intelligent medical management process. Analysis of historic data to understand the risks and cost drivers is the basis for an intelligent medical management system. For the risks identified, the organization sets its standards and priorities for which stakeholders are automatically alerted to those specific conditions in claims as they occur.

The stakeholders are usually claims reps and nurse case managers, but others inside or outside the organization can be alerted, such as upper management or clients, depending on the situation and the organization’s goals. Upper management establishes specific action procedures for specified conditions or situations, thereby creating consistent procedures that can be measured against outcomes.

See also: 25 Axioms Of Medical Care In The Workers Compensation System  

Data monitoring

Incoming data must be updated and monitored continuously. Random or interval monitoring leaves gaps in important claim knowledge that is overlooked until the next monitoring session. The damage may have escalated by then. With continuous data monitoring, everything is reviewed continually so nothing is missed. When the data in a claim matches the conditions outlined by the predictive modeling, an alert is sent to the stakeholder so action or intervention is initiated.

Some say the stakeholders will not comply with such a structured program because they resist being directed. To solve that problem, accountability procedures in the form of audit trails in the system act as overseer. At any point, management can view what alerts have been sent, to whom they were sent, for what claim and for what reason, thereby observing participation and supporting accountability.

Knowledge for decision support

The alerts sent offer collected knowledge about the claim needing attention so the stakeholder is not forced to search for information before deciding upon an action. The reason the alert was triggered, detailed claim history including medical costs paid to date is displayed for alert recipients. Importantly, the projected costs for a claim with similar characteristics are portrayed, making reserving adjustments easy and accurate.

The projected ultimate medical costs for the identified claim is portrayed for the claims rep based on the analytics, thereby providing decision support for adjusting reserves. Data entry into the system is never needed, therefore, accuracy and efficiency is optimized.

At the same time, a nurse case manager is automatically notified of the situation if indicated by the organization’s rules in the system and is informed with the same claim detail. Now the case manager and claims rep are collaborating to mitigate the costs for this claim. They know the projected ultimate medical cost for the claim and the projected duration of the claim, so they have a common and concrete target to challenge. Moreover, improvements on the projections offer objective and defensible cost savings analysis.

See also: Even More Tips For Building A Workers Compensation Medical Provider “A” Team  

Predictive analytics combined with properly designed technology to create an intelligent medical management process establishes a distinct advantage. Knowledge made available at the appropriate time for the right people leads to efficiency and accuracy. Early, intelligent intervention drives better results.  Stakeholders coordinate efforts to mitigate the claim, working toward a shared goal. Finally, knowledge provided for decision-support positions for measurable, objective, reportable savings at claim closure.

Confusion Reigns on Predictive Analytics

It seems everyone in workers’ compensation wants analytics. At the same time, a lot of confusion persists about what analytics is and what it can contribute. Expectations are sometimes unclear and often unrealistic. Part of the confusion is that analytics can exist in many forms.

Analytics is a term that encompasses a broad range of data mining and analysis activities. The most common form of analytics is straightforward data analysis and reporting. Other predominant forms are predictive modeling and predictive analytics.

Most people are already doing at least some form of analytics and portraying their results for their unique audiences. Analytics represented by graphic presentations are popular and often informative, but they do not change behavior and outcomes by themselves.

See Also: Analytics and Survival in the Data Age

Predictive modeling uses advanced mathematical tools such as various configurations of regression analysis or even more esoteric mathematical instruments. Predictive modeling looks for statistically valid probabilities about what the future holds within a given framework. In workers’ compensation, predictive modeling is used to forecast which claims will be the most problematic and costly from the outset of the claim. It is also the most sophisticated and usually the most costly predictive methodology.

Predictive analytics lies somewhere between data analysis and predictive modeling. It can be distinguished from predictive modeling in that it uses historic data to learn from experience what to expect in the future. It is based on the assumption that future behavior of an individual or situation will be similar to what has occurred in the past.

One of the best-known applications of predictive analytics is credit scoring, used throughout the financial services industry. Analysis of a customer’s credit history, payment history, loan application and other conditions is used to rank-order individuals by their likelihood of making future credit payments on time. Those with the highest scores are ranked highest and are the best risks. That is why a high credit risk score is important to purchasers and borrowers.

Similarly, workers’ compensation claim data can be collected, integrated and analyzed from bill review, claims system, utilization review, pharmacy (PBM) and claim outcome information to score and rank-order treating physicians’ performance. Those with the highest rank are the most likely to move the injured worker to recovery more quickly and at the lowest cost.

Both predictive modeling and predictive analytics deal in probabilities regarding future behavior. Predictive modeling uses statistical methods, and predictive analytics looks at what was, is and, therefore, probably will be. For predictive analytics, it is important to identify relevant variables that can be found in the data and take action when those conditions or events occur in claims.

One way to find critical variables is to review industry research. For instance, research has shown that, when there is a gap between the date of injury and reporting or the first medical treatment, something is not right. That gap is an outlier in the data that predicts claim complexity.

Another way to identify key variables is to search the data to find the most costly cases and then look for consistent variables among them. Each book of business may have unique characteristics that can be identified in that manner.

Importantly, predictive analytics can be used concurrently throughout the course of the claim. The data is monitored electronically to continually search for outlier variables. When predictive outliers occur in the data, alerts can be sent to the appropriate person so that interventions are timely and more effective.

For example, to evaluate medical provider future performance, select data elements that describe past behavior. Look at past return-to-work patterns and indemnity costs associated with providers. If a provider has not typically returned injured workers to work in the past, chances are pretty good that behavior will continue.

For organizations looking to implement analytics, those who have already made the plunge suggest starting by taking stock of your organization’s current state. “The first thing you need to know is what is happening in your population,” says Rishi Sikka, M.D., senior vice president of clinical transformation for Advocate Health Care in Illinois. “Everyone wants to do all the sexy models and advanced analytics, but just understanding that current state, what is happening, is the first and the most important challenge.”

The accuracy and usability of results will depend greatly on the quality of the data analyzed. To get the best and most satisfying results from predictive analytics, cleanse the data by removing duplicate entries, data omissions and inaccuracies.

For powerful medical management informed by analytics, identify the variables that are most problematic for the organization and continually scan the data to find claims that contain them. Then send an alert. Structuring the outliers, monitoring the data to uncover claims containing them, alerting the right person and taking the right action is a powerful medical management strategy.

How to Make IT Efforts Strategic

Has your IT come out of the proverbial and actual basement to be an integral part of your business strategy? Too often, business leaders assign IT a task and expect an initiative to be delivered. End of story. The truth is, business owners must engage and own the outcomes of their IT investments, driving them to a strategic value that can be measured.

What is IT strategy? Think about any infrastructure initiative (building highways, public transportation or urban development). Without the requisite strategic investment of time, funding and planning, these initiatives face delays, cost overruns, diversion from desired strategy and failure. True partnerships between IT and business operations insure that the best thinking of both can be applied to a given situation to produce strategic results.

See Also: The 7 Colors of Digital Innovation

Business value

IT should be viewed as a business strategy. Today, not a single discussion in the workers’ compensation industry relating to claims management or medical management does not include IT. As workers’ comp focuses on outcomes (both cost and quality), it is the only new strategy around. Moreover, it is the most effective and efficient strategy to achieve business goals. The following six elements are necessary to generate business value by leveraging the IT strategy. 

1.    Define the project—Describing how new technology or a new data application will function is only the first step in integrating IT into the business strategy. However, defining the project can be tricky. Remember, IT professionals talk a different language and appreciate different measures of success than those involved in operations. Business owners cannot assume their IT requests are understood as they were intended. Even slight misinterpretations of requests can result in frustration, cost overrides and a useless tool.

I recall one time, early in my career, when I submitted specifications for a development project. I used the word “revolutionary” to describe the powerful impact it would have on the business. However, the IT person, who was younger and male, interpreted “revolutionary” in an aggressive, military sense, which was not even close to what I had in mind. Always verify that you have an understanding and clarify of all elements of the IT project. 

2.    Design for simplicity—If the IT project outcome is complicated or requires too many steps, people will not use it.

3.    Define the expected business value—As a part of defining the IT project, define its expected business value. Both the business unit involved and the IT team need to align their expected outcomes. Not unlike evaluating ROI (return on investment), identify the financial investment and rewards of the IT project. Make sure to also describe the anticipated collateral outcomes of the IT project, such as PR, business growth or client involvement. Figure out how to measure the expected business outcomes when the project is complete.

Design the project outcome value measures at the beginning. Too often, business leaders do not articulate their expectations of value and, therefore, can never prove them. If you do not know where you are going, you could end up somewhere else.

4.    Commit resources—Funding and other resources such as personnel should be allocated at the beginning; short-shrifting resources will guarantee less-than-satisfactory results. Know from the beginning how the IT project will be implemented and who will do and be responsible for the work. Establish accountabilities and create procedures for follow-up.

5.    Monitor progress—Continuously monitor and manage the project, even throughout the IT development process. Discovering deviations from the plan early on minimizes damage and rework. Obviously, rework means cost and delay.

6.    Measure value—Once the project is accepted and implemented, begin continuous outcome evaluation. Execute the value measures outlined at the beginning. Make the necessary adjustments and keep your eye on the business value.

Not everyone can be an IT expert, but everyone can become an expert in how IT advances the strategies of their domain.

How Work Comp Can Outdo Group Health

We all know the current healthcare system in the U.S. delivers erratic quality at unsustainable, yet ever-increasing, costs. Workers’ compensation medical care is affected by those costs. 

A major shift in the health industry, value-based healthcare, will benefit workers’ compensation. Embracing selected new medical management methodologies put forth in value-based healthcare has the potential to be powerful.

Value-based healthcare means restructuring how medical care is organized, measured and reimbursed. It moves away from a supply-driven system organized around what physicians do to a patient-centered system organized around what patients need. The focus is shifted from volume and profitability to patient outcomes (quality care). When fully implemented, the overall impact will be nothing less than staggering.

Porter and Lee, healthcare industry strategists at Harvard, have described six value strategies necessary to achieve healthcare industry transformation. Many of the changes are now underway in ACOs (accountable care organizations) such as the Cleveland Clinic, proving the concept. These defined initiatives produce desired results—quality care at less cost. 

Six components of value-based healthcare

The following briefly describes the methodologies necessary to transform healthcare, according to Porter and Lee.

  1. Integrated practice units (IPUs)—meaning multiple specialists practice together, resulting in comprehensive and integrated medical care rather than fragmented, duplicated services
  1. Measure true outcomes and costs for every patientWhen outcomes are measured and reported publicly, providers are under pressure to improve. Fraud and self-dealing are reduced.
  1. Bundled paymentsPayment bundles are capitated single payments for all the patient’s needs during defined episodes of care, such as specific surgical procedures. Providers are rewarded for delivering quality while spending less.
  1. Integrate care delivery systemsServices are concentrated and integrated to eliminate fragmentation and to optimize the quality of care delivered at any given location.
  1.  Expand geographic reachCenters of excellence are developed where expertise is gained through higher volume of similar procedures.
  1.   Information technologyData mining powerfully enables the first five initiatives and informs services and decisions.

As Porter and Lee say, “Whether providers like it or not, healthcare is evolving from a proficiency-based art to a data-driven science, from freelance physicians to hospital-employed physicians, from one-size-fits-all community hospitals to vast hospital networks organized around centers of excellence.”

Value-based medical management in workers’ comp

The goal of value-based medical care is to enhance quality outcomes for patients (injured workers) while reducing costs. Focusing on quality (what the patient needs) actually reduces costs.

For group health, the measures are physical and philosophical, requiring widespread disruption in how services are organized, delivered and reimbursed. However, workers’ compensation payers can benefit by incorporating three of the six value measures into their medical management process now.

  1. Measure true outcomes and costs for every patient (the injured worker)

Physician performance is scored based on injured workers’ experience and outcomes along with cost. Providers who score poorly can be avoided.

  1. Bundle payments

Bundling is capitating payments for all the services required for procedures such as specific surgical procedures, including all associated pre-op and post-op care. The costs are kept in line because providers need to stay under the cap to be profitable. They also focus on quality, because re-dos, redundancy and complications add cost to the service bundle, thereby diminishing profits. Prepare to see bundled payment options available to workers’ compensation sooner rather than later.

  1. Information technology

The data in workers’ compensation, while in silos, is all organized around individual claims and injured workers. When the data is integrated at the claim level, patient experience, provider performance, outcome and cost analysis opportunities are unlimited. The more comprehensive and accurate the data, the greater the opportunity for gain.

Those who cling to traditional seat-of-the-pants medical management will be left behind. Those in group health may be hampered by slow regulatory change, organizational upheaval and resistant providers, while workers’ compensation payers are free to adopt transformative value measures now. Organizations that progress rapidly to implement the value agenda will reap huge benefits.