Reducing Health Costs with Data

Analysis Reveals Better Care Options, Less Cost 
reducing health costs with data

(Source: Kaiser Family Foundation)

In the past six years, health premiums have increased by 203%, reported a recent Kaiser Family Foundation study.[1] But workers’ earnings grew an average 56% during that period. How can employers better manage health care dollars?

The surge of sophisticated technology for big data analysis gives providers and employers unprecedented opportunities to target potentially unnecessary costs, while better caring for covered members.

Consider this example: Jane,* a 42-year old female member with moderately-controlled diabetes, has health benefits through her job. Jane’s biannual visit to her Primary Care Physician (PCP) documents her routine lab work, prescriptions and referrals for preventive screenings.

Between PCP visits, this diabetic member gets the flu, causing severe increases in blood glucose levels. When Jane goes to the Emergency Room, the ER doctor increases her medication dosage. After she goes home, Jane’s personal blood glucose meter shows an alarming drop in her blood sugar levels. Jane calls her PCP, who adjusts her dosage to prevent more complications. Jane’s next checkup is planned in six months.

Was all the data communicated from the hospital’s electronic records, the lab vendor’s system, payer claims and her home monitoring glucose meter? Will the PCP be able to verify that Janreduce health expensese actually obtained her preventive mammogram or flu vaccine prescribed before the ER visit?

At MedCost, Jane’s case would be carefully monitored by her nurse health coach. If there is an issue, her nurse health coach would follow up.

Big data equips providers to accurately analyze key metrics to do more than explain past diagnoses and trends in a group of employees. Advanced analytics can now identify patients and populations at risk for developing certain conditions prior to the actual onset of illness.

It is possible for employers to save on health expenses. Harness the power of accurate data analysis to preserve medical costs, while benefiting your employees’ health.

 

*Actual patient data not used.

[1]Journal of American Medical Association, 2016; 315(1);18, doi:10.1001/jama.2015.17349, http://bit.ly/1TSOFho (accessed Feb. 15, 2016)

 

Avoid These Common Data Mistakes

The United States wastes $275 billion annually on health care spending through inefficient record-keeping, duplicated files, fraud or abuse, according to Truven Health Analytics. Nearly $9,000 per second is lost on illegible writing, incomplete entries or inaccurate interpretations of data.[i]

Graph.iStock_000022706119XSmall

In this era of massive data generation, how can companies ensure accurate analyses of their employees’ population health? Here are four common data mistakes to avoid:

1. Making business decisions based on “uncleansed” data.

Electronic health records today overflow with complex treatments, prescriptions, lab results and other tests. Incorrect synthesis of these outcomes can obscure a 360-degree view of past medical history and future potential problems.

MedCost creates detailed reporting with Deerwalk software to help clients identify both medical and financial trends. Sophisticated analytics identify areas of data where misinterpretation may occur. When data is integrated and “scrubbed,” employers may then be assured of making accurate decisions based on those results.

 2. Assuming that claims are processed correctly.

Data integrity is key to avoiding skewed results. Were monthly premiums accidentally included in claim expenses? Have claims been duplicated? Were pharmacy costs integrated with the right patient’s claim?

No one would try to calibrate a car’s multiple computer systems without the right training and equipment. Not using standard query entries will produce data sets of unreliable results for financial and medical decisions. The company that manages your health plan benefits should do rigorous quality assurance audits before releasing “cleansed” data to you.

3. Failing to use technology to protect your group of covered members.

The operating rule of today’s digital health care is that if it can’t be measured, it can’t be managed. How can a company uncover excessive medical costs or emerging health issues for employees, unless clinical and claims data is tracked?

Smart businesses track profit and loss columns. Smart businesses also keep a close eye on cost trends to reduce medical spend and improve population health for employees. MedCost as a benefits administrator delivers monthly reports with specific cost analyses and recommendations to each of our clients.

4. Ignoring cost trends that are wasting your health care dollars.

Health care, despite the tsunami of data generated, is still about people. How can an employer know when an employee’s blood pressure is out of control? When blood glucose levels have gone sky-high? When prescribed meds are no longer being taken? Without careful
analysis of gaps in care, expensive treatments won’t be avoided. And employee health conditions may worsen that could also have been prevented.

Are these data mistakes costing your company thousands of dollars? Consider using quality analysis by a reputable benefits administrator to clarify complex data, while managing population health and more efficient health care spending.

For more information on benefit solutions, contact Jason at MedCost.

[i] “Claims Audit Solutions,” Truven Health Analytics™, http://truvenhealth.com/portals/0/assets/emp_12181_0113_auditsuiteoverviewbrochure.pdf (accessed November 9, 2015).