Health care is the only consistently booming “growth” sector in the auto industry. Increasing in cost at an average 7% per year, it is sucking away billions of dollars when the auto industry can least afford it. Information Technology (IT) alone can’t stop the onslaught. It can, however, at least slow down the meteoric rise in costs. Specifically, IT’s decision support systems (DSS) and data warehouses help penetrate the Byzantine maze of cost data, claims records and health-care vendors. Through data analysis, IT can get a manufacturer better health-care coverage for the same dollar.
IT in health care plays an analogous role to that in more familiar manufacturing areas:supplier selection; financial modeling; supplier performance; quality; preventive/predictive maintenance
The Big Three alone spent $8.2 billion last year on health care. Ford currently throws off more profit for its health-vendors than it makes itself selling vehicles. General Motors provides health care for 1.2 million individuals. Its $4.5 billion tab last year was more than it spent on steel. For decades, the U.S. autoworker has enjoyed the most comprehensive health coverage in the world. With their long experience, U.S. auto companies manage their benefits programs better than in other industries. Clearly health care is no longer a “fringe benefit.”
Indeed, GM is the largest, private buyer of health care in the world. It has major contracts with 127 health-care carriers. These include HMOs and traditional insurers. These carriers, in turn, contract with providers such as the national hospital chains, HCA and Tenet. Giant pharmacy benefits management (PBMs) firms such as Medco and Express Scripts handle the drugstore transactions.
At the same time, the automakers have their own large, dedicated, health-care systems. For instance, GM has two EDS-built systems. These pay claims to the carriers, check payroll records to identify eligible individuals, and perform other functions. Ford manages its own data warehouse, where it does DSS-style analysis on health-care data.
Health care in the auto industry isn’t merely about administrative chores. It has become a global, competitive issue. GM’s cost for retirees’ pensions and health care was $1,360 per vehicle, according to a Prudential Financial report. In contrast, Honda’s tab for its American retirees is a mere $107 per vehicle. Skyrocketing costs here are contributing to the steady exodus of auto manufacturing jobs from the United States. Virtually all the governments in other vehicle-manufacturing countries pay a higher percentage of the health-care costs than in the United States. In the U.S., the car buyer, in effect, must pick up the tab by paying more for the comparable vehicle.
IT plays a major role in almost every facet of health-care management. It aids employers in picking which plans it will make available to its employees. Hundreds of vendors, each with long menus of options, must be evaluated to understand the costs and to find the best mix for the manufacturer’s specific workforce. IT-based modeling programs help estimate what those costs could be. This can vary considerably, based on the demographics of each company’s workforce and those workers’ medical histories. As a general example, an employer with a predominately young work force could find the self-insurance route to be far cheaper than going with an HMO. Furthermore, dedicated IT/health-care firms like Medstat (Ann Arbor, MI) can analyze a company’s claims data and costs and determine if an employer is overpaying for its coverage, given the national averages for those types of claims.
Using a data warehouse, an analysis can also enable an employer to judge the quality of health care provided in its programs. This is through online transaction processing (OLAP)-style analysis. For instance, an OLAP analysis can match a patient’s medical diagnosis with the drugs prescribed. If the doctor is prescribing the wrong drug, it obviously indicates poor medical care. Likewise, a costly brand-name drug may be prescribed even when a low-cost, generic drug is available. This indicates unnecessarily high charges. GM does this type of analysis to identify high-quality, high-performing carriers. It steers its members toward these carriers by requiring lower monthly premiums for membership in those preferred plans.
Medstat is taking such analysis to the next level, said its director of strategic marketing, Aleks Engel. The firm is correlating worker productivity data with health data. For instance, it can correlate data on absenteeism with the types of medical problems common among its high-absenteeism workers. This analysis can even look at the worker’s output when such “piece count” productivity data is available. In doing so, the analysis calculates the total costs to the employer. This figure can be far higher than just the medical bill.
With a deep understanding of its workers’ health patterns, an employer can pro-actively initiate “wellness” programs. These preemptively reduce the occurrence of some predictable, costly but avoidable treatments. Good, cost modeling enables the benefits program to present compelling return on investment (ROI) justifications for these wellness programs.
Because of the near lifetime tenure of many auto employees, it behooves the employer to do all in its means to promote the health of its workers. One Japanese auto manufacturer rather fanatically combs through its data for cost-avoidance and cost-savings opportunities. For instance, it can identify which workers based on their health histories would more likely need higher levels of medical care in particular jobs. It avoids assigning these workers to those jobs. For instance, some jobs would be a poor match for a worker with a history of carpal tunnel syndrome.