Author Archives: Paul LaBrec

Analyze this! Administrative claims data or EHR data in health services research?

One of the ongoing debates in health services research concerns the relative merits of using administrative claims data versus electronic health record (EHR) data for research. Should one be preferred over the other? Some question the degree to which administrative claims data continue to be valuable for health services research given the growth of EHR systems. Continue reading

Some thoughts on risk measurement

One reader of my latest blog on segmenting health care consumers asked me if I knew of any tools to calculate a person’s chance of developing a particular disease. That question got me thinking again about the topic of risk in health and disease. I pulled a copy of John Last’s Dictionary of Epidemiology from my office bookshelf for a proper epidemiologist’s definition of risk:

“The probability that an event will occur, e.g., that an individual will become ill or die within a stated period of time or age. Also, a nontechnical term encompassing a variety of measures of the probability of a (generally) unfavorable outcome.”1 Continue reading

Can patients be segmented like other consumers?

What is consumer segmentation?

Market analysts have for decades used consumer segmentation to predict behavior. One of the more prevalent consumer segmentation databases, PRIZM®, originally developed over 30 years ago, uses data from the U.S. Census, large consumer surveys and various other household and individual data sources to create categories of “like-minded” consumers who presumably behave in a similar manner with respect to their consumption of goods and services. 1 PRIZM segments have names like “Young Digerati,” “Kids and Cul-de-Sacs,” and “Satellite Seniors.” These categories have generally been applied to geographic areas such as ZIP Codes or census tracts for targeting of direct mail marketing campaigns or brick and mortar store location decisions. Continue reading

Health care’s “one percenters:” Hot spotting to identify areas of need and opportunity

Since Atul Gawande popularized the term in describing the work of Dr. Jeffrey Brenner in a New Yorker article,1 “hot spotting” has been used in health care to describe the process of identifying “super-utilizers” of health care services, then defining intervention programs to coordinate their care. According to Brenner’s data from Camden, New Jersey, 1% of patients generate 30% of payments to hospitals, while 5% of patients generate 50% of payments.2 More recent reports on larger datasets have corroborated these metrics.3 I recently analyzed a sample dataset of (primarily commercial) health insurance claims representing about 2 million covered lives and found that the top 1% of the population representing the highest risk patients accounted for 17% of the Total Medical Allowed (TMA)–the sum of insurer allowed charges for inpatient, outpatient (including hospital emergency department), and professional claims. Casting a wider net, I found that the top 12% of high-risk patients accounted for 55% of charges.    Continue reading

The Internet of Things in Health Care

A few weeks ago, my wife and I were watching an interview with Dr. Michael Roizen, who leads the Department of Preventive Medicine at the Cleveland Clinic. Dr. Roizen was describing his “7 Action Steps to a Healthier You,” one of which is “Walk 10k a Day,” where one tries to take 10,000 steps each day. Dr. Roizen explained that this 10K threshold seems to impart important health benefits, although the mechanisms aren’t fully understood. While my wife and I try to get out most mornings and walk for 30-60 minutes—at least that’s our intention—we had no idea how many steps we were taking. Continue reading

Will Health Care Transparency Work? Four Unique Perspectives

Health care is not a commodity. Shopping for health care services is not like shopping for a refrigerator, a tennis racquet or a DVD. Identical commodities can be offered by numerous vendors and consumers can reasonably access their prices for comparison as an important element of their purchasing decision. Consumers, however, can’t (and shouldn’t) compare health services on price alone. Health care is a service, but one unlike most other services we use on a regular basis. Continue reading

All-Payer Claims Databases (APCDs) and More: Key Takeaways from the NAHDO Annual Conference

The 2014 National Association of Health Data Organizations (NAHDO) 29th Annual Conference and APCD Workshop was recently held in downtown San Diego. With over 200 attendees and speakers from government, research and healthcare institutions, the event explored the current challenges and discoveries related to healthcare data and reform. Here are some key takeaways from the three-day event:

1. APCDs are not going away.

This is the eighth year the APCD Workshop has been added to the NAHDO Conference. Its increasing prominence testifies to the importance of APCDs in healthcare market analysis, policy-making and consumer reporting. They continue to grow in number and variety—11 are now live and more are in development. Additionally, more vendors continue to enter this space—proof of the rising demand for APCDs. Continue reading