Category Archives: Methods

New methods in risk modeling: does adding EHR data improve predictions?

One of the challenges in delivering efficient medical care is identifying people who are at risk of a negative outcome, so we can focus our efforts on screening and treating those at elevated risk. We do this in individual face-to-face encounters through clinical, diagnostic processes: taking a patient’s history, performing a physical examination, recording signs… Read More »

The Past, Present, and Future of Risk Adjustment: An Interview with Arlene Ash

Recently, I sat down to talk with Arlene Ash, PhD about risk adjustment. Dr. Ash is Professor and Chief of the Division of Biostatistics and Health Services Research, Department of Quantitative Health Sciences at the University of Massachusetts Medical School. As a methods expert on risk adjustment in health services research, she has pioneered tools… Read More »

Can Claims Data Algorithms Identify the Physician of Record?

Medical claims data are collected for payment purposes. However, these data are often used for other purposes such as studying quality of care, assessing provider performance, and measuring health. These data are a rich resource for health services research, but when they do not include key pieces of information we can find ourselves bending over… Read More »

The Childhood Roots of Health Inequity: Part 4 – Dr. Jennifer Manly

This post is the final one in our 4-part series focusing on presentations that were delivered at a special panel session at APHA16 on the childhood roots of health inequity [part 1, part 2, part 3]. Our fourth presenter, Dr. Jennifer Manly, is Associate Professor of Neuropsychology in Neurology at the Gertrude H. Sergievsky Center and the… Read More »

Cost-Effectiveness of Antihypertensive Medication

Anytime I see the words “cost saving” in reference to a public health or medical intervention, my first thought is “Yeah, right!” It just doesn’t happen that often. One can spend more money to get better outcomes (or more care provided), or less money for worse outcomes, but rarely less money AND better outcomes. However,… Read More »

Correct inference from systematic reviews of RCTs

To gauge the effects of medical interventions, we often use meta-analysis to combine the results of randomized control trials (RCTs). RCTs commonly use odds ratios (ORs) to measure the effect of a given intervention on the frequencies of events. Conventional methods of estimating overall ORs suffer from a number of issues. Drs. Chang and Hoaglin describe… Read More »

Going Outside the Box: Identification of Active Diagnoses in the MDS 3.0

In an effort to improve the validity and person-centeredness of the nursing home resident assessment tool (the Minimum Data Set, or MDS), the Centers for Medicare and Medicaid Services introduced version 3.0 in October 2010. As a result, many of the measures and items health services researchers had grown accustomed to using in the MDS… Read More »

Quality Measurement in Home Care: Avoiding Unintended Effects

In theory, quality measurement and reporting generally benefits patients and their families, as (PDF link) public data on quality increases transparency and provider accountability. It also may benefit providers as a tool for quality assurance and improvement; however, the evidence does not always provide a clear picture. Unique challenges exist for patients receiving home care… Read More »

Feasibility of MDS 3.0 in Constructing Meaningful End-of-Life Quality Measures

Since the launch of Nursing Home Compare (NHC) in 2002, consumers have had access to information about the quality of care provided by most nursing homes (NHs) throughout the country. The intention is to help consumers distinguish among NHs and motivate informed decision making based on quality. For NHC to be useful, the quality measures… Read More »

Multidimensional frailty score as a predictor of postoperative mortality

According to the 2010 U.S. Census, there are 40 million people (13% of the population) older than 65 years of age living in the U.S. This population has increased dramatically during the last two decades. Currently more than half of all surgeries are performed on this group of patients in the U.S. Frailty is typically defined by… Read More »

Which Bias is Which?

Comparative Effectiveness Research (CER) seeks to compare alternative treatments and ways to deliver healthcare to inform healthcare decisions. It can provide evidence of the harms, benefits, and effectiveness of different treatment options. As the number of studies in CER continues to grow, it is vitally important that the types of bias that exist as a function of the study design be explained. In a Medical Care article published in April, Dr. Sebastien Haneuse lays out definitions and examples of selection bias and confounding bias in CER, with a particular emphasis on distinguishing between the two.

Measuring Cost-related Medication Burden

As readers of Medical Care are no doubt aware, prescription drug expenditures for Medicare beneficiaries are high – nearly $90 billion in 2012.  There is some evidence that Medicare Part D has reduced financial burdens, at least among some beneficiaries, but recent surveys suggest that around 4.4% of individuals ages 65 and older (including those not on… Read More »