Upcycling: Bringing new life to existing health data

From the Health Affairs Blog:

By now, most of us are familiar with recycling. Items with reclaimable value are collected; then base materials are salvaged to create new products—often of lesser quality.

Fewer people are familiar with the term upcycling, a form of recycling that involves reconceiving, and sometimes adding to, existing items with the goal of giving them a different purpose and higher value. Though the term may be unfamiliar, the concept is old. A hundred years ago, farm families upcycled feed sacks into dresses, and old doors into furniture. The fleece jackets we now see everywhere, often made from reclaimed plastic bottles, are a modern example of upcycling.

In the world of health care data, too, opportunities exist to upcycle by adding to and repurposing existing information. It makes good sense to leverage investments in data collection, many of which have already been made for other reasons, such as public health surveillance and provider billing: doing so reduces data collection and cost burdens. The California HealthCare Foundation, based in Oakland, is actively pursuing data-upcycling initiatives as part of its mission to make useful information about health care quality publicly available. Two such efforts are highlighted below.

Maternity Care Data
More than 500,000 California women give birth each year; yet little information exists to guide decisions about where to seek high-quality maternity care. Providers themselves often lack information about their own performance. To help fill this gap, the California Maternal Data Center was launched in 2012 (it is cofunded by the California HealthCare Foundation and the Centers for Disease Control and Prevention and operated by the California Maternal Quality Care Collaborative). By repurposing data that hospitals and the state government have long collected, it provides metrics on the quality of maternity care. The California Maternal Data Center links birth certificate data (for example, birth weight, delivering provider) with information included in patient discharge data (for example, diagnostic and procedure codes related to the birth) that hospitals are already required to submit to the state.

With this combination of data, the center is able to produce robust measures, such as rates of cesarean sections, episiotomies, and vaginal birth after C-section, on all California hospitals providing maternity care. With a small amount of additional work, hospitals can voluntarily submit additional data elements from targeted medical chart reviews (that is, reviews of a subset of charts identified by the California Maternal Data Center to be most relevant) to generate other measures, such as elective delivery before thirty-nine weeks. Many participating hospitals are using the center’s data to facilitate quality improvement, and plans are under way to support public reporting at the hospital and physician-practice levels.

To read the complete post, click here.

Webinar: Team training and patient safety

The Agency for Healthcare Research and Quality (AHRQ) will host a 1-hour webinar on the use of the agency’s teamwork training program, TeamSTEPPS® & what evidence is available to demonstrate the program’s efficacy in improving patient safety.  David Baker, Ph.D., TeamSTEPPS® Master Trainer & Senior Vice President at IMPAQ International, will discuss the following objectives:

  1. The key components of teamwork
  2. How to develop teamwork in health care
  3. The core components of TeamSTEPPS®
  4. The TeamSTEPPS deployment process
  5. The evidence on team training effectiveness
  6. The effectiveness of TeamSTEPPS

Most health outcomes following surgery are worse for low-income patients

From the Agency for Healthcare Research & Quality (AHRQ):

A new AHRQ study of 12 measures of outcomes following surgical procedures found that outcomes for patients from both high- and low-income geographic areas improved between 2000 and 2009. In fact, survival following two surgical procedures—coronary angioplasty and carotid endarterectomy—improved for both high- and low-income patients, and the disparity between the two groups narrowed. However, in nine of the remaining 10 outcomes studied, patients from low-income areas fared worse than patients from high-income areas across both years. For example, low-income patients had significantly increased risks for postoperative complications involving respiratory failure and lower survival rates following abdominal aortic aneurysm repair and coronary artery bypass graft. Prior research has shown that low-income patients were more likely to be either uninsured or covered by Medicaid as well as belong to a racial or ethnic minority group, the study said, noting that those characteristics were associated with poorer surgical outcomes. The study, “Despite Overall Improvement in Surgical Outcomes Since 2000, Income-Related Disparities Persist,” co-authored by AHRQ’s Roxanne Andrews and Mehwish Qasim, a doctoral candidate at the University of Iowa, appeared in the October issue of Health Affairs.

To read more articles in the most recent edition of the AHRQ Electronic Newsletter, click here.

New from HCUP – New state databases released

The Agency for Healthcare Research & Quality has released the following state Databases:

2010:

2011:

 2012:

HCUP’s “Most Expensive Conditions” infographic

From the Agency for Healthcare Research & Quality (AHRQ):

HCUP_MostExpensiveCond2011HCUP has released a new infographic, The Top Five Most Expensive Conditions Treated in U.S. Hospitals, which represents data from the recently released Statistical Brief #160: National Inpatient Hospital Costs: The Most Expensive Conditions by Payer, 2011. This statistical brief provides HCUP data on the distribution of costs by expected primary payer & illustrates the conditions accounting for the largest percentage of each payer’s hospital costs.

Find more HCUP infographics & a link to a complete list of statistical briefs here.

Delay in release of MEPS insurance component

From the Agency for Healthcare Research & Quality (AHRQ):

There will be a delay in the release of tables containing 2012 state and local government estimates from the MEPS Insurance Component. Originally scheduled for posting in late November 2013, the tables will be released in early Spring 2014 instead. This delay also effects the 2012 MEPS-IC civilian tables. Note that 2012 MEPS-IC tables for the private  sector were posted in July 2013.

The MEPS-IC is collected and processed by the Bureau of the Census on behalf of AHRQ. Budget cuts resulting from the sequester and the lapse in appropriations during October 2013 contributed to this delay. The Bureau of the Census published a note on the sequester here http://www.census.gov/econ/census/schedule.html and on delays due to the lapse in appropriations here http://www.census.gov/newsroom/releases/archives/economic_surveys/cb13-tps99.html.

We apologize to data users who are adversely impacted by this change in the tables’ release date. Please contact the MEPS Project Director at mepsprojectdirector@ahrq.hhs.gov if you need further information.

New publication model for PubMed citations

In mid-June 2013, a new publication model, Electronic-eCollection, was introduced for PubMed citations from electronic-only journals. “Electronic-eCollection” means that an article is published electronically on a specific date and is also associated with an electronic collection date (similar to an issue; this date can be a year or a year and month, but never a year, month, and day). NLM determines the publication model based on the data submitted by the publishers.

“eCollection” will be displayed preceding the collection date information in a citation. The specific article date will display after the journal title abbreviation while the collection date will display near the end of the source information.

Screen capture of a sample display for journal citation with PubModel = Electronic-eCollection.

This particular article was published online on January 25, 2013, yet was included in the Volume 3, 2012 collection as deposited in PMC.

Webinar: Integrating mixed methods in health services & delivery system research

From the Agency for Healthcare Research & Quality (AHRQ):

Register now for a webinar scheduled about how mixed-methods research offers powerful tools for investigating complex processes and systems in health care services and delivery. The webinar, which focuses on work by AHRQ on delivery systems and  patient-centered medical homes, will also announce and provide information on a new AHRQ-sponsored special issue on this topic in Health Services Research.

Presenters:

  • Benjamin Crabtree, Professor and Research Director, Department of Family Medicine, Rutgers Robert Wood Johnson Medical School
  • Debra Scammon, Emma Eccles Jones Professor of Marketing in the David Eccles School of Business, and Adjunct Professor, School of Medicine, Department of Family and Preventive Medicine, University of Utah
  • Andrada Tomoaia-Cotisel, Research Associate, Department of Family and Preventive Medicine, University of Utah

Moderator:  Michael I. Harrison, Ph.D., Senior Social Scientist, AHRQ

    • Date:  3 December 2013
    • Time:  1-2:00pm ET
    • Register here.

New database from CMS: Medicare Provider Charge Data

The Department of Health & Human Services has created a database that for the first time gives consumers information on what hospitals charge.  The data, on the charges for services that are provided during the 100 most common Medicare inpatient stays and 30 common outpatient services, show significant variation across the country and within communities.

For example, average inpatient charges for services a hospital may provide in connection with a joint replacement range from a low of $5,300 at a hospital in Ada, Okla., to a high of $223,000 at a hospital in Monterey Park, Calif.  Even within the same geographic area, hospital charges for similar services can vary significantly. For example, average inpatient hospital charges for services that may be provided to treat heart failure range from a low of $21,000 to a high of $46,000 in Denver, Colo., and from a low of $9,000 to a high of $51,000 in Jackson, Miss.

Access the database here and on the Health Statistics research guide.

 

Health spending projected to grow an average of 5.8 percent annually through 2022

From Health Affairs:

New estimates released today from the Office of the Actuary at the Centers for Medicare and Medicaid Services (CMS) project that aggregate health care spending in the United States will grow at an average annual rate of 5.8 percent for 2012-22, or 1.0 percentage point faster than the expected growth in the gross domestic product (GDP). The health care share of GDP by 2022 is projected to rise to 19.9 percent from its 2011 level of 17.9 percent.

The findings appear as a Health Affairs Web First article and will be published in the October issue. The article provides an analysis of how Americans are likely to spend their health care dollars in the coming decade, with projections for spending by different sectors, payers, and sponsors. The projections reflect a combination of factors affecting health care spending, including provisions of the Affordable Care Act (ACA) that increase health insurance coverage and forecasted changes in the nation’s economy.

For 2013 health care spending growth is projected to remain under 4 percent because of the sluggish economic recovery, continued increases in cost-sharing requirements for the privately insured, and slow growth for Medicare and Medicaid spending.

But starting in 2014 growth in national health spending will accelerate to 6.1 percent, reflecting expanded insurance coverage through the ACA, through either Medicaid or the marketplaces. The use of medical services and goods, especially prescription drugs and physician and clinical services, among the newly insured is expected to contribute significantly to spending increases in Medicaid (12.2 percent) and private health insurance (7.7 percent). Out-of-pocket spending is projected to decline 1.5 percent in 2014 due to the new coverage and lower cost sharing for those with improved coverage.

Read more here.