Category Archives: Data
A new NPR/Robert Wood Johnson Foundation/Harvard School of Public Health poll released today finds that about half of the public reported a major stressful event or experience in the past year. Nearly half (43 percent) reported that the most stressful experiences related to health.
More than half of those who experienced a great deal of stress in the past month say too many overall responsibilities and financial problems were contributors. More than a third of those with a great deal of stress say the contributors include their own health problems and health problems of family members.
“Stress touches everyone. Unfortunately, many of those feeling the most stress get trapped in cycles that can be very unhealthy. If we are going to build a culture of health in America, one big step we can take is recognizing the causes and effects not just of our own stress and the stress of those closest to us, but of others we encounter in our day-to-day lives,” says Risa Lavizzo-Mourey, MD, RWJF president and CEO.
In this interview with the Robert Wood Johnson Foundation's Steve Downs, SM, historian Keith Wailoo, PhD, discusses how we define our own cultures of health and shares how deeply held cultural narratives influence our perceptions of health. Wailoo is jointly appointed in the Department of History and the Woodrow Wilson School of Public and International Affairs at Princeton University. This video is part of the RWJF What's Next Health series. Also check out the accompanying infographic.
Infographic: When 'Good' Data Goes Bad
Good data can play a critical role in answering some of our most vexing questions concerning health. But history shows us that data is never collected or analyzed in a vacuum. Instead, the culture of the times acts as a lens that can either obscure or reveal truth. Here is one example, looking at the history of data collection concerning cancer and race.
Cary Gross, MD, is a professor of medicine and co-director of the Robert Wood Johnson Foundation (RWJF) Clinical Scholars Program at Yale University. Carley Riley, MD, MPP, is an RWJF Clinical Scholar and Brita Roy, MD, MPH, MS, is an RWJF/U.S. Department of Veterans Affairs Clinical Scholar. This post is part of the “Health Care in 2014” series.
As a new year begins, we are inundated with information summarizing the prior year: the top 10 movies, most newsworthy moments, and worst Hollywood breakups. Yet the topic that draws the most attention is the economy and our financial health. We gather a tremendous amount of information to assess this. The Census Bureau randomly selects 60,000 households each month, unleashing a swarm of 2,000 field representatives to track down the selected participants and assess their employment status. The Bureau of Labor Statistics surveys 500,000 businesses to estimate job creation. Approximately 5,000 “consumers” are surveyed each month to gauge their confidence. And so on.
So there you have it: we know that in 2013, the unemployment rate decreased from 7.9 percent to 6.7 percent, about 2.1 million new jobs were created, consumer confidence increased, and the Dow Jones index rose by 26.5 percent. Certainly, the health of the national economy is important, but is this the type of health that really matters most? When envisioning a healthy life, many people think about the sort of health that allows us to engage in enjoyable activities, maintain strong interpersonal relationships, and feel that our lives have purpose. A full assessment of health—of individuals, communities, and the country—should assess these dimensions.
Aren’t we already awash in data about health and well-being? Yes and no. There are abundant data concerning insurance status, prevalence of diseases, and utilization of health care. Additionally, large national survey efforts through the Centers for Disease Control and Prevention gather information on disease risk factors and health behaviors. But well-being is not captured by these data. Well-being is a comprehensive construct accounting for interwoven facets—such as physical, mental, and social health—that together comprise a global assessment of true health. It refers to a positive state of health that allows for the pursuit of meaningful activities, formation of a cohesive social network, planning for the future, and coping with, overcoming, and even growing from negative events.
Rural counties throughout the United States may be hardest hit by the country’s anticipated shortage of primary care physicians (PCPs), according to a new study from the WWAMI (Washington, Wyoming, Alaska, Montana, and Idaho) Rural Health Research Center at the University of Washington School of Medicine.
Researchers point to several factors that have implications for rural counties: PCPs deliver the majority of health care in those areas; a substantial percentage of primary care providers in the United States are approaching retirement age at the same time that fewer new medical school graduates are opting for primary care specialties; and demand for health care services is expected to increase as the population ages and millions gain health insurance coverage as a result of the Affordable Care Act.
The study, which used data from the American Medical Association and the American Osteopathic Association 2005 Physician Masterfiles, found a higher percentage of PCPs near retirement in rural counties than in urban ones, with the percentage increasing as the degree of rurality increased. (Physicians 56 or older in 2005 were considered to be near retirement and were the primary focus of analysis.) The 184 counties in the top 10 percent of near-retirement PCPs were characterized by lower population density and lower socioeconomic status, as measured by low education, low employment, and persistent poverty.
Timothy Landers, RN, CNP, PhD, is an assistant professor at The Ohio State University and a Robert Wood Johnson Foundation (RWJF) Nurse Faculty Scholar.
The Great Challenges Program is an ongoing effort by the TEDMED community to provide innovative, interdisciplinary perspectives on the most complex and challenging issues in health care. A year-long dialogue facilitated through social media tools and panels of experts continued at the annual gathering of TEDMED 2013.
One of the themes of TEDMED 2013 was the creative and thoughtful use of big data and small data to improve health and health care.
Small data includes individual level information specific to an individual or circumstance. In small data, “n=ME.” A vast amount of individual level information is now routinely collected. However, a large volume of data is not required for small data to be useful—in the words of one TEDMED speaker, it’s not the volume of the data, but the complexity of existing data. Data must be available and accessible in order to be useful as well.
Big data refers to patterns of data and information available at the population level. The goal of big data is to use information and take a “macroscopic” view of health. It includes the ability to recognize patterns that are not obvious or readily apparent. Big data analysis permits us to go from pieces of data to collective wisdom, a theme of TEDMED 2013.
Judith Hansen, MS, BSN, RN, is the executive director of the Wisconsin Center of Nursing and co-lead of the Wisconsin Action Coalition.
Since the release of the Institute of Medicine (IOM) report, The Future of Nursing: Leading Change, Advancing Health, leaders in Wisconsin have made concerted efforts to plan well and engage nurses and key stakeholders. Our goal is to empower them with a firm foundation so they will be ready to implement the report’s recommendations.
Our first task was to create awareness and knowledge of the IOM Report, so initial efforts began even before we were designated as a state Action Coalition. In September 2010, the University of Wisconsin-Madison (UW) School of Nursing launched the report by bringing ‘home’ Donna Shalala, PhD, FAAN, former chancellor at UW.
Shalala, also a former head of the U.S. Department of Health and Human Services, chaired the Committee on the Robert Wood Johnson Foundation (RWJF) Initiative on the Future of Nursing, at the IOM, and provided a powerful keynote address to engage the nurses of Wisconsin. To continue this process, the Wisconsin Center for Nursing (WCN), utilizing its partnership and grant funding through the Wisconsin Department of Workforce Development, sponsored a summit in May, 2011.
As the state’s nursing workforce center, WCN has existing partnerships with a vast array of partners including the Wisconsin Nurses’ Association, the Wisconsin Nurses’ Coalition, the Administrators of Nursing Education in Wisconsin, the Wisconsin Organization of Nurse Executives, the Wisconsin Department of Health Services, the Wisconsin Healthcare Workforce Data Collaborative, and baccalaureate and technical school education programs.
Data from the Bureau of Labor Statistics shows that health care employment rose by 44,000 jobs in September.
Most of the gains were in ambulatory care services (+30,000 jobs), with much of the growth in outpatient care centers. Hospitals added 8,000 jobs, and nursing and residential care added 6,000 jobs. Over the past year, employment in health care has risen by 295,000 jobs.
September’s gains are the second largest for the health care industry in a decade, according to a brief from the Altarum Institute, and the strong showing drove the health sector share of total employment to a new high of 10.81 percent.
By Jeannie P. Cimiotti, DNSc, RN, Executive Director, New Jersey Collaborating Center for Nursing, Associate Professor, Rutgers University College of Nursing
For decades, the Health Resources and Services Administration (HRSA) has employed experts in sampling and statistical analyses in its attempt to monitor the registered nurse workforce through the National Sample Survey of Registered Nurses (NSSRN). Though the NSSRN has been used widely to estimate the supply and demand of registered nurses nationwide, it is often criticized in that states appear to be underrepresented.
In New Jersey for example, it was reported that less than 1 percent of our registered nurses participated in the 2008 NSSRN. To address New Jersey’s issue of monitoring the nurse workforce, the New Jersey Collaborating Center for Nursing (NJCCN) has instituted a number of initiatives, including three surveys developed by the Forum of State Nursing Workforce Centers. These surveys assess New Jersey’s supply and demand of nurses, and the educational capacity of our nursing programs.
Even before the release of the Institute of Medicine (IOM) report, The Future of Nursing: Leading Change, Advancing Health, which recommends an infrastructure for collection and analysis of workforce data, NJCCN was collecting data on the educational capacity (registered nurse and licensed practical nurse) of all nursing programs statewide.
This year, the federal government did not continue a long-running survey of registered nurses that, since 1977, had provided a rich source of national data about nursing education and practice. Some nurse researchers are mourning the lapse of the survey, known as the National Sample Survey of Registered Nurses (NSSRN). Joanne Spetz, PhD, FAAN, professor, Philip R. Lee Institute for Health Policy Studies & School of Nursing; and faculty researcher, Center for the Health Professions, University of California, San Francisco, explains why she is among them.
Human Capital Blog: What does the lapse of the NSSRN mean for research about nurses and nursing?
Joanne Spetz: The NSSRN has been an important source of data for national and state policy-makers because it was designed to provide valid information about the nursing workforce at both the national and state levels. There are a few other surveys that can be used to get decent information about employed nurses for the nation, and for the largest states, such as the Current Population Survey (from the U.S. Bureau of Labor Statistics and the U.S. Census Bureau) and the American Community Survey (from the U.S. Census Bureau), but these data don’t yield any information about licensed nurses who are not working. They also don’t have enough data to help smaller states.
What many people don’t realize is that the NSSRN also has been used to learn about the basic behavior of the registered nurse (RN) workforce. Whenever we hear somebody talk about how much RN supply increases when wages go up, it is based on research from the NSSRN. What little we know about foreign-educated nurses comes from the NSSRN. Most research on wage discrimination, and the value of higher nursing education to nurses, also comes from these data. So, losing the NSSRN means we will lose a stream of basic research that helps us develop policies that will truly work to ensure adequate nursing resources.
By Patricia Moulton, PhD, executive director, North Dakota Center for Nursing and co-lead, North Dakota Action Coalition
In 2010, the Institute of Medicine (IOM) issued a groundbreaking report on the future of nursing that identifies as one of its key messages the need for improved data collection and an enhanced information infrastructure as requirements for effective workforce planning and policy-making.
The report, called The Future of Nursing: Leading Change, Advancing Health, recognizes that data “on the numbers and types of health professionals currently employed, where they are employed and in what roles” is imperative to the establishment of accurate workforce projection models. Such models are necessary to inform policy-makers in their aim to ensure effective workforce planning as well as to make needed changes in nursing practice and education to meet population needs.
Nurse leaders and researchers are working toward that goal.
In 2008, before the IOM released its report on the future of nursing, the Forum of State Nursing Workforce Centers embarked on a multi-year process to develop minimum data sets for the collection of nursing education, supply and demand data across the 34 nursing workforce centers. The minimum data sets were finalized in 2009 and are available at the forum’s website.
For the project, the forum’s research committee recently surveyed the 34 current nursing workforce centers to determine how many have implemented the minimum data sets.