The 1:100,000 NHDPlusV1 stream network over the conterminous US. The Mississippi basin is emphasized dark blue. The inserted box shows an example of complexity within stream networks, including braided streams.  Credit: Yin-Phan Tsang, Center for Systems Integration and Sustainability, Michigan State University

Today's natural resource manager tending to the health of a stream in Louisiana needs to look upstream. Way upstream - like Montana. Michigan State University (MSU) scientists have invented a way to more easily manage the extensive nature of streams.

There are 2.6 million stream reaches in the contiguous United States that are intricately interconnected. It's impossible to address the health of one reach without knowing what's happening upstream.

Science, wielding geographic information systems, has obliged with data on geology, climate, pollution and land use. But with that wealth of information comes a crushing amount of data files, making analysis slow and cumbersome.

In the current open-access edition of Springer Plus, Yin-Phan Tsang, a research assistant in MSU's Center for Systems Integration and Sustainability (CSIS), and her team present a new database and algorithm that allows other researchers and conservation managers to understand what's coming downstream without being weighted down by data files.

"Before, we needed a week to do an analysis on one parameter of land use in stream catchments," Tsang said. "Now, we can run 24 parameters for every one of the 2.6 million streams in five hours."

The algorithm script, included in the paper, can tackle entire countries, but also works with any database to characterize landscape factors in smaller areas. It just needs the regions in question to have its streams broken down into small "discrete" units assigned a unique identifier and an identifier that shows its upstream connectors.

Members of the aquatic landscape ecology lab and CSIS, parts of the Department of Fisheries and Wildlife, spend their time working to understand how landscape factors like agriculture and urban land use influence the physical characteristics like rivers and streams.

The paper, "An approach for aggregating upstream catchment information to support research and management of fluvial systems across large landscapes," was written by Tsang, Daniel Wieferich and associate professor Dana Infante from MSU, Kuolin Fung of 2DiiKaTwenty9 in East Lansing and Arthur Cooper of the Department of Natural Resources, Institute for Fisheries Research in Ann Arbor.

"We had been really struggling with one parameter at a time," Tsang said. "We are tired of it and we knew there was a better way to do this.."

More than 110,000 individual deaths and their causes across 13 countries, including Ghana, South Africa, Kenya, Bangladesh and Vietnam, are contained in the new INDEPTH dataset. The data, collected by hundreds of researchers over two decades, are the first meaningful community-based information about cause of death in countries where individual deaths are not recorded automatically by national governments.

The INDEPTH cause of death findings are published in a special issue of the journal Global Health Action, which is fully open access. There are six multisite papers dealing with specific causes of death: HIV/AIDS, malaria, pregnancy-related, external causes (including accidental death and suicide), adult non-communicable diseases and childhood illness. Other papers describe methods, and many sites have contributed papers with local details. The project has been substantially funded by the Wellcome Trust.

The data were collected in 22 sites, each containing around 100,000 people. Each death was recorded by a researcher in the field who conducted a standardised verbal autopsy, a structured interview with a family member of the deceased. Data were supercomputer-processed to establish likely causes of death.

The entire dataset (also now available in the public domain), which at some sites includes cause of death data collected as far back as 1992, represents more than a century of working time. It also proves that data relating to cause of death can be reliably collected by non-medical staff outside of a clinical setting.

Overall, the data provide a strong case for the value of recording cause of death for planning and improving public health services. They show high variability in cause of death across sites, particularly in deaths caused by endemic diseases such as malaria and HIV. Although the picture is complex, there is some evidence to link mortality with differing investment in healthcare over the two decades of the study. For example an INDEPTH site in rural northeast South Africa has documented the peak of HIV/AIDS-related deaths and is now seeing a substantial decline in HIV/AIDS mortality as public health programmes start to take effect.

The INDEPTH collaboration is able to estimate the global burden of major diseases. For example, they calculate that that under-5 child mortality ranged from 15 per 1,000 in the Vietnamese site to 152 per 1,000 in one Kenyan site. Malaria mortality ranged from zero at one Bangladeshi site to more than 2 per 1,000 in parts of Africa. HIV/AIDS mortality was more than 300 times higher in some African sites compared with Asian levels.

Unlike other mortality estimates, such as the ones made by United Nations agencies and the Global Burden of Disease project in Seattle that are based on mathematical models, the INDEPTH estimates are based on information about real deaths in defined areas of the population. Encouragingly for researchers, the findings of INDEPTH are very similar to the outputs from the mathematical modelling techniques, indicating that they confirm each other.

There are other important specific findings from the dataset. Across the countries, the data show consistently high rates of maternal and childhood mortality. Childhood drowning in Bangladesh and homicide among adult males in eastern and southern Africa are other causes for concern. Mortality from non-communicable diseases, particularly in younger adulthood, is an emerging problem, accounting for a high proportion of deaths in Asian countries.

Osman Sankoh, Executive Director of INDEPTH said: "It pleases me to note that our own scientists have conducted the research, generated, cleaned and analysed the data, and have written the papers in this Journal. Together with these publications we are making the datasets freely and widely accessible to the public on the INDEPTH Data Repository. This INDEPTH approach confirms that if scientists from low- and middle-income countries are funded to be able to analyse their data and publish their work, they will unquestionably make their data publicly available."

Marcel Tanner, Chair of the INDEPTH Board of Trustees, Director of the Swiss Tropical and Public Health Institute in Basel, Switzerland, said: "A fundamental achievement of INDEPTH that should encourage an international discourse on cause-specific mortality in these resource-poor settings."

Peter Byass, Director of the Umeå Centre for Global Health Research in Sweden, and a long term member of the INDEPTH collaboration, said: "Good cause-of-death data are absolutely essential to well-functioning public health systems. Thinly-stretched health care providers are not necessarily best-placed to consistently deliver reliable cause-of-death data, and many deaths do not occur in health facilities."

He added: "We have shown here that standardised verbal autopsies – now typically reduced to a 15-minute interview with a family member and carried out by non-clinical staff – can provide valuable data at modest cost and effort."

Ties Boerma, Director of Health Statistics and Information Systems at the World Health Organization, who has written an accompanying editorial for the special issue of Global Health Action, said that INDEPTH "presents the largest dataset of this nature ever," adding that this work "needs to be considered in the context of the need to strengthen country Civil Registration and Vital Statistics systems, and should be a central element in the post-2015 development agenda."

Abbas Bhuiya, Deputy Executive Director of the International Centre for Diarhoeal Disease Research, Bangladesh, a founding member centre of INDEPTH, said: "INDEPTH provides us the forum to present research results from several continents; this publication will make Asian and African policy makers see cause-specific mortality situations in other continents."

Fred Binka, the first Executive Director of INDEPTH, now Vice Chancellor of the University of Health and Allied Sciences in Ho, Ghana, said: "Publishing these crucial data and results is a huge achievement of INDEPTH. I am delighted that the Network is taking a lead role in the big data revolution from the Global South."


The much-talked-about Google Glass — the eyewear with computer capabilities — could potentially save lives, especially in isolated or far-flung locations, say scientists. They are reporting development of a Google Glass app that takes a picture of a diagnostic test strip and sends the data to computers, which then rapidly beam back a diagnostic report to the user. The information also could help researchers track the spread of diseases around the world. The study appears in the journal ACS Nano, a publication of the American Chemical Society, the world's largest scientific society.

"It's very important to detect emerging public health threats early, before an epidemic arises and many lives are lost," says Aydogan Ozcan, Ph.D. "With our app for Google Glass and our remote computing and data analysis power, we can deliver a one-two punch — provide quantified biomedical test results for individual patients, plus analyze all those data to determine whether an outbreak is imminent."

Google Glass looks like a pair of eyeglasses without the lenses, but with a small rectangular transparent screen near the right eye that functions as a tiny computer screen. A mouse is built into the right arm of the frame.

Ozcan and colleagues at the University of California, Los Angeles, designed a custom app for Google Glass. The app uses Glass' built-in camera to take a picture of a diagnostic test, called a lateral flow immunochromatographic assay. A familiar example of such an assay is a home pregnancy test.

The wearable computer transmits images of these test strips with their custom-created Quick-Response (known as "QR") code identifiers to more powerful supercomputers in other parts of the world for analysis. Then, a quantified diagnostic result is beamed back to the Google Glass user. If the user is in a remote area without Wi-Fi, then he or she can connect Glass to a smartphone to transmit the data along with geographical information for disease tracking.

In pilot tests, the team successfully used the method with HIV and prostate-specific antigen (known as "PSA") assays. Results were available within eight seconds for each individual test. They could even take a picture of several test strips next to each other in one image and come up with the correct diagnoses.

Other medical diagnostic devices based on smartphone technology, including one recently developed by Ozcan's team, require additional equipment to be attached to the device. Or they require extensive handling of the device and the tests. But the researchers note that their Google Glass set-up works without any external hardware attachments. It is also hands-free, allowing busy technicians to quickly go through many patient tests in a short period.

The report, which was issued by Calit2 with support from the Robert Wood Johnson Foundation, also indicates that researchers and companies are eager to access and use self-tracking data, although doing so will require new research methodologies and business models. 

San Diego, Calif., March 13, 2014 – A new report from the California Institute for Telecommunications and Information Technology (Calit2), supported by the Robert Wood Johnson Foundation, suggests that many people who track health-related data with wearable devices and smartphone apps are interested in sharing that data with researchers in medical and public health — provided adequate privacy controls exist. 

The report, titled "Personal Data for the Public Good: New Opportunities to Enrich Understanding of Individual and Population Health,” can be found here: 

It also indicates that a large number of researchers are eager to access and use self-tracking data to fill in gaps in more traditional clinical data collection, although doing so will require new research methodologies and business models for companies which deal in such data. 

The report was prepared by the Health Data Exploration project at Calit2 using a convenience sample of individuals and researchers who are already generating or using digital self-tracking data. Among survey respondents, the five most common health conditions tracked were exercise, diet, weight, athletic activity and sleep. 

“Behavioral research has always depended on observations made in the laboratory or the clinic,” said Robert Kaplan, a member of the Health Data Exploration Advisory Board and Associate Director for Behavioral and Social Sciences at the National Institutes of Health. “Now we can bring the laboratory to the person in his or her own environment. This greatly enhances the opportunity to learn about the determinants of behavior in the natural environments of everyday life.” 

The Health Data Exploration project, which is funded by the Robert Wood Johnson Foundation, is exploring how to bridge the “worlds” of health researchers, the set of mostly private and often small technology companies that hold these data, and individuals who may want to donate their own health or medical data. 

“We are encouraged to discover a willingness of a large number of behavioral and social scientists to partner with data scientists to delve into the depths of consumer-generated data,” said Lori Melichar, Senior Program Officer at the Robert Wood Johnson Foundation. “We are hopeful that we will be able to facilitate mutually beneficial partnerships between companies and researchers that can produce new insights into perplexing health challenges.” 

Sharing Personal Health Data 

Among individuals surveyed, the dominant condition (57%) for making their personal health data available for research was an assurance of privacy for their data, and over 90 percent of respondents said that it was important that the data be anonymous. On the whole, survey participants said they would be more likely to share their data if they knew that it would only be used for public good research. 

"We have known for a long time that altruism is a big reason why individuals participate in research studies that contribute to the common wealth, notably by evaluating new pharmaceuticals or medical devices,” said Dr. Kevin Patrick, a professor of Family and Preventive Medicine in the University of California, San Diego School of Medicine and a lead author of the report with Qualcomm Institute Chief of Staff Jerry Sheehan. “It's reassuring to see this same attitude applied to these new forms of health data." 

A Growing Area of Research 

Forty-six percent of the researchers interviewed for the report have already used self-tracking data in their research, and 23 percent have already collaborated with application, device or social media companies. These findings expand on a series of reports that have emerged in the past few years from the Pew Foundation, the Institute of Medicine and others, all of which point to what Patrick calls “a landscape of opportunity” for using ‘big data’ to improve public health. 

Patrick cautions, however, that from a research standpoint, the increasing volume of self-tracked data across large groups of people – for example people who use Fitbit™ to track their physical activity – raises entirely new methodological issues for researchers. “The amount of data captured by these devices and apps dwarfs anything that we have ever had before. New computational and analytical strategies will need to be applied that have not commonly been used in health-related research," he said. 

In addition to the challenges of dealing with the complexity of more data, Patrick says that researchers and bio-ethicists also need to consider carefully the appropriate ethical model for assessing the rights and responsibilities of individuals who are sharing their personal data. These considerations, which require additional qualitative research to better understand the expectations for privacy for personal health data, will help guide future policy considerations regarding informed consent. 

Geoffrey C. Bowker, a professor in the Department of Informatics at UC Irvine and a founding member of the social science Big Data Council, concurs. 
"The emergent field of the Quantified Self (QS) holds the possibility of transforming the generation and deployment of data about ourselves—and thereby of informing the generation of medical knowledge. Understanding how and why people use QS and how changing attitudes to privacy affect QS data is a core task for social scientists in this domain working with both design and policy communities." 

The Business Case 

Opportunities and obstacles for using personal health data also exist from a business perspective. Through a series of interviews, the report found that although companies which deal in such data consider advancing research a worthy goal – especially if that research validates the utility of their device or application – their primary business concern is maintaining their customer relationships. A number of companies interviewed were open to data sharing with academics, but noted the slow pace and administrative burden of working with universities as a challenge. 

Companies are already emerging to meet that challenge, according to the report. San Diego-based Small Steps Labs has developed a software platform called Fitabase that collects data from Internet-connected consumer devices and allows anyone – including researchers – to aggregate, analyze and export data gathered from people wearing the devices. 

“You could say my entire company and product exist because of these new friendly consumer wearable sensors like the Fitbit,” said Fitabase CEO and Founder Aaron Coleman. “People are (rightfully so) skeptical of health tools that are one-size-fits-all and don't attempt to understand them. Greater access to data helps us make more relevant tools that fit the lifestyle of the person who is engaging our tools to better their health.” Prior to founding Fitabase, the UC San Diego alumnus (B.S. ’06) led a software development team in Calit2’s Center for Wireless and Population Health Systems, which designed several systems and platforms used for health related research. 

University of Cincinnati research shows advances in data analysis technology are proving to be effective weapons for controlling the billions of dollars lost to Medicare and Medicaid fraud

The annual bill for Medicare and Medicaid fraud hit 11 digits in 2012. That's tens of billions.

The numbers might be daunting, but University of Cincinnati research shows that recent strategies to combat this unique form of white-collar crime are increasingly effective.

"Estimates show that Medicare and Medicaid fraud cost somewhere in the range of $29.8 billion to $99.4 billion in 2012," says Michael T. Czarnecki, a doctoral student in UC's College of Education, Criminal Justice, and Human Services. "This means that every day in 2012 Medicare and Medicaid fraud averaged between $81.5 million and $271.5 million, with every hour averaging between $3.4 million and $11.3 million lost to fraud. But the evolution of fraud control strategies has demonstrated some effectiveness in combating this problem."

Czarnecki will present his research "Medicare Fraud: The Controllers are Fighting Back" at the Academy of Criminal Justice Sciences (ACJS) annual meeting to be held Feb. 18-22 in Philadelphia. The ACJS is a 50-year-old international association of scholars and professionals dedicated to promoting criminal justice education, research and policy analysis. Czarnecki's research reviews what's known about Medicare and Medicaid fraud and how it's controlled, especially how control strategies have evolved during the past decade.

Medicare loses billions of dollars to fraudulent claims every year, according to U.S. Department of Health and Human Services and the Department of Justice. Some examples of Medicare fraud provided by these departments include: a health care provider bills Medicare for services you never received; a supplier bills Medicare for equipment you never got; and a company uses false information to mislead you into joining a Medicare plan. Ultimately, the fraud raises health care costs for everyone.

Recent advances in data analysis technology have given federal controllers, such as the Health Care Fraud Prevention and Enforcement Action Team, new and effective weapons in the fight against fraud, Czarnecki says.

"Controllers are getting better at identifying irregular and suspicious patterns in claim submissions," he says. "Collaboration and data sharing between agencies have improved. Teams are focusing their efforts in cities identified as hot spots."

The results are encouraging. Czarnecki's research shows that for every dollar spent to control fraud from 2009-2011, $7 was returned. In fiscal year 2011, $2.5 billion of Medicare funds were recovered; in 2012, more than $3 billion was recovered.

"Every dollar that is saved from fraudsters can be reallocated to some useful purpose such as providing better health care or reducing overall health care costs," Czarnecki says.

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