Supporting rapid exchange of public health data is urgent, crucial and laden with challenges

By Jody DeVoll, advisor, communications, APHL 

In an era when digital communications move at blazing speeds, public health laboratories still have to resort to fax, email or phone to exchange data with some partners. Yet, this is only one of the obstacles to rapid exchange of critical public health laboratory data needed for public health surveillance, emergency response and patient care.

The volume of public health laboratory data presents an obstacle in and of itself. Infectious diseases, environmental toxins, foodborne illnesses, radiological exposure, hazardous chemicals, high consequence pathogens, antibiotic resistance: public health laboratories test them all. Add to this exponential increases in volume from the expansion of advanced molecular technologies like next-generation and whole genome sequencing, and the result is terabytes of data that public health laboratories must manage, interpret, store and share.

In addition, dozens of different, stand-alone systems make programming and maintenance of laboratory reporting systems labor-intensive and costly. For example, the US Centers for Disease Control and Prevention (CDC) maintains over 100 surveillance programs, each with its own reporting system. Dari Shirazi, APHL’s health information technology manager, explains how these many systems affect public health laboratory operations: “It’s as though you have a houseful of furniture to arrange in dozens and dozens of different houses and, periodically, you receive shipments of additional furniture that also has to be arranged.”

Of course, CDC is not public health laboratories’ only data exchange partner. Other federal partners, state and local health agencies, hospitals and others also require laboratory data, and they too want it parsed and transmitted through their proprietary systems.

With all these demands, data scientists at public health laboratories face a mountain of work, yet their numbers are few. The number of graduates in public health informatics has not kept pace with demands for workers from public and private sector institutions. As a result, graduates can choose from an array of positions, and they often choose private sector jobs which tend to be higher paying and longer-term than lower-salaried, time-limited positions at a public health laboratory.

Huge data volumes, a multitude of reporting systems and a shortage of public health data scientists make data exchange a laborious, costly and frustrating enterprise for public health laboratories. However, the implications extend beyond laboratories to the populations the data is intended to protect, in other words, us. According to Peter Kyriacopoulos, APHL’s senior policy director, “We are fast approaching the confluence of events on the management of public health data that threatens the very relevance of governmental public health. The volume of data generated by new laboratory technologies adds to the burden of over 100 inefficient data reporting systems that each have been designed to move specific information to a point at CDC, which constrains the utility of that information.

Fortunately, there are signs of change. Four national health organizations — APHL, the Healthcare Information and Management Systems Society (HIMSS), the Council of State and Territorial Epidemiologists (CSTE) and the National Association for Public Health Statistics and Information Systems (NAPHSIS)  – launched the Data: Elemental to Health campaign calling for a $1 billion investment in congressional funding over the next decade to modernize public health data/IT systems and develop a skilled workforce of data/IT specialists. Under the plan, state, local, tribal and territorial health departments would receive direct funding for these purposes through the CDC.

Over the last six months, the campaign has convened stakeholders, made the case for improved data systems to congressional and administration staff, appeared before the House Appropriations Subcommittee, hosted Hill briefings and organized a Day of Digital Action. Already there are results:

  • The House appropriations bill includes $100 million in fiscal 2020 for public health data systems and workforce modernization
  • The House LIFT America Act authorizes $100 million per year for five years to develop public health data systems and train staff
  • The Senate Saving Lives Through Better Data Act authorizes $100 million per year for five years for systems and people
  • The Senate Lower Health Care Costs Act authorizes “such sums as may be necessary” over five years to modernize data systems.

How would legislation initiated through the campaign support public health laboratories? First and foremost, it would help them to strengthen their LIMS. Shirazi explains, “A LIMS is a living, breathing thing that has to grow with lab needs. These needs change every year as the lab takes on new and novel types of testing.” Building LIMS capacity would enable laboratories to expand capability for data capacity, exchange and analytics; eliminate manual entry of test results; and provide secure, instantaneous communication of results to health partners. In addition, legislation initiated through the campaign would underwrite laboratory systems for exchange of electronic health records, National Notifiable Disease Surveillance System data, vital health records (e.g., notices of births and deaths) and other public health surveillance data.

Looking forward, the US would do well to complement the advances initiated under the Data: Elemental to Health campaign with a data transfer solution that consolidates all public health data systems into one. Kyriacopoulos notes that: “the creation of a single reporting site, that multiple data providers and users can report to and receive information from, would be a significant improvement that would allow for the efficient and comprehensive use of this data throughout the federal/state/local public health system.”

 

Photo credit: James Marvin Phelps

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New Lab Matters: The ABCs of PFAS

New Lab Matters: The ABCs of PFAS | www.APHLblog.org

First discovered in the 1930s, per- and polyfluoroalkyl substances (PFAS) now pervade almost every aspect of modern life. In fact, PFAS compounds are found in everything from dental floss to cookware. But human exposure to PFAS comes at a cost, and as old compounds are removed from production, new compounds take their place. So how does a public health laboratory handle this challenge with limited resources? As our feature article shows, by establishing new public-private partnerships.

Here are just a few of this issue’s highlights:

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Gordon Research Conference on Craniofacial Morphogenesis and Tissue Regeneration (February 11 – 16, 2018): Licia Selleri & Ophir Klein

  Gordon Research Conference on Craniofacial Morphogenesis and Tissue Regeneration (February 11 – 16, 2018): Licia Selleri & Ophir Klein   Posted August 22, 2018 by post-info As part of its mission to encourage engagement

History of the word ‘data’

Sandra Rendgen describes the history of “data” the word and where it stands in present day.

All through the evolution of statistics through the 19th century, data was generated by humans, and the scientific methodology of measuring and recording data had been a constant topic of debate. This is not trivial, as the question of how data is generated also answers the question of whether and how it is capable of delivering a “true” (or at least “approximated”) representation of reality. The notion that data begins to exist when it is recorded by the machine completely obscures the role that human decisions play in its creation. Who decided which data to record, who programmed the cookie, who built the sensor? And more broadly – what is the specific relationship of any digital data set to reality?

Oh, so there’s more to it than just singular versus plural. Imagine that.

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PLOS Biology in the media – April

post-info April was a truly diverse month at PLOS Biology. This month we are talking about gravity-defying fungi, representation of endangered species in the media, gender gaps and information gaps in scientific research and why

Protocols: The Devil is in the Details

0000-0002-8715-2896 Protocols: The Devil is in the Details   Posted May 3, 2017 by Emma Ganley in Announcement, Biology, Data, Debate, Editorial policy, News, Open access, PLOS Biology, Policy, Publishing, Resources, Video post-info AddThis Sharing

Anaesthesia Response, Controlling Cas9, and How to Use Github: the PLOS Comp Biol January Issue

social_norms_in_small_scale_societies-5-690x320AddThis Sharing Buttons above Here are our highlights from the PLOS Computational Biology January issue: Brain Connectivity Dissociates Responsiveness from Drug Exposure during Propofol-Induced Transitions of Consciousness Scientific understanding of how brain networks generate consciousness

Episode 3: Managing scientific data feat. Tracy Teal

Good data management is so important to science, but learning how to use tools for handling data is a significant time investment. In this month’s PLOScast, Elizabeth Seiver speaks with Tracy Teal, the Executive Director

3 critical lessons learned from Louisiana’s flu data

By Melissa Warren, Senior Specialist, Influenza, APHL and Kelsey Vellente, Senior Technician, Food Safety & Infectious Disease, APHL

It’s flu season, the dreaded time of year when everyone hopes that they are not one of the thousands of Americans who falls ill. While the public gets their vaccines, loads up on hand sanitizer and researches magical tea recipes “guaranteed” to fight the flu, public health labs and epidemiologists prepare to test specimens and collect data that will provide a more detailed look at how this potentially serious virus is impacting the public’s health.

3 critical lessons learned from Louisiana’s flu data | www.APHLblog.orgSo what data is collected and what does it tell us? To get a better understanding, we spoke with Julie Hand, public health epidemiologist in the Infectious Disease Epidemiology Section of the Louisiana State Department of Health & Hospitals, who shared some of the most telling pieces of data they collected during the 2014-2015 flu season. (Louisiana has a centralized public health system which means there are no local or county departments of health. All flu surveillance work is performed at the state level.)

In Louisiana (and most other states), flu reporting is voluntary. There is no requirement for clinical staff to notify the state of flu cases. Louisiana has been working closely with hospitals and other clinical facilities to encourage flu reporting. In 2014-2015, approximately 45,000 rapid influenza diagnostic test results were reported (up approximately 25,000 from the previous season). More specimens and data provided by clinical facilities means the state can compile a more complete and meaningful picture of the flu season and its impact on the public.

While data was collected across various age ranges and geographic regions of the state, there were two different school outbreaks that were particularly interesting: one was influenza A (H3N2) and the other was influenza B. Both outbreaks peaked in November, only one month after the official start of flu season.

Here are the three critical lessons learned from Louisiana’s flu data:

1. Within those school outbreaks, the majority of people who were vaccinated at the time of infection had not received their vaccination early enough to have immunity.

  • Influenza A outbreak: 34% of those infected had been vaccinated but only 9% of those received their vaccination more than two weeks before the outbreak.
  • Influenza B outbreak: 16% of those infected had been vaccinated but only 1% received it more than two weeks before the outbreak.

Why does this matter? After receiving the flu vaccine, it takes about two weeks for your body to develop immunity. So while people thought they were protected, their bodies were not yet immune to the circulating flu virus. Flu season is a time to be proactive not reactionary – don’t wait for an outbreak to get vaccinated.

2. Antibiotics were prescribed to a surprisingly high number patients in those outbreaks, however antibiotics do not work to fight viruses such as influenza.

  • Influenza A outbreak: 20% of patients received antibiotics
  • Influenza B outbreak: 29% of patients received antibiotics

As stated above, antibiotics don’t fight viruses like influenza – they fight bacterial infections. Overuse of antibiotics when they will not be effective – such as in cases like this – contributes to the growing public health threat of antibiotic resistance. Medical professionals should be aware that treating flu with antibiotics isn’t recommended and is contributing to a larger public health problem.

3. In Louisiana during the 2014-2015 flu season, only those who received the quadrivalent vaccine were protected against the most prevalent strain of influenza B.

There are two categories of flu vaccines – trivalent (three strains) and quadrivalent (four strains). They both include a combination of influenza A and B strains, but the genotypes of the strains included in each season’s vaccines vary depending on what is expected to be most prevalent. In 2014-2015, influenza B Yamagata and Victoria lineages were included in the quadrivalent vaccine, but only influenza B Yamagata was included in the trivalent vaccine.

Influenza B accounted for 20% of all reported flu cases in Louisiana (state lab PCR results). Louisiana’s genotyping data showed that of those…

  • 74% were influenza B Victoria – the strain not included in the trivalent vaccine
  • 26% were influenza B Yamagata – the strain included in the trivalent vaccine

As each flu season comes and goes, data is critical to helping departments of public health understand which aspects of flu surveillance can be eliminated, continued and/or adjusted. And with every improvement and every new bit of previously unknown information, officials like Julie and her colleagues can help shape programs that protect the public from this hated virus.

Cell Volume, Self-Organisation, and Escher: the PLOS Comp Biol August Issue

Here are our highlights from August’s PLOS Computational Biology   The Role of Cell Volume in the Dynamics of Seizure, Spreading Depression, and Anoxic Depolarization Cell volume changes are ubiquitous in normal and pathological activity of the brain, yet we know … Continue reading »

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