PHI “in the news”

In the news part 2

Article 1 A Field Of Medicine That Wants To Know Where You Live by ALISON BRUZEK

As a geographic information systems (GIS) representative, I would like to introduce the concept of “geomedicine” and explain the role of geographic information systems and the positive implications for public health.  Location and environment have not been central in medicine, although there is new interest to consider this information in patient care.  Dr. Manchada notes “we are creatures of our environment.”  Perhaps the most famous association of location and disease is attributed to Dr. John Snow during the cholera outbreak in London of 1854.  Dr. Snow realized that location of victims of the cholera outbreak centered around a water pump on Broad St. in London, and concluded that water was from that pump contaminated.  Eventually local authorities removed the handle from the water pump.  A simple GIS, Dr Snow’s map, allowed him to curb the outbreak.

Dr. Manchanda presents a more recent example of using GIS tools in healthcare.  Working with GIS researchers, Dr. Manchanda linked 54,000 patient home addresses with maps of public housing data.  1 of the patterns that emerges is that asthma is more likely to be found in houses that are known to be infested with mold.  Both of these examples show the potential GIS has to improve public health.

The field of geomedicine, which refers to the “use of mapping in healthcare” has not flourished.  Some of this is attributed to the inability to quantify cost savings.  However, available data continues to expand with new health applications and technology, much of which has the ability to give a GPS location.

A geographic information system incorporates computer hardware, software and data which allows for mapping and analysis of data.  GIS mimics a database.  The distinguishing feature of a GIS is that every data point is tied to a geographic location.  There are 2 types of data that are incorporated into a GIS, spatial data and attribute data.  Spatial data are the coordinates that indicate a location on earth.  This data is linked with the attribute data.  Attribute data are variables that are the non-spatial aspects of the database.  Examples of this include number of a school children in a county, and immunization status of those children.  The attribute data and spatial data are linked in the GIS with a geocode, which is geographic identifier that is contained in both data components.

Both of the examples given in the article are epidemiological examples, however GIS has wider applications beyond that in public health.  One example is the Long Island Breast Cancer Study Project which was a consortium of 10 research projects to determine the cause of increased breast cancer incidence in Long Island, NY.  GIS techniques can illustrate distances from hospitals and medical centers to help planners determine the best site for a new facility.  Maps can be drawn to show mammography screening rates in a neighborhood or cervical cancer mortality rates within a community.

Geographic information systems will continue to provide useful public health information as the field of geomedicine expands to include relevant health and geographic data.

 

Article 2 Big data saves lives By Marco Lübbecke

The author of this CNN article advocates for “big data” in health care and provides examples of success stories in public health to solidify his point. Furthermore, as a CDC officer I will explain and define “big data,” and explain how some of this collected is collected and then used by public health officials.

The term “big data” is somewhat simplistic as it implies simple, vast data collection. But big data refer to large, often complex data sets, which are “interconnected and interrelated.” Furthermore, big data is characterized by volume, velocity, and variety. The raw facts and figures, or data, are analyzed and then this data becomes useful information and can be applied. This information is what allows public health officers make policy to protect the public.

The example of polio eradication is a key milestone in public health. CDC officials used data compiled from across the globe regarding polio, a devastating infectious viral disease than can cause paralysis. The CDC had to appropriate available funds for controlling outbreaks of polio or attempt to stop new cases of polio. Officials applied scientific evidence and field knowledge collected around the world to develop mathematical models. The results of the model allowed the CDC to conclude it would be possible to “prevent any further cases of wild polio viruses from emerging.” Similar techniques have been used to counter terrorism.

As public health officials examine data, there are several factors that characterize “good” data or data that is deemed appropriate for use. This includes accuracy and completeness of data. The data should be timely, sufficient and cost effective. Several sources of public health data are available such as global information from the world health organization, global health observatory and the centers for disease control, wide ranging online data for epidemiologic research (or WONDER) data.

The CDC has also implemented a strategy for public health surveillance, and defines it as “the ongoing, systematic, collection, and analysis and interpretation of health data, essential to the planning, implementation, and evaluation of public health practice, closely integrated with the dissemination of these data to those who need to know and linked to prevention and control.” CDC has partners in this effort including at the state, local, and federal levels.

Data collected for public health surveillance comes from several sources, and from all levels of the health care system. For example, public health agencies receives lab results for certain diseases that are of public health interest. Other sources of data include surveys of healthcare practitioners, electronic health records (EHR), and data from insurance claims and administrative sources. Specifically, syndromic surveillance data is real time data from hospitals and ambulatory doctor offices; however, this data includes no patient identifier but remains a key source of information. This data may be supplemented with field investigations when necessary. For example, a field investigation may entail tracking contacts of an index patient with an infectious disease. This was relevant in 2019 with an outbreak of measles was in the United States and lung injuries associated with vaping.

While the author presents 2 examples for “big data” in healthcare, this term incorporates a much larger strategy. Data, transformed into information, allows public health officials solve long standing public health challenges. However, big data also has the ability to keep the public safe and improve public health.

 

 

In the news part 1 :Public health informatics and health information exchange

Article 1 Use of Patient Medical Information Not Carefully Studied By Kimberly Leonard

This article in US News summarizes a recent review of health information exchange (HIE) by the RAND corporation. HIE is 1 of the components of the 2009 federal Health Information Technology for Economic and Clinical Health Act (HITECH) to promote exchange of health information. However, the efficacy of HIE has not been evaluated until now. I am a health informatics field representative for a local health care system, and I will summarize and expand upon key points of the article.

Access to health information is disorganized and cumbersome in the US. Healthcare practitioners are often unable to access information that is contained in another institution, such as a pharmacy, hospital, or ambulatory facility. Improving HIE is one way to alleviate this burden. Health information exchange is “designed to reduce health costs and overuse of resources.” However, beyond that HIE describes the ability of health care practitioners to be able to access health information and data that is contained at a separate facility that is not part of the same healthcare system. Improved sharing of information may also reduce medical errors.

The review found that there are barriers to “acceptance and sustainability of HIE.” 1 concern is the security of private health information, which is amplified because many states have adopted stricter privacy laws as compared to the federal HIPAA privacy law. Our ability to create a common foundation for privacy and security issues will enhance continued development of HIE. Secondly, cost concerns hinder sustainability. The RAND study was not able to decisively conclude that there was significant cost savings, mostly as a result of too little data regarding cost measures.

Furthermore, scientists and healthcare workers associated with the a HIE in Indiana, the Indiana Network for Patient Care, caution that if cost savings is the primary goal, HIE will likely fail. I believe success of HIE will be the result of improved health and healthcare delivery. Therefore, if patients, health care workers and health care institutions are able to coordinate efforts and promote improved health care delivery, this may reduce the focus on costs and focus attention on the benefits of improved HIE. For example, better public health.

Once public health officials are able to obtain information already available in electronic health records (EHR), this will reduce the cost of public health infrastructure, indirectly reducing healthcare costs. The previously mentioned HITECH act focuses on 4 public health measures, which are immunization registry reporting, electronically reported laboratory results, syndromic surveillance, and cancer registries. A concerted effort among all healthcare stakeholders to improve health information exchange and health data sharing will lead to better healthcare delivery and public health.

 

 

Article 2 The fax of life By Sarah Kliff

This article illustrates the fragmentation of health information sharing in the United States, primarily from the perspective of an Ob/GYN physician.  As a diagnostic radiologist, I share similar experiences regarding communication of health information.  And as the chief information officer of a local healthcare system, I will illustrate how the government has attempted to improve health information sharing.

The gynecology practice highlighted in the article is typical of a medical practice today.  While most healthcare entities, including outpatient facilities and hospitals, have largely adopted some form of electronic health record (EHR), these records do not communicate with each other. Therefore, information from the outpatient OB practice is not passively relayed to the local hospital where many of the patients deliver their babies.  Furthermore, the radiology practice within the same building faxes its reports to the OB doctors rather than an automatic electronic delivery to the EHR. Whenever I find urgent findings on a diagnostic radiology exam, I also fax a report to the referring physician promptly, so the referring doctor may act on it.

This OB practice finds similar limitations with lab results, that may or may not be available when the patient returns to the office for consultation.  Furthermore, paper versions of the patients’ health records are hand delivered to the hospital as the patient reaches term pregnancy.  Accidents occur there as well, if the patient delivers her baby early and the record has not yet been sent to the hospital.  Or the record gets misplaced.  This hindrance in health information sharing is the mainstay of current healthcare in the United States.

The adoption of EHR accelerated from 2008 to 2015, much of this was the result of a government incentive program.  The 2009 HITECH act included $30 million to encourage adoption of EHR and a component of the law called “meaningful use;” however, the limitation of this law was that it failed to mandate the EHR communicate with each other.  This has contributed to the current predicament, even though EHR utilization grew from 9% in 2008 to 83% in 2015.  Furthermore, HITECH also underestimated healthcare institutions willingness to share health data as they view this data as somewhat proprietary.

Meaningful use has several staggered stages to allow healthcare entities to plan and adopt these initiatives.  For example, 1 of the stage 1 meaningful use concentrations is “electronically capturing health information in a standardized format.”   Once this objective is met, it would be translated to “more rigorous health information exchange” as part of stage 2 meaningful use.

Furthermore, the Affordable Care Act (ACA) of 2010 also had components to encourage more collection of health data, but also see that better data is collected.  In the end, the crafters of these government programs hoped their efforts would lead to “improving population health,” 1 of the goals incorporated in the third and final stage of meaningful use.

 

 

References:

J.A. Magnuson, P.C. Fu, Jr. (eds.), Public Health Informatics and Information Systems, Health Informatics, DOI 10.1007/978-1-4471-4237-9_22, © Springer-Verlag London 2014

McDonald, C. J., Overhage, J. M., Barnes, M., Schadow, G., Blevins, L., . . . & the INPC Management Committee. (2005). The Indiana Network for Patient Care: A Working Local Health Information Infrastructure (Links to an external site.). Health Affairs, 24, 1214-1220.