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Article 1 : G.E.’s Bid to Connect Computerized Health Records
This article is about General Electric and its attempt to help create a large hub for Health Information Exchanges and to help provide large data-sharing sites for health care organizations.

Summary:
The article discusses General Electric’s push towards creating an information health exchange and the challenges and issues that need to be addressed in order to be successful in this venture. General Electric is looking to create a large data hub that will collect and store massive amounts of health information and data gathered from health care sites and clinics. The article mentions that General Electric has an initiative to invest $90 million dollars into its new “eHealth unit.” Included in this unit, General Electric will be offering unique software that offers security for sharing and storage of patient data as well as a web portal that can help doctors pull and access any patient information securely and easily. The article also mentions that the eHealth initiative is more than just a national venture and will include international cooperation and data as well. In addition to this, the database will also allow for notifying physicians of when their patients have been admitted or released from care as well as aggregated tracking of a patient’s lab and radiology tests. The article makes an important note as well that most physicians and health care groups are not incentivized to make their collected data available for sharing and are usually not paid to do so either. This does make the access and sharing of health data more difficult than expected.

Impact Assessment
Sharing and providing health information through large data hubs can provide many unique benefits that further the health care field both in the clinical application setting as well as in the research section. Companies such as General Electric that have the investing power to create these data hubs and maintain and provide the required maintenance and security needed for these. With the ability for researchers and clinicians to generate and analyze large amounts of data very quickly and easily the need for these data hubs is ever more prevalent. From the standpoint of a CDC officer, having access to these databases provides them with the ability to examine different population groups and demographics even if they may have no physical contact or access with these groups. This can allow for even more robust conclusions and reporting of different population health metrics. Chief Information Officers also can benefit from the creation of large health information exchange hubs by being able to access these databases without investing the additional capital required if the health care site was to create their own health information database. Even GIS experts can take advantage of these data bases by using demographic and geographic information that may be incorporated into patient health data allowing for unique mapping of areas with regard to different patient characteristics. Overall, the creation of large health information exchanges can provide a multitude of benefits and have a large impact across many different subfields with in the public health realm.

Article 2: Will Gathering Vast Troves of Information Really Lead To Better Health?
The article from NPR addresses the possibility of if collection large amounts of information is actually advantageous or if the information itself is more useless due to possible lack of specificity of the collected information.

https://www.npr.org/sections/health-shots/2017/12/28/572677879/will-gathering-vast-troves-of-information-really-lead-to-better-health

Summary:
The article addresses the idea of precision medicine and how the push towards this has created the ability for many to generate vast amounts of data and store these large amounts of data. The article goes further to describe the endless research and clinical applications that could result from the collection and analysis of this data however, it also points out that these large amounts of data could actually be detrimental to the advancement of health care by providing more information that may be necessary and preventing those who need the data from accessing the more specific data that may be needed. The article goes into detail as well about how it may not be necessary to pour more money into creating more advanced technologies for the sole purpose of collecting more and more data. It mentions that it may be more beneficial to examine public health issues through information on current effective treatments of patients instead of breaking each patient down into vast amounts of smaller information bits that may end up being useless in helping to treat their conditions. It ends with mentioning that whether the push for personalized medicine takes off or if it fizzles out that the data collected can help reduce costs while improving treatments and care is something that clinicians and researchers will need to be able to prove before pushing full steam ahead towards personalized medicine and the creation of large health information databases for sharing.

Impact Assessment
With the ease of technology allowing for creation of large amounts of data and with the ease for modern computers to analyzed and return valuable results and additional information really changes the way those in the health care field and those involved in health care information have to go about their work. For example, GIS experts may have much more information that is useful to them if geographic information is able to be integrated in with patient health data and made available. This exchange of health information could prove to be beneficial in that scenario but in the same time could provide an additional challenge to a Chief Information Officer in many different ways. This could range from providing the health care facility with the additional computing power and storage for this additional data to ensuring that HIPAA guidelines are still being adhered to if geographic information is provided with patient data that is accessed by or provided to that site. Also, ensuring that all the data provided is specific enough and able to be used to provide quality care based upon the data analyzed and shared. In the same breath however, there are also many different entities that can also benefit from this large amount of data being shared and being made available. For example, additional data can prove to be beneficial for a CDC officer who may need this data to paint a more robust picture of population health in a specific area, especially in regards to disease clusters or possible communicable disease outbreaks allowing for much better and effective public health responses.

Article 1, from NPR, discusses the use of Artificial Intelligence (AI) to help physicians analyze and diagnose patient images. This article is specifically focused on the use of AI to help physicians detect retinopathy in patients with diabetes and can have possible effects on public health informatics through the use of technology and application of computer science in the medical field.

https://www.npr.org/sections/health-shots/2019/04/14/711775543/how-can-we-be-sure-artificial-intelligence-is-safe-for-medical-use

Summary
The article describes a new software recently approved by the FDA for use in early-detection of diabetic retinopathy. The article explains how those diagnosed with diabetes are at risk for retinopathy, a condition that can cause permanent blindness if left untreated or undiagnosed. It mentions that many patients that have diabetes do not go in for annual vision checks therefore this condition goes undiagnosed. The recently approved software, named IDx-DR, is an “artificial intelligence” software that examines images of a patient’s retina in order to determine if the patient is showing early signs of retinopathy and if follow-up treatment is needed for that patient. The article also goes into detail about how the developers of the software had to ensure that their program was able to meet the standards and regulations set forth by the FDA. It also mentions that software approval through the FDA usually is very easy, in comparison to new drugs or medical devices, however this specific software was more of a challenge. The software had to ensure that it could be accurate across diverse populations and the FDA had set forth a goal that the software had to correctly indicate eye disease 85% of the time and correctly identify no serious eye damage at least 82.5% of the time. The article concludes with mentioning how the FDA is changing their methods to approve algorithm based software going to market and how these changes can help protect patients and ensure that software getting approval is effective and safe.

Impact Assessment
With artificial intelligence and imaging technology becoming more prevalent in the healthcare field, public health informatics of disease prevention and epidemiology is an area that may see more benefit than others. As the article mentioned, the use of the AI for detecting early signs of diabetic retinopathy through the analysis of captured images, allowed physicians to help refer patients for treatment much earlier and accurately than if a normal physician was examining the image. There are however potential issues and drawbacks that could occur with this push towards algorithms and computers making medical decisions. The biggest issue mentioned in the article was the large diversity in patient populations presents a challenge for those creating the software. Ensuring that all patients can be treated equally and diagnosed with the same accuracy is a huge challenge and requires a multitude of informatics data and developers to create a software that takes every detail into account. This type of technology can have a huge impact on public health informatics specifically in providing a huge benefit for public health representatives in the field who can bring these technologies to areas that may have never had access before. Field representatives can increase patient participation through the use of AI to diagnose diseases and abnormalities, even without patients ever having to leave their homes to receive a diagnosis. In addition to field representatives seeing a large benefit, CDC officers could also benefit from this type of technology through the gathering of large quantities of public health data to further analyze and find similarities between cases. This could allow for much more and consistent diagnosis for patients at-risk for the disease mentioned in the article as well as increase the understanding and knowledge of how the disease affects patient populations and provides information on clusters of patients.

Article 2, from Science News, discusses the collection and storage of patient genetic data and how third party companies that offer DNA sequencing and genealogy databases limit access from other entities including law enforcement and government affiliated groups. This can also have implications on public health informatics in creating vast databases of patient genetic information using new technologies and the use of this information to inform public health medical practices.

Genealogy companies could struggle to keep clients’ data from police

Summary
The article discusses the use of private and third party genetic databases from companies such as 23andMe and GEDmatch by police and law enforcement agencies to find and make arrests of potential suspects based upon DNA and genetic material collected and analyzed from crime scenes. The article goes into detail about how these companies are attempting to prevent these different police departments and law enforcement agencies from accessing these databases in order to protect patient privacy and information. The company that the article is focused on, GEDmatch, made a change in their access standards, preventing police from accessing user information unless the user selects to opt-in to allow police to search their information. This move had created some unintended side-effects in that those who were using the database as a research tool also found it much more difficult to access information and build their research databases. One of the biggest issues that was found with GEDmatch making the switch in access requirements is that those who had recently passed away were unable to change their settings and allow for police and others to search their data. A quote from the article likens this to “basically burning libraries” and that “data will never recovered.” The article closes on a discussion about the public reaction to the switch and while many were angered about police being able to search their data, the overall reaction was more positive in that many of them were in favor of allowing police searches through these databases.

Impact Assessment

From the viewpoint of a chief information officer concerned with information privacy, security and ethics, as a concern of public health informatics and the use of large databases of patient health information, ensuring that the data collected is protected from malicious access but available to those with a specific need. In regards to the situation that the article has described, making the data non-accessible to law enforcement agencies unless a user has opted-in creates a unique problem. In public health informatics, the idea that data sharing and access is considered a benefit and something that should be viewed in a positive and advantageous light however ensuring that protection of that data is also maintained while not infringing on access is a tough subject. This article highlights that exact scenario and from that viewpoint of ensuring data privacy and security while providing a database for research or public use can create difficulties for one or both sides. Chief information officers, informaticists, and IT professionals all must work together to create databases that are conducive to research use and allowing for adequate security measures to help keep public trust in these companies. CDC officers could also benefit from data like this in that they can use it to help understand unique population genetic information and even look at and determine inheritance patterns of specific genetic based diseases in those populations to determine possible clusters or patients that may be at higher risk and adjust preventive health practices for those patients.

Diary Entry #1: Describing the initial outbreak and brief overview of the issue.

Diary Entry #2: Describing the public health problem as well as bringing forth potential solutions and possible informatics tools that may useful to solving the problem.

Diary Entry #3: Discussion of the efficacy of the selected tools and methods and if those methods are contributing to containing and easing the outbreak or if they are not showing any real efficacy concerning the problem.

Diary Entry #4: Discussion of the final outcomes of the situation as well as ideas and possible informatics tools that should further be investigated as possible ways for rapid responses to future outbreaks.

The chronic health condition that I selected to create a survey on is obesity. I chose this chronic health condition to address with this survey because it is able to relate to more demographics and populations than just rural persons. I also came to this choice due to the observed increase in the rate of obesity in rural populations and that many of the drivers behind this include lesser access to healthier food options, lack of annual physician visits or a limited number of physicians in the area for rural populations to choose from. This tool should be created because most rural populations have chronic conditions that are not studied and if they are, they are usually lacking in data due to restrictions such as patients not having clinics or medical centers within a reasonable distance to participate in a survey or study. The purpose of this survey is to gather data on daily lifestyles of obese patients in rural populations and to analyze and extrapolate the reasons behind why these patients are obese. The data generated from this survey will be able to be applied to many more broad populations. The PHI tool that would work well with the data from this survey would be a surveillance tool that allows for easy data visualization and analysis showing population specific results and can be easily comparable across different populations. This tool can also help monitor and determine other at risk populations and trends that may lead to higher obesity rates in other populations. This data can be used to design and implement practices and interventions that will reduce and prevent an increase in obesity rates among various populations.

This is a link to the survey questions. Rural Obesity Survey

For the validity of the methods used in this survey, the use of multiple choice questions allows for answers to be more direct and less room for open-ended answers or answers that are unexpected given the question being asked. In addition to this, it allows for the internal validity of the survey to be much higher by reducing the chance for confounding variables to create poor results in the survey. The external validity of the survey is also very high in that it is easily applicable to other populations and can be generalized and applied to other scenarios allowing for easy collection and application of the collected data. The use of more broad questions that allow for all participants to select an accurate and meaningful answer help to improve the external validity of the survey.