Author: Mia Madduri (page 1 of 2)

Handling the Opioid Crisis

The opioid crisis has been ongoing epidemic with no end in sight - but there are new technologies that will be of great help. These technologies include ways to manage pain without opiates, track certain chemicals in the body, and connect pharmacies and providers to provide more data on patients.

A new way to manage pain through technology introduces a drug-free wearable device that is inserted underneath the skin near the nerve closes to wear the pain occurs and an external stimulator worn on a pad on the outer skin surface that alleviates pain; the goal is to treat chronic pain. Neurostimulators currently used are surgically inserted in epidural space and send electrical pulse to the spine. Although it is very effective in dealing pain management, the larger size of the device and the cost makes it a difficult option to offer.

Another new device is a swallowable pill developed to better understand opioid adherence and improve dosages and use of opiates. The capsule consists of a an embedded wireless ingestible sensor that is triggered by chemicals in the stomach that emits a radio frequency that is sent to a readable device.

Superscripts, a network that connects providers and pharmacies, helps to digitize the prescribing process. When a prescription is requested, the patient’s history is sent by the software to the provider in order to weed out patients who are seeking to abuse painkillers. E-prescribing is not commonly used because many providers don’t know that it’s a legal form of prescribing medications.

A multi-institutional, PCORI-funded study aims to understand how cognitive behavioral therapy and motivational interview can reduce the use of opioids for patients with chronic pain. The study is a partnership between RTI International and three Mid-South Clinical Data Research Network (CDRN) institutions: Vanderbilt University Medical Center (VUMC), Duke University, and UNC Chapel Hill. The Mid-South CDRN seeks to support multi-site research using electronic health record data by reducing technical and regulatory barriers. It is a collaborative effort between VUMC, Meharry Medical College; Vanderbilt Healthcare Affiliated Network; Greenway Health; Health Sciences South Carolina (including Medical University of South Carolina); UNC; and Duke. The Mid-South CDRN is one of 13 CDRNs in PCORnet, the National Patient Centered Clinical Research Network.

Data Management

Now that data is becoming bigger, where do we store and maintain it? Cloud-computing, the practice of using remote servers hosted on the internet to process data rather than on a local server, is becoming a more widely used method.

The San Diego Supercomputer Center has created a healthcare hybrid cloud environment, which is an interconnected infrastructure that uses local and public cloud computing such as third-party vendors such as Amazon Web Services or Azure. The main difference is the physical control; local cloud computing is managed by on-site staff while public cloud computing is managed by the third-party vendors. The benefits to having a hybrid method of managing data is having a larger scalability and more automation while also being able to provide for specific needs of the consumer.

Many EHR systems are moving their services to cloud-computing infrastructures. Microsoft Azure is being used to store genomic data, which can take up to 200 gigabytes of space. This data has been anonymized for sharing purposes in public data repositories. In addiction to increased storage, there is also an increased need for transparency. Amazon Web Services has introduced blockchain technology targeted towards the healthcare industry. They plan on debuting new templates that will make it easier for users to optimize blockchain technology for projects and networks via open source frameworks.

Dr. Stanley Ahalt, CHiP associated faculty and also director of RENCI, is working on Water Science Software Institute project that aims to provide a cyberinfrastructure for managing and sharing data from the institute. He is also a co-Principle Investigator with DataNet Federation Consortium, an NSF project, that aims to provide a platform for sharing, using, and managing data across science fields.

The Growing Need for Security

With patient data becoming digitized, the need for Health IT security is growing. Several electronic health record systems have gone through breaches in security, compromising patient data. Some of these breaches are due to misconfigured servers, ransomware, or using unencrypted laptops when dealing with patient information.

Two acts our government has put into place to penalize health organizations for breaches in security are the Health Information and Technology for Economic and Clinical Health and Health Insurance Portability and Accountability Act. While data sharing across hospitals and providers is important, making sure that data is secure is higher priority.

Symantec has come out with new technology dealing with analytics that will help with security - in combination with Fortinet’s new product, health systems will be able to detect targeted attack and help manage network operations and security operations centers. Symantec has technology called Targeted Attack Analytic tech that allows automation from machine learning to detect targeted attacks.

Fortinet’s new information security technology deals with automate security response. These responses are based on predefined triggers - the need for this type of security is due to the decrease in the IT workforce. Implementation across security disciplines will garner better visibility and control over security threats.

With numerous technological advances in medical devices, there is also a call for security and regulation. The FDA has created a five point plan called the Medical Device Safety Action Plan: Protecting Patients, Promoting Public Health that focuses on establishing a robust safety net for medical devices, exploring regulatory options to implement post-market mitigations, encouraging creation of safer medical devices, advancing cybersecurity, and implementing total product life cycle approach towards medical device safety.

The FDA enforce that medical devices will have the capability to be updated and have security patches, and is contemplating having companies disclose cybersecurity issues to consumers.

Recent Trends in EHRs

New strides in optimizing Electronic Health Records have to lead to major tech companies offering their services in healthcare. The transition from paper charting to digital records will be made easier with these recent trends.  

Electronic Health Records are a system that maintains and gathers a patient’s comprehensive health report. Apple is working with a number of hospitals, UNC Hospitals included, to create an mobile app that will give patients more access to their health records pertaining to allergies, medications, conditions, immunizations, and lab results. Fast Healthcare Interoperability Resources specification will be used to integrate data from EHRs to mobile devices.

Epic, a healthcare software company that deals with EHR, has set up an initiative called One Virtual System Worldwide that will enable its customers to exchange health data with other vendors’ health records platforms. The initiative is broken into 3 parts; Come Together, Happy Together, and Working Together. In the first stage, Come Together, data is gathered; the second stage, Happy Together, data is shared to the consumer-level in easily understood formats; the third stage, Working Together, data-driven decisions are made by other organizations. Data sharing is important because this ensures that patients get the best treatment more efficiently.

Another trend in electronic health records is combining precision medicine, genomics, and EHR systems. By incorporating genomic functionality in EHR systems, clinicians are able to navigate directly in the EHR system in order to recommend therapies. The eMERGE network is helping to prepare precision medicine in EMRs. eMERGE is a network funded by the NHGRI (National Human Genome Research Institute) that combines DNA repositories with EMR systems so there is an integration of genomic research and implementing it in genomic medicine.

ClinGen is another NHGRI project that centralizes resources pertaining to clinical relevance of genes and variants that can be used in precision medicine. With these added functionalities in EMR/EHR systems, medical professionals are able to treat their patients more individualistically.


Careers in Health Informatics

Health Informatics is a field that is gaining momentum quickly. What does Health Informatics mean exactly and why should people be interested?

Health Informatics is the intersection between technology and healthcare: it seeks to improve patient health, health care, public health, and health or biomedical related research. Adjacent fields include digital health, mobile health, telemedicine, telehealth, and health IT. While Health Informatics spans a variety of topics, relevant courses comprise of machine learning, data/text mining, natural language processing, human-computing and user interfaces, data management, and statistical or genetics courses, among others.

Health Informatics is playing a huge role in helping to improve medicine by reducing costs and bettering processes in healthcare to increase efficiency. Health Informatics also aims to make health-related information more accessible to patients and providers.

What does getting a degree in Health Informatics have to offer? Due to the expanse of topics that encompasses Health Informatics, it offers a plethora of paths and careers such as data analytics and management, research and development, consulting, data mining, health policy and management, and much more. Research topics for health informatics combine interdisciplinary subjects; students could take a route focused on policy or the entrepreneurial aspects of healthcare, or some may have interest in the human behavioral side of healthcare. Although Health Informatics is still a burgeoning field, there are many options for students to create groundbreaking roles.

RTP area offers a lot of career opportunities with companies such as RTI, Optum, SAS, RENCI, IBM, Epic, NC AHEC, and Cerner. For more career opportunities, please access the CHiP website.

Bringing Medical Knowledge to Consumers

Developing a system for bringing medical knowledge to a consumer level is a current challenge in health informatics today. Existing systems such as expert systems are computerized decision support systems that implement artificial intelligence to help provide advice when treating patients.

Past systems have been shown to benefit people working in medicine; medical students, medical professionals, providers, etc. The group of people it has been shown to be most valuable are to the medical students; those with the least experience and previous clinical knowledge. These existing systems can then be adapted to consumers based on this study.

The reason why decision support systems are not being used as widely as they should be is because there is reluctance from medical professionals and low priority assigned to AI in healthcare systems. However, setbacks from using expert systems include consumers having a hard time understanding how to use the technology, and no research has been done to show how effective these systems on the consumer level.

These systems not only provide decision-based support, but can also be used to help triage patients. This isn’t meant to replace medical professionals, but to be of aid in the process. This also allows for patients to be aware of certain drug interactions or health risks, and help the patient’s decision on whether or not it is appropriate to see a doctor.  

HouseCall, for example, is a consumer health informatics system based off of an existing physician knowledge base, called Iliad. The call for patient information to be more easily accessible is being addressed with this application; studies have shown that patients like interacting with the application and enjoy participating in trying to solve their medical problems.

Dr. Lisa Vizer, CHiP core faculty members and Assistant Research Professor in the School of Medicine, is doing research related to adapting, designing, and developing technology so that  patients can monitor their own health. By bringing medical knowledge to a consumer level, technologies can quickly pick up when treatment is becoming ineffective. Dr. Vizer has worked on a research project that focused on the usability of a patient education and motivation tool using heuristic evaluation. She has developed applications that provide educational content about a patient’s condition in order to identify problems more efficiently.


Joining Patients, Providers, and Hospitals Globally

Telemedicine, a branch of medicine that aims to connect patients and providers in alternative ways rather than face-to-face communication, is a rapidly expanding field that seeks to improve the quality and accessibility of patient health. With the establishment of this kind of technology in medicine, health informatics will be taking a more consequential role.

The benefit of telemedicine is that underserved and isolated populations are able to access the care they need. Due to the digitization of health records, now information can be easily passed on and patients can receive faster care of the same quality. A current need is for systems to be configured for the accessibility of patient information internationally. The result from telemedicine connecting hospitals and their constituents is that global systems will become more efficient in dealing with world-wide epidemics as well as providing care to remote areas.

The data gathered from remote patient monitoring, a discipline of telemedicine where providers use heart rate sensors, pressure gauges, and other medical devices to gather information on patient health, is used to identify high-risk patients and then consequently provide a personalized treatment plan.

Because it’s hard to share and analyze healthcare information due to HIPAA regulations, an NIH sponsored project allows datasets to be anonymous so that they can be more accessible to researchers. The project strips any identifying information and leaves the treatment plan and how the patient responded. This allows researchers to provide health analysis and improve patient care.

Dr. Saif Khairat, Assistant Professor in the School of Nursing and CHiP core faculty member, is the Principle Investigator of Carolina Applied Informatics Research. The focus for this research team is on EHR usability, teleconsent, and telemedicine. More specifically in telemedicine, Dr. Khairat’s research focuses on improving clinical management of chronic diseases. Based on existing data, this study aims to find a systematic approach to classifying potential patients who would benefit from telemedicine, whether it be due to geographic distance, lack of distance, or costs.

Artificial Intelligence Advancing Medicine

Artificial intelligence is aiding healthcare providers in data acquisition, management, and analysis. Previous topics discussed in relation to AI have been personalized medicine, drug repurposing, and data visualization. Predictive analysis is another way to improve efficiency and diagnoses with machine learning.

Two companies, Prognos and Google, are delving into machine-learning with a focus on healthcare. Machine-learning is a branch of artificial intelligence that allows systems to learn data, identify patterns, and make decisions, for the most part, autonomously. Data can be learned through supervised or unsupervised learning, as well as other methods, where the algorithm is given a training set of labeled examples (supervised learning) or the algorithm explores the data to find an existing pattern to provide a data structure (unsupervised learning).

Prognos is a healthcare company that uses AI to predict diseases, resulting in earlier decisions in healthcare in collaboration with diagnostic, insurance, and life science companies.They have recently raised over $20 million toward their mission of predictive analytics. By combining healthcare and AI to predict disease earlier, they are able to identify patients in need of improved treatment decision-making, risk management, and quality improvement.  

DeepMind Health is another AI support system, brainchild of Google, that deals with predictive analytics. With deep machine-learning, DeepMind Health is able to understand images and provide an analysis that offers feedback and data segmentation for clinicians.

Dr. Carlton Moore, CHiP core faculty member and Associate Professor at UNC School of Medicine, has done research pertaining to artificial intelligence, more specifically natural language processing.

Natural language processing is the field of computer science that combines machine learning with computational linguistics. Dr. Moore’s research focuses on extraction of certain keywords in patient electronic health records. He is also interested in researching medical errors during transitions in patient care and assessing the adequacy of abnormal tests results that are followed up after ambulatory care.

Big Data in Healthcare


Two datasets - Project Baseline and Alzheimer’s Disease Neuroimaging Initiative are affecting the way we look at healthcare. Data analysis is a key part of how we make decisions and changes in medicine; through digitization of this data, researchers are able to reduce costs and improve outcomes.

Project Baseline, a study created through the collaboration between Duke School of Medicine, Stanford, and Google, aims to take raw health data and create a baseline of this data that would be used to visualize connections between distinct populations. These connections can be utilized to make more informed decisions and to have a better understanding of health and disease. Participants are asked to take health tests, give bodily samples, and answer questionnaires about their health and lifestyles. Sensors and wearable devices are also provided to the participants to record heart rate, activity levels, and sleep habits.

Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a highly curated data set that contains MRI and PET images, genetics, cognitive tests, CSF, and blood biomarkers to help predict the onset of Alzheimer’s Disease. The purpose of gathering this data is to research new treatments that will slow and stop the progression of Alzheimer’s Disease. Researchers participating in the study follow a uniform procedure and protocol to ensure that any inconsistencies are eliminated. The data is free and available to any authorized researchers who request the data.

Gathering and maintaining data is necessary in research, but data-sharing is also important; validating results and furthering research from prior results all stem from promoting data-sharing. The National Science Foundation has started a project to supply resources and bring attention to data management principles called Sustainable Digital Data Preservation and Access Network Partners (DataNet).

Similar to the Visible Human Project, having highly curated datasets means that research can be reproducible, results can be verified, and across disciplines, researchers can make more connections when datasets are well maintained and shared.  

The Importance of Studying Genomics

What is the importance of studying genomics? Genomic medicine is a discipline that involves using an individual’s complete set of DNA to improve their clinical care. An exciting trend that has developed from studying human genomics is personalized or precision medicine. This is the practice of using genomics, epigenetics, environmental exposure, and other data to form a genetic profile in order to make an informed diagnosis or treatment plan for a patient.

For example, BRCA1 has been identified to be a gene that produces a tumor-suppressing protein. Mutations in this gene are commonly associated with breast cancer, one of the most common cancers found in women worldwide. When this protein malfunctions, breast cells start to divide uncontrollably, causing a mass to develop. Mutations such as the ones associated with BRCA1 can be passed down genetically; however, depending on environmental and lifestyle factors, these genetic mutations may not ever be expressed.

Getting genetic testing done can reveal if someone has mutations on the BRCA1 gene, and preventative measures can be taken to address the risk of breast cancer. Tools have also been developed to visualize the human genome such as BioViews, which is used to create a physical, annotated sequence map and DNA sequence display. Data can be analyzed, visualized, and annotated, making it easier to make connections and organize different datasets.

CHiP faculty member and Associate Professor, Dr. Di Wu, has worked with genomic data to explore drug repurposing for different cancer subtypes. Based on the genomic profiling of the tumours, normal cells, and cells in the cancer cell lineage, drug sensitivity is being researched to determine the most effective treatment.

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