Healthcare in today’s day and age has grown multifold, offering the best medical facilities to patients. As an organization providing healthcare solutions – be it a clinic, a hospital or a pharmacy, keeping all your services linked can get hard. Interoperability in healthcare is an ideal way out from the tangled mess of organising your patients’ data for them. This system can help the multiple departments of your healthcare organization or entirely different collaborating organizations function as one unit and be beneficial for your business in many ways. That said, given the current pandemic situation, interoperability can also help reduce physical contact between the patient and the various service providers. However, it does come with its own set of unique challenges which can definitely be tackled without much fuss. 

What are the benefits of interoperability?

For healthcare service providers

As said before, interoperability helps you unify your business. Once you have the system running, it can help save a lot of time on the back and forth that can happen between two departments; say, the pharmacy of your clinic and the billing system. Moreover, if you’re an organization aiming to provide your patients with multiple services such as operation or treatment aftercare, routine checkups, financial management and so on, running everything can get cumbersome. Interoperability can help you serve your patients better. Added to this is the benefit of efficiency. A unified system can give you more space to grow and connect with more organizations that complement your goals. Your patients can now get timely treatment enhanced by the data you collect via a patient’s mobile phone, wearable device, telehealth checkups, online prescriptions and medical bills that can be sent directly to a pharmacy from the clinic/ hospital and so much more. Lastly, interoperability can take your clinic to a global level by enhancing the quality of care you provide and in the process also save you millions.

For Patients 

As a patient, interoperability saves you the trouble of having to repeat your medical history to multiple practitioners. You can be assured that all your data – be it medications, allergies, conditions, tests or doctor’s who’ve treated you – will be stored in one encrypted corner for you to access when need be. A healthcare organization that provides you with this service can help save you a lot of time. Furthermore, you can also effortlessly connect with your pharmacy, insurance provider and the hospital billing to keep track of your expenses and bill payments. By remembering all your medical data for you, it’ll save you some bucks that would have otherwise been spent on discussing it with new doctors. 

For others

Interoperability can be a big help to pharmacies. They can now receive prescriptions from the healthcare providers and ensure that they’re always stocked for the same. Pharmacies that deliver medications to domiciles of patients can also use this option to upgrade their services. Apart from that, it can also be helpful to specialty pharmacies that undertake routine checkups, follow-up visits and offer other such medical services. Apart from that, interoperability can also help a clinic’s administrative staff segregate and store the information of the patient better which in turn helps avoid any errors on their part.

What about the challenges in interoperability?

Interoperability in simple terms is the ability to integrate multiple services into one entity to expedite data transfer. Despite its many advantages, not many clinics have been able to successfully inculcate it into their systems. In the US, less than 40 % of clinics have attempted to utilise it and have partially managed to share the data with other organizations. There are a handful of factors that hamper with the success of interoperability, the primary being the standards of use. Each organization has a different standard at which they operate. Bringing together such organizations  under a common system can get difficult and sharing data with them more so. The mode of operation can vary in the means of storing data, the format of retaining information and even the use of language in doing so. 

Secondly, when multiple organizations collaborate in one single system, the data gets too much to handle depending on the size of these organizations. If a pharmacy is exchanging data with more than one hospital for instance, there could be an overload of data in its system. This could decelerate the workflow of the pharmacy instead of expediting it. 

Lastly, corruption and lack of knowledge or resources also affect the success of interoperability. Some providers can input incorrect or faulty data for their personal gains which can affect the quality of services that the patient receives. Apart from that, there is also a possibility that providers can restrict information – in a process known as ‘information blocking’ – until the receiver pays a certain amount to be able to access it. Insurers can also sometimes be hesitant to provide a patient’s treatment and claim history to medical professionals. Apart from that a lot of providers are either rigid on sticking to the traditional systems or are unaware of the possibilities within interoperability. Moreover, the lack of financial resources for many organizations prevents them from investing in the same as well. Even if an organization does become a part of the system, its operators could lack the skills to exploit it in the best way possible. 

Is there a way to overcome these challenges?

• To start off, government funding towards standardizing interoperability in healthcare service providers could be helpful. 
• Secondly, usage of data integration tools and healthcare analytics solutions could help overcome the obstacle of data overload. These help with not just efficient allocation of resources but also cost-reduction for the healthcare service. 
• There also needs to be a standardization of the language used by the various integrated healthcare service providers. This can help avoid any misunderstanding and make interoperability more efficient by making it readable to both the sender and receiver as well as the computer. 
• Educating the operators on the availability of API (Application Programming Interface), AI (Artificial Intelligence) and healthcare analytics tools and on its utilization is crucial. They should also be made aware of the benefits of interoperability with regards to convenience and cost-cutting.
• Organizations standardizing interoperability need to also establish a privacy policy that has been agreed upon by all collaborators involved. Along with that, the interface for the interoperability software needs to be made user-friendly.

Machine Learning and AI Transform Healthcare Data Management so Healthcare Stakeholders Can Achieve Lower Costs and Better Patient Outcomes

Healthcare is a rapidly changing industry. Big data, artificial intelligence (AI), and machine learning – these terms have become mainstream in many industries and healthcare is no exception. AI applications are increasingly becoming a part of healthcare to the point where there have been rumblings about AI possibly taking over some healthcare jobs. But is this realistic? Should healthcare stakeholders all just embrace AI in healthcare?

What is Artificial Intelligence (AI)?

Artificial intelligence is a collective term used in reference to multiple technologies that aim to mimic human cognitive functions, making machines able to sense, understand, act, and learn. Some AI technologies that are important to healthcare stakeholders and the healthcare industry are:

• Machine learning – neural networks and deep learning: statistical techniques used to fit models to data and to ‘learn’ by training models with data.
• Natural language processing (NLP): making sense of human language with applications such as speech recognition, text analysis, and translation.
• Rule-based expert systems: based on “if-then” rules.
• Physical robots: actual robots such as surgical robots.
• Robotic process automation: computer programs used to perform structured digital tasks for administrative purposes.

AI in Healthcare – Past, Present, Future

Healthcare is a data rich industry which provides fertile ground for applications of AI in healthcare data management as well as other aspects of healthcare. In the past, AI technologies in healthcare were mainly algorithms or tools that complement a human. The rule-based expert systems of “if-then” rules were dominant in the 1980’s and for some time beyond. However, inefficiencies in such systems that result when the number of rules become too large, are causing them to be replaced by machine learning algorithms.

Today, AI in healthcare can truly augment human activity and is taking over tasks ranging from medical imaging to risk analysis to diagnosing health conditions. AI is being used to discover links between genetic codes, to power surgical robots, and to maximize hospital efficiency. As a result of this, growth of AI in healthcare is exploding and is estimated to reach $6.6 billion by 2021. An analysis of the market found that when combined, key clinical health AI applications can potentially create $150 billion in annual savings for the United States healthcare economy by 2026.

In the future, AI will play a critical role in precision medicine, which is the direction in which healthcare delivery is headed. AI is expected to improve areas such as diagnosis and providing treatment recommendations, imaging analysis, healthcare data management, patient communication, and capturing of clinical notes through speech and text recognition.

According to a PWC report, Why AI and Robotics will Define New Health, AI in past decades have focused on innovations in medical products (equipment, hardware, and software) that deliver historic and evidence-based care. The present decade has seen a rise in medical platforms focused on real-time, outcome-based care in the form of wearables, big data, healthcare data management, and health analytics. Healthcare stakeholders should be aware that it is believed that the next decade will see an increase in medical solutions involving robotics and augmented reality, which will deliver intelligent solutions for both evidence and outcome-based health and focus on collaborative, preventative care.

Uses of AI in Healthcare

“AI is being used to discover links between genetic codes, to power surgical robots, and to maximize hospital efficiency.”

One description of AI is that it “simplifies the lives of patients, doctors and hospital administrators by performing tasks that are typically done by humans, but in less time and at a fraction of the cost.” AI technologies have found a multitude of uses in healthcare such as:

• Efficiently and accurately diagnosing conditions and reducing errors
• Treatment recommendations
• Development of medicines
• Streamlining the patient experience
• Data mining and healthcare data management
• Robot-assisted surgery
• Administrative applications

With all these uses and more, AI in healthcare is here to stay and healthcare stakeholders who want to remain relevant and thrive in this space, need to make the necessary moves now to incorporate AI into their operations and optimize healthcare data management.

Impact of AI on Healthcare Data Management and Healthcare Stakeholders

The amount of data available in healthcare is staggering. Data sources include electronic medical records (EMRs), insurance claims, clinical trials, drug research and development, and patient generated health data. All these points of data have the potential to change the healthcare landscape if properly managed and leveraged accordingly. However, without proper healthcare data management, valuable data can become lost among the large volumes of data points available; this is where AI can help healthcare stakeholders.

“Healthcare could save up to $100 billion a year by utilizing big-data crunching algorithms backed by AI to inform decision-making and realize efficiencies in clinical trials and research”

It is estimated that the industry could save up to $100 billion a year by utilizing big-data crunching algorithms backed by AI to inform decision-making and realize efficiencies in clinical trials and research. There are companies that are leveraging the power of AI to assist healthcare stakeholders with healthcare data management and improving healthcare delivery. Tempus is one company that is using AI tools to collect and analyze the world’s largest library of clinical and molecular data to drive precision medicine. Its AI-driven data are being used in cancer research and treatment.

KenSci is another company that is using the power of AI and big data to improve healthcare. Their risk reduction platform aggregates data from existing sources such as EMRs, claims, and financial data to help uncover clinical, operational, and financial risks. It can predict who might get sick and the drivers behind healthcare costs; it can also provide solutions to these problems.

H2O.ai uses AI to analyze data throughout a healthcare system to mine, automate, and predict processes. It has been used to foresee ICU transfers, improve clinical workflows, and even pinpoint a patient’s risk of hospital-acquired infections.

AI-enabled applications are also impacting healthcare data management practices. Computer-assisted coding (CAC) is on the rise, utilizing NLP to read and interpret clinical documentation in patient health records and suggest applicable diagnosis and procedure codes. For CAC to be fully adopted and optimal efficiencies realized, the medical coding workflow will have to be re-engineered. As machine learning becomes more integral to reading images for diagnosis, the requirement for a physician to interpret an image may become less necessary. As such, medical coding and reporting guidelines and standards will need to be adjusted to account for AI applications.

Benefits of AI in Healthcare

AI has proven to be a boon to the healthcare industry. Some of the benefits from incorporating AI technologies in healthcare include:

• Faster, earlier, and more accurate diagnoses
• More efficient data mining and healthcare data management
• Lowered costs
• Improved patient outcomes
• Enhanced patient engagement
• Healthier behaviors and proactive lifestyle management with wearable technology
• Better understanding of the patient’s condition and improved management resulting from increased insight of the healthcare team into the day to day lives patients
• Improved clinical decision-making
• Reduced administrative burdens and improved efficiency in managing administrative tasks
• More efficient drug research and discovery process potentially cutting both the time to market for new drugs and their costs significantly

AI technologies are already proving to be a game-changer in healthcare and there is still a huge potential for them to do even more. Many companies including big names such as IBM and Google are investing heavily in AI for healthcare. We are on the cusp of many discoveries and breakthroughs as the potential of AI is fully realized in the healthcare industry.

Challenges/Pitfalls of AI in Healthcare

While the advancement of AI technologies in healthcare is exciting and offers numerous benefits, like everything else, it is not without challenges. Some healthcare stakeholders prefer to take a cautious approach, with some wondering how far is too far. Below are some of the challenges/pitfalls facing healthcare stakeholders and the evolution of AI in healthcare:

• Potential biases in results based on the data used to create algorithms and ‘train’ the AI technology.
• Transferability of algorithms ‘trained’ in one setting or population to another.
• Data ownership, confidentiality, and consent – who owns the data? Who is responsible for healthcare data management? How will patients’ data be kept confidential? How do healthcare stakeholders handle the need for consent in research?
• Ethical issues and professional responsibility – who is responsible when a patient is misdiagnosed?
• Legal risks and regulatory issues – at present, regulations are falling behind the explosion in AI development and use potentially creating a legal and regulatory nightmare for healthcare stakeholders.

Healthcare is experiencing an upsurge in the development and application of AI technologies. These technologies are very beneficial in that they can perform tasks that are usually done by humans in less time and at much lower costs, simplifying the lives of healthcare stakeholders including patients, doctors, and hospital administrators. Healthcare data management is one area that has benefited significantly from AI and has resulted in better patient outcomes and cost savings for healthcare stakeholders. However, there are some serious challenges to the use of AI in healthcare that need to be overcome. While AI might not take over healthcare jobs, these challenges need to be managed before we can all completely embrace the full potential of AI in healthcare.

To find out more about how wearables and patient generated health data are part of the bigger AI picture in healthcare, contact the healthcare technology experts at Acuma Health.

Appropriate PGHD Frameworks Need to Be Put in Place to Ensure Healthcare Stakeholders Comply with Regulatory Requirement

The healthcare landscape is changing. Patients are becoming much more interested and invested in their health and care decisions, and their voices and experiences are more important than ever before. Regulators are requiring and/or incentivising the inclusion of the patient’s voice in care delivery. Healthcare providers are increasingly being required to put the patient at the centre of the care they provide, and all healthcare stakeholders must find ways of incorporating the patient’s perspective into their care setting. Healthcare is moving towards what it should have always been about, the patients.

Healthcare Technology and the Rise in Patient Generated Health Data

Facilitated by an explosion in the use of healthcare technology, patients nowadays can collect and keep track of a variety of health indicators such as fitness levels, dietary factors, symptoms, and treatment history, which they can share with their healthcare providers. This patient generated health data has the potential to transform health systems, improving the quality of care and patient outcomes. Patient generated health data (PGHD) as defined by the Office of the National Coordinator for Health Information Technology (ONC) is “health-related data created, recorded, or gathered by or from patients (or family members or other caregivers) to help address a health concern.”

“There are over 318,000 mobile applications available to consumers and more than 340 consumer wearable devices on the market worldwide.”

–IQVIA Institute for Human Data Science Report

While PGHD has long been a part of healthcare in ways such as patients keeping track of their weight on paper or telling their providers about their symptoms, the significant increase being seen in the collection of PGHD is due largely to innovative digital health technologies such as wearables, which have become more popular and affordable. Consumer level devices such as the Fitbit and Smart Monitor’s Inspyre^TM; mobile health (mHealth) applications; and registered medical devices such as blood glucose monitors and interactive weight scales, are all giving the patient the power to easily collect and share their PGHD.

Benefits of Collecting and Sharing Patient Generated Health Data

When combined with existing clinical data, PGHD helps to provide a more fulsome picture of the health of the patient in the everyday environment outside of the care setting, which can be used to better inform care decisions. The collection and sharing of PGHD has benefits for the patient, the provider, and all healthcare stakeholders. These benefits include:

• Better disease management, especially for chronic conditions
• Improved patient outcomes through more timely diagnosis, proactive monitoring of changes in routine, and identification of conditions before they get worse
• Reduced costs due to fewer hospital admissions and readmissions as a result of earlier treatment interventions
• Decreased penalties from lower readmission rates
• Increased patient engagement
• Compliance with federal regulations requiring the incorporation of PGHD in electronic health records (EHRs)
• Improvements in the healthcare system through big data analytics

Leveraging PGHD can change the digital health game, improving analytics and reducing costs.

Challenges to the Collection and Use of Patient Generated Health Data

Despite the many significant benefits to be derived from collecting and using PGHD, it is not without challenges. The ONC in its whitepaper Conceptualizing a Data Infrastructure for theCapture, Use, and Sharing of Patient-GeneratedHealth Data in Care Delivery and Researchthrough 2024, shares some challenges that may be faced by patients, providers, and healthcare systems:

• Patients may not understand the advantages to be had in capturing and sharing their PGHD with providers and researchers
• Patients have different levels of health and technology literacy
• Data privacy and security concerns
• Lack of technical infrastructure, workforce capacity, and training in the healthcare system to adequately manage the intake and analysis of the large volumes of PGHD
• Confirming the validity and accuracy of the PGHD generated by varying devices

Notwithstanding these challenges, the potential and opportunities presented by the proper collection, handling, and use of PGHD in improving care and reducing costs, necessitate the development and implementation of proper frameworks to ensure that PGHD are utilized properly and healthcare stakeholders comply with requisite regulations while incorporating PGHD in their operations.

Proper Frameworks are Critical for Collecting, Storing, and Utilizing Patient Generated Health Data

PGHD are everywhere in the healthcare space. Numerous devices and mHealth applications abound that allow for collecting, storing, and sharing PGHD. Almost all patients are collecting PGHD in some form resulting in large volumes of data. Proper healthcare data management now becomes critical as without this, things get chaotic and the data can become useless. Additionally, data privacy and security issues can lead to non-compliance with regulations and fines. Some pertinent questions to be asked include when seeking to capture and utilize PGHD include:

• How do we properly collect all this data?
• How do we ensure the accuracy of the data being collected?
• How can we separate data that are useful from those that are not?
• How can we turn the raw data into useful information that can guide care decisions?
• Where will all this data be stored? Do we have the capability to store large amounts of data?
• What privacy and security measures do we need to put in place?
• Can PGHD be incorporated into our EHRs?
• How do we ensure that we properly handle and utilize PGHD such that we remain in compliance with relevant regulations?

When developing frameworks for the capture, sharing, and use of PGHD, it is critical to ascertain what federal, state, or organizational laws and regulations are relevant to the process to avoid non-compliance

All these questions can be answered with a proper framework in place. Stemming from two pilot demonstrations to test some concepts on the use of PGHD in real-life situations, the ONC has prepared a practical guide offering best practices and questions to consider when developing a policy framework for capturing, using, and sharing PGHD in clinical and research settings. The guide suggests that healthcare stakeholders should consider the following four areas:

1. Strategic planning: this includes determining the priorities and objectives of the organization, assessing the business case, and securing executive sponsorship and enlisting support at all levels
2. Defining requirements: identifying patient-facing technologies is covered in this section
3. Implementation: this incorporates training staff, recruiting and enrolling patients, and reviewing and acting on the PGHD collected
4. Monitoring and adapting: understanding and adhering to relevant privacy and security laws and regulations is one area should be looked at in this section

Following these steps will help to ensure that a proper structure is in place for leveraging PGHD while remaining compliant with regulations.

Regulations and Requirements on PGHD for Healthcare Stakeholders

One of the main concerns with the capture, sharing, anduse of PGHD, and which has the potential to cause violations to regulations, is privacy and security of the data. The Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule, while not necessarily specific to PGHD, aims to “assure that individuals’ health information is properly protected while allowing the flow of health information needed to provide and promote high quality health care and to protect the public’s health and well being.” This would mean that once a patient shares their PGHD with a healthcare provider or entity covered by HIPAA, it becomes protected under HIPAA and the healthcare organization becomes responsible for protecting the patient’s information. Any violations of HIPAA can lead to costly fines.

The Centers for Medicare and Medicaid Services (CMS), through the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA), requires that healthcare providers integrate PGHD into EHRs using Certified Electronic Health Record Technology (CEHRT).

“For 2020, eligible hospitals, critical access hospitals, and dual-eligible hospitals will have to report to CMS on health information exchange and provider to patient exchange, among other objectives.”

–CMS

The Food and Drug Administration (FDA) regulates certain devices and mobile applications and in September 2019, issued a Policy for Device Software Functionsand Mobile Medical Applications to clarify what is regulated. Healthcare stakeholders need to be aware of such policies to ensure they do not inadvertently violate FDA regulations.

There are also regulations that incentivize the use of PGHD and healthcare stakeholders can benefit from leveraging PGHD in their operations. The CMS operates the Promoting Interoperability Program (Meaningful Use) (previously the EHR Incentive Program) which pays eligible professionals, eligible hospitals, and critical access hospitals (CAHs) for meeting a set of standards for the use of CEHRT as part of their practices. Included in this are incentives for incorporating PGHD or data from a non-clinical setting into healthcare operations.

PGHD, spurred by rapidly evolving healthcare technology, is transforming the healthcare sector. There are many benefits to be realized from healthcare stakeholders working with patients to leverage this data, making it work for the patient, theprovider, and the health system. However, there are also challenges, especially regarding data accuracy, security, and privacy.  The large volumes of PGHD being collected by the myriad of devices and mHealth apps available, combined with the need to protect the privacy and security of the patient’s data, make it critical to develop a proper framework for any system being implemented to collect, share, and use PGHD. When developing such a framework, be sure to carry out a check of any regulations or requirement that may impact the collection, sharing, and use of PGHD to ensure compliance.

If you are seeking to incorporate healthcare technology into your organization or need help with leveraging PGHD, contact Acuma Health and we will work with you to find solutions that best suit you needs.

Internet of Medical Things (IoMT) Offers Significant Opportunities for Forward-Thinking Healthcare Stakeholders

Most of us are familiar with the term Internet of Things (IoT) which refers to all web-enabled devices – smart cars, smart thermostats, home security systems, fitness watches, internet-enabled kitchen appliances – all devices that connect to each other and to the internet. However, what many of us are less familiar with is the Internet of Medical Things (IoMT), a term used to describe internet-connected devices that can generate, collect, analyze, and transmit medical data, creating a connected infrastructure of health systems and services. Smart devices such as wearables, medical/vitals monitors, MRI scanners, mHealth applications, smart hospital beds, and medication dispensers, are all a part of the IoMT.

“The Internet of Medical Things (IoMT) is an amalgamation of medical devices and applications that can connect to health care information technology systems using networking technologies.”

–Alliance of Advanced Biomedical Engineering

The IoMTmarket is estimated to grow to $158.1 billion in 2022, and the number of IoMT devices are expected to top 20 to 30 billion by 2020. There are applications for IoMT in on-body consumer health wearables and clinical-grade wearables; in-home uses such as remote patient monitoring devices; community uses including mobility services that allow passenger vehicles to track health parameters during transit; in-clinic uses such as digital stethoscopes; and in-hospital uses such as wearable defibrillators.

Frost & Sullivan in their take on the IoMT reshaping proactive and coordinated care delivery, noted that there are some disruptive innovations that are possible with the IoMT:

• Medical-grade wearables and smart implants that communicate patient parameters
• Virtual assistants at home to help patients and seniors with their self-care, mHealth applications, and smart diagnostic medical devices that support telehealth services
• Smart cars that can track vitals of passengers during transit
• Exigency support by drones for emergency response
• Smart, digitized clinical devices like digital stethoscopes for clinicians in primary care
• Smart hospital rooms that allow patients to communicate with care teams virtually, from their bedside
• Kiosks at community centers to improve access to informational services, pharmaceutical products, and telemedicine services.

IoMT is continuing to change the face of healthcare and provides the opportunity for healthcare stakeholders to become more proactive instead of reactive. While patients can use IoMT to monitor, inform and notify them of their health status and notify caregivers of any issues, proactive healthcare stakeholders can leverage IoMT by utilizing the data generated to identify issues before they become critical or to allow for earlier invention. Patient-generated health data can be incorporated into care planning and used to provide more personalized care delivery to the patient. Proactive healthcare stakeholders can utilize predictive care solutions and artificial intelligence (AI) software to intelligently sort through the wealth of data from IoMT devices to deliver relevant data to healthcare providers, as well as to stratify and even predict risks and intervene long before a problem develops.

Major benefits can be derived by both patients and healthcare stakeholders from leveraging the technologies available through the IoMT. Healthcare organizations can achieve better patient outcomes, lower healthcare costs, improve efficiency, and activate new ways of engaging and empowering patients. Traditional healthcare is changing, and proactive healthcare stakeholders need to be on the right side of this change, leveraging the capabilities of the IoMT to improve their care delivery and operational efficiencies.

Contact Acuma Health for ideas on how to derive the benefits offered by the IoMT.

instagram takipçi satın al