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How AI-Driven Healthcare Data Management Impacts the Future of Healthcare

March 24, 2020

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. 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.

PGHD Patient Generated Health Data Acuma Health

Patient Generated Health Data (PGHD) Management to Improve Patient Care

February 18, 2020

Optimal Healthcare Data Management Can Achieve Benefits for Patients, Clinicians, and Payers

Patient generated health data (PGHD) is everywhere. There are many healthcare technology apps and devices that assist in patient data collection. Patients are eagerly collecting, tracking, and storing health data such as activity levels, and some are sharing that data with their healthcare providers. Some healthcare providers are utilizing patient data collection to aid in their decision-making to improve patient care. PGHD has the potential to change the healthcare landscape and healthcare stakeholders can leverage PGHD to improve outcomes and reduce costs.

In order to optimally leverage patient generated health data to produce useful insights and improve patient care however, proper patient data collection management is critical as data collected but not properly managed can become useless. Healthcare data is sensitive, personal, and protected by regulations such as the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule and, as such, healthcare data management can be an intricate process.

When looking to capture, store, and utilize PGHD, healthcare stakeholders need to consider factors such as data privacy and security, data accuracy, data governance, interoperability, and compliance with regulations. Because of this, the process requires careful thought and planning and development of proper PGHD frameworks to ensure optimal healthcare data management and utilization.

What is Healthcare Data Management and Why is it Important?

In a broad sense, healthcare data management is the process of storing, protecting, and analyzing data pulled from diverse sources. Healthcare stakeholders are swamped with patient data collection activities from myriad sources including electronic health records (EHR), electronic medical records (EMR), and of course, PGHD. All these data sources must be effectively managed if the power in the data is to be successfully harnessed and utilized.

“Managing the wealth of available healthcare data allows health systems to create holistic views of patients, personalize treatments, improve communication, and enhance health outcomes.”


Optimal healthcare data management,especially with the incorporation of patient generated health data, is important as it provides powerful insights into the patient life story beyond the walls of the medical establishment. This will enable the healthcare provider to better personalize the care offered to patients, improving patient outcomes and reducing costs associated with hospital admissions.

Healthcare data management through healthcare technology and data analytics is invaluable to population health management and precision medicine, driving research and improving health.

Leveraging healthcare technology for best-in-class healthcare data management is also critical if healthcare stakeholders are to remain compliant with regulations. In the era of value-based payments and meaningful use , healthcare data management must be a top priority for all healthcare stakeholders looking to remain relevant and functional in the healthcare space.

Benefits of Optimally Managing Patient Generated Health Data

There are many benefits to be gained from the optimal management of patient data collection and PGHD . There are benefits for a variety of healthcare stakeholders including patients, clinicians, payers, and researchers.

Advantages of Improved Patient Data Collection for Patients

Patients set to benefit from the optimal management of patient generated health data through ways such as:

  • More involvement in their personal healthcare as they take ownership of collecting and sharing PGHD with providers
  • Better engagement and communication with providers
  • Enhanced understanding of health conditions
  • Improved management of health conditions
  • Fewer hospitalizations and reduction in associated costs

Benefits of Optimized Healthcare Data Management for Clinicians

When PGHD is collected, shared with the provider and optimally managed through the use of healthcare technology, clinicians can realize many benefits. These include:

  • A more complete view of the patient’s quality of life over time and beyond the healthcare setting
  • Deeper insight into the patient’s adherence to treatment plans including medication adherence
  • Ability to note trends and intervene in a timely manner before acute episodes of illnesses
  • Better treatment outcomes and reduced hospitalizations
  • Increased patient engagement
  • Better patient retention

Benefits of Well-Managed Patient Data Collection and Management for Payers

Payers in the healthcare space can also benefit from optimal patient data collection and management.  Benefits to payers include:

  • Obtaining value for money by tying reimbursements to shared decision-making between providers and patients through incorporation of PGHD in care decisions
  • Offer incentives for the use of PGHD by providers

Patient Generated Health Data Management Benefits for Researchers

Patient generated health data when properly managed with healthcare technology, can provide a treasure trove of valuable information for researchers helping them to:

  • Conduct comparative effectiveness research to assess medical therapies to determine the best and most cost-effective therapeutic solutions for routine clinical use
  • Advance the field of personalized medicine
  • Develop predictive modelling and analytics
  • Make progress in the field of population health management
  • Monitor patients who are participating in clinical trials

Best Practices in Managing Healthcare Data with Healthcare Technology

Proper healthcare data management can be a daunting task. With the volumes of data that consistently flow into the healthcare system, added to the emerging field of PGHD, healthcare data management can overwhelm even the most seasoned healthcare professional if not done properly. However, the many benefits to be gained by different healthcare stakeholders from optimal healthcare data management, are enough to make the effort worthwhile.

Successfully managing healthcare data with healthcare technology to achieve the greatest benefits involves implementing measurement systems, as was executed in several healthcare case studies.  These measurement systems are designed on certain principles, such as: 

  • fitting the PGHD into the flow of care and using the data to make it easier for clinicians to do their jobs and for patients to engage in self-management and make informed decisions
  • ensuring the PGHD measurement system is co-designed with healthcare stakeholders engagement
  • engaging with patients and clinicians about how to use the PGHD
  • merging PGHD with data from other sources (clinician reports, medical records, claims) for optimal utility of the data
  • continuously improving the PGHD measurement system based on the experiences of users and new healthcare technology

Some healthcare stakeholders have begun optimizing patient generated health data, utilizing it to generate actionable insights and guide decision-making. A 2015 survey among healthcare executives found that 73% reported a positive return on investment (ROI) in healthcare technology  involving PGHD such as wearables that track fitness and vital signs.

“The use of such Digital Health apps in just five patient populations where they have proven reductions in acute care utilization (diabetes prevention, diabetes, asthma, cardiac rehabilitation and pulmonary rehabilitation) could save the U.S. healthcare system an estimated $7 billion per year.”


A congestive heart failure remote monitoring program initiated between Northern Arizona Healthcare and partners aimed to improve the management of patients with chronic diseases and/or high-risk conditions, by connecting patients with home-based medical devices and their care providers to ensure proper patient data collection and sharing of PGHD. An analysis of the program comparing data six months before and after implementation found an achievement of:

  • An average 44% reduction in readmission to the emergency room
  • An average 64% decrease in the number of days hospitalized
  • A reduction of $92,000 in per patient hospital charges

This program is a clear indication of the benefits to healthcare stakeholders that can be derived through successful healthcare data management.

The Dartmouth-Hitchcock Spine Center in Lebanon, NH, is a case study in the optimal use of PGHD to improve treatment outcomes. Patients complete a survey at home using a patient portal or in-office using a touchpad prior to their first visit at the center. The data are analyzed in real-time to create a summary report that is fed into the flow of care for use by the patient and the care provider. The provider also inserts some core clinical data elements into the clinical report and all information gets stored in a data warehouse for analysis and use in the care of the patient.

Overall results from a survey on the system found that over 80% of patients rated the system as“excellent to good” and one-third indicated that the system had led to positive changes in their visits. Approximately 50% of clinicians reported that the system saved time.

The Swedish Rheumatology Quality (SRQ) registry at the Karolinska University hospital, in Stockholm, Sweden, is another example where patient generated health data is incorporated into clinical care for optimal benefits.The SRQ registry is web-enabled and integrates real time, standardized data provided by patients, clinicians, and diagnostic tests. This data is used to improve the outcomes of care for individual patients, at the point of service as care is provided, and in the patient’s home to support self-management, as well as for quality improvement and research.

Efforts by patient care organizations to fit Digital Health tools into clinical practice has progressed, with 540 current clinical trials in the U.S. incorporating these tools and an estimated 20% of large health systems shifting from pilot Digital Health programs to more full-scale rollouts.

Researchers can benefit from well-executed healthcare data management. In one study of a framework for smartphone-enabled PGHD analysis, researchers at the Scripps Translational Science Institutelooked at blood pressure (BP) readings taken at variable times by persons in a study using a smartphone. They were able to detect an approximately 2 mmHg decrease in BP over a six-month trial, despite considerable intra- and inter-individual variation. This technique could prove useful for researchers in future study designs to analyze data as the field of digital medicine grows.

Of course, proper healthcare data management needs healthcare technology, and digital disease management solutions are available on the market to help with this. Ensure that selected solutions offer unified storage that is scalable and highly efficient to meet the requirements of multiple use cases.

Healthcare has become more patient-centric and policies such as value-based care will continue to push this movement forward. Patient generated health data has major potential for improving care, increasing patient engagement, lowering costs, and reducing wastes. However, there are many intricacies to properly leveraging PGHD to realize all these benefits. The process must include systems for proper healthcare data management which is inextricably linked to healthcare technology solutions.

Contact us at Acuma Health, where we assist healthcare stakeholders understand the digital health landscape including the benefits of PGHD, and provide you with solutions to solve your healthcare data management problems.

Patient Generated Health Data (PGHD) Frameworks, Regulations, and Requirements for Healthcare Stakeholders Appropriate PGHD Frameworks Need to Be Put in Place to Ensure Healthcare Stakeholders Comply with Regulatory Requirement

Patient Generated Health Data (PGHD) Frameworks, Regulations, and Requirements for Healthcare Stakeholders

January 22, 2020

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 InspyreTM; 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.”


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

Proactive Healthcare Stakeholders Lead the Way to a Brighter Future of Healthcare

December 16, 2019

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.

Patient Engagement Strategies for Healthcare Stakeholders

October 8, 2019

Ten Patient Engagement Strategies for Healthcare Stakeholders

Healthcare in the US has moved away from a fee-for-service model and is embracing value-based care largely driven by policies, regulations, and health care reform initiatives including the Affordable Care Act, and Meaningful Use. To maintain sustainability and remain competitive, healthcare stakeholders are developing and implementing new strategies to help them improve patient outcomes and the value and quality of the service they provide. Patient engagement, where providers and patients work together to improve health outcomes, is one such approach being embraced by healthcare stakeholders and has become integral to the success of healthcare organizations.

Here are 10 patient engagement strategies for healthcare stakeholders looking to improve the quality of care they offer:

1. Develop and implement patient engagement policies and procedures

Policies are necessary to demonstrate the commitment of the organization to patient engagement as well as to ensure that all staff and other stakeholders are aware that patient engagement is a focus of the organization. Specific procedures must be developed for all staff to follow to ensure that the policy is adhered to and the goal is achieved.

2. Develop a patient engagement framework

This framework should define the organization’s vision for patient engagement, stating clearly what the organization should look like when the patient engagement strategy is working. It will guide the organization in planning for, implementing and evaluating patient engagement activities across all departments and in all areas that can impact patient engagement. Some of these areas include; personal care and health decisions, organizational program or service design, delivery of service across the care continuum, and incorporating the patient’s family as well as other healthcare stakeholders into the process. Define the goals and expected outcomes for successful patient engagement at the individual level (patients and families), the healthcare team level, and the organizational level. The policies and procedures developed should form part of the patient engagement framework.

3. Create a culture of patient engagement

For any patient engagement strategy to be successful there must be buy-in from all stakeholders. Ensure that the organization creates a culture of patient engagement by involving staff, providers, and patients as much as possible in the creation of the patient engagement vision, policies and procedures, and framework. Creating a strong culture of patient engagement can support high quality health care.

4. Leveraging healthcare technology

Numerous healthcare technologies are available that can support patient engagement for healthcare organizations; implement the technologies that are right for your organization. Some of these technologies include:

  • Patient portals
  • Telephone calls/SMS/Email
  • Social media
  • Online appointment scheduling
  • Mobile health applications
  • Telehealth/telemedicine
  • Digital disease management solutions
  • Patient engagement solutions

Employing the right technology and services is key to successful patient engagement.

When adopting healthcare technologies, it is best to implement cloud-based services and software. You must also ensure that solutions are compliant with the different healthcare regulations such as the Health Insurance Portability and Accountability Act (HIPAA) and Meaningful Use mandates.

5. Educating patients and healthcare providers

Educating both patients and healthcare providers is fundamental to the success of any patient engagement strategy. Educational interventions for patients can focus on areas such as preventative health; safety improvement (including medication management); and managing their conditions, especially for those with chronic illnesses. It can take different formats such as holding educational sessions (including food demonstrations) in a hospital, clinic, or the community; pamphlets; brochures; YouTube videos; videos playing in waiting rooms; information on the organization’s website; and sending text messages with information such as medication safety reminders.

Healthcare providers need to be educated on the importance of the role of the patient in their own care and how to engage with patients. Educate providers to use lay language to communicate with patients instead of medical jargon, have open discussions on patient engagement, and include patient engagement in teaching sessions and workshops.

6. Touch points during patient visits

Look for opportunities to engage the patient when they visit the organization. There are many touch points that can be leveraged to engage the patient and improve their experience and satisfaction. Some touch points in a typical primary care setting and how they can be utilized for patient engagement include:

  • Waiting room – TV, print materials, posters
  • Reception area – receptionist (at check-in and check-out), computer kiosk, follow-up email and correspondence
  • Nurse’s examination room – nurse
  • Doctor’s examination room – doctor, posters, print materials

7. Incentives and rewards

Try to engage patients by offering incentives and rewards for active involvement in their healthcare. This can include providing discounts or entries into a raffle for meeting health outcomes set between the provider and the patient such as lower blood pressure or reduced Body Mass Index (BMI). The organization can partner with local gyms to offer a discount on membership to its patients.

8. Engage the patient as part of the healthcare team

Patients will feel more engaged and empowered when they are actively involved in the decision-making surrounding their healthcare. Interact with and enable patients to become involved through methods such as making online payments, viewing test results, scheduling appointments online, requesting prescription refills, and utilizing patient-generated health data.

Healthcare organizations can engage patients in planning committees, patient and public engagement groups, patient advisory committees or in prospective surveys to encourage change.

WHO Report

9. Empower caregivers

According to an American Association of Retired Persons (AARP) report of 2015, 43.5 million adults in the US had acted as unpaid caregiver to a child or adult in the previous 12 months. With so many persons functioning as caregivers, a good patient engagement strategy must incorporate the caregivers as well. Caregivers play an active role in the healthcare of patients, so empowered with the right education and provided with the proper tools and support, caregivers can have a significant positive impact on the success of any patient engagement strategy.

10. Measure progress and make changes

To ensure the organization’s patient engagement strategy is successful and sustained, it must be continuously measured, and changes made where necessary. Gather feedback from patients, their families, staff, and other healthcare stakeholders who have an impact on the strategy. Conduct surveys and assessments and use all results and feedback to revise and revamp the strategy. Remove what is not working and implement new viable suggestions.

If you are looking to develop or enhance the patient engagement strategies in your healthcare organization and seeking dedicated software tools for improving the care you deliver, Acuma Health’s Digital Disease Management Solution may be right for you.

Contact Acuma Health and request a consultation today or get started by downloading the Guide to Leveraging Healthcare Technology.