by Mark Heinemeyer
October 5, 2016

The United States health care economy has the deck stacked against it. An aging Medicare population means providers are faced with delivering care to more, older individuals with chronic diseases than ever before. Health care reform demands dictate that providers care for these individuals at lower cost while preserving or improving the quality of care. In the face of this dilemma, innovations in homecare are at the forefront of the discussion. The population the media has called the “grey tsunami”—the growing number of aging but tech-savvy baby boomers who want to receive care in their homes—is driving demand for home-centered care and remote monitoring technology.

Leveraging technology at home can potentially automate routine tasks, such as taking vital signs, that when communicated automatically to remote caregivers, offer providers insights into progress, as well as potential evolving risk factors for acute exacerbations of disease. Machine-learning technologies and predictive analytics have been utilized for decades across a number of industries. In recent years, the health care sector has begun adopting these technologies for a variety of applications, including chronic disease management, in-home and remote care delivery, staffing predictions and population health risk assessment.

Providing care at home facilitated by technology offers patients and providers the best of both worlds.

  • The use of in-home monitoring, communication and care team collaboration tools allow providers to stay on top of clinical issues while individuals enjoy the comforts of wellness at home and in their own communities.
  • Individuals have improved quality of life with care and wellness programs. Most seniors prefer to age at home; in-home technology allows them to do so.
  • Costs are reduced. Home-centered care, even when considering the cost of the technology required, is typically lower cost than other options, for all stakeholders.

However, not all home-centered technology suites are created equal. There has been a proliferation of wearable health devices and remote monitoring systems in recent years, and the preventative impact related to adverse events and readmissions among individuals with chronic diseases across the sum total of this technology has been underwhelming. Consumers, payers and providers must choose technology wisely if in-home care is to be beneficial and cost-effective. Optimizing the benefits of home-centered care technologies will require prescriptive utilization of collected data and empowered personalized engagement of participants.

Home health care technology, when combined with remote care, can play a dominant role in value-based care and patient engagement initiatives, especially in managing high-cost, high-risk chronic diseases. Care platforms should include in-home devices, communication tools for consumers, and extensive reporting. Reporting tools for doctors, caregivers, facilities and all stakeholders invested in an individual’s well-being should be available as part of a homecare program.

The benefits to accountable delivery initiatives supplemented by customized homecare programs for post-acute patients and individuals with chronic disease may include:
Reduce/prevent readmissions, or admissions. Emergency department visits and hospital inpatient stays are both the most costly way to deliver care, and the most uncomfortable and distressing for consumers. By delivering routine and preventative care at home, homecare programs seek to keep individuals healthy, and to identify early when signs and symptoms begin to appear that may signal the advent of a more-acute episode or disease exacerbation.

  • Improve workflow efficiency/productivity. Providers are subject to the same demographic trends, and a shortage of care professionals to treat the grey tsunami means efficiency and productivity are critical. In-home monitoring can help identify the patients who need attention and the most efficient way to deliver needed services, while keeping an eye on lower-intensity patients electronically, preventing wasted resources.
  • Improve participant satisfaction. Studies repeatedly show that patients who are treated at home, in the community, with access to friends and family, report greater satisfaction with their care and have better outcomes than those who end up in inpatient or long-term care facilities.
  • Gain competitive advantage. In the increasingly competitive health care marketplace, provider organizations need to differentiate themselves from competitors. Strong home-centered programs, delivered via a research-driven platform that uses machine-learning to customize its offering for patients, can serve as a differentiator for patients with a choice in health care providers.
  • Empower care teams and leadership. The aging populations of today are distinct from those of the past, with patients living longer and better with more chronic diseases than ever before. Chronic care platforms that use science- and data-driven decision support with visual guidance, and offer analytics such as risk scoring, tracking of trends, adherence scoring and recommendations based on data and patient histories, can help providers keep up.

Patient Adherence

With all of these potential benefits at play, the most important factor may be the ability to tailor care to the patient. Experience shows that tapping consumer behaviors and personalities is key to driving adherence and engagement. Customizing home-centered and remote care solutions to individual patients, and leveraging machine-learning and analytics to do so automatically, promises to hold the key to stronger patient engagement and greater efficiency.

Analytics provide valuable insights into the health of an individual based on collected data and contextual information. In the world of value-based medicine, data is critical for predicting the likelihood of adverse events so that caregivers have adequate time to enact proactive measures that enhance outcomes. Furthermore, the utilization of machine-learning allows providers to gain insight into the effectiveness of existing programs and protocols and identify the treatments and interaction styles that yield the best results for specific patients.

In order to offer customized services, digital health tools and apps need to interact with individuals to accurately identify potentially non-adherent patients. The tools should be able to tailor treatment and medication plans for those patients identified as high risk of being non-compliant, working with their preferences to improve engagement. Solutions should simulate empathy and utilize an individual’s unique personality profile to generate specific recommendations that will enable caregivers to optimize communication with each patient. Solutions should be aimed at seniors who desire and/or require assistance, but want to stay at home, with tools designed to serve as a constant companion and adjunct to homecare efforts.