By Dr. David Lee Scher
Cardiologist & Digital Health Technology Consultant
Founder and Director at DLS HEALTHCARE CONSULTING, LLC, advising digital health technology companies and their partnering investors, companies, and healthcare providers. Scher is a trusted and award-winning thought leader in digital health. Leveraging his experiences as a cardiologist, clinical trial investigator, IRB Chair, Medicare Advisory Committee member, and pharmaceutical and medical device marketing advisory consultant, he advises clients on best product and business development practices from technology, clinical and patient advocacy perspectives. Dr. Scher was a pioneer adopter of remote patient monitoring and its data integration with electronic health records. He served on the mobile health HIMSS Advisory Council, was Chair of its Mobile Health Roadmap Task Force, and was a member of the mHealth Regulatory Coalition. He travels worldwide speaking to professional organizations and the general public on topics related to remote patient monitoring and mobile health technologies. Board Certified in Internal Medicine, Cardiovascular Diseases, and Clinical Cardiac Electrophysiology.
What is needed is the transformation of Big Data into relevant data.
Real-time curation and analysis of patient health data sets over periods of time across disparate electronic health record systems is critical. In addition, patient reported outcomes must be included. This type of data collection and analysis, if performed with incorporated practice guidelines can facilitate changes to prevent CVD.
There are numerous high quality cardiovascular disease databases in use today. The role of registries in cardiology include quality assurance, source of development of research hypotheses, and a resource for information about patients who fall outside of clinical trials from which evidence based medicine guidelines were developed. Developing registries with the above attributes (interoperability, customizable analytics, PROs) will give Big Data meaning and utility.
The promise of digital health is a vision of redefining points of care from the clinic or hospital to the patient’s home. The future importance of health technology at home was the focus of a March, 2016 report by the United States President’s Council of Advisors on Science and Technology. The report “Independence, Technology and Connection in Older Age” discusses technologies for social connectivity and emotional health. Though not speaking directly to CVD, the holistic approach proposed addresses the use of technology at home and in activities of daily living which will ultimately make an impact on prevention and management of CVD and its risk factors, particularly for older patients living with CVD.
In similar governmental support of technology use at home, Simon Stevens, the chief executive of NHS England in a public forum expressed his support for wearable technologies in healthcare. He discussed a technology and innovation tariff and said that worthy and selected technology will be reimbursed by the NHS. Wearable technologies combined with video encounters with healthcare professionals create non-traditional, convenient and more realistic points of care.
We have always known that the same treatment for any disease will not be successful for all patients. Variations in therapeutic response have been demonstrated according to the genome of the patient and sometimes the genome of the diseased tissue.
The use of genomics in CVD has lagged significantly behind compared to other diseases such as cancer. However, strides have been made in determining specific genetic predispositions to certain CVD and even response (or lack thereof) to certain therapies. Combining raw digital data sets from genomics, pathology, imaging, and common text and data is possible today. Layering analytics with some artificial intelligence for clinical decision support on top of this depth of data will take the prevention and treatment of CVD where it needs to be, that is, where oncology already is. Many evidence-based guidelines in medicine bolstered by ‘large’ clinical trials (of a few thousand patients) have already demonstrated significant vulnerabilities.
While there is aggregated evidence from multiple clinical trials that digital health interventions can improve CVD outcomes with a positive impact on risk factor reduction, there is much more work to do. There has long been evidence of gender and racial bias in the care of patients with CVD. Furthermore, the use of mobile technology to bridge gaps in healthcare is not a new concept. It is this author’s hope that simple, easy to use digital health technologies with easy to interpret data layered with artificial intelligence will have a significant impact in the prevention, management, and research into CVD.
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