Welcome to the era of cognitive health care, a new partnership between human beings and technology with the goal of transforming health care on a global scale.
Cognitive systems that understand, reason, and learn are helping people expand their knowledge base, improve their productivity, and deepen their expertise. With cognitive computing, we can now see health data that were previously inaccessible, and we can impact the field of health care more than we ever thought possible. Humans generate an enormous amount of health-related data, from our personal fitness trackers and mobile apps to electronic medical records and genomic and clinical research. Unfortunately, much of this information is discarded or underutilized, and a majority of patients do not even have access to their own data.
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TOWARD PERSONALIZED CARE
Like any other industry, health care is being disrupted and transformed by an exponential growth in data. More healthcare data are generated today than at any other time in history. By 2020, the footprint of medical data will double every 73 days: an estimated 80% of this data will be unstructured. While medical professionals have access to an abundance of data, the volume is simply too significant for them to consume, analyze, and apply in ways that are meaningful for patients. In addition, the growth and pace of medical research, clinical trials, and treatment options are staggering. It is estimated that it would take a doctor 150 hours each week to read every piece of content published in his or her field of interest.
These growing pools of healthcare-related information, including electronic health records, clinical research, pathology reports, lab results, radiology images, voice recordings, and exogenous data, are difficult to share because they are fragmented. In addition, these information sources do not readily incorporate critical information about an individual’s non clinical conditions, which may have a strong bearing on health. As a result, patients and their healthcare providers are forced to make decisions based on a limited pool of evidence.
Based on machine learning, cognitive computing involves a category of analytics that are taught or learned. It is distinct from programmed or rules-based analytics and computing. Cognitive computing systems continually acquire knowledge from the data fed into them by mining these diverse data for pertinent streams of information. These systems themselves refine the way they look for patterns as well as the way they process data so they become capable of anticipating new problems and modeling possible solutions.
WHY COGNITIVE COMPUTING IN HEALTHCARE?
The promise of cognitive computing is driving interest and investment in the technology and its application across almost every field: for example, it has enabled autonomous vehicles, marketers are using it to better understand and target their audiences, and investors are employing it to improve their research and analysis.
- Cognitive computing enables researchers to uncover new insights in relationships among genes, proteins, pathways, phenotypes, and diseases.
- Helps identify the most critical attributes of a patient case and can provide easy-to-consume summaries for both patients and healthcare providers.
- Cognitive computing can assist in creating individualized treatment plans and thereby enhance the patient and physician experience.
- No longer having to spend countless hours reading, trying to find needles in haystacks of papers, researchers will be able to focus on the most promising leads, accelerating the pace of breakthrough discoveries.
- Can help attention-fatigued radiologists quickly find the anomalies of interest in images. There is less risk of missing something or of wasting time searching for an anomaly that does not exist.
- Patients will be able to send updates to their doctors through speech or text, anytime and from anywhere. These messages can be analyzed to find signs of progressing or deteriorating health, and a doctor will be notified if any patterns suggest intervention.
Cognitive healthcare decision assistance has the twin benefits of improving patient health and reducing the costs of missed diagnoses and suboptimal treatment plans. Ultimately, the application of cognitive computing in healthcare is about producing superior, best-practice, decision-relevant information for everyone in the health system. For healthcare practitioners, this means being able to provide more personalized care to patients with greater diagnostic certainty and best-practice treatment options based on the world’s latest medical evidence.