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Improving Doctor-patient Communication with AI

A computer analysis of hundreds of thousands of secure email messages between doctors and patients found that most doctors use language that is too complex for their patients to understand. The study also uncovered strategies some doctors use to overcome communication barriers.

Experts on health literacy, as well as leading health care organisations, have advised that doctors always use simple language when explaining things to their patients, to avoid confusing those with the least health literacy. But the study found that most doctors did not do this. Only about 40% of patients with low health literacy had doctors who used simple language with them.

Effective electronic communication is becoming increasingly important, as doctors and patients rely more on secure messaging, an innovation that has rapidly expanded during the COVID-19 pandemic. The study found that the doctors who performed best in surveys of how well patients understood their care tended to tailor their electronic messages to their patients’ level, wherever it was on the spectrum of health literacy.

The study employed computer algorithms and machine learning to measure the linguistic complexity of the doctors’ messages and the health literacy of their patients. Using data from over 250,000 secure messages exchanged between diabetes patients and their doctors through Kaiser Permanente’s secure email portal, the study sets a new bar for the scale of research on doctor-patient communication, which is usually done with much smaller data sets and often does not use objective metrics.

The algorithms evaluated whether patients were cared for by doctors whose language matched theirs. Then, the research team analysed the individual doctors’ overall patterns, to see if they tended to tailor their communications to their patients’ different levels of health literacy.

Our computer algorithms extracted dozens of linguistic features beyond the literal meaning of words, looking at how words were arranged, their psychological and linguistic characteristics, what part of speech they were, how frequently they were used and their emotional saliency.

– Nicholas Duran, Cognitive Scientist and Associate Professor, School of Social and Behavioral Sciences, Arizona State University

Patients’ assessments of how well they understood their doctors most likely reflected how they felt about their doctor’s verbal and written communications. But the ratings nevertheless strongly correlated with the doctor’s written communication style.

Unlike a clinic encounter, where a doctor can use visual cues or verbal feedback from each patient to verify understanding, in an email exchange, a doctor can never be sure that their patient understood the written message. The findings suggest that patients benefit when doctors tailor their email messages to match the complexity of language the patient uses.

As reported by OpenGov Asia, another study shows that machine learning techniques can offer powerful new tools for advancing personalised medicine, care that optimises outcomes for individual patients based on unique aspects of their biology and disease features.

The research with machine learning, a branch of Artificial Intelligence (AI) in which computer systems use algorithms and statistical models to look for trends in data, tackles long-unsolvable problems in biological systems at the cellular level.

Those systems tend to have high complexity—first, because of the vast number of individual cells and second, because of the highly nonlinear way in which cells can behave. Nonlinear systems present a challenge for upscaling methods, which is the primary means by which researchers can accurately model biological systems at the larger scales that are often the most relevant.

The promises of individualised medicine are rapidly becoming a reality. The combination of multiple disciplines—such as molecular biology, applied mathematics and continuum mechanics—are being combined in new ways to make this possible. One of the key components of this will certainly be the continuing advances in machine learning methods.

PARTNER

Qlik’s vision is a data-literate world, where everyone can use data and analytics to improve decision-making and solve their most challenging problems. A private company, Qlik offers real-time data integration and analytics solutions, powered by Qlik Cloud, to close the gaps between data, insights and action. By transforming data into Active Intelligence, businesses can drive better decisions, improve revenue and profitability, and optimize customer relationships. Qlik serves more than 38,000 active customers in over 100 countries.

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As a Titanium Black Partner of Dell Technologies, CTC Global Singapore boasts unparalleled access to resources.

Established in 1972, we bring 52 years of experience to the table, solidifying our position as a leading IT solutions provider in Singapore. With over 300 qualified IT professionals, we are dedicated to delivering integrated solutions that empower your organization in key areas such as Automation & AI, Cyber Security, App Modernization & Data Analytics, Enterprise Cloud Infrastructure, Workplace Modernization and Professional Services.

Renowned for our consulting expertise and delivering expert IT solutions, CTC Global Singapore has become the preferred IT outsourcing partner for businesses across Singapore.

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Planview has one mission: to build the future of connected work. Our solutions enable organizations to connect the business from ideas to impact, empowering companies to accelerate the achievement of what matters most. Planview’s full spectrum of Portfolio Management and Work Management solutions creates an organizational focus on the strategic outcomes that matter and empowers teams to deliver their best work, no matter how they work. The comprehensive Planview platform and enterprise success model enables customers to deliver innovative, competitive products, services, and customer experiences. Headquartered in Austin, Texas, with locations around the world, Planview has more than 1,300 employees supporting 4,500 customers and 2.6 million users worldwide. For more information, visit www.planview.com.

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SIRIM is a premier industrial research and technology organisation in Malaysia, wholly-owned by the Minister​ of Finance Incorporated. With over forty years of experience and expertise, SIRIM is mandated as the machinery for research and technology development, and the national champion of quality. SIRIM has always played a major role in the development of the country’s private sector. By tapping into our expertise and knowledge base, we focus on developing new technologies and improvements in the manufacturing, technology and services sectors. We nurture Small Medium Enterprises (SME) growth with solutions for technology penetration and upgrading, making it an ideal technology partner for SMEs.

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HashiCorp provides infrastructure automation software for multi-cloud environments, enabling enterprises to unlock a common cloud operating model to provision, secure, connect, and run any application on any infrastructure. HashiCorp tools allow organizations to deliver applications faster by helping enterprises transition from manual processes and ITIL practices to self-service automation and DevOps practices. 

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IBM is a leading global hybrid cloud and AI, and business services provider. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Nearly 3,000 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and business services deliver open and flexible options to our clients. All of this is backed by IBM’s legendary commitment to trust, transparency, responsibility, inclusivity and service.