The impact of artificial intelligence on the current and future practice of clinical cancer genomics

Artificial intelligence (AI) is one of the most significant fields of development in the current digital age. Rapid advancements have raised speculation as to its potential benefits in a wide range of fields, with healthcare often at the forefront. However, amidst this optimism, apprehension and opposition continue to strongly persist. Oft-cited concerns include the threat of unemployment, harm to the doctor–patient relationship and questions of safety and accuracy. In this article, we review both the current and future medical applications of AI within the sub-speciality of cancer genomics.

The full article can be downloaded below.  

Development of a real-time physician– patient communication data collection tool

This study highlights the importance of effective physician–patient communication and presents a unique data collection tool to assess and improve physician communication in real time. This tool can provide physicians with personalised feedback and relate specific communication behaviours to patient experience measures to provide high-quality care and improve the patient experience.

The full article can be downloaded below.  

Measuring Patient-Reported Shared Decision-Making to Promote Performance Transparency and Value-Based Payment: Assessment of collaboRATE’s Group-Level Reliability

Shared decision-making (SDM) between clinicians and patients is a key component of patient experience, but measurement efforts have been hampered by a lack of valid and reliable measures that are feasible for routine use. In this study, we aim to investigate collaboRATE’s reliability, calculate required sample sizes for reliable measurement, and compare Consumer Assessment of Healthcare Providers and Systems (CAHPS) patient experience survey items to collaboRATE. CollaboRATE’s provider group-level reliability reached acceptable reliability at 190 patient reports, while the CAHPS SDM measure demonstrated similar reliability at a sample size of 124. The CAHPS communication measure reached acceptable reliability with 55 patient reports. A strong correlation was observed between collaboRATE and CAHPS communication measures (r ¼ 0.83). As a reliable measure of SDM, collaboRATE may be useful for both building payment models that support shared clinical decision-making and encouraging data transparency with regard to provider group performance.

The full article can be downloaded below.

Are Wearables Decentralizing Medicine?

It’s no secret that increasing healthcare costs and an aging population are taxing the U.S. healthcare industry and exacerbating a skills gap within the medical industry. While automation and IoT are helping to alleviate the manufacturing skills gap, some companies are working on similar technologies to aid the medical industry. The following presents trends and products OEMs and doctors are hoping will lighten the workload of an aging population.

The full Machine Design article can be viewed at this link.  

NextGen explains why it is important to develop a strategy to capture, organize, and understand your practice’s data so these insights can be used to improve care and enhance revenue. Read the eBook Data Analytics in Ambulatory Care to help your practice thrive and grow. 
 

Slides and presentation from the 11.7.19 webinar

The vast majority of U.S. healthcare dollars and patient care efforts are currently spent on clinical factors and are not addressing the underlying socioeconomic and behavioral factors that greatly impact patient health. These forces, referred to as social determinants of health (SDOH), give providers and health plans meaningful insights into the health of their patient populations. SDOH data, which includes information on housing, income, crime, education, transportation, domestic circumstances, and food insecurity, allows stakeholders to proactively identify and treat those most at risk. SDOH improves both patient and population health by contributing to the complete picture of an individual, identifying populations that are most vulnerable, and facilitating connections with social services and programs that can improve their lives.

This webinar explores:

• SDOH data sources and use across organizations
• Center for Medicare & Medicaid Services (CMS) efforts regarding the use of SDOH
• The role of health information exchanges (HIEs) with SDOH data, including challenges and solutions

SPEAKERS
 

Leonides (Lizzy) Feliciano, Vice President, Marketing, LexisNexis Health Care
Lizzy brings more than 20 years of HIT marketing experience to LexisNexis Risk Solutions. In her role she is responsible for creating strategies to grow the LexisNexis brand, drive thought leadership and establish innovation-centric messaging frameworks for a broad portfolio of data insights solutions. She has experience working with data, technology, and analytics organizations that deliver solutions impacting patient outcomes, data quality and interoperability. Lizzy holds a BA in Organizational Communication with a minor in Public Relations from Rollins College, and a MBA with a double concentration in Business Management and Marketing from the Crummer Graduate School of Business located in Winter Park, FL.

Chris Hobson, MD, Chief Medical Officer, Orion Health
Dr. Chris Hobson has global experience in the development implementation and adoption of Health Information Exchange, population health solutions, disease management programs, and innovative value-based models of healthcare delivery. He has over twenty years’ experience in North America, Europe, Middle East and the Asia Pacific region always working in the broad population health space. Prior to joining Orion Health, he developed integrated care strategic projects for a major health system, over three years, in Auckland New Zealand and worked in primary care and internal medicine as a physician for more than ten years. He has broad and deep experience across all areas of Health Information Exchange from business and clinical strategy through product design and development; sales and marketing; implementation, project management and evaluation of health IT projects. Most recently he has been working closely with LexisNexis on ways of integrating SDOH into Health Information Exchange for provider and payor focused HIEs.

Jordan Luke, M.A.Ec., Director, Program Alignment and Partner Engagement Group, CMS OMH
Jordan Luke is the Director of the Program Alignment and Partner Engagement Group (PAPEG) at the CMS Office of Minority Health (CMS OMH). PAPEG is responsible for working across CMS programs, policies, models, and demonstrations to ensure that the needs of vulnerable populations are met. He leads the CMS Equity Plan for Improving Quality in Medicare and the Minority Research Grant Program. PAPEG also provides Health Equity Technical Assistance to organizations interested in embedding equity into their policies, programs, and initiatives. Jordan gained cross-cultural experience from living and working abroad for fifteen years in Chile, Mexico, Bolivia, Canada, and the Navajo Nation. Jordan completed his M.A. in Economics from Boston University and B.A. in Psychology from Lee University. His passion for equity was ignited as an undergraduate student, where he led a student group called Deaf Outreach and founded an LGBT group to support sexual and gender minority students. Jordan is a native Spanish speaker and knows intermediate American Sign Language (ASL).

Using Clinical Decision Support Tools To Facilitate Decision-Making In Precision Medicine

To fulfill its promise precision medicine requires accurate decision support tools, especially to streamline biomarker testing so that the appropriate targeted therapies are prescribed. Even in oncology, where precision medicine has advanced the farthest compared to other therapeutic categories, clinical decision tools are needed to sort through and analyze reams of clinical and molecular data for the purpose of optimizing treatment algorithms.

The full Forbes article can be viewed at this link. 

Public Concern About Monitoring Twitter Users and Their Conversations to Recruit for Clinical Trials: Survey Study

Social networks such as Twitter offer the clinical research community a novel opportunity for engaging potential study participants based on user activity data. However, the availability of public social media data has led to new ethical challenges about respecting user privacy and the appropriateness of monitoring social media for clinical trial recruitment. Researchers have voiced the need for involving users’ perspectives in the development of ethical norms and regulations.

This study examined the attitudes and level of concern among Twitter users and nonusers about using Twitter for monitoring social media users and their conversations to recruit potential clinical trial participants.

We used two online methods for recruiting study participants: the open survey was (1) advertised on Twitter between May 23 and June 8, 2017, and (2) deployed on TurkPrime, a crowdsourcing data acquisition platform, between May 23 and June 8, 2017. Eligible participants were adults, 18 years of age or older, who lived in the United States. People with and without Twitter accounts were included in the study.

While nearly half the respondents—on Twitter (94/603, 15.6%) and on TurkPrime (509/603, 84.4%)—indicated agreement that social media monitoring constitutes a form of eavesdropping that invades their privacy, over one-third disagreed and nearly 1 in 5 had no opinion. A chi-square test revealed a positive relationship between respondents’ general privacy concern and their average concern about Internet research (P<.005). We found associations between respondents’ Twitter literacy and their concerns about the ability for researchers to monitor their Twitter activity for clinical trial recruitment (P=.001) and whether they consider Twitter monitoring for clinical trial recruitment as eavesdropping (P<.001) and an invasion of privacy (P=.003). As Twitter literacy increased, so did people’s concerns about researchers monitoring Twitter activity. Our data support the previously suggested use of the nonexceptionalist methodology for assessing social media in research, insofar as social media-based recruitment does not need to be considered exceptional and, for most, it is considered preferable to traditional in-person interventions at physical clinics. The expressed attitudes were highly contextual, depending on factors such as the type of disease or health topic (eg, HIV/AIDS vs obesity vs smoking), the entity or person monitoring users on Twitter, and the monitored information.

The data and findings from this study contribute to the critical dialogue with the public about the use of social media in clinical research. The findings suggest that most users do not think that monitoring Twitter for clinical trial recruitment constitutes inappropriate surveillance or a violation of privacy. However, researchers should remain mindful that some participants might find social media monitoring problematic when connected with certain conditions or health topics. Further research should isolate factors that influence the level of concern among social media users across platforms and populations and inform the development of more clear and consistent guidelines.

The full article can be downloaded below.  

Reaching People With Disabilities in Underserved Areas Through Digital Interventions: Systematic Review

People with disabilities need rehabilitation interventions to improve their physical functioning, mental status, and quality of life. Many rehabilitation interventions can be delivered digitally via telehealth systems. For people with disabilities in underserved areas, digitally delivered rehabilitation interventions may be the only feasible service available for them.

The objective of this study was to evaluate the current status of digital intervention for people with disabilities in remote and underserved areas.

A systematic review was conducted on this topic. Keyword searches in multiple databases (PubMed, CINAHL, and Inspec) were performed to collect articles published in this field. The obtained articles were selected based on our selection criteria. Of the 198 identified articles, 16 duplicates were removed. After a review of the titles and abstracts of the remaining articles, 165 were determined to be irrelevant to this study and were therefore removed. The full texts of the remaining 17 articles were reviewed, and 6 of these articles were removed as being irrelevant to this study. The 11 articles remaining were discussed and summarized by 2 reviewers.

These 11 studies cover a few types of disabilities, such as developmental disabilities and mobility impairments as well as several types of disability-causing disorders such as stroke, multiple sclerosis, traumatic brain injury, and facio-scapulo-humeral muscular dystrophy. Most of these studies were small-scale case studies and relatively larger-scale cohort studies; the project evaluation methods were mainly pre-post comparison, questionnaires, and interviews. A few studies also performed objective assessment of functional improvement. The intervention technology was mainly videoconferencing. Moreover, 10 of these studies were for people with disabilities in rural areas and 1 was for people in urban communities.

A small number of small-scale studies have been conducted on digital interventions for people with disabilities in underserved areas. Although the results reported in these studies were mostly positive, they are not sufficient to prove the effectiveness of telehealth-based digital intervention in improving the situation among people with disabilities because of the small sample sizes and lack of randomized controlled trials.

The full article can be downloaded below.  

Long-term integrity protection of genomic data

Genomic data is crucial in the understanding of many diseases and for the guidance of medical treatments. Pharmacogenomics and cancer genomics are just two areas in precision medicine of rapidly growing utilization. At the same time, whole-genome sequencing costs are plummeting below $ 1000, meaning that a rapid growth in full-genome data storage requirements is foreseeable. While privacy protection of genomic data is receiving growing attention, integrity protection of this long-lived and highly sensitive data much less so. We consider a scenario inspired by future pharmacogenomics, in which a patient’s genome data is stored over a long time period while random parts of it are periodically accessed by authorized parties such as doctors and clinicians. A protection scheme is described that preserves integrity of the genomic data in that scenario over a time horizon of 100 years. During such a long time period, cryptographic schemes will potentially break and therefore our scheme allows to update the integrity protection. Furthermore, integrity of parts of the genomic data can be verified without compromising the privacy of the remaining data. Finally, a performance evaluation and cost projection shows that privacy-preserving long-term integrity protection of genomic data is resource demanding, but in reach of current and future hardware technology and has negligible costs of storage.

The full article can be downloaded below.