Mayo Clinic's Pulse Check: Health Opinions & Behaviors in America

One of the most pressing health issues of our time, the opioid epidemic is devastating communities — and driving health care professionals to examine and evaluate prescribing practices. The fifth Mayo Clinic National Health Checkup focuses on awareness and behaviors related to opioid use in pain management.

The full pdf can be downloaded below.  

Social Determinants of Health (SDOH) are the conditions in which people are born, work, live, and age. The healthcare industry increasingly recognizes that improvements in health and health equity will only be possible after addressing SDOH, including socioeconomic status, education, neighborhood and physical environment, social support networks, and access to healthcare. Currently, payers use ZIP code characteristics to determine investments at the neighborhood level. The approach does not consider customized resource allocation at the individual level unless the member/patient has had multiple, high-cost interactions with the healthcare system (i.e., “hotspotting”).

UnitedHealthcare (UHC) is piloting a more targeted approach to addressing SDOH and will be tracking the results of the pilot work closely.

The steps of the pilot are:

1. Identify “at-risk” members/patients using specific ICD-10 codes, CPT codes, and LOINC codes on claims
2. Have care managers perform direct outreach to conduct assessments to evaluate specific needs
3. Generate/update care plans that treats the entire patient, including social, medical, and behavioral services to address member-specific needs
4. Connect members/patients to other payers, such as Medicare and Medicaid, if appropriate
5. Enroll members/patients into relevant UHC programs, such as literacy programs or programs around self-care
6. Arrange follow up
7. Go back to step 3

These Considerations for Success were discussed as part of eHealth Initiative’s September 2018 Value & Reimbursement Workgroup meeting as presented by Anupam Goel, Chief Health Information Officer, Clinical Services, UnitedHealthcare.

Artificial intelligence (AI), and its sub-disciplines, machine learning (ML) and deep learning (DL), are beginning to play a significant role in healthcare. As AI moves out of research labs and into real-world applications, it is becoming a disruptive force in transforming patient care. These technologies, coupled with affordable data storage and computational power, enable healthcare organizations to analyze an immense volume and variety of data. Intelligence allows for progressively deeper insights which lead to proactive care, reduced future risk, and streamlined work processes. AI technologies are providing innovative solutions for precision medicine, organizational efficiency, and improved health outcomes.

Due to the significant volume of data created during patient care, the healthcare industry is well positioned to take advantage of the advancement and commoditization of computer algorithms and hardware. AI enables more automated decision-making on important data sets emerging from the Internet of Things (IoT), electronic health records (EHRs), and patient-generated health data. AI also gives machines the ability to mimic human behavior, an increasingly valuable feature in an industry that is experiencing high costs, high rates of physician burnout, and an increased focus on the patient experience.

On September 6, 2018, eHealth Initiative Foundation and Booz Allen Hamilton hosted a multi-stakeholder roundtable meeting to discuss expert opinions on the challenges and opportunities for AI and ML in healthcare. The meeting convened senior executives from provider, government, technology, pharmaceutical, clinical research, and professional organizations, representing radiology, pathology, cardiology, and other groups. This brief addresses the state of the field and includes examples of how AI and ML are being used within the industry; the challenges and barriers to the adoption of AI; current federal government initiatives; and where AI and ML may be headed in healthcare’s future.

Presentation slides and recording from 10.25.18 webinar.

As the healthcare industry moves into a more value-based market, consumer engagement is becoming an important factor. Patients who are more active in their own care, health, and well-being have lower healthcare costs and better health outcomes. In holistic, population focused-models, understanding and anticipating the needs of consumers is critical for patient engagement.

Combining a customer relationship management (CRM) system with a big data platform enhances consumer engagement and provides a clear picture about what affects patient care and health. These systems go beyond marketing and sales to track engagement, demographics, clinical status, behavior patterns, and preferences.

This webinar highlights the benefits of building a clinically-informed CRM solution. Speakers will share best practices on leveraging CRM technology to:

• Increase engagement and loyalty with enhanced customer experiences
• Close gaps in care and improve clinical and financial outcomes, with automated and proactive outreach
• Construct creative business efficiencies using closed-loop, integrated system

The Digital Scribe

Current generation electronic health records suffer a number of problems that make them inefficient and associated with poor clinical satisfaction. Digital scribes or intelligent documentation support systems, take advantage of advances in speech recognition, natural language processing and artificial intelligence, to automate the clinical documentation task currently conducted by humans. Whilst in their infancy, digital scribes are likely to evolve through three broad stages. Human led systems task clinicians with creating documentation, but provide tools to make the task simpler and more effective, for example with dictation support, semantic checking and templates. Mixed-initiative systems are delegated part of the documentation task, converting the conversations in a clinical encounter into summaries suitable for the electronic record. Computer-led systems are delegated full control of documentation and only request human interaction when exceptions are encountered. Intelligent clinical environments permit such augmented clinical encounters to occur in a fully digitised space where the environment becomes the computer. Data from clinical instruments can be automatically transmitted, interpreted using AI and entered directly into the record. Digital scribes raise many issues for clinical practice, including new patient safety risks. Automation bias may see clinicians automatically accept scribe documents without checking. The electronic record also shifts from a human created summary of events to potentially a full audio, video and sensor record of the clinical encounter. Digital scribes promisingly offer a gateway into the clinical workflow for more advanced support for diagnostic, prognostic and therapeutic tasks.

The full article can be downloaded below.  

Developmental roadmap for antimicrobial susceptibility testing systems

Antimicrobial susceptibility testing (AST) technologies help to accelerate the initiation of targeted antimicrobial therapy for patients with infections and could potentially extend the lifespan of current narrow-spectrum antimicrobials. Although conceptually new and rapid AST technologies have been described, including new phenotyping methods, digital imaging and genomic approaches, there is no single major, or broadly accepted, technological breakthrough that leads the field of rapid AST platform development. This might be owing to several barriers that prevent the timely development and implementation of novel and rapid AST platforms in health-care settings. In this Consensus Statement, we explore such barriers, which include the utility of new methods, the complex process of validating new technology against reference methods beyond the proof-of-concept phase, the legal and regulatory landscapes, costs, the uptake of new tools, reagent stability, optimization of target product profiles, difficulties conducting clinical trials and issues relating to quality and quality control, and present possible solutions.

The full article can be downloaded below.  

Looking to the future of patient-centered cancer research and treatment

Over the past 40 years, cancer research has seen revolutionary discoveries — about genes, targeted drugs, and immune therapies — that have already had dramatic effects for some patients.

But to speed progress toward better therapies, we need another kind of revolution: We need to enable cancer patients to become active partners in research.

The full article from Reed Jobs and Eric S. Lander can be found at this link.  

The development of a clinical policy ethics assessment tool

Clinical policies control several aspects of clinical practice, including individual treatment and care, resource management and healthcare professionals’ etiquette. This article presents Clinical Policy Ethics Assessment Tool, an ethical assessment tool for clinical policies that could be used not only by clinical ethics committees but also by policy committees or other relevant groups.

The aim of this study was to find or create a tool to identify ethical issues and/or confirm ethical validity in nursing practice policies, protocols and guidelines.

The development of Clinical Policy Ethics Assessment Tool involved first a literature review, followed by modification of the Research Protocol Ethics Assessment Tool, which was created to identify research protocols’ ethical issues, and finally, a trial of Clinical Policy Ethics Assessment Tool to ensure its reliability and validity.

The policies analysed trialling Clinical Policy Ethics Assessment Tool were in the public domain and did not contain any confidential information. Despite that, Clinical Policy Ethics Assessment Tool also had the approval of a research ethics committee.

Research Protocol Ethics Assessment Tool was chosen as the template for a Clinical Policy Ethics Assessment Tool, to which several modifications were added to adapt it to work within a nursing practice context. Clinical Policy Ethics Assessment Tool was tested twice, which resulted in a general test–retest reliability coefficient = 0.86, = 0.84, a1 = 0.817, a2 = 0.824 and interclass correlation coefficient = 0.874.

Contemporary nursing practice in a developed country is often ruled by clinical policies. The use of Clinical Policy Ethics Assessment Tool could confirm the ethical validity of those clinical practice policies, impacting on nurses’ education, values and quality of care.

Clinical Policy Ethics Assessment Tool has the potential to detect ethical issues and facilitate the correction and improvement of clinical policies and guidelines in a structured way. This is especially so as it has shown reliability in detecting issues in clinical policies involving human participants and in encouraging policymakers to consider common ethical dilemmas in nursing practice.

The full article can be downloaded below.  

Clinician opioid prescribing practices and patient utilization of prescribed opioids in pediatrics

Little is known regarding clinician prescribing of opioid medications and of patient use of prescribed opioid medications in pediatrics. The authors sought to learn more about pediatric clinician opioid prescribing practices and patient utilization and disposal of prescribed opioids. This was a cross-sectional, observational study that took place in a tertiary care pediatric healthcare center. Participants were pediatric clinicians who prescribe opioid medications and parents of children prescribed an opioid medication. Clinicians were surveyed about opioid prescribing practices for acute pain management in children, and parents were asked about utilization and disposal of prescribed opioids. Most clinician respondents (64 percent) reported prescribing opioid medications to manage acute pain. The typical length of opioid prescriptions was limited to 7 days (93 percent). Parents reported a high prevalence of leftover opioid medications (86 percent). Most (59 percent) did not dispose of the remaining medication. Ultimately, targets for intervention to reduce unnecessary opioid exposure in youth are identified.

The full article can be downloaded below.  

Shedding light on conditions for the successful passive dissemination of recommendations in primary care: a mixed methods study

Passive dissemination of information in healthcare refers to the publication or mailing of newly established guidelines or recommendations. It is one of the least costly knowledge translation activities. This approach is generally considered to be ineffective or to result in only small changes in practice. Recent research, however, suggests that passive dissemination could, under certain conditions, result in modifications of practice, similar to more active dissemination approaches. The objective of our study was to uncover the conditions associated with the change in primary care practice, namely Family Medicine Groups (FMGs) in Quebec (Canada), following the passive dissemination of recommendations for the diagnosis and management of Alzheimer’s disease and related dementia (AD).

We used a three-step, innovative, convergent mixed methods design based on a multiple case study in eight FMGs. Two studies were conducted in parallel: (1) a before and after retrospective chart review and a cluster analysis of FMGs performed on two clinical performance indicators—the rate of AD diagnosis and the quality of follow-up care; (2) a qualitative descriptive study using interviews and focus groups with FMG clinicians and healthcare managers. The results were integrated using joint displays. 

After the passive dissemination of the recommendations, some FMGs started to implement the recommendations while other FMGs did not change their practice with respect to the AD diagnosis rate and quality of follow-up care. Three interrelated conditions were identified for the successful passive dissemination of clinical recommendations: (1) FMG clinicians with a moderate to high baseline expertise and confidence, which was linked to their existing collaboration with hospital-based specialists in dementia and their motivation; (2) the presence of a self-identified champion (individual champion or collective championship) in the FMGs taking the lead, motivating the clinical staff or organizing training; (3) the availability of sufficient clinical staff enabled these two conditions to have an impact on the implementation of recommendations through passive dissemination.

Passive dissemination of clinical recommendations, a low-cost knowledge translation approach, may lead to practice change under some specific conditions. More active dissemination efforts may only be needed in sites where these conditions are absent.

The full article can be downloaded below.