Patient safety after implementation of a coproduced family centered communication programme: multicenter before and after intervention study

Families, nurses, and physicians coproduced an intervention to standardize healthcare provider-family communication on ward rounds (“family centered rounds”), which included structured, high reliability communication on bedside rounds emphasizing health literacy, family engagement, and bidirectional communication; structured, written real-time summaries of rounds; a formal training programme for healthcare providers; and strategies to support teamwork, implementation, and process improvement.

Although overall errors were unchanged, harmful medical errors decreased and family experience and communication processes improved after implementation of a structured communication intervention for family centered rounds coproduced by families, nurses, and physicians. Family centered care processes may improve safety and quality of care without negatively impacting teaching or duration of rounds.

The full article can be downloaded below.  

Prominent Doctors Aren’t Disclosing Their Industry Ties in Medical Journal Studies. And Journals Are Doing Little to Enforce Their Rules

One is dean of Yale’s medical school. Another is the director of a cancer center in Texas. A third is the next president of the most prominent society of cancer doctors.

These leading medical figures are among dozens of doctors who have failed in recent years to report their financial relationships with pharmaceutical and health care companies when their studies are published in medical journals, according to a review by ProPublica and The New York Times and data from other recent research.

In addition to the widespread lapses by doctors, the review by ProPublica and The Times found that journals themselves often gave confusing advice and did not routinely vet disclosures by researchers, although many relationships could have been easily detected on a federal database.

Medical journals, which are the main conduit for communicating the latest scientific discoveries to the public, often have an interdependent relationship with the researchers who publish in their pages. Reporting a study in a leading journal can heighten their profile — not to mention that of the drug or other product being tested. And journals enhance their cachet by publishing exclusive, breakthrough studies by acclaimed researchers.

In all, the reporting system still appears to have many of the same flaws that the Institute of Medicine identified nearly a decade ago when it recommended fundamental changes in how conflicts of interest are reported. Those have yet to happen.

The full ProPublica article can be viewed at this link.  

Now Mental Health Patients Can Specify Their Care Before Hallucinations and Voices Overwhelm Them

As the pendulum has swung from institutionalization to outpatient care, psychiatric advance directives (PADs) also offer a middle path by allowing patients to designate family members to speak for them when they’re too sick to do so themselves.

But some doctors and hospitals are wary that the documents could tie their hands and discourage treatment they consider warranted. Some worry the directives won’t be updated to reflect medical advances. Others question whether people with serious psychiatric conditions are ever capable of lucidly completing such directives.

Still, early research and experience suggest that PADs, authorized by law in 27 states and possible in others as part of conventional medical advance directives, could help some of the millions of people with serious mental illness cope better and guide doctors treating them.

The full article from the New York Times can be viewed at this link.  

A US National Study of the Association Between Income and Ambulance Response Time in Cardiac Arrest

Our analysis demonstrated that EMS responding to low-income communities had a lower likelihood of meeting 8-minute and 15-minute national benchmarks compared with EMS responding to highincome communities and showed that the mean EMS response time, on-scene time, and transport time were longer in low-income communities, even after controlling for observable differences. Given that whether or not a patient survives cardiac arrest can depend on a matter of minutes, even small delays in EMS response times may negatively alter patient outcomes. Our findings are disturbing given that poorer neighborhoods have higher rates of disease and other structural disparities in health care access that further compound their risk for worse outcomes. Our study shows that these structural disparities begin as early as the initial EMS activation and the resulting services, which is an area previously more traditionally administered by public services and considered less vulnerable to market forces. Recent trends in the financing and delivery of prehospital care suggest that these disparities are likely to worsen unless fewer economically driven forces are introduced. Understanding where gaps exist can help guide improvements in policies and develop interventions to address prehospital care disparities and ultimately disparities in patient outcomes.

The full article can be downloaded below.  

Prevalence of and Factors Associated With Patient Nondisclosure of Medically Relevant Information to Clinicians

In this research we examined what information patients are most likely to avoid telling a clinician, with a focus on types of information that are basic and essential to health care (eg, medication use, health behaviors, disagreement with recommendations, or lack of understanding of instructions). We also examined the characteristics that are associated with withholding information from clinicians and the reasons for this nondisclosure, distinguishing between, for example, nondisclosure due to embarrassment vs privacy reasons.

The full article can be downloaded below.  

Thought leader perspectives on benefits and harms in precision medicine research

Precision medicine research is underway to identify targeted approaches to improving health and preventing disease. However, such endeavors raise significant privacy and confidentiality concerns. The objective of this study was to elucidate the potential benefits and harms associated with precision medicine research through in-depth interviews with a diverse group of thought leaders, including primarily U.S.-based experts and scholars in the areas of ethics, genome research, health law, historically-disadvantaged populations, informatics, and participant-centric perspectives, as well as government officials and human subjects protections leaders. The results suggest the prospect of an array of individual and societal benefits, as well as physical, dignitary, group, economic, psychological, and legal harms. Relative to the way risks and harms are commonly described in consent forms for precision medicine research, the thought leaders we interviewed arguably emphasized a somewhat different set of issues. The return of individual research results, harm to socially-identifiable groups, the value-dependent nature of many benefits and harms, and the risks to the research enterprise itself emerged as important cross-cutting themes. Our findings highlight specific challenges that warrant concentrated care during the design, conduct, dissemination, and translation of precision medicine research and in the development of consent materials and processes.

The full article can be downloaded below.  

Predictive Modeling of 30-Day Emergency Hospital Transport of Patients Using a Personal Emergency Response System: Prognostic Retrospective Study

This study showed that remotely collected patient data using a PERS service can be used to predict 30-day hospital transport. Furthermore, linking these data to clinical observations from the EHR showed that predicted high-risk patients had nearly four times higher rates of emergency encounters in the year following the prediction date compared with low-risk patients. Health care providers could benefit from our validated predictive model by estimating the risk of 30-day emergency hospital transport for individual patients and target timely preventive interventions to high-risk patients. We are testing this hypothesis in a randomized clinical trial where risk predictions are combined with a stepped intervention pathway. This approach could lead to overall improved patient experience, higher quality of care, and more efficient resource utilization. Future studies should explore the impact of combined EHR and PERS data on predictive accuracy.

The full article can be downloaded below.  

Why Should You Care About Amazon's New Medical Language Processing Service

This week Amazon announced a new service called AWS Comprehend Medical at AWS Re:Invent 2018 that can potentially impact the whole medical records ecosystem. Although electronic health records (EHR) exist for more than a decade, the majority of historical patient data is still stored today as unstructured medical text, such as medical notes, prescriptions, audio interview transcripts, and printed pathology and radiology reports. Extracting meaningful information from these is still a time-consuming process, and either requires data entry by high skilled medical experts, or teams of developers writing custom code.

Comprehend Medical leverages Amazon’s AI technology to build a health record industry-specific solution, that uses natural language processing (NLP) to extract health-related text and data from virtually any medical record. Comprehend Medical empowers developers to process unstructured medical text and identify information such as patient diagnosis, treatments, dosages, symptoms and signs, and more. This will, in turn, help health care providers such as hospitals, insurers, and clinical trial investigators to improve clinical decision support, streamline revenue cycle and clinical trials management. Since Comprehend Medical has built-in HIPAA compliance, health care providers will be able to better address data privacy and protected health information (PHI) requirements. Other startups such as Mendel is building similar AI-powered medical data extraction platform for clinical data relevant to cancer research.

The full Forbes article can be viewed at this link.  

The First Frontier for Medical AI Is the Pathology Lab

Trained on vast troves of digitized slides showing an enormous variety of tumors, artificial-intelligence (AI) systems will likely provide more accurate diagnoses than human pathologists, at least on fairly rote diagnostic tasks. They may even pick up on subtle features that the best-trained human eyes could never see. In this crucial, high-stakes branch of medicine, AI tools may soon offer diagnoses—and treatment recommendations—that are as close to infallible as we’re likely to get in the foreseeable future. And they’ll do so in a matter of seconds.

Lately, dazzlingly high success rates for AI-based systems in recognizing the presence of certain specific illnesses have prompted speculation that such tools will replace doctors. But the developments in pathology show us a more likely outcome: that machines will make the ever-increasing complexity of modern medicine manageable for human beings. This human-machine combination will outperform what either could do individually. At first, the improvement will be small. But eventually, it will be great.

The full IEEE Spectrum article can be viewed at this link.  

How Blockchain Technology Could Disrupt Healthcare

From managing patient data to tracking drugs through the supply chain, blockchain could solve some of the healthcare industry’s biggest problems.

The healthcare industry is plagued by inefficiencies, errors, bureaucracy, and high administrative costs.

Could blockchain technology help solve some of these challenges?

For all the hype, there’s no question that blockchain’s distributed ledger technology can offer real value for the healthcare industry.

Blockchain could help solve some of the industry’s most pressing compliance, interoperability, and data security issues, as well as enable new patient-centric business models.

But unlocking blockchain’s potential for healthcare will be a slow process, and change is unlikely to come fast.

In this report, we analyze where blockchain is likely to be integrated into healthcare in the short, medium, and long term, based on known stakeholders, scalability requirements, and necessary safeguards.

The full CB Insights report can be viewed at this link.