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Brazil’s healthtech sector is new hot spot –

Brazil’s healthtech sector is new hot spot – | healthcare technology | Scoop.it

Like recent Brazilian investment booms focused on fintech innovation and new on-demand business models, there’s been a recent explosion in healthtech startups in Brazil.

 

About 75 percent of Brazil’s population (approximately 150 million people) only have access to the public healthcare system, which is poorly managed and inefficient. Often times, to schedule a single consultation or exam, a patient needs to wait weeks or even months to see a care provider. Technology-driven startups are springing up to address better, more efficient access to healthcare for a large and aging population.

 

To help make healthcare advice, diagnosis and monitoring more accessible, telehealth services in Brazil are expanding. 

 

Like many industries, AI and data analytics are transforming healthcare in Brazil and beyond from improving the speed of patient diagnoses to managing healthcare costs.

 

Last year, the Brazilian government launched a project to modernize patient records for more than 42,000 public health clinics across the country by the end of 2018. This digitization of records is estimated to save the federal government about $6.8 billion according to The World Bank. As of late last year, only 30 million Brazilians (out of 208 million) had electronic medical records (EMR), and nearly two-thirds of the family clinics in Brazil didn’t have any way of recording digital information about their patients.

 

Another major issue caused by a lack of digitization is that close to 70 percent of medical prescriptions in Brazil have potential for errors, according to the World Health Organization. As a result, Brazil has thousands of deaths per year linked to medication errors. A good number of them could be avoided by scanning. In the U.S., more than 77 percent of prescriptions are already done digitally.

 

Certainly, healthtech startups in Brazil have emerged as a sector to watch, and we’re only at the tip of the iceberg in terms of problems in the country to be addressed by healthtech innovation. The key ingredients to create another boom sector like fintech in the region are abundant. Healthtech in Brazil will surely remain a hot spot for entrepreneurs, and the investors who believe in them, for many years to come.

nrip's insight:

I have never posted something like this on this blog. 

 

I feel an upcoming market sometimes needs exposure so others can see opportunities to help, invest and mentor the growth there. I felt there are tons of new opportunities for so many of this blogs readers when I was reading this, and so I felt it would be useful to share.

 

Please use the comments section below, or the form on the right in case you wish to simply obtain some specific information or wish to collaborate and use our help with building out or scaling health tech in Brazil. 

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Social Media and Patient Advocacy

These are the slides from my talk at the 4th Annual Putting Patients First Conference in Mumbai.


If god were to manifest the world using technology, he would first create something like social media. Conceptually provide technology with the ability to understand the thoughts of a population


SocMed leaves behind the old model of 1-to-1 communication – “talking to someone over the phone”  Enables one-to-many communication (via blogs or microblogging) or many-to-many communication (discussion forums, social walls). Now anyone can setup an online community site/portal to represent a small or big offline community.


Further, anyone can setup an online site related to a treatment, a disease, a doctor, a drug , a concept or anything and see it grow into a popular site which in effect is simply the manifestation of a community which exists/ed but which no one ever knew of.

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Marie Ennis-O'Connor's curator insight, November 17, 2013 7:09 PM

Thanks so much for sharing your slides - i am looking forward to reading them. 

Plaza Dental Group's curator insight, January 29, 2014 8:53 AM

Great info! I think SocMed  will boost the thought of population and will effect change in local communities. 

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Pokemon GO Within the Context of Family Health -  A Retrospective Study

Pokemon GO Within the Context of Family Health -  A Retrospective Study | healthcare technology | Scoop.it

Pokémon GO illuminated the potential for mobile phone gaming apps to engage users and promote health. However, much work is needed to fully understand the mechanisms through which digitally supported behavior change interventions operate, particularly for children and families.

 

Objective: The aims of this study were

(1) to explore the Pokémon GO user experience from a family perspective and

(2) to investigate Pokémon GO within the context of family health.

 

Methods: Between January and February 2017, congruent with one of the largest anticipated Pokémon GO updates Gen 2, participants were recruited from parks, word of mouth, and social media to complete a Web-based survey. Participants were surveyed about family characteristics, interest, and experiences playing Pokémon GO and healthy lifestyle beliefs. Using a revised Godin Leisure-Time Exercise Questionnaire, a retrospective pre-post design assessed changes in parent physical activity (PA) before and after playing Pokémon GO.

 

Pokémon GO transcended traditional understanding of digital health and uniquely reached across generations to engage users. Findings from this study highlight that, for a period of time, Pokémon GO fostered social and physical well-being for children and families through a multifaceted approach.

 

 

read the study at https://pediatrics.jmir.org/2018/2/e10679/

 

nrip's insight:

Mobile Devices, Apps and Gaming can combine to create positive habit forming experiences. These can be manifested to bring about not just greater well being, but also easier to manage care plans for many.

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Corti heart attack detection AI can now deploy on the edge with Scandinavian design

Corti heart attack detection AI can now deploy on the edge with Scandinavian design | healthcare technology | Scoop.it

Amid all the talk that surrounds artificial intelligence — how it will simultaneously take jobs and improve lives — perhaps no form of AI could save more lives than the kind made to combat heart cardiac arrest, which is the biggest killer on Earth.

 

Detection of heart attacks is easily one of the most obvious ways AI should be used today. Cardiac arrest currently claims hundreds of thousands of lives a year around the globe.

 

With cardiac arrest events that occur outside of hospitals, every minute counts.

 

In initial trials, assistance  by Corti was found to identify cardiac arrest events more quickly than human operators.

 

Analysis of emergency calls involving cardiac arrest in Copenhagen in 2014 (published in a research paper in April), show Corti’s analysis of thousands of calls was 30 seconds faster than that of human operators, with an accuracy rate of 93 percent compared to 73 percent for human operators.

 

To serve a variety of needs and make it easier to get Corti up and running in more emergency call centers, the company created a hardware device to deploy its heart attack detecting AI on the edge. Enter: The Orb.

 

Work is underway to deploy Corti, an AI system that detects heart attacks during emergency phone calls, and it could be coming to some of the biggest cities in Europe.

 

Following plans announced earlier this year to roll Corti out in more cities, this summer the European Emergency Number Association (EENA), whose members include cities like London, Paris, Milan, and Munich, will deliver AI-powered assistance to emergency 112 operators.

 

Emergency call centers from Seattle to Singapore also want to make Corti part of their operations, but there’s no global standard for organizations working to save lives. Some are fine with the idea of deploying the AI through the cloud, while others with privacy concerns require the AI system to operate from on-premise servers.

 

read more at https://venturebeat.com/2018/10/14/cortis-heart-attack-detection-ai-can-now-deploy-on-the-edge-with-scandinavian-design/

 

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EHR Communication and Diabetes Patient Outcomes

EHR Communication and Diabetes Patient Outcomes | healthcare technology | Scoop.it

A study to correlate EHR Communication with patient outcomes for diabetes patients reported that "EHR team communication flow patterns may be an important avenue to explore in raising quality of care and lowering costs for patients with diabetes in primary care." The study found that Primary care teams whose EHR communication reached more team members indirectly (ie, via message forwarding) had worse outcomes and higher medical costs for their patients with diabetes.

 

The study was carried out to determine how changes in electronic health record (EHR) communication patterns in primary care teams relate to quality of care and costs for patients with diabetes.

The Study Design: EHR-extracted longitudinal observational study.

A total of 83 health professionals in 19 care teams at 4 primary care clinics associated with a large Midwestern university participated in the study.

 

Counts of messages routed between any 2 team members in the EHR in the past 18 months were extracted. Flow-betweenness, defined as the proportion of information passed indirectly within the team, was calculated.

 

The analysis related changes in team flow-betweenness to changes in emergency department visits, hospital stays, and associated medical costs for the teams’ patients with diabetes, while adjusting for team face-to-face communication, patient-level covariates, comorbidities, team size, and clinic fixed effects.

Results: Patient hospital visits increased by 13% (standard error [SE] = 6%) for every increase of 1 percentage point in team EHR message forwarding (ie, higher team flow-betweenness). Medical costs increased by $223 (SE = $105) per patient with diabetes in the past 6 months for every increase of 1 percentage point in team flow-betweenness.

Conclusions: Primary care teams whose EHR communication reached more team members indirectly (ie, via message forwarding) had worse outcomes and higher medical costs for their patients with diabetes.

 

EHR team communication flow patterns may be an important avenue to explore in raising quality of care and lowering costs for patients with diabetes in primary care.

 

read the whole study details at  https://www.ajmc.com/journals/issue/2018/2018-vol24-n10/putting-the-pieces-together-ehr-communication-and-diabetes-patient-outcomes 

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Why researchers are using AI to fake health data

Why researchers are using AI to fake health data | healthcare technology | Scoop.it

To get enough good data to train disease-hunting AI—and without violating patient privacy—scientists are turning to the AI techniques behind deepfakes

 

Current AI systems need a lot of data to learn on. That’s fine when you want an algorithm to recognize cats in videos—thank you, YouTube—but not all data is as easy to get. For researchers trying to train AI to spot medical conditions, privacy issues, financial concerns, and rare diseases with few examples all impede their efforts. But more AI could be the solution, with generative adversarial networks (GANs) creating realistic-enough medical images for AI to learn on.

 

In a new paper by chipmaker NVIDIA, MGH & BWH Center for Clinical Data Science and the Mayo Clinic, researchers showed how they used GANs–algorithms that iterate and improve by competing against each other–to create synthetic brain MRI images with tumors. The work was presented at the Medical Image Computing and Computer Assisted Intervention MICCAI conference in Spain last week.

 

The researchers used two open data sets of brain MRIs to train the system—one that showed brains with Alzheimer’s disease and the other with tumors.

 

The resulting images are good enough that using a mix of 10% real data and the rest GAN-created was as good at training the algorithm to spot tumors in new images as a data set made up of all real images.

 

There are limitations. GANs can’t create types of images with details it has never seen before, and could make the often unnoticed imbalances in data sets worse. And since the biology of tumors isn’t totally understood, creating images from scratch isn’t an option.

 

Still, GANs can produce pictures with tumors that are larger or smaller, or move them to the other side of the brain, and in realistic ways.

 

read the original unedited article at https://www.fastcompany.com/90240746/deepfakes-for-good-why-researchers-are-using-ai-for-synthetic-health-data 

 

nrip's insight:

Using dummy data(fakes) is an age old technique in any software design and algorithm building process. Using automated systems with self learning capabilities(thats becomes AI right) to generate fake data, is also an age old technique. After a point, it becomes interesting to see how the AI system can be used for ways besides simply generating the deepfakes

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Medical Device Cybersecurity - Regional Incident Preparedness and Response Playbook by MITRE for US FDA

Medical Device Cybersecurity - Regional Incident Preparedness and Response Playbook by MITRE for US FDA | healthcare technology | Scoop.it

Cybersecurity attacks on Healthcare and Public Health (HPH) critical infrastructure, such as healthcare delivery organizations (HDOs), are occurring with greater frequency.  Disruptions in clinical care operations can put patients at risk.

Securing critical infrastucture is a shared responsibility across many stakeholders, and with respect to medical
devices the primary stakeholders are FDA, Medical Device Manufacturers (MDMs), and HDOs.

 

A common preparedness and response challenge FDA heard from its stakeholders in the aftermath of the aforementioned attacks is that

  • HDOs did not know with whom to communicate (e.g. MDM-HDO interactions);
  • what actions they might consider taking;
  • and what resources were available to aid in their response.

 

Without timely, accurate information and incorporation of medical device cybersecurity into their organizational emergency response plans, it was difficult for HDOs to assess and mitigate the impact of these attacks on their medical devices.

 

To address this unmet need, the MITRE team (with the support of FDA), engaged with a broad distribution of stakeholder groups to understand the gaps, challenges, and resources for HDOs participating in medical device cybersecurity preparedness and response activities.

 

Their efforts resulted in the creation of this playbook that may serve as a resource for HDOs.

 

The playbook provides a stakeholder-derived, open source, and customizable framework that HDOs may choose to leverage as a part of their emergency response plans in order to ultimately limit disruptions in continuity of clinical care as well as the potential for direct patient harm stemming from medical device cyber security incidents.

 

The link to the PDF of the first version of the playbook -> https://www.mitre.org/sites/default/files/publications/pr-18-1550-Medical-Device-Cybersecurity-Playbook.pdf

 

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Complicated medical mysteries of more than 130 patients with rare unidentified diseases solved

Complicated medical mysteries of more than 130 patients with rare unidentified diseases solved | healthcare technology | Scoop.it

A national network of “disease detectives” has cracked the complicated medical mysteries of more than 130 patients with rare, previously unidentified diseases, though the bulk of the cases that come to them remain unsolved, according to an analysis of the network released Wednesday.

 

The Undiagnosed Diseases Network — which now has 12 clinics nationwide, including one at Stanford — has a solve rate of about 35 percent, according to the analysis, published in the New England Journal of Medicine. Considering that all of the cases the network investigates involve patients with extremely complex conditions for which they’ve gone years — sometimes decades — without a diagnosis, that’s an impressive outcome, said the authors of the report.

 

Most patients were diagnosed after a thorough analysis of their genome revealed a rare genetic mutation. Some were diagnosed only after the network was able to find just one or two other patients in the world with similar symptoms who had gotten a diagnosis.

 

If doctors can access previous research that has connected certain symptoms with specific parts of the genome, that can at least give them a clue of where to look for a diagnosis. The Undiagnosed Diseases Network, which often relies on genome sequencing to diagnose patients, could be a major contributor to that greater understanding

 

the original unedited story : https://www.sfchronicle.com/health/article/Disease-detectives-crack-cases-of-130-13297547.php

 

 
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Studies show that CBT-I delivered digitally through mobile phone apps is effective in treating # insomnia.

Studies show that Cognitive Behavior Therapy for Insomnia (CBT-I) delivered digitally through mobile phone apps is effective in treating insomnia.

 

Like a real therapist, the apps that use Cognitive Behavior Therapy for Insomnia (CBT-I) also provide practical tools to help the user worry less about their sleep and over time, be less anxious and more confident about their ability get a good night's rest. It's very similar to what physicians do face-to-face with patients,

 

And a recent study of Sleepio by Ong and the team that developed the product found that participants who used the product reported an improvement in insomnia symptoms and overall wellbeing.

 

However, these apps don't work for everyone.

 

The recent study hints at why. Less than 50 percent [of people who were assigned to use the app in a randomized controlled trial] are able to make it through the entire course of CBT delivered through digital platforms, For some people it may be hard to make it through all the sessions of CBT.

 

This is true of most health and wellness apps.

 

In other studies it has been found that of the 10,000 mental health apps out there, very few are actually being used.

 

We dont really understand how people are using technology towards their health and recovery,

 

But in some ways, he says, people with insomnia may be ahead of scientists in figuring out what works well for them.

 

read the original unedited piece at https://www.npr.org/sections/health-shots/2018/10/08/654883409/some-apps-may-help-curb-insomnia-others-just-put-you-to-sleep

 

 

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Deep learning is helping to make prosthetic arms behave more naturally

Deep learning is helping to make prosthetic arms behave more naturally | healthcare technology | Scoop.it

Deep learning is helping to make prosthetic arms behave more naturally.

 

 

Each year, more than 150,000 people have a limb amputated after an accident or for various medical reasons. Most people are then fitted with a prosthetic device that can recognize a limited number of signals to control a hand or foot, for example.

 

But Infinite Biomedical Technologies, a Baltimore startup company and another firm are taking advantage of better signal processing, pattern recognition software and other engineering advances to build new prosthetic controllers that might give amputees an easier life.

 

The key is boosting the amount of data the prosthetic arm can receive, and helping it interpret that information. “The goal for most patients is to get more than two functions, say open or close, or a wrist turn. Pattern recognition allows us to do that,” says Rahul Kaliki, CEO of Infinite. “We are now capturing more activity across the limb.”

 

Kaliki’s team of 14 employees are building the electronics that go inside other companies’ prosthetic arms. Infinite’s electronic control system, called Sense, records data from up to eight electrodes on his upper arm. Through many hours of training on the company’s tablet app, the device can detect the intent encoded in Rubin’s nerve signals when he moves his upper arm in a certain way. Sense then instructs his prosthetic hand to assume the appropriate grip.

 

read the original unedited story at  at https://www.wired.com/story/bionic-limbs-learn-to-open-a-beer/

 

 

 

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Automated malnutrition screening system for hospitalized children #NHITWeek

Automated malnutrition screening system for hospitalized children #NHITWeek | healthcare technology | Scoop.it

A team of clinicians, dietitians and researchers has created an innovative automated program to screen for malnutrition in hospitalized children, providing daily alerts to healthcare providers so they can quickly intervene with appropriate treatment. The malnutrition screen draws on existing patient data in electronic health records (EHR)

 

"Undernutrition is extremely common in children with cancer--the population we studied in this project," said study leader Charles A. Phillips, MD, a pediatric oncologist at Children's Hospital of Philadelphia (CHOP). "There is currently no universal, standardized approach to nutrition screening for children in hospitals, and our project is the first fully automated pediatric malnutrition screen using EHR data."

 

Phillips and a multidisciplinary team of fellow oncology clinicians, registered dietitians and quality improvement specialists co-authored a paper published Oct. 5, 2018 in the Journal of Nutrition and Dietetics.

 

The study team analyzed EHR data from inpatients at CHOP's 54-bed pediatric oncology unit over the period of November 2016 through January 2018, covering approximately 2,100 hospital admissions. The anthropometric measurements in the EHR included height, length, weight and body mass index. The researchers used software to take note of changes in those measurements, and used criteria issued by the Academy of Nutrition and Dietetics and the American Society for Parenteral and Enteral Nutrition, to evaluate each patient's risk of malnutrition.

 

For each child that the screening program judged to be at risk, the tool classified the risk as mild, moderate or severe. It then automatically generated a daily e-mail to hospital clinicians, listing each patient's name, medical record number, unit, and malnutrition severity level, among other data.

 

In the patient cohort, the researchers' automated screen calculated the overall prevalence of malnutrition at 42 percent for the entire period of study, consistent with the range expected from previous studies (up to about 65 percent for inpatient pediatric oncology patients). Overall severity levels for malnutrition were 47 percent in the mild category, 24 percent moderate and 29 percent severe; again, consistent with other research and clinical experience.

 

The study leader stated that:

 

This test study demonstrates the feasibility of using EHR data to create an automated screening tool for malnutrition in pediatric inpatients. Further research is needed to formally assess this screening tool, but it has the potential to identify at-risk patients in the early stages of malnutrition, so we can intervene quickly. In addition, this tool could be implemented to screen all pediatric patients for malnutrition, because it uses data common to all electronic medical records.

 

read the unedited original article at https://www.eurekalert.org/pub_releases/2018-10/chop-fam100918.php

 

nrip's insight:

Healthcare data is increasingly being analyzed. While we have written previously on AI, Prediction systems, automation, machine learning and other cool stuff, seemingly uncool technology is what provides the coolest benefits. 

 

But this article and the story behind is the perfect example of how technology can be most effective for improving healthcare workflows in 2018 and 2019. Further ahead the benefits of the previously mentioned cool techs will hopefully be starting to be realizable, but we must use automation and analysis to intervene in current workflows and make them more effective today as much as we can.

 

This directly benefits clinical staff, speeds up care and actually starts making EHR data directly beneficial to those pained by the process of generating it.

 

To know about how many such benefits can be extracted from uncool technologies, check out out websites to learn about Medixcel and talk to us in the comments below.

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Automation in Healthcare is Transforming Medicine #NHITWeek

Automation in Healthcare is Transforming Medicine #NHITWeek | healthcare technology | Scoop.it

Information technology has allowed much of our economy to automate processes. We have seen transformations of the airline, banking, brokerage, entertainment, lodging, music, printing, publishing, shipping and taxi industries through the availability of massive volumes of real-time price and service data. Across America, consumer-facing retail service continues to shift to a virtual environment.

 

Healthcare is the exception. Many health information technology (health IT) products initially focused on billing.

The misalignment between billing support and the sense that these tools do not materially automate clinician work to build in efficiencies or improve workflows adds to an overall frustration with the increasing amount of time providers spend at their screens.

 

Automation is hard because it tends to require interfaces of various types – both to other machines (Internet of Things) and to humans.

 

Often automation proposals involve solutions that focus on highly structured data. But, someone or something has to put energy (physician salary, for example) into organizing much of this information, assuming it is even knowable.

 

The underlying disease or patient behavior (e.g., smoking) is also often not knowable. And, automation relying on machine to machine interfaces regularly runs into a lack of application programming interfaces (APIs) supporting complex clinical data flows.

 

I posted this week old piece now and now when it was published as #NHITWeek is this week. A lot of posts this week deal with possibilities and problems with healthcare focussed automation. 

 

The original unedited piece can be read at https://www.himss.org/news/healthcare-automation-transforming-medicine

nrip's insight:

I posted this week old piece now and now when it was published as #NHITWeek is this week. A lot of posts this week deal with possibilities and problems with healthcare focussed automation. 

 

What has your experience been , or your opinion on automation, and its uses in life sciences and medicine.

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Proposing a Transactional Model of eHealth Literacy: Concept Analysis | JMIR

Proposing a Transactional Model of eHealth Literacy: Concept Analysis | JMIR | healthcare technology | Scoop.it

eHealth literacy was conceptualized in 2006 as the ability of internet users to locate, evaluate, and act upon web-based health information.

 

Now, advances in eHealth technology have cultivated transactional opportunities for patients to access, share, and monitor health information. However, empirical evidence shows that existing models and measures of eHealth literacy have limited theoretical underpinnings that reflect the transactional capabilities of eHealth.

 

This paper describes a conceptual model based on the Transactional Model of Communication (TMC), in which eHealth literacy is described as an intrapersonal skillset hypothesized as being dynamic; reciprocal; and shaped by social, relational, and cultural contexts.

 

The objective of this study was to systematically examine eHealth literacy definitions, models, and measures to propose a refined conceptual and operational definition based on the TMC.

 

Systematic review evidence revealed incongruity between operational eHealth literacy included in definitions compared with literacies included within models and measures. Theoretical underpinnings of eHealth literacy also remain dismal.

 

Despite the transactional capabilities of eHealth, the role of “communication” in eHealth literacy remains underdeveloped and does not account for physical and cognitive processing abilities necessary for multiway transactions.

 

read the full study at https://www.jmir.org/2018/10/e10175/

nrip's insight:

eHealth literacy is the ability of internet users to locate, evaluate, and act upon web-based health information. The result of this study identifies that the role of “communication” in eHealth literacy remains underdeveloped.

 

Current frameworks and technologies do not account for physical and cognitive processing abilities necessary for multiway transactions.

 

A study of the Consumption(access by patients) patterns of a majority of patient education resources will be interesting. It may shed light on this underdevelopment being required or not.

 

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DeepMind furthering AI cancer research program with new partnership in Japan to refine breast cancer detection algorithms

DeepMind furthering AI cancer research program with new partnership in Japan to refine breast cancer detection algorithms | healthcare technology | Scoop.it

Deep mind will use data available to it via a new partnership with Jikei University Hospital in Japan to refine its artificially intelligent (AI) breast cancer detection algorithms.

 

Google AI subsidiary DeepMind has partnered with Jikei University Hospital in Japan to analyze mammagrophy scans from 30,000 women.

 

DeepMind is furthering its cancer research efforts with a newly announced partnership.

 

The London-based Google subsidiary said it has been given access to mammograms from roughly 30,000 women that were taken at Jikei University Hospital in Tokyo, Japan between 2007 and 2018.

 

Deep mind will use that data to refine its artificially intelligent (AI) breast cancer detection algorithms.

 

Over the course of the next five years, DeepMind researchers will review the 30,000 images, along with 3,500 images from magnetic resonance imaging (MRI) scans and historical mammograms provided by the U.K.’s Optimam (an image database of over 80,000 scans extracted from the NHS’ National Breast Screening System), to investigate whether its AI systems can accurately spot signs of cancerous tissue.

nrip's insight:

Healthcare data is increasingly being analyzed and complex algorithms created to help various aspects of the healthcare ecosystem.

 

A big problem is the availability of huge data sets, and where available, the prevention of their misuse. Its great that Deepmind is able to source data sets , (being a sub of Google, am sure plays a role), and hopefully they will put their deep mind ;) to good use  and be able to improve detection algorithms.

 

I have written previously on this, and it will be useful for patients and  if the data sets do help create both faster as well as more accurate detection algorithms in the future.

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Use of EHRs to Gather Real-World Data on Pharmaceuticals

Use of EHRs to Gather Real-World Data on Pharmaceuticals | healthcare technology | Scoop.it

Using electronic health records (EHRs) to create a learning healthcare system, say the authors, can enable researchers to generate new knowledge that will accrue benefits to future generations of patients.

 

Real-world data are increasingly viewed as a crucial factor in the eventual acceptance of biosimilar drugs, and indeed, current real-world evidence points to the safety and efficacy of these products in the marketplace.

 

In a recent paper, officials from the European Medicines Agency, the Organisation for Economic Cooperation, and other European government entities explained that such data can help make decisions about pharmaceuticals—from development to reimbursement—more efficient.

 

The authors called for international cooperation on a learning healthcare system that will better harness these data. 

The authors note that the expense of prospective data generation in a research setting is high, limiting the number of research questions that can be answered in a randomized controlled trial (RCT).

 

RCTs are rarely large enough to detect infrequent outcomes, nor are they long enough to determine long-term outcomes. 

Using electronic health records (EHRs) to create a learning healthcare system, say the authors, can enable researchers to generate new knowledge that will accrue benefits to future generations of patients.

 

However, current inadequacies of EHRs present a “technical bottleneck” to the objective of gathering real-world data.  

The paper’s authors propose that governments establish and implement national health data governance frameworks to encourage the use of personal health data to serve the public interest.

 

The collection of data must translate into the production of useful evidence.

A coordinated and international effort will be key to speed the implementation of a true learning healthcare system for global benefit. 

 

read the news article at https://www.centerforbiosimilars.com/news/european-officials-promote-use-of-ehrs-to-gather-real-world-data-on-pharmaceuticals--

nrip's insight:

I am currently writing an Ebook on "Use of EHRs for Public Health" which covers this very concept. Please comment in the section below or tweet us at @plus91 (you can tweet to @nrip to reach me directly) your thoughts on EHR usage, and possible uses of EHR data for the benefit of the public healthcare system

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Healthcare Technology Insights for Oct 1st — Oct 14th 2018

Healthcare Technology Insights for Oct 1st — Oct 14th 2018 | healthcare technology | Scoop.it
This fortnight, in the spirit of the #NHITWeek ,as expected a lot of curations were based around the Uses of Automation and Artificial Intelligence in Healthcare.
 
Here are our top 5 insights by our experts on the stories from the past fortnight.

 

mHealth platforms are helping healthcare providers with Quick Access to Decision Support Resources

 

insight by Nrip Nihalani

 

Well how surprising! Collective human intelligence still works :)

 

As I been posting in my articles, speaking at my talks and offering my $0.02 in my insights, for all the talk of AI and Deep Learning, I feel technology’s best use in healthcare is in automation of processes and improving communication and collaboration between care teams. And such studies show that we have lots to gain by building better tools to help clinicians communicate and collaborate better. Someday , AI “may” replace human intelligence, but not today and not anytime soon.

 

Proposing a Transactional Model of eHealth Literacy: Concept Analysis

 

insight by Nrip Nihalani

 

eHealth literacy is the ability of internet users to locate, evaluate, and act upon web-based health information. The result of this study identifies that the role of “communication” in eHealth literacy remains underdeveloped.

 

Current frameworks and technologies do not account for physical and cognitive processing abilities necessary for multiway transactions.

 

A study of the Consumption(access by patients) patterns of a majority of patient education resources will be interesting. It may shed light on this underdevelopment being required or not.

 

more at https://medium.com/@plus91/healthcare-technology-insights-for-oct-1st-oct-14th-2018-8505bbd81fd9

 

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Virtual Assistant Eases EHR Distractions for Physicians 

Virtual Assistant Eases EHR Distractions for Physicians  | healthcare technology | Scoop.it

AI-powered smartphone app can reduce physician burnout, enhance patient experience

 

Virtual assistants are a fast-growing phenomenon, not only with the use of consumer products such as Amazon's Alexa, Google Assistant, and Apple's Siri, but as part of automated communications with many industries, such as airlines and banking. Market intelligence firm Research and Markets released a report earlier this year forecasting:

 

The healthcare market has lagged behind, but in September, Nuance and Epic released the first version of a conversational virtual assistant. It operates on Nuance's Dragon Medical cloud-based platform and is available through Epic Haiku, a mobile app for physicians that interfaces with the Epic EHR. The assistant is an upgrade to the app, used by physicians, which provides secure access to clinic schedules, hospital patient lists, health summaries, test results, and notes, while supporting dictation.

 

HOW VIRTUAL ASSISTANTS WILL CHANGE HEALTHCARE SHORT TERM 

According to Sean Bina, vice president of access applications for Epic, the assistant can answer questions such as:

  • What are the patient's A1c test results?
  • What medication is the patient taking?
  • What's my schedule for today?
  • Has the patient had a colonoscopy?

 

The immediate impact has the potential to reduce provider burnout, diminish difficulty locating information in the EHR, and change the physician-patient dynamic.

 

WHAT THE FUTURE HOLDS

VUMC is taking the virtual assistant another step further and developing contextually useful summaries to provide an overview of relevant patient information for the physician to listen to before entering the exam room.

 

Among the other capabilities in development:

  • Medication and test ordering. While Dragon Medical currently has these capabilities built into its system, Epic has not yet activated this feature. During testing with Vanderbilt, the mean time for ordering medications via the virtual assistant was 17 seconds, compared to 50 seconds using the mobile app without voice assistance.
     
  • Decision support tools that could issue alerts, for example, if a patient has adverse reactions or allergies to medications the doctor orders.
     
  • A desktop version of the virtual assistant is planned by Nuance and Epic.

 

read the entire article at https://www.healthleadersmedia.com/innovation/virtual-assistant-eases-ehr-distractions-physicians

 

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Text message based surveying appears to be a reliable source of health data during crisis

Text Messaging (SMS) technology is widely adopted in developing countries.

Text message-based health surveys distributed to 6,694 Liberians during an Ebola outbreak were generally on par with baseline demographic data collected in a prior household survey, according to a study recently published in Nature Digital Medicine. Further, the text surveys suggested that women sought fewer hospital-based deliveries during the outbreak, a trend consistent with other retrospective studies that have been published since the outbreak.

 

The Ebola outbreak was, and in some areas continues to be, a test of public health infrastructure. In regard to maternal care in particular, the researchers noted that many communities perceived a reduction in care quality as practitioners were advised not to make physical contact patients espousing fluids whenever possible.

 

As such, a viable, real-time data collection system that is based on a technology widely adopted by residents can be a substantial boon to health systems facing crisis,

 

 

Why it matters 

Taken together, these findings would indicate that these text-based surveys could be an avenue toward more real-time data collection in developing countries gripped by outbreaks.

 

for more, read the original unedited article at https://www.mobihealthnews.com/content/text-based-survey-offers-accurate-real-time-health-info-during-ebola-outbreak-study-says

 

 

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Estonia and Finland will start exchanging digital prescriptions at the end of 2018

Estonia and Finland will start exchanging digital prescriptions at the end of 2018 | healthcare technology | Scoop.it

Estonia and Finland will start exchanging digital prescriptions at the end of the year, in a groundbreaking move that Estonian Health Minister Riina Sikkut said she hoped other EU countries will follow.

 

Speaking to EURACTIV.com on the sidelines of the European Health Forum in Gastein, Austria, Sikkut said that in Estonia, it is common practice for healthcare professionals to use the e-health system to exchange patient medical records.

 

“But it is also important for people who have a need for healthcare services abroad to have his or her health data available to a doctor, nurse or a pharmacist so that they could also provide quality healthcare services and continuity of care,” she said.

 

The cross-border flow of data has taken centre stage in the discussion in Brussels. Right now, when citizens move to another EU member state, their healthcare data is in fact simply “lost”.

 

Advocates of the digitisation of healthcare say data mobility, or the “5th freedom”, in the EU could unlock the potential of innovation in the sector and make EU patients’ lives easier.

 

Estonia is known for its digitisation push in all sectors, and during its EU Presidency (July-December 2017), it took significant steps to create a “coalition of the willing” of EU member states to speed up healthcare data mobility in Europe.

 
 
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Brazil’s healthtech sector is new hot spot –

Brazil’s healthtech sector is new hot spot – | healthcare technology | Scoop.it

Like recent Brazilian investment booms focused on fintech innovation and new on-demand business models, there’s been a recent explosion in healthtech startups in Brazil.

 

About 75 percent of Brazil’s population (approximately 150 million people) only have access to the public healthcare system, which is poorly managed and inefficient. Often times, to schedule a single consultation or exam, a patient needs to wait weeks or even months to see a care provider. Technology-driven startups are springing up to address better, more efficient access to healthcare for a large and aging population.

 

To help make healthcare advice, diagnosis and monitoring more accessible, telehealth services in Brazil are expanding. 

 

Like many industries, AI and data analytics are transforming healthcare in Brazil and beyond from improving the speed of patient diagnoses to managing healthcare costs.

 

Last year, the Brazilian government launched a project to modernize patient records for more than 42,000 public health clinics across the country by the end of 2018. This digitization of records is estimated to save the federal government about $6.8 billion according to The World Bank. As of late last year, only 30 million Brazilians (out of 208 million) had electronic medical records (EMR), and nearly two-thirds of the family clinics in Brazil didn’t have any way of recording digital information about their patients.

 

Another major issue caused by a lack of digitization is that close to 70 percent of medical prescriptions in Brazil have potential for errors, according to the World Health Organization. As a result, Brazil has thousands of deaths per year linked to medication errors. A good number of them could be avoided by scanning. In the U.S., more than 77 percent of prescriptions are already done digitally.

 

Certainly, healthtech startups in Brazil have emerged as a sector to watch, and we’re only at the tip of the iceberg in terms of problems in the country to be addressed by healthtech innovation. The key ingredients to create another boom sector like fintech in the region are abundant. Healthtech in Brazil will surely remain a hot spot for entrepreneurs, and the investors who believe in them, for many years to come.

nrip's insight:

I have never posted something like this on this blog. 

 

I feel an upcoming market sometimes needs exposure so others can see opportunities to help, invest and mentor the growth there. I felt there are tons of new opportunities for so many of this blogs readers when I was reading this, and so I felt it would be useful to share.

 

Please use the comments section below, or the form on the right in case you wish to simply obtain some specific information or wish to collaborate and use our help with building out or scaling health tech in Brazil. 

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Why Cyber-Criminals Are Attacking Healthcare -- And How To Stop Them

Why Cyber-Criminals Are Attacking Healthcare -- And How To Stop Them | healthcare technology | Scoop.it

Healthcare organisations are a major target for cyber criminals – and the consequences are huge. How can attacks be stopped?

 

The last five years has seen a surge of attacks on the healthcare industry, with the largest breaches impacting as many as 80 million people. In July this year, it was revealed that 150,000 NHS patients' data was shared over a three-year period following a major breach.

 

Over in the US, the 2015 cyber-attack on Anthem saw hackers steal 78.8 million patient records, claiming highly sensitive data, including names, social security numbers, home addresses and dates of birth.

 

Meanwhile, this year, hackers breached the Singapore government’s health database with a targeted cyber-attack, accessing the data of 1.5 million patients.

 

Healthcare breaches are especially serious because personal data can, in some cases, mean the difference between life and death. For example, says Carlisle, it could cause medications to become mixed up – or people might fail to get treatment for conditions such as diabetes.

 

Healthcare providers often struggle to find room in tight budgets to invest in new IT systems, leaving them vulnerable. “Compliance issues are commonplace in healthcare too, where organizations need to meet stringent requirements of governing bodies such as HIPAA

 

While network and endpoint technologies are a required element of an organization’s IT security stance, they are increasingly less effective at keeping external attacks at bay, They are also an inadequate way of securing cloud, big data, internet of things (IoT) and container deployments.

 

The critical nature of healthcare environments means users require immediate access to healthcare data across a range of devices and applications. Therefore, Security can often be seen as a barrier rather than an enabler.

 

It’s integral that healthcare organizations bolster their data security and compliance efforts. Data should be encrypted so it would be “worthless” in the event of a cyber-attack.

 

The good news is that healthcare data breaches are now in the consumer collective consciousness – and organizations are more aware than ever of potential data misuse.

 

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mHealth platforms are helping healthcare providers with Quick Access to Decision Support Resources

mHealth platforms are helping healthcare providers with Quick Access to Decision Support Resources | healthcare technology | Scoop.it

Healthcare providers who access clinical decision support through mHealth platforms are finding a world of information at their fingertips – and they could be saving lives.

 

Digital technologies are changing the way medical information is gathered and exchanged.  Physicians of all ages and medical subspecialties from across the globe are utilizing tools to discuss potential diagnoses and obtain second opinions.

 

That’s the takeaway from researchers at the Scripps Research Translational Institute who took a closer look at online crowdsourced consult platforms.

 

Their conclusion is that these platforms, which include social media networks like SERMO, Medscape and HealthTap, are giving providers quick access to information that’s helping them reduce serious, costly and potentially deadly medical errors.

 

The study, focusing on an analysis of more than 37,000 active users on the MedScape Consult network between 2015 and 2017, appears in a recent issue of NPJ Digital Medicine.

 

The research points to the value of a mobile health resource for clinical decision support, giving providers a real-time portal for physician-to-physician engagement. Billed as a source for “the second to hundredth opinion in medicine,” these portals allow providers to gather best practices and apply them quickly, reducing the chances of a clinical error.

 

The study also points to the changing nature of clinical decision support.The study noted that providers can’t necessarily rely on informal face-to-face consults with colleagues – commonly known as curbside consults – because they’re “frequently inaccurate and incomplete.” Yet they can’t just call up a nearby specialist at a moment’s notice.

 

The study found that : "At a time when we’re turning to artificial intelligence to help improve diagnostic accuracy, there’s still plenty of room for tapping into human intelligence via such medical consulting platforms, Artificial intelligence has been advocated as the definitive pathway for reducing misdiagnosis, But the study's findings suggest the potential for collective human intelligence, which is algorithm-free and performed rapidly on a voluntary basis, to emerge as a competitive or complementary strategy."

 

 

nrip's insight:

Well how surprising! Collective human intelligence still works :)

 

For us, its not surprising. As I been posting in my articles, speaking at my talks and offering my $0.02 in my insights,  for all the talk of AI and Deep Learning, I feel technology's best use in healthcare is in automation of processes and improving communication and collaboration.  And such studies show that we have lots of gain by building better tools to help clinicians communicate and collaborate better. Someday , AI "may" replace human intelligence, but not today and not anytime soon.

 

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BlackBerry's new blockchain tools could boost security for medical IoT

BlackBerry's new blockchain tools could boost security for medical IoT | healthcare technology | Scoop.it

As the Internet of Things (IoT) and other emerging technologies continue to proliferate in healthcare, BlackBerry has developed a set of technologies to help leverage these technologies while prioritizing data security.

 

The first of these tools is a blockchain solution, powered by the company's network operation center (NOC), that aims to facilitate safer storage and transfer of medical data, the release said. For example, the data could be anonymized for use in medical research, it noted.

 

BlackBerry will be offering its blockchain tool to the Global Commission, an organization focused on eradicating rare diseases in children, the release said. The Global Commission hopes to use the tool to create real-time insights that will speed diagnoses.

 

"We are applying our expertise in security, data privacy, and communication work in regulated industries such as automotive, financial services, and government to tackle one of the biggest challenges in the healthcare industry: leveraging healthcare endpoints to improve patient outcomes while ensuring security and data privacy," BlackBerry CEO John Chen said in a press release.

 

 

 

read the original unedited piece at https://www.techrepublic.com/article/blackberrys-new-blockchain-tools-could-boost-security-for-medical-iot/

 

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Tencent partners with Medopad to improve Parkinson's disease treatment with AI

Tencent partners with Medopad to improve Parkinson's disease treatment with AI | healthcare technology | Scoop.it

Roughly 600,000 people in the U.S. are diagnosed with Parkinson’s every year, contributing to the more than 10 million people worldwide already living with the neurodegenerative disease. Early detection can result in significantly better treatment outcomes, but it’s notoriously difficult to test for Parkinson’s.

 

Tencent and health care firm Medopad have committed to trialing systems that tap artificial intelligence (AI) to improve diagnostic accuracy. They announced a collaboration with the Parkinson’s Center of Excellence at King’s College Hospital in London to develop software that can detect signs of Parkinson’s within minutes. (Currently, motor function assessments take about half an hour.)

 

This technology can help promote early diagnosis of Parkinson’s disease, screening, and daily evaluations of key functions.

 

Medopad’s tech, which uses a smartphone camera to monitor patients’ fine motor movements, is one of several apps and wearables the seven-year-old U.K. startup is actively developing.

 

It instructs patients to open and close a fist while it measures the amplitude and frequency of their finger movements, which the app converts into a graph for clinicians. The goal is to eventually, with the help of AI, teach the system to calculate a symptom severity score automatically.

 

Tencent and Medopad are far from the only firms applying AI to health care. Just last week, Google subsidiary DeepMind announced that it would use mammograms from Jikei University Hospital in Tokyo, Japan to refine its AI breast cancer detection algorithms. And last month Nvidia unveiled an AI system that generates synthetic scans of brain cancer

 

read the original story at https://venturebeat.com/2018/10/08/tencent-partners-with-medopad-to-improve-parkinsons-disease-treatment-with-ai/

 

 
nrip's insight:

Healthcare data is increasingly being analyzed and complex algorithms created to help various aspects of the healthcare ecosystem.

 

A big problem is the availability of huge data sets, and where available, the prevention of their misuse.  Its promising that Tencent has already been working on computer vision software that can diagnose skin cancer from pictures taken with a phone, and its AIMIS system already has the capability to detect esophageal cancer, lung sarcoidosis, and diabetic retinopathy from medical images

 

I have written previously on this, and it will be useful for patients and  if the data sets do help create both faster as well as more accurate detection algorithms in the future.

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New tool helps doctors determine which patients are most likely to forget or skip their appointments

New tool helps doctors determine which patients are most likely to forget or skip their appointments | healthcare technology | Scoop.it

Patients who don't show up for their scheduled medical appointments drain health care providers' time and resources, reducing appointment availability, increasing wait times, and reducing patient satisfaction.

 

In an effort to solve this problem, a team of researchers from the Johns Hopkins University's Malone Center for Engineering in Healthcare has developed a new algorithm that can reduce no-show rates and increase appointment availability.

 

The model, in use by two JHCP clinics since September 2017, has already provided helpful insights into which factors play the biggest role in no-show appointments.

 

For example, it indicates that patients who visit emergency departments more frequently are more likely to fail to attend scheduled appointments.

In contrast, patients who use the online patient portal to schedule their own appointments are more likely to keep appointments.

 

read the original unedited story at https://hub.jhu.edu/2018/10/04/algorithm-predicts-patient-no-shows/

 

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Many smart wearable devices can even monitor mental-health data 

Many smart wearable devices can even monitor mental-health data  | healthcare technology | Scoop.it

It is projected that by next year, over 7.6 billion people throughout the world will use over 30 billion smart, sensor-based wearable devices that will monitor human activities, including mental-health data.

 

Smartphones and wearable sensors are able to detect and analyze behaviors such as activity (by GPS, location, and speed); sleep hours (your total time in bed or asleep); and various brain functions through games prompted to test memory, executive capacities, emotions and moods.

 

This will soon become the paramount source of obtaining health data with a special emphasis on mental health issues.

 

Psychiatrists will be able to use these new technologies to identify a healthy person at risk by being able to analyze samplings of feelings, thoughts, and general behaviors as they occur in real time and in their real life.

 

Well, there are reliability issues, problem of missing data, retention/adherence abilities, and subjects neglecting to wear or charge their devices after a certain period of time.

 

The new learning algorithms of artificial intelligence technologies are able to integrate structured and unstructured data and should eventually be able to tackle these potential pitfalls.

 

Read the original article at https://www.miamiherald.com/living/health-fitness/article219558560.html

 

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Mobile tools to serve as first lines of defense for concerned consumers  #dermatology #mHealth - VisualDx officially launches Aysa

A lot of startups are starting to offer mobile tools to serve as “first lines of defense” for concerned consumers. A natural extension to patient education, they serve as the first line of diagnosis.

 

Dermatology is a particularly attractive area for this because of a national shortage of dermatologists in the United States.

 

Clinical decision support tool maker VisualDx officially launched Aysa, its first consumer-facing app, last month at Health 2.0 in San Francisco. The app allows users to upload pictures of skin lesions or rashes, enter some additional information about themselves and receive suggestions of what condition they might have and what actions to take next.

 

VisualDx stands out as a company that’s moving from provider-focused clinical decision support into the consumer world, which should lend it more credibility to its platform.

 

The app uses machine learning to identify skin conditions and make treatment suggestions.

 

services like this are crucial, even acknowledging their limitations, because people are already looking online for medical answers, so they might as well have the best ones possible.

 

CEO Dr. Art Papier in conversation with MobiHealthNews said 

“We know that everybody searches Google with their symptoms or they go to WebMD and use a symptom checker,” he said. “So the real question is how do you develop something that’s an educational symptom checker that’s safe? The art of this is to do a better job of educating so people know on a weekend, do I need to run to urgent care on a weekend, or can I get some better information that will help me make some decisions and then I’ll see the doctor later if necessary.”

 

read the original story at https://www.mobihealthnews.com/content/visualdx-launches-aysa-consumer-facing-dermatology-app

 

nrip's insight:

Tech solutions which offer at-home services like this are crucial, because people are already looking online for medical answers, so they might as well have the best ones possible. It definitely helps one get an insight as to what to search for rather than search the whole world wide web and drive up paranoia.

 

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