7- DATA, DATA,& MORE DATA IN HEALTHCARE by PHARMAGEEK

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--

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.

The face of medical care is rapidly changing thanks to major advancements in the capture, proliferation, and analysis of medical data. Technologies like the electronic health records (EHRs) and personal health records (PHRs) are drastically improving the way data is aggregated and shared.

Now the hope is that big data analytics will help to make sense of seemingly endless streams of medical information.

As many doctors are painfully aware, outcome-oriented care is no longer a buzzword but a reality. The Center for Medicare and Medicaid Services has started to implement a program where payments are based on the ability of providers to meet key National Quality Strategy Domains (e.g. care criteria). Public payers are testing this new methodology, and private payers are expected to soon follow.

These big data analytics applications can also be relevant for the FDA, which may want to see how drugs perform in a non-test environment to ensure the appropriate patient populations are receiving the drug. I also expect pharmaceutical companies to actively scour this data to track drug efficacy post-release or identify markets that could “benefit” from increased penetration.

I am eager to see how the data evolution improves outcomes for doctors and patients.

more at http://venturebeat.com/2014/10/16/how-big-data-is-beginning-to-change-how-medicine-works/ ;

New software could give people greater control over how their personal health information is shared between doctors and medical institutions—provided that enough health providers decide to use the system.

Today a patient’s data typically stays within a hospital group or doctor’s practice. If you get care elsewhere you are essentially a blank slate unless a special request for your data is made, in which case the entire record becomes accessible. But many patients may not want their entire medical history to be accessible by everyone they see, so there is pressure to develop tools that can be used to limit access. One tricky issue is that redacting details of a diagnosis may not remove all the clues as to that condition, such as prescribed drugs or lab tests.

A new tool developed by computer scientists at the University of Illinois can figure out which parts of a record may inadvertently reveal aspects of a patient’s medical history. The idea is that as data-sharing proposals advance, the patient would decide what parts of his or her record to keep private. A clinician would get advice from the technology on how to amend the record to ensure that this occurs.

The software bases its recommendations on a machine-learning analysis of many other medical records. This reveals what details could be associated with things like mental health episodes, past drug abuse, or a diagnosis of a sexually transmitted disease when the record is shared with another hospital or doctor. The tool could eventually automatically remove those additional details to keep that information confidential.

Incorporating persuasive design concepts into primary care electronic health records (EHRs) increased same-day data entry by 10 percent per physician, demonstrating the potential for persuasive design to change data entry behavior, a study published in JMIR Human Factors revealed.

Persuasive design is a way of developing technology to influence behavior by leveraging social processes. Healthcare stakeholders have primarily focused on using persuasive design in consumer-facing mobile apps to improve outcomes, but there are few examples of using persuasive design to influence clinician behavior.

In primary care settings, providers often face barriers to entering data into EHRs in a timely manner.  Data entry tasks often take a long time, and users may feel as if completing documentation is a lower priority than seeing patients or finishing other tasks.

“Persuasive design is a viable approach for designing and encouraging behavior change and could support effective data capture in the field of medical informatics. There may be opportunities to continue improving this approach, and further work is required to perfect and test additional designs,” the team concluded.

read the original unedited article at https://healthitanalytics.com/news/persuasive-ehr-workflow-design-increased-same-day-data-entry-by-10

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 

The face of medical care is rapidly changing thanks to major advancements in the capture, proliferation, and analysis of medical data. Technologies like the electronic health records (EHRs) and personal health records (PHRs) are drastically improving the way data is aggregated and shared.

Now the hope is that big data analytics will help to make sense of seemingly endless streams of medical information.

As many doctors are painfully aware, outcome-oriented care is no longer a buzzword but a reality. The Center for Medicare and Medicaid Services has started to implement a program where payments are based on the ability of providers to meet key National Quality Strategy Domains (e.g. care criteria). Public payers are testing this new methodology, and private payers are expected to soon follow.

These big data analytics applications can also be relevant for the FDA, which may want to see how drugs perform in a non-test environment to ensure the appropriate patient populations are receiving the drug. I also expect pharmaceutical companies to actively scour this data to track drug efficacy post-release or identify markets that could “benefit” from increased penetration.

I am eager to see how the data evolution improves outcomes for doctors and patients.

After decades as a technological laggard, medicine has entered its data age. Mobile technologies, sensors, genome sequencing, and advances in analytic software now make it possible to capture vast amounts of information about our individual makeup and the environment around us. The sum of this information could transform medicine, turning a field aimed at treating the average patient into one that’s customized to each person while shifting more control and responsibility from doctors to patients.

The question is: can big data make health care better?

“There is a lot of data being gathered. That’s not enough,” says Ed Martin, interim director of the Information Services Unit at the University of California San Francisco School of Medicine. “It’s really about coming up with applications that make data actionable.”

The business opportunity in making sense of that data—potentially $300 billion to $450 billion a year, according to consultants McKinsey & Company—is driving well-established companies like Apple, Qualcomm, and IBM to invest in technologies from data-capturing smartphone apps to billion-dollar analytical systems. It’s feeding the rising enthusiasm for startups as well.

Venture capital firms like Greylock Partners and Kleiner Perkins Caufield & Byers, as well as the corporate venture funds of Google, Samsung, Merck, and others, have invested more than $3 billion in health-care information technology since the beginning of 2013—a rapid acceleration from previous years, according to data from Mercom Capital Group. 

  more at http://www.technologyreview.com/news/529011/can-technology-fix-medicine/ ;