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Is Your Hospital Technology Killing Time And Productivity?

Is Your Hospital Technology Killing Time And Productivity? | Healthcare and Technology news | Scoop.it

For community hospitals with small operating margins, clinician time and productivity are at a premium.

Yet, today, clinicians still lose an average of 78 minutes per day to ineffective technology use.

 

If your hospital's information technology hurts time and productivity, here’s some more bad news: Your patient care and revenue suffer, too.

 

But, don’t despair. We’re here to help you spot troublesome IT symptoms in your organization, diagnose the problems and, most importantly, treat them.

Symptoms: Signs Of Poor IT

If your hospital’s clinicians are raising the hue and cry over your IT, you already know there’s trouble afoot.

But, to restore lost productivity (and profitability), you must take stock of your surroundings and see exactly where your technology and processes are falling short.

Here’s a short list of things to look for:

  1. Paper still dominates. Paper-intensive processes dictate most of your workflow after EHR implementation is complete.
  2. Manual processes abound. Users don’t trust your systems and resort to manual data entry where automation exists, costing you considerable time.
  3. Duplicate or missing data. Patient, medication and billing information is inaccurate or incomplete, leading to mistakes in patient care and/or billing delays.
  4. CPOE delegation is the norm. Physicians routinely delegate CPOE to nurses or other staff, slowing down the entry processes and increasing the risk of error.
  5. Workarounds are commonplace. In general, users are going around your technology and completing tasks based on preference, not protocol.

Do any of these situations sound familiar? If so, your hospital’s technology is likely creating productivity, care and revenue barriers.

Diagnosis: Who (Or What) Is To Blame?

In most cases, these issues can be traced back to people, processes and technology.

People. Frequently, the source of your IT woes isn’t the technology itself, but rather the people using it. If an anti-IT mentality pervades your hospital, the shiniest, most expensive HCIS in the world won’t deliver value. User workarounds are the most common culprit behind poor data and operational delays.

 

Processes. If your infrastructure and applications don’t align with required workflow, users will find other ways to complete their tasks. Implementing an EHR or any other HCIS for a single purpose – such as meeting compliance requirements or acquiring a new system version – inevitably leads to incongruity between your technology and workflow.

 

Technology. Sometimes, your technology is actually to blame. If your organization has implemented IT best practices and disciplines but still grapples with slow systems or downtime, your technology might not be performing. Certain vendors may be slow to provide critical updates and fixes, further exasperating the issue.

Treatment: Make Your Technology Valuable

It’s time to reclaim your hospital’s productivity, time and profitability.

First, implement effective hospital IT governance and make it the driver for any IT-related decision moving forward. Effective governance looks like this:

  • A leadership team committed to the use of IT as a care and business facilitator
  • Technology purchasing and implementation based on a long-term strategy that’s aligned with patient care and business value
  • Endorsement of best practices and user adoption at all levels of the organization

Working with an experienced, qualified healthcare technology consultant is the best way to create effective governance and align people, processes and technology with business goals. A non-biased third party can be useful for assessing your IT budget against business needs and making strategic recommendations.

Once you’ve established strong governance, align your technology and workflow by surveying day-to-day operations and eliminating obstacles wherever possible.

 

By following a physician as he or she works, you’ll learn volumes about the impediments, large and small, that impact productivity and time. Then, you can use IT to drive positive change, producing tangible benefits for clinicians and staff.

Triage Your IT Now

If you recognize red flags and think your hospital’s technology is directly impacting productivity and time, don’t wait until the consequences show up on your balance sheet. Take action today and help your clinicians deliver the best care possible.

Technical Dr. Inc.'s insight:
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What Your Healthcare Organization Needs to Know About Measure Selection and EHR Configuration 

What Your Healthcare Organization Needs to Know About Measure Selection and EHR Configuration  | Healthcare and Technology news | Scoop.it

Participation in pay-for-performance plans like MACRA’s Quality Payment Program (QPP) poses new challenges for resource-strapped healthcare organizations. Many provider sites lack the time and technical expertise needed to retool their EHR implementation to document new metrics under value-based reimbursement models like the Merit-based Incentive Payment System (MIPS).

 

Nonetheless, that is precisely what clinicians must do to deliver on quality reporting requirements. When using EHR documentation tools, many factors must be considered for a provider to get credit on having met clinical quality measures (CQMs). How that information gets stored in the EHR directly affects reporting. Many healthcare organizations are finding that customizing an EHR to recognize when a measure has been met—preferably in a manner that poses as few interruptions to patient engagement as possible—is easier said than done.

Overcoming EHR Limitations

Many outpatient and inpatient settings still struggle with common EHR data management headaches. As clinicians bring new quality measures into the EHR, those underlying data management issues can foil even the best-laid reporting plans.

Discrete Data Capture

The push to better document clinical quality is causing a transition in EHRs to focus more on structured or discrete data that is easier to trend over time. Unfortunately, many healthcare providers still receive patient data from healthcare affiliates via fax. Those faxed documents show up as attachments in the patient chart and are not fully integrated into the patient data file. If that information was sent via HL7 interface instead, details on the care rendered by that hospital or other healthcare entity would flow into the EHR as discreet data variables. For many providers today, capturing that information in a manner that makes it usable in reporting and analytics still requires timely, manual data entry.

Documentation and Data Consistency

Provider sites with multiple clinicians may also encounter issues related to the slightly different way that each EHR user documents care. MIPS and other quality programs require consistency and a high degree of specificity in clinical documentation. If a clinician does not get diagnosis specifics into the patient chart, that patient may not be included in the CQM calculation they need to be included in. Many clinicians are having to modify their documentation process during patient encounters so they and the staff can capture all the necessary information in the EHR.

Clinical documentation will have even bigger repercussions under the Cost component of MIPS, which is slated to be factored into performance scores in coming years. Take, for example, a patient that is in for the flu. That patient has a certain anticipated cost impact (the average Medicare spending per beneficiary), calculated based on past medical history and services rendered. If a patient goes to a physician and has the flu but also has diabetes, heart failure, and asthma, that flu patient is probably going to cost more to care for. If the physician only submits the flu diagnosis and fails to document patient co-morbidities then the healthcare organization will not get the same allowance under the MIPS Cost category and could be labeled as “higher cost” than a comparable provider encounter for a patient that required fewer resources to care for.

Clinicians, coders, and staff need to make a mental transition away from “we’re submitting claims” to “we’re submitting data” to better serve clinical reporting initiatives and patient care analysis.

Making Informed CQM Selections

Beyond adapting to new data management processes, clinicians reporting under value-based programs also have a great deal to learn as they layer in additional quality measures under MACRA. One of the biggest challenges clinicians and administrators face is selecting the best measures for their specific healthcare organization. With limited spare time on their hands, many healthcare teams are leaning on outside expertise to help them evaluate the implications of various measure selections.

Measures Without Benchmarks

Many quality measures under MACRA are carry-overs or “relics” from other reporting programs. For these CQMs, providers can look to prior performance averages to evaluate the likelihood of success should the healthcare organization elect to report on those measures. That data does not exist for some CQMs, which are referred to as “measures without benchmarks.” On measures that have no benchmark data available, providers will be limited to a maximum of three reporting points instead of the ten points available on measures with benchmarks established.

To further complicate things, details on the availability of some benchmark data will not be calculated until after the March 2018 QPP reporting deadline. Providers may wish to further diversify or report on additional measures that could help offset low point earnings on measures without benchmarks.

Topped Out Measures

Another CQM caveat that providers should be aware of relates to “topped out” measures. These relic measures from other reporting programs are very engrained in many healthcare settings. Medication reconciliation, for example, was a requirement under Meaningful Use. Widespread adoption and universally high compliance rates on that measure makes it more difficult for clinicians to out-perform peers. Achieving maximum points on such measures requires a perfect or near-perfect score.

Keep average performance thresholds in mind when evaluating CQM selections, not just the healthcare entity’s individual performance track record. Look at a broader set of measures to maximize MIPS score potential. Clinicians could earn more points by scoring 70 percent on a non-topped out measure than they would earn scoring 95 percent on a topped out measure. Some topped out measures will likely be eliminated in future years to help diversify CQMs, as was the case under Meaningful Use.

Understanding the intricacies of CQM selection and EHR data management will be vital to success under value-based payment programs. Healthcare administrators and clinicians who proactively work to better understand the impact of various measures and streamline EHR processes will be best positioned to maximize program incentives.

 

Does your organization have the resources it needs to successfully navigate MIPS

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5 digital trends to watch in 2015 | Healthcare IT News

5 digital trends to watch in 2015 | Healthcare IT News | Healthcare and Technology news | Scoop.it

The year 2014 goes down in history as a breakout year for digital healthcare, according to a recent report from StartUp Health, whose stated mission is to help 1,000 health startups reimagine and transform healthcare over the next 10 years.

StartUp Health's calculations show that some $6.5 billion was invested in digital health in 2014, a 125 percent increase over the $2.9 billion invested in 2013.

"Signs of a maturing market continue as investors place larger bets on fewer companies," according to the report, which lists the market's top deals and investors.

StartUp Health executives also reveal the five trends they will be watching closely in 2015:

  • Healthcare reform continues to spur innovation: As incentive structures change and new penalties come into effect in 2015, providers and payors look to entrepreneurs to create effective solutions. The unmet need is evidenced as big data and analytics ($1.5 billion); population health ($1.1 billion); and healthcare system navigation ($975 million) net the largest amounts of private funding in 2014.
  • Acceleration of chronic disease & aging population leads to increased consumerism: Rising costs continue to be the second largest catalyst for innovation in healthcare. Patients are not only encouraged, but enabled through mobile technology, to manage their health through preventive measures. Consumer health companies raised $880M in 2014.
  • Clinical decision support & personalized medicine gain traction: With the advent of the $1,000 genome, truly personalized medicine is in our reach. Genomic companies raised $632 million and diagnostics $962 million this year. This data, coupled with $624 million that went into clinical research companies will revolutionize the way that diseases are treated.
  • Convergence of technology in clinical settings: Mobile and wireless technology has permeated not only our daily lives, but those of professionals in clinical settings. Practice management tools allowing physicians to focus on treatment, rather than admin tasks, raised $783 million, while those focusing on improving workflows raised $681 million. Payor-related toolkits raised $699 million.
  • Innovation globalization: More than 7,500 startups around the world are developing new solutions in digital health, based on data from the StartUp Health Network. Even within the U.S., areas outside of the Bay Area, New York and Boston are seeing an uptick in the number of companies obtaining funding.


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What could a digital future look like in health care?

What could a digital future look like in health care? | Healthcare and Technology news | Scoop.it

It took me until 2010 to buy an iPhone and in just a few years, I’ve become so dependent on it, without fail, I will always make a U-turn to make sure it’s with me — my smartphone is essentially a new limb for me.

I know I’m not alone.


Most did not predict the rocket speed adoption and transformative power of modern smartphones when the iPhone launched in 2007. But, in just seven years, smartphone penetration in the U.S. is approximately 70 percent of the population, making it the fastest adopted technology in history.

While other industries have embraced mobile technologies, the health care industry is still mostly in the experimentation phase, with only a few players actually committing to mobile health solutions. That’s a missed opportunity given the vast potential for digital health to improve operational efficiencies and patient outcomes.

If we in health care don’t lead the charge with incorporating digital delivery into the current physical delivery care model within the next half-decade, outside pressures and disruptive companies will surely force this change on us.

We’ve seen recent evidence in other industries that technology can disrupt incumbents and position new players in the market at astonishing speed: retail being shaken up by Amazon, financial services with e-trade, ride sharing companies such as Uber with traditional taxi service and potentially private car ownership, and a host of others built on the principal of white glove, instant gratification service.

What could a digital future look like in health care?  It’s my job at Boston Children’s Hospital’s Innovation Acceleration Program to figure that out. But, also as a patient in the health care system here’s what I hope my future as “patient 3.0” will resemble: it will be a simplified, connected and digital experience seamlessly integrating my everyday life into health and care delivery.

1. My smartphone becomes my health care brain, connecting all the sensors in wearables on me or in my environment to analyze my health in real-time, providing me with insights when I want them. My doctor will be able to analyze my relevant data in the context of my personalized genomic data and years of electronic health record information will be visually displayed in less than a minute, powered by big data analytics. Our precious few minutes during the e-visit will be laser focused to target the right medication and treatment plan for me.

2. In my home, we will have a “robot” that is connected to all the smart devices like my fridge, coffee maker, front door, you name it. Everything in my home will be synced up to this digital ecosystem with Apple’s iBeacons or comparable technology. If I forget to take my medications my robot will tell me . Maybe even my walls or coffee maker will signal me if one of my biometric data points are out of range — and alert others if I’m unresponsive. I’m sure my prescription lenses will incorporate augmented reality to project relevant information on command about health care shopping choices.

3. I want my entire care team to know the relevant information and have it seamlessly integrated into my patient experience. I want technology to make this effortless. The last thing I want in my future patient 3.0 experience is technology creating a life of noise about every detail. The data should be contextual, relevant, and actionable. I want technology to be smart enough to adapt to my routine and notify me only when needed. See for example, Viv.

With the buzz of activity in the entrepreneurial community, the growing expectations of patients, untenable costs, and the interest of non-health care technology players like Facebook, Apple or Google, this future of health care could become a reality. And yet, my reality as a patient today? I’m lucky to have email exchanges with my doctor. What will it take to move beyond already outdated technologies?

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Why barriers between tech, healthcare are fading

Why barriers between tech, healthcare are fading | Healthcare and Technology news | Scoop.it

The barriers between healthcare and tech companies are disappearing as companies focused on greater efficiency disrupt the landscape, Bob Kocher and Bryan Roberts, investors at a venture capital firm Venrock, write at Harvard Business Review.

They point to the myriad ways in which technology is promoting services, while eliminating jobs not focused on providing care, including:

  • Digital insurance markets
  • Digital price transparency tools
  • Cloud services
  • Self-service mobile applications

Reducing healthcare administrative costs is projected to save up to $250 billion a year, they say.

To seize on the opportunities that software-as-a-service offers, they urge companies to:

  • Attack inefficiencies to generate quick customer return on investment
  • Focus on improvements for the network, in which one user enhances the product's value for others, including future users
  • Use software-enabled service models, rather than pure software-as-a-service, so that it helps patients adhere to high-quality, cost-effective care

"As each innovation wave generates more data, disruption-cycle times will shorten, thereby forcing all players in the healthcare ecosystem to address inefficiency as they compete on quality and value creation. Those who fail to act will be washed away by the tide that lifts all other boats to greater productivity," they write.

Funding for digital healthcare startups in the U.S. is expected to double to $6.5 billion by the end of 2017, FierceHealthIT previously reported. The market is moving toward what global consulting firm Oliver Wyman calls Health Market 2.0--a focuse on prediction and prevention rather than traditional cures.

The transition to personalized healthcare delivery and incentives for health information exchange will boost adoption of cloud services in healthcare, with the market expected to hit $3.5 billion by 2020, according to a Frost & Sullivan analysis.



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2015 Healthcare Technology Trends -

2015 Healthcare Technology Trends - | Healthcare and Technology news | Scoop.it

There is much debate whether the long awaited ACO reimbursement model introduced through the Affordable Care Act (ACA) will be successful in achieving the goals of health reform. I think critics are missing the point. ACO’s are just one of many emerging and evolving reimbursement models that are moving U.S. Healthcare away from a fee-for-service, pay-for-volume approach to value-based payment models.

Even if the ACO structure is not it, the horse is out of the barn. Bundled payments, gain sharing, managed care, readmission penalties and value-based purchasing are just variations on the same theme. The growth in healthcare is moving toward payment models based on cost-effective outcomes.

The transition to a value-based payment system is going to be rocky. U.S. healthcare is broken into silos of care that are locally optimized based on a dysfunctional fee-for-service payment model. Poor hand-offs between these silos result in failed transitions that undermine clinical outcomes and waste a lot of money. In addition, there are significant gaps in visibility of outcomes, making it difficult to know what is (and is not) an effective clinical intervention. For example, up to 30% of hospital readmissions are patients that are discharged from one hospital, only to be re-hospitalized at another.

There are two potential approaches to fix the fragmented care silos. One approach is to vertically integrate. Essentially, buy up the resources required to deliver integrated care, rip out fragmented disconnected technology and replace it with an integrated platform that spans most or all of the key components of the healthcare delivery system. Kaiser Permanente is often held up as an example of what can be accomplished through a fully integrated model. Their EHR offers the kind of end-to-end integrated platform that aspires to manage virtually all aspects of healthcare delivery.

When the integrated model works well, it can be a wonderful thing in terms of improved visibility and better efficiency. However, it is incredibly difficult to pull off. The path is littered with acquisitions gone bad as the pendulum swings between waves of consolidation only to be followed by divestiture. Culture clashes, incentive misalignment and complex replacement or integration of technology systems are just a few of the barriers to overcome.

For most of the market, vertical integration, followed by a rip and replace systems strategy is just not an option. The challenge for Healthcare Technology providers in 2015 and beyond is to provide a credible alternative that leverages integration of disparate systems, spanning healthcare providers that are not financially integrated. In fact, we need technology that can enable coopetition: a care delivery system that will enable intervention solutions that span the care continuum to address the needs of specific populations, while still protecting the ability for the same players to be competitors in other parts of their business.

I see three significant trends developing as the healthcare delivery system struggles to find a path to a virtual integration model that works.

  1. Community Coalitions
  2. Narrow Networks
  3. Evidence-based Models

Community Coalitions

Healthcare is local, with the majority of healthcare costs incurred within a few miles of patient’s home. Some of the early Pioneer ACOs tried to manage the vertical integration path without the connectivity infrastructure in place and have already thrown in the towel. Too many of their patients were receiving care out of network. Not only did they have difficulty in impacting outcomes for these patients, they were not even able to track where they went until after the bills came in.

However, in some city markets, health coalitions comprised of competing healthcare providers are taking shape. Most of these participating providers have already invested heavily in EHR systems to improve care delivery within their own walls. Now they also need healthcare IT infrastructure to coordinate transitions of care beyond their walls – efficiently sharing data with selected partners, reducing gaps in visibility and improving care coordination and care transitions. To compete against vertically integrated rivals, these care networks need to span the care continuum, including hospitals, post-acute care, physicians, out-patient clinics, social service agencies, pharmacists and other community-based organizations.

The catalyst for forming a community coalitions vary – perhaps visionary hospital system or post-acute care provider, a grant funded pilot or a CMS demonstration project. In each case, some critical mass is required to get the ball rolling to establish sufficient value for other coalition partners to join. In 2015, Healthcare IT infrastructure will allow coalition providers to collaborate with other providers across the care continuum, without sacrificing each provider’s distinct competitive interests.

Narrow Networks

Health systems and other referral sources are no longer content to refer their patients to any and all post-acute providers. There are new incentives to form narrow networks of post-acute care providers that are committed to high quality and can provide credible outcome data. Until recently, health systems thrived if they kept their volume of admissions high and their length of stay low. Hospital discharge planners and case managers primarily served as expeditors to ensure that beds turned over. However, under changing reimbursement, it is no longer sufficient to get patients in and out. Health systems also need to ensure the downstream providers are capable of providing needed care so patients won’t be re-hospitalized.

In the past, very few hospitals have tracked the destination of patients leaving their facility. Even fewer have meaningful outcome data to assess which post-acute care providers have the right expertise to effectively manage high risk patients. New Healthcare IT solutions will be needed to enable networked coalition partners across the care continuum to operate as effectively as vertically integrated systems. In 2015, I believe we will see the traditional relationship-based referral process steadily displaced by data-driven informed referrals that match the right patient with the right care setting at the right time.

Evidence-based Models

Because of the growing emphasis on oncomes, there is strong interest in evidence-based models that have shown efficacy through a peer-reviewed study. Popular evidence-based models related to transitions of care include BOOST, STARR, RED, CTI, TCM, INTERACT and Bridge. However, when these academic models are implemented in the real world, the results can be disappointing. There is seldom any feedback system to ensure that the process steps of the original evidence-based models are followed. Enthusiasm for each new approach fades as the high variability of subsequent implementations fails to measure up to the results produced by the carefully controlled clinical trial.

A technology infrastructure is needed to make sure that providers can distinguish between problems with patient targeting, process execution or the model design. In 2015, Healthcare IT will enable providers seeking to build on success of evidence-based models to measure the fidelity of program and provide the teams tasked with the implementation a feedback loop that will ensure continuous improvement.



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Institute for Critical Infrastructure Technology's curator insight, December 8, 2014 10:15 AM

for more news on critical infrastructure see the Institute for Critical Infrastructure Technology blog http://icitech.org/latest-critical-infrastructure-news-cybersecurity-healthcare/

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HIMSS18 – What, Where and How HealthIT can impact healthcare 

HIMSS18 – What, Where and How HealthIT can impact healthcare  | Healthcare and Technology news | Scoop.it

With the annual #HIMSS18 conference just a few weeks away, most of the industry’s attention is turning to matters relating to technology, cyber security and the regulations around HealthIT. We thought it would be fitting, therefore, to team up with the wonderful folks at @HIMSS for a tweetchat focused on technology and healthcare.

 

I am a fan of artificial intelligence, machine learning and virtual reality (even though I cannot physically use VR for more than 2 minutes at a time). However, the technology that I’m most intrigued by is 3D printing – specifically the 3D printing of organs and organic material.

 

First, there is the impact this technology could have on solving hunger and nutrition. Imagine if we could “print” healthy food in places where growing it is difficult or where shipping it is cost-prohibitive. Imagine also if we could print foods that are personalized to each person’s unique metabolism and dietary needs. The impact on public health would be significant and worldwide.

 

A long time ago I read a science fiction novel that talked about the advent of this type of technology: Gateway by Fredrick Pohl. The novel made frequent mention of something called CHON-food. Pohl imagined a world where CHON machines were able to replicate food by combining four key elements: carbon, hydrogen, oxygen and nitrogen. The advent of these machines helped to solve world hunger and ended many of the wars for water and food that that plagued the Earth. I hope we are at the start of CHON revolution.

 

Second, there is the impact of 3D printing on surgery and transplants. Researchers are very close to being able to print human skin using organic printers that can be used in reconstructive surgeries. The impact this technology could have on burn patients would be incredible. So too could the impact on patients that need a transplant. According to UNOS, every ten minutes someone is added to the national transplant waiting list and on average 20 people die each day while waiting for a transplant. With organ-printing technology these premature deaths might be prevented. Using tissue samples, organs can be printed to exactly match the patient’s physiology. Bonus: no more worries about organ rejection.

 

I’ve got my eye on 3D printing and over the next few years I expect it to have an impact beyond technologies like AI, machine learning and analytics. However, it’s going to take time for this technology to mature. In the meantime, there are certain areas of healthcare that can use a little boost TODAY.

 

Patient engagement and behavior change is an area of healthcare I hope #HealthIT will be able to help. Patients are the most untapped resource available to healthcare. Despite all the trackers, portals and video tutorials, health literacy remains extremely low. Some would argue that the widespread adoption of EHRs had even contributed to patient dis-engagement as doctors and nurses spend more time staring at screens rather than speaking to patients about their health. I see a golden opportunity in healthcare for patient engagement technology.

 

In the early 90s, the field of behavioral economics took shape. Richard Thaler, the University of Chicago professor who recently won the Nobel Memorial Prize in Economic Sciences, began publishing a series of papers that combined psychology and economics. His work led many to begin studying the ways that human behavior influences financial decisions. We need to apply those same theories to healthcare and design #HealthIT systems that nudge patients (and clinicians) into healthier behaviors.

I am incredibly excited about the future of healthcare. I am certain we are making progress towards a brighter day for patients, doctors, nurses, family caregivers and administrators. As I walk the #HIMSS18 exhibit hall I will be on the hunt for companies that share this outlook and whose products show clear signs of patient/provider design input.

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Computers Replacing Doctors, Innovation and the Quantified Self: An Interview with Atul Gawande | The Health Care Blog

Computers Replacing Doctors, Innovation and the Quantified Self: An Interview with Atul Gawande | The Health Care Blog | Healthcare and Technology news | Scoop.it

Atul Gawande is the preeminent physician-writer of this generation. His new book, Being Mortal, is a runaway bestseller, as have been his three prior books, Complications, Better, and The Checklist Manifesto.

One of the joys of my recent sabbatical in Boston was the opportunity to spend some time with Atul, getting to see what an inspirational leader and superb mentor he is, along with being a warm and menschy human being. In my continued series of interviews I conducted for The Digital Doctor, my forthcoming book on health IT, here are excerpts from my conversation with Atul Gawande on July 28, 2014 in Boston.

I began by asking him about his innovation incubator, Ariadne Labs, and how he decides which issues to focus on.

Gawande: Yeah, I’m in the innovation space, but in a funny way. Our goal is to create the most basic systems required for people to get marked improvements in the results of care. We’re working in surgery, childbirth, and end-of-life care.

The very first place we’ve gone is to non-technology innovations. Such as, what are the 19 critical things that have to happen when the patient comes in an operating room and goes under anesthesia? When the incision is made? Before the incision is made? Before the patient leaves the room? It’s like that early phase of the aviation world, when it was just a basic set of checklists.

In all of the cases, the most fundamental, most valuable, most critical innovations have nothing to do with technology. They have to do with asking some very simple, very basic questions that we never ask. Asking people who are near the end of life what their goals are. Or making sure that clinicians wash their hands.

Once we’ve recognized the recipe for really great performance, the second thing we’ve discovered is that our most important resource for improving the ability of teams to follow through on those really critical things is data. Information is our most valuable resource, yet we treat it like a byproduct. The systems we have – Epic and our other systems – are not particularly useful right now in helping us execute on these objectives. We’re having to build systems around those systems.

The third insight is that, for the most part, the issues have less to do with systems than with governance. The people who are buying these systems, installing these systems, and determining how they’re to be used… What are they responsible for? What are their objectives? We’re having to figure out how to get quality and outcomes higher on the list of priorities of everybody running health systems.

Our dumb checklist, or our incredibly sophisticated predictive analytics algorithm, or that incredibly expensive EHR system… none of those change that fundamental failure – the failure of governance. And none of them can, no matter how you design them.

Gawande raised the example of hospitalists. He asked me about my group at UCSF, which has – by focusing on performance improvement as our core mission – become a key innovation engine at our institution.

AG: I think your hospitalist example is really important. Over and over again, it’s the pattern I see: a powerful idea creates a momentum of its own. When you’ve shown that there’s an obvious better way to take care of people. It’s controversial, and hospitalists can be used in ways that destroy the original intent. I’m sure you think about this all the time.

But when it works, it forces the leadership change. Leadership didn’t create hospitalists. Hospitalists created leadership. I think that’s the way it happens.

The same kind of thing happened with anesthesia. People didn’t say, “Oh, we have to find a better way to manage the pain of patients, because surgery is causing horrible suffering.” Somebody came up with an idea, and demonstrated that you could relieve this problem. But it required incredible system change. You had to double the number of people working in operating rooms at a time when the United States had a lower GDP than China does today. “We’ve got a better way of doing surgery. Oh, and it will involve doubling the number of physicians you have providing the care?” Is that a great model? It was dismissed as totally non-viable, can’t work. But it didn’t matter. It was too important, and it became the driver of leadership change, rather than the other way around.

A similar thing happened with Paul Farmer. There were debates for a decade about whether you could treat HIV in poor patients. Oh they don’t have watches, they can’t take the drugs, they can’t do this, they can’t do that. Farmer is like, “Fuck it!” I am going to Haiti, and I’m going to do it in a little old clinic in the middle of nowhere. And no, they didn’t change a whole country … but they changed a paradigm.

I think that’s the cool thing, that it’s not the technology. It was the values and the core idea that demonstrated you could accomplish this, that got you there.

I asked Gawande a question I asked most of my interviewees: Will computers replace physicians?

AG: The variousness of the healthcare world is pretty extreme. When we look at the way that disease presents itself, we’re moving increasingly away from science. When it turned out that lung cancer is not one disease, but rather that it’s four or five different histologic subtypes, that made it more complicated. Now we know there are 47 – and the number is growing – genes that, in different combinations, govern the behavior of those cancers. Forty-seven genes, and then you look at the multiples of different ways that people have these genes. Now we learn that the epigenetics and the expression of those genes are incredibly dependent on the environment. Did they smoke, how did that affect the genes? Did they have any kind of industrial exposure? How old are they at the time that the cancer appears?

Our cells on our little Excel spreadsheets are getting smaller and smaller and smaller. We’re getting back to the world of the 18th century “art of medicine,” where everything is becoming an “eyeball test.” The danger is that it becomes actually increasingly data-free – that every single person becomes a case of one. That becomes impossible to learn from. Period.

Where we’re moving, I think, is towards saying, “I have a class of people. I’m going to try Process A on this class of people who have some combination of these different genes,” and stuff like that. And then, does that process lead to better outcomes? The processes will be things like, “I’m going to watch them for three months. Then if X happens, I’m going to do an operation. If Y happens, I’m going to give them chemotherapy.” That increasingly becomes the way we learn.

RW: In your work as a physician, do you think care is getting better or getting worse?

AG: I think it’s massively better.

RW: Why?

AG: It’s fundamentally because of values, more than technology. I think we’ve changed our values over time. That patient suffering matters. I remember as a surgical trainee, I was expected to inflict levels of pain that today are just not acceptable. In my first month as a resident, I went into an operation to do a rib removal on a young girl. I’d never done one before; I had a month of operating experience. A fellow was standing at the door in his scrubs, saying, “Yeah, yeah, yeah, cut there.” The attending is in another room. I didn’t know what the hell I was doing.

The culture was, even to suggest that was a problem, meant you were weak.

Gawande asked me how I perceived the training environment today – particularly the tension between the patient and the technology.

RW: The residents’ instinct about teamwork is much better than mine was. I mean, the idea of my caring about what the nurses thought just wasn’t on my radar screen. And the residents’ instinct to get back to the bedside – when they’re spending all their time on the computers, they feel this loss and I think they’re trying to reconnect with their patients. We’re trying to create structures to allow that to happen.

But it’s hard – the residents feel they’re caught up in this world where everything they need to know is on the computer screen. That’s creating angst in their day-to-day life. You go up to the floor of the medical service in my hospital, and there are no doctors there. They come, they see the patients, and then they escape to this tribal room where all 15 residents hang out together, each doing his or her computer work. That means that many of the informal interactions that used to occur between the docs and the nurses, or the docs and the patients and their families, have withered away.

AG: Everything that they’re measured on and that defines their success happens outside the patient’s room.

RW: Correct.

AG: There’s a difference in surgery training. Everything that you’re measured on and that matters happens in the operating room. Although the patient’s asleep, the residents are having to work on their people-to-people interactions. How do you handle yourself with the nurses? How do you handle yourself with the doctors? What are your skills? They’re trying to figure it out and navigate it. It’s often a complete mystery to the students, and for a long time to the residents, too.

But except in the most egregious cases where you really piss off a patient, their success – being labeled an A versus a B – relates to “how much do I really know this patient?” It’s not getting my to-do list done for the day. Yet getting through the to-do list is the dominant task.

And we’ve both contributed to discoveries that indicate that all these little steps on the to-do list matter. It’s become an endless list of details that really, really, really matter. Do you have the right combination of antibiotics? Is the head of the bed at 30 degrees? When I think about the to-do list that I had when I was an intern, and the to-do list that the residents have today – today’s is just massively longer.

I closed by asking Gawande about the concept of the Quantified Self – patients wearing sensors and accumulating all kinds of personal data. While he is generally supportive of the concept, he has a concern, one that echoes the central theme of Being Mortal.

AG: I worry that we could become tyrannized by a combination of experts and sensors that have no close relationship to our priorities. That’s why I just keep coming back to the values. We’re here to alleviating suffering. I think it’s about this deeper connection we all have to something important.


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How Healthcare Organizations Can Turn Big Data Into Smart Data

How Healthcare Organizations Can Turn Big Data Into Smart Data | Healthcare and Technology news | Scoop.it

Only a very small percentage of healthcare organizations today seem to be leading the way in healthcare data analytics, while the vast majority are very early in the business intelligence (BI)/analytics process, or haven’t even started. As a result, organizations seem to see big data as something that’s off in the very distant future; for most of them, anything outside of five years is almost nonexistent, says Shane Pilcher, vice president at the Bethel Park, Pa.-based Stoltenberg Consulting.

It is important to remember that big data is more than just a sea of information; it is an opportunity to find insights in new and emerging types of data and content.  So what are hospitals and healthcare organizations forgetting in their paths for eventual success with big data? According to Pilcher, the answer is “smart data.” In the below interview with HCI Assistant Editor Rajiv Leventhal, Pilcher talks about the difference between big data and smart data, strategies for collecting the right data, and advice for physicians in getting on board with the movement.

When you say “smart data,” what do you mean? How does smart data differ from big data?

The data that organizations are collecting today that they will be using for big data are going into this black hole (usually the data warehouse) somewhere. They are happy that they’re collecting it and preparing for when big data finally does come around to their organization, but if they aren’t careful and if they don’t monitor what they’re recording, the quality and quantity of the data when it’s to be used five years from now will not be sufficient enough. These organizations might think that they have five years of historical data to start their analytics, but in reality, the data is often not of the quality or quantity, or even the type, that is needed. That’s the smart data—that step that focuses on the type of data that they have, the volume of data, and also the validity of that data. You have to make sure that what you’re collecting is what you’re expecting.

Do healthcare organizations recognize this need?

Big data is a common theme with CIOs at healthcare organizations everywhere—they know it’s coming. However, there are CEOs at their hospitals who hear about “big data” at conferences and have no idea what it is, yet they will still come back and tell their CIOs that they “have to be doing big data.” And thus, it’s left in the lap of CIOs. But for the CIOs, they have Stage 2 of meaningful use and ICD-10 coming [for many providers, Stage 2 is here already], so they are not in the best place to be dealing with big data. So for the most part—except for about 5 percent of organizations out there, they tend to move it to sideline. It’s like looking at the side view mirror on your car and not seeing the message, “images are closer than they appear.” They see big data reflected, but it’s a lot closer than what they’re thinking. For the places that have limited resources and time, this is something that is being pushed to the side until they can get to it down the road.

How can organizations better ensure they are collecting the right quantity and quality of data?

First, you need to start developing your strategy now. Using the standard data models and approaches other industries are using doesn’t necessarily translate to healthcare IT. The amount of data, the data structure, and the data model is off the chart compared to even something as large as automotive manufacturing—the complexity isn’t even comparable. You have to develop as you go. The biggest thing I can suggest, as this industry is developing and our tools are growing, is to develop those peer networks with other healthcare leaders that are already further down the road than you. About 5 percent of healthcare organizations are right now in “stage two” of the data maturity model where they could start looking at predictive and prescriptive approaches to data. Those that are on the forefront of data analysis and intelligence are going to be critical to the rest of the industry following along. So learn from and use your peers.

And again, the quality of the data is critical. Organizations often think that they initiated the data collection, it’s implemented, and it’s working, so they turn to next project, thinking that when they’re ready, they will have it there in the warehouse. But then when it gets closer to the time to use the data, they don’t have the quantity that they thought they had. If you are collecting the wrong information or it’s incorrect, when you do your analysis, you will get wrong results and not even know it. Decisions could be devastating because your data was inaccurate leading to wrong analysis.

So you also need to assess the data on a regular basis constantly and ensure that what you think you’re collecting is actually what you’re getting. Then you can depend on the accuracy of that data when it’s time to start analyzing. Being able to analyze unstructured data for trends is very difficult, almost borderline impossible.  Yet, about 80 percent of hospitals expect to use unstructured data in their data warehouse. Turning that data into structured data, or finding a tool that can do that for you with accuracy, becomes a huge push. If organizations are not prepared for that, they are racing against time at the last minute.

You need to trust the accuracy of your data. You know that your electronic health record (EHR) is collecting certain data and dumping into the data warehouse. But is anything happening with that transfer of data that is changing it in any way? Is it remaining accurate? Was it accurate to begin with? I wouldn’t say there is an issue of incorrect data in EHRs, but people can’t 100 percent say, “Yes, it’s ready to be analyzed.”

What are some other challenges organizations are facing with big data?

Time and money are the two big ones, of course. Everyone has a limited amount of time, with more projects and initiatives than time to do them in. And dollars are tight for healthcare organizations, so the things that tend to be more in the future get less priority when it comes to budgeting than things needed for today.

But staffing is also a problem—having trained staffs who know how to analyze and know how to approach intelligence processes can be challenging. A 2012 CHIME CIO survey, from last September, found that 67 percent of healthcare CIOs were reporting IT staff shortages. The issue is that organizations either didn’t have enough staffers, or didn’t have anyone internally with that skill set. At the end of the day, almost all organizations are having problems making up a BI department.

What is your advice to helping physicians get on board with big data?

This is definitely adding to the challenge for physicians. In many cases, a lot of them can view EHRs as taking up more of their time and causing more of a workload rather than being more efficient. Often, that is accurate. EHRs do not save you time, not at the beginning. And that’s why physicians tend to be resistant; they understand the need for meaningful use dollars, and that has pushed them in the direction, even though they have been reluctant to go there in the past.

But the day we can take that information and turn it into a tool for them to better take care of their patients, creating better outcomes at a lower cost, will be a benefit to all of the efforts and work they have been doing. That is why hospitals that have implemented BI initiatives; rather than just focus on the financial, they have to focus on the patient care strategies and initiatives. Because it’s not until then do doctors see a purpose for their extra work and start to get on board.



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Docs critical to wearables success | Healthcare IT News

Docs critical to wearables success | Healthcare IT News | Healthcare and Technology news | Scoop.it

As the "race to the wrist" intensifies and more and more smartwatches and fitness bands enter the market, one has to wonder who stands a better chance for success: the device that caters to the user or one that caters to the doctor?

In all likelihood, the percentage of the population that is really, truly interested in collecting biometric data – the so-called quantified-selfers – isn't going to increase by any great margin. You'll always have the super-healthy fitness fanatics, but they won't outnumber the average consumer, no matter how stylish that watch or bracelet looks or how cool it displays your heart rate and blood sugar. 

There are sure to be wearables on display at the upcoming mHealth Summit 2014 in December and the data they collect is going to be much more valuable to the doctor, the nurse, the public health worker or the health and wellness advocate (whatever they'll be called in the future). After all, they're the ones who are going to know what to do with the information, and how to use it in such a way that it holds value to the consumer.

That's the plan, at least.

The one enduring fallacy in consumer-centered mHealth right now is that a device's success in the market comes down to the whims of the wearer. That's only half the battle. If that device isn't collecting information that a healthcare provider wants or needs, and if it isn't providing an easy means of connecting with that provider and sending that information, all it's going to end up being is a fancy – and expensive – watch or bracelet.


Too many of these devices flooding the market aren't taking that provider connection seriously. They're expecting the user to find a way to bring his or her doctor, nurse or health coach into the loop, and expecting the healthcare provider to be more than happy to go that extra mile to get this information. This is the workflow intrusion that we've all been warned about.

Most healthcare providers would agree – they don't want to be inundated with all that extra information coming in from wearables. If it's of value to the healthcare of the user – their patient – then yes, but it had better be coming into their EHR or in some fashion that is easy to see, work with and act on. It would then be up to them to turn that data around and, in so doing, make it of value to the user.

Take a look at the wearable devices on display or being discussed at this year's mHealth Summit. Chances are each one is closely tied to a clinician-friendly platform, or ready to prove their ease and value to clinicians.

That's the market they want to please.



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New dimensions for wearable tech | Healthcare IT News

New dimensions for wearable tech | Healthcare IT News | Healthcare and Technology news | Scoop.it

And here you thought Google Glass was the ultimate head-mounted game-changer for healthcare.

Another (admittedly smaller) Mountain View, Calif. tech company is hoping its own futuristic goggles will be just as transformative to healthcare as many expect Google Glass will be. Atheer Labs has developed what it calls "wearable augmented reality."

Leveraging Atheer’s three-dimensional immersive computing platform – offering wearers a way to interact with and manipulate data and devices that surround them – its 3D glasses, among many other uses, could be coming to clinical setting soon.

As Soulaiman Itani, founder and CEO of Atheer Labs, pointed out in press statement late this past year explaining the technology, there's a lot to think about when designing wearable computers. For example, "people cannot wear glasses that are more than 100 grams for longer than twenty minutes," he said.


"We were able to get all of the functionality and immersive experience in 75 grams," he said, "and we’re now putting it in the hands of the developers."

So for the past years or so the Atheer Developer Portal has offered access to the wearable device technology, and smart people have been working on applications that "augment the world around the user in 3D," enabling interaction via touch, voice or head motion.

Healthcare is in Atheer's sights. It's been showing off the technology at various healthcare conference, touting the ways it could change workflows offer new insights into smarter care delivery.

Sina Fateh, MD, is executive vice president at Atheer Labs, where he's in charge of optics development and the visual experience of the wearable technology. An ophthalmologist, Fateh has "expertise in binocular vision, smart glasses, visual image processing, and digital eyecare," according to Atheer officals.

Fateh tells Healthcare IT News the "augmented interactive reality" offered by these new 3D goggles can "enable clinicians to better serve patients in today’s hospitals by increasing efficiency, safety and privacy."

Efficiency gains could be in the offing too, he says. "Clinicians currently rely on desktop computers or tablets to access patients’ information. With the Atheer AiR platform, clinicians can now see information on a mobile heads-up display and have access to all this wherever they are, at the patients side, or on-the-go, and all hands-free.”

He says the glasses could also help in terms of safety and sanitation – "clinicians to access and navigate patient information with gesture control without the need to ever touch a physical surface" – and offer new dimensions to the patient record: "stereo see-through optics that allows clinicians to see medical records and images in high-resolution right in front of their eyes."

How are these 3D glasses different from, say, Google Glass, or other immersive reality technology such as Oculus Rift?

For one thing, this technology was specifically developed with input from "scientists, doctors, researchers" and other medical technologists, says Fateh.

"On a more technical level, Google Glass is a small, monocular display that can present only very limited information to the wearer, unlike Atheer’s binocular glasses which provide a large display area in front of you for a rich experience," he says.

"The interaction is also very different, with Google Glass relying on voice commands and a touchpad on the side, whereas the Atheer glasses are able to see your hands and fingers, enabling the user to naturally reach out and touch, tap and swipe the digital information they see displayed."

And while Oculus Rift is a virtual reality platform, "where the user is transported into a virtual simulated world and separated from reality," Atheer's is an "augmented reality platform that overlays relevant information onto the real world you see around you."

Notably, the AiR platform is fully compatible with the existing Android platform, he adds – enabling most Android applications to run directly.

In the next year Atheer will be "field testing" the technology in hospitals and other clinical settings, says Fateh: "We are eager to see our technology be put to use, and work with early adopters to identify other uses for it that will hugely impact the future of healthcare."

The company already has early users developing medical apps, and as early as 2015, these workflows "will be put into use in a selected number of medical facilities," he says. "It will probably take another year to get this technology into most modern medical facilities."



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