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Eliminate These Five Flaws to Improve Asset Utilization in Healthcare

Posted on October 4, 2017 I Written By

The following is a guest blog post by Mohan Giridharadas, Founder and CEO, LeanTaaS.

The passage of the Health Information Technology for Economic and Clinical Health (HITECH) Act accelerated the deployment of electronic health records (EHRs) across healthcare. The overwhelming focus was to capture every patient encounter and place it into an integrated system of records. Equipped with this massive database of patient data, health systems believed they could make exponential improvements to patient experiences and outcomes.

The pace of this migration resulted in some shortcuts being taken — the consequences of which are now apparent to discerning CFOs and senior leaders. Among these shortcuts was the use of resources and capacity as the basis of scheduling patients; this concept is used by hundreds of schedulers in every health system. While simple to grasp, the definition is mathematically flawed.

Not being able to offer a new patient an appointment for at least 10 days negatively impacts the patient experience. Likewise, exceeding capacity by scheduling too many appointments results in long wait times for patients, which also negatively impacts their experience. The troubling paradox is that the very asset creating long wait times and long lead times for appointments also happens to perform at ~50 percent utilization virtually every day. The impact of a mathematically flawed foundation results in alternating between overutilization (causing long patient wait times and/or long delays in securing an appointment) and under-utilization (a waste of expensive capital and human assets).

Here are five specific flaws in the mathematical foundation of health system scheduling:

1. A medical appointment is a stochastic — not deterministic — event.

Every health system has some version of this grid — assets across the top, times of the day for each day of the week along the side — on paper, in electronic format or on a whiteboard. The assets could be specific (e.g., the GE MRI machine or virtual MRI #1, #2, etc.). As an appointment gets confirmed, the appropriate range of time on the grid gets filled in to indicate that the slot has been reserved.

Your local racquet club uses this approach to reserve tennis courts for its members. It works beautifully because the length of a court reservation is precisely known (i.e., deterministic) to be exactly one hour in duration. Imagine the chaos if club rules were changed to allow players to hold their reservation even if they arrive late (up to 30 minutes late) and play until they were tired (up to a maximum of two hours). This would make the start and end times for a specific tennis appointment random (i.e., stochastic). Having a reservation would no longer mean you would actually get on the court at your scheduled time. This happens to patients every day across many parts of a health system. The only way to address the fact that a deterministic framework was used to schedule a stochastic event is to “reserve capacity” either in the form of a time buffer (i.e., pretend that each appointment is actually longer than necessary) or as an asset buffer (i.e., hold some assets in reserve).

2. The asset cannot be scheduled in isolation; a staff member has to complete the treatment.

Every appointment needs a nurse, provider or technician to complete the treatment. These staff members are scheduled independently and have highly variable workloads throughout the day. Having an asset that is available without estimating the probability of the appropriate staff member also being available at that exact time will invariably result in delays. Imagine if the tennis court required the club pro be present for the first 10 and last 10 minutes of every tennis appointment. The grid system wouldn’t work in that case either (unless the club was willing to have one tennis pro on the staff for every tennis court).

3. It requires an estimation of probabilities.

Medical appointments have a degree of randomness — no-shows, cancellations and last-minute add-ons are a fact of life, and some appointments run longer or shorter than expected. Every other scheduling system faced with such uncertainty incorporates the mathematics of probability theory. For example, airlines routinely overbook their flights; the exact number of overbooked seats sold depends on the route, the day and the flight. They usually get it right, and the cancellations and no-shows create enough room for the standby passengers. Occasionally, they get it wrong and more passengers hold tickets than the number of seats on the airplane. This results in the familiar process of finding volunteers willing to take a later flight in exchange for some sort of compensation. Nothing in the EHR or scheduling systems used by hospitals allows for this strategic use of probability theory to improve asset utilization.

4. Start time and duration are independent variables.

Continuing with the airplane analogy: As a line of planes work their way toward the runway for departure, the controller really doesn’t care about each flight’s duration. Her job is to get each plane safely off the ground with an appropriate gap between successive takeoffs. If one 8-hour flight were to be cancelled, the controller cannot suddenly decide to squeeze in eight 1-hour flights in its place. Yet, EHRs and scheduling systems have conflated start time and appointment duration into a single variable. Managers, department leaders and schedulers have been taught that if they discover a 4-hour opening in the “appointment grid” for any specific asset, they are free to schedule any of the following combinations:

  • One 4-hour appointment
  • Two 2-hour appointments
  • One 2-hour appointment and two 1-hour appointments in any order
  • One 3-hour appointment and one 1-hour appointment in either order
  • Four 1-hour appointments

These are absolutely not equivalent choices. Each has wildly different resource-loading implications for the staff, and each choice has a different probability profile of starting or ending on time. This explains why the perfectly laid out appointment grid at the start of each day almost never materializes as planned.

5. Setting appointments is more complicated than first-come, first-served.

Schedulers typically make appointments on a first-come, first-served basis. If a patient were scheduling an infusion treatment or MRI far in advance, the patient would likely hear “the calendar is pretty open on that day — what time would you like?” What seems like a patient-friendly gesture is actually mathematically incorrect. The appointment options for each future day should be a carefully orchestrated set of slots of varying durations that will result in the flattest load profile possible. In fact, blindly honoring patient appointment requests just “kicks the can down the road”; the scheduler has merely swapped the inconvenience of appointment time negotiation for excessive patient delays on the day of treatment. Instead, the scheduler should steer the patient to one of the recommended appointment slots based on the duration for that patient’s specific treatment.

In the mid-1980s, Sun Microsystems famously proclaimed that the “network is the computer.” The internet and cloud computing were not yet a thing, so most people could not grasp the concept of computers needing to be interconnected and that the computation would take place in the network and not on the workstation. In healthcare scheduling, “the duration is the resource” — the number of slots of a specific duration must be counted and allocated judiciously at various points throughout the day. Providers should carefully forecast the volume and the duration mix of patients they expect to serve for every asset on every day of the week. With that knowledge the provider will know, for example, that on Mondays, we need 10 1-hour treatments, 15 2-hour treatments and so on. Schedulers could then strategically decide to space appointments throughout the day (or cluster them in the morning or afternoon) by offering up two 1-hour slots at 7:10 a.m., one 1-hour slot at 7:40 a.m., etc. The allocation pattern matches the availability of the staff and the underlying asset to deliver the most level-loaded schedule for each day. In this construct, the duration is the resource being offered up to patients one at a time with the staff and asset availability as mathematical constraints to the equation (along with dozens of other operational constraints).

Health systems need to re-evaluate the mathematical foundation used to guide their day-to-day operations — and upon which the quality of the patient experience relies. All the macro forces in healthcare (more patients, older patients, higher incidence of chronic illnesses, lower reimbursements, push toward value-based care, tighter operating and capital budgets) indicate an urgent need to be able to do more with existing assets without upsetting patient flow. A strong mathematical foundation will enable a level of operational excellence to help health systems increase their effective capacity for treating more patients while simultaneously improving the overall flow and reducing the wait time.

About Mohan Giridharadas
Mohan Giridharadas is an accomplished expert in lean methodologies. During his 18-year career at McKinsey & Company (where he was a senior partner/director for six years), he co-created the lean service operations practice and ran the North American lean manufacturing and service operations practices and the Asia-Pacific operations practice. He has helped numerous Fortune 500 companies drive operational efficiency with lean practices. As founder and CEO of LeanTaaS, a Silicon Valley-based innovator of cloud-based solutions to healthcare’s biggest challenges, Mohan works closely with dozens of leading healthcare institutions including Stanford Health Care, UCHealth, NewYork-Presbyterian, Cleveland Clinic, MD Anderson and more. Mohan holds a B.Tech from IIT Bombay, MS in Computer Science from Georgia Institute of Technology and an MBA from Stanford GSB. He is on the faculty of Continuing Education at Stanford University and UC Berkeley Haas School of Business and has been named by Becker’s Hospital Review as one of the top entrepreneurs innovating in healthcare. For more information on LeanTaaS, please visit http://www.leantaas.com and follow the company on Twitter @LeanTaaS, Facebook at https://www.facebook.com/LeanTaaS and LinkedIn at https://www.linkedin.com/company/leantaas.

Will ACOs Face Tough Antitrust Scrutiny?

Posted on August 2, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

For some reason, I’ve always been interested in antitrust regulation, not just in the healthcare industry but across the board.

To me, there’s something fascinating about how federal agencies define markets, figure out what constitutes an unfair level of market dominance and decide which deals are out of bounds. For someone who’s not a lawyer, perhaps that’s a strange sort of geeking out to do, but there you have it.

Obviously, given how complex industry relationships are, healthcare relationships are fraught with antitrust issues to ponder. Lately, I’ve begun thinking about how antitrust regulators will look at large ACOs. And I’ve concluded that ACOs will be on the radar of the FTC and U.S. Department of Justice very soon, if they aren’t already.

On their face, ACOs try to dominate markets, so there’s plenty of potential for them to tip the scales too far in their favor for regulators to ignore. Their business model involves both vertical and horizontal integration, either of which could be seen as giving participants too much power.

Please take the following as a guide from an amateur who follows antitrust issues. Again, IANAL, but my understanding is as follows:

  • Vertical integration in healthcare glues together related entities that serve each other directly, such as health plans, hospitals, physician groups and skilled nursing facilities.
  • Horizontal integration connects mutually interested service providers, including competitors such as rival hospitals.

Even without being a legal whiz, it’s easy to understand why either of these ACO models might lead to (what the feds would see as) a machine that squeezes out uninvolved parties. The fact that these providers may share a single EMR could makes matters worse, as it makes the case that the parties can hoard data which binds patients to their network.

Regardless, it just makes sense that if a health plan builds an ACO network, cherry picking what it sees as the best providers, it’s unlikely that excluded providers will enjoy the same reimbursement health plan partners get. The excluded parties just won’t have as much clout.

Yes, it’s already the case that bigger providers may get either higher reimbursement or higher patient volume from insurers, but ACO business models could intensify the problem.

Meanwhile, if a bunch of competing hospitals or physician practices in a market decide to work together, it seems pretty unlikely that others could enter the market, expand their business or develop new service lines that compete with the ACO. Eventually, many patients would be forced to work with ACO providers. Their health plan will only pay for this market-dominant conglomerate.

Of course, these issues are probably being kicked around in legal circles. I’m equally confident that the ACOs, which can afford high-ticket legal advice, have looked at these concerns as well. But to my knowledge these questions aren’t popping up in the trade press, which suggests to me that they’re not a hot topic in non-legal circles.

Please note that I’m not taking a position here on whether antitrust regulation is fair or appropriate here. I’m just pointing out that if you’re part of an ACO, you may be more vulnerable to antitrust suits than you thought. Any entity which has the power to crush competition and set prices is a potential target.

A Hospital CIO Perspective on Precision Medicine

Posted on July 31, 2017 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

#Paid content sponsored by Intel.

In this video interview, I talk with David Chou, Vice President, Chief Information and Digital Officer with Kansas City, Missouri-based Children’s Mercy Hospital. In addition to his work at Children’s Mercy, he helps healthcare organizations transform themselves into digital enterprises.

Chou previously served as a healthcare technology advisor with law firm Balch & Bingham and Chief Information Officer with the University of Mississippi Medical Center. He also worked with the Cleveland Clinic to build a flagship hospital in Abu Dhabi, as well as working in for-profit healthcare organizations in California.

Precision Medicine and Genomic Medicine are important topics for every hospital CIO to understand. In my interview with David Chou, he provides the hospital CIO perspective on these topics and offers insights into what a hospital organization should be doing to take part in and be prepared for precision medicine and genomic medicine.

Here are the questions I asked him, if you’d like to skip to a specific topic in the video or check out the full video interview embedded below:

What are you doing in your organization when it comes to precision medicine and genomic medicine?

Hospitals Aren’t Getting Much ROI From RCM Technology

Posted on July 24, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

If your IT investments aren’t paying off, your revenue cycle management process is clunky and consumers are defaulting on their bills, you’re in a pretty rocky situation financially. Unfortunately, that’s just the position hospitals find themselves in lately, according to a new study.

The study, which was conducted by the Healthcare Financial Management Association and Navigant, surveyed 125 hospital health system chief financial officers and revenue cycle executives.

When they looked at the data, researchers saw that hospitals are being hit with a double whammy. On the one hand, the RCM systems hospitals have in place don’t seem to be cutting it, and on the other, the hospitals are struggling to collect from patients.

Nearly three out of four respondents said that their RCM technology budgets were increasing, with 32% reporting that they were increasing spending by 5% or more. Seventy-seven percent of hospitals with less than 100 beds and 78% of hospitals with 100 to 500 beds plan to increase such spending, the survey found.

The hospital leaders expect that technology investments will improve their RCM capabilities, with 79% considering business intelligence analytics, EHR-enabled workflow or reporting, revenue integrity, coding and physician/clinician documentation options.

Unfortunately, the software infrastructure underneath these apps isn’t performing as well as they’d like. Fifty-one percent of respondents said that their organizations had trouble keeping up with EHR upgrades, or weren’t getting the most out of functional, workflow and reporting improvements. Given these obstacles, which limit hospitals’ overall tech capabilities, these execs have little chance of seeing much ROI from RCM investments.

Not only that, CFOs and RCM leaders weren’t sure how much impact existing technology was having on their organizations. In fact, 41% said they didn’t have methods in place to track how effective their technology enhancements have been.

To address RCM issues, hospital leaders are looking beyond technology. Some said they were tightening up their revenue integrity process, which is designed to ensure that coding and charge capture processes work well and pricing for services is reasonable. Such programs are designed to support reliable financial reporting and efficient operations.

Forty-four percent of respondents said their organizations had established revenue integrity programs, and 22% said revenue integrity was a top RCM focus area for the coming year. Meanwhile, execs whose organizations already had revenue integrity programs in place said that the programs offered significant benefits, including increased net collections (68%), greater charge capture (61%) and reduced compliance risks (61%).

Still, even if a hospital has its RCM house in order, that’s far from the only revenue drain it’s likely to face. More than 90% of respondents think the steady increase in consumer responsibility for care will have an impact on their organizations, particularly rural hospital executives, the study found.

In effort to turn the tide, hospital financial execs are making it easier for consumers to pay their bills, with 93% of respondents offering an online payment portal and 63% rolling out cost-of-care estimation tools. But few hospitals are conducting sophisticated collections initiatives. Only 14% of respondents said they were using advanced modeling tools for predicting propensity to pay, researchers said.

One Hospital Faces Rebuild After Brutal Cyberattack

Posted on July 20, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Countless businesses were hit hard by the recent Petya ransomware attack, but few as hard as Princeton, West Virginia-based Princeton Community Hospital. After struggling with the aftermath of the Petya attack, the hospital had to rebuild its entire network and reinstall its core systems.

The Petya assault, which hit in late June, pounded large firms across the globe, including Nuance, Merck, advertiser WPP, Danish shipping and transport firm Maersk and legal firm DLA Piper.  The list of Petya victims also includes PCH, a 267-bed facility based in the southern part of the state.

After the attack, IT staffers first concluded that the hospital had emerged from the attack relatively unscathed. Hospital leaders noted that they are continuing to provide all inpatient care and services, as well as all other patient care services such as surgeries, therapeutics, diagnostics, lab and radiology, but was experiencing some delays in processing radiology information for non-emergent patients. Also, for a while the hospital diverted all non-emergency ambulance visits away from its emergency department.

However, within a few days executives found that its IT troubles weren’t over. “Our data appears secure, intact, and not hacked into; yet we are unable to access the data from the old devices in the network,” said the hospital in a post on Facebook.

To recover from the Petya attack, PCH decided that it had to install 53 new computers throughout the hospital offering clean access to its Meditech EMR system, as well as installing new hard drives on all devices throughout the system and building out an entirely new network.

When you consider how much time its IT staff must’ve logged bringing basic systems online, rebuilding computers and network infrastructure, it seems clear that the hospital took a major financial blow when Petya hit.

Not only that, I have little doubt that PCH faces doubts in the community about its security.  Few patients understand much, if anything, about cyberattacks, but they do want to feel that their hospital has things under control. Having to admit that your network has been compromised isn’t good for business, even if much bigger companies in and outside the healthcare business were brought to the knees by the same attack. It may not be fair, but that’s the way it is.

That being said, PCH seems to have done a good job keeping the community it serves aware what was going on after the Petya dust settled. It also made the almost certainly painful decision to rebuild key IT assets relatively quickly, which might not have been feasible for a bigger organization.

All told, it seems that PCH survived Petya successfully as any other business might have, and better than some. Let’s hope the pace of global cyberattacks doesn’t speed up further. While PCH might have rebounded successfully after Petya, there’s only so much any hospital can take.

The Fight For Patient Health Data Access Is Just Beginning

Posted on July 11, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

When some of us fight to give patients more access to their health records, we pitch everyone on the benefits it can offer — and act as though everyone feels the same way.  But as most of us know, in their heart of hearts, many healthcare industry groups aren’t exactly thrilled about sharing their clinical data.

I’ve seen this first hand, far too many times. As I noted in a previous column, some providers all but refuse to provide me with my health data, and others act like they’re doing me a big favor by deigning to share it. Yet others have put daunting processes in place for collecting your records or make you wait weeks or months for your data. Unfortunately, the truth, however inconvenient it may be, is that they have reasons to act this way.

Sure, in public, hospital execs argue for sharing data with both patients and other institutions. They all know that this can increase patient engagement and boost population health. But in private, they worry that sharing such data will encourage patients to go to other hospitals at will, and possibly arm their competitors in their battle for market share.

Medical groups have their own concerns. Physicians understand that putting data in patient’s hands can lead to better patient self-management, which can tangibly improve outcomes. That’s pretty important in an era when government and commercial payers are demanding measurably improved outcomes.

Still, though they might not admit it, doctors don’t want to deluge patients with a flood of data which could cause them to worry about inconsequential issues, or feel that data-equipped patients will challenge their judgment. And can we please admit that some simply don’t like ceding power over their domain?

Given all of this, I wasn’t surprised to read that several groups are working to improve patients’ access to their health data. Nor was it news to me that such groups are struggling (though it was interesting to hear what they’re doing to help).

MedCity News spoke to the cofounder of one such group, Share for Cures, which works to encourage patients to share their health data for medical research. The group also hopes to foster other forms of patient health data sharing.

Cofounder Jennifer King told MCN that patients face a technology barrier to accessing such records. For example, she notes, existing digital health tools may offer limited interoperability with other data sets, and patients may not be sure how to use portals. Her group is working to remove these obstacles, but “it’s still not easy,” King told a reporter.

Meanwhile, she notes, almost every hospital has implemented a customized medical record, which can often block data sharing even if the hospitals buy EMRs from the same vendor. Meanwhile, if patients have multiple doctors, at least a few will have EMRs that don’t play well with others, so sharing records between them may not be possible, King said.

To address such data sharing issues, King’s nonprofit has created a platform called SHARE, an acronym for System for Health and Research Data Exchange. SHARE lets users collect and aggregate health and wellness data from multiple sources, including physician EMRs, drug stores, mobile health apps and almost half the hospitals in the U.S.

Not only does SHARE make it easy for patients to access their own data, it’s also simple to share that data with medical research teams. This approach offers researchers an important set of benefits, notably the ability to be sure patients have consented to having their data used, King notes. “One of the ways around [HIPAA] is that patient are the true owners,” she said. “With direct patient authorization…it’s not a HIPAA issue because it’s not the doctor sharing it with someone else. It’s the patient sharing it.”

Unfortunately (and this is me talking again) the platform faces the same challenges as any other data sharing initiative.

In this case, the problem is that like other interoperability solutions, SHARE can only amass data that providers are actually able to share, and that leaves a lot of them out of the picture. In other words, it can’t do much to solve the underlying problem. Another major issue is that if patients are reluctant to use even something as simplified as a portal, they’re not to likely to use SHARE either.

I’m all in favor of pushing for greater patient data access, for personal as well as professional reasons. And I’m glad to hear that there are groups springing up to address the problem, which is obviously pretty substantial. I suspect, though, that this is just the beginning of the fight for patient data access.

Until someone comes up with a solution that makes it easy and comfortable for providers to share data, while diffusing their competitive concerns, it’s just going to be more of the same old, same old. I’m not going to hold my breath waiting for that to happen.

Scenarios for Health Care Reform (Part 2 of 2)

Posted on May 18, 2017 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The first part of this article suggested two scenarios that could promote health care reform. We’ll finish off the scenarios in this part of the article.

Capitalism Disrupts Health Care

In the third scenario, reform is stimulated by an intrepid data science firm that takes on health care with greater success than most of its predecessors. After assembling an impressive analytics toolkit from open source software components–thus simplifying licensing–it approaches health care providers and offers them a deal they can’t refuse: analytics demonstrated to save them money and support their growth, all delivered for free. The data science firm asks in return only that they let it use deidentified data from their patients and practices to build an enhanced service that it will offer paying customers.

Some health care providers balk at the requirement to share data, but their legal and marketing teams explain that they have been doing it for years already with companies whose motives are less commendable. Increasingly, the providers are won over. The analytics service appeals particularly to small, rural, and safety-net providers. Hammered by payment cuts and growing needs among their populations, they are on the edge of going out of business and grasp the service as their last chance to stay in the black.

Participating in the program requires the extraction of data from electronic health records, and some EHR vendors try to stand in the way in order to protect their own monopoly on the data. Some even point to clauses in their licenses that prohibit the sharing. But they get a rude message in return: so valuable are the analytics that the providers are ready to jettison the vendors in a minute. The vendors ultimately go along and even compete on the basis of their ability to connect to the analytics.

Once stability and survival are established, the providers can use the analytics for more and more sophisticated benefits. Unlike the inadequate quality measures currently in use, the analytics provide a robust framework for assessing risk, stratifying populations, and determining how much a provider should be rewarded for treating each patient. Fee-for-outcome becomes standard.

Providers make deals to sign up patients for long-term relationships. Unlike the weak Medicare ACO model, which punishes a provider for things their patients do outside their relationship, the emerging system requires a commitment from the patient to stick with a provider. However, if the patient can demonstrate that she was neglected or failed to receive standard of care, she can switch to another provider and even require the misbehaving provider to cover costs. To hold up their end of this deal, providers find it necessary to reveal their practices and prices. Physician organizations develop quality-measurement platforms such as the recent PRIME registry in family medicine. A race to the top ensues.

What If Nothing Changes?

I’ll finish this upbeat article with a fourth scenario in which we muddle along as we have for years.

The ONC and Centers for Medicare & Medicaid Services continue to swat at waste in the health care system by pushing accountable care. But their ratings penalize safety-net providers, and payments fail to correlate with costs as hoped.

Fee-for-outcome flounders, so health care costs continue to rise to intolerable levels. Already, in Massachusetts, the US state that leads in universal health coverage, 40% of the state budget goes to Medicaid, where likely federal cuts will make it impossible to keep up coverage. Many other states and countries are witnessing the same pattern of rising costs.

The same pressures ride like a tidal wave through the rest of the health care system. Private insurers continue to withdraw from markets or lose money by staying. So either explicitly or through complex and inscrutable regulatory changes, the government allows insurers to cut sick people from their rolls and raise the cost burdens on patients and their employers. As patient rolls shrink, more hospitals close. Political rancor grows as the public watches employer money go into their health insurance instead of wages, and more of their own stagnant incomes go to health care costs, and government budgets tied up in health care instead of education and other social benefits.

Chronic diseases creep through the population, mocking crippled efforts at public health. Rampant obesity among children leads to more and earlier diabetes. Dementia also rises as the population ages, and climate change scatters its effects across all demographics.

Furthermore, when patients realize the costs they must take on to ask for health care, they delay doctor visits until their symptoms are unbearable. More people become disabled or perish, with negative impacts that spread through the economy. Output decline and more families become trapped in poverty. Self-medication for pain and mental illness becomes more popular, with predictable impacts on the opiate addiction crisis. Even our security is affected: the military finds it hard to recruit find healthy soldiers, and our foreign policy depends increasingly on drone strikes that kill civilians and inflame negative attitudes toward the US.

I think that, after considering this scenario, most of us would prefer one of the previous three I laid out in this article. If health care continues to be a major political issue for the next election, experts should try to direct discussion away from the current unproductive rhetoric toward advocacy for solutions. Some who read this article will hopefully feel impelled to apply themselves to one of the positive scenarios and bring it to fruition.

Scenarios for Health Care Reform (Part 1 of 2)

Posted on May 16, 2017 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

All reformers in health care know what the field needs to do; I laid out four years ago the consensus about patient-supplied data, widespread analytics, mHealth, and transparency. Our frustration comes in when trying to crack the current hide-bound system open and create change. Recent interventions by US Republicans to repeal the Affordable Care Act, whatever their effects on costs and insurance coverage, offer no promise to affect workflows or treatment. So this article suggests three potential scenarios where reform could succeed, along with a vision of what will happen if none of them take hold.

Patients Forge Their Own Way Forward

In the first scenario, a tiny group of selfer-trackers, athletes, and empowered patients start a movement that ultimately wins over hundreds of millions of individuals.

These scattered enthusiasts, driven to overcome debilitating health problems or achieve extraordinary athletic feats, start to pursue self-tracking with fanaticism. Consumer or medical-grade devices provide them with ongoing data about their progress, and an open source platform such as HIE of One gives them a personal health record (PHR).

They also take charge of their interactions with the health care system. They find that most primary care providers aren’t interested in the data and concerns they bring, or don’t have time to process those data and concerns in the depth they need, or don’t know how to. Therefore, while preserving standard relationships with primary care providers and specialists where appropriate, the self-trackers seek out doctors and other providers to provide consultation about their personal health programs. A small number of providers recognize an opportunity here and set up practices around these consultations. The interactions look quite different from standard doctor visits. The customers, instead of just submitting themselves to examination and gathering advice, steer the conversation and set the goals.

Power relationships between doctors and customers also start to change. Although traditional patients can (and often do) walk away and effectively boycott a practice with which they’re not comfortable, the new customers use this power to set the agenda and to sort out the health care providers they find beneficial.

The turning point probably comes when someone–probabaly a research facility, because it puts customer needs above business models–invents a cheap, comfortable, and easy-to-use device that meets the basic needs for monitoring and transmitting vital signs. It may rest on the waist or some other place where it can be hidden, so that there is no stigma to wearing it constantly and no reason to reject its use on fashion grounds. A beneficent foundation invests several million dollars to make the device available to schoolchildren or some other needy population, and suddenly the community of empowered patients leaps from a miniscule pool to a mainstream phenomenon.

Researchers join the community in search of subjects for their experiments, and patients offer data to the researchers in the hope of speeding up cures. At all times, the data is under control of the subjects, who help to direct research based on their needs. Analytics start to turn up findings that inform clinical decision support.

I haven’t mentioned the collection of genetic information so far, because it requires more expensive processes, presents numerous privacy risks, and isn’t usually useful–normally it tells you that you have something like a 2% risk of getting a disease instead of the general population’s 1% risk. But where genetic testing is useful, it can definitely fit into this system.

Ultimately, the market for consultants that started out tiny becomes the dominant model for delivering health care. Specialists and hospitals are brought in only when their specific contributions are needed. The savings that result bring down insurance costs for everyone. And chronic disease goes way down as people get quick feedback on their lifestyle choices.

Government Puts Its Foot Down

After a decade of cajoling health care providers to share data and adopt a fee-for-outcome model, only to witness progress at a snail’s pace, the federal government decides to try a totally different tack in this second scenario. As part of the Precision Medicine initiative (which originally planned to sign up one million volunteers), and leveraging the ever-growing database of Medicare data, the Office of the National Coordinator sets up a consortium and runs analytics on top of its data to be shared with all legitimate researchers. The government also promises to share the benefits of the analytics with anyone in the world who adds their data to the database.

The goals of the analytics are multi-faceted, combining fraud checks, a search for cures, and everyday recommendations about improving interventions to save money and treat patients earlier in the disease cycle. The notorious 17-year gap between research findings and widespread implementation shrinks radically. Now, best practices are available to any patient who chooses to participate.

As with the personal health records in the previous scenario, the government database in this scenario creates a research platform of unprecedented size, both in the number of records and the variety of participating researchers.

To further expand the power of the analytics, the government demands exponentially greater transparency not just in medical settings but in all things that make us sick: the food we eat (reversing the rulings that protect manufacturers and restaurants from revealing what they’re putting in our bodies), the air and water that surrounds us, the effects of climate change (a major public health issue, spreading scourges such as mosquito-borne diseases and heat exhaustion), disparities in food and exercise options among neighborhoods, and more. Public awareness leads to improvements in health that lagged for decades.

In the next section of this article, I’ll present a third scenario that achieves reform from a different angle.

Nursing Informatics Pros Seeing Growing Salaries, Opportunities

Posted on March 24, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Here’s something I missed in the explosion of news around HIMSS17. According to a recent study released late last month by the organization, nurse informaticists are largely well-paid and satisfied with their jobs.

According to the American Nurses Association, nurse informaticists have broad responsibilities, including integrating data and supporting provider and patient decision-making. The job description continues evolve with health IT trends, and may vary from one institution to the other,but their work usually involves a mix of nursing science, health records management and information technology solutions.

As the job description has solidified, nursing informatics has begun to become a well-liked specialty. Eighty percent of respondents to the HIMSS study, the 2017 Nursing Informatics Workforce Survey, reported being satisfied or highly satisfied with their careers, HIMSS found. This may be in part due to their pay, with almost half respondents telling researchers that they had a base salary of over $100,000. Not only that, 34 percent said they also got a bonus.

Meanwhile, highly-trained nursing informaticists did better still. Those who had gotten a nursing informatics certification or post-graduate degree took home higher salaries than those who hadn’t. With over half of those who had additional education made more than $100,000 a year, as opposed to 37 percent of those who didn’t, the trade group said.

In addition, nurse informaticists are advancing themselves to a striking degree, with over half of respondents having a post-graduate degree, often in informatics or nursing informatics, HIMSS reported. (Of this group, 57 percent had completed post-graduate degrees, and 29 percent had a master’s degree or PhD in informatics.)

Meanwhile, 41 percent of nurses are involved in a formal informatics program, and almost half had a certification. These efforts seem be paying off, with two-fifths of respondents reporting that they moved into a new position with more responsibility after they got certified.

As nurse informaticists grow, they are accumulating deeper levels of experience.  All told, 31 percent of respondents had more than 10 years of informatics experience, 36 percent had five to 10 years of experience – dwarfing the 24 percent that had just one to four years. One-third of respondents said they’d been in their current position for more than five years, and a majority of respondents reported having seven years plus of related experience.

While these nurses seem like they enjoy their careers, they are still facing some bureaucracy-related problems.  For example, when asked about their concerns, they rated a lack of administrative and staffing resources as the top barrier to their success.

Ongoing shifts in their reporting roles may also be leading to some dissatisfaction. While most respondents told HIMSS that they reported to the information systems or tech department of their organization, a growing number report to administrative or corporate headquarters. (On the other hand, one-third said that their organization has a senior nursing informatics executive or CNIO, which one would hope proves to offer extra support.)

Though the HIMSS summary doesn’t say so explicitly, it seems very likely that demand for nurse informaticists is outstripping supply, given the substantial salaries these experts can command. If your organization needs to recruit such a person, be prepared for some tough competition.

EMR Information Management Tops List Of Patient Threats

Posted on March 23, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

A patient safety organization has reached a conclusion which should be sobering for healthcare IT shops across the US. The ECRI Institute , a respected healthcare research organization, cited three critical health IT concerns in its list of the top 10 patient safety concerns for 2017.

ECRI has been gathering data on healthcare events and concerns since 2009, when it launched a patient safety organization. Since that time, ECRI and its partner PSOs have collected more than 1.5 million event reports, which form the basis for the list. (In other words, the list isn’t based on speculation or broad value judgments.)

In a move that won’t surprise you much, ECRI cited information management in EMRs as the top patient safety concern on its list.

To address this issue, the group suggests that healthcare organizations create cross-functional teams bringing varied perspectives to the table. This means integrating HIM professionals, IT experts and clinical engineers into patient safety, quality and risk management programs. ECRI also recommends that these organizations see that users understand EMRs, report and investigate concerns and leverage EMRs for patient safety programs.

Implementation and use of clinical decision support tools came in at third on the list, in part because the potential for patient harm is high if CDS workflows are flawed, the report says.

If healthcare organizations want to avoid these problems, they need to give a multidisciplinary team oversight of the CDS, train end users in its use and give them access to support, the safety group says. ECRI also recommends that organizations monitor the appropriateness of CDS alerts, evaluating the impact on workflow and reviewing staff responses.

Test result reporting and follow-up was ranked fourth in the list of safety issues, driven by the fact that the complexity of the process can lead to distraction and problems with follow-up.

The report recommends that healthcare organizations respond by analyzing their test reporting systems and monitor their effectiveness in triggering appropriate follow-ups. It also suggests implementing policies and procedures that make it clear who is accountable for acting on test results, encouraging two-way conversations between healthcare professionals and those involved in diagnostic testing and teaching patients how to address test information.

Patient identification issues occupied the sixth position on the list, with the discussion noting that about 9 percent of misidentification problems lead to patient injury.

Healthcare leaders should prioritize this issue, engaging clinical and nonclinical staffers in identifying barriers to safe identification processes, the ECRI report concludes. It notes that if a provider has redundant patient identification processes in place, this can increase the probability that identification problems will occur. Also, it recommends that organizations standardize technologies like electronic displays and patient identification bands, and that providers consider bar-code systems and other patient identification helps.

In addition to health IT problems, ECRI identified several clinical and process issues, including unrecognized patient deterioration, problems with managing antimicrobial drugs, opioid administration and monitoring in acute care, behavioral health issues in non-behavioral-health settings, management of new oral anticoagulants and inadequate organization systems or processes to improve safety and quality.

But clearly, resolving nagging health IT issues will be central to improving patient care. Let’s make this the year that we push past all of them!