Data Demands Still Tax Physicians | Healthcare IT Today

Though most medical groups have invested heavily in health IT, particularly EHRs, most are still struggling to manage the data necessary for running the practice.

The federal government incentivized the adoption of the EHR by giving a bonus to practices which purchased EHRs. while at the same time imposing a perverse penalty for those who did not do so.  A comopressed time frame forced practices to purchase inadequate, poorly designed software.  The feds also imposed requirement which they called meaningful use (MU). Meaningful use (MU), in a health information technology (HIT) context, defines minimum U.S. government standards for using electronic health records (EHR) and for exchanging patient clinical data between healthcare providers, between healthcare providers and insurers, and between healthcare providers and patients.

Author

Anne Zieger

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 considerable investment burden was placed on vendors in lieu of prioritizing an adequate user interface. In fact most doctors remain very dissatisfied with lack of user efficiency leading to lower productivity of their practices.  A few specialty providers have a niche of customized software that is properly designed .

Meaningful Use stages

• Stage 1. Promotes basic EHR adoption and data gathering.
• Stage 2. Emphasizes care coordination and exchange of patient information.
• Stage 3. Improves healthcare outcomes.

Select the links below to learn more about the measures for Stage 1/Modified Stage 2 , Stage 2 , and Electronic Clinical Quality Measures (eCQMs).

• STAGE 1/MODIFIED STAGE 2 MEASURES »
• STAGE 2 MEASURES »
• ECQMS »

Though most medical groups have invested heavily in health IT, particularly EHRs, most are still struggling to manage the data necessary for running the practice. Sure, Meaningful Use incentives helped them get the technology in the door, squeezing the best performance out of it calls for institutional and financial resources that many can’t afford.    

As a result. new survey results underscoring the difficulty practices face in managing data came as little surprise to me.  The survey, which was sponsored by Geneia found that 89% of responding physicians felt that the “business and regulation of healthcare” has had a negative effect on the practice of medicine.   Fifty-two percent of those responding were ambivalent about the impact of EHRs in their workplace. This included 21% who had a positive view and 22% a negative view of the role of EHRs.  In addition, while 96% of respondents said that they believe that EHRs should integrate better with technology systems used by the office and insurance providers, 57% said that their EHRs don’t integrate these systems. Meanwhile, more than two-thirds of respondents said they didn’t have the staff and resources needed to analyze and use EHR data efficiently.

Seventy-nine percent of respondents said they’d like to use an integrated EHR analytics tool to access predictive and reporting on existing data. Also, many said they’d like to have population health tools available to identify high-risk patients, find patients who need proactive screenings or monitoring and stratify patients into low-, rising- and high-risk categories.     

Also, 68% said they need advanced analytics tools to be successful under value-based care arrangements, with 64% of population health users reporting that they think they such tools can help them assess patient history and needs more efficiently.

As things stand, however, these physicians don’t seem to be getting enough IT bang for their buck. Virtually all (96%) reported that the amount of time they spend on data input and reporting has grown over the last 10 years, and they’re having trouble keeping up with the pace. Also, 86% agreed that “the heightened demand for data reporting to support quality metrics and the business side of healthcare has diminished my joy in practicing medicine.”

Demands Still Tax Physicians | Healthcare IT 

The End Well Project: Reimaginging Dying, with Dr. Shoshana Ungerleider ...

We will all face death. Few are prepared to think about how or where they will die.. One should not be passive in preparing for death. I am not referring to financial or legal preparation such as wills, estates, burial plots or other things.

Watch this video, and contemplate the inevitable.  Some of us will go out kicking and screaming. You will often hear family and friends tellling us what a 'fighter'  he/she was, how she never gave up. Others will say he accepted his end, having accomplished many of his own important goals.

The talk was given at Exponential University 2017, by Shoshana Ungerleider, MD



Do you want to die in your own bed, in a nursing home, in a hospital ? There are many ways to approach this challenge.  None of us can predict how, where or how quickly we die. We have a large amount of emotional baggage, our family also carries emotional baggage of which we may not even be aware.

How often I have heard about the son or relative that lives at a distance who will take time to arrive to see their loved one before they pass on.  Each case has it's own set of circumstances which determine how and when you may die.

Much of this sounds pretty morbid to write or speak about, yet it happens thousands of time each day, as often as other events, birthdays, bar mitzvahs, weddings, and births.  It is a passage and a rite of life.  Dying is a part of what we call life.  For certain no one knows what happens after we 'die'. In fact there are different definitions of death. At one time we thought it was when our heart stopped beating. Today it can be defined as brain death (when the brain ceases it's electrical/chemical activity. Yet the body goes on living, in some cases breathing on it's own or with ventilatory assistance.

80% of patients wish to die at home while only 20% actually do die at home.
Doctors do not know how to share this information, They lack the training.
30% of patients die in the ICU
Some doctors perceive death as a failure.

Palliative care is meant to extend quality of life, decrease suffering and match patient wishes for dying.     

There are many participants family, friends, nurses, doctors, and volunteers. Dying is not an easy experience.  We need major changes.

The baby boomer generation is now upon us, 10,000 boomers will turn 65 each day. The major cause of death in this group is due to chronic disease. 

Fill out your advanced directives today, specifying how you want to be treated and specify what measures you do not want to take place on your road to dying.

Join us for a fast-paced day of learning and connection as we engage with one another, across disciplines, to transform the end of life into a human-centered experience.

Just 15% Of U.S. Doctors Use Telehealth In Their Practices

 Just 15.4 percent of U.S. physicians worked in practices that used telemedicine in 206 "for a wide spectrum of patient interactions, including e-visits," American Medical Association researchers report in the December issue of Health Affairs

Despite a favorable regulatory climate, just 15% of physicians are using tele-health in their practices, according to new research in the December issue of the journal Health Affairs.

The research, gleaned from a nationwide physician database by researchers at the American Medical Association, is the latest to show that use of tele health, also known as telemedicine, isn’t yet a standard part of the U.S. healthcare system.

The report in Health Affairs follows a report in JAMA last week by researchers from Harvard University that described access to physicians via telehealth as “uncommon” despite laws passed in more than 30 states requiring health insurance coverage and payments to virtual medical care providers.

The mounting research comes as telehealth companies like American Well, MDLive and Teladoc Health and an array of startups sign deals with commercial health insurance companies, offering their subscribers access to physicians via smart phone, tablet or computer. Employers are also embracing telehealth to make healthcare more convenient for their workers, helping them avoid costly and unnecessary trips to the emergency room or a more expensive in-person visit to a physician’s office.

What becomes increasingly apparent is that insurance companies control what modalities are used for diagnosis and treatment. CMS seems to be leading the way to  telehealth. The prime beneficiary of telehealth are the patients who gain efficiency, less travel time and expense.

Providers are on the downslope for using telehealth, except where patient access is poor, such as rural healthcare.

Here is a breakdown by state of ongoing regulatory changes for Telehealth Reimbursement 

Whether doctors use telehealth technolgy may have to do with the size of the practice with physicians in larger medical groups and at hospitals more likely to use telehealth for patient care and in interactions with other healthcare professionals.

“(Telehealth) use for patient interactions ranged from 8.2% among physicians in the smallest practice size category to 26.5% among physicians in the largest (at least fifty physicians),” AMA researchers Gillis and Kane wrote. “This suggests that despite regulatory and legislative changes to encourage the use of telemedicine, the financial burden of implementing it may be a continuing barrier for small practices.”

But telehealth companies say they continue to see unprecedented growth by doctor practices, patients and between healthcare providers.

Teladoc said “visit growth continues to outpace access growth, with visits growing at a 63%+ cumulative annual growth rate.”

“Without a doubt, patients are learning when and how to go virtual first,” Teladoc said in a statement. “When you dive further into physician use, there has been significant growth in hospital and health system use of telehealth in just the past year. The number of facilities having their first telehealth roll-out continues to increase, and established programs are adding more and more use cases for how they can fully leverage telehealth.”

MDLive compared the trend of consumer use of telehealth to the early days of online banking, travel and dating. All are now part of the mainstream and continue to grow.

Just 15% Of U.S. Doctors Use Telehealth In Their Practices

Readiness Assessment: Improve and Sustain Outcomes

Should we replace meaningful use with meaningful analytics?  Brian Ahier  writes in Health Catalyst

From Meaningful Use to Meaningful Analytics

I’ve written about the three data waves we are facing in healthcare: data capture, data sharing, and data analytics. Primarily due to the “meaningful use” program the United States has made huge strides in electronic health record (EHR) adoption and is beginning to make progress in health information exchange (HIE). These are the principal drivers of the increased capability and use of clinical analytics, since it is the patient data captured, shared, and aggregated by these applications that is the primary source of the data that healthcare organizations analyze using these clinical analytics tools. This allows us to turn those data into information – actionable information that actually provides the ability to improve quality and lower the cost of care. It is the meaningful use of EHR technology that will ultimately enable meaningful analytics.

Two key factors for using clinical analytics to translate data into information are: achieving high quality of care and improving patient safety, as well as increasing awareness about the costs associated with providing care. One way in which organizations are framing these quality of care issues is within the context of meaningful use. Because of incentives when meaningful use criteria are met, and the impending penalties when they are not, many healthcare organizations and providers are evaluating how they are capturing and sharing data. Since organizations are required to report on multiple measures to achieve meaningful use, they often attempt to find ways to capture and report successfully on all measures rather than focusing on only a handful of measures. Clinical data analytics do not only leverage meaningful use rules, but also can help satisfy compliance with them.

One benefit from HIE, besides improved care coordination, is the ability to perform queries and apply analytical tools to those data that were not previously available. The five health outcomes policy priorities included in meaningful use are:

• Improve quality, safety, efficiency, and reduce health disparities
• Engage patients and families
• Improve care coordination
• Improve population and public health
• Ensure adequate privacy and security protections for personal health information

Meaningful Use Analytics

Obviously the reporting requirements for meaningful use can make good use of clinical analytics tools, but some of this reporting capability is also useful when participating in new payment models such as accountable care organizations (ACOs). Although not directly called out in meaningful use, lowering costs is a high priority and part of the over-arching Triple Aim. I cannot imagine succeeding in a truly transformed healthcare system without having the clinical and business intelligence tools that will allow for targeted interventions and not only a retrospective look via claims data, but the real-time capabilities of an Enterprise Data Warehouse (EDW) with robust analytic and reporting functionality.

In addition to a focus on meaningful use measures and ACOs, the industry’s shift to the use of ICD-10 (International Statistical Classification of Diseases and Related Health Problems-10th revision), mandated for the coding of all inpatient and outpatient claims beginning in October 2014, will also impact the use of clinical analytics. Conversion to the ICD-10 coding will dramatically increase the specificity and granularity—and therefore the value—of diagnostic datasets. For example, this change will increase the number of codes available for identifying diagnoses and procedures from 17,000 to 155,000. This will improve the classification of patient interactions by expanding the information that is relevant to ambulatory and managed care encounters, offer expanded injury codes and enable the combination of diagnosis and symptom codes to reduce the number of codes needed to fully describe a condition. This increased granularity, combined with the continued increase in digital capture of clinical data will yield new data sets which healthcare organizations will have the opportunity to translate into meaningful information that can be used to improve the delivery of healthcare.

Health Catalyst offers solutions to measure readiness. 

The Outcomes Improvement Readiness Assessment (OIRA) Tool

Significant trends in U. S. healthcare demand a focused effort on sustained clinical, operational, and financial outcomes improvements. Healthcare organizations have been asking us to help them understand the competencies necessary to drive and sustain outcomes improvements—and help them assess their readiness for implementing the necessary changes. No tool existed that assessed the full spectrum of competencies essential for driving sustainable outcomes improvements. Nothing existed to guide organizations—until now.

OIRA Tool Development: And Future Plans

The OIRA Tool was developed using an integrated literature review of healthcare organizational improvement research across three databases: CINAHL, MEDLINE®, and Web of Science™. The articles were assessed and used to derive an initial set of competencies. A three-round, modified Delphi nominal group method was used with a panel of 11 subject matter experts to evaluate the relevancy and clarity of the competencies using an item-level content validity index (I-CVI) and a scale content validity index (S-CVI)1.

The evaluation panel included healthcare executives and directors responsible for organization-wide outcomes improvements, multidisciplinary improvement team members (clinicians, data architects, and data analysts), and healthcare improvement consultants and analysts. Following round three of the evaluation, the 22 OIRA Tool competencies were grouped into five main keys for success. An S-CVI index of 0.92 was achieved, with I-CVI indices ranging from 0.82 to 1.0, indicating the OIRA Tool competencies are clear, understandable, and relevant to how ready organizations are to drive and sustain outcomes improvements.

How to deal with Non Structured Data

Healthcare NLP: Four Essentials to Make the Most of Unstructured Data

The healthcare industry has recently realized a sharp increase in interest in natural language processing (NLP). The unstructured clinical record contains a wealth of insight into patients that isn’t available in the structured record. Additionally, advances in data science and AI have introduced new techniques for analyzing text, broadening and deepening understanding of the patient. Any organization seeking to leverage their data to improve outcomes, reduce cost, and further medical research needs to consider the wealth of insight stored in text and how they will create value from that data using NLP.

The first step in using NLP can be the most difficult, and many organizations never meet the initial challenge of making the data available for analysis. NLP requires that data engineers transform unstructured text into a usable format (see need to know aspect #2 below) and in a location where the NLP technology can make use of it. This NLP pre-requisite can be a complex process, involving larger data sets and different technologies than many data engineers are familiar with.

This article outlines four need-to-know ways to meet and overcome the challenges of making unstructured text available for advanced NLP analysis. It’s focused on the challenges and skillsets required to build a solid foundation for text analytics.

Understanding Free Text Is the Foundation for Healthcare NLP

In my role of leading NLP efforts for healthcare analytics vendor, I recently worked on a patient safetysurveillance tool that helps health systems monitor for potential adverse events. For example, administering Narcan to reverse the effects of a patient who doesn’t respond well to a pain killer or hospital-acquired pressure ulcers. While the administration of Narcan is commonly documented in structured data, pressure ulcers are often found in unstructured nursing notes.

To get the necessary data to improve patient safety, we needed to leverage the free text of nursing notes. We found that five of the 33 adverse events were primarily documented in unstructured text. To access and leverage the text data in the patient safety tool, we needed NLP. We needed more, however, than the right tools for NLP itself to use the rich information unstructured text holds.

Four Need-to-Know Aspects of Working with Unstructured Text

To effectively build a data pipeline for text, and navigate unfamiliar challenges, data engineers must understand four key points:

1. Text Is Bigger and More Complex

An average EMR record—such as a medication, allergy, or diagnosis, etc.—runs between 50 to 150 bytes, or 50 to 150 MB per million records. On the other hand, the average clinical note record is approximately 150 times as large. With large health systems storing hundreds of millions of note records, this scale introduces data transfer and storage complexities that many data engineers won’t have previously confronted.

2. Text Comes from Different Data Sources

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Readiness Assessment: Improve and Sustain Outcomes: Are you ready? Take the readiness assessment and in minutes get your free, custom report that will help you assess your readiness to drive and sustain outcomes.