The Changing Face of Healthcare

Several significant forces in the last several years have been changing the way healthcare has and will continue to be delivered. The emergence of more unique ways to deliver care such as clinics incorporated into businesses and factories, the increased use of mid-level providers (nurse practitioners & physician assistants), the increase integration of technologies such as telemedicine and robotics and the shift from interventional reimbursement to outcomes reimbursement are just a few examples.

Compounding these are the ever-increasing costs of healthcare, the strain of funding Medicare on the U.S. economy, and the complications of insurance and healthcare payments under the affordable care act, ACA.

This has led to changes in how businesses intend to interface with the healthcare system going forward. CVS’s acquisition of Aetna will try to leverage healthcare delivery through their pharmacy structure. United Healthcare’s acquisition of DaVita hopes to leverage cost containment and resource control by directly controlling physicians. And the recently announced collaboration among Berkshire Hathaway, Amazon and J.P. Morgan Chase presents a yet unknown structure whose stated goals is improved quality and less cost. How they will implement their strategy is yet to emerge.

The decline in hospital admission over the last several decades has further led to restructuring by hospital corporations such as Tenet. Premise Health has emerged as a company placing physicians and other healthcare providers directly in corporate/business offices.

The big question then with these new ventures are how do organizations know what works financially and how do they track performance… In other words, how do you track, measure and value the relationships between cost and outcomes?

How can the analyst measure which methods(s) may generate better or best outcomes?

A simple return on investment, ROI, calculation will not provide needed nor valid insights. However, the use of cost-effectiveness analysis (CEA) would provide quite useful, valid and actionable information. CEA uses decision tree models to compare not only cost outcomes but effectiveness outcomes of various treatments on patient health and even on future healthcare usage based on various current actions. It can further be used to determine how effective a set amount of money spent on a particular treatment or method will impact outcomes (i.e. willingness to pay calculation). CEA models are flexible and can incorporate a wide variety of scenarios. As opposed to Big Data, CEA makes use of Broad Data so that comparisons of treatment modalities can be evaluated using real life outcomes. It can compare effects on a discrete problem such as a cancer tumor, or on chronic ongoing diseases such as COPD or CHF.

As the delivery of effective yet profitable, or at least cost effective, healthcare becomes more challenging, methods for evaluating treatments and programs become more necessary if not essential. Methods must be implemented to evaluate these new treatments and programs once they are in place so adjustments can be made. CEA enable organizations to both initially evaluate and subsequently monitor new methods and programs in a meaningful way.

Is Team Training Effective at Healthcare Sites?

In the June 2016 issue of the Journal of Applied Psychology the authors Eduardo Salas, Lauren Benishek, Megan Gregory and Ashley Hughes in an article titled “Saving Lives: A Meta-Analysis of Team Training in Healthcare” set out to answer the question as to whether team training is effective in healthcare, whether it leads to reduced mortality and improved health outcomes.

Their research stated that a preventable medical error occurs in one in every three hospital admissions and results in 98,000 deaths per year, a figure corroborated in To Err is Human. Teamwork errors through failure in communications accounts for 68.3% of these errors. Thus, effective team training is necessary to reduce errors in hospitals and ambulatory sites.

The authors used a meta-analysis research method to determine whether there are effective training methods in the healthcare setting that can have a significant impact on medical errors, which would in turn improve outcomes and reduce costs by eliminating the costs associated with the errors. A meta-analysis is a broad research of existing literature to answer the research questions posed by the research team or authors.

The research team posed three questions to answer:

1. Is team training in healthcare effective?

2. Under what conditions is healthcare team training effective?

3. How does healthcare team training influence bottom-line organizational outcomes and patient outcomes?

The team limited its meta-analysis to healthcare teams even though there is a great deal of research available about the effectiveness of team training in other industries and service organizations. The team believes that healthcare teams differ significantly from teams in other areas in as much that there can be much greater team fluidity in healthcare. That is, team membership is not always static, especially at sites such as hospitals and outpatient surgical centers. There are more handoffs at these sites.

Although there is greater fluidity in team membership at healthcare sites, roles are well defined. For instance, a medical assistant’s role at a primary care site is well defined even though different MA’s may be working with one physician. These roles are further defined and limited by state licensure. As the research team stated in their article, “these features make healthcare team training a unique form of training that is likely to be developed and implemented differently than training in more traditional teams… ”

The team assessed their research of articles using Kirkpatrick’s model of training effectiveness, a widely used framework to evaluate team training. It consists of four areas of evaluation:

1. Trainee reactions

2. Learning

3. Transfer

4. Results

Reaction is the extent to which the trainee finds the instruction useful or the extent to which he enjoys it. Learning is defined as a relatively permanent change in knowledge, skills and abilities. The authors note that team training is not a hard skill, as learning to draw blood. Rather, it is a soft knowledge skill. Some researchers question whether it is possible to measure the acquisition of these soft team skills effectively. The team of authors effectively argue that it can.

Transfer is the use of trained knowledge, skills and abilities at the work site. That is, can team training be effectively applied in the work setting? Results are the impacts of the training on patient health, the reduction of medical errors, the improved satisfaction of patients and a lowering of costs in providing care.

In order to assure that the changes in these four areas were ‘real’ the team only used literature that had both pre-assessments and post-assessments to see if there were statistically significant changes in the four areas.

Using this assessment rubric the team was able to answer the three questions that it posited. First, team training in healthcare is effective. Healthcare team training closely matches training in other industries and service organizations.

Secondly, training is effective, surprisingly, regardless of training design and implementation, trainee characteristics and characteristics of the work environment. The use of multiple learning strategies versus a single training strategy does not matter. Simulations of a work environment are not necessary. Training can occur in a standard classroom.

Training is effective for all staff members regardless of certification. Training of all clinical personnel as well as administrative staff is effective. Team training also is effective across all care settings.

Lastly, the team’s meta-analysis shows that within the Kirkpatrick rubric team training is effective in producing the organizational goals of better care at lower costs with higher patient satisfaction. In the rubric trainee reactions are not nearly as important as learning and transfer in producing results. It is important that trainers use both pre-training assessments and post-training assessments to measure whether there learning of skills, knowledge and abilities were learned and whether these were transferred to the work site. Effectiveness of training should always be assessed in order that training programs can be consistently improved.

In my September 2017 newsletter “Team Meetings” I described the elements of good team training as well as provided a link to the American Medical Associations team training module as part of Stepsforward series of learning modules. You can find this newsletter online here. With these training instructions as a beginning healthcare providers can learn to work more effectively as teams and thus produce better care at a lower cost with higher satisfaction of both patients and providers.

Accurate Diagnosis & Patient Comfort at the Core of Innovation in ECG/EKG, EEG, and MRI Technologies

Over the past decade, researchers have made several undeniable breakthroughs in curing diseases that were once thought to be deadly and incurable. And this feat can be attributed to significant improvements in diseases diagnosis and testing.

In recent years, newer as well as safer methods of disease testing have been developed to avoid incorrect diagnosis among patients and to ensure they do not have to undergo any additional harm. Development of the latest diagnostic tests and procedures – such as electrocardiogram (ECG), electroencephalography (EEG), and magnetic resonance imaging (MRI) – enables physicians to make accurate decisions about their patients.

Thanks to constant innovation and dedication of healthcare companies and research organizations, diagnostic testing has helped achieve tangible improvements in not just the survival of patients but also in their overall health and quality of life.

Portable and Wearable ECG/EKG Monitors a Prominent Innovation in Cardiovascular Health

The electrocardiogram (ECG) has played a crucial role in understanding cardiovascular diseases. Its wide scope of application encompasses clinical diagnosis and prognosis of cardiovascular diseases, biomedical recognition, health assessment, fatigue study, and others. Ongoing research in the technology is mainly focused on accuracy of ECG diagnosis and application, big data mining for ECG, and improved ECG instrumentation.

Remote ECG monitoring systems are fast becoming commonplace medical devices for remote as well as long-term physiological monitoring. These devices are not just targeted for elderly and frail patients but also for healthy individuals merely looking to monitor overall wellbeing.

Wearable technology is one of the most prominent innovations in the field and continues to be used in everyday clinical practice.

Qardio, Inc., a global digital health company, launched a revolutionary wearable ECG monitor in January 2017. The QardioCore is reportedly the first wearable medical ECG/EKG monitor that lets users monitor heart health without any patches or wires. This innovation is a far cry from conventional ECG monitors used in hospitals, which are known to be bulky and burdensome. By contrast, this wearable device is designed for monitoring anywhere and anytime.

Looking to capitalize on the growing trend of remote patient monitoring, especially to maintain heart health, medical device companies are working on devising new and innovative methods of tracking patient health. One such example is startup AliveCor’s Heart Monitor. The monitor comprises a case that can be simply attached to the back an Android device or an iPhone, while the test is administered and results are revealed through the company’s mobile app AliveECG. This gives new meaning to the concept of having health at your fingertips.

Increased Focus on making EEG Technology Minimally Invasive

Generation after generation, scientists and researchers have tried to understand the human brain. The 18th century pseudoscience of “bumpology”, which believed that the shape of a person’s skull lent insights into their mental state and personality, was discredited as a science 50 years after its introduction. It was nearly a century later that studying the electrical activity inside a living brain came to be the go-to technique to understand various neurological conditions.

Although the technique, called electroencephalography (EEG), was rather invasive initially, contemporary research and modern technology have enabled the development of non-invasive methods to study brain function, pathology, and behavior.

In recent years, the many intrinsic advantages of EEG have allowed the technique to expand its application scope to include diagnosis of conditions such as epilepsy, seizures, dizziness, head injuries, brain tumors, headaches, and sleep disorders. After a groundbreaking move away from analog to digital recordings, automated and integrated computer-EEG systems have opened doors to adaptable and accessible research methodologies. These systems have also become relatively portable and cheap.

Capitalizing on recent technological innovations, Maryland-based BrainScope raised U$16 million in August 2017 to be dedicated toward research and development of mobile, non-invasive devices to assess traumatic brain injury. In September 2016, the company launched “Ahead 300″, the third version of its commercial product BrainScope One. It comprises an EEG headset and a handheld display equipment to help clinicians conduct 4 tests to determine the existence of a traumatic brain injury. These tests – two cognitive performance and two sensor-based tests – have the potential to allow the device to eliminate one third of unnecessary CT scans.

For several developing regions and countries, access to costly diagnostic technologies such as EEG means overcoming a number of geographic and economic constraints. However, penetration of the Internet and proliferation of smartphone usage has brought these countries closer to gaining access to advanced technologies. The Bhutan Epilepsy Project, for instance, has been tackling the aforementioned challenges by using a smartphone-based EEG. Developed by the Technical University of Denmark, the device and overall setup amounts to less than US$500, is highly portable, and is easy to use.

Constant Innovation in MRI Hardware and Software

Perhaps one of the most common and widely-used diagnostic/medical imaging technique, magnetic resonance imaging (MRI) has been highly valued for its versatility. MRI has a wide range of applications in the field of medical diagnosis, ranging from neuroimaging, cardiovascular, and musculoskeletal to angiography, liver, and gastrointestinal. And even though the effect of this imaging technique on the improved health outcome of a patient is uncertain, its role in the diagnosis and treatment of various disorders is irrefutable. Based on recent developments, GE Healthcare has been among the front-runners in MRI technology.

Innovation in design is crucial in MR technology and this can add immense value to patient-friendly medical imaging. Take the 2011 Optima MR430s, for instance. This GE Healthcare innovation marked a major leap in MR imaging as it was designed for specific targeted anatomy, be it an arm or a leg, rather than traditional whole-body systems. Overcoming the challenges of immobilization and patient confinement, this innovative scanner has helped improve patient experience. For physicians, this has meant fewer demands on a full-body scanner, smarter investment options, relieving patient backlogs, and low total cost of ownership.

In the last couple of years, however, major advances in MRI technology have been on the software side. This has resulted in more simplified cardiac imaging workflows, faster contrast scans, and allowing MR scans of the lungs.

In September 2016, the US FDA granted approval to the MAGnetic resonance image Compilation, or MAGiC, software by GE Healthcare. This is reportedly a first-of-its-kind multi-contrast MRI technique that delivers eight contrast media in a one acquisition. This is done in a fraction of the time taken by traditional imaging, primarily by allowing users to flexibly manipulate MR images retrospectively. This has led to fewer rescans and therefore considerable time and cost savings.

Cardiac MRI has been a rather limited field owing to lengthy exam times, complexity, and high cost. RSNA 2015 saw GE Healthcare introduce a new MRI technology, one with the potential to simplify cardiac MR to a great extent. The ViosWorks cardiac MRI software helps create what the company calls a 7-D cardiac MRI exam.


Advances in diagnostic/medical imaging over the last five years alone have revolutionized practically every aspect of medicine. Access to detailed imaging has enabled physicians to see things from a new perspective. With doctors realizing just how accurate and valuable these tests can be and manufacturers investing in research and development, the day isn’t far when exploratory surgery will become obsolete.