Why Your Next Doctor Visit Could Be Over The Phone

Fever, sore throat, cough, chills…The last thing anyone with these symptoms wants to do is get out of bed and sit in the waiting room at the doctor’s office. That is if there's even an appointment available.

With telemedicine, healthcare providers can accommodate routine visits virtually. This provides patients with a more convenient way to access care, while reserving in-person appointments for more complex health issues. Other common applications of telemedicine include remote follow-up, treating patients with chronic conditions such as diabetes, as well as expanded care for patients in remote or rural locations. Couple virtual visits with the latest wearable health devices such as heart monitors, blood and glucose sensors, and activity trackers, and providers can remotely monitor at-risk patients who require additional care — while also freeing them from frequent in-person visits.

Despite years of buzz and technological advancement, however, telemedicine, or telehealth, has failed to achieve widespread adoption. In fact, most medical consumers aren’t even aware telemedicine is an option — never mind having actually participated in a remote visit with their physician. In concept, telemedicine seems like an ideal solution for many of the current challenges facing healthcare. Patients receive convenient treatment and providers have more time to focus on patients who really need it. So why is adoption lagging? 

The full Forbes article can be viewed at this link.  

Electronic Health Records as a GPS for Healthcare

As patients are bombarded with more choice and information than ever, the burdened health system seems to lack the appropriate support to manage increasing demands for personalized and convenient care.

Today’s infographic comes to us from Publicis Health, and it demonstrates how electronic health records are an important piece in the puzzle to improve experiences for patients and providers alike.

The full infographic and article can be viewed at this link.  

Deprescribing interventions and their impact on medication adherence in community-dwelling older adults with polypharmacy: a systematic review

This systematic review found that deprescribing as an intervention did not routinely improve medication adherence in this patient population. The theory that a reduced medication burden would improve adherence could not be substantiated in the literature. This is because the interventions described in the studies did not convincingly reduce medication burden. There is a range of bio-psycho-social factors reported that associate with improved adherence, but medicines review processes vary and rarely report the population demographic. Adherence is mostly reported as a secondary outcome and there is no standard report of successful adherence to medication. The authors recommend further study into the efficacy and outcomes of medicines management interventions. A consensus on priority outcome measurements for prescribed medications is indicated.

The full article can be downloaded below.  

Association of Pharmaceutical Industry Marketing of Opioid Products With Mortality From Opioid-Related Overdoses

Prescription opioids are involved in 40% of all deaths from opioid overdose in the United States and are commonly the first opioids encountered by individuals with opioid use disorder. It is unclear whether the pharmaceutical industry marketing of opioids to physicians is associated with mortality from overdoses.

The objective was to identify the association between direct-to-physician marketing of opioid products by pharmaceutical companies and mortality from prescription opioid overdoses across US counties.

This population-based, county-level analysis of industry marketing information used data from the Centers for Medicare & Medicaid Services Open Payments database linked with data from the Centers for Disease Control and Prevention on opioid prescribing and mortality from overdoses. All US counties were included, with data on overdoses from August 1, 2014, to December 31, 2016, linked to marketing data from August 1, 2013, to December 31, 2015, using a 1-year lag. Statistical analyses were conducted between February 1 and June 1, 2018.

The main outcomes and measures were county-level mortality from prescription opioid overdoses, total cost of marketing of opioid products to physicians, number of marketing interactions, opioid prescribing rates, and sociodemographic factors.

Between August 1, 2013, and December 31, 2015, there were 434 754 payments totaling $39.7 million in nonresearch-based opioid marketing distributed to 67 507 physicians across 2208 US counties. After adjustment for county-level sociodemographic factors, mortality from opioid overdoses increased with each 1-SD increase in marketing value in dollars per capita (adjusted relative risk, 1.09; 95% CI, 1.05-1.12), number of payments to physicians per capita (adjusted relative risk, 1.18; 95% CI, 1.14-1.21, and number of physicians receiving marketing per capita (adjusted relative risk, 1.12; 95% CI, 1.08-1.16). Opioid prescribing rates also increased with marketing and partially mediated the association between marketing and mortality.

In this study, across US counties, marketing of opioid products to physicians was associated with increased opioid prescribing and, subsequently, with elevated mortality from overdoses. Amid a national opioid overdose crisis, reexamining the influence of the pharmaceutical industry may be warranted.

The full article can be downloaded below.  

Error types with use of medication-related technology: A mixed methods research study

Health information technology has been integrated throughout the medication use process to enhance safety, quality, and care efficiency. However, technologies have the potential to eliminate or reduce, but also create some new types of errors.

The objective was to ssess specific error types before and after the incorporation of two different health information technologies (HITs), e-prescribing and automated dispensing cabinets (ADCs), into pharmacists’ daily work.

A mixed methods design guided use of a pre-existing database of pharmacist survey responses describing patient safety HIT-related issues in the form of errors prevented and errors observed. In vivo descriptive text responses were converted into error types. Descriptive analysis was performed to characterize the error types associated with each HIT.

Four error types were eliminated with the use of e-prescribing, three new error types emerged, and three error types persisted. With ADC use, four error types were eliminated, three new error types emerged, and three error types persisted.

Each technology has its own error types, and some persist regardless of HIT use. There is a need to determine optimal risk reduction approaches for each unique HIT introduced, and design safety practice improvement for error types unaffected by the introduction of HIT use.

The full article can be downloaded below.  

Assessing the Unintended Consequences of Health Policy on Rural Populations and Places 

Because of the complexity of the U.S. health care system, thoughtfully designed health policies carry a risk of having unintended consequences, particularly for health systems in rural places that have place-based fundamentals that deviate substantially from urban and suburban areas. Policies developed without consideration of rural contexts are likely to create unanticipated and negative consequences for rural residents, providers, and communities.

When health policies are being developed, a number of themes that emerge are useful to keep in mind. Specifically, how will this policy impact the ability of a rural health system to offer essential, affordable, and high-quality services to rural populations? How might this policy result in disparate outcomes and widen health inequities, such as threatening access, slowing quality improvement, or creating financial barriers to obtaining health insurance or buying health care services?

The rural-proofing framework presented in this paper is a policy analysis tool for thinking about what the unintended consequences of a policy may be on rural populations and places vis-à-vis the objectives of a high-performance rural health system. Policy analysis must be applied to all sources of authoritative actions given that policies are produced not just in the legislative context, but also through judicial, administrative, and rulemaking actions.

The full report can be downloaded below.  

Not the same old, same old

New physicians, no matter their specialty, are likely to care for elderly patients, says Mandi Sehgal, MD, director of the Geriatrics Curriculum Thread at FAU.  And in the future this will be increasingly important because fewer new physicians are choosing geriatric medicine: The AAMC’s 2018 Physician Specialty Data Report found that the number of first-year residents and fellows studying geriatrics declined 14.3% between 2012 and 2017.

“Even pediatricians will,” Sehgal says. “Sometimes people will bring grandchildren to the office and that pediatrician may see that the grandparent might be a fall risk or may see signs of cognitive impairment. It applies across the spectrum.”

FAU is one of the medical schools putting geriatrics front and center. The college of medicine hired the former President of the American Geriatrics Society, Joseph Ouslander, MD, to develop and direct the geriatrics program, and the school weaves geriatrics education into almost every single one of its classes, says Sehgal.

For example, a neuroscience and behavior course includes an entire section on dementia, and staff and caregivers are brought in from the local memory and wellness center.

“The principles of geriatric medicine are just good medicine,” Sehgal says.

R. Sean Morrison, MD, agrees. The Ellen and Howard C. Katz professor and chair for the Brookdale department of geriatrics and palliative medicine at the Icahn School of Medicine at Mount Sinai is leading the effort there to get its students up to speed on aging and the physiology of aging, not by requiring a separate class or curriculum, but by incorporating the care of older adults into all preclinical experiences, Morrison says. Students are required to make house calls and spend time in ambulatory care practices where patients skew older.

The full AAMC News article can be viewed at this link.  

Success At Cleveland Clinic And The Future Of Healthcare

Healthcare is being transformed with new alignments of medical personnel, digitalization and personalization, focus on prevention and internationalization, according to Cleveland Clinic CEO Tom Mihaljevic. Cleveland Clinic is leading the way in a number of these areas. I interviewed Tom on The CEO Show, and he outlined some of the key features that have earned top-ratings for Cleveland Clinic and his vision of the future of healthcare. 

Cleveland Clinic is an international healthcare provider employing 60,000 caregivers. The majority of its hospitals are around the City of Cleveland, Ohio, and they have hospitals in southeast Florida, Las Vegas, Toronto and Abu Dhabi in the United Arab Emirates. They are now building a hospital in London.

I asked Tom what sets Cleveland Cleveland apart as it earns its top ratings in clinical care and outcomes year after year.

“The most important differentiator for Cleveland Clinic, in our belief, is in our model of care. Cleveland Clinic is organized in such a way that we work as teams,” Mihaljevic said.

The full Forbes article can be viewed at this link.  

Rapid detection of internalizing diagnosis in young children enabled by wearable sensors and machine learning

There is a critical need for fast, inexpensive, objective, and accurate screening tools for childhood psychopathology. Perhaps most compelling is in the case of internalizing disorders, like anxiety and depression, where unobservable symptoms cause children to go unassessed–suffering in silence because they never exhibiting the disruptive behaviors that would lead to a referral for diagnostic assessment. If left untreated these disorders are associated with long-term negative outcomes including substance abuse and increased risk for suicide. This paper presents a new approach for identifying children with internalizing disorders using an instrumented 90-second mood induction task. Participant motion during the task is monitored using a commercially available wearable sensor. We show that machine learning can be used to differentiate children with an internalizing diagnosis from controls with 81% accuracy (67% sensitivity, 88% specificity). We provide a detailed description of the modeling methodology used to arrive at these results and explore further the predictive ability of each temporal phase of the mood induction task. Kinematical measures most discriminative of internalizing diagnosis are analyzed in detail, showing affected children exhibit significantly more avoidance of ambiguous threat. Performance of the proposed approach is compared to clinical thresholds on parent-reported child symptoms which differentiate children with an internalizing diagnosis from controls with slightly lower accuracy (.68-.75 vs. .81), slightly higher specificity (.88–1.00 vs. .88), and lower sensitivity (.00-.42 vs. .67) than the proposed, instrumented method. These results point toward the future use of this approach for screening children for internalizing disorders so that interventions can be deployed when they have the highest chance for long-term success.

The full article can be downloaded below.  

You can now look up charges at your local hospital. Good luck understanding them.

The Trump administration rang in 2019 by enacting a seemingly great health care policy: requiring all hospitals to list the price of their most common procedures on their websites.

The whole idea was to make the American health care system more transparent, allowing patients to research the cost of care at thousands of hospitals across the country.

All in all, it seemed like a common-sense and well-intentioned policy to liberalize health care data. And, on January 1, the policy rolled out into the real world. We’ve quickly seen some big shortcomings in this effort to increase price transparency — ones that tell us a lot about how hard it is to give patients good cost estimates in a health care system rife with secretive prices.

One of the biggest shortcomings? The data that hospitals are posting can be hard to find, and difficult to parse. I looked up the prices at some of my local hospitals in DC.

It usually took me about five to 10 minutes of searching around their websites to locate the price data — not great, but not terrible either. Once I did find it. ... That’s where things got interesting.

The full Vox article can be viewed at this link.