2018 has brought renewed attention to high and rising employer health care costs, especially among employees. Teacher strikes across the country, motivated in part by rising health costs that have essentially canceled out small yearly raises, demonstrate the impact of these cost increases, which impact workers in all sectors of the economy. Over the last five years, the employer share of health care costs for family coverage increased by 32%, while employees’ share increased 14%. Average premiums have almost tripled since 2000.
Taking action is imperative. However, no single group can drive change of its own, not even giants like Amazon and JP Morgan. The total number of employees at most organizations represents a very small number of the commercially insured population. A critical mass of employers is needed to drive change, and should include an often overlooked and underused group: state employee health plans.
State employee health plans are frequently the largest commercial plans in the state; in 18 states, they cover more than 10% of the privately-insured population. Their members are often spread across the state, giving the plan a footprint in every major market. State employees have than double the median tenure of private sector employees and are often insured through retirement, making it more financially viable for the state to make long-term investments in employee health. States often have regulatory flexibility to try new initiatives, and their transparency requirements allow state employee health plans to signal to the market their future direction and leverage publicly shared information in negotiating reforms.
As state funded plans, they are also under pressure to run efficiently, with many succeeding. Nevada’s plan runs almost 10% leaner than comparable commercial plans while still reimbursing providers competitively. While running a lean plan limits some plan flexibility and management options, it offers an example for how plans can operate at the lowest possible cost.
I remember when visiting a city required paper maps and often actual guidebooks. Today, I tap on a map app on my phone, enter my destination, and review options for getting from point A to point B. In recent years, these applications have expanded to integrate ride-sharing, bike-sharing, and public transit information. Map apps provide two key real-time data points to help me compare the different options: the time it will take to get to my destination and the cost.
Behind those data points are elegant algorithms that analyze traffic patterns and conditions, as well as the real-time data exchange between multiple apps through modern, REpresentational State Transfer (RESTful) application programming interfaces (APIs). What makes our smartphones so powerful is the multitude of apps and software programs that use open and accessible APIs for delivering new products to consumers and businesses, creating new market entrants and opportunities. There is nothing analogous to this app ecosystem in healthcare.
ONC’s interoperability efforts focus on improving individuals’ ability to control their health information so they can shop for and coordinate their own care. While many patients can access their medical information through multiple provider portals, the current ecosystem is frustrating and cumbersome. The more providers they have, the more portals they need to visit, the more usernames and passwords they need to remember. In the end, these steps make it hard for patients to aggregate their information across care settings and prevent them from being empowered consumers.Continue reading…
This past October CMS Administrator Seema Verma announced the agency’s “Meaningful Measures” initiative. Ms. Verma launched the initiative because, she admitted, the agency’s current quality measurement programming, widely criticized for years by MedPAC and others, ran the risk of outweighing the benefits. Under “Meaningful Measures,” CMS will, Ms. Verma stated, put “patients first” by aligning a smaller number of outcome-based quality measures meaningful to patients across Medicare’s programs. Since “the primary focus of a patient visit,” Ms. Verma said, “must be the patient,” the primary focus of the initiative will be “to focus health care quality efforts on what is really important to patients.” As an indication of this commitment, immediately after Meaningful Measures was announced the National Quality Forum’s (NQF’s) Measures Application Partnership (MAP) began work reviewing a record number of CMS-recommended Patient-Reported Outcome Measures (PROMs).
There appears to be an ever increasing interest in PROMS in the US. For example, last year The NewEngland Journal of Medicine published three PROMs-related “Perspective” essays that moreover described initial success by a few early US PROMs adopters. One of these essays also noted that England and Scotland had “extensive experience” in the use of these measures. Though possibly overstated, we believe providers in the US can benefit from, for example, our experience in the United Kingdom (UK) developing and implementing My Clinical Outcomes (MCO) (at: www.myclinicaloutcomes.com), a digital patient reported outcomes measurement and analytics platform that is now used in the treatment of several chronic conditions in a variety of clinical settings across the UK.
MCO was initially developed in collaboration with orthopedic surgeons working in the National Health Service (NHS). These surgeons were seeking a way to systematically follow-up with their patients after joint replacement surgery largely in order to better economize on their use of clinical resources or more appropriately or efficiently identify those patients in need of follow up face-to-face consultations. The web-based platform was developed to work flexibly around existing clinical work flows.
Doctors can be two-faced. This isn’t necessarily a negative attribute. Doctors have distinct personas for our patients and our colleagues. With patients, doctors strive for a compassionate but authoritative role. However, with each other, doctors often reveal a different demeanor: thoughtful and collaborative, but also opinionated and even sometimes petty. These conflicts are often the result of our struggle with evidence-based medicine. The modern practice of evidence-based medicine is more than the scientific studies we read in journals. Medicine doesn’t just change in rational, data-driven increments. Evidence-based medicine is a dialectic, a conversation. Doctors are being continually challenged to reconcile personal experience, professional judgment, and scientific data. Conflict can naturally result.
This struggle has been ongoing since the rise of evidence-based medicine decades ago. There are factions in medicine who are skeptical of clinical trials as the answer to all of medicine’s important questions, while other factions are wary of authority and consensus-driven medicine. These battles have traditionally been confined to the doctor’s lounge, both literal and in the figurative “safe spaces” of academic journals and conferences. But now the doctor’s lounge is going public. Social media is enabling doctors to rapidly communicate with each other. The heated public arguments that often result are in turn raising new questions about the effect of public discourse on the medical profession and the patients we serve.
Should young athletes be allowed to play tackle football?
Are concussions and chronic traumatic encephalopathy (CTE) a public health problem or merely one associated with professional sports?
Join experts in science, media, policy and administration at New York University, Wednesday April 18th, as they discuss whether our current understanding of head injuries and their pathology require immediate public action.
If it weren’t for the round, scaly patch on the young woman’s shoulder, her doctor might never have known that she served in the Navy for 6 years. He wouldn’t have learned about her sun exposure during a year-long station in east Africa, where temperatures regularly reached over 100°F. But because he didn’t ask about her military history, he didn’t hear about the burn pits and dust storms that filled her lungs with toxic particles. He didn’t hear about the infectious diseases to which she was exposed. He didn’t hear about whether or not she was exposed to combat, or if she experienced military sexual trauma. Perhaps if she were an older man with fading tattoos and a Marine Corps baseball cap, he might have thought to ask.
Or perhaps not.
It takes a remarkable amount of courage for an individual to choose to serve in the military. Their time in the service unquestionably impacts their worldview and every other aspect of their lives. Their health and well-being are no exceptions. That is why all health care providers should know how to ask their patients about their military experiences. More veterans receive healthcare outside the Veterans Affairs (VA) healthcare system than within it, and that number is surely to grow if the VA is privatized, as recently proposed. The time is now for healthcare providers to educate themselves about taking a military history. As physician and nurse practitioner resident trainees, we ask these questions as part of our routine screening both inside and outside the VA healthcare system. The patient who was just described was one of us, and the answers to these questions play a large part in how our patients are diagnosed, treated and understood as people.
When Amazon, Berkshire Hathaway, and JP Morgan (AmBerGan) announced their healthcare partnership, Berkshire CEO Warren Buffett declared “the ballooning costs of healthcare act as a hungry tapeworm on the American economy.” He is right. Our broken system is infested with tapeworms. Tapeworms are parasites; they exploit their hosts, drain resources, and suck the life out of their prey. Unfortunately, Buffet failed to call attention to the tapeworms specifically –they are insurers, hospital conglomerates, pharmaceutical companies, and pharmacy benefit managers.
As healthcare costs continue to skyrocket, Americans increasingly find themselves struggling to make ends meet. Direct Primary Care (DPC) is a tapeworm-free medical concept whereby: 1) a periodic fee is charged for comprehensive primary care services, (2) the arrangement is free from billing through third parties, and (3) if additional fees are charged, those are less than the monthly fee. Depending on age, fees range between $60-150 per month. Patients gain direct access to their physician coupled with unprecedented levels of affordability.
DPC physicians provide protracted office visits, after-hours appointments for emergencies, and occasionally, even home visits. DPC practices can dispense chronic medications at wholesale prices, perform basic procedures in-office, and when outside testing is necessary, these physicians can negotiate discounted “cash” prices on behalf of their patients. This model goes a long way toward restoring the sacred relationship between a patient and their physician. It is no wonder patients are leaving the health care system in droves.
The last obstacle facing expansion of the DPC practice model is their misclassification as an “insurance” product rather than a “healthcare” entity. Legislation, known as the Primary Care Enhancement Act, already exists to repair this mistake and has 29 cosponsors. H.R. 365/ S.R.1358 would allow for two things: 1. Taxpayers participating in a DPC arrangement may qualify for an HSA plan and 2. HSA funds could be used for monthly fees for a DPC arrangement. According to the Moran Company, this legislation is nearly “deficit neutral.”Continue reading…
Jessica DaMassa asks me about money in (Livongo) money out (Theranos), and how much is enough money for challenges (AMA & Google); all in this episode of #healthin2point 00–now on its own Youtube channel. Look for the weird 30 second extreme psoriasis I get in this video!–Matthew Holt
Artificial Intelligence and Machine Learning are very buzzy and in the storm of tweets and scandals it’s easy to use the terms interchangeably, as if they are synonyms. They’re not synonyms, but here’s a rule of thumb: All Machine Learning is AI, but not all AI is Machine Learning.
Examples of Machine Learning in everyday life abound, and for all the attention aimed at the behemoth Facebook, and their epic fail of data protection and privacy, the benefits of Machine Learning generally outweigh the bad. Here we explore the opportunity within Healthcare for AI and ML to do good.
Medicare is a big deal in U.S. healthcare: no doubt.
It’s the $683 billion federal program that provides insurance coverage to 59 million Americans, up 3 million from 2015. It covers 16% of the population and accounts for 20% of total health spending today. By 2020, it will cover 64 million and 81 million by 2030.
Its beneficiaries are a complex population: One in six is disabled, two of three have at least 2 chronic ailments, half have an income less than two-times the federal poverty level ($26,200 in 2016), one in four has less than $15,000 in savings or retirement accounts, and the average enrollee pays 17% of their total income on out of pocket health costs (30% for those above 85 years of age).
It’s a complicated program: Medicare Part A covers hospital visits and skilled nursing facilities, Part B covers preventative services including doctor visits and diagnostic testing and Part D covers prescription drugs.
So, Medicare is the federal government’s most expensive health program. It gets lots of attention from politicians who vow to protect it, hospitals and physicians who complain its reimbursement stifles innovation and seniors who guard it jealously with their votes. But policymakers and many in the industry might be paying too much attention to it. After all, 84% of the U.S. population and 80% of our total spending falls outside its span of coverage and responsibility.