Recent statistical reports indicate that the medical field is experiencing a shortage of both primary care and specialty physicians, increasing the likelihood of a widespread serious physician shortage in the United States.  A physician shortage, as calculated by the AAMC, is a calculation of the gap between physician supply and demand. According to the Association of American Medical Colleges’ Center for Workforce Studies, the physician shortage is expected to approach 104,900 physicians by 2030. By physician category, the AAMC predicts a shortage of between 7,300 and 41,300 for primary care physicians, as compared to a shortage of between 33,500 and 61,800 for non-primary physicians.^[1] The latter category includes physicians categorized under specialty services, under which anesthesiology is housed. Note that the AAMC projections are variable to account for a variety of elastic conditions implicit in physician supply and demand calculation. The lower end of the spectrum provides estimates for an optimistic calculation, referencing several policy approaches to ameliorate the physician shortage. However, the higher end of the range represents a final sum based on inaction on the part of healthcare providers, anesthesia management services, and medical educators alike.

A multipronged approach is necessary to avoid a serious physician shortage in 2030, particularly in specialized fields such as anesthesia services. In sum, a multipronged approach may be comprised of the intersection between innovative medical technologies, modernized medical education policies, and optimized collaborative delivery practices. Innovative medical technologies will provide an incentive for physicians to enter a specialized field by minimizing time spent on administrative services. For example, many novel medical database applications streamline the documentation process, allowing physicians to focus on diagnostic and therapeutic work above clerical tasks. In addition, a push for modernized medical education policies will encourage students to pursue medical careers, specifically in anesthesiology and other specialty fields. These policies may be advocated via support for post-medical school training at the federal level; an increased emphasis on medical specialization in the medical school curriculum; or other such policy levers that add incentives for medical students to specialize and thus reduce the projected physician shortage. Finally, the optimization of collaborative delivery practices will minimize physician shortage by effectively applying assets towards medical cases. In practice, this will require maximizing the use of Certified Registered Nurse Anesthetists (CRNAs) in anesthesiology practices, as well as a reconfiguration of other key members of the medical team. In this way, anesthesiologists will be supported throughout the duration of each medical cases, ensuring the longevity of physicians in the field.

Taken together, the above multipronged approach is one potential mechanism to address serious physician shortage. However, anesthesiologists, anesthesia management companies, and medical educators must share knowledge to develop further techniques to address a physician shortage in anesthesia, thus minimizing the threat of a serious and impactful shortage in the United States.

^[1] https://aamc-black.global.ssl.fastly.net/production/media/filer_public/73/32/7332e443-2302-4daa-a56e-6937a43646ea/2017_workforce_projections_key_findings.pdf

On May 4, 2017, House Republicans fulfilled a key platform promise that has served as an effective political lynchpin for nearly a decade: repealing and replacing Obamacare. The American Health Care Act (AHCA) will effectively repeal the ACA’s individual mandate, cost-sharing reduction payments, and premium tax credits, in favor of age-stratified tax credits and community rating waivers to help states manage their individual insurance markets.

According to the CBO, the bill is expected to leave 23 million Americans without health insurance within a decade, as well as increase premiums for older and poorer Americans.[i]   Conversely, the bill is a victory for fiscal conservatives, with cuts of $834 billion dollars in federal spending over 10 years, most of which is projected to come from critical changes in how the federal government funds Medicaid.

Broadly speaking, the AHCA discontinues the ACA-era matching rates by 2020 and converts Medicaid federal matching funds to a state-opted per capita cap payment or block grant (i.e. for eligible groups who are not disabled or aged). In the former option, a set amount, calculated to ensure federal savings, would be given to states for each Medicaid enrollee.[ii] The per capita cap and block grants would allow for annual payment adjustments based on the Medical Consumer Price Index, but states are financially responsible for additional spending. On the other hand, states keep nothing if they spend under the cap.

Despite proponents’ arguments that per capita caps are less disruptive than block grants, both options ultimately present a sore point for states, especially the 31 states that had implemented the ACA-sponsored Medicaid expansion. Medicaid currently covers 69 million Americans, which means that not only do states have to contend with lower federal support for a greater number of beneficiaries, but they may also be subject to increased administrative costs associated with implementing the per capita cap, as some critics have pointed out.

Unfortunately, the “cut of first resort” is likely affect “payments to providers,” as Drew Altman of Kaiser Family Foundation recently wrote in Axios. This is problematic since healthcare entitlement reimbursements have historically served as determinants of service provider supply in different regions of the United States. In 2005, a GAO report investigated the effect that the difference between local private payments for healthcare services and Medicare reimbursements had on the locality’s provider supply. The report found that CRNA supply is negatively correlated with differences in payments and that anesthesiologist supply is negatively correlated with beneficiary concentration. Additional strategies that states may employ to contain Medicaid costs include cutting services and limiting eligibility to Medicaid.

Should the consolidated AHCA pass the House and Senate, it is likely that will become increasingly important to deal with issues relating to anesthesiology practitioner supply.

[i] https://www.cbo.gov/system/files/115th-congress-2017-2018/costestimate/hr1628.pdf

[ii] http://healthaffairs.org/blog/2017/05/17/can-states-survive-the-per-capita-medicaid-caps-in-the-ahca/

The recent institutional support for EHR and the proliferation of data accessing devices in the healthcare industry present both significant opportunities and threats. This “data-ization” of health has numerous consequences, not the least of which involves the ushering of Big Data to healthcare. With EHRs, telehealth, and IoT medical devices constantly generating patient data, the hope is that eventually the data can be leveraged to optimize machine learning algorithms that will significantly enhance care decisions.

We are a long way from truly integrating Big Data utilization in healthcare, but given the large role that data does and will continue to play in health care, it’s only fair to wonder what steps health care organizations can take to safeguard their data.[i] While big data can yield significant potential boons, it can only realize its benefits if stakeholders are willing to fully engage in the technological transfer. That will not happen in the absence of data security.

The Age of Cyberattacks

According to a 2016 report by the Ponemon Institute, healthcare facilities have been victims of one cyber-attack per month, and that half of all healthcare facilities “have experienced the loss or exposure of patient information.” A further quarter of healthcare facilities reported being unsure whether they have lost patient data or not.[iii] Organizations that find themselves the victims of cyber attacks may lose considerable sums of money to ransom, delays in operations, and loss of reputation.[iv]

Cybersecurity threats that are the most common include malware that may expose or steal sensitive patient information, including financial details, as well as ransomware, a type of malware that blocks user access to data or threatens exposure of data unless a ransom is paid. These attacks primarily favor systems that have not been properly maintained. The structure of today’s multi-stakeholder healthcare system is also expected to dilute security, as the number of entry points for cyber attacks increases with each participating actor.

What can health organizations do to prepare for these attacks?

Among the viable security options are to increase user access security through multi-factor verification and device security, or BYOD (“bring your own device”) security, as the frequency of use of personal mobile devices and PCs in care increase to meet the demands of telehealth.[v] Additionally, security of the actual patient data may be economically relegated to a third-party IT security firm. The security needs of EHR increasingly encourages centrality, in which the administrative and management expertise of healthcare organizations can allocate funds to address cybersecurity concerns across a variety of independent, certified providers.

As malicious use of private information and the extensiveness of data’s role in healthcare increases, so will the financial incentive of targeting healthcare organizations with malware. Experts foresee attacks, girded by machine learning algorithms, to increase in frequency and sophistication. It is essential for healthcare providers to protect both themselves and their patients.

[i] https://www.healthcatalyst.com/big-data-in-healthcare-made-simple

[ii]http://healthaffairs.org/blog/2017/01/17/building-the-value-based-health-care-system-of-the-future-depends-on-meeting-clinicians-data-needs/

[iii]https://www2.idexpertscorp.com/sixth-annual-ponemon-benchmark-study-on-privacy-security-of-healthcare-data-incidents

[iv] http://healthitsecurity.com/news/preparing-for-the-2017-healthcare-cybersecurity-threats

[v] http://healthitsecurity.com/news/prioritizing-byod-security-mdm-in-evolving-healthcare-sector

As outcomes research in anesthesiology progresses to novel heights, an increased emphasis on quality data reporting will be essential to optimize the impact of research, from practitioner to patient. Intrinsic to quality data reporting are the ability and consistency of EMR, or electronic medical records, in combination with actor leadership in the realm of research.

Electronic medical records (EMR) are emerging as an invaluable tool for harnessing the power of data.

While these three intents are consistent across the board, individual EMR platforms may vary by storage capability, metrics gathered, and/or access to data input. The database capabilities of an EMR platform are often a highly negotiated factor. As the transition from paper to EMR takes place among anesthesia facilities, practices, and hospitals, it is necessary for the storage capabilities of the platform to keep pace with the rate of data acquisition. This is particularly important in anesthesia services, which are often paired with other practices, e.g. surgery or rehabilitative care. Data must be easily stored and transferred among practices within a facility or hospital, with appropriate capacity to render large files and collect multiple quantities of data.

Moreover, what data should be collected? The metrics for anesthesia services are oft debated by practitioners, anesthesia management companies, and academics alike. High-quality metrics must include patient outcomes, patient experiences, and, more recently, the cost incurred to the patient, in order to form a comprehensive summary of the clinical case. The Anesthesia Quality Institute provides several frameworks for collecting outcome data from both the physician and patient perspectives. These metrics include such descriptors for adverse patient experiences (anaphylaxis, adverse drug reactions, cardiac arrest); operating room or facility events (OR fire, equipment malfunction); and administrative errors (wrong patient, wrong site surgery). The AQI is a preeminent source for practice-based quality management, and thus has a fundamental role in developing guidelines for metric-driven outcome research.

In collecting data, attention must be placed on confidentiality and right to access. The relationship between availability of data and patient confidentiality is a delicate balance that is increasingly addressed by EMR platforms, most recently by use of mandatory identity verification functionalities. The ability to access data varies depending on the selected platform. For example, large-scale EMR platforms may only be accessible by an anesthesiologist or CRNA, while more modern start-up EMR ventures may include patient inputs in the platform design.

The importance of harnessing data, as explored through the versatility of EMR platforms, is an essential component to maximizing outcomes research in anesthesia practices. However, EMR and robust data must work in concert with effective actor leadership in order to ensure that outcomes research plays a role in modifying anesthesia policies and practices. Historically, leadership for anesthesia outcomes research came primarily from physicians or academics. Yet, a modern approach to research-based practice includes a variety of actors. The American Association of Nurse Anesthetists notes in a scientific paper that, “80% of CRNAs conducting research participated in quantitative research”, concluding that “[it] is likely that the CRNAs conducting research are doing quality research” (Cowan et al., 2002). As active practitioners of anesthesia care, CRNAs demonstrate valuable potential to lead the field of outcomes research in anesthesiology. In addition, patients are evidently central to outcomes research, as partners in the journey to the highest-quality anesthesia care. Patient advocate organizational leadership may represent a resource to further develop outcomes research. Finally, anesthesia management services play an important role in mobilizing outcomes research to research-driven quality improvement in care. A high-quality anesthesia management service organization such as Xenon Health can integrate physician perspective with quality benchmarks and cost-effective practices in order to deliver excellent care to patients. Anesthesia management services take a practical approach, ensuring a commitment to high-quality care and research-driven practices.

Anesthetic management of the geriatric patient is becoming increasingly commonplace. It is predicted that by 2030, 20% of the U.S. population will be over the age of 65, and many senior citizens will have complex medical issues often requiring surgical intervention. Recognizing the physiologic changes that occur with aging and tailoring anesthetic care to this unique patient population is an asset to the practicing anesthesiologist.

CNS changes occurring with age include decreased white and gray matter, as well as reductions in neurotransmitter levels (e.g. dopamine, acetylcholine, norepinephrine, and serotonin). Elderly patients are therefore more sensitive to anesthetics (MAC decreases 4-6% per decade after age 40) and are at increased risk for perioperative delirium and postoperative cognitive dysfunction. Neuraxial local anesthetic dosages should also be decreased, given the smaller epidural space, increased dura permeability, and decreased CSF volume.

Cardiovascular changes include left ventricular thickening and diastolic dysfunction, decreased contractility due to myocyte loss, decreased β-adrenergic sensitivity due to decreased conduction fiber density and a decreased number of sinus node cells, and increased resting sympathetic tone. Vascular stiffness due to breakdown of elastin leads to higher mean arterial pressure and increased pulse pressure. These changes explain why geriatric patients benefit from adequate preload, low heart rates to ensure time for coronary perfusion, and sinus rhythm. Loss of the elevated native sympathetic tone by anesthetic induction or neuraxial anesthesia are not tolerated as well in the elderly, given decreased responsiveness to sympathomimetic drugs.

Respiratory changes include increased lung compliance due to loss of elastic elements and altered surfactant production, decreased chest wall compliance, increased closing capacity (CC) due to early collapse of the small airways on exhalation, and loss of overall alveolar surface area. These result in increased anatomic dead space, decreased diffusion capacity, increased work of breathing, impaired gas exchange, and increased air trapping. Total lung capacity is unchanged, vital capacity decreases, residual volume increases, functional residual capacity (FRC) is unchanged or slightly increased. At 44 years of age, FRC and CC are equal in the supine position, and at 66 years of age in the upright position (CC is not affected by position, unlike FRC). As FRC falls below CC, increased shunting occurs leading to desaturation. The importance of fastidious preoxygenation of the elderly patient is therefore especially important, as is the maintenance of PEEP during positive pressure ventilation.

Renal changes include decreased GFR, necessitating cautious dosing of renally cleared medications. Serum creatinine remains unchanged given a coincidental decrease in muscle mass, and is therefore a poor predictor of GFR in the elderly. Liver volume decreases 20-40% with aging, and hepatic blood flow decreases 10% per decade.

The physiology of aging is important to understand for the proper anesthetic management of the geriatric patient. General trends are toward conservative dosing of medications, accounting for decreased cardiopulmonary reserve, and keeping in mind the susceptibility to a prolonged postoperative recovery.