What You Should Know:

• Luma Health unveiled its integration and partnership with one of the healthcare industry’s top electronic health record providers, MEDITECH, which brings powerful new capabilities to the thousands of healthcare providers that use the MEDITECH Expanse EHR. 
• As an initial member of the MEDITECH Alliance program and currently the only patient-facing vendor included in the program, Luma collaborated with MEDITECH to validate the integration of its Patient Success Platform™ and MEDITECH-enabled workflows for integration with MEDITECH Expanse, including patient scheduling, conversational messages, operational and clinical forms, staff scheduling, and more.

Broadening the Horizons of Patient Success Capabilities 

To provide Luma’s developers with hands-on access to its proprietary APIs, MEDITECH invited Luma to participate in MEDITECH Greenfield Workspace, a preferred-access partner engagement initiative for organizations with proven, interoperable products that complement, enhance, or extend the Expanse EHR. The MEDITECH Greenfield Workspace provides a collaborative environment enabling third-party developers and Expanse customers to test solutions within a real MEDITECH EHR.

“Our collaboration with the MEDITECH team showcases the power of partnering at both a technical and commercial level,” said Luma Health co-founder and CTO Aditya Bansod. “Our respective teams benefited from each other’s insights to break technical ground and harness the latest standards to simplify and improve the lives of healthcare providers and patients alike. We’re excited to bring MEDITECH users breakthrough new capabilities using MEDITECH’s standards-based, FHIR-based scheduling APIs.”

At Phelps Memorial Health Center (Holdrege, NE), the MEDITECH Greenfield Workspace allowed Luma to set up, test, and fine-tune its software before moving it into Phelps Memorial’s installation of Expanse. The result was a fast and smooth implementation that has already delivered significant patient success outcomes for Phelps Memorial.

Using MEDITECH Expanse APIs, appointment, demographic, and schedule data is seamlessly sent from MEDITECH’s scheduling module to Luma, where a rules-based system sends text, email, and voice reminders to patients on a regular cadence based on Luma Bedrock™ data-driven best practices. Once an appointment is confirmed through a Luma communication, the information is instantly sent back into MEDITECH, changing the appointment status to confirmed or canceled, allowing MEDITECH end users to have an up-to-the-second view of their day. Patients can also self-schedule appointments via Luma that are immediately synced to MEDITECH’s scheduling module via MEDITECH Expanse APIs. 

Since adding Luma to their MEDITECH Expanse platform, nurses have seen a significant reduction in the time spent contacting patients about appointments and test results. Today, more than 90% of Phelps Memorial patients confirm their appointment with a Luma reminder, and the system is delivering other significant outcomes for Phelps’ patients:

1. Simplified appointments using pre-visit intake: 84% of patients who receive intake forms from Luma complete them ahead of their appointment.
2. Successful engagement with older patients via SMS: 82% of patients aged 61-80 are responding to Luma messages.
3. Reclaimed staff time through automated outreach: Phelps Memorial now reaches over 98% of its patient population using Luma.

What You Should Know:

• Magenta Medical, the developer of the world’s smallest heart pump, announced today a $55M financing round led by global healthcare investment manager OrbiMed, with participation from existing investors New Enterprise Associates (NEA), Pitango VC, and ALIVE – Israel HealthTech Fund.
• The financing will be used, among other things, to advance the clinical programs of the company’s product in the United States toward its first FDA approval.

Furthering Magenta’s Clinical Programs in Support of FDA Approval For World’s Smallest Heart Pump

Temporary mechanical circulatory support (MCS) is one of the fastest growing markets in interventional cardiology, encompassing devices that aim to augment the output of a failing heart, in the setting of dangerously low blood pressure, while resting the heart and providing a bridge to recovery over a period of hours or days. Existing temporary MCS devices provide limited flow, require an invasive surgical procedure, or both.

Magenta’s percutaneous Left Ventricular Assist Device (pLVAD) is a powerful heart pump that is initially folded, inserted through the groin using a small puncture, and expanded for activation inside the left ventricle. The flow of the pump is adjusted based on the clinical circumstances of the patient, up to the entire cardiac output, allowing the heart to rest and the patient to recover. Once the Magenta technology is approved, physicians will be able to rely on a single device to treat the full range of MCS patients, thus eliminating the need to escalate therapy to a new device and subject the patient to unnecessary and invasive replacement procedures.

“Magenta is proud to add OrbiMed to its growing roster of leading MedTech investors as a highly reputable partner for innovative medical device companies,” said Dr. David Israeli, CEO of Magenta Medical. “I am confident that together we can build an organization well-equipped to bring to the market high-impact technology that can potentially address multiple unmet needs in the general cardiology patient population, as well as in many under-served patient groups.”

The potential advantages of Magenta’s high-flow, low-profile device were recognized by the US FDA, resulting in Breakthrough Device Designation for two indications: high-risk percutaneous coronary intervention (HR-PCI) and cardiogenic shock (CS). Magenta successfully completed a HR-PCI first-in-human (FIH) study in Tbilisi, Georgia, the results of which were presented at the recent 2022 Transcatheter Cardiovascular Therapeutics (TCT) conference in Boston, MA, by Dr. Duane Pinto of Beth Israel Deaconess Medical Center and Harvard Medical School. Building on this experience, Magenta is now preparing to launch its clinical programs in the US, starting with an imminent HR-PCI Early Feasibility Study.

What You Should Know:

• Quest Diagnostics has reached an agreement to acquire Haystack Oncology  an early-stage oncology company focused on minimal residual disease (MRD) testing to aid in the early, accurate detection of residual or recurring cancer and better inform therapy decisions
• Under the terms of the agreement, Quest will pay $300 million in cash at closing, net of cash acquired, and up to an additional $150 million on achieving future performance milestones.
• The acquisition will leverage Quest’s expertise and scale in oncology, genomics and pathology. Quest employs approximately 400 pathologists through its AmeriPath specialty pathology-diagnostics business and provides approximately 7,000 patient access points in the United States for blood and other specimen collection.

Adding Sensitive Liquid Biopsy Technology for Improving Personalized Cancer Care to Oncology Portfolio

MRD testing is a fast-growing category of liquid biopsy tests that identify circulating tumor DNA (ctDNA) in the bloodstream of patients following surgery and treatment for cancer. Founded in 2021, Haystack has developed a ctDNA-based technology specifically for MRD detection, based on 20 years of research and development by world-renowned luminaries from Johns Hopkins University, including Drs. Bert Vogelstein, Ken Kinzler and Nick Papadopoulos. In a prospective, multi-institution study published in the New England Journal of Medicine in June 2022, an earlier version of the Haystack technology demonstrated the ability to better identify patients with residual disease for adjuvant chemotherapy after surgery for stage II colon cancer, thereby reducing chemotherapy use in the overall patient population without compromising recurrence-free survival.

Following the close of the acquisition, Quest expects to adapt the MRD test developed at Haystack as the basis for new clinical lab services available beginning in 2024. Development efforts will focus initially on MRD tests for colorectal, breast and lung cancers.

“Combining Haystack with Quest is a major step forward in translating two decades of world-class liquid biopsy research and development into clinical laboratory services that are highly reliable and broadly accessible. Like looking for a needle in a haystack, accurately detecting MRD has been very challenging to date,” said Dan Edelstein, CEO and President, Haystack. “With Quest, we expect to increase and accelerate access to important tests that will improve the quality of cancer MRD detection and recurrence monitoring for patients. Working together, we have the potential to greatly transform the patient journey and save lives.” 

What You Should Know:

• Notable, an intelligent automation company for healthcare, launches Patient AI, a solution leveraging large language models (LLMs) and GPT (the technology powering ChatGPT) to bring personalization at scale to healthcare.
• Using GPT to scan existing clinical documentation, this tech can detect missed diagnoses, identify lapsed insurance cards, incorrect addresses, eligible clinical trials, or costly care gaps in real-time across an entire patient population. 

How Patient AI Works

Patient AI continuously reviews millions of data points across medical records and third-party data sets to develop a comprehensive clinical and social understanding of each patient. These insights are automatically translated into personalized recommendations that are surfaced to the patient before, after, and in between encounters through adaptive design without any staff involvement. The result is that patients are engaged at precisely the right moment to take action in achieving their health goals.

For example, a patient with lung cancer who frequently misses appointments due to a lack of transportation can be matched by Notable to:

• A one-click ride booking with a rideshare service
• A recommendation to learn more about a clinical trial to treat symptoms of her cancer
• An opportunity to request a refill of an expiring medication
• The option to reschedule multiple upcoming appointments into a single day

Alternatively, a patient being discharged after knee surgery can be matched with:

• A home health nurse
• A medical equipment provider for crutches
• A series of periodic questionnaires to assess patient-reported outcomes (PROs)

Notable presents all of these services to patients in an intuitively designed digital experience. 

Previously, this level of personalization required teams of professionals – including care coordinators, medical assistants, and nurses – and multiple hours of work to deeply examine a patient’s clinical history, assess social determinants of health (SDOH), and manually contact the patient. Patient AI powers this level of proactive, personalized care without any increase in staff. 

What You Should Know:

– Hospital finances are beginning to stabilize as razor-thin margins become the new normal, according to the newest data from Kaufman Hall. The National Hospital Flash Report draws on data from more than 900 hospitals from Syntellis Performance Solutions.

 – The latest National Hospital Flash Report shows that the high level of variance that plagued hospital margins over the past three years is beginning to subside as external economic factors like labor shortages, higher material expenses, and a patient population that is increasingly seeking care outside of the hospital affect hospital finances. 

Key findings include:

Median YTD Operating Margin Remains Negative

The median year-to-date operating margin index for hospitals was -1.1% in February, down slightly compared to -0.8% in January. Despite the slight dip in financial performance, February marked the eighth month in which the variation in month-to-month margins decreased relative to the last three years.

Non-Labor Costs Drive Hospital Expenses

Hospitals continued to incur high expenses that negatively affect margins. Kaufman Hall experts point out that February represented a shift from labor to goods and services as the primary driver of hospital expenses. Inflationary pressures led to significant cost increases in goods and services, increasing non-labor expenses by 6% year-over-year. While hospitals still face labor shortages, labor expenses appeared to hold steady, indicating less dependence on contract labor.

Ongoing Shift in Patient Care Setting

The onset of the COVID-19 pandemic kickstarted a shift in patient behavior that continues today. Patients continued to seek more of their care away from inpatient settings, with February 2023 outpatient revenue up 14% compared to February 2022. Due to the shorter month, discharges, patient days, and ED visits were all down slightly in February compared to January. On a per-day basis, however, the average length of stay in hospitals was down, while ambulatory surgery centers and outpatient operating room minutes saw volume increases last month.

What You Should Know:

– Health equity – or the lack thereof – is one of the biggest challenges facing US healthcare organizations today.

– A new report from Accenture, US health inequity: beyond the statistics, analyzes the role US healthcare ecosystem participants can play in addressing health inequities due to race and ethnicity. The statistics are staggering. 

Analysing Key Trends Concerning Health Inequities 

To understand the human and economic impacts of health inequity, Accenture conducted a systematic analysis of peer-reviewed literature and critical opinion leader views to then collate insights from extensive client engagements.Additionally, Accenture spoke with subject matter experts from the life sciences, healthcare and public health industries. Through these actions, one could synthesise health inequities’ leading causes and effects.

Accenture identified five interconnected areas that negatively affect people:

1. Implicit bias: Implicit racial and ethnic biases are unconscious attitudes or stereotypes that affect our understanding of, and responses to, individuals and groups other than our own. These biases erode quality of care and access for underrepresented patients, in turn leading to a lack of trust in, and even fear of, the healthcare system as well as lowering participation by POC in their healthcare journey.

2. Lack of trust and fear: Given longstanding issues with the medical system (such as mistreatment of, and unethical studies among POC in the US), their relationship with the healthcare system is characterized by a general lack of trust and high levels of fear.

3. Access barriers: Access barriers are roadblocks which prevent underrepresented groups from receiving equal access to care such as the affordability of care/medicines, the effects of implicit biases, health education, participation in clinical trials and other barriers such as language or transportation.

4. Uneven quality and experience: Stark differences in the quality of care exist between races. Patients from racial and ethnic minorities frequently receive sub-par care and experience worse outcomes relative to white patients. This uneven quality is directly tied to biases, trust and fear, and access barriers.

5. Racism in R&D/Clinical practices: Lack of representation of people of color (POC) among both patients and physicians, barriers to access and other obstacles like bias, lack of trust and fear, and limited care access all limit the quality of health and research outcomes among affected groups.

According to the report, health ecosystem players’ current efforts to address inequities are disconnected from the daily realities faced by underrepresented communities. Their efforts need to be more relevant, organized, streamlined and cohesive. To achieve health equity, the next generation of actions must consider three core areas that tackle the five key interconnected areas:

1. Mitigate bias in data analytics and algorithms: Clinical algorithms are at the heart of the digital core of Health organizations. They intend to improve accuracy and efficiency but have sometimes proven to widen healthcare disparities. The most cited example is the large commercial health decision algorithm that used healthcare costs as a proxy for health needs, which inappropriately led to Black and African American patients being labeled as “healthier” than equally sick white patients. To advance health equity, data analytics and algorithms must be inclusive, fair, accountable, transparent and easily explainable.

2. Design inclusive products and services: Health equity must be considered from the start of product and service design. Inclusive design methods enable and draw on the full spectrum of human diversity and individual experiences to create solutions. This does not mean that a single product or solution meets every person’s needs. Instead, it means designing different ways for people to receive the same access, experience and outcomes while having a sense of belonging. Considering health equity at this stage encourages better practices, greater accessibility and a more inclusive healthcare environment which drives value for people and ecosystem participants.

3. Create sustainable structural change: To make long-lasting, meaningful change, participants must ensure that their actions bring about structural change. Racism and implicit biases are embedded throughout the ecosystem. Addressing institutional policies such as inclusive hiring practices, the types of partnerships created, and how participants execute clinical treatment and tools will have far- reaching effects on the sustainability of the healthcare ecosystem. Additionally, engraining equity as a core tenant of participants’ foundation will aid in normalizing these activities across the ecosystem.

Lastly, the report includes suggested actions for healthcare payers and providers, along with suggested actions for bio Pharma companies and public health institutions, to mitigate healthcare inequities, as follows:

Mitigating bias in data analytics and algorithms(healthcare payers and providers)

1. Employ critical evaluation when using non-user-generated demographic data: Analyze gaps in data collection and work with local community brokers (like EMTs, social care organizations, food pantries or schools) to inform available public (or purchased) datasets. This will produce more inclusive data around disease onset, hospitalization and adherence to treatment plans. Comprehensive demographic data collection is a health equity priority for CMS.

2. Leverage existing member health processes and outcomes: Stratify them by race, ethnicity and language (REL), sexual orientation and gender identity (SOGI), disability status, rurality and other variables. Acknowledge bias and gaps in data analysis that don’t accurately reflect communities.

3. Implement frequent and standardised audits: Assess algorithmic and data collection processes. Use machine learning auditing techniques to build in representational fairness, counterfactual reasoning, error rate balance and error analysis to account for confounding racial/socioeconomic factors.

Mitigating bias in data analytics and algorithms(biopharma companies)

1. Develop equitable algorithms: Set organisational diversity standards for any data leveraged for any R&D or other algorithmic purposes to ensure that data is more representative and less fragmented. Doing so will also streamline the ability to amalgamate this data for additional analyses on both social and clinical dimensions. Assess algorithms for bias potential/relative degree of inherent bias. Continuously revise algorithms as more diverse data sets become available. Develop non-biased diagnostic algorithms. Also, consider Institutional Review Board-type data auditing boards or 3rd party auditing of data and algorithms to identify risks and bias.

Mitigating bias in data analytics and algorithms (public health institutions)

1. Use data and analytics to enhance decision-making processes: Create public health dashboards that are broadly accessible and communicate metrics stratified by race, ethnicity, gender and geography, focusing on reporting disparities. Invest in automated data capture and reporting that can produce closer to real-time insights to reduce process hurdles and increase the uptake of evidence-based programs by underrepresented communities.

2. Convene ecosystem partners to advance interoperability, such as enhancing the infrastructure for health information advances: Promote data sharing, interoperability and cross-agency/organization partnerships to be more effective in implementing and adopting programs and interventions.

Ensuring inclusive product and service design (healthcare payers and providers)

1. Ensure that cultural competency training, upskilling and credentials are embedded throughout the organization: Help meet cultural needs through third-party partners (e.g., SameSky, Violet Health, Spora Health). Engage community-based organizations and leaders from the beginning. Defer to the community via interviews and keep them engaged in the design experience to create culturally appropriate service designs and facilitate omnichannel care access.

2. Focus on improving the health literacy of members: Create Explanation of Benefits (EOB) guides and claims material simplified at a more accessible reading level with clear, multilingual and culturally tailored content. Payers can also collaborate with third parties that focus on outreach to specific populations (e.g., CityBlock Health).

3. Implement omnichannel engagement strategies: Provide high-tech or analog/lower-fidelity digital alternatives for people to choose from. Providers can co-design experiences with trusted community leaders (like faith leaders, teachers, librarians and EMTs) using community networks for patients through sustainable partnerships with community-based organizations.

Ensuring inclusive product and service design (biopharma companies)

1. Incorporate health equity considerations in early development and at launch planning: Organize a cross-functional team with individuals who represent specific patient populations by demographic, geography, or living conditions. Tailor marketing plans and materials to include diverse perspectives from the voice of the customer research to appropriately reach the target patient population and respective healthcare professionals.

2. Enhance the patient experience across their entire journey: Involve diverse patients and caregivers (across dimensions of age, race, socio- economic status, ability, etc.) in the design of the clinical trial protocol and associated planned experience. Incorporate more holistic segmentation and design mindsets to provide products and services tailored to specific communities thereby extending these thoughtful strategies across more disease states. Engage relevant partners (e.g., community-based, systems-based) to create patient support programs that drive care coordination beyond financial aspects, such as emotional support, transportation, etc.

Ensuring inclusive product and service design (public health institutions)

1. Develop health and life intervention: Develop and implement interventions to sustainably improve underrepresented groups’ health and overall life outcomes. This may also be done through collaborations, such as public-private and community partnerships, providing ridesharing to help with transportation barriers or leveraging funding tools, like state waivers, to approve broader use of Medicaid dollars for social services related to housing, food insecurity, transportation and interpersonal violence.

2. Influence health equity accountability: Use contractual agreements to hold key partners responsible for health equity. For example, state contracts with managed care organizations (MCOs) can ensure accountability for health equity goals and build momentum. States can also increase the emphasis on outcomes-based care as well as support and review to key partners to ensure a health equity lens is being applied at each step of the decision-making process.

Creating sustainable structural change (healthcare payers and providers)

1. Reinvent care delivery: New care delivery models must tie to payment innovation and address patient access and quality needs. Rising patient demand combined with decreasing provider supply will ultimately harm the most vulnerable among us. Health systems need to stabilize the existing workforce, source talent more flexibly, deploy top of license clinicians more effectively (focusing on what they trained to do) and reskill their teams

2. Move from unsustainable one-time philanthropic efforts to scaled social investments: These social investments aim to improve social, economic, and environmental conditions in vulnerable communities while simultaneously creating opportunities for financial returns for investors. These programs, such as Kaiser Permanente’s Thriving Communities Fund, address inequities at the root, generate value for the entire health system and empower underserved communities.

3. Align executive incentives to reducing disparities: Actions such as tying portions of annual executive bonuses to their success in reducing disparities create greater urgency, generate innovative and cross- functional solutions and prioritize health disparity initiatives. These incentives also create a trickle-down effect and permeate the rest of the company’s culture as leadership emphasizes these actions (e.g., SCAN Health Plan)

4. Develop care continuum plans that integrate clinical research: Every patient should have the opportunity to be matched to the best therapy for their personal situation, and that includes clinical research. In addition to clinical research improving adherence rates, underrepresented communities can access previously unavailable therapies.

Creating sustainable structural change (biopharma companies)

1. Ensure everyone can afford and access the latest medicines: Engage in innovative access models—pricing, distribution and contracting—that drive equity in access and reduce affordability barriers and further offset barriers for underrepresented communities through patient assistance programs, bridge programs, free trial offers and co-pay programs. Create new channels for access to services or treatments. Focus especially where communities of color are disproportionately impacted by lack of proximity to care for therapies that require access to a center of excellence (CoE) or academic center’s care. Ensure that access models drive equitable and broad access and that people from different demographic groups know, can access, and use these support programs.

2. Improve clinical trial diversity through multiple actions: Partner with non-traditional organizations such as retail pharmacies and local labs that are entering the clinical trial space to identify trial-ready, diverse patient populations quickly. Consider decentralized and hybrid clinical research methods to lower the barriers to entry that many marginalized communities face when accessing clinical trials. Develop diversity standards to ensure equal representation among investigators. Provide greater optionality for ways patients might engage with clinical trials in certain parts of the protocol. Identify target patient populations based on disease epidemiology and any social determinants of health that exasperate health status.

Creating sustainable structural change (public health institutions)

1. Implement more proactive public and institutional policies: Intentionally think about how underrepresented communities would fare and benefit when advancing regulatory actions, rulemaking, and other policy levers. Analyze past performance of decision impacts on disparate areas beyond health, from labor to demand for social services as part of policy formulation process. Include social risk factors such as dual eligibility, low-income and rural residency as variables in the payment structure so that providers who disproportionately treat these patients are not penalized due to worse outcomes.

2. Create key partnerships across the entire healthcare ecosystem: Create and lead interdisciplinary alliances that address the social determinants of health while including community members and leaders in these coalitions. Payers, providers, and community groups could better drive referral networks and organize tailored interventions if they worked together. Invest in and develop early- stage community-based organizations. Support the growth of early-stage organizations by connecting them with needed resources (e.g., government funding, infrastructure, technology tools).

The American Cancer Society’s Cancer Statistics 2023 report highlighted a few major accomplishments within oncology, such as decreased cancer mortality rates and increased trial diversity. However, there is still much work to be done. Especially with the multiple types of new and ongoing challenges clinicians and staff members are facing – such as high turnover rates, decreased budgets and increased feelings of burnout – taking the necessary steps to enhance clinical trial procedures is crucial to the continuous improvement of clinical trials and overall quality of life of cancer patients.

While there is not a “be-all and end-all” solution to these issues, one strategy clinicians can take is the implementation of modern eClinical and precision oncology solutions. These tools can help healthcare providers ease their staffing turnover pain, work within their assigned budgets and provide staff members with accurate tools to improve job performance and satisfaction. 

Clinicians Currently Face Multiple Up-Hill Battles 

Although it’s been three years since the COVID-19 pandemic emerged, its lasting effects have greatly impacted the quality, efficiency and overall success of clinical trials. With higher staffing turnover rates, decreased budgets and elevated feelings of burnout among staff members, trial workflows have suffered. Clinicians are currently faced with complex challenges and need modern strategies and tools to mitigate ongoing and arising obstacles.

Through precision oncology solutions, such as AI-enabled software, physicians and staff can automate traditionally manual processes, such as trial feasibility, patient-matching and data analysis procedures. Thus, improving the overall accuracy and efficiency of the trial, decreasing staffing turnover rates through mitigated feelings of burnout and enabling site workers to have more availability for training and development and engaging in higher-quality workloads.

AI’s Role in Mitigating Staff Burnout and Turnover Rates

Each staff member plays a crucial role in maintaining the quality of a trial through important procedures, including patient chart analysis and the identification of pertinent trial data. With recent high staffing turnover rates and elevated feelings of burnout, disruptions within critical trial tasks, such as patient-facing activities, decrease workflow efficiency and even place trials at risk of being terminated. Keeping these issues in mind, the investment in new solutions to enhance the overall well-being of staff members has never been more critical to trial and patient-outcome success.

Through AI-enabled precision oncology solutions, clinicians can provide their staff with the much-needed tools to increase the efficiency and success of trials without the burden of extra workloads. With these tools, staff members engage in various enhanced procedures including:

Increased Patient Engagement – The patient-facing portion of clinical trials is the most important aspect of a trial and the most affected by turnover rates. Disruptions within the patient-facing sector are cited as one of the main reasons trials fall behind and often why they are terminated. With increasingly heavy workloads, fatigued staff members continue to quit their jobs, risking disruptions to a very crucial sector within a clinical trial. By leveraging precision oncology solutions, clinicians can cut down the time spent on tedious manual tasks from multiple hours to just minutes. In turn, employees’ feelings of burnout are alleviated and hundreds of hours become available for staff members to spend increased time on activities such as engaging with and caring for patients, a crucial part of clinical trial timeliness and success.

More Time for Higher-Level Tasks – Lack of motivation, reduced personal accomplishment and overall exhaustion are stated within the National Library of Medicine as key factors in why healthcare workers leave their positions. The ongoing fluctuation of staff can lead to devastating financial impacts, as thousands of dollars are lost with each employee’s exit.

Through the automation of clinical trial workflows, physicians and staff can both enhance their overall quality of work and optimize time spent on tasks. Most of all, staff members have more time, energy and motivation to engage with projects they are most interested in, such as writing post-trial use cases and allocating more time toward the bench. This enablement of higher-level activities is a major factor in improving employee retention rates.

Working Within a Budget

Along with tackling high turnover and burnout rates, clinical research sites are also dealing with the burden of decreased trial budgets. Various factors, including inflation and practice profitability margins, have tightened the expenditures among many trials, leaving the significant task of being as successful and most cost-efficient as possible with the limited resources clinicians have.

Through an automated, data-driven approach to trial procedures, such as matching patients to intricate clinical trial protocols, processes are completed at an exponentially faster and more efficient rate. As physicians and staff face limited budgets and resources to address the needs of their patient population, leveraging tools led by artificial intelligence will provide them with the ability to work well within their budgeted hours and complete tasks in a timely manner. With benefits including the rapid analysis of structured and unstructured data – along with the ability to extract relevant information at any time – staff members can reduce their time spent on time-consuming and costly procedures from multiple hours to just minutes. 

This access will ultimately reduce workloads and enable physicians and their staff to maximize their budgeted hours and raise their confidence to accurately collect, transform and utilize patient data, without needing additional expenses to ensure the trial’s success.

Propelling the Success of Clinical Trials

Oncology has achieved great success this year and there’s even more to come. While precision technologies are not the sole solution to mitigating the multitude of external challenges clinicians currently face, they are a tool that can be leveraged to accelerate the efficiency and accuracy of trials. Technology removes many of the common challenges and time-consuming tedious tasks facing site workers that can lead to burnout. In helping these teams focus on the more critical, rewarding aspects of working with patients, it benefits all – the sites, sponsors and patients – in achieving even greater outcomes.

About Marie Lamont

Marie E. Lamont is the Global Head of RWE Data Strategy, Access & Enablement at IQVIA and General Manager at Inteliquet, a patient-matching clinical trial software company. She is the former president of the patient services business at Dohmen Life Science Services (DLSS), which was subsequently sold and is now part of EVERSANA. Prior to DLSS, Marie was global head of business strategy and commercial operations for rare disease at Sanofi Genzyme.

What You Should Know:

– Protai, a proteomics and AI-powered drug discovery startup revolutionizing the way new drugs are discovered, today announced a $12 million extension of its seed round, bringing the total amount to $20M.

– The round includes existing investors Grove Ventures and Pitango Healthcare and was joined by Copenhagen-based Maj Invest Equity Fund. The additional funding will be used to build Protai’s oncology drug discovery pipeline, expand data acquisition as well as increase its discovery activities via pharma partnerships.

Portai Launches Collaborations With Leading Hospitals and Expands Advisory Board

Genomic biomarkers are only relevant for approximately 15% of tumors, thus limited in use. Protein-level biomarkers can predict patient populations not seen by genomic means, by directly measuring proteins, their interactions, and their functions. To tap into the potential of protein-level data, Protai has built a proteomics AI-based platform that comprehensively maps the course of a disease on the protein level. Its technology allows it to better predict which patients will respond to a given drug, as well as discover novel drug targets that were missed by genomic approaches. These discoveries may be the key to significantly accelerating drug discovery and clinical development, lowering the time and costs of R&D.

Since its initial funding last year, Protai has opened laboratories at its Israel R&D center for data acquisition, biological validation and drug discovery activities and recruited an experienced drug discovery team with significant experience in successfully bringing drugs to the clinic. Additionally, Protai established collaborations with several leading hospitals, and now has access to over 100k well-defined banked samples for its comprehensive tumor mapping process, focused on gyno-oncology and lung cancer indications.

With the additional funding, Protai will expand its activities to include an oncology drug discovery pipeline, initially focusing on targets with a clearly-defined novel patient population biomarker, derived from its AI proteomics platform. To help navigate these efforts, the company has added Dr. Sharon Shacham, a serial biotech entrepreneur and Founder of Karyopharm Therapeutics, to Protai’s Board of Directors. In addition, Protai is supported by leading oncology experts, including Prof. Giulio Draetta, Chief Scientific Officer at MD Anderson and former Pharma executive; Prof. Bradley J. Monk, Director of Gynecologic Oncology at the St. Joseph’s Hospital and Director of GOG Partners; Prof. Funda Meric-Bernstam, Chair of the Department of Investigational Cancer Therapeutics at MD Anderson Cancer Center, and Dr. Jurgen Moll, former Head Molecular Oncology, Sanofi Vitry.

“We are excited to announce this funding that supports our mission to enhance the drug development pathway from discovery through to commercialization,” said Eran Seger, CEO and co-founder of Protai. “I am extremely proud of our talented team and the achievements we have made to date. We look forward to scaling our organization and its important work towards revolutionizing the drug development landscape.”

The United States only represents five percent of the world’s population; however, Americans consume 80 percent of the world’s opioids.¹ The U.S. is the world’s leader in the use of opioid medications to cope with physical and emotional difficulties. And the recent Walgreens and Wal-Mart multi-state opioid settlement agreement disclosures have only hammered home the point. America continues to have an opioid addiction problem. 

In light of all these circumstances, the recent CDC announcement that it was softening guidelines for U.S. doctors prescribing oxycodone and other opioid painkillers seems to stand in stark contrast to the current reality. With such significant, impactful reparations coming from the original guidelines and accompanying grim statistics, does it make sense to soften them so soon? The answer may surprise many, but for some, it’s yes. 

Relaxed CDC guidelines call for new investment in data and technology 

With the proper precautions, tools, and technologies to harness the data needed, loosening the guidelines will likely not significantly harm the outlook for SUD patients. Why? The more stringent restrictions didn’t blunt the crisis at hand. If anything, it even got worse. 

So, while the new guidelines place more decision-making power on physicians prescribing opioids, guidance without continuous monitoring and feedback can potentially worsen the crisis. And providers could easily find themselves further in the deep end if nothing else changes. They need a new path forward. 

Therefore, unlocking the correct data–at the individual patient and population levels–is critical to reversing this crisis. If providers could easily and securely access dynamic and actionable behavioral health data, they could develop more effective treatment plans based on a patient’s complete history. They could better assess addiction risk and make the best judgment on the type of care delivered. 

Severe SUD disparities prevent facilities from tackling significant challenges 

Nonetheless, behavioral health practices are years behind other healthcare fields when it comes to technology and tools, leaving them largely unprepared for the 

challenges of a nation in the throes of a mental health crisis compounded with record opioid addictions. The reasons are numerous, but a conspicuous absence from the incentives provided by the Health Information Technology for Economic and Clinical Health Act (HITECH) of 2009 certainly left behavioral health at the back of the pack for technology access and funding. A June 2022 report from Medicaid and CHIP Payment and Access Commission (MACPAC) further illuminated the issue, explicitly citing an extension of the financing through state Medicaid programs to drive health IT adoption as a decisive step to addressing gaps in access, outcomes data, and oversight. 

Data-driven SUD care enables high-powered opioid-ready interventions 

With many deficiencies and a growing opioid patient population, data insights unlocked through technological investment are the most effective path forward. And there are several data processes, best practices, and tools that facilities can utilize to build a solid future-ready data foundation ready to meet the challenges ahead. 

To start, providers should use an advanced data approach that absorbs, connects, and cleans data from multiple sources. When data is missing or of lower quality, leveraging advanced data science algorithms that account for the missing pieces can correct systematic errors in SUD and mental health data. Then, artificial intelligence and machine learning can take it to the next level by detecting meaningful patterns and insights in this data. And by implementing these powerful technological capabilities and innovations, behavioral health providers can more quickly and effectively make up for incomplete values and standardize disorganized data. 

Further, prescriptive analytics can deliver refined insight into risk and the best care protocol even with dirty or incomplete data (as with many SUD providers). Dynamic algorithms can quickly transform crude data into a product. In this way, providers can leverage predictive modeling to identify patterns demonstrating people at risk of developing substance abuse or opioid relapse. And the infrastructure for predictive capabilities already exists, including patient engagement solutions, electronic surveys, and analytics. Industrializing, standardizing, and making these capabilities available to all providers will augment individual patient care and the industry’s alignment to measurement-based care. 

Beyond raw data, implementations such as the social vulnerability index (SVI) can enrich patient-level information, providing the foundation for dynamic analytics. Moreover, care coordination and implementing innovative models and tools such as Accountable Care Organizations (ACOs) and Health Information Exchanges (HIEs) 

are imperative to driving the best patient outcomes and ensuring visibility across the patient care experience. 

This cooperation and new data implementations will empower a holistic patient treatment model, allowing everyone involved to make informed and educated decisions about patient care, including prescription opioids. And by harnessing the power of their data assets and proven advanced analytic capabilities that are already solving some of the most challenging SUD patient health complications, providers can also empower ongoing operational and clinical improvements. 

New data approaches and tech power the future of SUD and opioid treatment 

SUD providers have a significant opportunity to advance patient care, particularly when it comes to substance abuse and opioid addiction, by harnessing the power of increasing and ever-available data. Through data unlocked via novel technologies and approaches, facilities can identify predisposed patient populations, early warning factors, and signs of addiction. 

These information insights, enabled by data science, predictive algorithms, and other technology-first implementations and tools such as SVI, ACOs, and HIEs, will be crucial to combating the opioid epidemic in the coming years. By leveraging this toolbox, SUD providers can create more opioid challenge-worthy treatments from the start. The coming years and softened guidelines cause concern across the SUD community. It’s evident, however, that the needle barely moved even with more binding restrictions, without impactful analytics and insight. Consequently, dynamic and actionable data-driven modeling and the technical foundations to support it remain necessary course corrections that can provide substantial progress. 

About Jeremy Bloom, CEO of NorthSight Recovery

Jeremy has more than ten years of healthcare experience. During this time, he has held various senior and executive leadership positions where he gained expertise in organizational management, regulatory guidelines, and care delivery. Mr. Bloom has built alliances with key local and national stakeholders and has assisted in developing many programs, including psychiatric crisis centers, inpatient facilities, outpatient facilities, and patient-centered medical homes. Mr. Bloom is passionate about healthcare innovation and developing systems that take a data-driven approach to measure outcomes and costs to improve the overall delivery of healthcare services.

References

1. “Opioid Crisis: Table of Experts.” The Phoenix Business Journal, January 5, 2018, p. 16.

Today, food insecurity affects more than 41 million Americans and is prevalent among children and the elderly population. Food insecurity is defined as the limited availability of nutritionally adequate and safe food or the inability to acquire these foods in socially acceptable ways. As a result, food insecurity can exacerbate medical conditions driving up hospital/health systems patient care costs. To learn more about how healthcare providers can address food insecurity, we sat down with Dr. Arti Masturzo, Chief Medical Officer at CCS for her insights.   

How do you, as a healthcare professional, diagnose and help address food insecurity with patients today?

Dr. Arti Masturzo, Chief Medical Officer at CCS: As a practicing clinician, I see two specific challenges today when it comes to addressing and supporting individuals facing food insecurity. First, there is no consistency across the healthcare industry on how to screen and measure the severity of impact for individuals in relation to food insecurity. Even in standardized settings, like the hospital outpatient department where I see patients, we do the screening, but either the patient doesn’t answer honestly because they are embarrassed or they answer yes, but the clinicians, unfortunately, don’t have a way to immediately address it. One of the issues with electronic medical records is that these types of questions when they are asked of people, become part of the day-to-day paperwork and don’t get the attention they truly deserve. With many clinicians dealing with decreased staffing and increased workloads, these challenges are only further exacerbated.

In the patient population, I see — complex non-healing chronic wounds — I make it a point during the initial visit to specifically ask about social determinants of health (SDoH) in order to better understand what things I need to address immediately or be on the lookout for to best serve my patients. SDoH is not only critical to the successful healing and recovery of a patient but, if unaddressed, it’s often the cause of costly medical issues down the line.  

One of my top priorities as the first-ever Chief Medical Officer at CCS was to understand the social needs of individuals living with advanced diabetes. When we recently surveyed our customer base, we were shocked to learn that more than 10% of respondents living with diabetes indicated they have concerns specific to food insecurity, and 25% expressed low confidence in being able to always afford medical supplies. 

The single most important thing a patient can do to successfully manage their diabetes is to regulate what they eat. Someone living with diabetes should never have to choose between healthy food or medical supplies. 

How does food insecurity set back patients living with chronic diseases, like diabetes?

Dr. Masturzo: Food insecurity plays a major role in the overall well-being, care outcomes, and costs of care for people living with diabetes. Honestly, the quality of food a patient ingests is more important than any medical device or drug we can provide them as a clinician. I think we do a major disservice to people when we push technology and drugs on them as a solution to managing their diabetes if we aren’t, in tandem, having conversations and helping them access healthy food. Not only does food intake directly impact diabetes, but an unhealthy diet can bring on or worsen other chronic diseases such as cardiovascular disease or kidney disease.  

Does technology have a role to play in identifying and supporting patients living with food insecurities?

Dr. Masturzo: Technology is playing an increasingly important role in healthcare delivery, and studies have shown that even our elderly population can successfully use health-related technology with the right support. Technology can extend the bandwidth of clinicians who frankly don’t have the resources to address SDoH themselves. But technology isn’t always enough. Care teams must be on the front lines of accessing patient data to help risk stratify individuals facing serious SDoH challenges. More importantly, this burden should not fall on the clinicians alone; all healthcare organizations (clinical or non-clinical) can play a role when it comes to SDoH.  

Education, coaching, and improved access to healthy, nutritious foods are part of the solution to addressing both food insecurity and issues like obesity and even diabetes. Can you explain how CCS is uniquely offering holistic support for patients living with diabetes today?

Dr. Masturzo: Our team at CCS recognizes that the individuals we serve don’t just have diabetes; they have serious challenges when it comes to managing and controlling their diabetes. Additionally, many of the individuals we serve are living with other complex chronic conditions. We want to make sure that those we support, in addition to getting the necessary devices and prescribed drugs, have everything they need to successfully manage their diabetes at home. And part of holistic care is realizing that food truly is medicine, and care teams need to place equal emphasis on prioritizing patient access to affordable, healthy foods for people and their families.

What I’ve learned through my years of practicing medicine is that people must trust you before they will follow your guidance. Prioritizing patient engagement through disease-specific education and coaching improves outcomes and helps reduce the total cost of care. That’s why we work diligently to set people up to successfully utilize a medical device to manage their care — and why we also prioritize the collection of information on nutrition, activity, and sleep habits. Our CDCES-certified clinicians truly are trusted diabetes educators, and they play a crucial role in ensuring individuals understand how these various factors impact disease progression. 

How do you see providers and health plans evolving in the next five years to prioritize SDoH as an integral part of patient care and cutting costs related to chronic disease management?

Dr. Masturzo: From my broad experience in different sectors of the U.S. health industry and the time I spent watching medicine practiced in a developing country, I believe that we underappreciate just how much of an impact SDoH plays in health outcomes and cost of care. By doing so, we view SDoH as a complicating factor in healthcare delivery rather than the leading factor, thereby continuing to reinforce antiquated fee-for-service models of care that prioritize sick care over preventive, proactive care. 

Nutrition is a big component of chronic disease management, and I remain hopeful that there will be more scrutiny on what we allow companies to sell as food. I believe that in the next five years, there will be more awareness and regulation of “hidden” sugars, fats, and salt in prepared food. Regulatory bodies and food producers need to work together to ensure that prepared foods meet a minimum threshold of nutritional composition. We cannot cure financial insecurity overnight, but we can start by making sure that affordable and readily available food today isn’t making us sicker. 

In five years, my biggest hope is that the healthcare industry will have made major headway in adopting value-driven care best practices that put SDoH at the center of the care program as opposed to on the periphery. I am a firm believer that SDoH must be screened as the fifth vital sign. My main hope is that by 2028, SDoH is a care priority between clinicians and patient — and between industry and regulators. 

About Dr. Arti MacsturzoArti Macsturzo is a board-certified MD and a healthcare transformation executive with extensive experience in the delivery of services across multiple sites of care. As Chief Medical Officer, Dr. Masturzo pairs her strategic vision and passion for improving healthcare to guide the profitable growth of CCS Health solutions focused on diabetes care and other chronic conditions at home. She has nearly 20 years in medical leadership, including roles as CMO and a deep focus on clinical innovation across her career. Dr. Masturzo’s success is a result of a combination of factors, including strategic vision, operational mindset, collaborative approach, and a strong passion for helping improve patients’ lives by innovating care delivery models and fostering technology-enabled products and services that lead to measurable impact and positive change.

What You Should Know:

– Bicycle Health, a telehealth provider of integrated medical and behavioral health treatment for opioid use disorder (OUD) is teaming up with Wellpath, the premier provider of localized, compassionate care to vulnerable patients in challenging clinical environments, and the Federal Bureau of Prisons (FBOP).

– The collaboration will enable patients to access Bicycle Health’s evidence-based, life-saving clinical care model delivering virtual Medication for Opioid Use Disorder (MOUD) services to individuals living in the FBOP’s Residential Reentry Centers (RRC).

Opioid Use Disorder Treatment to Federal Bureau of Prisons

The collaboration will enable patients to access Bicycle Health’s evidence-based, life-saving clinical care model delivering virtual Medication for Opioid Use Disorder (MOUD) services to individuals living in the FBOP’s Residential Reentry Centers (RRC). Medications like buprenorphine – an FDA-approved medication that limits painful opioid withdrawal symptoms, helps prevent overdose, and supports long-term recovery – have been widely successful at curbing opioid use. The Substance Abuse and Mental Health Services Administration has found that MOUD treatment regimens are significantly underutilized in criminal justice settings. The primary goal of this collaboration is to improve availability and clinically appropriate utilization of MOUD among this underserved patient population.

Bicycle Health’s virtual treatment model, which has shown patient retention rates that are appreciably higher and no-show rates that are significantly lower than in-person averages, will deliver life-saving clinical and behavioral care to a population in need. The collaboration between Bicycle Health and Wellpath will provide improved access to MOUD in RRCs across 42 states, with plans to expand. Bicycle Health and Wellpath plan to grow the service to meet the recovery needs of formerly incarcerated patients – to improve their health, the overall health of the community, and reduce recidivism.

What You Should Know:

– Over the past few years, Artificial Intelligence (AI), and more specifically, Machine Learning (ML) technology, have experienced rapid adoption in the healthcare space as tools for diagnosis and decision-making. Such tools are intended to address challenges in the healthcare system to both processes and put into practice the proliferating medical findings, and also to support delivery of the promise of personalized and precision medicine.

– Unintended bias in AI and AI-driven healthcare applications is an evolving topic that developers, reviewers, and experts are still learning to address effectively and consistently. The Good Machine Learning Practices Working Team of the AFDO/RAPS Healthcare Products Collaborative believes the topic of bias could benefit from standard taxonomy, consistent approaches to identification, and addressing any identified sources of bias.

Understanding Bias in Artificial Intelligence

This is the third paper from the GMLP Working Team. The team is an industry-led volunteer team that has come together to lift the use, adoption, and implementation of AI through the teams’ collaborative and innovative efforts.

“Unintended bias in AI-enabled systems is a challenge in the development of ML algorithms,” says Pat Baird, working team co-chair and Sr. Regulatory Specialist at Philips.  “The whitepaper outlines a framework for bias opportunity detection, assessment, and mitigation of unintended bias that can be used by product developers.” Leveraging established and proven methods currently used for risk analysis in healthcare systems specifically for unintended bias should enable more robust management, adds Baird. The paper asserts that bias can occur at points in the data supply chain and product supply chain. While focused on product developers, the paper also discusses perspectives from regulatory reviewers or other stakeholders of these solutions.

Currently, medical devices that use AI-enabled algorithms utilize machine learning (ML) as a mechanism to “learn” during the algorithm development process. Being diligent about the identification and mitigation of unintended biases is important as a guard against bias impacting certain patient populations and resulting in inequities in healthcare delivery. Unless bias is circumvented, resulting reports of inequity may lower trust in the output of an AI-enabled medical device and create a barrier to the adoption of ML technology in healthcare.

Unintended bias in AI-enabled healthcare applications (including medical devices) will continue to be an evolving topic that developers, regulators, and experts must continue to address. This paper leverages existing risk management and related processes and proposes a framework for bias opportunity detection, assessment, and mitigation of unintended bias.

Here are the additional key take-aways from the paper regarding identifying and dealing with bias:

Initial Bias Analysis:

Identify the Intended Use of the System: The first step in mitigating bias in AI/ML-based systems is to define the intended use and indications for use of the system against which the impact of unintended bias can be measured. The intended use of a medical device is variously identified as the “use for which a product, process, or service is intended according to the specifications, instructions, and information provided by the manufacturer,” and “… should take into account information such as the intended medical indication, patient population, part of the body or type of tissue interacted with, user profile, use environment, and operating principle” while considering “reasonably foreseeable misuse.” For software systems, a more granular view of intended use and indications for use and an elaboration of the above definitions can be found in a technical report providing guidance for non-device regulated software. The description, however, applies across the spectrum of device and non-device systems. “

Identify Applicable Biases: Accordingly, a first step in determining the presence of unintended bias could be to identify known foreseeable sources and types of bias associated with the intended use of the system.

Estimate the Impact of Bias on Intended Use:  The next step would be to evaluate the impact of unintended bias on the intended use of the system. This could be achieved by:

● Providing a subjective narrative for each bias source/type/sequence combination that details the positive, negative, or neutral impact of the application of unintended bias on the intended use of the system.

● If the bias source/type/sequence combination has an impact on safety (including data privacy), then ensure the combination is considered as part of safety risk analysis.

● Establishing a qualitative scale to categorize each bias source/type/sequence combination incorporating the following elements:

● Likelihood that the bias source/type/sequence combination will occur during real- world use of the system.

● Likelihood that there will be impact to the intended use of the system if the bias source/type/sequence combination occurs.

● Degree (and categorical type) of impact to the intended use of the system if the bias source/type/sequence combination occurs. (Note: A more granular view of this attribute may be provided if there are variable degrees of impact each with a separate likelihood for that impact, given that the combination occurs.

● Scoring based on the qualitative scale of positive, negative, or neutral impact of the bias source/type/sequence combination to the intended use of the system.

● Indicator of safety impact or no safety impact (including data privacy) of the bias source/type/sequence combination.

Evaluate Bias:

Determine Acceptability of Each Bias: Based on the impact estimation above, determine whether each unintended bias source/type/sequence combination is acceptable (requiring no further mitigation) or unacceptable (requiring mitigations be identified and implemented). Consider one of the following methods for this determination:

– If a subjective narrative was used for impact estimation, provide a further narrative rationalizing whether the unintended bias source/type/sequence combination is acceptable or unacceptable.

– If a qualitative or quantitative scale was used for impact estimation, use a series of decision matrices to make the acceptability determination

Mitigate Unintended Bias

Determine Mitigations: For the unintended bias source/type/sequence combinations considered unacceptable, determine (and document in the bias analysis) mitigations (e.g., changes to requirements, architecture, design, data, code/algorithms, and/or algorithm training) necessary to bring bias source/type/sequence combinations to an acceptable state. The goal of determining appropriate mitigations is to reduce the likelihood that the bias source/type/sequence combination will occur, reduce the likelihood the bias source/type/sequence combination will have a negative impact if it occurs, and/or reduce the level of impact of the bias source/type/sequence combination.

Implement/Verify Mitigations: Where mitigations have been identified, implement them in the system using controlled design change and configuration management, where applicable. Verify implemented mitigations through both static and dynamic means (e.g., requirement reviews, technical reviews, code reviews, static code analysis, unit testing, integration testing, functional system testing).

Determine Residual Impact of Bias on Intended Use: Using the methods defined above to estimate and evaluate bias, determine the residual impact of unintended bias to the intended use of the system after bias mitigation mechanisms have been implemented and verified.

Determine Potential Bias Arising from Mitigations: Perform an estimation and evaluation of potential new or changed unintended bias source/type/sequence combinations that may arise from the implementation of bias mitigations. Where applicable, identify, implement, and verify mitigations on these new or changed bias source/type/sequence combinations.

Determine Completeness of Mitigations: Review all bias mitigation activities to ensure that the impacts from all identified bias source/type/sequence combinations have been considered and that all bias mitigation activities are complete.

Evaluate Overall Bias:

Determine Overall Acceptability of Bias in the Systems: Taking into consideration the residual impacts of all bias source/type/sequence combinations, determine whether the overall residual impact of bias source/type/sequence combinations is acceptable or unacceptable. If the overall impact is considered unacceptable, consider identifying and implementing further bias mitigations, making changes to intended use, identifying and documenting an acceptable benefit vs. bias assessment (refer to next paragraph), or reconsidering whether to release the system in its current configuration.

Articulate Benefit vs. Bias: For unintended bias source/type/sequence combinations that remain unacceptable, gather and review data to determine if the benefits of the intended use of the system (e.g., technical, clinical, economic) outweigh the residual impact for this specific combination. Consider also making an overall benefit vs. bias determination at the system level. If the benefits do not outweigh the residual impact, consider further system design changes (including bias mitigations and/or changes to intended use), or reconsidering whether to release the system in its current configuration.

Disclose Residual Bias: Disclose known residual bias source/type/sequence combinations including their predicted impact on the intended use of the system to relevant internal and external stakeholders (e.g., company management, customers, users, regulatory authorities). This may be done via a formal report, release notes, instructions for use, or other applicable communication mechanisms. In support of transparency, clear disclosure of intended bias needs to be disclosed as well

Some people think of retail pharmacists as standing behind the counter bottling pills, answering insurance questions, or discussing side effects with a customer.  

But the COVID pandemic fundamentally changed the role of the neighborhood pharmacist, from primarily dispensing medication to increasingly being the source of urgent and primary care for patients.  With the successful administration of more than 300 million COVID vaccinations, an ongoing doctor shortage, and healthcare deserts in large parts of the country, the need for this transformation has never been more evident.  

Pharmacies are increasingly well-positioned to serve at the start of the healthcare continuum by providing easy access to clinical services, medication therapy management, immunizations, and walk-in patient consultations.  With 95 percent of Americans living within five miles of a pharmacy and healthcare provider shortages impacting communities across the country, it only makes sense that pharmacists become first-choice providers for a growing number of clinical services.  Pharmacies are now the “front door” to health care.  

Driven by the Biden Administration’s Test-to-Treat program, pharmacies are now in the process of going beyond immunizations into areas such as infectious disease, prescribing hormonal contraceptives, tobacco cessation, medical nutrition therapy and preventive counseling.  

Pharmacists’ role as health care providers will reach an unprecedented scale, making it easier than ever for patients to access basic care, creating business opportunities for pharmacies to provide more health care services to the communities they serve.    

Recognizing the role pharmacists are ready and able to play as accessible, convenient health care providers, Kentucky became the first state in the nation to enable pharmacists to offer potentially life-saving colon cancer screenings in 2022.  Making it easier for patients to access colon cancer screenings is just the latest example of the expanding, patient-centric, clinical role pharmacists play and is a trend to watch in the delivery of health care.

Filling the Void

The United States has been facing a primary care physician shortage that is only projected to get worse.  According to the American Association of Medical Colleges (AAMC), “a shortage of up to 122,000 physicians is projected by 2032, including up to 55,000 in primary care and 66,000 in other specialties.”

Supporting retail pharmacies as they fill the care gap left by physician shortages and transition to an effective, patient-centric clinical services business model requires real-time communication and seamless data sharing among pharmacists, diagnostic providers, physicians, and patients.  Linking the care team together in a way that provides for not only the efficient delivery of care but efficient provider billing with full interoperability will be essential to the long-term success of pharmacies as providers of clinical services. 

The need for simplicity and interoperability of pharmacy data management systems and patient communications solutions has never been greater.  Today’s community pharmacy can only optimize patient care and profitability with technology solutions that empower pharmacists with improved efficiencies in billing and workflow, and that provides easy access to patient records to bring actionable data and functionality to the point of care, when and where it’s needed. 

Interoperability makes it possible for quick configuration and synchronization of ever-evolving data-sharing formats and protocols, enabling quick response to new requirements and opportunities as they arise over time.   

Among the top 10 benefits of choosing the right HIPAA-compliant, SaaS-based platform that promotes vendor-neutral and device-agnostic interoperability that enables sharing and reuse of curated patient health data sets are:

– Delivering more patient-centric healthcare services that cater to the patient community

– Executing and documenting flawless clinical encounters from start to finish

– Using a billing-enabled EHR that guides documentation for effective patient encounters, follow up and billing.  Establishing timely billing practices to ensure optimal reimbursement and pharmacy revenue growth

– Surging adoption of electronic medical records now means there are many new formats that have generated additional demands for better integration.  Bridging data and imaging silos across and between institutions using semantic ontological frameworks

– Protecting privacy and compliance through multiple security layers, including: 

   – User access authentication

   – Access and permissions defined by an administrator

    – Full audit traceability with role-based access control

    – Data encryption in transit and at rest

– Ensuring always-updated software helps avoid situations like the recent Southwest Airlines technology debacle that led to the cancellation of thousands of flights.  By using cloud-based solutions, pharmacy users can always have automatic access to the latest software versions, without ever having to deal with maintenance or costly, time-consuming software updates. The platform itself and the data pool would both be scalable

– Analyzing data,  including documenting and reporting quality of care metrics and transforming information into actionable insights, can lead to searching individual patient records to visualize longitudinal patient encounters.  However, search “like” functionality at the patient population level can help pharmacies visualize distinct disease characteristics, distinct patient biomarkers and other characteristics such as outcomes

– Elevating pharmacists to the role of a care provider will require efficient credentialing but will also empower freedom of movement to other states.   Credentialing and payor enrollment tools will help pharmacists get enrolled, contracted, and credentialed so they can deliver more clinical services more efficiently and get reimbursed for them

– Implementing crucial provider collaboration that runs across all verticals

– Collaborating with data-sharing APIs that ingest data and deliver it across disparate platforms

Will pharmacists seize the empowerment opportunity? 

Only with true interoperability will pharmacists be able to increase revenues, collaborate effectively, enhance operating efficiencies, improve health outcomes, and lower the costs of healthcare management.  

Working with clinical and financial data in today’s extremely complex healthcare environment is extraordinarily challenging. Even with the best platform, experience and expertise are essential to properly combine and utilize technology elements so that analytics can make sense of and convey accurate and meaningful information and manage it all intelligently, and to be more informed it is necessary to take healthcare training in a continuous manner

Simplified interoperability in the pharmacy greatly improves efficient access to information and makes pharmacies less reliant on any one system or technology.  With the right system, pharmacists can have at their fingertips electronic access to patient’s lab and immunization history, companion vaccine opportunity identification, immunization registry and public health reporting, prescriber communication and targeted outbound patient communications – all to keep the pharmacist and their patients in sync at the center of care.  

Time is of the essence to make data system improvements and stay ahead of the rapid transformation of the pharmacy industry as it evolves from a medication dispensing model to a clinical care service model.  

There has never been a greater call for technology-empowered pharmacists to step in to fill healthcare provider voids and to deliver the kind of accessible, convenient patient-centric care expected today.  The technology is ready.  Are America’s pharmacists?

About David Pope, PharmD, Chief Pharmacy Officer

In his role as Chief Pharmacy Officer at XiFin, David drives the company’s innovation and product portfolio strategy for pharmacy. He is a nationally-recognized expert in medical informatics and clinical services in the pharmacy space, and has served as an advisor for the Center for Disease Control (CDC) as well as multiple Fortune 500 healthcare-related organizations.

The material cost of COVID-19 has been at the center of public discourse since the early days of the pandemic. In 2020, growth in federal government spending on healthcare increased 36 percent, compared to the 5.9 percent bump in 2019. While the distribution of vaccines has allowed for a version of pre-pandemic life to resume, hospitals are still not recovered from the high rates of hospitalizations that occurred in March 2020, and the indirect costs of the pandemic continue to loom over the American population as a result of strained health systems. 

During the early days, the cost of hospitalizing a patient seemed obvious: the sheer volume of long stays, expensive ventilators, a lack of one-size-fits-all treatment solutions, and the pause of elective surgeries. Now, Covid-19 continues to wreak havoc on our health systems, but in a more covert way. With only 4% of Americans fully boosted as we move into this winter’s ‘triple-demic’ – and long covid impacting the lives of as many as 16 million people on a daily basis – it’s clear that public health officials need to do more in order to support the American population and our struggling health systems. 

The Cost of Healthcare Provider Burnout 

Across the country, healthcare providers are reporting extreme rates of burnout. It is important to underscore that healthcare providers and hospital systems were stressed prior to Covid-19, but the pandemic has exacerbated it. Employment across healthcare is down 1.3 percent, or 223,000 jobs, from pre-pandemic levels. Over 90 percent of nurses said they are considering quitting their jobs by the end of 2022 in a survey, with 72 percent of nurses stating they had already experienced burnout before March 2020. In addition, the increased stress that doctors have experienced is resulting in worse patient care – with 28% of doctors who reported burnout sharing that the quality of care they are providing has significantly declined. 

We are amid a mass healthcare provider exodus, and, according to estimates, each instance of physician turnover costs healthcare organizations at least $500,000, and each instance of staff registered nurse (RN) turnover costs $46,100. Without proper staffing, hospitals are at risk of closure and patients’ health is at risk of worsening. 

The Cost of Hospital Closures 

Before the pandemic, hospitals closed for several reasons, including insufficient staffing, lack of funding, and/or having a large uninsured patient population. Since March 2020, 21 hospitals across the United States, predominantly in rural areas, have closed. Health systems are still recovering from the significant loss of revenue from canceled appointments – according to a report from The Chartis Center for Rural Health, 82 percent of the rural hospitals surveyed said suspension of outpatient services resulted in a loss of at least $5 million per month. 

So, what happens when hospitals and health systems close? 

Rural areas experience more Covid-19-related deaths than urban communities and public health experts attribute these deaths to the rampant hospital closures, as well as a general lack of healthcare providers. It is a vicious cycle: Covid-19 strains hospital systems, healthcare professionals leave, hospitals close, and more patients will die from infectious diseases like Covid-19, the flu or respiratory syncytial virus (RSV) – not to mention the other reverberating public health complications that come as a result of these closures. Vaccinations have helped these hospitals stabilize, but to keep up with covid fatigue and the ever-evolving variants we need a variety of treatments in our arsenal. 

More Covid-19 Treatments Will Bolster Struggling Health Systems  

Increasing the number of vaccinated individuals around the world, in addition to broadening access to effective non-vaccine treatments, such as antivirals and monoclonal antibody therapies, will significantly lessen the impact of the disease on individuals and lessen the burden on the healthcare system. Antiviral treatments have proven to reduce hospitalization, but diversity in treatments is essential to keep up with the ever-evolving Covid-19 variants. Dr. Andrew Pavia, chief of pediatric infectious diseases at the University of Utah Health, was quoted on the effectiveness of antivirals: “If there is anything we know about viruses and antiviral drugs is that eventually, we will see some sort of resistance.” For the time being, antivirals are effective – this is not a call to leverage one type of therapy over another – this is a call to help patients and our health systems survive by equipping healthcare professionals with as many treatments as possible. 

One such treatment that has proven highly effective when applied properly are neutralizing monoclonal antibody therapies. Like antivirals, monoclonal antibodies reduce hospitalization, the risk of death, and shorten the length of the infection – resulting in better patient outcomes and stronger health systems. 

According to Yale Medicine, it is estimated that about three percent of the United States population, or up to 25 million individuals, is considered moderately-to-severely immunocompromised, making them more at risk for serious illness if they contract Covid-19, or other viruses. Monoclonal antibodies are a highly safe and efficacious treatment, which is extremely important for this vulnerable population, especially as a complement to vaccines for prevention. An infusion can reduce the risk of hospitalization by 80 percent or more in a high-risk person, and unlike antivirals, monoclonal antibodies target specific parts of the virus spike protein leading to fewer side effects and interactions with other drugs. 

Collaboration between the government and the biotech industry will be essential for creating a portfolio of therapies to treat a variety of patient profiles who experience a range of Covid-19-related health issues. With our healthcare systems in such a precarious state, investing resources in the development of these treatments will prepare hospitals for future variants that threaten the health of our nation. The hope is that by bulking up our Covid-19 hospital response strategy, our already volatile health system will have a chance to recover, increase individuals’ access to quality healthcare, and ensure a healthier population. 

About Eugene Y. Chan, MD 

Dr. Chan is a physician-inventor. He is currently Chairman, Co-Founder of Abpro, CEO of rHEALTH, and President, CSO of DNA Medicine Institute, a medical innovation laboratory.  He has been honored as Esquire magazine’s Best and Brightest, one of MIT Technology Review’s Top 100 Innovators, and an XPRIZE winner. His work has contributed to the birth of next-generation sequencing, health monitoring in remote environments, and therapeutics. Dr. Chan holds over 60 patents and publications, with work funded by the NIH, NASA, and USAF.  Dr. Chan received an A.B. in Biochemical Sciences from Harvard College summa cum laude in 1996, received an M.D. from Harvard Medical School with honors in 2007, and trained in medicine at the Brigham and Women’s Hospital.  He is one of few individuals who has been in zero gravity. 

Patient data in electronic health records (EHRs) holds a wealth of insights that can enable health systems to better serve their patient populations.  

However, data from EHRs is challenging because this data is messy due to the lack of standardization in how clinical data is collected, and often times valuable information is buried in unstructured fields such as notes. Additionally, EHR data is disconnected from EHR data at other sites of care resulting in an incomplete view of the patient.  

For example, there are dozens and dozens of ways for blood pressure to be recorded in an EHR. Aggregating data from many EHR sources need to have quality processes in place to ensure the standardization of clinical information like blood pressure is reliable.  

Having the ability to scrub and accurately aggregate data from multiple clinical systems is step 1 in the process of empowering health systems to gain a fuller picture of their patient population. Layering on top of this aggregated data set the ability to match patients across clinical sources and even tie it to claims data allows health systems to unlock the true power of their clinical data.  

EHR data in action: Insights into long COVID
The primary advantage of EHR data is the low latency compared to the 90-day lag of claims data. For example, in the early stage of the pandemic, clinical researchers in collaboration with the COVID-19 Patient Recovery Alliance needed to study patients with long COVID-19. EHR data proved particularly important during this time before there was an ICD code to identify COVID patients. Researchers were able to look at the free-text notes about symptoms and diagnoses for patients who had COVID within EHR data. The ability to analyze timely, early COVID-19 data enabled researchers to obtain insights that they would have had to wait months to extract from more structured forms of data, such as claims. 

The long-COVID analysis was based on COVID-19 infection and vaccination data gathered during a 15-month period from February 2020 to May 2021. The study included about 1.1 million patients infected with COVID-19, of which more than 240,000 had available a complete longitudinal history prior to the pandemic as well as at least one encounter with a healthcare provider at least eight weeks after their COVID-19 diagnosis. 

Key findings from the study include:

– Patients who received at least one dose of any of the three COVID vaccines (Pfizer-BioNTech, Moderna, and Johnson & Johnson) prior to their diagnosis with COVID-19 were up to ten times less likely to report two or more long COVID symptoms compared to unvaccinated patients. 

– Unvaccinated patients who received their first COVID-19 vaccination within four weeks after SARS-CoV-2 infection were up to six times less likely to report multiple long-COVID symptoms.

– Those who received their first dose 4-8 weeks after diagnosis were three times less likely to report multiple long-COVID symptoms compared to those who remained unvaccinated.

– Vaccination had a protective effect even when the first dose was administered up to 12 weeks after diagnosis.

Despite the many challenges posed by the COVID-19 pandemic, there is one key difference that enabled our 21st-century response compared with past public health challenges: timely EHR data. To fight such a devastating virus, the world did not have time to wait for years-long randomized controlled trials to reveal every single detail about vaccine response. We needed timely data to enable immediate action, and, ultimately, the aggregation and organization of patient records have given us the tools to create a better recovery.

About Jake Hochberg

Jake Hochberg is Executive Director of Customer Insights for Arcadia, a leading data analytics platform for healthcare and life sciences, transforming data from disparate sources into targeted insights, putting them in the decision-making workflow to improve lives and outcomes.