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For payers, RoboticProcess Automation (RPA) provides a way to address all three challenges.

The healthcare industry is not a newcomer to RPA adoption. Payers have used the technology for a handful of tasks such as extracting structured and unstructured data, pre-authorization of services claims processing, and to exchange data with providers.

Now, in the shadow of COVID-19, there has been a rising demand for applying RPA to a wider range of processes. These include speeding up claims processing, enhancing customer care through chatbots, improving new enrollments through data enrichment and validation, renewing contracts, meeting regulatory requirements through data interoperability, and enabling a remote workforce by automating day to day IT tasks (for example, incident response) and administrative processes (related to finance, human resource,etc.). The range of use cases is wide.

The urgency for payers to deploy RPA implies that they need to be cautious as well. RPA can be applied in several areas — all with varying benefits—and evaluating and prioritizing the functions where the technology could deliver the highest and fastest ROI can be tricky. With the right decisions, RPA will deliver on its promise.

According to a report called “Intelligent Automation in Healthcare: Addressing COVID-19 Scenarios” published by global management and strategy consulting firm, Zinnov, the areas where RPA has proven ability include:

• Claims Adjudication
• Customer Support
• Regulatory Reporting
• Claims Data Management
• Interoperability

Once a payer has identified a business function wherein RPA can be applied, the next step is to implement the technology where it will result in cost reductions, productivity increase, risk reduction, and improved patient and employee experience, in the shortest possible time. ROI and time-to-value are important considerations. Both determine the amount and pace of investments the payer can commit to, on RPA. This is where 91���� makes a substantial difference. Our team of healthcare technology experts has studied the impact of COVID-19 on payers and has created a Special Task Force with a single mandate: to identify critical pain points that payers need to address and provide cost-optimal, easy-to-implement, and high ROI yield solutions.

We execute leveraging our catalog of process frameworks that can be applied to IT and business along with a library of ready-to-use bots. These need minimal refinements and customizations (to align them with the goals and the needs of individual payers) to achieve a faster time to value. Our industry and processes mining expertise allow us to quickly identify the automation opportunities in a payer’s environment. We stitch the solution in line with enterprise mandated business outcomes ensuring that the business is ready for automation at scale. The automation can be for practically any process ranging from member enrollment to premium collection and from claims settlement to reporting.

RPA can be deployed by our experts quickly and precisely, to reduce the cost of claims processing that COVID-19 is bound to lead to, provide augmented support to producers/agents to improve and onboard new enrollments, and alleviate the pressure of claims management caused by the imminent spike in elective procedures. For a detailed examination of use cases where RPA can deliver an immediate impact, please download the Zinnov – 91���� joint whitepaper.

Authors:

Manish Jaiswal
Vice President, 91����

Sanjana Bhattacharya
Principal Consultant, 91����

Nikhil Kulkarni
Principal, Zinnov

AV Ruchir
Project Lead, Zinnov

References:

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Data to save lives

The ask in this pandemic is the sharing of information and best practices at every level from local to global. All stakeholders including governments, pharmaceuticals, hospitals, and citizens need to work together to shift from the diagnosis and cure of the disease to the prediction and prevention of disease.

IT teams across care delivery ecosystems are working tirelessly to ensure that clinical applications such as EHR, LIMS, and other supporting IT systems are working, thus ensuring access at every point of care. Analytics can also help in effective population health efforts by identifying patients who are risk-prone to COVID-19 as well as other homeless patients to narrow their efforts and deploy proactive outreach efforts to check COVID-19 spread. Also, data can be facilitated by the work of care teams creating new alerts systems and methods to stratify COVID-19 patients, helping medical support teams and nurses in decision care delivery. Researchers at Stanford University have launched an interactive, data-driven model that evaluates possible outcomes of non-pharmaceutical interventions for COVID-19, including social distancing and quarantine².

Telehealth to be the frontrunner of the new care delivery model

With an ever-increasing number of infected patients, COVID-19 has demanded unparalleled coordination and collaboration between private and public healthcare. Physicians, nurses, and other care supporting teams are leading the fight at ground zero. Telehealth can provide contactless care-in-need and thus minimizes the risk transmission. Also, patients in isolation can communicate with their families and friends with mobile phones, tablets, etc., and doctors can remotely monitor vast numbers of patients that are recovering at home.

In the US, CMS, its nodal agency for healthcare regulations, has eased rules around telehealth, allowing physicians to care for patients at rural hospitals via mobile, radio, or online communication – without having to be physically present. Physicians are changing the patterns of their practice because of the COVID-19 pandemic, with nearly half of them using telehealth to treat patients, up from just 18% in 2018³.��Most countries in the EU have also embraced telehealth and have deployed telehealth solutions and relaxed regulatory requirements attached to it.

The 91���� Advantage

91���� helped a leading��not-for-profit integrated health delivery system provider in the US and provided a comprehensive analytics-driven engagement platform for patient outreach to address gaps in care. ITC implemented a CRM solution that impacted over 200 Contact Agents and 345K patients. The one-stop customer intelligence platform reduced patient phone call-time by ~14%, improved ROI by 3.5%, and improved productivity of the patient experience team by 22% respectively.

91���� has also recently developed a mobility solution for the COVID 19 surveillance for John Hopkins University. This surveillance applet will help to predict the outburst of Covid-19 in a specific area or county across the US and help healthcare communities & other government authorities to take corrective action as necessary to stop COVID spread.

Improving healthcare is not a singular effort. You need assistance from specialists who can plan a roadmap for you and make the digital transformation seamless. With our healthcare technology experts, you can make the shift from legacy systems to on-cloud cutting-edge technologies.

Moving toward a digitized and connected value care delivery healthcare ecosystem is the need of the hour and we can facilitate the change for you.

Author:
Jeewan Das Mohta
Lead Consultant- Healthcare

Reference:

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The surge in demand for healthcare services has been crippling. Test kits, masks, Personal Protection Equipment (PPE), ventilators, sanitizers, hospital beds, isolation facilities, nursing staff and telemedicine capacity are scarce. The message in the big picture is sharp: It is not enough for the healthcare industry to be reactive.

What can healthcare providers do differently to stay better prepared?

The simplest step to take is to adopt a platform thinking approach. Using platforms, most solutions can be strategized in 3 days, designed in 3 weeks and developed/deployed in 3 months. These digital platforms draw their power from the ability to suck in vast amounts of near real-time data. They are embedded with analytical engines, AI and ML capabilities. They can track the health of populations and identify people at risk, enable real-time visibility of supply chain risks, provide supplier quality visibility and more important provide patient personalisation capabilities at scale.

91����’s Intelligent Planning for Resilience (see Figure 1 for architecture) is one such unique solution that combines the power of early warnings, rapid simulation for anticipating impact across the supply chain and connected planning to help rewire the organization for superior “resilience” (see Figure 2). It is a “must-have” capability for healthcare providers. With a platform like this, healthcare businesses can respond effectively to the next emergency.

Figure 2: Intelligent Planning for Resilience

The platform, with a rich library of pre-built accelerators, is bundled with a rapid deployment methodology –3 days for strategy, 3 weeks for design and 3 months for development for the first minimal viable product.

Intelligence-led digital capabilities are now the source of differentiation and competitive advantage. More than that, coordinated data management and analytics will ensure providers become pro-active and respond to developing emergencies with accuracy. Whether it is quality-based reporting, financial modelling, or projects such as personalized health and science discoveries, they will benefit from platform thinking to deploy solutions at scale and speed.

We call these ‘Platforms of Intelligence’—systems that are designed to address the future of healthcare and remain resilient in the face of the toughest medical challenges.

To see if your business could benefit from our Platforms of Intelligence write to contact.us@itcinfotech.com

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For years, the most prominent model of healthcare delivery was fee-for-service. The patient would approach the provider for treatment in exchange for reimbursement by the patient’s payer. This was a very transactional interaction where the treatment results were not tracked and healthcare costs simply kept spiraling. The reason: progress of the patient’s health condition was inconsequential to healthcare organizations; they were paid for the treatment provided regardless of the outcome. Eventually, there was a realization, especially among regulators, that there is�� need for a new direction that ensures the ultimate wellbeing of the patient.

This gave way to the introduction of value-based care. Under this new paradigm, the focus was on the patient. Providers would be reimbursed based on the patient’s health outcomes. This evidence-based approach ensured higher quality in care delivery and curtailed healthcare costs. This would specifically benefit patients with chronic conditions. Providers would have the incentive to work towards bringing down the incidence of such diseases in new patients and lowering their impact in existing patients.

Value-based payment programs are now present in as many as 48 states and 50% of these programs are multi-payer in scope¹.��

All Healthcare Stakeholders Stand to Benefit

1. Lower costs – Chronic diseases like cancer, high blood pressure, diabetes, etc., demand ongoing care and healthcare bills keep piling up. If the focus is on a healthier lifestyle, they will recover faster and have fewer doctor’s visits. Naturally, spends on medical procedures and prescription medications will be contained.
2. Lower health risks – Mortality as well as chances of acquiring new diseases are risks that can be curtailed. This leads to fewer claims, which further help reduce the burden on payers’ pools.
3. Better quality ratings, provider efficiency and patient satisfaction – Quality of care is the key focus in value-based programs. It ensures that providers do not waste time and resources on unnecessary tests and procedures. Financial gains from volume-based care cease to remain the driving force for providers. This ensures better patient care, which leads to better patient experiences.
4. Increase in supplier profitability – The products and services of suppliers get automatically aligned to patient outcomes. This reduces costs and improves the efficiency of the whole ecosystem. Individualized therapies might witness tying up of drug prices to actual value the patient derives.

Pay-for-Performance Programs

There are numerous quality-based programs that have been formed by various health stewards to help organizations keep track of their performance with regards to delivering quality care to patients. The idea is to measure performance across key quality metrics as defined by the steward. In return, the providers are reimbursed only if value has been delivered to the patient. These programs monitor aspects of healthcare delivery such as quality, effectiveness, patient experience, etc. Thus, the concept of financial incentives is more redefined when compared to the earlier fee-for-service model.

Role of Data

The healthcare ecosystem is comprised of huge data reservoirs such as medical records captured in EHR, lab results, insurance claims, patient demographics, clinician notes, etc. All this data provides a great opportunity to analyze performance across the care continuum and identify insights to guide patients towards a healthy path. The volume of data is increasing at an unprecedented pace. Today, there is a need for�� big data architecture implementation together with advanced analytics and machine learning algorithms to derive actionable insights.

Physicians and provider members must be made aware of these insights to reduce costs, improve efficiency of the system and help patients lead healthier lives. One of the primary objectives of value-based care is population health management. A comprehensive view of the member is imperative to make it possible. Here’s how it can be achieved: Clustering techniques to segment the population based on similar characteristics. Predictive analytics to identify a set of population that is most likely to remain noncompliant with expected health standards. Focused attention and new strategies can then be executed to deal with the illnesses of such patients.

Using descriptive analytics, we can find out critical areas to focus on for each quality-based program. This will help in not only improving provider performance and score but also in identifying the right levers to achieve higher financial profitability.

The 91���� Advantage

91����’s Healthcare Insights platform is a state-of-the-art quality management solution called Quality Maximiser, which comprises of predefined quality measures (regulator driven or defined in-house), business workflows and advanced analytics capabilities to engage members effectively for gap closure and improved member experience.

The performance across programs can be visualized through highly insightful dashboards. Predictive and prescriptive analytics are applied to identify members in need of interventions and recommendations for their wellbeing.

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SDOH Factors contribute to about 40% of variation in health status among individuals^2.��Despite the impact of SDOH on a patient’s health outcomes and costs, providers and payers are not equipped to address the several social determinants including housing, education, food security, and economic stability.

Understanding The Problem

It is important to understand the factors, other than medical, affecting the life of an individual.��
Factors like housing, food security, access to care, etc., are concerns that may affect the health of the population. An approach of SDOH-led quality initiatives lies beyond the four walls of the clinical setting. Data gathering, with screening tools, focus groups, community congregation, etc., is required to gain an understanding of key social factors that impact population health. In the process of data collection, consider factors that are vital to population health, significant for the care giver/provider and health insurers, since these factors might not be related and may belong to different datasets all together.

Thinking Beyond The Walls

New interventions need to be developed for quality improvement activities to tackle issues attributable to SDOH. Also, an intervention that works with one population set may not work for another.�� Minimal or no attention to SDOH factors can lead to failure of understanding of the problem for the given population set. Quality improvement programs that directly address SDOH will need to engage representatives from housing, transportation, education, public safety, school, social care, and beyond. Due to the varied spectrum of stakeholders, it might create new challenges for implementation because of separate priorities, funding streams, etc. Nevertheless, it is the only way to address interlocking influences on health. It is to be noted that this approach does not undermine the inclusion and efforts of nurses, caregivers, providers, administrators, etc., in quality improvement activities.

Developing New Measures Of Success

As the healthcare ecosystem moves towards a value-based care delivery order, it has become useful for the payers and providers to have the inclusion of new quality measures, keeping in line with the changing landscape. This also signals the next step in the direction of population health management. Chicago-based Advocate Health Care, an ACO, reduced healthcare costs by $3,800 per patient, by screening all patients at admission for malnutrition risk, resulting in $4.8 million in total savings. Patients with increased risk scores were given an oral nutritional supplement within two days of admission, The ACO also saw hospital readmission rates drop among patients at risk for malnutrition, within six months of launching quality improvement initiatives ³. In another example, healthcare spending fell by 11% when the payer addressed SDOH⁴.

New measures may include�� SDOH elements like employment rates, number of dependents, distance to nearest care center, educational qualification, access to clean environment, availability of daily food, etc. (Exhibit 1). With the inclusion of new quality measure and processes, it will help stakeholders to understand and address these SDOH factors in a meaningful manner. This will also define and build new engagement levels that go beyond clinical settings.

Exhibit 1: Measuring SDOH Interventions

Conclusion

To address health outcomes associated with social determinants of health, physicians, payers, policymakers, communities, and individuals need to understand the role these factors play in individual and community health, and focus their efforts in reaching out to the maximum number of people possible. Integration of social determinants into the health care system delivery may help in reducing health disparities, improve quality of care delivered and reduce cost. Social determinants of health is bound to have an impact on health, as it is a critical component that cannot be ignored in the healthcare ecosystem.

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The Partnership to Fight Chronic Disease estimates that by 2030, 83 million people in the U.S. will have three or more chronic health conditions, up from 31 million in 2015².

Chronic conditions are the leading cause of death & disability and a leading driver of US annual healthcare cost. US healthcare costs for chronic diseases such as heart disease, cancer, diabetes, and Alzheimer’s disease totaled $1.1 trillion in 2016. If the lost economic productivity is accounted, the total economic impact was $3.7 trillion. This is equivalent to nearly 20 percent of the US gross domestic product².

As per CMS estimates, healthcare spending is expected to continue to grow at an average of 5.5 percent through 2025, with chronic disease treatment comprising a major portion of it. Chronic diseases eat up significant healthcare dollars for payers and other health organizations, leaving them with challenges of covering care for patients with these expensive, long-term conditions.

Analytics to drive care value

By 2020, it is estimated that the amount of individual health information will double every 73 days³. Data gathered from structured and traditional sources, IoT devices, and large sets of unstructured big data information can help create new-generation tools that can bring us better insights, dependable recommendations, and real-time feedback.

As care delivery continues to evolve from reactive disease treatment to proactive preventive care, more healthcare organizations are looking at advanced technologies like artificial intelligence and machine learning to assist in drawing actionable items from their big data resources.

Analytics is playing an increasingly important role in risk stratification. For instance, it helps predict which individuals might develop chronic conditions such as diabetes or heart failure. Integrating such actionable insights into payer and provider prevention initiatives, clinician workflow, and patient engagement activities can help raise awareness of risk for both clinicians and patients. It can lead to the recommendations for evidence-based preventative measures to reduce risk.

Healthcare organizations can follow these steps to utilize analytics in chronic care management within their own workflows:

• Identify the sources of data in healthcare, both internal and external.
• Apply analytics model to specific healthcare challenges in chronic management, such as managing pre-diabetes and diabetes at the population level.
• Use observations and actionable insights from analytics to achieve desired care outcomes

Having advance knowledge pertaining to chances of contracting a disease paves the path for effective prevention and improves patient care. Preventing chronic diseases or at least managing symptoms when prevention is not possible can reduce costs.

The 91���� Advantage

91����’s Healthcare Insights platform allows payers and providers to leverage big data, analytics, artificial intelligence and machine learning to gain actionable insights for healthcare enterprises.

Improving healthcare is not a singular effort. You need assistance from specialists who can plan a roadmap for you and make the transformation seamless. With our healthcare technology experts, you can make the shift from legacy systems to on-cloud cutting-edge technologies.

Moving toward a connected value care delivery healthcare ecosystem is the need of the hour and we can facilitate the change for you.

The post Role of Analytics in Managing Chronic Conditions appeared first on 91����.

Artificial Intelligence has been around the block for a while now. It aims to imitate the way cognitive functions work in humans. Essentially, AI is the application of machine learning concepts, be it support vector machines, neural network, deep learning or natural language processing. The most important features of AI are its self-learning and correcting abilities. By analyzing large volumes of data, AI can be used to assist all healthcare entities in hospitals, insurance and clinical trials. It can be leveraged to build proactive protocols where real-time inferences are used to make predictions and take action before an adverse event occurs.

AI Applications in Healthcare

Automation of Jobs¹

Providers and radiologists spend a lot of time analyzing test results, CT scans, X-rays, etc. These are mundane tasks that can easily be taught to a machine based on rules and repetition. Image recognition/computer vision technologies are capable enough to analyze and draw inferences from images. AI-based systems can reduce the workload on medical personnel tremendously, while delivering results fast and more accurately.

Complex data analysis²

Clinical data takes diverse shapes as medical notes, doctor’s prescriptions, EMR data, lab images, patient history and so on. Specific applications of AI are capable of making sense of this data and finding hidden patterns that can be used to discover new ways of handling sick patients. Unstructured data is usually difficult to leverage and there are possibilities that some critical information is missed by medical professionals. Using AI we can analyze this data more effectively and provide additional information to doctors to make the process of diagnosing diseases faster and more efficient.

Health Treatment^{1, 2, 3}

Disease management is another area where AI can help physicians in coordinating the care and managing chronic diseases. By identifying which patients display high-risk probability, physicians can focus their resources on the more critical patients. Customized treatment paths that are specific to an individual can be devised and monitored even on a real-time basis. Patients’ social and economic factors can be taken into consideration to deliver much more effective care. Predictive analytics can aid clinical decision-making.

Precision Medicine^{1, 3}

Personalized care by understanding genetic data, EHR data, wearables and other lifestyle data has gained popularity in recent times. AI can be used by doctors to develop precision treatments for complex diseases. The insights can come handy in discovering new ways of using old drugs, creating new ones and predicting risk of diseases in patients. Drug discovery costs and errors can be brought down by creating huge datasets of patients and running AI algorithms to develop precision treatments.

Drug Discovery¹

A lot of research is involved in the process of creating drugs. AI can be used to analyze clinical trials, research papers, patient records and patents. Relationships between biological entities such as symptoms, proteins, diseases and genes can be inferred easily using machine learning algorithms. Assessment of drugs during clinical trials requires sophisticated pattern recognition and AI is capable of performing this. The whole process of drug discovery can be made cost effective and faster by using machine-learning-driven programs.

Member Experience

Healthcare members today are demanding a retail-like experience. They want quick responses and expect the healthcare insurers to not only pay their bills but also make sure they are healthy. AI-powered Chatbots and Virtual Assistants can speed up the dissemination of information to members and reduce errors. Another use of AI is in bringing out the element of personalization. By using non-traditional data sets like social determinants of health (poverty, economic condition, etc.), demographics, psychographics and attitudes towards health in hand with traditional data sets of claims and medical records, 360-degree member views can be created. The approach is to use machine learning algorithms across these views to predict member behaviors. Using this information, targeted and relevant communication and recommendations can be sent to members to improve efficacy of care activities. Apart from this, AI can also be used to analyze member feedback and predict which members are likely to be dissatisfied with services rendered, making preemptive action possible.

The 91���� Advantage

91���� offers its expertise in AI and machine learning along with deep domain knowledge. Using, machine learning algorithms, our solutions offer advanced analysis and insight capabilities working on large volumes of data. We endeavor to change the existing healthcare landscape and solve critical problems using advanced analytics and AI-based solutions which will improve patient lives, reduce mortality rates, reduce costs, improve profitability and lead to a much enhanced patient/member experience, consequently high patient/member satisfaction.

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According to a famous RAND study, American adults receive recommended care only 55 percent of the time ³. The gaps in treatment lead to avoidable complications, ER visits, and hospitalizations — a major component of the waste in the system. Additionally, understanding and managing patient risks is a huge problem for population health today

Evolving healthcare policies and rise in consumerism place a heavy burden on organizations to improve patient care outcomes, while reengineering patient engagement.

Putting PHM to work

As the industry continues its transition from volume-based to value-based healthcare, it is important to proactively identify population segments that are in need of care as well as apply differential and relevant care strategies for patients while also focusing on reducing costs, improving experiences and driving appropriate utilization.

The pivot for success in this new value-care-driven ecosystem is maintenance or improvement of patient’s health and reduction in cost of care. The way forward is managing population health effectively and efficiently.

Population health management (PHM) programs are key to clinical and financial success under value-based care delivery models. It begins with risk stratification of the population to identify patients who have the greatest health risks (therefore, pose financial risks to the organization).

PHM requires a high degree of intelligent automation to assess and reach everyone in the population, engage patients in self‐care, and maximize the chances of each person receiving proper preventive, chronic, and acute care when needed. The health system needs vendors who can deliver a comprehensive solution that unifies data, analytics, and services.

The 4 broad pillar of PHM program are:

• Member Stratifications: The purpose of stratification is identifying members based on the risk that they carry, for e.g. complex care (multiple comorbid conditions). These patients can then be targeted and care can be delivered effectively.

• Performance Reporting: The healthcare system needs an efficient performance management framework to track performance against industry programs such as ACO, MIPS Star, etc., and help analyze care delivered at the individual patient level.

• Care Gap Management: Using a unified care management solution, payers and providers can collaborate to improve the health of the patient by closing any identified care gaps. Timely closure of gaps leads to healthy patients and improved financial reimbursements.

• Member Engagement: 80% of a member’s health is dependent on non-clinical factors. By employing personalized engagement strategies, members can be empowered to get invested in taking care of their own health.

How 91���� can help!

91����’s ‘Healthcare Insights’ is a big data analytics platform that supports population health initiatives. It helps healthcare organizations measure and track performance of services delivered. It leverages machine learning to predict performance and patients who are likely to not receive optimal care.

With nearly a decade’s experience in working with healthcare organizations globally, 91���� has developed significant experience in helping payers and providers improve quality of care delivered, care coordination and engagement. We bring our strong consulting skills and technology expertise supported by pre-built analytical assets. The combination makes 91���� the preferred strategic partner for advisory, data analytics and information management the world over.

Healthcare Insights – Improving Patient Outcomes

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