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Matt Brow, President and General Manager, Pharmacy, InovalonThis relies heavily on tracking and reporting systems that can turn clinical information into shareable data and the ability to align pharmacy workflows with regulatory requirements and profitability goals.
The keys? technology and data.
Inovalon addresses these needs with its industry-leading cloud-based SaaS solutions, which securely capture, store, and leverage data to drive better patient outcomes.
Inovalon serves the pharmacy, payer, provider, and life sciences markets through the Inovalon ONE® Platform. The Platform drives efficiency and improves patient outcomes for specialty and infusion pharmacies nationwide with the ScriptMed® suite of products, which are revolutionizing the pharmacy segment.
ScriptMed combines advanced analytics, real-time primary source data access, and national-scale connectivity in a sophisticated, cloud-based solution. It focuses on the specific requirements of pharmacies serving patients who have complex medical conditions and require highcost drug therapies. With its distinctive and unmatched capabilities, ScriptMed enables specialty and infusion pharmacies to manage all of their patients, including specialty infusion, home infusion, and ambulatory infusion patients, holistically and at scale within a single system.
In order to determine the best interventions and escalations to achieve exceptional health outcomes, ScriptMed accesses clinical protocols and patient-specific data insights and streamlines many of the communications and information exchanges between partners and approved pharmacy stakeholders.
Automation of processes and incorporating data-driven workflows enable pharmacies to improve the delivery of patient care while increasing staff and cost efficiency. “Our solutions allow customizable workflows that customers control and configure to align with their needs without requiring vendor-supported enhancements,” says Matt Brow, President and General Manager of Pharmacy at Inovalon.
One of Inovalon’s unique attributes is its primary source database, which delivers the information a pharmacist needs within the ScriptMed pharmacy system in real time, often eliminating the need for additional outreach that can cause delays.
In a recent instance, the Inovalon ONE Platform gave Walgreens Specialty Pharmacy access to disease codes, patient medical histories, and other information critical to getting the patient started on therapy faster.
Inovalon also assists payers with quality improvement software and risk adjustment accuracy software that ingests enormous amounts of payer data and uses predictive analytics to help them raise their quality scores and risk adjustment accuracy.
Our solutions allow customizable workflows that customers control and configure to align with their needs, without requiring vendor-supported enhancements
For providers, Inovalon delivers software to optimize revenue cycle management, care quality management, and workforce management in a single-sign-on, easy-touse portal.
In an effort to better serve specialty and infusion pharmacies, Inovalon is collaborating with organizations that are looking to expand their operations and gain access to networks and limited distribution products. With its real-time data access, Inovalon seeks to optimize pharmacy operations and workflows. Inovalon’s seamless process empowers pharmacists to work faster, ensure timely payment, and allow patients to begin treatment sooner.
Company
Inovalon
Management
Matt Brow, President and General Manager, Pharmacy, Inovalon
Description
Inovalon is a leading provider of cloud-based SaaS solutions, serving the pharmacy, payer, provider, and life sciences markets through the Inovalon ONE Platform. The Platform drives efficiency and improves patient outcomes for specialty and infusion pharmacies nationwide.
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Inovalon News
Inovalon and HealthVerity Partner to Advance Use of Real-World Evidence in Research
New Research From Inovalon and Harvard University Finds Medicare Advantage Beneficiaries Have Superior Quality Outcomes Relative to Traditional Medicare
Data Shows Lack of Care Management and Coordination of Services in Fee-for-Service Medicare Leads to Lower Quality of Care and Worse Outcomes
• Medicare Advantage (MA) has 70% fewer readmissions than Fee-for-Service (FFS) Medicare
• MA has 24% fewer preventable hospitalizations than FFS, primarily driven by 59% fewer preventable acute hospitalizations
• MA has 21% lower rates of high-risk medication use, while overall medication use is in line with FFS
BOWIE - Inovalon, a leading provider of cloud-based software solutions empowering data-driven healthcare, and Harvard Medical School researchers today released new research that shows Medicare Advantage (MA) delivers superior quality and health outcomes relative to traditional Fee-for-Service (FFS) Medicare. Using Inovalon’s unique data assets and analytics to look at a broad range of quality measures across care settings, the research shows that patients enrolling in MA realize substantially reduced rates of chronic and acute care complications. The findings are the latest to be released from the first-of-its-kind research collaboration with Inovalon and Harvard Medical school and builds on earlier research showing substantial inpatient utilization reductions under MA.
MA now covers more than half of Medicare beneficiaries, including a disproportionately large share of socioeconomically disadvantaged patient populations. Despite the growing popularity of MA plans, limited information is available on how care quality differs under MA and FFS coverage. The study, “Quality Outcomes Under Medicare Advantage versus Medicare Fee-for-Service,” found consistently better quality outcomes under MA than FFS, including 70% fewer readmissions under MA. MA also had 24% fewer preventable hospitalizations, with 59% fewer preventable acute hospitalizations. In addition, the study found 21% lower rates of inappropriate high-risk medication use under MA while overall medication use was similar in MA and FFS.
“The study provides strong evidence that care management and coordination are key to better outcomes,” said Boris Vabson, PhD, health economist at Harvard Medical School and co-lead researcher on the project. “While recent reforms such as the introduction of Accountable Care Organizations (ACOs) have attempted to improve Medicare care management, our research shows additional steps are needed to improve care coordination and quality of care under Fee-for-Service Medicare.”
To quantify the impact of MA vs. FFS on key quality outcomes, the research team analyzed quality measures for a large, nationally representative population over a two-year timespan as beneficiaries transitioned from commercial insurance to MA or FFS coverage, while accounting for pre-existing differences prior to Medicare enrollment. This unique study was made possible through the use of data from Inovalon’s Medical Outcomes Research for Effectiveness and Economics (MORE2) Registry®, the nation’s largest primary source healthcare dataset covering 100% of public Medicare lives and 30% of all private insured lives.
“We believe this data can help health plans identify opportunities for quality improvement, especially for those in our health system who have been historically underserved and are at higher risk of needing complex care,” said Christie Teigland, PhD, Vice President of Research Science and Advanced Analytics at Inovalon and co-lead researcher on the project. “Under the new CMS Health Equity Index framework, it will be imperative for health plans to address socioeconomic disparities to improve 5-Star ratings and qualify for bonus payments. Our research gives them the insights they need to maximize financial incentives and, most importantly, promote health equity and deliver better health outcomes.”
Future research will look at specific, actionable opportunities for improving care quality and outcomes from a policy and plan design perspective.
• Medicare Advantage (MA) has 70% fewer readmissions than Fee-for-Service (FFS) Medicare
• MA has 24% fewer preventable hospitalizations than FFS, primarily driven by 59% fewer preventable acute hospitalizations
• MA has 21% lower rates of high-risk medication use, while overall medication use is in line with FFS
BOWIE - Inovalon, a leading provider of cloud-based software solutions empowering data-driven healthcare, and Harvard Medical School researchers today released new research that shows Medicare Advantage (MA) delivers superior quality and health outcomes relative to traditional Fee-for-Service (FFS) Medicare. Using Inovalon’s unique data assets and analytics to look at a broad range of quality measures across care settings, the research shows that patients enrolling in MA realize substantially reduced rates of chronic and acute care complications. The findings are the latest to be released from the first-of-its-kind research collaboration with Inovalon and Harvard Medical school and builds on earlier research showing substantial inpatient utilization reductions under MA.
MA now covers more than half of Medicare beneficiaries, including a disproportionately large share of socioeconomically disadvantaged patient populations. Despite the growing popularity of MA plans, limited information is available on how care quality differs under MA and FFS coverage. The study, “Quality Outcomes Under Medicare Advantage versus Medicare Fee-for-Service,” found consistently better quality outcomes under MA than FFS, including 70% fewer readmissions under MA. MA also had 24% fewer preventable hospitalizations, with 59% fewer preventable acute hospitalizations. In addition, the study found 21% lower rates of inappropriate high-risk medication use under MA while overall medication use was similar in MA and FFS.
“The study provides strong evidence that care management and coordination are key to better outcomes,” said Boris Vabson, PhD, health economist at Harvard Medical School and co-lead researcher on the project. “While recent reforms such as the introduction of Accountable Care Organizations (ACOs) have attempted to improve Medicare care management, our research shows additional steps are needed to improve care coordination and quality of care under Fee-for-Service Medicare.”
To quantify the impact of MA vs. FFS on key quality outcomes, the research team analyzed quality measures for a large, nationally representative population over a two-year timespan as beneficiaries transitioned from commercial insurance to MA or FFS coverage, while accounting for pre-existing differences prior to Medicare enrollment. This unique study was made possible through the use of data from Inovalon’s Medical Outcomes Research for Effectiveness and Economics (MORE2) Registry®, the nation’s largest primary source healthcare dataset covering 100% of public Medicare lives and 30% of all private insured lives.
“We believe this data can help health plans identify opportunities for quality improvement, especially for those in our health system who have been historically underserved and are at higher risk of needing complex care,” said Christie Teigland, PhD, Vice President of Research Science and Advanced Analytics at Inovalon and co-lead researcher on the project. “Under the new CMS Health Equity Index framework, it will be imperative for health plans to address socioeconomic disparities to improve 5-Star ratings and qualify for bonus payments. Our research gives them the insights they need to maximize financial incentives and, most importantly, promote health equity and deliver better health outcomes.”
Future research will look at specific, actionable opportunities for improving care quality and outcomes from a policy and plan design perspective.
Inovalon and Amazon Web Services Collaborate on the use of AI/ML to Improve Healthcare
Advanced AI/ML Together with Large Training Datasets and Enhanced Logical Scaffolding Show Significant Promise of Superior Performance
BOWIE - Inovalon, announced at its annual Customer Congress event in Washington, D.C. a collaboration with Amazon Web Services (AWS) to develop superior software solutions to support the healthcare industry’s pursuit of better outcomes and economics. The combination of AWS’ Artificial Intelligence (AI) products, including Amazon Comprehend Medical, further enhanced through the application of logical scaffolding informed by Inovalon’s AI/machine learning (ML) capabilities and deep subject matter expertise is yielding superior results when compared to previously available technologies.
The collaborated capabilities are being developed for multiple applications across the broader Inovalon ONE® Platform, the Company’s SaaS-based software platform supporting more than 20,000 customer organizations across the healthcare ecosystem. Demonstrations being provided today at Inovalon’s Customer Congress event include a next-generation capability pertaining to health plan risk score accuracy improvement software.
Health plans primarily depend upon medical documentation and medical claims to determine the disease burden, or risk score, of the members of their managed populations. This risk score is then utilized to inform the application of appropriate resources to support members’ health care needs as well as accurate payments and reimbursements. Unfortunately, meaningful disconnects exist between medical documentation and claims data resulting in an incomplete understanding of patient disease status, progression, and care needs, as well as inaccurate payments and reimbursements. As a result, health plans expend significant resources to more accurately understand and substantiate their members’ risks scores.
While Natural Language Processing (NLP) technologies have been applied within the healthcare industry to aid in the capture and analysis of risk score information, the industry’s currently available NLP solutions struggle to tease out key data points from the medical records without an extremely high false positive rate. Further, today’s solutions fail to provide meaningful targeting insight to guide a clinician, medical record reviewer, or auditor to precisely where an area of concern within a patient’s case documentation may lie. The net result is lower accuracy within risk scores, lower understanding of individual patient’s disease status and care needs, higher costs related to accuracy-improving initiatives, and greater risk to health plans with respect to their inadvertent submission of inaccurate risk score data which can lead to potential legal liability and financial penalties.
The NLP/ML powered application being developed collaboratively by Inovalon leverages AWS’s Amazon Comprehend Medical® NLP service to derive insights from unstructured clinical text and map clinical concepts to standardized medical codes like ICD10-CM. The enriched output from Comprehend Medical is combined with a logical scaffolding created from Inovalon’s AI/ML capabilities and deep subject matter expertise. The result is an advanced capability to analyze targeted member medical records to identify those that are highly likely to have meaningful disconnects between the clinical documentation and that of the claims data associated with the patient. Additionally, the solution not only is able to determine the probability of such disconnects being statistical true positives, but also highlight where the evidence which supported a concern resides. The result is a solution that empowers users with powerful insights and enriched patient-level data with greater risk score accuracy to augment claim review efficiency and decrease costs. Inovalon expects the application to be generally available early in 2024.
“Our focus is on the relentless enhancement of the Inovalon ONE Platform so that we can in turn empower our customers to achieve their missions,” said Eron Kelly, President of Inovalon. “This is the first of several collaborations we are doing with AWS to empower our customers to improve healthcare outcomes and economics through the thoughtful and careful use of AI/ML.”
“AWS’s expertise in the practical use of AI/ML technologies alongside Inovalon’s leadership in healthcare data and analytics can help deliver more efficient and accurate healthcare applications,” said Tehsin Syed, GM Health AI, AWS. “Medical documentation and claim review solutions built with these technologies can offer health plans a wide range of benefits, including reduced effort and cost.”
BOWIE - Inovalon, announced at its annual Customer Congress event in Washington, D.C. a collaboration with Amazon Web Services (AWS) to develop superior software solutions to support the healthcare industry’s pursuit of better outcomes and economics. The combination of AWS’ Artificial Intelligence (AI) products, including Amazon Comprehend Medical, further enhanced through the application of logical scaffolding informed by Inovalon’s AI/machine learning (ML) capabilities and deep subject matter expertise is yielding superior results when compared to previously available technologies.
The collaborated capabilities are being developed for multiple applications across the broader Inovalon ONE® Platform, the Company’s SaaS-based software platform supporting more than 20,000 customer organizations across the healthcare ecosystem. Demonstrations being provided today at Inovalon’s Customer Congress event include a next-generation capability pertaining to health plan risk score accuracy improvement software.
Health plans primarily depend upon medical documentation and medical claims to determine the disease burden, or risk score, of the members of their managed populations. This risk score is then utilized to inform the application of appropriate resources to support members’ health care needs as well as accurate payments and reimbursements. Unfortunately, meaningful disconnects exist between medical documentation and claims data resulting in an incomplete understanding of patient disease status, progression, and care needs, as well as inaccurate payments and reimbursements. As a result, health plans expend significant resources to more accurately understand and substantiate their members’ risks scores.
While Natural Language Processing (NLP) technologies have been applied within the healthcare industry to aid in the capture and analysis of risk score information, the industry’s currently available NLP solutions struggle to tease out key data points from the medical records without an extremely high false positive rate. Further, today’s solutions fail to provide meaningful targeting insight to guide a clinician, medical record reviewer, or auditor to precisely where an area of concern within a patient’s case documentation may lie. The net result is lower accuracy within risk scores, lower understanding of individual patient’s disease status and care needs, higher costs related to accuracy-improving initiatives, and greater risk to health plans with respect to their inadvertent submission of inaccurate risk score data which can lead to potential legal liability and financial penalties.
The NLP/ML powered application being developed collaboratively by Inovalon leverages AWS’s Amazon Comprehend Medical® NLP service to derive insights from unstructured clinical text and map clinical concepts to standardized medical codes like ICD10-CM. The enriched output from Comprehend Medical is combined with a logical scaffolding created from Inovalon’s AI/ML capabilities and deep subject matter expertise. The result is an advanced capability to analyze targeted member medical records to identify those that are highly likely to have meaningful disconnects between the clinical documentation and that of the claims data associated with the patient. Additionally, the solution not only is able to determine the probability of such disconnects being statistical true positives, but also highlight where the evidence which supported a concern resides. The result is a solution that empowers users with powerful insights and enriched patient-level data with greater risk score accuracy to augment claim review efficiency and decrease costs. Inovalon expects the application to be generally available early in 2024.
“Our focus is on the relentless enhancement of the Inovalon ONE Platform so that we can in turn empower our customers to achieve their missions,” said Eron Kelly, President of Inovalon. “This is the first of several collaborations we are doing with AWS to empower our customers to improve healthcare outcomes and economics through the thoughtful and careful use of AI/ML.”
“AWS’s expertise in the practical use of AI/ML technologies alongside Inovalon’s leadership in healthcare data and analytics can help deliver more efficient and accurate healthcare applications,” said Tehsin Syed, GM Health AI, AWS. “Medical documentation and claim review solutions built with these technologies can offer health plans a wide range of benefits, including reduced effort and cost.”
Inovalon Announces Converged Submissions To Support Health Plan Risk Adjustment Programs
Medicare and Commercial Affordable Care Act Plans Can Easily Deploy New Cloud-Based SaaS Solution to Submit Encounter Data to CMS to Support Their Risk Adjustment Programs, Improve Compliance, and Drive Stronger Economic Performance
BOWIE - Inovalon, a leading provider of cloud-based software solutions empowering data-driven healthcare, launched Converged Submissions today to simplify and improve encounter data submissions in support of risk adjustment programs. This cloud-based SaaS solution is part of Inovalon's Converged Risk Solution Suite and analyzes encounter data to determine risk adjustment eligibility and deliver complete and accurate encounter data submissions on demand. Health plans with risk-adjustable lives using Converged Submissions receive proactive insights to validate data, correct errors, and prioritize submission efforts to achieve higher first-pass acceptance rates for greater financial impact and efficiency.
The Centers for Medicare & Medicaid Services (CMS) requires Medicare Advantage (MA) plans, Medicare-Medicaid plans, and Commercial Affordable Care Act (ACA) plans to submit encounter data that is used to evaluate and accurately reimburse the health plans. Incorrect submissions and errors can delay payments anywhere from 6 to 18 months and must be corrected to avoid financial impact or regulatory penalties. Most solutions available today are reactive and wait to correct claims that CMS rejects causing further delays and acceptance rates as low as 80%. Health plans using Inovalon’s solutions average 94% to 99% acceptance rates.
Converged Submissions leverages customer data feeds and analytics informed by Inovalon’s MORE² Registry®, the nation's largest longitudinal primary source healthcare dataset, to train an advanced pre-validation and correction analytics engine, empowering a superior error catch rate and auto correction of data capability. Combined with comprehensive, up-to-date regulatory and submission rules algorithms, these capabilities are designed to maximize first-pass acceptance rates for help health plans, reduce expensive errors, avoid claim rejections from CMS and the Department of Health & Human Services (HHS), and accelerate reimbursements. Additionally, Converged Submission’s cloud-based architecture provides for industry-leading scalability, reliability, and on-demand usability so that customers of all sizes can undertake data submission updates easily and at whatever frequency they may want, enabling greater financial visibility and end-to-end reporting transparency.
"Lack of subject matter expertise in encounter data submissions and evolving CMS requirements lead many health plans to overspend on labor and technology, or worse, miss submission deadlines, which leads to delays in payments," said Mike Jones, President and General Manager at Inovalon. "Health plans need insights into the complex risk adjustment submissions process and solutions that adhere to CMS regulations. Converged Submissions fulfills these requirements across encounter data and supplemental data submissions in a highly accurate, efficient, fully integrated product suite that reduces the likelihood of delayed reimbursements."
Powered by the Inovalon ONE® Platform, Converged Submissions is fully interoperable with Inovalon’s complete Converged Solution Suite for health plans to optimize quality initiatives, value-based care agreements, risk score accuracy, member engagement, and more. Customers of any one of Inovalon’s Converged Solution Suite products can easily activate additional products within the suite, reducing time-to-impact, avoiding redundant data provision risks and costs, and increasing operator team efficiency.
BOWIE - Inovalon, a leading provider of cloud-based software solutions empowering data-driven healthcare, launched Converged Submissions today to simplify and improve encounter data submissions in support of risk adjustment programs. This cloud-based SaaS solution is part of Inovalon's Converged Risk Solution Suite and analyzes encounter data to determine risk adjustment eligibility and deliver complete and accurate encounter data submissions on demand. Health plans with risk-adjustable lives using Converged Submissions receive proactive insights to validate data, correct errors, and prioritize submission efforts to achieve higher first-pass acceptance rates for greater financial impact and efficiency.
The Centers for Medicare & Medicaid Services (CMS) requires Medicare Advantage (MA) plans, Medicare-Medicaid plans, and Commercial Affordable Care Act (ACA) plans to submit encounter data that is used to evaluate and accurately reimburse the health plans. Incorrect submissions and errors can delay payments anywhere from 6 to 18 months and must be corrected to avoid financial impact or regulatory penalties. Most solutions available today are reactive and wait to correct claims that CMS rejects causing further delays and acceptance rates as low as 80%. Health plans using Inovalon’s solutions average 94% to 99% acceptance rates.
Converged Submissions leverages customer data feeds and analytics informed by Inovalon’s MORE² Registry®, the nation's largest longitudinal primary source healthcare dataset, to train an advanced pre-validation and correction analytics engine, empowering a superior error catch rate and auto correction of data capability. Combined with comprehensive, up-to-date regulatory and submission rules algorithms, these capabilities are designed to maximize first-pass acceptance rates for help health plans, reduce expensive errors, avoid claim rejections from CMS and the Department of Health & Human Services (HHS), and accelerate reimbursements. Additionally, Converged Submission’s cloud-based architecture provides for industry-leading scalability, reliability, and on-demand usability so that customers of all sizes can undertake data submission updates easily and at whatever frequency they may want, enabling greater financial visibility and end-to-end reporting transparency.
"Lack of subject matter expertise in encounter data submissions and evolving CMS requirements lead many health plans to overspend on labor and technology, or worse, miss submission deadlines, which leads to delays in payments," said Mike Jones, President and General Manager at Inovalon. "Health plans need insights into the complex risk adjustment submissions process and solutions that adhere to CMS regulations. Converged Submissions fulfills these requirements across encounter data and supplemental data submissions in a highly accurate, efficient, fully integrated product suite that reduces the likelihood of delayed reimbursements."
Powered by the Inovalon ONE® Platform, Converged Submissions is fully interoperable with Inovalon’s complete Converged Solution Suite for health plans to optimize quality initiatives, value-based care agreements, risk score accuracy, member engagement, and more. Customers of any one of Inovalon’s Converged Solution Suite products can easily activate additional products within the suite, reducing time-to-impact, avoiding redundant data provision risks and costs, and increasing operator team efficiency.
Tough RCM Questions with Michael Quinn from Inovalon
AI for Revenue Cycle Management (RCM) is hot topic right now. Are we heading for a day when RCM will be completely automated? Is that the path we are on and if so, is it a good path? Hear honest answers to these and other tough questions.
To explore this topic, Healthcare IT Today, wanted to ask an executive that works in this area to come on-camera for a “Tough Questions” interview. Michael Quinn, VP of Strategic Partner Development at Inovalon, graciously agreed to participate.
Inovalon is a company that offers a platform that brings together national-scale connectivity, real-time primary source data access, and advanced analytics in a cloud-based platform. The company’s analytics capabilities are used by 53,000 sites of care.
Watch as Michael Quinn answers these tough RCM-related questions:
1. AI is the hottest technology at the moment. It is EVERYWHERE. But has AI made any meaningful improvement to the RCM process?
2. Since RCM processes are so standardized, are we heading for a day when it will be completely automated and not require any people?
AI is Making Meaningful Improvements to RCM
In his response, Quinn highlighted the nebulous definition of AI. The science-fiction definition of AI that is human-like in behavior, is not real (yet). He is skeptical of these types of outlandish claims.
“However, AI that refers to data mapping, language, and analytics – that is something that can benefit healthcare right now,” said Quinn.
This more practical application of AI has Quinn excited and he believes that it will have a positive impact on RCM.
People Are Still Important for RCM
According to Quinn, since many RCM processes are standardized and repeatable, they are a good candidate for automation, especially AI-enhanced process automation. Although Quinn believes that one day AI may automate many RCM processes, he does not believe this is something that will happen soon, nor does he believe that the entire process can be done with out human oversight or intervention.
“I don’t think we can ever, nor should replace human intervention,” stated Quinn. “We need human beings to be part of the process. The rules for payments are constantly changing and there are always exceptions that need to be handled uniquely.”
To explore this topic, Healthcare IT Today, wanted to ask an executive that works in this area to come on-camera for a “Tough Questions” interview. Michael Quinn, VP of Strategic Partner Development at Inovalon, graciously agreed to participate.
Inovalon is a company that offers a platform that brings together national-scale connectivity, real-time primary source data access, and advanced analytics in a cloud-based platform. The company’s analytics capabilities are used by 53,000 sites of care.
Watch as Michael Quinn answers these tough RCM-related questions:
1. AI is the hottest technology at the moment. It is EVERYWHERE. But has AI made any meaningful improvement to the RCM process?
2. Since RCM processes are so standardized, are we heading for a day when it will be completely automated and not require any people?
AI is Making Meaningful Improvements to RCM
In his response, Quinn highlighted the nebulous definition of AI. The science-fiction definition of AI that is human-like in behavior, is not real (yet). He is skeptical of these types of outlandish claims.
“However, AI that refers to data mapping, language, and analytics – that is something that can benefit healthcare right now,” said Quinn.
This more practical application of AI has Quinn excited and he believes that it will have a positive impact on RCM.
People Are Still Important for RCM
According to Quinn, since many RCM processes are standardized and repeatable, they are a good candidate for automation, especially AI-enhanced process automation. Although Quinn believes that one day AI may automate many RCM processes, he does not believe this is something that will happen soon, nor does he believe that the entire process can be done with out human oversight or intervention.
“I don’t think we can ever, nor should replace human intervention,” stated Quinn. “We need human beings to be part of the process. The rules for payments are constantly changing and there are always exceptions that need to be handled uniquely.”
With the establishment of this program, Inovalon is pleased to announce HealthVerity as the first partner to commit to Inovalon’s rigorous program standards for governance, compliance, and oversight. HealthVerity, a leader in real-world data synchronization, has established itself as a trusted and credible source of health data and is an outstanding strategic partner for Inovalon.
“Inovalon’s breadth and depth of primary source, longitudinal clinical and de-identified claims data stand unique in the healthcare marketplace,” said Andrew Goldberg, Co-Founder and Chief Operating Officer, HealthVerity. “We are proud to be partnered with Inovalon as we work together to empower leading organizations’ initiatives to advance research, development, and achieve expanded understanding in important areas across the healthcare landscape.”
The Preferred Data Partner Program will empower organizations to extend their research, analyses, and data-enabled solution offerings beyond otherwise available data to encompass select, deidentified elements of Inovalon’s highly comprehensive, primary source healthcare datasets. This will enable analyses that require deeper, more comprehensive, more up-to-date, and more accurate longitudinally matched data.
Enabled through the connectivity of the Inovalon ONE Platform, Inovalon maintains the nation’s largest primary source de-identified dataset with real time access across more than 40,000 data sources, resulting in a data lake of more than 79 billion medical and pharmacy events across one million physicians, 654,000 clinical settings, and 375 million unique patients.
“We believe that data holds the power to improve healthcare in many ways,” said John Chinnici, President and General Manager of Inovalon’s Insights business. “That’s why we launched the Preferred Data Partner Program. We are providing an opportunity for highly qualified organizations across the healthcare ecosystem to access data necessary for research and the empowerment of data-driven solutions that will lead to better healthcare outcomes for all.”