Blog
Log In
Contact us

Category: Editorial

Categories
Editorial

Linking Real-World Clinical Data with Medical Device Data to Demonstrate Device Value

Clinical Data, Medical Device

Real-World Data in the Medical Device Market

Many life sciences organizations are focused on harnessing real-world data (RWD) capabilities to inform every part of the drug development product life cycle. The same types of RWD can, and should, be applied to innovation around the development and measurement of the effects of medical devices. RWD derived from healthcare sources, such as electronic health records, provides insights into the burden of disease, and after a device market launch, provides insights into competitive stance, safety, efficacy, and outcomes. Traditionally, these types of analyses have been difficult to perform for medical devices because the specific details surrounding the medical device make, model, and manufacturer used in procedures are often buried in the electronic health record or other IT systems, and historically have not been collected uniformly. 

Medical Devices in the Real World

Medical Devices have become a critical part of a patient’s daily life, and how patients interact with these devices can tell us a lot about their effectiveness. From joint replacements to life-saving arterial stents and pacemakers, device manufacturers are interested in the benefit-risk profiles to inform future device modifications and technological advancements, Providers can glean important evidence for the clinical effectiveness of these devices, helping to inform what devices to use in their procedures. 

Medical device manufacturers are motivated to invest in new strategies to support success. According to McKinsey, despite a period of growth from 2012 through 2019, S&P medical device investments slowed during the pandemic. Recently, however, signs have been promising; in 2023, the U.S. approved more novel medical technologies than in any single year before, and revenue growth rates are starting to stabilize to pre-pandemic levels. 

Aggregation of RWD to Inform Device Safety and Evidence for Effectiveness

Using relevant and reliable RWD is important for generating RWE to understand and regulate medical device usage and safety. To get a complete picture of the patient’s use and interaction with a medical device, RWD from clinically relevant sources is required to give a holistic view of the clinical experience both before device implant/initiation and after usage has been initiated. The ability to combine disparate data from multiple sources and care settings is where OMNY Health excels. 

The OMNY Health Medical Device Data Advantage

OMNY Health’s Medical Device product offering is a best-in-class view into the healthcare industry’s use of medical devices in patients. Our Medical Device offering is constructed directly from our health provider data sets, with precision down to the patient encounter level. Utilizing the Unique Device Identifier (UDI) and the device version, we have partnered with the FDA’s AccessGUDID database to ensure the highest quality and completeness of data, with unrivaled recency. 

OMNY Health’s Medical Device product offering linked with OMNY Health’s EHR data, can help device manufacturers and provider networks better understand and assist the patients they are servicing by examining: 

  • Medical Device use and trends 
  • Patient journeys and continuity of care
  • Impact of medical devices on clinical, functional, cost, and utilization outcomes
  • Safety/adverse event reporting
  • Providers who are interested in value-based contracting and making procurement decisions

Check out the Total Knee Replacement study utilizing the OMNY Health Medical Device product offering. 

Contact OMNY to learn more about how our Medical Device product offering will boost your real-world evidence generation.

Categories
Editorial

Social Determinants of Health: Generating Accurate Clinical Insights Using Real-World Data

Social Determinants

Recent innovations in healthcare analytics and patient-oriented AI demonstrate the power of leveraging real world data (RWD) to generate ecologically valid actionable insights for life sciences companies to improve patient lives and streamline new therapeutic advances. Such insights are essential for decision-making in health economics and outcomes research (HEOR) and in the clinical trial planning and implementation processes. However, the breadth, depth, and inclusivity of the data used to generate such insights can have a huge impact on both the accuracy and validity of any analyses. Various sources of bias, such as the lack of demographic and socioeconomic diversity in a cohort, can undermine the main benefit of using RWD to supplement life sciences research. To combat this, many researchers and providers have publicized the need for clinically-validated metrics that can be used to measure and quantify cohort-level bias and provide more transparency in the field.

Social Determinants of Health Data Account for Notable Variations in Clinical Outcomes

One commonly referenced set of measures that has received growing recognition is social determinants of health (SDoH) data – a set of criteria used to capture economic and social vulnerabilities across key domains. Various studies have estimated that accounting for SDoH variables, such as income level, housing security, transportation, gender identity, and race and ethnicity, can account for 40 – 60% of the variation in clinical outcomes and care patterns. A recent study examining Antihypertensive and Lipid‐Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) data illustrates this all too well. Researchers found that trial participants in the lowest-income trial sites had poorer blood pressure control and worse outcomes for some adverse cardiovascular events, even when treatment access and adherence were accounted for. The authors concluded that these results clearly illustrate “the importance of measuring and addressing socioeconomic context in [randomized controlled trials] RCTs.” The incorporation of these factors into studies leveraging RWD is just as important.  

United States Government Support for Clinical Research and RWD Inclusivity

Researchers are not the only ones promoting the importance of SDoH – the U.S. government is facilitating efforts to foster greater inclusivity in clinical trial participation across multiple fronts. The Food and Drug Administration has issued new guidelines about the use of RWD in clinical research, pointing to the utility of inclusive data sources to identify clinical trial participants. The Centers for Medicare & Medicaid Services (CMS) are also focused on health equity. At the end of 2023, CMS released an updated framework for health equity with a focus on the collection of interoperable, standardized SDoH. As of January 2024, CMS requires the screening of five SDOH domains for admitted hospital patients.  

Challenges with Obtaining and Utilizing SDoH Data

Despite the power of SDoH to create a more inclusive real-world environment for clinical trials and research analyses, patient-level SDoH data availability to pharmaceutical companies has been lacking. This is in large part due to barriers relating to extracting and aggregating relevant material. In typical healthcare systems, patient-level SDoH data are often difficult to expose and curate as the relevant information is buried in clinical codes and unstructured notes. However, the aforementioned efforts by various government entities have resulted in an exponential increase in the amount of patient-level SDoH data available in medical records – including increased use of structured surveys and other collection tools. 

Much of the SDoH data currently available in the RWD marketplace rely on a combination of 3-digit zip-code-level data and aggregated claims or credit data, which only provide inferred modeled proxies, not insight into actual patient-level information. Those that are able to derive SDoH variables through direct access to EHRs often face issues such as data lags, inconsistent data collection vehicles, and gaps in reporting. OMNY Health has the technology in place at the provider level creating a direct flow of data through the OMNY platform so that data is captured consistently with limited lag time. These unique integrated partnerships with large integrated delivery networks (IDNs) and specialty networks have enabled us to quickly capitalize on the growing availability of SDoH data in patient records.  

OMNY Health Top-tier SDoH Data Sets

OMNY Health is focused on creating a best-in-class SDoH data product to augment our existing EHR-derived, de-identified clinical data sets. Our ​​Social Determinants data offering is constructed from point-of-care documentation aggregated at the patient-encounter level. To ensure deep, multi-faceted coverage, we leverage multiple streams of information, including ICD-10 diagnostic codes, self-reported responses to standardized SDoH surveys, and estimated SDoH burden derived using research-grade, validated NLP models run on unstructured clinical notes.  

OMNY Health’s Social Determinants data offering, when integrated with our extensive clinical data sources, can help pharmaceutical companies and provider networks better help the patients they are serving and be more successful by informing: 

  • More accurate HEOR analyses 
  • Inclusive clinical trial planning and implementation 
  • Analysis of clinical trial results and differences in real-world populations 
  • The development of precision medicine treatments 
  • The understanding of the barriers to drug access and adherence and how to develop targeted programs to reduce those barriers 
  • Different disease severity and outcomes across populations and geographies 
  • Market access and pull-through strategies for contracting and drug promotion. 

SDoH data can offer insight into the everyday non-clinical factors that influence how individuals develop diseases, respond to treatments, and participate in clinical trials.  

Contact OMNY to learn more about how our SDoH data sets will boost your real-world evidence generation.

Categories
Editorial

Five Strategies To Boost Clinical Trial Diversity

Five Strategies To Boost Clinical Trial Diversity
Categories
Editorial

Practical Applications of FDA’s Guidelines on Use of Real-World Data and Real-World Evidence to Support Regulatory Decision-Making for Drug and Biological Products

Practical Applications of FDA’s Guidelines

On August 31, 2023, the U.S. Food and Drug Administration (FDA) released “Considerations for the Use of Real-World Data and Real-World Evidence to Support Regulatory Decision-Making for Drug and Biological Products: Guidance for Industry.”[1] FDA issued this guidance as part of its Real-World Evidence (RWE) program stemming from the 21st Century Cures Act (Cures Act).[2],[3] The Cures Act was signed into law in 2016 to accelerate medical product development. One of the key provisions was for FDA to create the RWE program to evaluate the use of RWE in regulatory decision making.  

The newly released Guidance clarifies FDA’s expectations for clinical studies using real-world data (RWD) but does not establish any legally binding requirements. This Guidance discusses the applicability of 21 CFR Part 312 (investigational new drug application)[4] for studies using RWD and summarizes regulatory considerations for non-interventional studies using RWD. We summarize below the key facets of these considerations and discuss their practical application to the current landscape of available RWD.  

Applicability of 21 CFR Part 312 

21 CFR Part 312 outlines the requirements for Investigational New Drug Applications (IND) for review by the FDA. While they specifically concern interventional studies, these guidelines recognize the utility of RWD in these studies. The example applications of RWD are identifying potential participants for trials, ascertaining outcomes (e.g., diagnoses, hospitalizations), and creating external control arms. The guidelines also note that non-interventional studies are not clinical investigations subject to 21 CFR Part 312. 

Practical Application: The potential use of RWD in clinical research has been long recognized but remains an emerging practice. One challenge to overcome is finding sources of data with enough details to ascertain study inclusion/exclusion criteria, covariates and outcomes. Often, multiple sources must be used. It is also important to understand the underlying characteristics of the RWD source population, as most RWD are samples of convenience. Critical subgroups could be missing from the source, regardless of the level of detail that the RWD source offers. Finally, RWD sources that are readily available are generally de-identified. This presents challenges to finding patients to participate in trials. Careful evaluation of available data sources must be conducted before committing to use RWD in INDs. The FDA’s recommendations noted in these guidelines offer a path to evaluate the usability of RWD sources for this purpose. 

Regulatory Considerations for Non-Interventional Studies 

The majority of the FDA’s new Guidance discusses use of RWD for non-interventional studies. It describes the common sources of RWD for non-interventional studies, including registries, electronic health records (EHRs), and administrative claims. It recognized that while many non-interventional studies involve already collected RWD, some involve collection of additional data (e.g., questionnaires, laboratory tests, and imaging studies), which are subject to regulations protecting human subjects. Data privacy is also noted as a key consideration in using RWD.  

The Guidance discusses requirements to establish transparency in the design of the study. Steps to be taking include sharing drafts of protocols and statistical analysis plans (SAPs), publicly posting protocols, evaluating sources of RWD for fit and assurance that the sources as well as study cohort selection and analysis do not favor a certain conclusion, justification of selected data sources, and maintaining audit trails and documentation of the data extraction and analyses. 

The Guidance recommends that for studies intended for use in a marketing application, sponsors should ensure that they can submit patient-level data and can make the source data available if further verification is necessary. The source data could include “original records of clinical findings, observations, or other activities in a clinical investigation used for reconstructing and evaluating the investigation”, though the Guidance does note that appropriate justification may exist for why the sponsor cannot submit patient-level data. Programming code and algorithms submitted to the FDA must be well documented and complete enough to allow for study replication. 

The Guidance also offers recommendations for study monitoring (from RWD extraction to application of the protocol/SAP), safety reporting, study oversight, and researcher and third-party roles and responsibilities. 

Practical application: Study sponsors typically rely on outside parties for access to RWD. Most of these guidelines cannot be successfully implemented without close partnership with the RWD source. Input from the RWD source can be critical to protocol and SAP design, particularly in determining whether the source meets study requirements. RWD sources vary in their ability (contractual and technical) to track the linage of the patient record, share records with additional parties, or provide detailed documentation. It is important to communicate study requirements and FDA expectations to the RWD source and ascertain their ability to meet these requirements. RWD sources have varying strengths and limitations.  

It is also important to discuss how sources can or cannot meet these guidelines and engage with the FDA in the selection of the optimal source given specific study requirements. To start, the source of RWD is not always the generator of the data. For example, RWD could be sourced from a vendor who is aggregating claims from multiple payers or an aggregator who is procuring EHRs from hospital software vendors. Accessing RWD closer to the source offers greater transparency and traceability, as well as opportunities to collect additional retrospective or prospective data. Also, most sources of RWD include only de-identified patient data. De-identification involves the removal of direct identifiers and the removal or obfuscation of indirect identifiers. Additionally, the RWD source may be required to anonymize providers, facilities, or payers. It is important to understand what data elements have been redacted and consider any impact to the study.  

Conclusion 

Stakeholders in medical product and drug development have long recognized the practical application of RWD to accelerate innovation and bring them to patients who need them faster. The FDA’s Guidelines summarize many of the methods already in practice and stress the importance of planning and communication between the sponsor and regulator. It is equally important to find and partner with the right RWD sources who can offer not just the patient population and data points necessary for a study, but offer enough transparency about the data and their origin to meet the recommendations in this Guidance while respecting patient privacy and ensuring data security.  

[1] https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-use-real-world-data-and-real-world-evidence-support-regulatory-decision-making-drug

[2] https://www.congress.gov/114/plaws/publ255/PLAW-114publ255.pdf

[3] https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence

[4] https://www.ecfr.gov/current/title-21/chapter-I/subchapter-D/part-312

Categories
Editorial

OMNY Health Presenting and Exhibiting at ISPOR Annual

Visit the Booth

OMNY Health will be presenting and exhibiting at ISPOR Annual on May 7-10, 2023 in Boston, Massachusetts at Booth #1325. Schedule an in-person meeting to learn more about:

  • Clinical measures and social determinants of health data extracted from clinical notes using NLP algorithms
  • Cutting-edge research and studies from our Data Science team, preview some of this research in our podium presentation and poster sessions

View Presentations

OMNY Health will also be presenting a podium presentation and multiple poster sessions.

The podium presentation will be:

Title: Severity Score Extraction from Unstructured Clinical Notes Using a Disease-Agnostic Natural Language Processing Question-Answering Pipeline

  • Presenter: Vikas Kumar, MD
  • Date: Monday, May 8, 2023
  • Time: 4:45PM – 5:45PM
  • Descriptions: In this presentation, Dr. Kumar will describe how OMNY Health uses a natural language processing (NLP) question-answering (QA) pipeline to extract disease severity from electronic health record (EHR) clinical notes.  He will report on the accuracy of the pipeline and demonstrate how findings can be used to perform healthcare resource utilization (HCRU) analyses.

In addition, five posters will be on display:

Categories
Editorial

Top Of Mind in Q1 2023

We are nearing the close of Q1 and our provider ecosystem partners have been actively sharing information with us on their key pain points and strategic priorities for this year. Here are the issues they reported as “top of mind” in our latest strategic discussions:

Increasing Cost Pressures

Concerns about the recent changes to the Medicare Physician Fee Schedule were echoed throughout our conversations with administrators across the healthcare continuum this quarter, from specialty networks to health systems. The 4% rate reduction is not the only financial factor impacting the already frail margins in healthcare. Provider organizations told us they are also wary of inflation and supply chain issues driving the rising cost of supplies and pharmaceuticals as well as costs of labor and the ability to maintain staff. Many were seeking out alternative revenue streams to help offset these additional costs.

Focusing on Improving Health Equity and Incorporating Voice of Patient

The disparities in care exposed during the COVID-19 crisis remain top of mind with some organizations using digital health and quality improvement initiatives to try to identify and address gaps in care for certain populations. Centers for Medicare and Medicaid Services (CMS) recently doubled the weight of patient experience in the Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey, and our provider ecosystem partners have taken notice. That combined with the patient reported outcomes (PROs) component of CMS’ Merit-Based Incentive Payment System (MIPs) program has elevated the impact of patient experience in care delivery more than ever. CMS and the National Quality Forum (NQF) have a major initiative underway to promote the benefits and actively encourage the completion of PROs to support value-based care and alternative payment models. Our provider partners are motivated and see the value of collecting additional measures on or from patients that would give them greater insight into disease severity and quality of life, driving better patient outcomes.

Staying Current with New Treatment Options

The ever-expanding assortment of new treatment options available across many prevalent and rare diseases is exciting and challenging for providers and patients. Accelerated Approval, Breakthrough Therapy, Fast Track, and Priority Review programs from the US Food and Drug Administration (FDA) have introduced more treatment options, and healthcare providers (HCPs) are feeling the pressure to stay current on available treatments, monitor changes to treatment guidelines, and keep up with the abundance of prior authorization procedures required for these new therapies across payer organizations. Most of our provider partners are exploring how to best educate themselves on these new products and communicate more broadly within their organizations on best practices, while simultaneously balancing the need to meet their patients’ unique and individual treatment needs.

Participating in Research Activities

Provider interest in participating in clinical trials and other research initiatives is on the rise. Many of the organizations in our provider ecosystem have been involved in research activities, but many are asserting that they want to grow their footprint, expand the types of research activities, and be a more active participant in innovation. Research and innovation are now being seen by regional community health care providers as a differentiator that attracts new patients, retains patients and providers, and drives new revenue dollars into the organization. This sentiment is consistent with the latest guidance from the FDA to begin requiring sponsors to incorporate diversity planning for late-stage clinical trials. In a news release from last year, the FDA cited the need to “facilitate the development of better treatments and better ways to fight diseases that often disproportionately impact diverse communities.”

To learn more about how OMNY Health is helping provider organizations proactively address these top-of-mind issues, stop by to see us at  ViVe on March 26-29 in Nashville, TN, Becker’s on April 3-6 in Chicago, IL, or ARVO on April 23-27 in New Orleans, LA. We also invite you to continue the conversation by reaching out to join@omnyhealth.com to schedule some time to discuss these topics further. We look forward to assisting our data ecosystem partners as we work to navigate these issues with you in 2023.

About the Authors:
Matia Cary is Chief of Staff at OMNY Health. As Chief of Staff she leads the Delivery and Customer Success teams responsible for supporting all of OMNY’s provider ecosystem partners and strategic initiatives. Internally, she helps lead people operations, strategy, cross-functional collaboration across teams, and investor relations. Matia holds a Bachelor’s degree in Biochemistry, Cellular, & Molecular Biology from Drake University and an MBA for Leaders in Healthcare from the University of Kentucky.

Jessica Walling is Director of Product Management at OMNY Health. She is currently working on a new suite of SaaS products to help healthcare providers and life sciences customers glean insights from OMNY Health’s real world data. She is responsible for product strategy and product marketing and enjoys working closely with  customers on product launches and continuous product improvement. Jessica holds a Bachelor’s degree in Industrial Engineering from Georgia Institute of Technology and an MBA from Georgia Institute of Technology.

Categories
Editorial

OMNY Health platform surpasses 50 million patient lives after recent expansion in provider system network coverage

omny health

This continued growth will expand the scope of research opportunities, which will result in more life-changing innovation to meet patients’ unmet needs. 

ATLANTA, GA, May 31, 2022 – Today, OMNY Health announced that it has reached a milestone in building its national platform of de-identified clinical data from provider systems, representing over 50 million patients receiving care over the past five years. Much of this growth is attributed to the addition of several large health systems and specialty practice networks that recently joined OMNY Health’s ecosystem. The OMNY Health platform of data includes care delivered in both inpatient and outpatient settings across a variety of provider organizations that is utilized to advance patient-focused research.  Basic electronic health record (EHR) data is augmented with data from a variety of systems within the provider organization including lab systems and imaging and third-party data sources such as claims data to provide a holistic view into the patient experience. This granular data follows the patient journeys of these 50 million+ patients across the care continuum for five or more years.  

“As a physician who has dedicated his career to transforming healthcare, it has always been my vision to build a national data ecosystem that helps connect healthcare providers with researchers, but more importantly, to impact the lives of patients. This expansion is validation that we are on course to achieving that goal. Although we have plenty of opportunity and intend to continue to grow and expand, this marks an exciting milestone for OMNY Health.” said Mitesh Rao, MD, CEO, OMNY Health.  

For provider organizations and their patients, the appeal to joining the OMNY Health network is multi-faceted and presents a number of unique benefits: 

  • Alignment of research opportunities. OMNY Health enables healthcare and research organizations to compliantly explore the breadth and depth of data available to identify and align the right patients for various research initiatives, including opportunities to participate in clinical trials, patient surveys, and quality improvement initiatives.  
  • Maximizing data utilization. OMNY Health facilitates more opportunities for each healthcare organization to utilize data at scale. These organizations work closely with OMNY Health to reinforce their internal data usage through better data capture, reporting, and conversion of data into insights. In addition, they rely on OMNY Health to manage relationships with external parties who require access to vetted de-identified real world data. 
  • Enhancing the patient experience. Whether a healthcare provider or researcher, all parties participating in the OMNY Health ecosystem are aligned on a singular goal of improving patient care through innovation. Regardless of how the healthcare provider engages, OMNY Health impacts patient outcomes by focusing on major disease groups that touch large patient populations within broader therapeutic areas, such as dermatology and ophthalmology, while also being able to reach those with rare diseases.

The ever-increasing breadth, depth, and diversity of the OMNY network will allow healthcare providers and researchers to participate in research at scale and accelerate new and improved medical innovations and treatments that help address disparities in health equity. 

About OMNY Health

The OMNY Health ecosystem features a wide range of products that compliantly facilitate collaboration between researchers and providers while maintaining patient privacy. Serving as a key resource and central intermediary, OMNY Health minimizes the effort required by providers and life sciences organizations to achieve these objectives. By aligning the goals of all sides and forging relationships to provide unique, curated data sets and mechanisms to establish compliant partnerships, OMNY Health fuels innovation where patients need it the most. For more information or to join the OMNY Health network, please contact us.

Categories
Editorial

OMNY Health launches ophthalmology-centric real-world data platform in partnership with leading ophthalmology practices focused on improving patient outcomes

In alignment with OMNY Health’s mission to deliver data and insights to accelerate life-changing innovation, these solutions will serve as a catalyst for research and improved outcomes for the 2+ billion individuals impacted by ophthalmic disease

ATLANTA, GA, May 10, 2022 – Today, OMNY Health announced that it has partnered with the nation’s leading community-based ophthalmology practices to launch a first-of-a-kind, real-world data ecosystem focused on driving collaborative research partnerships to advance treatments and improve outcomes in patients with ophthalmic disorders.  Derived from electronic health record data, OMNY solutions provide valuable information on the evolving treatment paradigm for patients with ophthalmic disease, including difficult to obtain insights on the rationale behind treatment decisions, and the impact of social determinants of health on care delivery and outcomes.  De-identified images from retinal scans and other images also are available from ecosystem partners, allowing researchers to view physical changes in condition severity over time.

A diverse set of providers are participating in the ecosystem, from large independent ophthalmology group practices to academic medical centers, integrated delivery networks, specialty hospitals, and regional health systems.  Practices participating in the OMNY ecosystem will leverage OMNY’s platform to opt into clinical trials, prospective observational surveys, and other collaborative research opportunities.

“We are thrilled to welcome our new ophthalmology providers to our network. Over the past year, we have made great strides connecting researchers and providers in the dermatology space and are looking forward to making the same level of impact on ophthalmology,” said Mitesh Rao, MD, CEO, OMNY Health.

“US Eye looks forward to continuing to strengthen our partnership with OMNY Health and find new ways to leverage our data internally,” said Kinga Huse, President, US Eye. “The ability to make more data-driven decisions that improve outcomes and the patient experience will be a valuable asset for our providers and patients.”

“We are excited to have a partner in OMNY that chose to prioritize Ophthalmology. As a data driven organization, we view this partnership as a conduit to leverage our data to gain new insights in providing care for our patients. The added visibility into additional clinical research opportunities will allow our providers to continue their focus on finding new ways to care for and treat our patients in their efforts to preserve sight,” said Amy Goodson-Burke, Chief Revenue Officer, American Vision Partners.

“As a leading administrative services provider for top notch ophthalmology practices, Sight Growth Partners’ primary focus is to listen to our doctors and provide support for them so they can care for their patients in a better way. We are partnering with OMNY Health to do exactly that…exceed our physician’s needs so they can exceed their patient’s needs,” said Jonathan Lujan, CEO, Sight Growth Partners.

“We are thrilled to be a part of the OMNY Health network. It will allow us to better understand our patient populations, obtain more insight into the impact of care patterns on outcomes, and better align clinical trial opportunities with specific patient cohorts,” said David Shoemaker, MD, Founder and CEO, US Eye.

With an uptick in ophthalmology drug research and approvals in the past few years, researchers can utilize this data to expedite clinical trial recruitment and design, understand evolving treatment patterns, assess trends in healthcare resource utilization, understand current gaps in care, conduct comparative effectiveness studies, and partner with ophthalmology practices around joint missions focused on quality improvement and patient outcomes.

Key populations available in the dataset include dry eye (296K patients), dry age-related macular degeneration (AMD) (109K patients), wet AMD (31K patients), and diabetic retinopathy (64K patients). This unique data asset also includes populations with rare eye diseases such as Stargardt Disease and pediatric populations with congenital disease.

Like other OMNY Health specialty-focused databases, the ophthalmology data set also includes information on pharmacy orders, lab results, medical device detail for implants, and detailed provider clinical assessment measures such as best corrected visual acuity and intraocular pressure values. OMNY will be conducting ophthalmology solution demonstrations and presenting results from studies during a variety of events this summer, including ISPOR, DIA, and ICPE.

About OMNY Health

OMNY Health connects patients, providers, and life sciences companies through data and insights to transform healthcare delivery, improve clinical outcomes, and address patients’ unmet needs. Our platform, representing more than 35M patients, enables turnkey research and the ability to convert insights to actions for over 150 disease areas across more than 115,000 providers.

In addition to its ophthalmology data-centered solutions, the OMNY Health ecosystem features a wide range of products that compliantly facilitate collaboration between researchers and providers while maintaining patient privacy. Serving as a key resource and central intermediary, OMNY Health minimizes the effort required by providers and life sciences organizations to achieve these objectives. By aligning the goals of all sides and forging relationships to provide unique, curated data sets and mechanisms to establish compliant partnerships, OMNY Health fuels innovation where patients need it the most.

For more information, go to www.marketing-dev.omnyhealth.com or email lifesciences@omnyhealth.com.

MEDIA INQUIRIES:  please contact Stacey Long, stacey@omnyhealth.com

View full press release

Categories
Editorial

Three Tips for Building a Strong Security Posture in Healthcare

Regardless of where your company plays in the healthcare industry or your particular role within an organization, cybersecurity in healthcare is of utmost importance and should be a top responsibility for all members of any organization. Below, we share three tips that we implement here at OMNY, but also recommend for any organization in the healthcare industry. 

Tip #1: CIA Triangle 

The first is the CIA Triangle, a set of guiding principles that help ensure data security. CIA stands for Confidentiality, Integrity, and Availability. 1.) Confidentiality is the principle that objects are not disclosed to unauthorized subjects. 2.) Integrity is the principle that objects retain their veracity and are intentionally modified by only authorized subjects. 3.) Availability is the principle that authorized subjects are granted timely and uninterrupted access to objects. For more details, check out this video: 

 Tip #2: Compliance and Certification 

Generally, compliance means adhering to a rule such as a policy, standard, specification, or law. Certification means that your system has been certified to be in conformance (compliance) with all the requirements of a selected standard. A certification is done in five major steps: 1.) Select an industry-standard framework, 2.) Work with a trusted third-party auditor, 3.) Conduct a security gap analysis and remediate gaps, 4.) Undergo the audit and achieve certification, 5.) Maintain certification. For more information, check out this video:

Tip #3: Maintaining Certification 

As you may have guessed, obtaining certification is only the beginning of an ongoing process to maintain that certification. Here are four efforts that your company should implement to maintain a solid security posture at all times: 1.) Make it a company effort, 2.) Automate evidence collection, 3.) Maintain awareness and alert levels, 4.) Set regular security checkpoints. For more information, check out this video:   

We recently implemented all three of these tips with our SOC 2 certification. We found that these three tips were great guidance and hope you can implement some of these to protect your organization as well.

About the Author:

Dr. Maik Lindner is OMNY’s Chief Information Security Officer (CISO). As CISO, he is responsible for the strategic direction and alignment of the Information Security Program. Dr. Lindner has over 25 years of Information Systems experience in multiple industries and currently holds the ISC2 certification CISSP – Certified Information Systems Security Professional. Prior to OMNY he held various positions at Dell and SAP. 

Categories
Editorial

Four Ways to Create Knowledge and Value from Healthcare Data Using Analytics and Data Science

Improving outcomes, lowering costs, and increasing quality — in healthcare, these three objectives are known as the “triple aim.” How does investment in healthcare data and analytics help health systems achieve these goals? This question is important. Too often in this field, workers focus on the “how” while ignoring the “why.” It can be relatively easy for data and analytics teams to build an app or a notebook that “looks cool” or grabs some attention on social media by demonstrating a new functionality; however, the challenge is applying that work towards the healthcare triple aim.  

So how exactly can data and analytics teams contribute towards the healthcare triple aim? At a high level, here are four ways: 

Invest in open-source tools

Sometimes, analytics teams rely on certain tools or software with less favorable properties than others. Some tools are not suited for big amounts of healthcare data and may have file size limitations; some rely on a learning curve that includes “learning where to mouse-click”; some may require expensive licenses. Clinical and healthcare analytics experiences indicate that the future lies in tools that rely/focus on the following: (1) knowledge of coding; (2) open-source, community-based development; and/or (3) repeatable, reproducible, and programmatic processes.   

Embrace new analytics technologies

The field of healthcare can be resistant to change. For example, when automated blood pressure machines were introduced to hospital wards, there was some hesitancy and disbelief that automated cuffs could accurately take blood pressure. Today, these cuffs are a mainstay in hospitals and free up precious time of nurses to achieve other care needs. Analytics technologies that face similar skepticism include specific types of artificial intelligence, including machine learning, deep learning, and natural language processing. 

Align with healthcare systems towards product development

To ensure that time consuming product development will benefit health systems, it is important to involve health systems at multiple points throughout the process. For analytics applications, this involvement often involves using a modern agile approach that focuses on rapid sprints and repeated healthcare system touchpoints, releases, iterations, and improvements of a product, rather than a traditional waterfall model that focuses on a single, lengthy iteration of the software development lifecycle. 

Take advantage of new payment models and government incentives

As the United States switches from a fee-for-service payment system towards a value-based care system that rewards quality over quantity of healthcare services, the government is offering many financial incentives for health systems to improve outcomes, quality of care, and satisfaction. An overview of such programs at the federal level can be found here: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/Value-Based-Programs .  

Generating useful insights from healthcare data through analytics is not a one-day project — it can take weeks to several years for relevant teams to achieve desired goals, depending on the bottom-line impact amount and the project. These four high-level ideas described above can serve as a starting point to extract value from healthcare data. Looking forward to bringing you more webinars and blog posts throughout the year that will focus on specific, lower-level techniques and tools for creating knowledge and value from healthcare data. 

About the Author:
Vikas Kumar, MD, MS is a Senior Data Scientist at OMNY Health where he works on data science projects that focus on real-world clinical evidence, machine learning, and natural language processing. In his spare time, he has also authored a book on healthcare analytics, contributed to two online healthcare informatics courses, and currently serves as a teaching assistant for a graduate level data science course at the Georgia Institute of Technology. He holds a Doctor of Medicine degree from the University of Pittsburgh and a Master of Science in Computational Science and Engineering degree from the Georgia Institute of Technology. s across the country in order to help guide the development of innovative solutions that can sustainably impact patient care.