Optimum-Data-Analytics

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Optimum provides analytics and information management services to help healthcare organizations improve patient care and outcomes. Their consultants have extensive experience in healthcare operations and understand the demands on healthcare IT teams and regulatory compliance. Optimum helps clients integrate data, eliminate silos, share knowledge, improve episodes of care, population health management, and provider performance through their expertise in domains like enterprise data management, data governance, clinical research, and process engineering.

ANALYTICS & INFORMATION
MANAGEMENT SERVICES
Better Solutions.
Better Patient Care.
The Optimum Advantage
Analytics Services Analytics Domains
Optimum has deep experience working inside healthcare
organizations. We understand healthcare operations, the current
demands on healthcare IT staff, and the OCR’s expectations for
compliance with HIPAA. Our consultants have served as hospital CIOs,
CTOs and CISOs. We have the experience and insight to share industry
best practices and solutions to common problems. Whatever the
engagement, we deliver an individualized experience, customized to
the needs and culture of your organization.
Integrate and improve ﬁnancial and clinical outcomes
Eliminate data silos
Share knowledge across the organization
Episodes of care
Population Health Management
Provider Performance Improvement
Provider growth
Enterprise Data Management
Data Governance
Health Services and Clinical research
Data Quality
Process Engineering
Copyright © 2016 Optimum Healthcare IT, LLC. All Rights Reserved.
It is our mission to deliver best
practices and leading IT solutions for a
stronger healthcare community.
OptimumspecializesinmeetingtheBusinessIntelligence
andAnalyticsneedsofhealthcareorganizations.
Ourconsultantsareseasonedexpertswithabroad
understandingofhealthcareoperationsanddataneeds.
i
Healthcaredeliveryisrapidlytransformingdueto
changesinlaws,regulations,andreimbursement
mechanisms.
Inordertosurviveandthriveinthisstormy
environment,hospitalsandhealthcarenetworksare
turningtohealthcareanalyticstoconvertrawclinical
andﬁnancialdataintoactionableknowledgetheycan
usetoimproveperformance,care—andthebottomline.
i
The Optimum healthcare analytics approach leverages
enterprise-level, vendor-neutral data sources to
identify short- and long-term opportunities to help:
Our approach relies on a multi-disciplinary team composed of
analytics consultants, advanced analytics experts, predictive
modelers and technology, Our Analytics domains include:

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As the healthcare industry shifts from a fee-for-service to pay-for-performance and accountable care organizations are under greater pressure to make improvements to their clinical, financial and operational outcomes. As clinical quality improvement efforts grow systematically improving and sustaining care across the organization becomes more challenging. In order to ensure sustainable, long-term change a cross-functional, team-based approach that accelerates the implementation of change throughout the organization is necessary. This is the deployment system. Without a deployment system, improvement initiatives become a series of one off projects that may have a temporary positive impact, but soon return to the baseline level.

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Healthcare organizations are turning to the enterprise data warehouse (EDW) as the foundation of their analytics strategy. But simply implementing an EDW doesn’t guarantee an organization’s success. One obstacle organizations come up against is that their analytics team members don’t have the right skills to maximize the effectiveness of the EDW. The following six skills are essential for analytics team members: structured query language (SQL); the ability to perform export, transform, and load (ETL) processes; data modeling; data analysis; business intelligence (BI) reporting; and the ability to tell a story with data.

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COVID-19 has escalated healthcare’s decision-making demands, reinforcing the industry’s need for highly skilled analytics team members. As a result, health systems face mounting pressure to hire the best-suited analytics talent in a timely manner and with minimal burden on existing team members. Five proven inclusive strategies will help hiring managers efficiently build an analytics team that can adapt to healthcare’s shifting environment and also fit within an organization’s culture: Open positions to remote employees and conduct interviews via video conferencing. Insert “tollgates” into the hiring process. Use scenario-based role play to assess many competencies concurrently. Assess cultural fit. Follow up with and provide feedback to all candidates.

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Shifting health plan landscape brings more competition focused on performance and value. Health care payers of all kinds must innovate, manage big data and harness new technology to deliver better performance at lower costs. Early results from this Survey of 180 commercial and Medicaid health plans feature population health management challenges and solutions, the use of data aggregation as a business strategy, resources to address complex populations, and the role of technology for health plans in the shift to value-based care.

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Setting KPIs that are realistic, measurable, and achievable is the only way to properly understand the ROI of social media campaigns. Whether you’re measuring client satisfaction or calculating leads generated, measuring the right KPIs is the key to success for modern marketers. In this webinar, Christine Carzo, Marketing Director at Digimind, explores: - How to build effective KPIs for your social media strategies - 10 rules to develop your KPIs - 20 essential KPIs for you to measure your social media ROI - How to design and use KPI dashboards

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With the release of the Accountable Care Organization (ACO) regulations, healthcare providers must be able to identify, access, and seamlessly share patient information to drive efficiencies and enjoy a potential share in ACO program incentives. Additionally, more than half of the 93 draft National Committee for Quality Assurance (NCQA) ACO measures are also Meaningful Use measures, which further elevates the need to achieve meaningful use stage 2 or higher. Given these goals, success will ultimately depend on an organization’s ability to share patient data at the point of care and its ability to gain meaning from historical and longitudinal data for use in managing population health. Healthcare organizations will need to give focused attention to the IT strategies, appropriate architectures, and roadmaps they will use to move from desired state to reality. We discuss the practical architectural approach for creating an ACO. As Health Information Exchanges (HIEs) evolve into their second generation, they are able to the support the functional ACO tasks of delivering and managing care for a defined population, accept payment, distribute savings to participants, and perform disease management with predictive modeling to improve outcomes. We will also discuss the need to achieve meaningful use stage 2 or higher and the data/analytics requirements for ACO participants. Presenter Martin Sizemore is the Director of Healthcare Strategy for Perficient. Martin has been a consultant and trusted advisor to CEOs, COOs, CIOs and senior managers for global multi-national companies and healthcare organizations, and is a certified Enterprise Architect with specialized skills in Enterprise Application Integration (EAI) and Service Oriented Architecture (SOA).

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The fifth annual Huron Healthcare CEO Forum brought together dozens of the most experienced executives in hospitals and health systems across the country to address challenges, share experiences and assess high-level strategies to achieve success in the year ahead. The Forum also featured executives from leading brands outside healthcare, such as The Home Depot and Coca-Cola, who shared valuable and applicable advice for navigating the rapidly changing healthcare environment.

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In healthcare we tend to think of predictive or prescriptive model building and deployment as technical challenges. We do not put enough emphasis on the importance of change management. This disorientation leads to uneven adoption and results. In this webinar Jason Jones discusses and demonstrates three perspectives, accompanied by tools, to help you drive action and deliver better outcomes. We develop predictive and prescriptive models in healthcare to improve Quadruple Aim outcomes—population health, patient experience, reduced cost, and positive provider work life. Successful adoption of predictive and prescriptive models heavily depends upon behavior change. This requires more than technical accuracy. While prediction algorithms abound, tools to facilitate change management remain scarce. During this webinar, we will discuss how to achieve model understanding using three perspectives: functional, contextual, and operational. View the webinar to learn: - Why a predictive or prescriptive model endeavor is more a change management challenge than a technical one - How to apply three types of model understanding to a use case in your own organization In this webinar, Jason Jones, PhD, Chief Data Scientist at Health Catalyst discusses and provides examples of our work using three perspectives of understanding to help clinical and operational leaders achieve value from predictive and prescriptive models. Investing time and effort to ensure model understanding is necessary for broad scale adoption.

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Information blocking has been a hot-button issue for years as it has impeded innovation and patient healthcare options for too long. The 21st Century Cures Act (Cures Act) sought to eliminate these problems but information blocking persisted. However, in February 2019 the Office of the National Coordinator for Health Information Technology (ONC) announced a proposed rule with consequences to non-compliance with the Cures Act that may finally force true interoperability. As a healthcare decision maker you have a real opportunity to build an innovation strategy around these changes. To learn how, view this webinar. True data interoperability enables innovation and better patient experience. In aggregate, both of these activities have the potential to accelerate the shift away from fee-for-service and towards fee-for-value healthcare. Dan Orenstein has spent much of his career providing legal counsel to healthcare organizations on regulatory and risk management issues as well as how to implement growth initiatives that comply with healthcare laws and regulations. That experience has made him an expert in applying policy to healthcare strategy. He has studied the proposed rule and in this webinar he will provide a summary of the existing legislation, implications of non-compliance with the proposed rule as well as insight into putting it into practice. View this webinar and learn: - To identify information blocking practices - Seven exceptions to the information blocking provision and how they may apply to your work - Summary of the public comments about the proposed rule and the overall perception of it in the industry - The potential impact to your healthcare organization

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Referral management solution has come as an asset to the healthcare industry to improve care coordination, increase referral volumes and revenue, reduce readmissions and improve outcomes. Secure messaging is a critical aspect of the healthcare industry. Referral Management Solution allows the providers to seamlessly communicate for exchanging patient related data and for improving patient care through a secure network. Watch how an effective medical referral management increase revenue upto 65%

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As the Age of Analytics emerges in healthcare, health system executives are increasingly challenged to define a data governance strategy that maximizes the value of data to the mission of their organizations. Adding to that challenge, the competitive nature of the data warehouse and analytics market place has resulted in significant noise from vendors and consultants alike who promise to help health systems develop their data governance strategy. Having gone on his own turbulent data governance ride as a CIO in the US Air Force and healthcare, Dale Sanders, Senior Vice President at Health Catalyst will cut through the market noise to cover the following topics: General concepts of data governance, regardless of industry Unique aspects of data governance in healthcare Data governance in a “Late Binding” data warehouse The layers and roles in data governance The four “Closed Loops” of healthcare analytics and data governance

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Health systems rely on effective revenue cycle management to follow the patient journey, navigate claims, and ensure the organization collects payment for its services. In today’s complex and fluid healthcare industry, in which revenue cycle management is about much more than billing and collecting payment, traditional revenue cycle approaches can’t meet escalating demands. Additionally, with lost volume due to COVID-19, organizations can’t afford to miss an opportunity for payment. The contemporary healthcare landscape requires a comprehensive, standardized, and data-driven revenue cycle process. Health systems that leverage data to support revenue cycle management improve their financial outcomes in three significant ways: 1. Reduce denials. 2. Increase collections with propensity-to-pay insight. 3. Improve discharged-not-final-billed efforts.

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A systematic approach to performance improvement initiative includes three components: analytics, content, and deployment. Taking six steps will help an organization to effectively cover all three components of success. Step 1: Integrate performance improvement into your strategic objectives. Step 2: Use analytics to unlock data and identity areas of opportunity. Step 3: Prioritize programs using a combination of analytics and a deployment system. Step 4: Define the performance improvement program’s permanent teams. Step 5: Use a content system to define program outcomes and define interventions. Step 6: Estimate the ROI.

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With HP Converged System for Microsoft APS, Power BI and Sogeti, you can easily get started visualizing, modeling and reporting data insights for the healthcare industry through what we call the Unleash Enterprise Innovation3 solution. Learn how your organization can easily unite your relational inpatient and outpatient data with non-relational data from public sources and social media, allowing you to capture and analyze the data that will effectively impact your decision-making processes.

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About the presentation. Based on Chapter 3 of my book "Healthcare Analytics for Quality and Performance Improvement", this presentation describes the key components of a strategic analytics framework that can enable your healthcare organization to leverage data from source-systems to achieve its quality, safety, and performance improvement goals. What is an analytics strategy? Analytics is currently a very “trendy” topic. The internet is scattered with many buzzwords, marketing angles, white papers, and opinions on the topic of healthcare analytics. With all this “noise”, it is easy to get distracted from what is actually required, from an analytics perspective, by your organization. An analytics strategy helps cut through the noise and keep focus on what is important for the organization. Regardless of what the latest “buzz” is, your analytics strategy will enable your organization to Invest now for what is required now, and invest later for what is required in the future. An analytics strategy helps ensure that analytics development and capabilities are in alignment with enterprise quality and performance goals and helps avoids the “all dashboard, no improvement” syndrome. Furthermore, a well formed strategy document helps to achieve optimal use of analytics within a healthcare organization and can mean the difference between a “collection of reports” versus a high-value information resource. An analytics strategy can rarely stand on its own. In general, the analytics strategy should use as input an organization’s Quality Improvement (QI) strategy and should be used to inform an organization’s Business Intelligence (BI) or Information Technology (IT) strategy. The analytics strategy is an important input to technical strategies because analytics, after all, can involve a sophisticated use of data and technology. Requirements for analytics may trigger a cascade of enhancements throughout other components of IT and BI (i.e., reporting, data storage, ETL, etc) The document is intended to accompany Chapter 3, “Developing an Analytics Strategy to Drive Change”, so please refer to the chapter for further information about developing an analytics strategy.

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Healthcare organizations are always looking for data management strategies to improve clinical outcomes, population health and reduce costs. The Rootfacts, one of the healthcare industry's leading big data consultancies, has a team with hands-on healthcare skills trained in the use of clinical data management and analysis. The big data solution in healthcare can be implemented for any type of dataset, whether your goal is to modernize patient care or improve outcomes.

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The role of big data service provider companies in healthcare is to help the company to utilize enormous amounts of data and provide the right intervention to the right patient at the right time for either individualized care or the overall community of patients. This will also benefit all the constituent parts of a healthcare system, including providers, payers, patients, and management. Evidence-based healthcare such as big data solutions in healthcare is replacing somewhat haphazard and subjective decision-making in routine medical practice.

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In this presentation, our approach to patient volume modeling is reviewed. This model is used for marketing and operations strategic decision making. As hospitals and healthcare systems are trying to increase commercial revenue (non-government funded) to sustainable profitability, many are unable to address this problem strategically due to data dispersion and the analytical model required to establish cause and effect relationships. Endeavor Analytics’ digital tool assembles, models and predicts the impact of market changes, marketing and operational activities on all-payer patient volumes.

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Optimum-Data-Analytics

1. ANALYTICS & INFORMATION MANAGEMENT SERVICES Better Solutions. Better Patient Care. The Optimum Advantage Analytics Services Analytics Domains Optimum has deep experience working inside healthcare organizations. We understand healthcare operations, the current demands on healthcare IT staff, and the OCR’s expectations for compliance with HIPAA. Our consultants have served as hospital CIOs, CTOs and CISOs. We have the experience and insight to share industry best practices and solutions to common problems. Whatever the engagement, we deliver an individualized experience, customized to the needs and culture of your organization. Integrate and improve ﬁnancial and clinical outcomes Eliminate data silos Share knowledge across the organization Episodes of care Population Health Management Provider Performance Improvement Provider growth Enterprise Data Management Data Governance Health Services and Clinical research Data Quality Process Engineering Copyright © 2016 Optimum Healthcare IT, LLC. All Rights Reserved. It is our mission to deliver best practices and leading IT solutions for a stronger healthcare community. OptimumspecializesinmeetingtheBusinessIntelligence andAnalyticsneedsofhealthcareorganizations. Ourconsultantsareseasonedexpertswithabroad understandingofhealthcareoperationsanddataneeds. i Healthcaredeliveryisrapidlytransformingdueto changesinlaws,regulations,andreimbursement mechanisms. Inordertosurviveandthriveinthisstormy environment,hospitalsandhealthcarenetworksare turningtohealthcareanalyticstoconvertrawclinical andﬁnancialdataintoactionableknowledgetheycan usetoimproveperformance,care—andthebottomline. i The Optimum healthcare analytics approach leverages enterprise-level, vendor-neutral data sources to identify short- and long-term opportunities to help: Our approach relies on a multi-disciplinary team composed of analytics consultants, advanced analytics experts, predictive modelers and technology, Our Analytics domains include:

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