data organization

When it comes to making decisions that positively impact care delivery and business outcomes, great leaders will tell you it’s better to rely on data than on myth. Through healthcare analytics, the clinical and financial leadership at Regions Hospital in Saint Paul, Minnesota used data to do just that—and set a strong course for reliable, trusted decision-making that helps address their most pressing issues. Using strong IT systems, accompanied by a cooperative and inquisitive organizational culture that brings together clinical and financial decision makers together to address pressing issues, put Regions on the path to create powerful healthcare analytics that fuel organizational change.

The need for analytic tools to make sense of disparate data sources will certainly be expanding in the upcoming years. This report highlights what analytical data healthcare leaders are currently focusing on, as well as the challenges they expect to face when using analytics to support their organizations in the future.

Even as the move to electronic health records (EHR) progresses in earnest, there are a myriad of challenges involving legacy data systems. Chief among these challenges is the cost of maintaining obsolete systems solely for the patient information they contain. When up to 70% of a typical IT budget is spent on maintaining the current IT infrastructure and application portfolio, organizations have little left to invest in much-needed innovation. According to a recent HealthLeaders Media Survey, many organizations are still adjusting after their migration to a new EHR system. Hospitals need to get a better grasp on all forms and sources of data that they have—and the data they don’t yet have—so that the right information can be delivered to the right individual, and in the right context, at the point of care.

Creating a state-of-the-art clinical documentation improvement (CDI) program isn’t just about boosting coding accuracy. It’s a key strategy in managing the transition from volume-based to value-based care, say healthcare leaders. That transition is a risky endeavor that is putting hospital and physician financial performance to the test. As hospitals participate in new care and business models aimed at improving value, leaders must ensure that their organizations are able to maintain reimbursement levels, effectively treat the chronically ill—especially in outpatient settings—and gather accurate data that will allow them to assess performance and segment their varying populations. While some organizations often believe they are leaving revenue on the table because of documentation and coding issues, CDI offers numerous opportunities for improving financial performance, finds a recent HealthLeaders Media survey of 149 healthcare executives at provider organizations.

Electronic health record (EHR) system implementation is one of the largest IT investments most healthcare systems have ever made but it’s success is largely dependent upon the data which feeds it. One the main data sources for the EHR is the item master, which drives not only supply chain processes but also a broad range of clinical and financial functions. Only with a clean, accurate and complete item master can a healthcare organization trust the outputs generated from its EHRs – from evaluating the clinical effectiveness of products to securing reimbursements. Learn how to execute a master data management strategy to derive the greatest value from your EHR investment.

HealthLeaders' survey on workforce management queried leaders from a cross-section of U.S. healthcare organizations, including hospitals, health systems, physician organizations, and long-term care/skilled nursing facilities. The 150 respondents represent executives across all disciplines — administration, clinical, operations, finance, marketing, and information. In the next three to five years, hospitals, health systems, and other patient service providers expect to augment their time-and-attendance and payroll systems with integrated applications that enable more sophisticated data crunching around labor analytics, acuity management, and staffing assignments. The goal? To convert the workforce from overhead to asset — a flexible, agile asset that will help organizations succeed in an increasingly demanding regulatory and competitive environment.

Data is one of your enterprise's most valuable assets and the key to accelerating growth and improvement. Yet most organizations keep data in silos, stunting its value. Are you giving it the enterprise-level attention it needs?

Building a data-driven organization takes more than technology. And, healthcare leaders can all agree that issues facing today’s industry are daunting; determining how to react in a way that matches your organization’s strengths and vulnerabilities may be even more challenging. With the right resources in place, you can take pragmatic steps to reduce data silos and deliver efficient, coordinated care across all your settings.

Powerful IT doesn’t have to be complicated. Hyperconvergence puts your entire virtualized infrastructure and advanced data services into one integrated powerhouse. Deploy HCI on an intelligent fabric that can scale with your business and you can hyperconverge the entire IT stack. This guide will help you: Understand the basic tenets of hyperconvergence and the software-defined data center; Solve for common virtualization roadblocks; Identify 3 things modern organizations want from IT; Apply 7 hyperconverged tactics to your existing infrastructure now.

"IT needs to reach beyond the traditional data center and the public cloud to form and manage a hybrid connected system stretching from the edge to the cloud, wherever the cloud may be. We believe this is leading to a new period of disruption and development that will require organizations to rethink and modernize their infrastructure more comprehensively than they have in the past. Hybrid cloud and hybrid cloud management will be the key pillars of this next wave of digital transformation – which is on its way much sooner than many have so far predicted. They have an important role to play as part of a deliberate and proactive cloud strategy, and are essential if the full benefits of moving over to a cloud model are to be fully realized."

Are you considering data virtualization for your organization today? In this paper you will learn 10 core truths about data virtualization and gain essential knowledge for overcoming analytic data bottlenecks and driving better outcomes.

Are you considering data virtualization for your organization today? If so this whitepaper synthesizes the 10 things you need to know as you commence your data virtualization journey.

Employees frequently become unwitting participants in attacks, aiding the lateral movement of threats through the distribution of malicious URLS and attachments or the exposure of sensitive data. In this E-book, we’ll take a closer look into several email-related activities that employees often engage in that contribute to the spread of these insider (“hidden”) threats and then discuss what measures your organization can take to protect itself from these “hidden” threats.

As data science becomes a critical capability for companies, IT leaders are finding themselves responsible for enabling data science teams with infrastructure and tooling. But data science is much more like an experimental research organization than the engineering and business teams that IT organizations support today. Compounding the challenge, data science teams are growing fast, often by 100% a year. This guide will quickly help you understand what data science teams do to build their predictive models and how to best support them. Learn how to modernize IT’s approach to ensure your company’s data science teams perform their best, and maximize impact to the business. Some highlights include: Why data science should not be treated like engineering. How to go beyond simple infrastructure allocation and give data science teams capabilities to manage their workflows and model lifecycle. Why agility and special hardware to support burst computing are so important to data science break

How Security Solutions Enable Cloud Success Cloud applications have transformed how organizations conduct business, increasing productivity and reducing costs. However, moving to the cloud means critical data now flows outside the organization’s traditional security boundaries. Unsurprisingly, security concerns still rank as the number one reason for not using cloud services. Read the eBook to find out the five information security lessons learned from transitioning to the cloud.

Downtime Is Not an Option: High Availability Next Generation Firewall Access to applications, data, and resources on the Internet is mission-critical for every organization. Downtime is unacceptable. Security for that network must also be highly available and not cause performance degradation of the network. The increased workload of security devices as they analyze traffic and defend users from malicious attacks strains computing resources. The next generation of security solutions must build in high availability that can scale as the business changes. Download this whitepaper to find out how high availability is at the core of the Forcepoint NGFW (Next Generation Firewall).

Transforming Cloud Connectivity & Security in Distributed Networks Today’s digital transformation initiatives frequently begin with moving applications and data to the cloud. But traditional networking and security infrastructure, such as backhauling data from remote locations to central offices over MPLS lines, can’t keep up. Fortunately, new approaches that also move connectivity and security to the cloud are rapidly overcoming these hurdles. Technologies such as direct-to-cloud SD-WAN and site-to-site VPNs dramatically cut the cost of connectivity. However, they put pressure on other parts of the organization to adopt new ways of defending each site against internet intruders, protecting the use of web content, and securing data stored in cloud apps. In this webcast, we’ll discuss a new, integrated approach to connectivity and security. View the webinar today!

Data is a truly inexhaustible resource for an organization. It creates endless possibilities to make data do more. As a technology partner of hundreds of organizations around the world, Infosys helps clients navigate the journey from their current state to the next. Facilitating clients’ transition into data-native enterprises is a crucial part. To understand how companies are using data analytics today and their expectations in a world of endless possibilities with data, we recently commissioned an independent survey of 1,062 senior executives from organizations with annual revenues exceeding US$ 1 billion, in the United States, Europe, Australia, and New Zealand. The respondents were from business and technology roles, who were decision makers, program managers and external consultants; represented 12 industries, grouped into seven industry clusters, such as, consumer goods, retail and logistics, energy and utilities, financial services and insurance, healthcare and life sciences, h

The Business Case for Data Protection, conducted by Ponemon Institute and sponsored by Ounce Labs, is the first study to determine what senior executives think about the value proposition of corporate data protection efforts within their organizations. In times of shrinking budgets, it is important for those individuals charged with managing a data protection program to understand how key decision makers in organizations perceive the importance of safeguarding sensitive and confidential information.

Virgin HealthMiles reached out to a variety of companies to get this data-rich snapshot of the goals, programs and investments American organizations are making in health and wellness.

Data Governance has emerged as the point of convergence for people, technology and process in order to manage the crucial data (information) of an enterprise. This is a vital link in the overall ongoing data management process for it maintains the quality of data and makes it available to a wide range of decision making hierarchy across an organization

11 ways to identify the best supplier verification partner for your organization Most of us know that operating a thorough and sustainable supplier qualification program is critical to reducing risk. But how many can say they feel confident in their process? From the ongoing collection and verification of data, to the oft-required cooperation between departments; building and maintaining a great program can be challenging. Avetta suggests there are 11 requirements of a world-class supplier qualification program. See how your organization measures up when you download the Ultimate Supplier Qualification Guide.

There’s strong evidence organizations are challenged by the opportunities presented by external information sources such as social media, government trend data, and sensor data from the Internet of Things (IoT). No longer content to use internal databases alone, they see big data resources augmented with external information resources as what they need in order to bring about meaningful change. According to a September 2015 global survey of 251 respondents conducted by Harvard Business Review Analytic Services, 78 percent of organizations agree or strongly agree that within two years the use of externally generated big data will be “transformational.” But there’s work to be done, since only 21 percent of respondents strongly agree that external data has already had a transformational effect on their firms.

The operation of your organization depends, at least in part, on its data. You can avoid fines and remediation costs, protect your organization’s reputation and employee morale, and maintain business continuity by building a capability to detect and respond to incidents effectively. The simplicity of the incident response process can be misleading. We recommend tabletop exercises as an important step in pressure-testing your program.

If your business is like most, you are grappling with data storage. In an annual Frost & Sullivan survey of IT decision-makers, storage growth has been listed among top data center challenges for the past five years.2 With businesses collecting, replicating, and storing exponentially more data than ever before, simply acquiring sufficient storage capacity is a problem. Even more challenging is that businesses expect more from their stored data. Data is now recognized as a precious corporate asset and competitive differentiator: spawning new business models, new revenue streams, greater intelligence, streamlined operations, and lower costs. Booming market trends such as Internet of Things and Big Data analytics are generating new opportunities faster than IT organizations can prepare for them.