In the second of a two-part series, we dive into what exactly location-based data can unlock, the reality that coronavirus may be here to stay, and what organizations can do if a data-overhaul is not an immediate, or near term, possibility.
Last week, in part one, we examined the critical role that location-based data plays in an organization’s response, planning, and reaction to crisis situations. One of the ramifications of the COVID-19 pandemic being that it is a location-by-location challenge, specific geographical information can be key in navigating the patchwork of the United States’ federal response to the outbreak.
This is the dark side of federalism: it encourages a patchwork response to epidemics. States and localities may decide to implement aggressive disease-mitigation measures, but need not do so. The defining feature of the U.S. response to Covid-19 therefore continues to be localized action against a threat that lost its local character weeks ago.—The New England Journal of Medicine
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In the first of a two-part series, we examine the critical role that location-based data plays in an organization’s crisis response efforts and how compounding crises lead to an even more immediate need.
While initial outbreaks of COVID-19 hit densely-populated, urban areas of the United States the hardest, the coronavirus is now beginning to surge across less populated parts of America.
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In November 2018, Baylor St. Luke’s Medical Center in Houston made two medical errors, the second of which lead to the death of a 75-year-old patient. After an investigation by the Houston Chronicle and ProPublica, the Centers for Medicare and Medicaid Services issued a report in early 2019 that outlined a pattern of blood labeling errors at the hospital. A ProPublica article on the report states:
Dr. Ashish Jha, an expert in hospital quality, reviewed the government’s findings and said it appeared St. Luke’s was struggling to meet basic care standards. The labeling mistakes, he said, seemed indicative of ‘a broader systemic problem.’… St. Luke’s appeared to miss warning signs in the months prior to the deadly mistake, according to the government report.
The “broader systemic problem” Dr. Jha mentions is, unfortunately, not unique to St. Luke’s. Many hospitals and healthcare systems face organization-wide, process-related issues, especially in a modern healthcare landscape that’s rife with change. Mergers, multiple technology platforms, and changing healthcare policies, to name just a few, contribute to widespread miscommunication and a lack of transparency. This, in turn, jeopardizes the overall quality of care within these organizations.
Hospitals can stem the scope of these issues by implementing a healthcare enterprise risk management (ERM) program. Healthcare ERM establishes a standardized framework for identifying risk across an organization, encourages cross-departmental collaboration, and shifts hospitals from a reactive clinical risk program to a proactive holistic risk management program. A straightforward process, along with the right technology that leverages healthcare analytics, can help to make this shift effective.
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Data silos not only create obstacles to effective operations, but can also directly affect your bottom line. Listed below are five common issues associated with siloed data and ways to avoid them.
1. Creates a dependency on inefficient external reporting applications
Multiple platform architecture complicates the reporting process. While third-party reporting tools can be used to analyze data across multiple systems and produce unified reports, there are costs incurred. Forrester reports that nearly half of all data professionals spend at least as much time prepping data as they do analyzing it. This inefficiency worsens in cases where reporting reveals a need to modify how data is captured or organized, forcing analysts and IT resources to trace data all the way back to its original source and then make changes.
In some cases, third-party reporting tools can also create a gulf between those who master the reporting technology and those seeking answers from the reports. In a recent interview, Christopher Ittner, chair of the accounting department at The Wharton School, discussed how this division affects the business process:
“What we are finding is that in a lot of companies, there are great data scientists and great business people but what is missing is business people who know enough data analytics to say, ‘Here is the problem I would like you to help me with.’ And then they can take the outcome from the data scientists and see how they can best leverage it. That is where we must get to in the next couple of years if we want to take advantage of the digital technologies.”
Providing users with direct access to reporting that requires no prep work solves both issues. End users can become their own data analysts and answer the business questions that apply to their work. Without the requirement to master the technical process of assembling, scrubbing, and joining data from multiple systems, reporting becomes more efficient, effective, and scalable.
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An abundance of data accumulates in the claims management process. And while that data relays critical facts about each claim, that’s not the only insight it can provide. Data, no matter how seemingly unimportant, has the power to unleash valuable insight into your overall claims strategy. As the article Effective Data Discovery Can Be A Difference Maker For A Company’s Long-Term Success says, “Data that you may not even take into consideration can end up giving your company great insight after using proper analytics and data discovery techniques to make sense of it.” The failure to engage in data analytics means your organization may miss out on potentially rich data that sparks innovative strategy.
Benchmarking is one of the most powerful forms of data analytics. Used to measure competitor success and find areas for your organization to improve, benchmarking thrives on an abundance of data. With the right risk management information system (RMIS), you’ll not only be able to seamlessly collect troves of essential data, but also use benchmarking and other data analytics tools to extract meaning from it.
How does benchmarking make your data meaningful?
Data analytics can improve claim outcomes and, in some cases, help to prevent future claims by identifying trends and outliers that may otherwise go unnoticed. Benchmarking, specifically, involves comparing your data and performance against the industry’s best, which helps identify opportunities for improvement and establish long-term goals.
For example, risk managers, insurers, TPAs, and others who work with workers’ comp claims benefit from the annual Workers’ Compensation Benchmarking Study, conducted by Rising Medical Solutions. The study goes beyond merely reporting how claims payers are conducting business and outlines “how organizations turn the challenges identified in the prior studies into solutions and action.” The report’s mission is “to advance claims management in the industry by providing quantitative and qualitative research that identifies what high performing claims payers are doing differently than their peers.”
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Insurance carriers that rely on multiple-vendor application stacks to manage core functions such as policy management, billing, and claims administration may be placing limits on the strategic advantage IT departments can offer. As the number of supported vendors increases, more IT resources are forced to focus on managing application stacks rather than identifying and developing competitive technological advantages.
An Ivanti survey analyzed in The CIO’s Conundrum: Can IT Move From ‘Keep the Lights On’ to Creative Thinking? underscores the tension between maintenance and innovation. “In this survey, what became crystal clear was the counterbalancing of maintaining essential IT services with the desire to be bold and to act as a creativity dynamo.” Matthew Smith, President, Demand Generation at IDG Communications, notes that the survey results indicate that organizations “need to liberate their CIOs to think ahead of the curve rather than obsess over day-to-day operations. But today IT is all too often still regarded as a support function or information leaders are too stretched to drive competitive differentiation.”
Sandra Gittlen writes in Whittle down application sprawl, “out-of-control application stacks can jack up costs, introduce vulnerabilities, add to infrastructure complexity, jeopardize licensing and waste staffing resources.” This pulls resources toward the maintenance side of the spectrum and away from the strategic side. Glitten concludes, “IT’s value is not in supporting technology, but in understanding the business and using technology to achieve business goals.”
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Implementing an enterprise risk management (ERM) program can be a daunting, intimidating project. Trying to introduce new frameworks and controls across the organization, roll up risk reporting from the unit to enterprise level, and initiate discussions with the board that lead to action can be overwhelming. Using techniques proven to work with startups, however, can make the process far more manageable and increase the odds for success.
Startup incubators often promote a few common themes:
- Let customers/market dictate the product
- Scale it down – start small and go live fast
- Do the research and learn about the market
- Get feedback as quickly as possible
- Fail silently – incorporate lessons learned without dragging the whole effort down
These techniques suggest that the traditional high-profile, enterprise-wide rollout of a new ERM program may not always be the best way to launch. Instead, focusing on the smallest scale project—one with the potential to yield meaningful results—and relying on a customer-driven approach may be the key to creating a sustainable, effective ERM program.
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Technology can play a pivotal role in improving claims management by providing adjusters, claims managers, and other stakeholders with direct, centralized access to the pertinent claims information that they need to do their jobs. As Improving claims administration with an integrated solution points out, centralizing claims data in an integrated system “that combines workflow automation tools with all of the functionality needed for end-to-end claims adjusting can be transformative.” This is especially true when the system is used to streamline claims handling processes, increase adjuster productivity, and inform decisions that contribute to swift, cost-effective claim closure.
Improving incident reporting, controlling costs, and closing claims more quickly certainly count as claim management “wins.” Yet, as Christopher Mandel points out in Next-Level Claim Strategies, there is the potential to take claims management to an even higher level.
“Just when you thought risk managers understood and had explored all the opportunities around optimizing the claims management function, next-level opportunities emerge,” he writes at the outset of the article, which examines the shared goals, motivations, and hurdles that make up the “long minimized and largely untapped synergy between casualty claims (risk management) and the benefits world.”
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Whether you’re an organization whose business is handling claims for others or one that administers its own claims, claimants are your customers. Viewing claimants through this lens will help focus your efforts on strengthening relationships and delivering better support. You also have the opportunity to go a step further and establish your reputation as truly customer-first. How? Through a straightforward branding exercise.
Before dismissing branding as something far removed from the claims world and better left to marketing and advertising executives, consider that every customer interaction further establishes an organization’s brand. Your reputation for customer service — however good or bad — is out there. You can continue with the status quo, or you can take control and push the narrative.
“Think about it,” says the Insurance Thought Leadership article 3.5 Ways to Deliver Happiness in Claims. “The claimant is going through your process during a time of grief, hardship and huge loss. Your process should not add to the stress. Your process should be easy. It should work to deliver a little happiness for them during this time. You want your beneficiaries to tell stories to their friends, family or other loved ones about how seamless your process was.”
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Data Breach Today offers predictions in What’s Ahead for Health Data Privacy, Security in 2019? While the article focuses primarily on health data, a few key trends apply more broadly and are likely to resonate with all types of organizations.
Prediction: Disruption from regulatory changes is likely
Rebecca Herold, author of 19 books on information security and CEO of The Privacy Professor consultancy, begins the list of predictions by examining the potential for agency updates to HIPAA. “Based on continued pressure from local, state and federal government agencies, law enforcement, researchers and others to ease the sharing of patient and mental health data by removing the need to obtain patient consent, I expect to see OCR issue proposed HIPAA updates,” she notes.
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