Tag: Health Data Management

Modern Health Data Management Requires a Proven Patient Identity Solution

Gevik Nalbandian

By Gevik Nalbandian, vice president of software engineering, Lyniate.

As healthcare providers manage market shifts such as value-based care, increased consumer expectations, staffing shortages, changing reimbursement models, and competition from non-traditional healthcare players including Alphabet, Amazon, Apple, and Microsoft — what will it take to compete?

Providers must strengthen the internal IT infrastructure systems to better manage patient relationships. This all begins with easy access to accurate patient data. But with the explosion of data in the healthcare ecosystem, this is no small feat.

Interoperability doesn’t end with integration

Reducing friction in health data exchange requires seamless interoperability among different systems. Interoperability is often viewed as accessing and exchanging data, typically through an integration engine for extracting, composing, standardizing, and passing data between disparate systems. This is a necessary component, but it is not sufficient to achieve a full and accurate picture of your patients and patient populations.

A second component is patient identity management. An identity layer, managed through an enterprise master person index (EMPI), is critical to knowing which patients the data is tied to. In an April 2022 report, Gartner describes EMPIs as “crucial tools for reconciling patient identity and addressing medical record matching challenges needed for high-quality healthcare delivery and health information exchange.”

Accurate patient identification ensures every interaction in which data about an individual is captured — regardless of system or location — is linked correctly for a single, up-to-date view of one’s care. This includes diagnosed medical conditions, lab work, imaging, diagnostic tests, medications, allergies, and family medical history. When a patient’s data is trapped in various systems across the continuum, it can have potentially disastrous downstream clinical, operational, and financial effects.

Gaps or errors in the patient identity management process can have serious consequences for patients. According to a recent survey, nearly 40% of U.S. healthcare providers have incurred an adverse event in last two years as the result of a patient matching issue.

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Data Resilience Requires More Than An Annual Check Up

Stephen Manley

By Stephen Manley, CTO, Druva.

The biggest healthcare innovation in the last twenty years is … data. Every day, healthcare organizations use data to operate more efficiently, improve patient care, and advance medical research. Over the last 24 months, the industry used data to advance mRNA technology, which laid the groundwork for the COVID-19 vaccines, and even led to a new treatment for type-two diabetes.

The recent medical breakthroughs speak to the power of data and the vast potential it has to help improve lives. Unfortunately, as data becomes more valuable, the threats become more dire. As the attackers evolve, organizations need to take a holistic approach if they want to defeat the threats.

The Critical Risks to Healthcare Data 

Ransomware is the leading risk. Sensitive data is a honey pot to cybercriminals, and because healthcare organizations maintain so much of it (i.e., medical records, patient forms, health insurance claims, provider and patient communication records, etc.) they are vulnerable targets.

Cyber attacks on healthcare organizations have become so frequent that 45 million people were directly affected in 2021. This summer, one of the largest healthcare cyber incidents to date struck more than 2 million patients across 50 facilities in an attack on Shields Health Care Group.

If the right systems aren’t in place, recovering after a cyber attack such as ransomware can be an exhausting process that takes weeks or months. Even more concerning, businesses are sometimes unable to fully restore data lost in an attack. Aside from productivity disruption, losing critical healthcare data could impact an organization’s ability to maintain its operations. If you are a hospital or healthcare provider – this could be catastrophic. Some often resort to paying large ransoms to resolve the issue, but this should never be the solution.

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Real-World Data: How Clear Is Your Picture?

By Ben Holmes, senior clinical data analyst, Syapse.

When it comes to getting a clear picture from real-world data, breadth of view and careful analysis matter equally.

Interpreting data is always a challenge; it’s a problem space with high dimensionality, deeply interrelated variables, and where data completeness is defined in infinite ways. Separating actionable insights from mountains of data requires rigorous statistical validation, thoughtful modeling, and a variety of analytic approaches. Biostatisticians take these steps to avoid biasing results, and to make sure that samples are truly representative and relationships between variables are accounted for.

But even with all possible care and due diligence taken, it’s possible to arrive at skewed results if the view from the data sources included is limited by their inherent biases. For example, mortality is an important data element in oncology research that helps oncologists communicate chances of remission to their patients. Yet, in the real-world setting, there isn’t a single complete source for mortality data that can be used to better understand remission and survival rates.

This is, partly, because many of the traditional mortality data sources only apply to certain groups of patients. For example, death data from hospital registries is only applicable for patients in cases where registry data is available. Additionally, registries tend to rely on electronic health record (EHR) and obituary data to capture deceased status, which do not naturally account for all patients—for example, women and minorities are less likely to have obituaries. With that in mind, datasets that rely heavily on obituary data alone are going to under-represent deaths and overall survival curves associated with women and minorities. This finding is consistent with recently published studies of digitized obituaries which showed that women were awarded significantly fewer obituaries compared to men.

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Solving The Challenges of Provider Database Management

By Priya Sabharwal, practice leader, network operations, HGS.

Priya Sabharwal
Priya Sabharwal

Imagine a scenario: A patient looking for a new doctor searches her insurer’s online network directory to find a provider her plan will cover. She selects what seems to be the perfect doctor based on her criteria, which could include gender, office location, languages spoken or other qualifications, in addition to being in-network with her health plan.

But there’s a plot twist: The patient eventually learns the doctor she found is not, in fact, the right option for her – but it took her scheduling and arriving at the appointment for her to realize this. It turned out the entry in her insurer’s directory was outdated, and her doctor had moved offices.

This scenario is hardly out of the ordinary. A 2019 Health and Human Services survey uncovered errors in half of the listings in Medicare plans alone. These significant inaccuracies cause issues not just for patients, but for payers and providers, too:

So what are some steps payers and health plans can take to create a solid provider data foundation? It starts with fundamentally changing the way we think about, use, enter and maintain data.

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Data Trends In Healthcare Informatics

By Adrian Johansen, freelance writer; @AdrianJohanse18.

Person Holding Pen Writing on Daily Report Schedule Paper

Without a doubt, data is the driving force for innovation within healthcare. It has allowed for processes to be streamlined, busy work to be automated, and medical professionals to have more time with their patients. This data within health informatics is giving doctors, nurses, and the like access to better patient information and allowing more precision within their work.

This patient information includes data on socioeconomic, environmental, biomedical and genetic factors. Data insights are transforming the healthcare industry, and experts point to artificial intelligence (AI) as the future of medical tech. One thing agreed on across the board is that, with these advancements, medical professionals will be able to treat patients with better accuracy.

These innovations are disrupting two arenas within the industry: patient care and institutional structure. Not only do these innovations in healthcare informatics better inform doctors and allow patients to receive an improved quality of care, but they can ensure that healthcare facilities run more smoothly. Here are a few ways that innovations from data informatics have been changing the world of healthcare.

More Patient-Focused Care

Data has allowed medical care to become more patient-focused. This means more time and effort is given to patients individually. Doctors have less paperwork to do because a lot of the organizational work is automated. But patients are also able to take care of themselves at home, or at least effectively communicate with doctors about their condition.

There are many applications for telemedicine and remote patient monitoring. We are seeing sexual health, disease symptoms and concerns, heart rate, dietary problems, and mental health counseling being addressed with apps or telemedicine practices.

For instance, rather than waiting for regularly scheduled checkups, some patients are able to take their own blood pressure and report it to their doctor using a mobile app. This is done through a process called computerized provider order entry (CPOE). Some doctors are wary of this practice, which has inspired conversations about the trustworthiness of patients. But it could be incredibly helpful for those with limited means of transportation or who rely on a caretaker.

AI is able to operate with expert precision and analyze patients in a way that doctors have never been able to. For instance, AI can accurately detect skin cancer. In the past, doctors would have to determine this from dermoscopic images. AI is able to analyze patients and provide a more accurate result. This advancement could have incredible consequences for cancer prevention.

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The Most Useful Technological Advancements In Healthcare

It’s no secret that healthcare has greatly improved with the advent of technology. We all know the drill. The usual benefits that we’ve been able to derive from technology comes in the form of better data management, clearer communication, minimized margin of error, and the improved accuracy and efficiency of medical diagnoses.

These are all the usual advantages we hear and read about, and it’s come to a point that these are now part of the norm. Nowadays they are generally integrated into the system of any hospital. But there’s a downside to that. These advancements are sometimes forgotten because they’ve become so common in the healthcare business.

So, as a gentle reminder to appreciate the things that we already have, these are some of the ways that technology has definitely improved the healthcare industry:

Improved Communication

 The link between doctors and patients has definitely improved because of technology. For example, if you find yourself involved in a vehicular crash, there are two people you’re going to want to call: Car and bus injury lawyers and doctors. Because of their busy schedules and HIPAA regulations, most doctors can prove to be difficult to contact.

There are several platforms on the internet that allow you to get in touch with a doctor to ask for medical advice. There are many apps that are also able to translate spoken word into a language that whomever you’re speaking with is able to understand, which is handy when traveling in a foreign country.

Better Data Management and Sharing

Gone are the days when patient files had to be physically stored in filing cabinets. There was the problem of these files taking up physical space, of course, but there was also the problem of having to organize these files. Human error is always a factor, but as the scope of work increases, so do the chances that an error may be committed. Today, we are able to store medical data in computers, which also means that we are able to recover data when needed. You never know when medical data may be needed by professionals from other fields of study. Whichever the case, data management is far more secure and far more efficient today than it ever was.

Remote Observing and Alerting

 Thanks to home monitoring systems, doctors are now able to check on their patients without the need to be physically present. This reduces the costs involved with recurring clinic visits and the time spent doing so. Patients will also be able to alert emergency medical personnel if something is wrong. This is especially vital for patients who have a pacemaker put in.

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Will Industry Outsiders Save Healthcare Dollars Through Data?

By Luke Bonney, co-founder and CEO, Redox.

Luke Bonney
Luke Bonney

With every sector of the economy feeling the effects of ever-increasing healthcare costs and no relief in sight, it’s no wonder household names outside of traditional healthcare are stepping in and attempting to improve what could only be characterized as a problematic system.

Industry outsiders take an interest in “solving” healthcare

This year began with three modern-day titans of industry declaring they are ready to disrupt healthcare. Jeff Bezos of Amazon, Warren E. Buffett of Berkshire Hathaway, and Jamie Dimon of JP Morgan Chase announced they were forming an independent healthcare company for their employees. By June they named a CEO for this venture: Dr. Atul Gawande. A Harvard surgeon, author, and executive director for Ariadne Labs, Dr. Gawande has built his career on examining how medicine is practiced in the US.

While the details of their effort remain scarce, Dimon has shared some broad strokes of what the triad is focused on, his list ranges from improving wellness programs aimed at smoking and obesity to using big data and virtual technology to align incentives.

Industry outsiders see data as a key leverage point

What is noticeably apparent with this surge in “healthcare outsiders” is that none of these big players are attempting to remake all of healthcare. To remake a system as vast and complex as the US healthcare system is more than any one company or consortium can reasonably hope to do.

However, they all do seem to be focused on data as the key point of leverage for disrupting and remaking a segment of healthcare. Gathering and processing data into diagnostic, predictive, or operational information is seen as the leverage point for ultimately making healthcare more efficient and effective.

Some of these industry outsiders are focusing their efforts directly on finding and exploiting opportunities for cost savings. Here are some examples.

Optimizing the pharmacy purchasing experience

Making the patient purchasing experience for pharmaceuticals, medical devices, and medical supplies seamless and reliable has drawn the attention of Amazon.

For the patient ordering and refilling prescriptions, the process could be automated and culminate in same-day delivery to the patient’s door. To some extent, patients will be able to comparison shop for non-prescription items and bundle purchases. For the seller inventories and distribution can be centralized and possibly some operational savings can be realized.

Finding a more efficient way of selling and delivering medical supplies will increase convenience for patients. But patients rarely pay the full cost of their prescriptions, so the cost drivers present in optimizing retail sales aren’t present at the pharmacy.

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HIMSS15 Trade Show Vendor Highlight: BridgeHead Software

In this series, we are featuring some of the thousands of vendors who will be participating in the HIMSS15 conference and trade show. Through it, we hope to offer readers a closer look at some of the solution providers who will either be in attendance – with a booth showcasing and displaying key products and offerings – or that will have a presence of some kind at the show – key executives in attendance or presenting, for example.

Hopefully this series will give you a bit more useful information about the companies that help make this event, and the industry as a whole, so exciting.

Elevator Pitch

A leader in healthcare data management, BridgeHead Software is addressing the constraints of the traditional vendor neutral archive (VNA) with HealthStore, the first independent clinical archive (ICA).

About Statement

With 20 years’ experience in data and storage management, BridgeHead Software is trusted by over 1,200 hospitals worldwide. Today, BridgeHead Software helps healthcare facilities overcome challenges stemming from rising data volumes and increasing storage costs while delivering peace of mind around how to store, protect and share clinical and administrative information.

BridgeHead’s Healthcare Data Management solutions are designed to work with any hospital’s chosen applications and storage hardware, regardless of vendor, providing greater choice, flexibility and control over the way data is managed, now and in the future.

Services and Products Offered       

BridgeHead HealthStore, is the first Independent clinical archive (ICA) for long-term storage, protection and sharing of hospital data. A modular solution built on top of the BridgeHead Healthcare Data Management (HDM) platform, BridgeHead HealthStore enables hospitals to standardize access to key elements of the patient record while simultaneously freeing them from dependence on any single system to locate the information.

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