Data analytics is the next step in the evolution of healthcare as it uses data-driven findings to predict and address health issues. Healthcare data analytics can also help to keep track of inventory and access methods and treatments faster than conventional systems. Data analytics is often paired with health information exchanges (HIEs) to provide safer and more personalized care based on patients’ medical history, chronic conditions and medications. Healthcare data analytics software extracts, translates and synthesizes vast amounts of data to reduce costs, involve patients more in their own health and wellness and improve patient outcomes.
Opportunities and practical applications of data analytics in healthcare
Data analytics in healthcare relies on big data (vast quantities of digitized information) that gets consolidated and analyzed. The application of data analytics in healthcare has life-saving outcomes as it uses data of a subset or a particular individual to prevent potential epidemics, cure diseases and cut down on healthcare costs. Here are a few of the opportunities and practical applications of data analytics in healthcare.
Predictive analytics for personalized treatments
Predictive data analytics is the process of using historical data in order to make predictions that are personalized to each individual. Typically, analytics tools use information from millions of patients to help doctors make data-driven decisions and improve the delivery of care. Predictive data analytics helps to identify individuals who are at an elevated risk of developing chronic conditions based on lab tests, biometric data and patient-generated health data. Physicians can provide insight on lifestyle changes, wellness activities and enhanced services that can help patients avoid long-term health problems. This is particularly useful for patients with complex medical histories and suffering from multiple conditions,
Data analytics to advance telemedicine
Data analytics and telemedicine go hand in hand as it helps to empower physicians and patients and offers opportunities for remote patient monitoring and remote clinical services. Smart devices are the future of telehealth monitoring as they monitor a patient’s vitals in real-time and communicate with other devices and cloud health information systems based on data analytics to alert physicians about potential problems and provide analysis on possible interventions. Data analytics in telemedicine can help to predict acute medical events – this doctors to alter medication dosages to avert negative outcomes and prevent deterioration of patients’ conditions. Telemedicine also cuts down on costs, reduces the need for hospital visits and allows patients to live healthier and more comfortable lives.
Data analytics for real-time alerting
Hospitals have started employing clinical decision support (CDS) software that analyzes medical data on the spot and provides health care experts with suggestions as they make prescriptive decisions. However, in cases where patients are unable to make frequent hospital visits, doctors recommend wearables that collect patients’ data and send it to the cloud continuously. This data is analyzed continuously so that the system can identify potential problems and send real-time alerts to physicians. Doctors can then contact patients immediately to administer medications to prevent problem escalation.
By Dr. Chris Hobson, chief medical officer, Orion Health.
Dr. Chris Hobson
Health information exchanges (HIE) help care teams provide more informed patient care by supplying a complete longitudinal healthcare history of the patient to healthcare professionals, as well as enabling high quality reporting and analytics on the data. The goal of an HIE is to accurately store all relevant patient information from as many sources as possible, including medical history, medication history, past treatments and detailed personal information. A comprehensive reporting system allows for health delivery that is more responsive and tailored to each patient, and subsequently, the broader population.
Today the transition to value-based funding models seeks to lower costs and improve patient care and outcomes in order to lead to the better management of entire populations. Population health management (PHM) involves changing the behavior of engaged consumers to lead healthier lives and encouraging physicians to focus on providing the best possible quality of patient care at the lowest possible price. This requires providers to collaboratively address whole populations and orchestrate healthcare provision at large scale. Below are several challenges organizations must overcome before closing in on the goal of PHM.
Payer-provider collaboration and targeted incentives
Payers and providers must work together and, in particular, must find ways to effectively share their different types of data. Collaboration is needed to achieve shared goals such as understanding and improving the health of a population and enhancing the patient experience, all while constraining costs.
A key issue between payers and providers is agreement on the quality measures that will be incentivized. PHM places an unfair, high burden on providers if required quality measures vary widely across payers or if the measure does not clearly reflect a meaningful quality of care indicator. In the latter situation, a provider’s time and effort are used for inefficient purposes adding to a physician’s frustration with the healthcare system. Conversely, payers have additional data that can often help providers significantly with their population health management needs.
Care coordination
Fragmentation of care poses a challenge for health systems globally, and there is research to suggest that this problem is more persistent in the U.S. than its international peer countries. Studies have highlighted the major consequences of a poorly coordinated health system, including delays in care, incorrect care, and unnecessary complications, tests and procedures. Frequently, poor communication, difficulty sharing care plans and challenges coordinating actions by multiple caregivers across organizations results in confusion, delays in care and even incorrect care actions, putting the patient’s health on the line. A health system that is not well coordinated cannot deliver high quality care at lower costs.
Physician involvement in preventive care and the social determinants of health
For physicians, finding ways to move care from the acute setting toward health promotion, disease prevention and addressing the social determinants of health is quite difficult and not something they are necessarily empowered to do today. Currently, the majority of physicians do not have the tools to solve major intractable social issues such as poverty, so involving physicians and patients in the strategic design of a social determinants of health program is an essential step toward resolution of these types of concerns.
By Ken Perez, vice president of healthcare policy, Omnicell, Inc.
Ken Perez
It was such a beautiful, logical vision: The creation of “an electronic circulatory system for health information that nourishes the practice of medicine, research, and public health, making health care professionals better at what they do and the American people healthier,” as David Blumenthal, the National Coordinator for Health Information Technology from 2009 to 2011, wrote in an article on the potential of the HITECH Act’s subsidization of the adoption of EHRs by hospitals and physician practices that appeared in the Dec. 30, 2009, issue of the New England Journal of Medicine.
The HITECH Act was combined with the American Recovery and Reinvestment Act of 2009 (ARRA), an economic stimulus bill created to help the U.S. economy recover from an economic downturn that began in late 2007. The passage of the bill spawned an ambitious vision of an elaborate national health information infrastructure that would enable frictionless, collaborative data sharing primarily through a National Health Information Network (NHIN) that would connect an interlocking web of regional health information organizations (RHIOs) and health information exchanges (HIEs).
It must be emphasized that the NHIN vision was a federal government vision—not one generally shared by the private sector. It was never realized, and the adoption of EHRs by healthcare providers has been described as “a digital revolution gone wrong” and “a bridge to nowhere,” in the 15-page cover article of Fortune magazine’s April issue, entitled “Death by a Thousand Clicks,” by Erika Fry of the magazine and Fred Schulte of Kaiser Health News.
For their report—which has the feel of an exposé — Fry and Schulte interviewed more than 100 physicians, patients, IT experts, administrators, health policy leaders, attorneys, government officials, and representatives from several leading EHR vendors. They employ a combination of poignant vignettes of patients who were harmed by EHR shortcomings — including the experiences of former Vice President Joe Biden’s son Beau and the husband of CMS Administrator Seema Verma — as well as ample facts and figures.
Per Fry and Schulte, the federal government has spent $36 billion to date to subsidize the adoption of EHRs by healthcare providers, and today, 96 percent of non-federal acute care hospitals and 86 percent of physician offices have EHRs.
Despite the significant amount of federal funding and broad adoption of EHRs, they have not fulfilled their potential, as Blumenthal has admitted. The expected “digital dividend” from EHRs has not materialized, or at least its magnitude is much smaller than hoped for. According to Fry and Schulte, EHRs’ general demerits include poor, tedious usability—which adds work and is cited as a major contributing factor to physician burnout — rampant errors that lead to patient safety risks, “upcoding” (bill inflation), lack of interoperability, widespread data blocking, and patients’ inability to access their EHRs. Data silos clearly exist between the 700 federally certified EHRs of widely varying functionality, as well as between provider organizations and other players in the healthcare system. In short, idealism has run into the reality of commercialization.
Fry and Schulte provide no optimistic, Hollywood ending to the article. Industry attempts to promote interoperability are described as fledgling, and their sobering conclusion is that the state of EHRs in the United States is “an unholy mess.”
Hardly a day goes by without some new revelation of a US IT mess that seems like an endless round of the old radio show joke contest, “Can You Top This”, except increasingly the joke is on us. From nuclear weapons updated with floppy disks to needless medical deaths, many of which are still caused by preventable interoperability communication errors as has been the case for decades.
According to a report released to Congress, the Government Accountability Office (GAO) has found that the US government last year spent 75 percent of its technology budget to maintain aging computers where floppy disks are still used, including one system for US nuclear forces that is more than 50 years old. In a previous GAO report, the news is equally alarming as it impacts the healthcare of millions of American’s and could be the smoking gun in a study from the British Medical Journal citing medical errors as the third leading cause of death in the United States, after heart disease and cancer.
The GAO interoperability report, requested by Congressional leaders, reported on the status of efforts to develop infrastructure that could lead to nationwide interoperability of health information. The report described a variety of efforts being undertaken to facilitate interoperability, but most of the efforts remain “works in progress.” Moreover, in its report, the GAO identified five barriers to interoperability.
Insufficiencies in health data standards
Variation in state privacy rules
Difficulty in accurately matching all the right records to the right patient
The costs involved in achieving the goals
The need for governance and trust among entities to facilitate sharing health information
CMS Pushing for “Plug and Play” Interoperability Tools that Already Exist
Meanwhile in a meeting with the Massachusetts Medical Society, Andy Slavitt, Acting Administrator of the Centers for Medicare & Medicaid Services’ (CMS) acknowledges in the CMS interoperability effort “we are not sending a man to the moon.”
“We are actually expecting (healthcare) technology to do the things that it already does for us every day. So there must be other reasons why technology and information aren’t flowing in ways that match patient care,” Slavitt stated. “Partly, I believe some of the reasons are actually due to bad business practices. But, I think some of the technology will improve through the better use of standards and compliance. And I think we’ll make significant progress through the implementation of API’s in the next version of (Electronic Health Records) EHR’s which will spur innovation by allowing for plug and play capability. The private sector has to essentially change or evolve their business practices so that they don’t subvert this intent. If you are a customer of a piece of technology that doesn’t do what you want, it’s time to raise your voice.”
He claims that CMS has “very few higher priorities” other than interoperability. It is also interesting that two different government entities point their fingers at interoperability yet “plug and play” API solutions have been available through middleware integration for years, the same ones that are successfully used in the retail, banking and hospitality industries. As a sign of growing healthcare middleware popularity, Black Book Research, recently named the top ten middleware providers as Zoeticx, HealthMark, Arcadia Healthcare Solutions, Extension Healthcare, Solace Systems, Oracle, Catavolt, Microsoft, SAP and Kidozen.
Medical Errors Third Leading Cause of Death in US
The British Medical Journal recently reported that medical error is the third leading cause of death in the United States, after heart disease and cancer. As such, medical errors should be a top priority for research and resources, say authors Martin Makary, MD, MPH, professor of surgery, and research fellow Michael Daniel, from Johns Hopkins University School of Medicine. However, accurate, transparent information about errors is not captured on death certificates which are the documents the Center for Disease Control and Prevention (CDC) uses for ranking causes of death and setting health priorities. Death certificates depend on International Classification of Diseases (ICD) codes for cause of death, but causes such as human and EHR errors are not recorded on them.
According to the World Health Organization (WHO), 117 countries code their mortality statistics using the ICD system. The authors call for better reporting to help capture the scale of the problem and create strategies for reducing it. “Top-ranked causes of death as reported by the CDC form our country’s research funding and public health priorities,” says Makary in a press release. “Right now, cancer and heart disease get a ton of attention, but since medical errors don’t appear on the list, the problem doesn’t get the funding and attention it deserves. It boils down to people dying from the care that they receive rather than the disease for which they are seeking care.”
The Root Cause of Many Patient Errors
Better coding and reporting is a no-brainer and should be required to get to the bottom of the errors so they can be identified and resolved. However, in addition to not reporting the causes of death, there are other roadblocks leading to this frighteningly sad statistic such as lack of EHR interoperability. Unfortunately, the vast majority of medical devices, EHRs and other healthcare IT components lack interoperability, meaning a built-in or integrated platform that can exchange information across vendors, settings, and device types.
Various systems and equipment are typically purchased from different manufacturers. Each comes with its own proprietary interface technology like the days before the client and server ever met. Moreover, hospitals often must invest in separate systems to pull together all these disparate pieces of technology to feed data from bedside devices to EHR systems, data warehouses, and other applications that aid in clinical decision making, research and analytics. Many bedside devices, especially older ones, don’t even connect and require manual reading and data entry.
Healthcare providers are sometimes forced to mentally take notes on various pieces of information to draw conclusions. This is time consuming and error-prone. This cognitive load, especially in high stress situations, increases the risk of error such as accessing information on the wrong patient, performing the wrong action or placing the wrong order. Because information can be entered into various areas of the EHR, the possibility of duplicating or omitting information arises. Through the EHR, physicians can often be presented with a list of documentation located in different folders that can be many computer screens long and information can be missed.
The nation’s largest health systems employ thousands of people dedicated to dealing with “non-interoperability.” The abundance of proprietary protocols and interfaces that restrict healthcare data exchange takes a huge toll on productivity. In addition to EHR’s physical inability, tactics such as data blocking and hospital IT contracts that prevent data sharing by EHR vendors are also used to prevent interoperability. Healthcare overall has experienced negative productivity in this area over the past decade.
With the implementation of the Affordable Care Act pushing hospitals and health systems to provide services more efficiently, a significant number of hospitals, health systems and providers are sharing secure patient information through health information exchanges (“HIEs”), and accountable care organizations (“ACOs”). The advent of both the HIEs and the ACOs are additional opportunities for protected health information to be shared by hospitals, doctors and other providers.
HIEs allow for patient information, including lab tests, imaging tests, prescriptions and treatments, to be shared by the participants in the HIE. The development of these electronic HIEs allow for the secure exchange of health information among entities participating in the HIE. Generally, the rights and responsibilities of those entitled to share the information is governed by participation agreements. Many providers believe that sharing data will improve healthcare and promote not only quality of care, but efficient care, as well. Similarly, the development of ACOs by otherwise independent providers results in more patient information shared in electronic fashion. The advent of both HIEs and ACOs provide another medium for possible breaches of the privacy rule.
The privacy rule requires that covered entities verify the identity and authority of persons requesting Protected Health Information (“PHI”) if the individual requesting it is not known to the entity. The Rule, however, does not specify in great detail the verification that must be made and, thus, there is flexibility that can be applied with regard to HIEs and ACOs.
Generally, in a HIE, the participants agree, by contract or otherwise, to provide to the HIE a list of authorized persons so the HIE can appropriately authenticate users of the network. Documentation required for uses and disclosures may be provided in electronic form, and documentation requiring signatures may be provided as scanned images. It is important from an HIE perspective for the various participants to agree on a common set of privacy safeguards that are appropriate to the risk associated with exchanging PHI to and through the HIE. Similarly, with ACOs, the ACO should establish a common set of privacy safeguards that are appropriate to the privacy risks associated with multiple providers using PHI. These common standards would include a breach notification policy or procedure. To fully understand what must be done, one must have a basic understanding of what is considered a breach.
Guest post by Fauzia Khan, MD, FCAP, is chief medical officer and co-founder of Alere Analytics.
This has been a very interesting year for the healthcare industry, which appears to be on the brink of a real sea change. Government mandates are driving transformative discussions in the C-suite circles on topics such as meeting meaningful use Stage 2 and Stage 3 requirements, satisfying Accountable Care Organization (ACO) standards, care delivery models in the patient-centered medical home and much, much more.
Some of the most concise, yet useful, information about health information exchanges must come from Medicity. In a “primer” page (that might be written for the HIE novice) there’s quite a nice bit of information about the importance of the technology.
Obviously, Medicity is biased, as HIE is what it does, but I admit that after reading some of the points Medicity makes about the importance of HIEs, I’m sold (though I already was).
Let’s dig in.
As we know, health information exchanges help connect healthcare providers with information they likely would not have through paper records, and in many cases, not even with electronic health records as the EHRs are often fragmented or don’t depict the entire health scenario of a patient.
As noted by Medicity, HIEs help create efficiencies in the care setting in many ways, primarily by helping make information available across many platforms and even across many care locations.
Additionally, and I’m paraphrasing here: HIEs help reduce duplicate testing of patients; help create a more complete picture of a patients’ care and prior treatment protocols; and they help eliminate costs and fees associated with redundancies.
The best case I can make for an HIE (probably for an EHR, as well) is a story from a former colleague. Her mother was diagnosed with an aggressive form of cancer. At best, she was given months to live. However, after multiple specialist visits, redundant tests, labs and scans delivered the same information as the previous test, the woman died just a few weeks after initial diagnosis.
Moral of the story is this: according to my colleague, for every specialist she and her late mother visited, each one requested the same tests as the previous doc because the doc didn’t have an accurate, or complete, record. To make matters worse, the records were paper. My former colleague said the task of trying to assemble a complete care record was beyond arduous, not to mention difficult to construct given the red tape each practice had in place as the gate keeper of the records it kept.
If only the information had been in a single repository, perhaps her mother wouldn’t have wasted so much time on taking the same tests and she could have received the care she needed, my colleague said. I agree.
So does Medicity, which operates on the belief that HIEs change all of that. Simply and clearly put, HIEs “break down silos and make information available” to providers at virtually any location that’s connected to the HIE when the information is needed and required.
HIEs, like EHRs I suppose, can change and possibly save lives. Interestingly enough, at least to me, is that HIE’s lag in favor or in the very least have a history of not being able to generate the support they need to thrive (perhaps survive?).
As the government continues to place more importance on the availability of health information through exchanges and electronic records, the market will find a way to monetize HIEs (probably the biggest hurdle vendors face when considering whether to develop technologies to support them).
There are now, though, several vendors with their own HIE-like devices that can function within their EHRs the same way their patient portals work. They are able to trasmit data to other users of their company’s specific technology.
As these vendors continue to develop their own HIEs, and try to sell them, it will be interesting to see which technology – private or public – will be adopted by the healthcare community.
Data analytics is the next step in the evolution of healthcare as it uses data-driven findings to predict and address health issues. Healthcare data analytics can also help to keep track of inventory and access methods and treatments faster than conventional systems. Data analytics is often paired with health information exchanges (HIEs) to provide safer and more personalized care based on patients’ medical history, chronic conditions and medications. Healthcare data analytics software extracts, translates and synthesizes vast amounts of data to reduce costs, involve patients more in their own health and wellness and improve patient outcomes.
