At the beginning of their existence, electronic health records (EHRs) were primarily used as a document management system. Now, they have realigned their objectives and value to the physicians and practices they serve, to focus on data intelligence. If specialty practices want to stay independent they need to continue to evolve, prioritize value-based care and stay profitable. Moreover, they need the right partners to help enhance operational efficiency, increase patient engagement and achieve better clinical outcomes. As such, the scope of the EHRs responsibility for the practice’s health, growth, and sustainability has increased exponentially.
How will specialty practices ensure their future? By leveraging the power of clinical and operational data in their EHR and supplemental business applications, working together within the healthcare IT (HCIT) ecosystem. Businesses across all industries analyze data to measure overall industry performance. Metrics are the foundation for any successful business and physician groups are not excluded. Metrics should be the driving force behind every major decision that will boost productivity. However, physicians are not data scientists, but by utilizing the next generation HCIT systems, they can employ technology that will streamline the decision making process.
Challenges turn into opportunities
According to the Centers for Medicare and Medicaid Services (CMS), 171,000 physicians who did not collect and use data to comply with government regulations are looking at a three percent Meaningful Use penalty in 2017. Coupled with a new focus on value-based care requirements playing a critical role in care and outcomes, upgrading their data platform and capabilities should be the number one priority to comply with new industry standards. Data driven HCIT solution providers can prepare specialty practices for these coming changes. They help collect and analyze data to ensure effective treatment plans at lower costs.
Bottom line: This helps improve patient health and satisfaction.
Today’s HCIT systems are considered business tools that help physicians analyze data and reveal insights to use for enhanced decision making. Popular “big-box” HCIT systems try to be all things to all providers, yet they are tailored to hospitals and primary care physicians—many who typically see far fewer patients in a day than specialists. This puts a major burden on specialists, who rely on different clinical and operational data to help maximize outcomes.
Specialists potentially see up to 60 patients a day – and cover surgeries, follow-ups and everything in between. Generic HCIT systems fall short in relation to appointment volume. Combined with the fact those systems make data entry inefficient, impede clinical workflows, and lack business metrics, this is the major argument for specialty-focused HCIT solutions. Some groups acquired by hospitals or health systems have not adopted the integrated systems of their new parent companies. Instead, they stay with their specialty HCIT systems—interoperable with their parent companies’ technology—because of their ability to serve existing, proven workflows.
Data insights and a workflow makeover
Specialty HCIT systems that analyze a variety of data and provide practices with the knowledge to improve their performance will deliver the best outcomes for patients and practices. Analyzing operational data provides an understanding of how to deliver the best patient care at the lowest cost, thereby delivering optimal outcomes and increasing patient satisfaction levels.
Specialists should take the opportunity to re-evaluate their EHR and determine if their goals are helped or hindered by their current HCIT ecosystem. A productivity-boosting HCIT system can harness the power of data to deliver clinical and business applications, workflows, and insight through one user interface and make compliance with reporting requirements simple and straightforward.
Guest post by Joel Rydbeck, director, healthcare technology and strategy, Infor.
Healthcare is undergoing rapid “digitization” – a move toward an integrated ecosystem of mobile applications and data exchange that integrate consumer data into the enterprise. For healthcare, this could enhance patient engagement and enable care to become more efficient and “real time”.
Nonetheless, moving to a more digital healthcare enterprise presents a series of challenges:
How will the data be transmitted and is it semantically interoperable?
Where and how much should be persisted?
How can the data be made “actionable” for the clinician?
We’ve all visited a doctor and been asked “How are you sleeping?” and “Are you getting exercise?”. If you are among the growing number of people with a fitness tracker, you may think, “Hold on, I have that recorded”. So, you pull out your mobile phone and respond “I am getting six to seven hours of sleep a night and about 11,000 steps a day. Is that good?” While your doctor may understand your quick synopsis of the data, imagine if they were getting the data real-time. Would they know what to do with it? What if it contains disturbing trends? It would be unfortunate if crucial information wasn’t put to good use. But how?
Interactions like these prompted Washington University’s Olin School of Business and Infor Healthcare to collaborate on improving the usability of personal tracker data. This collaboration included conducting a small survey of 39 physicians from a broad spectrum of specialties asking their thoughts about the use of tracker data for clinical care.
The survey uncovered differing views on what information would actually be useful, showing:
56 percent thought active hours would be useful,
46 percent said miles walked or intensity of movement,
36 percent included steps taken as a useful metric,
and 10 percent the said the degree of upward incline during movement would be useful.
The survey also asked providers what factors would enhance their likelihood of using tracker data for patient care. Majority would like to see better integration with their electronic health record (EHR), more patients using the devices, and additional data, such as blood sugar, being collected.
Physicians reported lack of education as a barrier to effectively using the data. About 50 percent believed that education, in the form of a short presentation or discussion, would be useful while 31 percent thought that a short guide would suffice.
While two-thirds of providers were open to discussing personal trackers with their patients, they did express concerns in using the data for care. The data must be proven accurate before physicians will place trust in it. Inconsistent or inaccurate data could lead to unnecessary anxiety and possibly harm. Also noted is that extraneous data can clutter the EHR and complicate patient care. Many of the providers mentioning drawbacks to using device data stated that the devices might work best as motivational tools for patients. More study towards interpreting tracker data for clinical use is needed.
Guest post by Abhinav Shashank, CEO and co-founder, Innovaccer.
The story of Geraldine Alshamy explains how a minor complication in healthcare network can be catastrophic! The patient started experiencing severe headaches, and she was rushed to an emergency room. Since she didn’t have a primary care physician, she had a previous condition of hypothyroidism. But because of a lack of proper communication channel, her care process wasn’t the best that she could have gotten and, unfortunately, she had a heart attack!
This story might seem unusual but enough to understand that the consequences of uncoordinated health care could be grave. Health care is too critical and margin of error doesn’t exist here, it is imperative that we realize the importance of coordinating the healthcare sector and bridge the gaps in care.
Why Coordinated Healthcare?
When patients are brought in to be treated, the thing that physicians, nurses, assistants and other professionals require are the relevant medical information about them. For such a scenario, healthcare providers need to be well connected to provide coordinated care through smooth information flow.
According to a survey, some 40 percent of physicians believe that their patients undergo problems because of lack of coordination and information exchange between providers. The possibility of repetitive tests, unnecessary visits to the emergency rooms and preventable readmissions increases, giving way to poor health outcomes. Inadequate care coordination is estimated to cost as much as $45 billion to the healthcare industry, tagged as wasteful spending — $8.3 billion are lost every year because of inefficient technology.
What is the aim?
With everything around us changing and healthcare picking up pace, it’s high time we start thinking accordingly. The future of healthcare is smart teams aiding the one-on-one patient-physician interaction for better outcomes. These teams have physicians, nurses, financial advisors, health coaches and even family members and watch over patient’s health, follow-ups, and the insurance matters as well.
We have to move beyond the paradigm of isolated partial care towards integrated teams performing comprehensive patient care by encouraging the development of technology and providing care at hand with the center of our focus being:
1.) Accessible Care Anywhere
There used to be a time where people were not as well-connected to each other, and the only way of staying informed was telephones, letters, and postcards. With the evolution of information technology, we can safely share every ounce of information.
We need to put the rapid evolution of information technology to use and have patients connected with their physicians. Real-time alerts, genome sequencing, and data analytics will help us establish a world where patients won’t necessarily have to travel to a particular building and wait for hours to get treated.
2.) Connected Care Networks
Coordinated healthcare will hardly be possible without interoperable technology: teams connecting providers and specialists everywhere with the aim to deliver quality care. And the primary requirement for creating this team would be health information exchange, followed by notifying the PCPs.
As developers of electronic health record (EHR) software, my company gets into a lot of conversations with providers about their expectations for the future. This information helps us make decisions about what to build next. Here are three trends we’re hearing from our customers right now:
Low-tech beats high-tech in telemedicine
Unlike the way it was imagined decades ago by science fiction writers, telemedicine does not necessarily mean holographic images or live video conferencing with a physician half a continent away. Patients would rather receive “low tech” remote care from their primary care physician who has a full picture of their health status.
This form of telemedicine happens whenever an EHR system adds to a patient’s clinical chart the messages, pictures, or videos sent securely via smartphone. It happens whenever a smartphone connects to a remote health monitoring device for collection of real-time data such as blood pressure, oxygen levels, and heart rate.
The new rules allowing reimbursement of telemedicine and other non-face-to-face services will encourage physicians to bill for these remote care activities. Medicare’s recently expanded set of billing codes for Chronic Care Management (CCM) is a good example of how the future of value-based care goes beyond the office visit to keep patients out of hospitals and emergency rooms. The ability to securely and rapidly receive and answer a patient’s questions via text, and then capture those activities in the patient’s permanent clinical record is a critical step in that direction.
Primary care providers are trying new types of practices
Primary care physicians are frustrated with the hassle and expense of dealing with insurance companies. The new Medicare fee-for-value quality payment program is creating uncertainty about future reimbursement levels and requires additional reporting. Also, there is an acute level of burnout with “corporate medicine,” which has providers booked for dozens of daily appointments, only to spend less than 15 minutes with each patient.
In order to remain independent, a small but growing group of primary care practitioners are becoming more financially creative and experimenting with new models of practice. One example is direct care, in which a financial relationship is established directly between patient and provider, cutting out insurance altogether. This model includes concierge and direct primary care (DPC), where patients become “members” of a practice and pay a fixed monthly fee for unlimited primary care – similar to a gym membership, but for healthcare. Another example of direct care is the cash-only practice that sees walk-in patients for urgent care.
EHR interoperability will catch FHIR
Physicians and their patients are frustrated with the lack of interoperability in health IT. The concept of having a patient’s medical records accessible to any authorized provider at any time is still a rare occurrence. When a patient switches primary care physicians, the first office typically prints out and faxes their medical records to the second office, which introduces the possibility of errors, HIPAA violations, and others.
Guest post by Abhinav Shashank, CEO and co-founder, Innovaccer.
The picture of healthcare industry is changing rapidly and still continues to evolve, with technology playing a huge role and the other factor being the government. With a new administration in the White House, the Senate and the House of Representatives, there ought to be numerous changes in healthcare, modifying ACA being one of them. Come January, what will be the effect of the new policies of the GOP have on health IT?
In his victory speech, President-elect Donald Trump emphasized on restoring and improving infrastructure and calling healthcare and hospitals an integral part of that plan. The Trump administration even after a session is less likely to remove its focus from IT investments and developments in healthcare; the Republicans believe in leveraging technology and healthcare experts are confident that healthcare-related initiatives like Cancer Moonshot and Precision Medicine Initiative will continue to speed up.
According to a recent ONC report, 96 percent of hospitals and 78 percent of physician offices were using certified EHRs to maintain patient data.
With digital initiatives developing, the hassle in prescribing medicines, scheduling appointments and access to vital records have reduced.
Making the consumer the center of the healthcare system and empowering them has been favorable. According to a survey conducted on 13,000 users, it was revealed that 28% changed their providers based on data made available online – implying that patients wish to be a part of the decision making.
A substantial number of digital health startups have emerged, and their revenue in 2015 was over $4.5 billion – and continues to grow.
Health IT developments to look ahead
Although Donald Trump has his healthcare plan for the country under the covers, some significant advancements are coming our way and following is a slice of what’s coming:
Value-Based Care: One of the most important thing Trump has asserted on in his plan is that he wants to ensure that “no one slips through the cracks simply because they cannot afford insurance.” With U.S. healthcare accounting for 17.1% of the entire nation’s GDP, it’s important to back this transition towards value-based care.
Advancements in Interoperability: In ONC’s latest report to Congress, interoperability was tagged as an essential priority. There are still a lot of factors getting in the way of free flow of data between providers, topped with the inability on patients’ part to access their medical information freely. There are many initiatives on the block: the Sequoia Project’s Care Quality programs, the development of FHIR standards that will be backed by Trump and will pan out impressively.
Banking on Digitization: In sustaining the momentum of this transformation, digitization would be the cornerstone. The use of data analytics, machine learning, patient-centered technology developments and the Internet of Things will unleash their forces under Trump administration and fuel further developments and investments.
Changing the Dynamics of the Marketplace: Donald Trump plans to allow insurance companies to sell their plans across the state lines which may result in an increase in competition and making their plans value-focused. Allowing a free market for drug import could also prove critical in reducing the cost of healthcare: he said in one of his speeches that Medicare could save as much as $300 billion every year, if drug prices were negotiated.
Health IT will stay because the need is to continue to work on making healthcare industry interoperable. Major value-focused programs on healthcare by federal government, such as MACRA won’t see significant changes. However, there is a possibility that the Quality Payment Program could be “enhanced.”
Guest post by Santosh Varughese, president, Cognetyx.
Since cybersecurity healthcare threats on hospital EHR systems have become a topic of nightly newscasts, no longer is anyone shocked by their scope and veracity. What is shocking is the financial damage the attacks are predicted to cause as they reverberate throughout the economy.
In the 30 days of June 2016, more than 11 million patient EHRs were breached, making it the year’s worst incident according to a study by DataBreaches.net and Prontenus. For comparison, May had less than 700,000 and 2016’s former breach leader (March) topped out at just over 2.5 million.
While traditional security filters like firewalls and reputation lists are good practice, they are no longer enough. Hackers increasingly bypasses perimeter security, enabling cyber thieves to pose as authorized users with access to hospital networks for unlimited periods of time. The problem is not only high-tech, but also low-tech, requiring that providers across the healthcare continuum simply become smarter about data protection and privacy issues.
Healthcare security executives need to pick up where those traditional security tools end and investigate AI cybersecurity digital safety nets. IDC forecasts global spending on cognitive systems will reach nearly $31.3 billion in 2019.
CISOs are recognizing that security shields must be placed where the data resides in the EHR systems as opposed to monitoring data traveling across the network. Cloud deployment directly targeting EHR systems data is needed rather than simply protecting the network or the perimeter.
Pre-cursors to AI are also no longer that reliable. Organizational threats manifest themselves through changing and complex signals that are difficult to detect with traditional signature-based and rule-based monitoring solutions. These threats include external attacks that evade perimeter defenses and internal attacks by malicious insiders or negligent employees.
Along with insufficient threat detection, traditional tools can contribute to “alert fatigue” by excessively warning about activities that may not be indicative of a real security incident. This requires skilled security analysts to identify and investigate these alerts when there is already a shortage of these skilled professionals. Hospital CISOs and CIOs already operate under tight budgets without needing to hire additional cybersecurity guards.
Some cybersecurity sleuths deploy a variety of traps, including identifying an offensive file with a threat intelligence platform using signature-based detection and blacklists that scans a computer for known offenders. This identifies whether those types of files exist in the system which are driven by human decisions.
However, millions of patient and other medical data files need to be uploaded to cloud-based threat-intelligent platforms, scanning a computer for all of them would slow the machine down to a crawl or make it inoperable. But the threats develop so fast that those techniques don’t keep up with the bad guys and also; why wait until you are hacked?
The Mix of Forensics and Machine Learning
Instead of signature and reputation-based detection methods, smart healthcare CSOs and CISOs are moving from post-incident to pre-incident threat intelligence. AI innovations that use machine learning algorithms to drive superior forensics results and deploy pre-incident security are just what the IT doctor should be prescribing.
In the past, humans had to look at large sets of data to try to distinguish the good characteristics from the bad ones. With machine learning, the computer is trained to find those differences, but much faster with multidimensional signatures that detect problems and examine patterns to identify anomalies that trigger a mitigation response.
The current plight of America’s healthcare industry is not wholly unprecedented. In fact, it isn’t even unique.
American education — higher education in particular — is going through a parallel period of turmoil and scrutiny. It is really uncanny how closely the two industries actually reflect one another. Consider:
Both are critical industries whose public/private status is up for constant debate
Both serve an essentially captive market: everyone needs education to succeed in the economy, and everyone, sooner or later, will require some form of healthcare
There has been a historical tendency for both to treat the people they serve as customers, rather than as students or patients. It is more than semantics: it is a reflection of an underlying philosophy that can potentially compromise the mission of each type of institution
Both are going through a crisis of accountability, in terms of what standards are used to measure their performance, and to whom they must answer for that performance
Both have been very slow to adopt modern technology, and as a result are going through a rapid, disruptive catch-up period
In the race to modernize and reconcile many of these conflicts of purpose and identity, it appears that higher education as a whole may be slightly ahead. Because of this relative lead on the healthcare industry, behavior within the American college and university system can act as a rough preview for the health sector. So, what do we see upon gazing into this crystal ball?
All for One?
A helpful place to direct this gaze is the recent ASU GSV Summit. The name alone reveals much about what is happening in higher education, and needs to happen in healthcare: Arizona State University, in the interest of promoting innovation, collaboration, and evolution in the higher education sector, joined forces with Global Silicon Valley’s family of companies to create their joint summit.
The summit began in 2009, seven years into the tenure of ASU president Michael Crow, who has become one of the leading voices and actors in higher education’s 21st century evolution. The summit is just one of the many strategic partnerships Crow has helped organize through ASU. Aligning the school with everything from technology startups supporting the development of ASU’s online degree programs, to the Mayo Clinic Medical School to offer future doctors transdisciplinary education in fields like business or engineering, Crow is expanding the reach of America’s largest public university by strategically sharing its resources.
In American medicine, there is a clear need for a similar attitude toward strategic partnerships and mission alignment, especially with technology companies and developers. This need is most acute in terms of EHR interoperability. Despite all the rhetoric, the old mentality of siloes, competition, and proprietary ownership prevail, and information remains immobile.
This symptom has implications that extend into every other facet of healthcare.
Patrick Soon-Shiong, billionaire, surgeon and incorrigible optimist, has set his sights on curing cancer. Much like the Precision Medicine Initiative, Soon-Shiong’s approach to this challenge is a matter of getting more, better data from as many partner institutions as possible.
“Cancer is really a rare disease,” he explains. “Because of the molecular signature, because of the heterogeneity, no single institution will have enough data about any [single] cancer. So you actually need to create a collaborative overarching global connected system.”
The end result — better medicine, better outcomes — is something common to the mission of every clinical organization, and ever caregiver practicing medicine. But the means — large scale collaboration, facilitated by transparency and a suspension of select elements of competition — are seldom realized in the current environment. Reconciling the ends and the means requires organizations to think bigger than themselves, and prioritize the sort of partnerships that bring new perspectives, larger pools of data, and creative solutions where they are desperately needed.
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.
Guest post by Alexandra Roden, content editor, Connexica.
Just a few years ago, big data and the Internet of Things (IoT) were terms generally unheard of. This year they continue to revolutionize technology and the ways in which we acquire and process data, but what do they mean for the healthcare industry?
Xenon Health describe IoT as “a phenomenon through which the operational aspects of the physical world become increasingly integrated with digital platforms, enabling information to move seamlessly toward the computational resources that are able to make sense of it.” Essentially, IoT goes hand-in-hand with the mobile age and the diversity of data that is currently being retrieved from agile and mobile locations.
Big data is a related concept – it addresses the ever-increasing amounts of data that are created every second of every day and recognizes that these figures will only continue to grow. For example, in the “social media minute” every single minute there are 277,000 tweets are sent, Whatsapp users share 347,222 photos and Google receives more than 4,000,000 search queries. These figures are remarkable even for those of us caught up in the social media hype, and most shocking of all is the realization that the global Internet population now represents 2.4 billion people. That’s a lot of people creating a lot of data – the question now is how we can utilize this data in a meaningful way.
IoT has revolutionized many industries and will continue to do so in the foreseeable future, but what about healthcare? Organisations within this industry tend to adopt new technologies slowly, relying upon solid evidence and demonstrable impact and efficiency before committing to any such change. The shift towards IoT is, however, beginning to take place, and increasing amounts of available patient data are beginning to inform decision making processes within this sector.
By Darin M. Vercillo, MD, chief medical officer and co-founder, Central Logic.
Healthcare has been changing rapidly for the last 60 years and advances have now reached record speed, including in the realm of data intelligence. In trying to keep pace as well as to protect and advance their own businesses, many processes and systems have understandably been organized into silos. That era must come to a close.
Care coordination teams need rich collaboration of data and must now be connected. Hospitals, clinics, home health care workers, primary care physicians, vendors, and others must speak with each other, in the same language, and completely share patient data with an open, collaborative attitude. The industry is all abuzz with this uncharted territory called interoperability. It is clear that data warehouses, now bursting with valuable information, must be streamlined for three very simple reasons: patient safety, cost-effective healthcare delivery and overall population health management. A happy byproduct when data intelligence becomes actionable and systems work collaboratively is a financial benefit, but as a physician, I believe excellent patient care always wins the day, and should be the driving factor.
At the risk of this being looked at as “just a financial issue,” consider also that hospitalization is generally a marker for severe illness. Our goal is a healthier population. As we (patients and providers) succeed collectively with hospital treatment and post-acute care, then re-admissions will naturally decrease, and patients will live healthier, more satisfied, lives. Ultimately, this is our goal.
Appropriate, timely sharing of vital patient information will not only address re-admission rates that have clearly become egregious, but improved collaboration of data needs to happen to better inform decision making at the point of care. Without a keen eye to patient safety and success, it is too easy for details to slip through the cracks. All too often, history has demonstrated that hand-off points are the riskiest for failures in patient care.
Nearly everyone has a story where the current system has failed patients — just ask Jennifer Holmes, our CEO. Her father’s healthcare team made an error in medication that ultimately cost him his life. Similar medication errors and decreased duplicate testing can be avoided when a patient’s entire care coordination team has visibility into the data – all the data – to improve care efficiencies and diagnoses.
But all this sharing and playing nice in the sandbox is easier said than done.