In recent years, the public sector has become increasingly aware of the multifaceted potential of big data. These days, government agencies around the world collect vast amounts of data from people’s activities, behaviors, and interactions—a virtual treasure trove of information that the public sector can utilize and turn into actionable insights, and later, into actual solutions.
The big challenge, however, is that government agencies are falling under more and more pressure to find relevant insights from complex data while relying on limited resources and technologies with inadequate capabilities. And with the sheer size of data being generated nowadays, it’s becoming more difficult to extract meaning from what the data hides beyond their colossal façade.
Thankfully, there is one critical technology that is redefining the way public sector agencies study and utilize data, and this is artificial intelligence. Today, artificial intelligence solutions that make use of technologies like machine learning and topological data analysis can automatically process big data and discover patterns and anomalies no matter how complex and seemingly disjointed these different points of data are.
Precisely because of these advantages, artificial intelligence solutions are now being used by numerous public sector agencies and institutions around the world. In this article, we’ll fill you in on the basics of three important areas of the public sector in which AI is currently making waves.
The financial industry is one of the biggest producers and exchangers of data, and as such, it stands to benefit immensely from artificial intelligence technologies. Every day, government-owned banks and other financial institutions buy, borrow, and trade currencies and financial products, generating massive amounts of data from customers, partners, and other stakeholders.
In many jurisdictions over the world, value-based care is being adopted as an alternative healthcare model that focuses more on accountability, and on the type and quality of service provided to patients instead of the volume of care provided. With this increased emphasis on value, government-aligned health providers and insurance systems have begun using artificial intelligence software in order to become more agile and proficient at managing the risks of patient pools.
This way, even with the immensity and complexity of patient data, public sector providers and health payers are able to better understand clinical variations, as well as automatically predict individual and subpopulation risk and health condition trajectories. Through insights gained from these data, clinicians and other personnel across the healthcare spectrum can then better determine the best and most affordable courses of care, in addition to being able to confidently recommend the most appropriate health programs for their governments to implement.
Guest post by Abhinav Shashank, CEO and co-founder, Innovaccer.
Time is money, an adage the world follows. When providers realized paper medical records were time-consuming, Electronic Health Records were developed to make things streamlined. Early EHRs were only meant to capture basic clinical information, and over the time EHRs have taken the form of a digital version of paper medical records. In an industry as dynamic and as focused on value as healthcare, it’s not feasible to have physicians spend almost half their time on EHRs.
Challenges physicians face with EHRs
EHRs, in their current state, not only consume a lot of physicians’ time, but they also draw their attention away from their direct interactions with patients. Some of the several significant challenges physicians face are:
Data entry and administrative tasks take up a lot of physicians’ time, according to a study, during the office day, physicians spend as much as 49.2 percent of their time on EHRs.
The demands of desk work and administrative work are not being reconciled with patient priorities and clinical workflows; creating huge gaps between patients and providers. For example, during patient examinations, physicians spend 37 percent of their time on data entry and desk work, compromising on their direct interaction with patients.
Physicians are only reimbursed for face-to-face visits, lab work, and medical procedures and not for EHR tasks. This increases the misalignment in fee-for-service payments and compounds the risk of physician burnout.
Why can’t we do away with EHRs?
While EHRs are not without their own set of challenges, their implementation was necessary, and that still holds true. Only recently, under the Merit-Based Incentive Payment System (MIPS), providers have started to make an effort to enhance value in the care they deliver and the meaningful use of EHRs has been included in MIPS with other substantial quality reporting initiatives. Besides that, there are many offerings of EHRs:
A quick and real-time access to patient records.
Reliable drugs and test prescriptions.
Complete clinical documentation, inclusive of patient medical history.
Accurate and streamlined coding and billing operations.
Reduced cost of operation.
EHR Optimization: Boosting your EHRs
EHR optimization is the process of enhancing and refining the operations of an already installed EHR, to enhance clinical productivity and efficiency. As more and more practices have begun the push for value-based reimbursement, they are demanding more integrated and efficient EHRs.
Opportunities for EHR optimization vary for every practice and range from simple to complex. However, the primary objective of every optimization is reducing the time consumed. Here are some ways healthcare IT platforms can optimize time spent on EHRs for improved patient outcomes:
Establish key performance indicators: Once a healthcare organization has examined its baseline performance, it can decide on goals and target a benchmark for future. Organizations can leverage advanced analytics to determine their progress across each key performance indicator which in turn, helps with quality reporting.
Comprehensive and complete clinical records: It’s important that a patient record is complete- right from their past medical history to their last lab test results. Along with that, if providers are able to look at all vital signs at once, the entire process of designing and implementing a care plan would become efficient.
Implementing clinical decision support: By combining clinical decision support with EHR data, providers can ensure safer and efficient care delivery by documenting every interaction and eliminating redundancies. With every information documented, providers can address the gaps in care well in time.
Sharing vital information across the network: More often than not, the delay in accessing information is the major reason behind improper or delayed care. It’s important that clinical data, lab test results, referrals, etc. are shared across all providers to ensure seamless treatment and population health management.
Monitor, evaluate and maintain results: To ensure the success of optimization isn’t short-lived, providers should continuously monitor their process improvement. Organizations should evaluate their growth and shortfalls and make their efforts to sustain and improve the results they achieve.
Guest post by Abhinav Shashank, CEO and co-founder, Innovaccer.
The way we see healthcare today is very different from what it was a couple of decades ago. Back then, we did not have the technology to capture the best practices. But, today we have the capability to use medical data as a source of innovation and create impact at scale. But the question is are we capitalizing on it? Have we made the lives easier for both patients and care teams? Are we close to the goals we started chasing ten years ago?
When we talk about innovation in healthcare, we stumble across intuition. The intuition of care teams enhanced by data-driven approaches. It is not just limited providing connectivity to healthcare organizations; it is also about providing advanced analytics and reducing the cumbersome, tedious work! Like deep diving for hours on Excel or making quality tracking and reporting easier.
The concept of population health management is a new one. It has evolved from an idea to become a clinical discipline that works on developing and continually refining measures to improve the health status of populations. A successful population health management program thrives on the vision to deliver robust and coordinated care through a well-managed partnership network. This said, there is no one definition of Population Health Management, fifty different CIOs in an interview gave different definitions to this term. It is a broad concept and covers a lot under its umbrella.
What does an ordinary health IT setup lack?
True, the healthcare systems are working on building the skills to interact and develop well-planned health intervention strategies to move away from the traditional fee-for-service model to value-based reimbursements and incorporating value, but they are falling short in many areas:
Limited EHR capability: EHRs played a pivotal role in digitizing health care, but with EHR technology many restrictions came along. Today, only a few are equipped to support the necessary interoperable standards. To deliver better clinical outcomes, it is of paramount importance that we have the data and right analytics to ensure improvements; something healthcare organizations lack even today.
Integrating data sources: A patient who is being relocated to a new state and will have a new PCP and Care Coordinator. Can we say with confidence that the patient’s information will be available to the new PCP? In a large healthcare network, there is labs, pharmacy, clinical, claims, and operational data, but the capability to integrate it into a single source of truth is still a challenge for many! This has limited the potential of care teams and made them communicate in a disconnected ecosystem.
Risk Stratification: 50 percent of expenditure in healthcare is on 5 percent patient population. Wouldn’t it be great if we could find these patients and cure them before any acute episode? Back in 2012, about 117 million Americans had one or more chronic conditions, and account for 86 percent of the entire healthcare spending. The road to population health management will require care teams to recognize at-risk population timely to reduce cost and improve outcomes!
Guest post by Abhinav Shashank, CEO and c0-founder, Innovaccer.
Former US President Abraham Lincoln once said, “Give me six hours to chop down a tree and I’ll spend four hours sharpening the ax.” After having a look at the efficiency of the US healthcare system, one cannot help but notice the irony. A country spending $10,345 per person on healthcare shouldn’t be on the last spot of OECD rankings for life expectancy at birth!
A report from Commonwealth Fund points how massive is US healthcare budget. Various US governments have left no stone unturned in becoming the highest spender on healthcare, but have equally managed to see most of its money going down the drain!
Here are some highlights from the report:
The US is third when it comes to public spending on health care. The figure is $4,197 per capita, but it covers only 34 percent of its residents. On the other hand, the UK spends only $2,802 per capita and covers 100 percent of the population.
With $1,074, the US has the second highest private spending on healthcare.
In 2013, US allotted 17.1 percent of its GDP to healthcare, which was highest by any OECD country. In terms of money, this was almost 50 percent more than the country on the second spot.
In the year 2013, the number of practicing physicians in the US was 2.6 per 1000 persons, which is less than the OECD median (3.2).
The infant mortality rate in the US was also higher than other OECD nations.
Sixty-eight percent of the population above 65 in the US is suffering from two or more chronic conditions, which is again the highest among OECD nations.
The major cause of these problems is the lack of knowledge about the population trends. The strategies in place will vibrantly work with the law only if they are designed according to the needs of the people.
What is Population Health Management?
Population health management (PHM) might have been mentioned in ACA (2010), but the meaning of it is lost on many. I feel, the definition of population health, given by Richard J. Gilfillan, president and CEO of Trinity Health, is the most suitable one.
“Population health refers to addressing the health status of a defined population. A population can be defined in many different ways, including demographics, clinical diagnoses, geographic location, etc. Population health management is a clinical discipline that develops, implements and continually refines operational activities that improve the measures of health status for defined populations.”
The true realization of population health management (PHM) is to design a care delivery model that provides quality coordinated care in an efficient manner. Efforts in the right direction are being made, but the tools required for it are much more advanced and most providers lack the resources to own them.
If population health management is in place, technology can be leveraged to find out proactive solutions to acute episodes. Based on past episodes and outcomes, better decision could be made.
The concept of health coaches and care managers can actually be implemented. When a patient is being discharged, care managers can confirm the compliance of the health care plans. They can mitigate the possibility of readmission by keeping up with the needs and appointments of patients. Patients could be reminded about their medications. The linked health coaches could be intimated to further reduce the possibility of readmission.
Over the past few years, healthcare technology has seen many advances. We’ve achieved mass-market adoption of EHRs, many organizations are making meaningful progress on data aggregation and warehousing information from multiple diverse systems, and wearables and other sensors show much potential to unlock personal information about each patient. The pace of change in healthcare is quickening, with each new technology or initiative sending off a chain of reactions across the entire ecosystem, ultimately improving patient care.
I see three trends driving the industry toward change:
Analytics will help predict population heath management
One of the persistent industry challenges is the “datafication” of healthcare. We’re amassing more and more data now than ever before. And new sources (like wearable devices) and new health factors (like DNA) will contribute even more. This data explosion is putting increased pressure on healthcare organizations to effectively make this data useful by delivering efficiency gains, improve quality of care and reduce overall healthcare costs.
Navigating this digitized healthcare environment will require increasingly sophisticated tools to help handle the influx of data and make the overload of healthcare information useful. In 2016, the industry will begin to take concrete steps to transition to a world where every clinician will see a snapshot of each of their patients to help them synthesize the critical clinical information they need to make a care decision. Moreover, hyper-complex algorithms will allow providers not only to know their patients, but to accurately predict their healthcare trajectories. By giving providers insights into how each patient is trending, clinicians will be able to make better-informed, precise decisions in real-time.
Consolidation leads to new healthcare models, improved outcomes
New models for effective population health management continue to drive change across healthcare systems. These models incentivize stakeholders to optimize costs, identify organizational efficiencies and improve decision-making processes to deliver better care at a lower cost through an emphasis on care coordination and collaboration.
After years of underinvestment, CIO’s in healthcare may have something to cheer about this year. The biggest trend seems to be the increased focus and investment in IT in healthcare enterprises. With more than $30 billion invested in electronic health record (EHR) systems, and meaningful use (MU) requirements out of the way, we are seeing enterprises turn toward the more strategic aspects of IT in the ongoing transformation of the healthcare sector.
These investments, however, will follow the money. In other words, funding will focus on initiatives that have the biggest impact in terms of revenues, cost avoidance, and transformative potential. A recent survey by technology provider Healthedge suggests that investments among payers will be targeted at selective enhancements to the most critical systems that support business development, and not a wholesale upgrade of IT. Here are a few of the top investment areas across healthcare:
Population Health Management (PHM): Everybody is on board with the concept of PHM as the defining principle in an outcomes-based business model. However, PHM has eluded a consistent definition, other than that its desired impact is to reduce overall costs of patient populations, and improve clinical outcomes. Analytics has been an important aspect of this discussion, however standalone analytics solutions have struggled to demonstrate value, and progress on advanced analytics involving predictive models and cognitive sciences has been slow. This year may change all of that. Many standalone analytics companies are likely to be acquired, and IBM Watson will gain more traction. M & A in healthcare will drive PHM as well.
Information Security: With healthcare data breaches at over 112 million in 2015, including high-profile breaches at Anthem, Premera, and Excellus, IT security is now a CEO level issue. There is no doubt what this means – investments in data security technologies are going to increase. However, there is no guarantee that data breaches will not increase.
Healthcare Consumerism: Changing demographics and unexpected increases in the costs of health insurance are driving the consumerization of healthcare today. Silicon Valley startups, flush with VC money, are coming up with direct-to-consumer approaches that are making traditional healthcare firms sit up and take notice. At the same time, the newly awakened healthcare consumer is also demanding information and price transparency. New York Presbyterian has launched a patient-first marketing strategy aimed at improving engagement with patients through information sharing, and is revamping its website completely. BCBS of NC has already released the cat among the pigeons by publishing price data (and is facing pushback from its provider network). IT investments will now be focused on maximizing the reach and value of the information to empower consumers to make the right choices.
Guest post by Kirk Larson, national CIO, healthcare, NetApp Inc.
As we start a new year, let’s take a moment and take stock of the past 12 months. Like an annual physical, it gives us a chance to take a pulse check on the industry and see what the next year has in store – the opportunities and the obstacles.
During 2015, we had the opportunity to chat candidly with CIOs, healthcare technology partners and healthcare providers to discuss the big questions affecting the industry:
— What are the big topics the industry will be focused on?
— What changes do you see coming?
— What new challenges lay ahead and what new technologies will help us overcome them?
Based on these discussions, here are some of the key trends healthcare CIOs can expect in 2016:
Electronic Health Record (EHR) Optimization
As healthcare organizations move beyond implementation phase of EHRs, CIOs and IT are refocusing their efforts towards enhancing care workflow and benefits realization by way of optimizing the IT infrastructure. Basically, the status quo on overspending on legacy hardware is no longer being tolerated.
While the high availability, performance and security requirements for IT infrastructure certainly aren’t lessening anytime soon, IT is feeling greater cost pressures to run EHRs more efficiently. As a result, organizations are looking to simplify IT operations for running on-premises data centers with improved data management solutions, with the end-goal of moving toward building their own private clouds.
In addition to greater cost efficiency, we are seeing a growing demand for increased agility of IT services. As such, organizations are looking to advanced analytics capabilities as a means of achieving greater responsiveness. But before they can reap the benefits of employing a population health management system, IT needs to shift from tired legacy IT environments to highly agile IT infrastructure.
Population Health Management
Population health management programs have long been used by healthcare insurers to increase wellness and decrease claims cost. Organizations leverage multiple data sources such as EHRs, pharmaceutical data, insurance claims, etc.; to enhance and preserve wellness, as well as, programs that anticipatory and pre-emptive in design.
Guest post by Mohd Haque, vice president and global business head, healthcare, Wipro Technologies.
Population health management (PHM) isn’t just the latest buzzword. Or a new initiative mandated by the Affordable Care Act. Implementing a successful PHM program requires a complete shift in mindset from volume healthcare to value-based and outcome-based. PHM can’t be something that your healthcare facility “does,” but it must become the cornerstone of everything related to how your facility practices medicine.
Although the shift in perspective is the first step, it is essential to arm yourself with Population Health Management IT tools as well. According to 26th Annual HIMSS Study, half of the respondents (51 percent) have improved PHM through IT tools with only 38 percent saying that their organization was using specific Population Health Management tools.
By using big data analytics, EHR integration, IT infrastructure and security as part of a PHM program, providers can ensure patients that need high levels of care aren’t overlooked and the lower risk patients don’t get unnecessary care. This will in turn increase quality of care while saving money on interventions needed for low risk patients.
What are the Components of Effective PHM Program?
Since PHM is such a large shift, it is important to know exactly how to go about creating an environment that focuses on outcomes instead of volume. Population Health Alliance recommends the following four components to a PHM program:
Assessment – Evaluate each patient’s health and assign patients to a risk group (high to low)
Stratification – Provide the same interventions for everyone in the same risk group
Person-Centered Intervention – Provide interventions based on each specific patient’s needs, including community health research
Impact Evaluation – Determine the impact of interventions for each risk group as well as each individual patient
However, you can’t simply change the process without changing how each person on the team views healthcare and their patients. It must be a fundamental shift in your facility from the receptionist to the department chief.
Electronic health record (EHR) technology has become truly transformative for the healthcare industry; prepared or not, healthcare teams are increasingly relying on new information technologies to improve the delivery and management of care. EHRs have enabled faster and easier access to patient information, and hold the promises of improved workflows, efficient sharing of information across communities and reduced costs for many physicians and hospitals.
But now that nearly 80 percent of physician practices in the U.S. today have EHR systems in place and the Centers for Medicare & Medicaid Services’ (CMS) meaningful use program is well underway, it is time to look to the next stage of health care technology and innovation. Health care teams must now move beyond the first step of digitizing patient records to transforming this valuable data into meaningful and actionable knowledge that will help care teams make more informed decisions at the point of care and ultimately, improve outcomes.
For this impact to take place at both the individual level and at the population level, care teams need to leverage clinical analytics that will provide visibility into important clinical trends across the entire population. For example, being able to review trends in diabetes care or readmission rates across a population represents an opportunity for specific, meaningful change to improve care delivery and outcomes.
For a practicing clinician, “population health management” means being able to see where an individual patient is within the clinician’s or clinic’s population (e.g., whether the individual’s chronic condition is above or below population benchmarks) and to take action at the point of care, as well as being able to refer to relevant population health metrics.
For a patient, clinical analytics presumes trust, not only in the competency and care of the physician, but also in the security of his or her information. Population health management and analytics tools must ensure that patient information can be gathered, stored, and used in a way that is demonstrably secure.
Care teams should consider four key elements when exploring clinical analytics tools for population health management:
Guest post by Diane D. Homan, MD and Adam Lokeh, MD.
As the healthcare industry unwraps the next phase of population health management (PHM), providers are increasingly embracing its promise to drive success with healthcare’s triple aim of improving population health, enhancing patient experiences and reducing costs. It’s a 180-degree shift in thinking for many providers who have been conditioned to long-standing fee-for-service models, one that will require a coordinated care effort and an advanced technological infrastructure to support decision-making based on the latest industry evidence.
As regulatory initiatives, such as meaningful use and value-based purchasing converge to up the ante on improved outcomes, the proactive premise of PHM will be critical to success. A foundational component to effective implementation of a PHM model is a clinical decision support (CDS) strategy that drives standardization of care based on best practices.
For Rush-Copley Medical Center, the first step in this process was deployment of evidence-based order sets and a complete clinical content management solution— ProVation Order Sets, powered by UpToDate Decision Support. The decision to leverage evidence-based order sets at the point of care has proven advantageous on many fronts, from supporting recent responses to public health crises to raising the bar on outcomes improvement and laying a foundation of accountability across the continuum.
Reducing Variation for Improved Response
Getting clinicians on the same page and helping them to adopt industry best practices in their day-to-day workflows is certainly a key element in bending the quality curve, but ensuring that variations are minimized in a public health crisis is absolutely critical to success.
A 210-bed hospital serving the greater Fox Valley region of Illinois, including the state’s second largest city, Aurora, Rush-Copley uncovered an outbreak of tuberculosis (TB) in late 2009 following two admissions over the course of two months. In cooperation with the Kane County Health Department, an investigation traced the outbreak back to a homeless shelter, which, in turn, presented a considerable challenge to containing the outbreak as the population was highly transient.
With evidence-based order sets and an advanced clinical content management solution already deployed to address standardization of care, the clinical team was able to quickly deploy a point-of-care strategy for identifying at-risk patients, apply isolation management tactics and develop collaborative efforts throughout the community to minimize exposure. The strategy was three-fold: 1) contain the epidemic, 2) provide highest quality treatment based on industry best practices and 3) avoid duplication of services.