10 HEALTHCARE ANALYTICS TRENDS FOR 2016
Healthcare industry transformation is providing organizations with an opportunity to revolutionize how they operate. The digitization of medical records, wearable technologies, mobile, and the Internet of Things are contributing to the data deluge, and innovations in technology are making it possible to transform this data into meaningful and actionable insights to enhance patient care and consumer experience, reduce overall costs, and transform business. It is critical for healthcare organizations to strategically align technology initiatives with business objectives in order to meet the demands of the new healthcare era. Patients, just like consumers in other industries, are accustomed to having access to data and being in the driver s seat throughout their journey. They are seeking personalized approaches, transparency, and more control of their overall healthcare experience. Expectations are higher than ever before, making it imperative for organizations to invest in technologies that will help meet these rising expectations and drive loyalty through patient satisfaction. THE DIGITAL STRATEGY OF A HEALTHCARE ORGANIZATION MUST BE ALIGNED WITH EVERYDAY CONSUMER EXPERIENCES IN OTHER INDUSTRIES. - DAVID CHOU, HEALTHCARE CIO Meeting the rising expectations of patients and members requires organizations to manage their data. While this may seem like a simple task, for most organizations it is quite daunting. Healthcare organizations are inundated with data; unfortunately, this data is not useful unless it can be transformed into timely and actionable insights. Transforming data into knowledge requires integrating disparate data sources, creating true interoperability, and having a strong business intelligence and analytics strategy. With these pieces in place, healthcare executives can make decisions on hard data rather than intuition, and healthcare providers have realtime insights at their fingertips in order to deliver high-quality and affordable patient care. In this guide we take a look at ten analytics trends healthcare executives need to be thinking about in 2016 and beyond. We identify technology strategies and solutions that will help healthcare organizations succeed in a data-driven, digital world.
10 HEALTHCARE ANALYTICS TRENDS FOR 2016 1 2 3 4 5 6 7 8 9 10 Align Clinical, Quality and Financial Analytics to Enable Value-Based Care Integrate Clinical and Claims Data to Enable Population Health Management Insight Leverage Cross-Continuum Data Analysis for Improved Patient Care and Outcomes Grow Enterprise Intelligence to Measure and Improve Patient and Organizational Health Utilize Reusable Accelerators to Quickly Achieve Actionable, Data-Driven Insights Use Predictive Analytics to Reduce Readmissions and Improve Outcomes Leverage New Tools and Skills to Transform Large Volumes of Data into Meaningful Information Increase Level of Understanding and Control Over ACO Data and Analytics Develop and Implement a Strong Governance Strategy and Organization Position Big Data Technologies to Enable the Everyday Use of Data Science
#1 ALIGN CLINICAL, QUALITY AND FINANCIAL ANALYTICS TO ENABLE VALUE-BASED CARE Healthcare organizations today are being challenged to reduce costs, improve care coordination and outcomes, be patient-centric, and provide more with less. And they are doing all of this while trying to adhere to regulatory requirements and untangle the entrenched web of inefficiencies that negatively impacts both progress and, ultimately, clinical outcomes. One change that is directly impacting healthcare providers is the transition from a volume-based (fee-for-service) to a value-based care delivery model. Value-based care requires reporting hundreds of process and performance measures to various quality and regulatory programs, like the Medicare Shared Savings and Pioneer ACO programs, in order to be reimbursed. The Patient Protection and Affordable Care Act (ACA) changes provider reimbursements by focusing on the Triple Aim: improving the health of the population, enhancing the experience and outcomes of patients, and reducing the cost of care. Medicare reimbursements are based on value, not volume. This means hospitals and physicians will see their payments modified so that those who provide higher-quality care will receive higher payments than those who provide lower-quality care. For example, looking at just the value-based purchasing adjustment, which incorporates a number of quality measures, Definitive Healthcare estimates in 2015 there were 100 hospitals that received more than $250,000 in additional revenue, and nearly 130 hospitals that were penalized more than $250,000. To avoid these penalties, it is critical for healthcare organizations to unite quality indicators and measures with clinical analytics that drive operational performance. Care delivery teams within healthcare organizations are dependent on high-quality data in order to make timely decisions that positively impact the outcomes of the individuals, organizations, and communities they serve. By truly harmonizing clinical analytics and quality indicators, healthcare organizations can move from reactive reporting to proactive and actionable insights that uncover process improvement opportunities in real-time. 100 SHORT-TERM ACUTE CARE (STAC) HOSPITALS RECEIVED A POSITIVE REVENUE ADJUSTMENT OF MORE THAN $250,000 DUE TO VALUE-BASED PURCHASING 129 STAC HOSPITALS RECEIVED A NEGATIVE REVENUE ADJUSTMENT OF MORE THAN $250,000 DUE TO VALUE-BASED PURCHASING 539 STAC HOSPITALS HAD AN ESTIMATED REVENUE LOSS OF MORE THAN $250,000 DUE TO THE READMISSION PENALTY Stats per Definitive Healthcare estimates FY 2015
Success Story NORTHWESTERN MEDICINE Northwestern Medicine is a leader in quality healthcare and service, bringing together faculty, physicians, and researchers to support and advance care through leading-edge treatments and breakthrough discoveries. Northwestern Medicine did not have a central repository to perform enterprise-wide analytics, and its infrastructure, business rules and processes were not defined or robust enough to support the new value-based care model. It lacked the dashboards and tools necessary to both provide a complete view of the patient population, and to track physician performance as it relates to ACO measures. Perficient implemented a centralized data warehouse to house all patient data, physician rosters and claims files including MSSP, ACE and BCBS data. This central repository provided a complete view of all of Northwestern Medicine s patients regardless of their hospital affiliation. Business intelligence reporting and analytics dashboards helped Northwestern Medicine proactively monitor physician performance and identify cohorts of patients with chronic conditions, or those who qualify for wellness screenings, based on a specified inclusion and exclusion criteria. A series of clinical integration physician progress reports were generated monthly to indicate whether physicians are compliant with ACO and Northwestern Medicine performance measures.
#2 INTEGRATE CLINICAL AND CLAIMS DATA TO ENABLE POPULATION HEALTH MANAGEMENT INSIGHT Technology-enabled population health initiatives have traditionally relied solely on either clinical data or claims data. While this method has value, there is a tremendous opportunity for healthcare organizations to take population health efforts to the next level by integrating both clinical and claims data. Integrating clinical data from electronic medical records with claims data can help develop a more complete patient view and improve overall care. Merging clinical and claims data provides healthcare organizations with a more complete picture and delivers the insights needed to address their most complex challenges. When combined, clinical and claims data can be used to: 1. Compare recommended care against evidence-based practices 2. Improve overall care management and population health efforts 3. Reduce unnecessary clinical procedures 4. Help patients avoid hospitalization by identifying early risk factors The integration of clinical and claims data empowers healthcare providers to delivery higher quality and more proactive care for their patients. Healthcare organizations should leverage insights generated from clinical and claims data to drive greater coordination of care and provide robust reporting to enhance population health initiatives. Population health is a big focus for the healthcare industry, and there are many different programs, resources, and technologies available to support this initiative. Robust healthcare data is becoming more readily available as healthcare provider organizations and health plans recognize the importance of sharing patient data to improve outcomes and reduce costs. Organizations that leverage the combination of clinical and claims data will have a strong foundation for population health management. However, those that maximize the value of this data by transforming it into meaningful and actionable insights to help meet quality, cost and patient satisfaction objectives will thrive in the quickly evolving ecosystem.
INTEGRATING DATA FOR POPULATION HEALTH MANAGEMENT At ProHealth Care, we were challenged with immense amounts of data coming from various systems and sources. We not only needed to integrate our systems to manage this data, but we needed to make the data actionable. The implementation of our data warehouse has provided our organization with the tools and processes to better manage population health data, giving physicians access to information in real-time, setting the stage for preventive care and improving overall patient care and the health of our population. Perficient has been our go-to partner and trusted advisor in this endeavor due to their deep healthcare industry expertise and we look forward to continuing our partnership with them on ongoing improvements and future projects. - CHRISTINE BESSLER, CIO, PROHEALTH CARE
#3 LEVERAGE CROSS-CONTINUUM DATA ANALYSIS FOR IMPROVED PATIENT CARE AND OUTCOMES Despite all the changes within the industry, the healthcare continuum remains relatively the same. However, our perspective across that continuum has changed considerably due in large part to the enhanced view enabled by healthcare analytics. Historically, healthcare analytics has been used to manage care within the four walls of the traditional care setting. Healthcare reform, specifically the arrival of accountable care and payment reform, has led to a greater emphasis on care across the entire continuum. As the transformation from a volume-based to a value-based care model continues, healthcare organizations are experiencing a reduction in reimbursement. This reduction in reimbursement is putting added pressure on organizations that are trying to meet new demands. The increasing number of individuals covered by high-deductible health plans, (many of whom are delaying care as long as possible) is adding to the complexity, forcing healthcare organizations to look for alternate ways to reduce costs while still providing quality care. Healthcare organizations are turning to cross-continuum analytics to discover opportunities to reduce care delivery costs, streamline processes, and enhance patient care for the populations they serve. Cross-continuum analytics requires the integration of multiple, disparate clinical and operational systems. Healthcare organizations need access to timely and accurate data across the entire continuum of care to leverage the power of information and turn it into meaningful and actionable insights to improve care delivery for individuals and populations. HOW CROSS-CONTINUUM ANALYTICS CAN INCREASE QUALITY OF CARE One way to begin to analyze cross-continuum data in the absence of full system integration is to leverage claims data to analyze claims by a certain population across different providers. This allows hospitals to analyze their network leakage, share of patient care, referral patterns, and more. For example, according to Definitive Healthcare, Massachusetts General Hospital (MGH) saw more than 77,000 unique Medicare patients in 2013, generating $497 million in payments in the inpatient and outpatient settings. However, this accounted for just half of the total payments for this patient group. A deeper dive into this data would reveal where MGH might have an opportunity to keep more revenue within their hospital system and help identify what procedures its patients were using other providers for.
#4 GROW ENTERPRISE INTELLIGENCE TO MEASURE AND IMPROVE PATIENT AND ORGANIZATIONAL HEALTH Most healthcare organizations are collecting more data than they know what to do with. Unfortunately, data is not helpful unless it can be transformed into timely and actionable insights that impact performance throughout the organization. Organizations that leverage enterprise intelligence have access to the relevant clinical, financial and operational data and can transform this rich data set into actionable information that can improve decision-making and overall performance. Enterprise intelligence creates accountability for all stakeholders because it provides transparency at an organizational level rather than at just a departmental level. According to Definitive Healthcare, many organizations are not using enterprise intelligence software. In fact, of the approximately 7,257 hospitals in the United States, only 3,450 are known to use some type of enterprise intelligence software. Healthcare has made tremendous strides with electronic medical records (EMRs) and business intelligence capabilities. However, many organizations are still challenged by a lack of interoperability and are struggling to translate data into actionable information. System integration and the ability to access data across the organization empowers employees and helps stakeholders predict, model and measure best practices and ideal outcomes. Data-driven decisions are the key to the health of an organization and the patients they serve. With enterprise intelligence, healthcare executives and clinicians can leverage the power of data to make sound decisions based on information, not intuition. Health IT solutions are a critical component in the delivery of enterprise intelligence for healthcare organizations. Perficient s High-Performance Costing Expressway provides a complete solution that enables hospitals to rapidly deploy a micro-level costing solution. These transparent costing models indicate profitability by service, patient and procedure allowing healthcare organizations to quickly identify opportunities for improvement. Learn more about Perficient s High-Performance Costing Expressway. <50% OF HOSPITALS IN THE U.S. ARE KNOWN TO HAVE ENTERPRISE INTELLIGENCE SOFTWARE. DEFINITIVE HEALTHCARE
True enterprise intelligence delivers a complete, 360-degree view of the organization so that stakeholders can easily identify gaps and opportunities for improvement and make smarter, faster, and more impactful business and clinical decisions.
#5 UTILIZE REUSABLE ACCELERATORS TO QUICKLY ACHIEVE ACTIONABLE DATA- DRIVEN INSIGHTS One of the keys to a data-driven organization s success is interoperability of all data systems. Data integration is not only critical for making sound business decisions but it is also the cornerstone to understanding and engaging with consumers. For healthcare organizations, integrating data is a struggle in itself, but understanding data and turning it into useful and actionable information to improve decision-making and patient outcomes is a great challenge. In most cases, data resides in inflexible, disparate silos inside and outside of the organization, making it impossible to create a holistic and complete view of this information. Extracting data from critical sources including electronic medical records, financial systems, operational data, and external data sources including claims is imperative for population health initiatives, enhancing patient experience and reducing the cost of care. One way to combine some of this data is through an interface engine that connects legacy systems by using a standard messaging protocol providing the framework for the exchange, integration, retrieval and sharing of electronic health information. According to Definitive Healthcare, of the 7,257 hospitals in the United States, 4,400 are known to have some type of interface engine. A more complex but comprehensive way to combine this type of data is through the extract, transform, and load (ETL) process. Historically, ETL processes required to obtain this necessary data and place it in a data repository took 12-to-18 months to complete. However, many organizations are leveraging accelerators, reducing ETL time by more than 50%. Healthcare accelerators allow organizations to focus on delivering rapid results by fast-tracking the time-to-value. With healthcare accelerators, data is integrated much quicker so executives can spend less time collecting data and more time making data-driven decisions that positively impact business. Perficient s Health Analytics Gateway is a next-generation accelerator that pulls together advanced tools into an intuitive, easy-to-use framework that can help healthcare organizations begin to generate results much more quickly. The standardized data for business intelligence (BI) reporting can be used for ACO measures and to analyze key areas of the business such as readmissions, claims, pharmacy utilization, disease management, and patient safety. Learn more about Perficient s Health Analytics Gateway. 60% OF HOSPITALS IN THE U.S. ARE KNOWN TO HAVE AN INTERFACE ENGINE. DEFINITIVE HEALTHCARE
Success Story UNC HEALTH CARE UNC Health Care had a disparate IT system environment that lacked continuity. Data integration between existing legacy systems was a problem, and managing an environment with multiple IT systems and integration environments was no longer sustainable. UNC Health Care chose to adopt a single enterprise system and integration platform to enable better, safer, and more collaborative patient care. UNC Health Care leveraged the Perficient Health Analytics Gateway, a next-generation accelerator, allowing them to achieve rapid results from their enterprise data. The integration of clinical, financial, operational, and claims data was accelerated by 50% when compared to integrations that did not use the Perficient Health Analytics Gateway. Perficient operated with great flexibility and set up multiple check points with executive stakeholders from UNC Health Care. In addition to the data integration and warehousing project, Perficient developed and implemented: An automated quality assurance engine to identify defects during the project to allow a more proactive approach A detailed financial forecasting model that predicted the budget within 0.1% UNC Health Care and Perficient collaborated to ensure all data was successfully integrated into the new data warehouse and that mapping from Epic was completed. As a result, UNC Healthcare System recognized business values including: Eliminated dependency on older technologies Integrated the platform to enable efficient data management Complete integration between data from legacy systems and Epic Developed a comprehensive data warehouse to support future analytics requirements
#6 USE PREDICTIVE ANALYTICS TO REDUCE READMISSIONS AND IMPROVE OUTCOMES Predictive Analytics solutions uncover insights from trends and patterns to determine the impact of operational adjustments and market forces on healthcare organizations. Statistical analysis and predictive modeling expand on the findings gained through business intelligence solutions to answer What will happen? given certain business and/or clinical situations. Predictive analytics combs through massive amounts of data and analyzes it to find patterns, assess probability of occurrence, and predict outcomes. Healthcare organizations are leveraging predictive analytics to: Reduce patient readmissions Increase the accuracy of patient diagnosis Deliver more targeted care to high-risk patients Provide better overall outcomes for the individuals they serve Mobile and wearable technologies play a key role in predictive analytics. Data from wearable and mobile devices helps provide a 360-degree view of the patient and delivers insights that are critical to enhancing patient care. It is important to remember that predictive analytics should link to clinical priorities and measurable events such as cost, clinical protocols, and patient outcomes and preferences. Predictions just for the sake of predicting are a waste of both money and time. In the past, there was not enough information to support predictive analytics. But with the evolution of mobile, social, and the Internet of Things, healthcare organizations are engaging more frequently with healthcare consumers outside the walls of the brick-and-mortar. Data from these interactions has not only grown in volume, but it has also become more valuable for healthcare organizations as their focus is on providing high-quality and cost-effective care. According to Definitive Healthcare, very few hospitals are currently leveraging predictive analytics software, indicating that the market is ripe for growth. Learn more about how Perficient is helping healthcare organizations reduce hospital readmissions with predictive analytics solutions.
PREDICTIVE ANALYTICS WILL BE A $2.3 BILLION MARKET BY 2019. - MICROMARKET MONITOR Success Story VIBRA HEALTHCARE Hospital system Vibra Healthcare needed an interactive, flexible, and scalable analytics platform for greater visibility into financials. Perficient implemented a BI, forecasting, and reporting solution using financial performance management tools. Now, Vibra can achieve revenue growth through predictive analytics around patient stays for better capacity management, and through automated reporting, improved billing processes, and process improvements. Success Story LARGE HEALTH SYSTEM A large unified health system of physicians, hospitals and communities, needed to reduce patient readmissions and improve patient and family education. Rather than focusing on a single disease or condition, which is standard for healthcare models, we implemented a solution that predicts readmissions across all diseases and conditions and helps to optimize hospital resources to provide interventions to those who stand to benefit the most. During the engagement, we discovered that ER visitors were the most likely to be readmitted. Our client is now exploring staffing the ER with social workers who can intervene, coordinate primary care access, and decrease hospital admission, which could lead to millions in annual savings.
#7 LEVERAGE NEW TOOLS AND SKILLS TO TRANSFORM LARGE VOLUMES OF DATA INTO MEANINGFUL INFORMATION Healthcare analytics have traditionally been reactive, and many healthcare organizations have taken the approach of we will figure it out when the time comes. That approach is simply not effective in today s transforming healthcare industry. In order to survive, organizations must re-evaluate their approach to analytics and identify the skills and tools needed to improve patient outcomes and operational efficiencies. These tools and skills are necessary to help sift through and make sense of all the data. Healthcare organizations are inundated with an enormous amount of data that has the potential to not only make sense of the past but also to predict the future. The challenge is filtering through the mountains of data and turning it into useful information. While traditional analytics methods were performed by database administrators, the new era of healthcare analytics requires new competencies and a fundamental shift that focuses on preventing and targeting desired patient outcomes rather than reacting to past events. Historically, data analysts worked in isolation. However, today s healthcare data scientists must be team-oriented and lead the collaboration of cross-functional teams. While new skills are the foundation of transforming healthcare analytics, even the most skilled healthcare data scientists need new tools to convert data into powerful and actionable insights that impact patient outcomes and improve operational efficiencies. Business intelligence and analytics tools remove data silos that inhibit strategic decision making, resulting in: Greater transparency within the organization Improved operational performance Better executive understanding of the impact that business decisions have on patient outcomes
Success Story LARGE HEALTH SYSTEM A large, integrated healthcare system that includes hospitals, health centers, long-term care facilities, nursing homes, and in-home care implemented an enterprise data warehouse to deliver a single source of truth and insights to manage population health. Multiple and disparate data repositories made it impossible for our client to gain a holistic view of patient data, and manual reporting and analytics functions were labor-intensive and inaccurate. Perficient implemented an enterprise data warehouse to house clinical, financial and claims data. The Perficient Health Analytics Gateway was used to shorten the implementation timeline by providing standardized integration formats of data for multiple sources. Our client identified nine preventive services they wished to monitor among their primary care population in an effort to move toward a more population health-oriented approach to the care they delivered. The services include: Colorectal Cancer Screening Breast Cancer Screening Cervical Cancer Screening Influenza (Flu) Immunization Pneumococcal Immunization HIV Screening Hepatitis C Screening Depression Screening Body Mass Index (BMI) Screening Using interactive dashboards and patient compliance reports generated through the EDW integrated with a leading BI platform, our client is now able to identify and monitor patients who are non-compliant with their recommended preventive services and encourage them to comply.
#8 INCREASE LEVEL OF UNDERSTANDING AND CONTROL OVER ACO DATA AND ANALYTICS Accountable Care Organizations (ACO) spend a good amount of time discussing which technology systems to use, but very little time on determining who owns the data. ACOs have multiple stakeholders including partners in the ACO, patients, and insurers. Each of these stakeholders have a vested interest in the vast amounts of data within the ACO, but many times the question of who owns the data goes unanswered. According to Definitive Healthcare, there are more than 800 ACOs representing more than 200 health plans, 3,900 providers, and 300,000 physicians. And these ACOs use more than 125 different technology vendors, making it a very complex environment. There are many different opinions on the topic of data ownership. Some will say patients own their own data; others believe providers own the data on their systems, and insurance companies own the data on their systems. Each of these scenarios provides challenges for ACOs, making it critical for them to have a strategy in place to tackle the issues of data ownership. In today s healthcare landscape, all stakeholders need to be true stewards of patient data, and they should act in the best interest of the patient. If patients are expected to be more accountable for their care then they need access to their own health information. If an ACO, health plan or healthcare provider is going to be more accountable for patient outcomes, then they need to have access to the data. Ideally, data should be available to all stakeholders involved in the care process. Prior to merging existing systems or purchasing new healthcare IT systems, ACOs need to sort out the issues of ownership, usage, and changeability. Without quality control mechanisms and a data governance and organization strategy in place, the integrity and reliability of data within the ACO is likely to become compromised and in turn could compromise the whole essence of the ACO collaboration to improve patient care.
65% OF PATIENTS SAID DATA SECURITY IS MORE IMPORTANT THAN CONVENIENT ACCESS FOR IMAGING AND TEST RESULTS, DOCTORS NOTES, DIAGNOSES, AND PRESCRIPTIONS. HEALTHCAREDIVE.COM #9 DEVELOP AND IMPLEMENT A STRONG GOVERNANCE STRATEGY AND ORGANIZATION Data governance is the overall management of enterprise data. It encompasses the people, processes, and information technology required to consistently ensure data value, quality and integrity, improvement, development, and maintenance. It also includes a single shared definition for all data, data security, and availability of the right data at the right time to the right people in the right format across the organization 1. The healthcare industry has loosely thrown around the term data governance for many years. However, as regulators, hospital executives, and patients have more consistently enforced, demanded, and expected better quality of care, healthcare organizations have begun investing a great amount of time and money into seeking the true value behind data governance. Healthcare organizations own significant amounts of data and data resources, but turning that data into an information asset that can be managed for effective decision making is simply not happening at an enterprise level. Managing information as an enterprise asset requires effective data governance 2. Data security is especially critical in the healthcare industry. Definitive Healthcare tracked 72 data breaches at hospitals and health systems in 2014, affecting more than five million individuals. These breaches cost hospitals money, impact their reputation, and potentially expose them to lawsuits. Data governance serves as the quality control component of an organization s data. Its primary goal is to allow for data across the organization to be consistent, accurate, available, and timely in order to help drive improved and effective clinical, operational and financial decision-making. However, understanding and establishing data governance is not an easy task. It takes time, effort and the commitment of a cross-functional team to lay a strong foundation for its success. As demands and expectations for improved care coordination continue, healthcare organizations are going to not only have to understand the importance of data governance, but more importantly learn how to optimize and leverage its true benefits. Resources: 1. http://www.eiminstitute.org/library/eimi-archives/volume-1-issue-1-march-2007-edition/datagovernance-best-practices-2013-the-beginning 2. http://www.nascio.org/publications/documents/nascio-datagovernance-part1.pdf
THE ANALYTICS OF THINGS (AOT) TRUMPS THE INTERNET OF THINGS. #10 POSITION BIG DATA TECHNOLOGIES TO ENABLE THE EVERYDAY USE OF DATA SCIENCE The Internet of Things (IoT) has been growing significantly as consumers and businesses recognize the benefits of connecting devices to the Internet. Gartner, Inc. forecasts that there will be 25 billion connected things by 2020. Healthcare organizations are also beginning to understand the value of the IoT. According to a report from MarketResearch.com, the healthcare IoT market segment is poised to hit $117 billion by 2020. While the number of connected devices is impressive, the attention shouldn t just be on the sheer number of devices but rather the data, analytics, and insights these devices generate. The healthcare industry is seeing explosive growth in the amount of data available for analytics. One of the biggest drivers is the collection and use of data from IoT devices such as medical devices, sensors and wearables. The IoT generates a massive amount of structured and unstructured data; in fact, healthcare providers are equipped with more data than ever before. A lack of data is not the challenge; the challenge is creating meaningful information that enables healthcare providers to focus on the highest priorities and drive improvements from strategic, operational, and, most importantly, from a quality of care perspective. There have been vast improvements in analytics tools and techniques, but a lack of system integration continues to be a challenge for healthcare organizations. Uncovering and capturing the value of IoT data and marrying it to other source systems, such as electronic medical records, financials, and claims, is critical to generating a 360-degree patient view and the key to many initiatives such as population health management. The IoT is not a technology trend on the horizon; it is here today, and it is having an enormous impact on the healthcare industry. Analytics capabilities are finally robust and intuitive enough to make sense of the IoT by generating data-driven, meaningful, and actionable insights in real-time. With the digitalization of medical records, wearable technologies, mobile data and the IoT, healthcare providers have a holistic view of their patients and are equipped with the data necessary to deliver personalized healthcare. The combination of the IoT and the AoT is powerful, and it is critical for healthcare organizations to stay focused on their highest priorities to ensure they don t take on too much.
Success Story UNIVERSITY OF COLORADO ANSCHUTZ MEDICAL CAMPUS Perficient has tremendous expertise and experience with Big Data projects, including those related to precision medicine initiatives. The University of Colorado Anschutz Medical Campus, which includes the University of Colorado, University of Colorado Health, Children s Hospital Colorado and University Physicians, Inc., needed to integrate data from various sources into a data warehouse to enable reporting and analysis for the purposes of improving access to research data, improving clinical quality and operations, and supporting advancements in personalized medicine. Perficient assembled a cross-functional team of experts to install, configure, and test the solution. Once all planned phases are complete, the University of Colorado team will have a comprehensive, centralized, and compliant system that will help answer complex questions, improving the lives of patients, and leading to breakthroughs in precision medicine. Learn more about Precision Medicine in our new guide: Precision Medicine in Life Sciences and Healthcare: The Industries are Honing In.
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