UC San Diego Health sought to transform its organization, expanding beyond fee-for-service, transitioning to value-based care, and improving the health of its patient population—forming its Medicare Shared Savings Program (MSSP) ACO. It realized it needed a better understanding of its organizational strengths, opportunities for improvement, and needed actionable, timely data that would enable it to improve outcomes, reduce waste, and succeed in value-based care. The organization leveraged an analytics platform to give insight into performance and improvement opportunities, educating and engaging ACO providers.
Accountable Care Organization
OneCare Vermont sought to identify which of its patients were at the highest risk of serious illness or mortality from COVID-19 and which of its patients with chronic healthcare problems needed care for medical issues other than COVID-19. Leveraging its data platform, OneCare Vermont enabled rapid identification of at-risk patients. Providers and care teams use the risk-stratification care coordination tool to proactively conduct patient outreach, including telephone calls and telemedicine virtual visits, ensuring patients receive needed social support and medical care during the pandemic.
OneCare Vermont, an accountable care organization (ACO), is focused on reducing costs by reforming payment models. As the organization methodically and rapidly moves toward value-based payments, it is challenging current delivery methods and seeking to engage providers and patients in new care models. To be successful, OneCare needed to implement strategies to effectively drive change. With robust data analytics, it was able to prioritize opportunities for improvement and ultimately change the way care is coordinated and delivered throughout its network. Results include nearly $20M in positive, value-based financial results in just one year.
Seeking to drive down unnecessary cost, Hospital Sisters Health System (HSHS) needed a way to automate risk stratification of patients who may benefit from care management services and eliminate the burdensome manual work its care managers were performing to identify at-risk patients. HSHS utilized a population health analytics platform to accurately risk stratify its care management and identify patients who would benefit from additional care management interventions.
Learn how The Queen’s Health Systems (QHS) and The Queen’s Clinically Integrated Physician Network (QCIPN) adopted a Rapid Response Analytics Solution, enabling the accelerated implementation of custom algorithms to better identify patients.
Learn how Allina Health leveraged its analytics platform and Health Catalyst professional services to perform an analysis demonstrating the impact of pharmacist-led medication therapy management (MTM).
Partners HealthCare utilized technology—including its analytics platform, analytics applications, and EMR—to collect data about serious illness conversations and to evaluate the impact of those conversations on trends at the end of life.
By leveraging data from its analytics platform along with a risk predictive model to identify patients who would benefit from its home-based palliative care, Partners HealthCare has improved the end of life care for patients and reduced costs.
Five percent of patients account for half of healthcare spending in the U.S., and patients with multiple chronic conditions cost up to seven times more than those with only one. Read how Partners HealthCare has maintained its integrated care management program (iCMP) and is continuing to decrease costs while improving outcomes.
The positive impacts of community health workers (CHWs) have been well documented, yet in general, CHWs remain underutilized and have not been fully integrated into care teams. Read how Partners HealthCare successfully integrated CHWs into its integrated care management program (iCMP) care team to improve patient outcomes and reduce cost.
Hospital readmissions can impact the health outcomes for patients and result in costly readmission penalties from CMS. Learn how the data analytics teams at Westchester Medical Center Health Network and network member Bon Secours Charity Health System utilized its analytics platform, in coordination with a machine learning algorithm, to build a knowledgeable and accurate readmission risk model that better reflected its patient population.
On an annual basis, ACOs are required to accurately report data that is used to assess quality performance which is also linked to eligibility to share in any savings generated. Read how Mission Health implemented a proactive approach to measure and evaluate performance, including widespread adoption of analytics and shared responsibility for ACO measure performance, enabling the organization to sustain and further improve its performance across multiple ACO measures.
Providing and documenting best practice preventative and primary care measures is critical for MSSP success. Read how USMM integrated data from disparate sources and utilized its analytics platform and applications to achieve 80th and 90th percentile performance for various ACO measures, resulting in significant contributions to Medicare savings.
Contemporary colorectal surgery is often associated with long LOS, high costs, and surgical site infections (SSI) approaching 20 percent. Much of the LOS variation is not attributable to patient illness or complications, but most likely represents differences in practice style. Successfully reducing SSI requires a multimodal strategy under the supervision of numerous providers with high compliance across the spectrum.
Allina Health was using established, evidence-based clinical guidelines, yet clinical variation remained high across pre-arrival, preoperative, intraoperative, and postoperative care areas, leading to substantial variation in LOS, cost of care, and the patient experience. To ensure greater consistency, Allina Health developed an enhanced recovery program (ERP) for patients undergoing elective colorectal surgery, which built standard protocols into the EHR to address elements of care from pre-arrival through post-discharge.
To facilitate the program and monitor performance, Allina Health developed an ERP analytics application with an administrative dashboard to easily visualize first-year results:
78 percent relative reduction in elective colorectal SSI rate.
19 percent relative reduction in LOS for patients with elective colorectal surgery.
82.4 percent utilization of preoperative and postoperative order sets, increasing the consistency of care and reducing unwarranted variation.
Growth in the government payer mix and an increased cost burden to the commercial population, decreases in the private payer population, and programs like the Medicare Shared Services Program, have caused joint ventures, partnerships, and co-branding efforts, better known as at-risk contracts, between payers and providers to increase.
Allina Health has three Integrated Health Partnership (IHP) contracts, an accountable care model that incentivizes healthcare providers to take on more financial accountability for the cost of care for Medicaid patients, which cover approximately 90,000 members. To achieve success in its IHP contracts, and avoid losses, Allina Health needed to reduce healthcare costs while improving patient outcomes and experience.
Allina Health has integrated several data sources, including claims and developed the infrastructure required to perform opportunity analysis. Using data and analytics for opportunity analysis has given Allina Health insight into its IHP patient population, supporting the development of interventions to decrease the total cost of care and improve outcomes.
Health equity means that everyone has an equal opportunity to live the healthiest life possible – this requires removing obstacles to health. The U.S. ranks last on nearly all measures of equity, as indicated by its large, disparities in health outcomes. Illness, disability, and death in the United States are more prevalent and more severe for minority groups. Health inequities persist in Minnesota as well, which motivated Allina Health to take targeted actions to reduce inequities.
Allina Health needed actionable data to identify disparities and to reduce these inequities. This came in the form of REAL (race, ethnicity, and language) data, which Allina Health analysts used to visualize how health outcomes vary by demographic characteristics including race, ethnicity, and language. To understand the root causes of specific disparities as well as to identify solutions within their sphere of influence as a healthcare delivery system, Allina Health consulted the literature and also consulted patients, employees and community members. Then Allina Health created appropriate interventions based on this information.
As a result, Allina Health created an awareness of the health inequities among its patient populations, as well as effective approaches to breach the barriers that were preventing these patients from getting the care they needed. While much work remains in this long journey to achieve health equity, Allina Health has taken some significant steps forward, including:
Three percent relative improvement in colorectal cancer (CRC) screening rates for targeted populations, exceeding national CRC screening rates by more than ten percentage points.
REAL data embedded in dashboards and workflow to easily identify and monitor disparities.
Research shows that despite an increase in the number of improvements in clinical, cost, and operational outcomes, there is a lack of sustained improvements. Some of the key challenges can be access to the data and analytics, and adherence to data-driven clinical standards, things the Allina Health Spine Clinical Service Line (CSL) clinical leadership team experienced.
By providing widespread access to the data and analytics, the Spine CSL at Allina Health has been able to continue its reduction in LOS and further improve its reduction in complications, all while increasing cost savings and achieving pay-for-performance incentives.
$1 million in pay-for-performance incentives received.
More than $2 million in supply chain savings, a result of data-driven clinical standardization.
31 percent of expected complications avoided.
22 percent relative reduction in surgical site infections.
Every three seconds, someone in the United States will need a blood transfusion, which adds up to nearly 17 million blood components transfused annually. Yet, evidence shows that up to 60 percent of red cell transfusions may not be necessary. In 2011, Allina Health, a healthcare delivery system that serves Minnesota and western Wisconsin, had a wide variation in transfusion practices throughout the system and a transfusion rate that was 25 percent above national benchmarks. In an effort to improve outcomes of high-risk transfusions, Allina Health turned to its data to develop an evidence-based blood conservation program aimed at reducing costs and saving valuable blood resources.
$3.2M decrease in annual blood product acquisition costs since 2011
30,283 units saved annually
111 units of red cells saved per 1000 inpatient admissions
Today’s healthcare industry, in which a lack of insight into clinical variation has contributed to increased expenses, has significant opportunities to use data and analytics to improve outcomes and reduce costs. As part of its ongoing commitment to improve clinical value, Allina Health has employed a systemwide process to identify, measure, and improve clinical value. The health system has been able to quantify the value of clinical change work to improve outcomes, while reducing costs and increasing revenue for reinvestment in care.
Allina Health achieved the following meaningful results with this collaborative, data-driven opportunity analysis process:
Identified nearly $33 million in potential cost savings for the first three quarters of 2017.
Achieved over $10 million of confirmed savings during the first three quarters of the year.
Elevated discussions of cost concerns, leading to the development of standard processes, and significantly reducing unwarranted clinical variation.
Healthcare suffers from an overabundance of metrics, many of which are used to determine payment in several federal healthcare programs. While these metrics are intended to improve the quality of care that patients receive across the country, they provide no insight into how disease and treatment impact patients’ daily lives.
Partners HealthCare recognized that while it had data for patient outcomes such as mortality and morbidity, and an abundance of data for process measures, it did not have data about patient symptoms, function, or quality of life. To improve care, the healthcare system needed to engage patients to understand the impact of treatment on how patient’s felt and functioned following treatment.
Partners implemented a patient-reported outcome measures (PROMs) survey program to collect this data. Partners now has several years of experience collecting PROMs and is gaining insight into how to successfully collect and use the information to improve shared decision making with patients and their providers.
Patients have completed nearly 300,000 questionnaires in more than 20 specialties and over 75 clinics at most of Partners’ hospitals.
Clinicians actively use this data to facilitate shared decision-making with their patients.
Improving Clinical Processes and Effectiveness of Care through Creation of a Disease-Specific Registry
Multiple Sclerosis (MS) is a disease that affects the central nervous system of about 400,000 people in the United States. With no known cure, current treatment for MS is to slow disease progression, manage symptoms and maintain the patient’s quality of life. Effective treatment of MS requires detailed patient information be readily available.
To better monitor disease progression and long-term patient outcomes, clinicians with OSF HealthCare Illinois Neurological Institute collaborated with researchers at the University of Illinois College of Medicine Peoria (UICOMP) to build a customized database.
The customized MS flowsheet registry resulted in several benefits, including:
20.9 minute reduction (per patient) physician time spent searching for data.
2.2 minute reduction (per patient) support staff time spent searching for data.
300 percent increase in investigator initiated studies.
The success of the customized database suggests possible expansion may improve outcomes in other chronic or specialty care patient populations.
Nearly half (46 percent) of all physicians report that they suffer from burnout, citing too many bureaucratic tasks as one reason. Providers want to find meaning in their work, and improvement on many current quality metrics do not predict better patient outcomes or experience of care. They are looking for tools to reduce their workload and improve their ability to provide excellent care, including having metrics and registries that are meaningful and informative.
Faced with the challenge of making quality measures meaningful, Partners HealthCare worked to redefine measures to be more relevant, create point-of-care registries to manage an all-payer population, created teams of Population Health Coordinators to support front-line teams in managing the registries, and used its analytics platform to monitor change and explore provider variation in order to improve quality. This resulted in:
85 percent of clinicians surveyed felt that the new metrics helped them take better care of their patients.
Quality improved at an unprecedented rate on an all-payer population five times bigger than the standard pay-for-performance population.
Near real-time measurement using clinical data eliminated months-long delays, while run charts and provider and clinic-comparison views turbo charged quality improvement.
125 percent increase in user adoption of the analytic tool (99 unique users, 674 unique sessions, and rising).
Allina Health needed to ensure the data it reported to regulatory agencies was timely and accurate. The integrated health system sees 100,000 inpatient hospital admissions annually, 340,000 emergency care visits, and 6,000 physicians and 1,600 nurses providing and documenting care. Due to the sheer volume of patients and employees, clinical data abstraction at Allina Health is not a small undertaking.
Looking to stay compliant while reducing resource utilization, Allina Health sought to change its workflow procedures for faster, more accurate clinical data abstraction. A large amount of clinical data required for compliance with CMS performance measures and Joint Commission Core Measure resides in unstructured data, such as narrative notes, which require manual data abstraction. With the help of data analytics, Allina Health was able to develop evidence-based standardized processes for clinical reporting and automate some clinical data abstraction.
76 percent relative improvement in time to data availability at each site. Data is typically available within 14 days of discharge, far exceeding the 30-day target.
95.5 percent accuracy for CMS validation.
Influenza, a contagious respiratory illness spread by droplets, can lead to hospitalization and even death. Millions of people get influenza each year, hundreds of thousands are hospitalized, and thousands to tens of thousands die from influenza related causes each year. The key to preventing a devastating outbreak is vaccinating enough people that an outbreak is unlikely.
When Allina Health identified that its own rates for influenza vaccination were lower than desired, the health system studied data gleaned from its EHR and an Analytics Platform from Health Catalyst, which includes a Late-Binding™ Enterprise Data Warehouse and broad suite of analytics applications, to understand its true current vaccination performance. The data revealed that changes were in order, which Allina put in place through clinician feedback, engagement, and education.
4.8 percentage point improvement in influenza vaccination rate, exceeding the Healthy People 2020 goals for vaccination.
Each day, 91 Americans die from an opioid overdose. Historically, illegal opioids, such as heroin, were the primary contributing factor to overdoses. Today, it is well understood that a driving force for opioid abuse is prescriptions, which contribute significantly to the overdose epidemic.
Following a series of adverse outcomes related to opioid misuse within the community, Allina Health sought to evaluate how it managed acute non-cancer pain in the outpatient setting, particularly among opioid-naïve patients. By leveraging the Health Catalyst Analytics Platform, including the Late-Binding™ Data Warehouse and broad suite of analytics applications, Allina Health obtained data on prescribing patterns and identified several opportunities to reduce the number of opioids prescribed.
980,527 fewer opioid pills prescribed in the outpatient setting in 2016, a 12 percent relative reduction.
1,079 fewer patients (with acute or chronic pain) receiving eight or more opioid pill prescriptions over 12 months, a 10.3 percent relative reduction.
13,391 fewer patients receiving opioid prescriptions for more than 20 pills, a 13 percent relative reduction.