Reducing Opioid Availability with Improved Prescribing Practices

Historical approaches to the use of opioids in pain management have been associated with overprescribing and have inadvertently contributed to the opioid abuse crisis. Optimizing the use of opioids can help reduce the number of excess pills circulating in the community.
Allina Health, a not-for-profit health system serving Minnesota and western Wisconsin, achieved previous success in reducing opioid prescriptions in outpatient settings through the adoption of standard practices. Though Allina Health had initial success with its opioid prescription reduction efforts, providers still lacked visibility into prescribing practices, leading to variability that made further sustainable improvements challenging. With the help of analytics, Allina Health leveraged its data to develop prescription standards aimed at reducing the oversupply of opioids in the community, while still effectively managing patients’ acute pain after procedures.
Results:

15,730 fewer opioid pills prescribed at discharge in one year.
16 percent relative reductionin the number of opioid pills prescribed per patient.
95 percent of patients that delivered a baby via cesarean section and received opioids at discharge received fewer than 30 opioid pills.

Enabling Informed Surgical Choices for Breast Cancer Through Shared Decision Making

One out of every eight women in the U.S. will develop breast cancer in her lifetime, and men have a lifetime risk of one in 1,000. This year, over 3.1 million women are currently being treated or have finished treatment for breast cancer.
The Virginia Piper Cancer Institute had clear evidence-based practice guidelines that directed recommendations for early breast cancer treatment options. Even with these evidence-based recommendations, however, the organization’s mastectomy rates were higher than expected.
Recognizing the organization could do better, the breast cancer program committee endorsed the spread of shared decision making for patients with early-stage breast cancer to all Virginia Piper Cancer Institute locations. The spread of shared decision making allowed patients to receive evidence-based information early in their course of care and make informed decisions that aligned with their values and preferences.
Within nine months of implementing a standard process for shared decision-making visits, the Virginia Piper Cancer Institute clinics that have completely adopted the process have made significant progress in engaging patients with early breast cancer in the shared decision-making process:

81 percent of eligible patients (207 people) participated in shared decision-making visits.
62 percent of the shared decision-making visits were in person.
27 percent relative increase in surgical decision of lumpectomy over mastectomy.

Shared Decision-Making Leads to Better Decisions and Improves Patient Relationships

Shared decision-making is the process by which clinicians and patients work together to make decisions and select tests, treatments, and care plans based on clinical evidence. Shared decision-making balances risk and expected outcomes with patient preferences and values, empowering patients to make informed decisions.
Project leadership at Allina Health didn’t have a way to know if shared decision-making interventions were being applied. By utilizing its analytics platform, Allina Health was able to track whether or not decision support tools were being used consistently and if shared decision-making conversations were happening, if there was variation in how and when they were being used, and if they were making a difference.
Within nine months of implementing the standard shared decision-making process Allina Health substantially increased the number of patients participating in the program:

749 patients have participated in a shared decision-making visit across the system, including:

69 percent of eligible patients with low back pain.
84 percent of eligible patients with early breast cancer.

Improving Accuracy of Clinical Documentation Positively Impacts Risk Adjustment Factor and HCC Coding

The Hierarchical Condition Category (HCC) risk adjustment model is used by CMS to estimate predicted costs for Medicare beneficiaries, and the results directly impact the reimbursement healthcare organizations receive for patients enrolled in a Medicare Advantage plan. CMS requires that all qualifying conditions be identified each year by provider organizations. Documentation that is linked to a non-specific diagnosis, as well as incomplete documentation, negatively affects reimbursement.
Allina Health, a not-for-profit integrated healthcare delivery system serving Minnesota and western Wisconsin, needed to improve its HCC coding and clinical documentation in order to ensure the correct risk adjustment factor (RAF) was applied to its patients, since failing to do so would jeopardize its reimbursement and result in lower than expected compensation. After identifying opportunities for improvement by comparing its HCC risk adjustment coding data to other organizations and vendor metrics, Allina Health improved clinical documentation precision, medical diagnoses accuracy, and ensured eligible patients are seen each calendar year.
Results:

10 percent increase in RAF for the target population in one year.
72 percent relative improvement in four key problem list diagnoses.

Dedication to Quality Improvement Delivers on the Triple Aim: Saves Tens of Millions Annually

Unwarranted variation in clinical care is costly: representing as much as $30 million of actionable savings opportunity for a typical organization. Addressing clinical care at Allina Health, however, was challenging—as a large system with limited resources, the organization struggled to standardize work to impact outcomes and reduce costs.
Allina Health’s executive team understood that, due to market and system demands, it needed sharper focus on increasing clinical value to improve financial margins. In response, the organization launched its Clinical Value Program, a systemwide effort to measure and improve clinical value. The program quantifies the value of clinical change work to improve outcomes, while reducing costs and increasing revenue for reinvestment in care.
With a data-driven, multidisciplinary team effort, Allina Health’s Clinical Value Program has improved care and delivered on the Triple Aim, achieving the following results:

More than $33 million positive margin impact by expense reduction and additional hospital in/outpatient revenue.
Identified $13 million in additional opportunities for cost reductions, which have been integrated into the health system budget plan.

Enhanced Recovery Program Improves Elective Colorectal Surgical Outcomes

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.

Opportunity Analysis Permits Successful Execution of At-Risk Contracts

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.

Advancing Health Equity – Data Driven Strategies Reduce Health Inequities

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.

Unleashing the Data to Sustain Spine Service Line Improvements

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.
Results:

$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.

Blood Conservation Program Yields Millions of Dollars in Savings

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.
Results:

$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

Data-Driven Approach Identifies Nearly $33 Million of Savings Annually

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.

Clinical Data Abstraction as a Service Improves Accuracy and Efficiency

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.
Results:

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.

How Allina Engaged Clinicians and Analytics to Improve Influenza Vaccination Rate

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.
Results:

4.8 percentage point improvement in influenza vaccination rate, exceeding the Healthy People 2020 goals for vaccination.

Combatting Opioid Abuse with Data-Driven Prescription Reduction

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.
Results:

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.

Enhancing Mental Health Care Transitions Reduces Unnecessary Costly Readmissions

Nationally, hospitalization for persons with mental health disorders has increased faster than hospitalization for any other condition. Of concern is the lack of bed space to intake these patients on a timely basis. In Minnesota, for example, more than 50 percent of available state psychiatric beds were closed between 2005 and 2010. Furthermore, readmission rates for patients with mood disorders is higher than any other mental health condition, with 15 percent readmitted within 30 days of hospital discharge and up to 22.4 percent of patients with schizophrenia being readmitted. While the average cost of a readmission in the U.S. is approximately $7,200, of greater concern is hospital readmission represents poor patient outcomes related to lack of adequate access to community mental health resources and challenges with adherence to care plans needed to prevent chronic relapse.
In response to these challenges, Allina Health put a new care transition process in place, redesigned workflow, and added key patient support roles. To measure the effectiveness of new interventions, Allina relied on the Health Catalyst Analytics Platform, which includes the Late-Binding™ Enterprise Data Warehouse and a broad suite of analytics applications.
Results:

27 percent relative reduction in potentially preventable readmission rate.
80 percent patient retention rate in established outpatient mental health services.

Data-Driven Process Improvement Raises Patient Safety for Highest-Risk Medication

Intravenous (IV) heparin is widely used to prevent thrombosis in a variety of clinical settings, yet it is considered one of the highest-risk medications used in the inpatient setting because of the potential for dosing errors. Allina Health identified multiple IV heparin protocols among its hospitals, a variation that increased the risk of errors. Standard practices that addressed patients’ clinical needs in a disease-specific way were lacking. Over the course of 1.5 years, more than 9,000 patients at Allina Health had an IV heparin protocol ordered, so IV heparin safety was of utmost concern.
To address this quality issue and improve clinical value, Allina Health created a systemwide interdisciplinary team to standardize IV heparin therapeutic guidelines and monitor the impact of the standard guideline on patient outcomes. Allina Health engaged multiple physician stakeholder groups to review proposed protocols and provide critical feedback to help ensure the best possible patient care and safety. To effectively monitor IV heparin outcomes, patient safety, and the impact of the new, standard guidelines and protocols, Allina Health developed an anticoagulation safety analytics application, using the Health Catalyst Analytics Platform, including the Late-Binding™ Data Warehouse and broad suite of analytics applications. These outcomes improvement efforts resulted in:

A seven percent relative improvement in the percentage of patients therapeutic within 24 hours of protocol initiation.
Paring 20+ site-based documents (e.g., policies, protocols, and order sets) to one systemwide guideline and four systemwide protocols.

How Allina and Minnesota Perinatal Physicians Lowered Stress and Raised Satisfaction for High Risk Maternal Patients

Assuring patient satisfaction can be challenging, particularly when providing care to pregnant women with high-risk pregnancy conditions. As one of the foremost perinatal practices in the country, Minnesota Perinatal Physicians (MPP) acted swiftly to end a significant delay in scheduling ultrasound appointments, and reduced wait times for other visits.
With an aim to improve patient care and experience, the maternal fetal medicine (MFM) specialists at MPP, employees of Allina Health, leveraged Allina’s “Improving Clinical Value” Program—an initiative that has elevated the patient care experience for numerous other patient populations while simultaneously lowering the per capita cost of care for each one.
Results:

$210,000 in increased revenue because of improved access, projected to be $280,000 within 12 months.
20.8 percent relative improvement in no-show rate.
20 percent increase in available ultrasound appointments and an 18.2 percent increase in utilization.

Data-Driven Clinical Documentation Improvement Program Increases Revenue and Improves Accuracy of Risk Adjusted Quality Metrics

Allina Health, an integrated delivery system throughout Minnesota and western Wisconsin, has long understood the value of clinical documentation improvement (CDI), and its growing importance in recent years. With the implementation of ICD-10, the specificity needed for accurate coding has increased, and reimbursement shifts have occurred as well, creating sizeable payment disparity for some clinical conditions. Leaders at Allina wanted to understand where their CDI program would have the greatest return on investment. However, data from the EHR was not sufficient to inform their strategy. CDI specialists still lacked the ability to perform a comprehensive assessment of the accuracy of clinical documentation, and were unable to confidently target improvement efforts in areas that would generate the greatest return on investment. To take a more data-driven approach, team members leveraged the Health Catalyst Analytics Platform, including their Late-Binding™ Data Warehouse and broad suite of analytics applications to develop a CDI analytics application. With the application, the team identified opportunities and thoroughly vetted them, before collaborating with physicians and service line leaders to educate providers on documentation improvements.
They achieved the following results:

12.1 percent improvement in CV surgical cardiology CC/MCC capture rate.
6.3 percent increase in medical cardiology CC/MCC capture rate.
Increased accuracy in publically reported risk adjusted quality metrics
Revenue capture improvement across the system – resulting in millions of dollars of additional reimbursements.

ICU Avoidance: Lowering Costs, Patient Risk, and LOS

A stay in the intensive care unit (ICU) is both costly and risky. In a sobering example of the latter, nearly one third of patients admitted to the ICU experience delirium, a state of cognitive impairment that can increase risk of death in the hospital. Still, many cardiovascular patients need intensive care that can only be provided safely in an intensive care unit, requiring hospitals to assure enough beds and skilled ICU staff for these patients—while quickly identifying which patients can receive care as good or better in another unit.
Allina Health has achieved this dual objective with a concerted ICU avoidance strategy for specific complex sub-populations of cardiovascular (CV) patients. The foundation of this strategy is risk-informed decisions about which patients can avoid the ICU; clinical staff education; and an analytics platform and enterprise data warehouse (EDW) from Health Catalyst that enables CV care leaders to monitor safety metrics for those patients who avoid a stay in the ICU. So far, Allina Health’s efforts have resulted in the following achievements:

636 additional ICU days made available for more critically ill patients by employing ICU avoidance strategies
One-day reduction length of stay (LOS) for Transcatheter Aortic Valve Replacement (TAVR) patients
$589,000 cumulative cost savings

Nurse-Driven Protocol Optimizes Management of Post Op Afib While Reducing LOS and Costs

Post Operative Atrial Fibrillation occurs in up to 30 percent of all patients after cardiac surgery. This serious complication increases the length of the patient’s hospital stay, and is associated with a twofold increase in the incidence of cerebral infarction and an increased risk of 30-day mortality. Timely and consistent management of Post Op Afib can prevent significant complications and help prevent death. To standardize such an approach to managing Post Op Afib, Allina Health’s Minneapolis Heart Institute created a physician committee to raise consensus on and develop a protocol for Post Op Afib management.
The committee ultimately created a nurse-driven protocol and decision support algorithm linked to the health system’s electronic health record (EHR). Additionally, it uses analytics, supported by Health Catalyst’s Late-Binding™ Enterprise Data Warehouse (EDW), to track physician ordering rate, patient outcomes, and cost. This combination of people, processes, and analytics tools has made a significant difference for Allina and its patients.

Two-day reduction in ICU LOS.
5.9 percentage point reduction in ICU readmission rate.
$1.5 million savings.

Leveraging Risk Assessment to Decrease LOS and Cost for PCI Patients

Percutaneous Cardiac Intervention (PCI) is a minimally-invasive alternative to open heart surgery—a procedure that approximately 600,000 U.S. patients will undergo this year.
Allina Health, a non-profit health system with 90+ clinics and 13 hospitals with locations throughout Minnesota and western Wisconsin, is a leading provider of the procedure in Minnesota. Allina Health discovered that major bleeding events following PCI procedures (the most common non cardiac complication of PCI), though not affecting mortality, were increasing length of stay (LOS) and cost.
To improve the quality of its PCI procedures and decrease costs, Allina Health recognized the need to accurately assess bleeding risk and then implemented best-practice interventions to prevent major bleeding events.
Already, physicians and patients have seen that these new interventions, which includes a bleeding risk assessment tool, allows clinicians to focus interventions based on risk and reduce complications. The top results from Allina Health’s interventions include:

5.3 percentage point reduction (a 21.7 percent relative reduction) in complication rate.
$1.8M cost savings.
1.4 percentage point reduction (a 36.5 percent relative reduction) in LOS for patients at high risk for bleeding who receive a closure device.

Data-Driven Approach to Improving Cardiovascular Care and Operations Leads to $75M in Improvements

Health spending in the United States is greater than the gross domestic product of most nations, and the costs for cardiovascular disease (CVD) and stroke care alone total $193.1 billion. CVD accounts for approximately one out of every three deaths in the U.S. and contributes to the shorter life expectancy of Americans. Thirty-five percent of CVD related deaths occur before the age of 75 years, and 19 percent before the age of 65.
Allina Health is a large integrated healthcare delivery network operating in Minnesota and western Wisconsin that includes three large cardiac centers. Due to the prevalence and mortality rate of CVD, leaders at Allina Health recognized that they needed to focus on cardiovascular health in order to truly impact the population health and patient outcomes of the communities they serve.
By leveraging real-time data from its enterprise data warehouse (EDW), Allina Health effectively identified and addressed clinical practice variation and operational issues affecting cardiovascular care and costs. In doing so, the health system realized more than $75 million in performance enhancement savings and revenue increase over a four-year period by focusing on supply chain, lab test and blood utilization, clinical practice changes and clinical documentation improvement.
 

Developing a Multilevel Approach to Improving Population Health

Heart attacks are the leading cause of death for both men and women in the United States, yet heart attacks are largely preventable through healthier lifestyles. Spurred on by this knowledge, New Ulm Medical Center, the Minneapolis Heart Institute Foundation, and the rural community of New Ulm, Minnesota, teamed up to create Hearts Beat Back: The Heart of New Ulm (HONU) Project. This population-based prevention demonstration project aims to reduce the number of heart attacks and heart disease risk factors among the New Ulm population.
Recognizing the complex web of personal, institutional, and societal factors that influence an individual’s heart-health behaviors, HONU leaders implemented a multilevel strategy spanning 10 years to improve the health of the entire population.
The HONU Project’s multilevel, data-driven approach has resulted in substantial changes in improving population health in New Ulm:

Significant improvements in blood pressure and cholesterol at the population level.

86 percent of residents now have blood pressure within the recommended range.
72 percent have LDL cholesterol within the recommended range.

Improvements are greater than changes seen in the national comparison population.

A Care Model to Support the Needs of Medically Complex Patients

People with disabilities face daunting challenges in accessing basic healthcare. As a result, they frequently use hospitals and emergency rooms, and are four times as likely to be hospitalized compared to the general population.
Allina Health has deployed an effective “primary care medical home” model that gives patients with disabilities the care and support they need outside of the hospital setting. Key strategies of the model include assigning dedicated care coordinators to each patient; strengthening care coordination across the continuum of services; and an analytics platform from Health Catalyst to target opportunities for improvements and savings.
Allina’s data-driven efforts to strengthen care of patients with disabilities have made a clear and meaningful impact; most importantly, on patient outcomes. They have achieved: 30% reduction in hospitalizations and 66% reduction in hospitalization days; 79% reduction in 30-day readmissions days; significantly improved access to care; and saved $4.5 million over a one-year period.

Reduce Readmissions with Predictive Analytics and Process Redesign

With nearly 20 percent of elderly patients released from a hospital being readmitted within 30 days, Allina Health is focused on providing patients optimum care and support post discharge to minimize readmissions. Focusing on 30-day potentially preventable readmissions (PPRs) as its global outcome measurement, Allina Health used key clinical variables to derive the clinical relationships between hospitalizations that determine PPRs. It further built analytic capabilities to identify opportunities for improvement in care management and to test quality improvement ideas.
Allina Health’s multipronged solution included redesigning care management processes, implementing predictive analytics to identify at-risk patients, using analytics to measure the impact of its interventions, and educating patients, families, and clinicians.
These efforts are driving measurable improvements including: 10.3 percent overall reduction in PPRs, 27 percent reduction in PPRs for patients with clinic follow-up within 5 days, and $3.7 million reduction in variable costs due to avoided readmissions.