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Activity-Based Costing and Clinical Service Lines Team up to Improve Financial and Clinical Outcomes

Healthcare costs continue to increase at a disproportionate rate relative to gross domestic product, and Americans are becoming increasingly aware that they aren’t getting their money’s worth. To build a sustainable healthcare system, healthcare organizations must identify and address waste and reduce the total cost of care.

UPMC recognized that the common denominator to addressing threats to sustainability is to fully understand and effectively manage costs. It implemented activity-based costing (ABC), facilitated by the Health Catalyst CORUS™ Suite, to deliver detailed and actionable cost data across the analytics environment, and support service line reporting, contract modeling, and clinical process improvement. UPMC has used this approach to effectively drive cost savings and improve clinical outcomes in many of its service lines, including Surgical Services, Women’s Health, Orthopedics, and Cardiovascular. For example:

  • $3M cost savings/avoidance over 2 years through the implementation of the ERAS program.
  • Increased insight into cost variation and drivers of inefficiency in the operating room setting.
  • Improved patient outcomes and quality (readmissions, complications, patient reported outcomes, patient satisfaction, etc.) for patients undergoing joint replacement.
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Application of Analytics to DNFB Improvement Effort Continues to Deliver Impressive Results

Financial challenges rank as the number one issue hospitals face, and hospital CEOs are always looking for opportunities to boost revenue through improved reimbursement. Managing discharged not final billed (DNFB) cases, where bills remain incomplete due to coding or documentation gaps, is one important way hospitals can improve financial performance. However, without analytics to support efforts, meeting a target for DNFB improvement remains a serious challenge.

Thibodaux Regional Medical Center, a 180-bed community hospital in Louisiana, invested in analytics and resources to improve their DNFB rates. By expanding the use of analytics to every aspect of the work, the hospital transformed financial improvement efforts with impressive results.

While some organizations struggle to sustain hard-won financial improvements, two years after Thibodaux Regional launched its initial DNFB improvement effort, it has sustained the initial outcomes, and further reduced AR days by 27.5 percent, while achieving these additional improvements:

  • $1 million in additional annual reimbursement, attributable to improvements in the accuracy of clinical documentation and CMI.
  • 66.7 percent relative reduction in DNFB dollars, significantly improving cash flow.
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Accuracy of Readmission Risk Assessment Improved by Machine Learning

Hospital readmissions carry significant financial costs and are associated with negative patient outcomes. While the reasons behind patient readmissions are multi-factorial, and the specific rates vary by institution, nearly 20 percent of all Medicare discharges nationwide led to a readmission within 30 days. Preventing even 10 percent of these readmissions could save Medicare $1 billion.

North Carolina’s only not-for-profit, independent community healthcare system, Mission Health, is comprised of seven hospitals, 750 employed/aligned providers, and one of the largest Medicare Shared Savings ACOs in the nation. Mission had been using the LACE index to predict risk for readmission, and while it was helpful, Mission’s patient population was different than the population used to develop the LACE index, leaving the health system with some uncertainty regarding the readmission risk of its patients. With the help of data analytics, Mission developed its own predictive model for assessing readmission risk, aimed at preventing readmissions and improving outcomes for patients.

Results:

  • The area under the curve (AUC) for Mission’s readmission risk predictor is 0.784, outperforming LACE, and meeting the organization’s goal for performance.
  • Mission’s readmission rate is 1.2 percentage points lower than its top hospital peers.
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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.
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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.

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Using Data to Spotlight Variation and Transform Total Joint Care

Total Hip (THA) and Total Knee (TKA) Arthroplasty are the most prevalent surgeries for Medicare patients, numbering over 400,000 cases in 2014, costing more than seven billion dollars annually for the hospitalization alone. Today, more than seven million Americans have hip or knee implants, and the number is rising. Furthermore, substantial variation in the cost per case has raised questions about the quality of care. At Thibodaux Regional Medical Center, total joint replacement for hips and knees emerged as one of the top two cost-driving clinical areas with variation in care processes.

To address this, Thibodaux Regional maintained its focus on the IHI Triple Aim while developing organizational and clinical strategies to transform the care of patients undergoing THA and TKA. It commissioned a Care Transformation Orthopedic Team that set multiple outcome goals. Among its many efforts, the team established standard care processes, created an educational program, redesigned order sets and workflows, and deployed a joint replacement analytics application.

Thibodaux Regional reduced variability and decreased costs significantly while maintaining high levels of patient satisfaction:

  • 76.5 percent relative reduction in complication rate for total hip and total knee replacement.
  • 38.5 percent relative reduction in LOS for patients with total hip replacements.
  • 23.3 percent relative reduction in LOS for patients with total knee replacement.
  • $815,103 cost savings, achieved in less than two years.

 

 

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Clinical and Financial Partnership Reduces Denials and Write-Offs by More than $3 Million

CMS denies nearly 26 percent of all claims, of which up to 40 percent are never resubmitted. The bane of many healthcare systems is the inability to identify and correct the root causes of these denials, which can end up costing a single system tens of millions of dollars. Yet almost two-thirds of denials are recoverable and 90 percent are preventable.1 Despite previous initiatives, The University of Kansas Health System’s denial rate (25 percent) was higher than best practice (five percent), and leadership realized that, to provide its patients with world-class financial and clinical outcomes, it would need to engage differently with its clinical partners.

To effectively reduce revenue cycle and implement effective change, The University of Kansas Health System needed to proactively identify issues that occurred early in the revenue cycle process. To rethink its denials process, it simultaneously increased organizational commitment, refined its improvement task force structure, developed new data capabilities to inform the work, and built collaborative partnerships between clinicians and the finance team.

As a result of its renewed efforts, process re-design, stakeholder engagement, and improved analytics, The University of Kansas Health System achieved impressive savings in just eight months.

  • $3 million in recurring benefit, the direct result of denials reduction.
  • $4 million annualized recurring benefit.
  • Successfully partnered with clinical leadership to transition ongoing denial reduction efforts to operational leaders.
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Machine Learning, Predictive Analytics, and Process Redesign Reduces Readmission Rates by 50 Percent

The estimated annual cost of readmissions for Medicare is $26 billion, with $17 billion considered avoidable. Readmissions are driven largely by poor discharge procedures and inadequate follow-up care. Nearly one in every five Medicare patients discharged from the hospital is readmitted within 30 days.

The University of Kansas Health System had previously made improvements to reduce its readmission rate. The most recent readmission trend, however, did not reflect any additional improvement, and failed to meet hospital targets and expectations.

To further reduce the rate of avoidable readmission, The University of Kansas Health System launched a plan based on machine learning, predictive analytics, and lean care redesign. The organization used its analytics platform, to carry out its objectives.

The University of Kansas Health System substantially reduced its 30-day readmission rate by accurately identifying patients at highest risk of readmission and guiding clinical interventions:

  • 39 percent relative reduction in all-cause 30-day.
  • 52 percent relative reduction in 30-day readmission of patients with a principle diagnosis of heart failure.
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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.
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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.
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