Operations, Financial & Workflow

Success Stories

Health Catalyst

Employer Health Plan Successfully Lowers Costs and Boosts Benefits

Offering competitive employee health benefits is a business essential, and a differentiator for attracting top talent, but as healthcare costs continue to rise, employers are challenged to offer affordable healthcare with extensive benefits. The traditional approach of reducing benefits and raising premiums is unsustainable as a long-term strategy, but without a good way to understand, rationalize, or reduce healthcare costs, these costs are unpredictable and unmanageable.
Health Catalyst decided to embrace self-insurance earlier than what would be typical for a company of its size to take the management of its healthcare costs and benefit design into its own hands, as well as gain access to the data it needed to manage its population health. The organization is leveraging data and analytics to help uncover insights into improvement opportunities and methods to drive behavior change in its team member population. The company designed an intelligent benefit plan based on the needs and preferences of its team member population and engaged team members in an ownership and accountability mindset. These efforts have resulted in:

Successfully moved from a fully-insured/unmanaged organization to a self-insured/managed organization in less than five years.
Reduced healthcare spending by more than 20 percent while increasing the benefits offered in significant ways.
Maintained cost-effective, data-driven quality solutions that sustained the overall level of benefits offered to team members.
Re-invested cost savings into enhancing employee benefits.

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Quality as Strategy Transforms Care

Wasteful spending in healthcare now exceeds $1 trillion annually, which is double the money required to fund Medicare each year. Allina Health, a non-profit healthcare system, embraced a vision of the future where 100 percent of healthcare services add value, and everyone has access to quality, compassionate care.
Allina Health president and chief executive officer Dr. Penny Wheeler recognized the critical importance of data and analytics to measure and track performance. To meet those needs, the organization leveraged its analytics platform, using the integrated clinical, financial, and operational data to enable, measure, and scale data-driven improvement initiatives. With input from users, the analytics platform delivers ready access to the data and information providers and operational leaders need to improve and sustain outcomes.
Since undergoing this healthcare quality improvement initiative, select results include:

Improved care for spine patients.

31 percent of complications avoided.
22 percent relative reduction in SSIs.
$1 million VMP incentives received and over $2 million additional cost savings.

Enhanced recovery program elective colorectal surgery improvements.

78 percent relative reduction in elective colorectal systemwide surgical site infections.
19 percent relative reduction in systemwide length of stay, saving $90K in just six months.

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Boosting Readiness and Change Competencies Key to Successfully Reducing Clinical Variation

Reducing unnecessary clinical variation is necessary in today’s healthcare market for both clinical and financial reasons. Two major drivers for this are the shift from fee-for-service to value-based reimbursement and the need for improving clinical outcomes such as reducing complications and readmissions.
Leaders for UnityPoint Health, a healthcare system serving Iowa, western Illinois, and southern Wisconsin, recognized the importance of reducing clinical variation, and the need to have strong physician champions and robust analytics to effectively support improvement efforts. However, it also realized that without understanding organizational strengths and weaknesses related to adopting change and improving outcomes, it would struggle to successfully implement initiatives that delivered the desired benefits and sustained improvements over time. By consistently integrating information from a readiness assessment, an opportunity analysis, and expert resources, UnityPoint Health was able to establish a prioritization and implementation approach to outcomes improvement that has produced the following results:

Variable costs were reduced by more than $1.75 million based on the deployment of interventions in sepsis alerts, order sets, and other clinical decision support tools.
Reductions in length of stay have allowed patients to return home earlier and spend more than 1,000 additional nights in their homes.
Millions of clicks have been reduced for clinicians based on deployment of new sepsis screening tools.
36 percent increase in sepsis screenings completed in the emergency department (ED).
Sepsis order set utilization in the ED has increased by more than 185 percent.

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New Generation Activity-Based Costing Accelerates Timeliness of Decision Support

In healthcare, the timely delivery of patient-activity level cost metrics to clinical, financial, and operational leaders is critical; it allows the organization to respond to internal and external shifts and challenges to positively impact financial performance without negatively impacting patient care and the patient experience.
UPMC determined that the amount of manual effort needed to overcome the deficits of a suboptimal technical infrastructure and database supporting its cost management system drove many of the delays built into its closing process. After exploring the options to enhance and commercialize its cost management intellectual property, UPMC partnered with Health Catalyst to use the Health Catalyst® Data Operating System (DOS™) to co-develop and commercialize the CORUS™ suite activity-based costing module.
The new, analytics-driven cost management system supported a 50 percent reduction in the time needed to complete month-end close:

Three-day reduction in time to close.
Monthly preliminary results are typically reviewed within one business day, affording more time for validation and analysis.
Executives receive financial data up to three days sooner.
Reduction of 3.5 FTEs needed to complete the monthly close.
Reduced 60 human touchpoints and opportunity for error.
Multiple months of data can now be run simultaneously.
Provided support for new data-driven governance structure.

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Readiness Assessment Key to Sustainable Outcomes Improvement

Experiencing pockets of success is not enough to prosper during the transformation to value-based care. Leaders at UnityPoint Health, a healthcare system serving Iowa, western Illinois, and southern Wisconsin, determined that outcomes improvements needed to be sustained and spread easily across the organization to best utilize resources and serve its patients.
UnityPoint Health required an objective way to understand the strengths and weaknesses of the organization relative to outcomes improvement and its readiness for change. To this end, it chose the Health Catalyst® Outcomes Improvement Readiness Assessment (OIRA) Tool and professional services to administer it and identify the competency levels in the organization in the five areas known to influence an organization’s readiness for change. This resulted in:

Competency for improving outcomes measured at the organization, department and role level.
Recommendations made for increasing competency levels across the organization.
Clear direction and focus obtained from opportunity analysis.

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Analytics Improves Insight into PMPM, Reduces Liabilities in Rate-Setting Agreements

In the U.S., Medicaid provides health coverage to more than 68 million low-income men, women, and children, and is funded jointly by states and the federal government. Growing at an unsustainable rate, Medicaid programs have left many states with the challenge of finding new ways to create fiscally stable systems of care that also improve health outcomes.
Oregon established an accountable care model unique to the state composed of coordinated care organizations (CCOs) which are local organizations charged with managing care for members of the Oregon Health Plan—Oregon’s Medicaid program—in addition to finding innovative ways to meet the goals of the Triple Aim: better care, smarter spending, and healthier people. Like all CCOs, Health Share of Oregon required accurate and timely data to support forecasting for rate-setting to remain financially solvent and limit liability in this innovative model. Health Share leveraged analytics to obtain a holistic evaluation of the drivers of per member per month (PMPM) payment performance. Through improved access to this strategic and timely data, Health Share has successfully minimized liability, improved the accuracy of rate-setting utilization data, and reduced analyst time spent compiling complex regulatory reports.
Results:

Timeliness of rate-setting utilization data improved from two years to just a few months.
Identified opportunities to effectively reduce liabilities, helping to ensure ongoing financial viability of the organization.
Rapid integration of new member cost data.

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Machine Learning Automates Outpatient Coding

Accurate service line reporting is necessary for a healthcare organization to understand its total cost of care. Organizations that do not understand the total cost of care cannot be successful in risk-sharing and other forms of value-based payment, resulting in a loss of reimbursement.
In an effort to reduce costs, MultiCare Health System, an integrated delivery system serving Washington, decided to outsource all encounter coding, which eliminated the coding of outpatient encounters, negatively impacting service line reporting. To ensure accurate reporting, MultiCare asked its coders to assign an MS DRG code to all hospital-based outpatient encounters, which brought significant additional costs. To mitigate this, MultiCare utilized data analytics and machine learning to develop an algorithm that predicts the MS DRG code for hospital-based outpatient encounters.
By employing machine learning, MultiCare has achieved impressive results, including:

Successfully restoring service line reporting, enabling the organization to better understand the total cost of care, and supporting future participation in value-based care and risk-sharing agreements.
Ability to avoid additional labor costs that would be required to perform dual coding, saving more than $1M annually.

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Integrating Data and Analytics into Provider Workflow Improves ACO Performance

Reimbursement rates for an Accountable Care Organization (ACO) are based on the quality composite score from the Physician Quality Reporting System Group Practice Reporting Option, examining best practice preventative care and primary care measures. As a result, ACO participants may receive payment adjustments based on their quality composite performance.
U.S. Medical Management (USMM), a leading provider of home-based primary care services for complex patient populations and managed care clients, also operates a multi-state Medicare Shared Savings Program ACO serving over 23,000 complex or fragile Medicare patients. USMM needed to support its providers in meeting their patients’ necessities, while also ensuring they were providing and documenting appropriate best practice preventative and primary care ACO measures.
USMM turned to its analytics platform and analytics applications, implementing the Community Care Advanced Application to aid its efforts. The analytics platform integrates data from the organization’s EMR, billing system, and external claims data, bringing cross-organizational data into focus and delivering specific, actionable interventions needed to improve performance.
After implementing Community Care, USMM achieved a 90th percentile performance for:

Tobacco screening and cessation plan.
Clinical depression screening and follow-up plan.

The organization also earned an 80th percentile performance for:

Influenza immunization.
High blood pressure screening and follow-up plan.
Screening for future fall risk.

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Care Transitions Improvements Reduces 30-Day All-Cause Readmissions Saving Nearly $2 Million

Researchers estimate that in just one year, $25 to $45 billion is spent on avoidable complications and unnecessary hospital readmissions, the result of inadequate care coordination and insufficient management of care transitions.
While increasing its efforts to reduce its hospital readmission rate, the University of Texas Medical Branch (UTMB) discovered that it lacked standard discharge processes to address transitions of care, leading to a higher than desired 30-day readmission rate. To address this problem, UTMB implemented several care coordination programs, and leveraged its analytics platform and analytics applications to improve the accuracy and timeliness of data for informing decision making and monitoring performance.
This combination of approaches proved successful, resulting in:

14.5 percent relative reduction in 30-day all-cause readmission rate.
$1.9 million in cost avoidance, the result of a reduction in 30-day all-cause readmission rate.

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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.

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Data-Driven Practice Intelligence Increases Provider Engagement and Strengthens Improvement Efforts

Physicians are under increasing cost pressure from commercial health insurers and government payers. Physician groups that wish to remain independent must embrace the changes associated with the shift to value-based care, adopt new technologies to reduce and streamline costs, and demonstrate ongoing quality improvement.
Acuitas Health is a population health services organization that empowers physicians to make a successful transition to a value-based care delivery system. While the organization has the requisite expertise to provide these services to providers of care, Acuitas Health lacked the timely, actionable data required to effectively engage providers in improvement efforts.
Acuitas Health implemented the Health Catalyst® Data Operating System (DOS™) to support the development of practice intelligence profiles—comprehensive views of partner practices used by the practice intelligence team to increase provider engagement and strengthen improvement efforts.
As a result of the DOS implementation, Acuitas Health improved overall data quality to achieve significant results:

Substantial increase in provider engagement.
90 percent improvement in using data to identify improvement opportunities.
Provider- and practice-specific data, which would have previously taken months to compile, is now available daily.

 

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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.

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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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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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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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Care Management Solutions Improve Sprint to Value

Data-driven decisions and analytics are critical for organizations and physician practices transitioning to value-based care, although many organizations struggle with measuring the effectiveness of these population health initiatives.
To obtain sophisticated, actionable analytics and automate processes, Acuitas Health deployed the Health Catalyst® Patient Intake and Care Coordination applications concurrent with beginning the implementation of the Health Catalyst Data Operating System (DOS™) platform.  Acuitas meets the needs of its customers through a sprint to value—going faster than the typical time to value. The concurrent implementation approach used in this roll out set the pace for that sprint to value. In less than 60 days, the organization successfully implemented these tools and began receiving value. Acuitas is now able to:

Collect discrete data, and begin enhancing the work of the integrated care management team in a user-friendly way.
Identify individual caseloads.
Instantly obtain a complete, comparative, real-time picture of caseloads across the team—this reporting took weeks to compile in the past.
Make data-driven decisions on how to improve outcomes.

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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

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Designing Hospital Quality Function Around the Value Chain

Publicly reported measures of healthcare quality includes the Hospital Safety Score Grades which award a letter grade representing performance for 30 evidence-based measures of patient safety. An “A” represents the best Hospital Safety Score, followed in order by “B,” “C,” “D,” and “F.” In the fall of 2014, Piedmont’s Hospital Safety Score Grade for its five hospitals included four “C’s” and a “D.” This demonstrated a need to change its approach to quality improvement and ensure proper resources were allocated and aligned with the value chain, enabling it to efficiently conduct surveillance activities, perform analysis, and facilitate sustained outcomes improvement.
To increase capacity for performing more value-added work, Piedmont leveraged its analytics platform to automate surveillance activities and monitor the effectiveness of quality improvement efforts. These tools helped Piedmont redesign its quality improvement efforts, resulting in a:

35 percent relative reduction in healthcare facility acquired infections per patient day.
50 percent reduction in the time required for peer review.
50 percent reduction in the time to implement improvement projects.

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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.

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Using Data-Driven Insights to Improve Practice Management

Effective practice management includes tracking and reporting patient outcomes, and effectively managing revenue cycle, as well as keeping an eye out for market changes and growth opportunities. Well-managed practices effectively balance supply and demand on a daily, weekly, and long-term basis, actively managing encounter volume, panel size and scope, timeliness of available appointments, and payer mix.
John Muir Health faced challenges in obtaining data that would provide leaders with strategic decision support information that fostered effective practice management. John Muir Health had attempted to use its EHR to obtain this information, but discovered it was unable to meet the complex demand. As a result, the organization relied on burdensome manual work processes, resulting in delays and a backlog of data requests, and limited ability to make well-informed, data-driven decisions.
After leveraging the information within its data warehouse and analytics platform to create a network leadership encounter application, John Muir Health acquired the following capabilities:

All leaders have on-demand access to performance data at multiple levels from the organization-wide performance down to the patient and provider level.
Senior leaders are making data-driven decisions for strategic responses across John Muir Health to shifts in market, growth opportunities, and emerging markets.
The regional management teams are using the application to inform:

Daily operations.
Encounter processing
Patient access
Budget variances.

By leveraging these new capabilities, John Muir Health has achieved:

Transparency of the data and accountability of the regional management teams for key performance indicators
14 percent improvement in completed physician encounters, resulting in faster revenue capture, when compared with the previous year.
Eliminating the encounter-associated report backlog.

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Capturing the Voice of the Patient: Using PROMs Improves Shared Decision Making

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.

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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.

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Clinically Meaningful Quality Metrics Improve the Provider Experience

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).

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