Hospitals spend over $7.5 million every year on regulatory compliance. Payers, such as CMS, rely on these quality measures to evaluate health system and provider performance and determine reimbursement rates for services rendered. As a result, regulatory performance is critical to the care process and revenue stream. However, many health systems fail to meet these care standards and maximize reimbursement rates because they lack analytic insight into regulatory performance. With a data engine that tracks and submits quality measures data, leaders understand their compliance performance, gaining insight into opportunities to improve patient-centric care and value-based performance. This data-informed approach allows organizations to increase profits through peak regulatory performance and avoid financial penalties associated with underperformance.
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With data and data sources on the rise in healthcare, organizations need to more effectively organize, track, and distribute data to team members. A data governance strategy gives health systems a standardized approach to manage data, their most precious asset. Effective data governance helps leaders maximize their data, promote systemwide data-informed decision making, and drive sustainable improvement. Healthcare leaders can operationalize data governance in their organizations by considering three key elements of an effective strategy:
- Start with the data governance basics.
- Ensure the data governance strategy supports sustainable improvement.
- Align the data governance strategy with organizational priorities.
As healthcare decisions, data points, and options increase, time, resources, and margin of error decrease. To succeed in this environment, leaders and analysts must know where to focus and how to allocate resources and set accountability targets. With Healthcare.AI™, five super-powered assistive augmented intelligence capabilities help healthcare leaders and analysts determine values, understand context, and provide data-driven motivation to transform healthcare:
- Enhancing humans’ natural visual pattern recognition.
- Calculating trajectories.
- Accelerating the pace at which analysts produce and experiment with how to present the insights.
- Producing high-caliber, high-quality analytic results.
- Building trust by enabling immediate, visual, and transparent results.
With mounting pressures to deliver quality care with fixed resources, data-driven healthcare is pivotal to organizations’ well-being. From operations to the front lines of clinical care, data can drive the best outcome if decision makers have relevant information when they need it. However, many organizations simply use data in one-off situations rather than integrating it into systemwide processes and workflows. To understand what it means to become data driven and take the right steps forward, organizations can apply four key elements:
- Invest in one source of data truth.
- Apply a data governance strategy.
- Promote systemwide data literacy.
- Implement a cybersecurity framework.
Surviving on thin operating margins means health systems must maximize every financial earning opportunity. To identify threats to the revenue stream, organizations need access to precise, accurate costing information. An activity-based costing (ABC) system leverages patient resource utilization data to reveal exactly how much it costs to deliver care. Unlike traditional costing systems that provide average cost estimates for services rendered, ABC includes five benefits that help systems understand the cost for every aspect of the care delivery process:
- Comprehensive costing data.
- Ease of use.
- Precision and accuracy.
- Near real-time analytics.
- A proactive cost strategy.
Increased patient engagement leads to better clinical outcomes, but organizations still struggle to engage patients and their families in their care. To start, patients have different levels of interest in their care and competency regarding healthcare, which adds to the challenge of treating each patient like a member of the care team. However difficult these patient engagement roadblocks are, organizations can use data to overcome them. Access to data allows healthcare leaders and providers to identify opportunities to optimize patient engagement. By implementing four data-informed tactics, systems can increase patient engagement and improve health outcomes:
- Implement shared decision-making interventions.
- Advance health equity.
- Prioritize patient feedback.
- Provide patient-centered education.
The long-term success of healthcare performance improvement relies on a sustainable infrastructure and strategic execution. Otherwise, improvement initiatives risk becoming one-off projects that don’t support ongoing advances in critical areas, such as critical areas, clinical outcomes, patient experience, and organizational cost. Healthcare organizations can follow six steps for a sustainable, impactful performance improvement program: 1. Integrate performance improvement into strategic objectives. 2. Use analytics to unlock data and identify areas of opportunity. 3. Prioritize programs using a combination of analytics and an adoption system. 4. Define the performance improvement program’s permanent teams. 5. Use a best-practice system to define program outcomes and interventions. 6. Estimate the ROI.
Delivering precision medicine requires healthcare to transition from a one-size-fits-all methodology to an individualized approach. This means healthcare professionals tailor treatment and prevention strategies according to each patient’s personal characteristics—their genomic makeup, environment, and lifestyle. To realize these precision care goals, researchers and clinicians must leverage vast and varied amounts of real-world data. Data access and interoperability barriers have often impeded the precision medicine transformation. However, current healthcare industry trends increase opportunities for researchers and clinicians to more comprehensively understand medical conditions and the patients in their care. These insights establish the foundation for precision medicine and support actionable pathways towards more efficient development of targeted treatments.
Many organizations face high costs and diminishing returns due to unnecessarily high length of stay (LOS) and readmission rates. Elevated LOS and readmission rates can indicate low quality care and also result in costly financial penalties. Therefore, addressing LOS and readmission rates can eliminate avoidable financial consequences, while keeping patients out of the hospital and less likely to develop hospital-acquired infections. Health systems can leverage analytic insight to reduce unnecessary patient LOS and readmission rates, resulting in lower costs for health systems and better health for patients, by applying three data-driven strategies:
- Implement process changes.
- Remove discharge barriers.
- Improve care transitions.
As the healthcare industry recovers from COVID-19, providers are re-evaluating the financial arrangements that motivate them to improve their processes while benefiting payers and patients. With the pandemic driving lower provider volumes and straining hospital resources, the industry has a renewed urgency for policies that drive better outcomes while lowering cost and improving revenue. Moving forward, healthcare must reset its payer-provider performance standards to the post COVID-19 environment. Renewed approaches to the following models will consider the impact of remote care, how to reimburse telehealth services, and the need for consistent payments to providers:
- Pay for performance.
- Bundled payments.
Pediatric care has unique challenges, such as communicating with young patients through a parent or guardian and assessing pain levels with children. To overcome these challenges, organizations can rely on operational data to target pediatric improvement areas that lead to lower costs and higher profit margins. Leveraging operational data—instead of focusing solely on pediatric outcomes data—can reveal opportunities for health systems to improve pediatric patient access and, in turn, increase revenue. Organizations can deliver higher quality pediatric care while increasing profits by implementing three data-informed strategies:
- Maximize space utilization.
- Improve patient scheduling.
- Implement virtual care.
Treating mental health is often a low priority for health systems because of its high costs and low reimbursement rate. But health systems should not underestimate the impact mental health has on one of their costliest areas—treating chronic diseases. As research links higher costs to patients with chronic disease and a mental health disorder compared to patients without a mental health disorder, organizations should consider mental health treatment a key part of chronic disease management. By following four steps, providers and care teams can address patients’ mental health, thereby improving chronic disease outcomes and lowering costs:
- Identify the patient population.
- Identify the financial impact.
- Develop a plan with experts.
- Measure the impact and show ROI.
As health systems continue to adapt to the pandemic healthcare landscape, certain challenges remain—including generating revenue on thin operating margins. Poor charge capture is a common reason behind lost revenue that healthcare leaders often fail to address. Because charge capture is the process of getting paid for services rendered at a hospital, poor charge capture processes mean the hospital does not get paid in full for a service, resulting in lost revenue that is typically unrecoverable.
Health systems can avoid financial leakage and increase profits by focusing on five problem areas within charge capture practice:
- Emergency services.
- Operating room services.
- Pharmacy services.
- Supply chain and devices.
- CDM mapping.
Health systems rely on effective revenue cycle management to follow the patient journey, navigate claims, and ensure the organization collects payment for its services. In today’s complex and fluid healthcare industry, in which revenue cycle management is about much more than billing and collecting payment, traditional revenue cycle approaches can’t meet escalating demands. Additionally, with lost volume due to COVID-19, organizations can’t afford to miss an opportunity for payment. The contemporary healthcare landscape requires a comprehensive, standardized, and data-driven revenue cycle process. Health systems that leverage data to support revenue cycle management improve their financial outcomes in three significant ways:
- Reduce denials.
- Increase collections with propensity-to-pay insight.
- Improve discharged-not-final-billed efforts.
Healthcare financial leaders are constantly brainstorming ways to increase operating margins through better revenue cycle performance. These efforts often lead revenue cycle leaders to denied claims—when a payer doesn’t reimburse a health system for a service rendered. Although denials are a common reason for lost revenue, experts deem nearly 90 percent avoidable. Effective denials management starts with prevention. Organizations can use revenue cycle performance data, combined with artificial intelligence, to predict areas within each claim’s lifecycle that are likely to result in a denial. With denial insight, health systems can optimize revenue cycle processes to prevent denials and increase operating margins.
As health systems experience more pressure to deliver quality care with limited resources during a pandemic, data analysts play a vital role in helping organizations overcome new COVID-19-induced challenges. Data analysts provide direction about the best way to dissect data, identify areas for improvement, and solve complex problems that stand in the way of better healthcare delivery. However, by developing four specific skills, data analysts can optimize their work and help leaders make sound operational, clinical, and financial decisions:
- Begin with the end in mind.
- Focus on problem solving.
- Master the foundational competencies.
- Play the data detective.