When it comes to outcomes and process improvement in healthcare, Maureen Bisognano is the industry expert. With deep healthcare experience that began at Quincy Hospital, where Maureen worked as a staff nurse, then Director of Nursing, then Director of Patient Services, and then COO, she is currently the Institute for Healthcare Improvement (IHI) President Emerita and Senior Fellow. Maureen’s interest in healthcare improvement began when her brother, Johnny, was diagnosed with Hodgkin’s disease at age 17. Johnny’s hospital experiences inspired Maureen to dedicate her life to improving patient lives. As a keynote speaker at HAS 17, Maureen will share her inspirational story and practical approach to quality improvement.
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Trump/Republican rhetoric recently met reality when it comes to the Affordable Care Act (ACA). The latest version of the bill that passed in the House is far from a complete repeal and replacement of the ACA. However, the bill includes significant changes to healthcare policy and coverage, from severe Medicaid cuts to shifting financial accountability. ACA uncertainty has healthcare leaders concerned about how to plot a path forward, with three questions on the top of their minds:
- What will the final bill look like?
- How do I plan for the changes?
- What should happen next to fix the problems with the ACA?
It’s no easy task to lead a real-time, outcomes-focused, high-performing health system. That’s why every chief medical officer (CMO) needs a healthcare executive dashboard—a decision support tool that helps these senior physician leaders ensure their organizations continue to achieve the seven key attributes of a high-performing health system:
- Efficient provision of services.
- Organized system of care.
- Quality measurement and improvement activities.
- Care coordination.
- Use of information technology and evidence-based medicine.
- Compensation practices that promote the above-listed objectives.
For healthcare organizations to be successful with their quality and cost improvement initiatives, physicians must be engaged with the proposed changes. But many physicians are not engaged because their morale is suffering. While some strategies to encourage buy-in for improvement initiatives don’t work, there are six strategies that have proven to be effective: (1) discover a common purpose, (2) adopt an engaging style, (3) turn physicians into partners, not customers, (4) segment the engagement plan, (5) use “engaging” improvement methods, and (6) provide them with backup—all the way to the board. Once the organization has their trust, physicians will gain enthusiasm to move forward with improvement efforts that will benefit everyone.
As access to healthcare data grows, healthcare leaders are using more data to make decisions. Executives and front-line clinicians need a decision-support tool that meets the demands of today’s increasingly data-rich environment. Healthcare dashboards once filled this niche, but no longer keep up with ever-growing data demands. Fortunately, an innovative visual reporting system, Leading Wisely™, picks up where dashboards fall short—enabling faster reporting and customized, self-service capability for comprehensive data-driven support. Leading Wisely’s key next-level features include:
- Customization, allowing the individual user to personally tailor measures.
- Proactive alerts, prompted by personalized notification settings.
- User friendly layout, with easy-to-read highlights that indicate if a measure if moving off course.
In today’s data-rich healthcare environment, patient registries put knowledge in front of the people who will use it to improve outcomes and population health. Non-IT professionals (e.g., clinicians and researchers) often don’t have direct, timely access to operational and clinical data. As a result, organizations miss out on important improvement opportunities and data-driven point-of-care decisions. Knowledge too often remains siloed in the enterprise data warehouse (EDW) or among specialized groups. Patient registries remove these barriers. It allows clinicians and researchers to make informed choices and frees up data analysts to focus on their priority areas.
As data availability and open source tools make predictive analytics increasingly accessible for health systems, more organizations are adopting this advanced capability. Organizations won’t, however, use predictive analytics to its full potential—making it routine, pervasive, and actionable—without a deployment strategy that scales the technology. Three recommendations can help health systems successfully deploy predictive analytics and leverage data experience to improve data-driven interventions and outcomes:
- Fully leverage your analytics environment.
- Standardize tools and methods using production quality code.
- Deploy with a strategy for intervention.
Unnecessary barriers to practice and licensing limitations have severe consequences for health systems’ population health initiatives, especially as the nationwide shortage of healthcare practitioners continues to grow:
- Delayed access to clinicians.
- Decreased access to care, particularly primary care and care in rural areas.
- Limited labor supply.
- Increased costs of services.
- Loss of potential revenue for healthcare organizations.
Healthcare CEOs and other C-Suite leaders can’t make quality decisions in today’s rapidly changing, complex environment without decision support. Healthcare CEOs are starting to realize that executive dashboards with personally tailored views of key metrics are no longer a luxury, but an absolute necessity, for three key reasons:
- Helps leaders analyze and digest large amounts of data relating to care quality, operations, contracting, and major purchasing decisions.
- Gives leaders a clear understanding of the financial aspects of their systems, such as revenue streams, cost drivers, costs of capital, bundled payments, and payment reforms.
- Facilitates conflict resolution and helps leaders work collaboratively—using a matrix management approach—with peers, direct reports, and system experts.
Machine learning in healthcare is already proving its worth in clinical applications. From identifying tumors in mammograms, to diagnosing skin cancer and diabetic retinopathy from images, algorithms can perform certain duties more quickly and reliably than humans. While only used for specialized medicine now, the time will come where every practitioner and patient will benefit from cyber-assisted bedside care. This won’t develop without ethical implications, but the advantages that machine learning will bring to healthcare in terms of lower costs, improved quality of care, and greater provider and patient satisfaction, will easily outweigh those concerns. In this article, Dr. Ed Corbett explores the intricacies of machine learning from two perspectives: as a physician and as a family caregiver with a personal story about how this data science could benefit patient lives today.