Hospitals & Health Systems

We tailor our approach to individual hospital and health system needs in light of each organization’s operating priorities, available data resources and existing capabilities. We bring deep expertise to helping better quantify quality measures and outcome and process measures such as avoidable mortality, length of stay, throughput and ICU utilization. We surface key insights into the drivers of events and outcomes that can be tied back to pragmatic actions at the operational level. Baselining is good, understanding root causes is better – but our goal is to help organizations go beyond both by evolving a data-driven strategy for improvement that is achievable within the confines of existing staffing and resources constraints

Sample Solutions

Population Health Management

Risk Stratification: Stratify patient populations based on risk factors to enable targeted interventions, preventive care, and resource allocation to those who need it most.

Chronic Disease Management: Implement effective disease management programs, optimize treatment plans, and improve patient outcomes.

Quality Improvement

Monitor Performance Metrics:
Baseline, benchmark, and monitor longitudinal trends for key performance indicators and quality metrics.
 
Identify Opportunities and Drivers: Explore trends and patterns to identify performance gaps or variations and conduct root cause analyses for patient outcomes, safety measures, efficiency indicators, and patient satisfaction scores.

Operational Efficiency

Resource Optimization: Optimize resource allocation, including staff scheduling, bed management, and equipment utilization.

Patient Flow: Identify bottlenecks, reduce wait times, and enhance the overall patient experience by improving the efficiency of care delivery.

Adherence to Protocols: Ensure adherence to evidence-based protocols and guidelines, improving the consistency and quality of care provided across the organization.

Cost Containment

Identify Cost Drivers: Identify cost drivers, assess the financial impact of different initiatives, and implement cost containment strategies without compromising patient care quality.

Revenue Cycle Management: Support effective revenue cycle management by identifying opportunities to streamline billing processes, reduce denials, and optimize reimbursement.

Regulatory Compliance

Ensuring Compliance: Support monitoring and reporting on quality measures, risk adjustment, and other regulatory obligations.

Health Equity: Evaluate risk-adjusted outcome and process measures across health equity dimensions to identify potential disparities, identify potential drivers and create an action plan.

Patient Engagement

Personalized Medicine: Develop personalized treatment plans and interventions tailored to individual patient needs and preferences.

Behavioral Analysis: Understanding patient behaviors and drivers of risk to implement targeted outreach and engagement strategies, improving patient adherence to treatment plans and preventive care measures.

Delivering top-tier analytical and research solutions that truly make a difference in the healthcare landscape

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Joseph Beals, PhD, MBA, FAMIA

Joe is an accomplished healthcare executive with a track-record of bringing innovative technologies to market and helping client organizations develop and execute digital health strategies. A common thread throughout his career is a passion for translational data science – the “bench to bedside” operationalization of evidence-based insights and data driven technologies.

Joe has extensive experience in health informatics research, including predictive model development, clinical trial design, and process and outcomes improvement. He has published widely and received research awards from the American Medical Informatics Association, the Society of Critical Care Medicine, and the Journal of Biomedical Informatics. He worked closely with the FDA on one of the first real-world evidence supported regulatory clearances for AI/ML software used in predicting patient deterioration. Joe has led US and European federal grant projects, most recently as co-principal investigator on a contract from the US Department of Health and Human Services Biomedical Advanced Research and Development Authority to develop and deploy an Emergency Department triage tool.

In a prior role as CEO of PeraHealth, Joe expanded the company’s focus to encompass health care delivery challenges across the care continuum, including in sub-acute and home health environments and he oversaw the transformation of the company’s analytics service offerings in these areas. Following the acquisition of PeraHealth by Spacelabs Healthcare, Joe led Spacelab’s data science and analytics strategy, spear-heading the company’s digital health and analytics roadmap. Joe is a long-time proponent of the concept of augmented intelligence in healthcare – the operationalization of innovative AI/ML technologies which can both enhance the effectiveness and improve the experience of clinical care providers.

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Kathy W. Belk

Kathy is a clinical informaticist, data scientist and healthcare technologist with over 25 years of experience conducting healthcare research and performance improvement initiatives.

She has a passion to transform healthcare through data-driven care redesign and a diverse background enabling her to balance innovative strategy with rigorous scientific methodologies to create fit-for-purpose solutions.
She has extensive experience leading data-driven projects for pharmaceutical, biotech, medical device companies, health service providers as well as specialty societies and government agencies. Her work includes both traditional and innovative study designs across a wide range of topics and clinical areas and has resulted in more than 100 peer-reviewed publications and/or presentations in scientific journals and conferences.

Kathy has extensive data collection and linkage experience across many types of healthcare datasets including two used by the U.S. Food and Drug Administration, for which she was a subject matter expert. In a prior role with Premier, Inc., she served as data expert and lead scientist for an innovative pay-for-performance demonstration project with the Centers for Medicare & Medicaid Services. More recently she has led a range of data science, analytics and clinical technology initiatives for effective development and deployment of clinical decision support technology.