Advanced Analytics and AI for Value-Based Programs and Contracting
In today’s rapidly changing healthcare landscape, payers and providers are moving away from fee-for-service to new models of Value-Based Reimbursement and Care Delivery . This shift requires proven models to systematically improve outcomes while reducing cost across the continuum of care.
The Mside AccelarMed is a flexible Big Data, Analytics and AI platform that fosters operational excellence, value based performance and reimbursement optimization. It leverages comprehensive quality and financial analytics combined with advanced machine learning algorithms and enables payers and providers to collaboratively design sustainable payment and care delivery models through planning, monitoring and proactively managing various Value-Based programs.
Key Goals and Objectives of the Innovative Care Delivery Organization
In Value-Based Contracting models, reimbursement is tied to the provider’s performance on cost efficiency and quality performance measures. It can be associated with meeting specific performance criteria or negotiated through “shared savings/shared risk” contracts. For providers it requires the deep understanding and effective planning, negotiating and monitoring of the three components – quality, reimbursement and cost – utilizing data-driven, fact-based approaches.
Quality: maintaining or improving quality is a key element for successful alignment of financial incentives such as bonus and shared savings payments
Payment: typically value based payment models require reduction of total payments for the care of selected patient populations
Cost: providers need to find effective methods to redesign care delivery to reduce cost while ensuring sustainable revenue margins
AccelarMed was conceived and designed by clinical, financial and technology experts to help Innovative Care Delivery Organizations provide the best possible and highly individualized care while accurately managing value across service lines by improving the ratio of patient outcomes achieved per dollar expended.
Data Driven Optimization of Performance, Operations Excellence and Reimbursement
AccelarMed platform offers following unique advantages:
- Enables providers to apply a data driven and advanced analytics approaches to identify paths to sustainability for innovative Value-Based contracts and care delivery programs
- Provides advanced capabilities to evaluate and manage key aspects of managing the Value-Based Contract as well as delivering high value services and redesigning healthcare delivery options
Value-Based Program Management
AccelarMed provides the advanced algorithms, interactive and intuitive dashboards and reports to manage various value-based programs:
- Identify opportunities for Value-Based Programs,
- Set quality, cost and utilization targets,
- Monitor actual-to-budget performance across the various enterprise service lines,
- Design the provider network – identify opportunities for partnerships, acquisitions and outsourcing models
Learn more about the comprehensive AccelarMed Value-Based Program Management features.
Proactive recognition of patient-cohorts within the served population that require special Value-Based Modelling and Care Delivery using the AccelarMed AI and advanced machine learning models
Driving growth in Value-Based Care environment requires tailoring quality, reimbursement and cost targets to the specifics of the various Value-Based Contracts and the served populations leveraging big data, real-time analytics with artificial intelligence (AI) and machine learning models.
AccelarMed helps identify well defined population cohorts with specific clinical characteristics, utilization and cost patterns using:
- State of the art risk analysis algorithms based on the CMS HCC, CMS RxHCC, the ESRD/PACE, HHS-HCC, Charlson-Deyo Risk, Readmission and LOS risk
- Advanced machine learning models with flexible configuration capabilities: A core component of the AccelarMed AI platform includes the machine learning models for patient cohort analysis. The advanced ML algorithms can identify specific cohorts of the served patient population based on prevalent co-morbidity combinations (such as “ESRD and Other Endocrine and Metabolic Disorders”, “COPD, CHF and Arrhythmia” or “Pneumonia, Pressure Ulcer”), the patient risk profiles as well as common patterns for utilization of services/ pharmaceutical products.
The AccelarMed Dashboards and Reports provide actionable insights about cost, quality and utilization, unwarranted variations of services for these patient cohorts with a high level of granularity and across the enterprise service lines. The detailed analysis enables organizations to design sustainable Value Based Contracts and Care Delivery Models with appropriate cost thresholds and quality goals tailored to the specific needs of the identified patient sub-population.
AccelarMed offers a deep-dive performance analysis across integrated service lines, in- and out-of-network providers with the out-of-the-box capabilities for:
- Break-down of cost, utilization and quality metrics per individual provider, practice, site, division and service line,
- Answering key questions such as: “what is the typical service utilization for a particular population group”, “who are the providers with high quality and high efficiency that can help drive down the cost while improving overall outcome” or “what is the performance of providers across the enterprise organizational structures compared to the average in the state”,
- Leveraging proprietary and public data, AccelarMed augments the performance information about in- and out-of-network providers to enable new partnerships that foster quality and efficiency improvements,
- Optimize provider performance and identify virtual teams for patients in specific narrow cohorts – e.g. after leveraging the machine learning models to identify high-risk patient cohorts in the served population (e.g. in the narrow patient cohort of “COPD, CHF and Arrhytmia”), organizations can identify the providers with best quality, efficiency and patient satisfaction performance as well as “best virtual teams” across service lines (inpatient, outpatient, professional).
Quality and Patient Safety
AccelarMed provides following comprehensive features:
- Allows providers to measure quality and patient safety indicators across enterprise service lines, specialties and various Value Based Payment Programs by leveraging over 200 best practices quality and patient safety indicators endorsed by NQF, AHRQ and various medical societies and used in MIPS, PQRS and other quality programs
- Offers intuitive tools to customize existing or create new quality metrics
- Provides the possibilities to set targets, track and monitor actual-to-target development
- Configure actionable alerts when indicators fall short on certain predefined thresholds
- Insight into specific quality performance for the patient cohorts identified through our powerful machine learning algorithms
Reduction of Unwarranted Variations
AccelarMed provides the tools to gain deep insights into the root-cause for unwarranted variations, define new targets to support informed decisions and the definition of meaningful improvement initiatives. AccelarMed provides out-of-the box capabilities to measure:
- Cost Related Variations: due to price differences, utilization of services, different sites of service (Inpatient, Outpatient, Professional or Emergency room) resulting in different costs for comparable procedures
- Quality Related Variations: such as per geographic distribution (by ZIP code), health plans and health plan type (e.g. Medicaid, Medicare/MA, Commercial), health plans
The variation analysis can be performed for the entire patient populations or refined based on the identified narrow patient cohorts using the Mside AccelarMed machine learning models.
Effective ABC Costing and Reduction of Workflow Waste
AccelarMed provides the capability to use flexible Time-Driven Activity Based Costing to:
- Track expenses at a very detailed patient level
- Identify sources of unwarranted variations
- Identify easily areas with potential for improvement such as finding and removing bottlenecks or intermediaries in processes, moving process steps in the system closer together, do tasks in parallel and many more