Now that meaningful use is transforming into the value-based care delivery model, providers face a major challenge of adapting to changes in how service delivery is organized, measured, and reimbursed. ‘attention. No need to brown any pills here, it’s the “Do it or die” dilemma.
The “Do or Die” dilemma.
Significant use stipulates fee-for-service payments, so the main focus here is on the volume and profitability of services provided (appointments, testing, admissions, and treatments). Performance-based care puts improved value in the spotlight, which means getting the best results at the lowest cost.
If the organization does not improve value, it will no doubt face growing pressure from insurers, employers, Medicare and Medicaid struggling to cut costs. Thus, caregivers seeking to retain their strengths need to change their strategy and base it on relevant data on the progress, outcomes, and costs of providing care.
Success strategy: costs and results
Care value is probably the most significant variable in this transformation of care delivery. To measure this systematically, suppliers need a set of autonomous systems health data analysis tools that can be integrated with healthcare computer systems that are already in use.
What needs to be analyzed to improve value? EMR or EHR is a good place to start; however, it is not enough. “EMR systems are, at a very basic level, sophisticated billing systems,” said Matt Schuchardt, director of sales for market intelligence solutions at HIMSS Analytics. “They capture a lot more data and allow you to bill more effectively. But they’re just the beginning of what the big data revolution will do to health.”
The essential components of the concept of value are outcomes and costs at the level of a patient’s medical condition (such as Lisa’s diabetes), not the level of specialty (e.g., endocrinology) or examination (pancreatic ultrasound). ). Therefore, these components are difficult to measure if you do not know where to look.
Measurement of results
The results cover the entire disease care process and beyond, tracking a patient’s health status after recovery, during the rehabilitation period, and beyond. EHR / EMR systems and chronic disease management / population health management applications provide providers with key information to effectively analyze and report results in a health data analysis solution, such as:
- Length of hospital stay
- State of health or recovery
- Time to get back to work
- Level of recovery from physical activity
- Mortality, and others
Most healthcare organizations do not have an accurate picture of how much the entire care process costs for a patient’s medical condition, as most costing systems are designed to bill fee-for-service transactions, not for to episode payments based on value.
To effectively measure relevant costs, caregivers must use at least two sources: their EHR and their accounting system. An EHR provides a health data analysis application with information about the resources used to provide care (staff, medical equipment, facilities). An accounting system can shed light on unit costs of time (to supply each resource used) and overhead costs (IT, administration, and department-level overhead).
Using these three attributes, a data analysis system correctly calculates the cost of each particular intervention, adds these interventions, and defines the cost of the episode.
Value assessment through an analysis system
By processing relevant data, analytical solutions allow caregivers to relate costs to outcomes and gain visibility into a wide range of errors and achievements in care delivery, for example:
- Variations in expenses to treat specific conditions, supported by data on specific patients and their respective results
- Variations in results based on demographic factors (age, income level, lifestyle)
- Variations in results based on the internal factors of a healthcare organization (a specific doctor, a treatment, a center, and more)
- Relationship between results and costs over various periods of time, providing information on the results of different changes in the care process
Milestones of technical implementation
To perform their functions effectively, these solutions must meet the following requirements:
- Independence. The data analysis system must not be linked to any particular application or EHR.
- Coverage. The data warehouse should collect information from various sources, such as EHR, PMS, RCM, population health / chronic disease management systems, departmental systems, and others important to a particular caregiver.
Customization. Business solutions are useful in predictable circumstances and established processes. However, when a whole new healthcare paradigm emerges, only agile, customizable applications can help providers painlessly adapt to the value-based care model. We propose to use a Microsoft SQL Server based data warehouse together with:
- OLAP Cubs from Microsoft SQL Reporting Services
- A Microsoft SQL Reporting Services front-end environment for predefined reports
- Microsoft Excel for exploratory analysis
Accept the challenge based on values
The values-based approach to care is a challenge. What we suggest is to accept it in the best possible way: cold-blooded, armed with effective data analysis tools. By reducing the abstract concept of value to relevant metrics and attributes, caregivers can gain control over the quality of their services and improve outcomes by keeping costs at the right levels.