Data is the prerequisite for everything based on value, including AI

In value -based care, nothing happens without access to robust data. It feeds everything, advanced analyzes with predictive AI models. It provides a holistic image of population health and patient needs of patients, informing the appropriate care interventions that improve results and reduce costs. As the AI tools become more widespread in health care in general and in value -based care, it is essential to obtain the right Data Foundation foundation.

But health care data is and has always been extremely difficult. Organizations need corporate data management capacities which can safely bring together extended data sets and go beyond the retrospective audit of what has happened in the past to proactively manage patient care today, and anticipate patient needs in the future to personalize care.

Why data is fundamental to VBC

In VBC, performance is measured on three dimensions: quality, cost and experience of patients. To be successful, organizations must follow progress in the three – identify care gaps, follow references and align incentives. It is impossible without precise, complete and timely data to:

• Effectively monitoring and managing patient populations
• Assign patients correctly for care and reimbursement
• Reconcile payments under complex contractual structures or payment models
• Pinpoint opportunities to improve the service and results of care

Having all of this in a single source of truth – normalized, enriched and available at the right time for the good members of the team – is a challenge for the most experienced VBC participants. Most organizations still have trouble with fragmentation, interoperability, data delays, confidentiality problems and limited resources – and this slows down our collective progress in value -based care.

Date + you have

Artificial intelligence (AI) and advanced analyzes hold a huge promise in VBC. With these capacities, health care organizations can predict population health trajectory, predict the performance of VBC contracts with a drop risk and recommend interventions adapted to individual needs – and all this can be done more quickly and more precisely than ever possible before. But AI is as good as its data foundation, which comes from several sources:

• Data complaints This provides information and advanced analysis capacities, but which has a significant delay time (90+ days in certain cases) and lack of current clinical context
• Clinical data DSE, laboratories, imagery and other sources, which is essential for making care decisions at the time
• SDOH data This informs care teams on potential access obstacles or potential risk factors apart from what is contained in a medical file or complaint data
• Pharmacy data on current and old drugs, including membership data
• Data generated by the patient From tools such as portable devices and home health care and can supplement DSE data on the current patients of patients
• Cost and use data For better comparative analysis and reconciliation of contracts in alternative payment models based on complex or risk -based values

Precise AI models require significant data libraries, training algorithms to improve care while avoiding traps, such as:

• Incomplete data Led to biased or inaccurate models – and the issues are too high in health care so that this aspect of data management and AI development is bad.
• Delayed data Cours missed intervention possibilities for suppliers and payers, and potentially worse costs and higher costs when the teams do not need the information they need to understand what is happening with patients and members today.
• Lack of governance And railings considerably increase risks and can lead to serious damage, inappropriate care or even death in the most serious cases.

The key to successfully use AI to advance VBC is to find health technology companies that balance rapid development and deployment with transparency and appropriate guarantees to protect the integrity of ideas, forecasts and care recommendations from AI tools.

Build a data -based VBC infrastructure

Solid data foundations do not occur by accident. They require strategic planning and investments in tools that can:

• Appracting data from the whole health care ecosystem
• Normalize and enrich the data so that it is clean, consistent and usable throughout your technological platform
• Act as a single source of truth with the possibility of sharing data in a transparent manner on several platforms, applications and systems
• Protect data and partition access to protect against violations and ensure that everyone works with the data they need to guarantee optimal results for patients

With these tools in place, organizations can then build a culture of data literacy and data -based decision -making that strengthens confidence between collaborative partners to improve care, reduce costs and create positive experiences for patients.

Our collective future of health care depends on the data

Data is only part of value -based care – this is the node of VBC’s success. Without robust, timely and usable information, even the most well -intentioned initiatives will fail. To exploit AI, improve patient care and succeed in risk -based contracts, organizations must first obtain their data in order. When the right data is in place, the possibilities for transforming American health care from a broken remuneration system develop exponentially.