Analytics for Accountable Care Organizations
There will be a strong significance of integrated clinical, operational and financial analytics in helping ACOs achieve their objectives. Integrated analytics will provide a clear line-of-sight into inefficient operational areas and their cascade effect on quality of care as well as cost of care. ACOs also need to analyze historical data for various disease progression paths and the cost associated with them. For creating a successful and sustainable ACO, advanced healthcare analytics needs to be leveraged for:
• Value scan to identify operational areas with significant potential for cost savings. By fine-tuning operations, cost of delivering care services can be reduced.
• True clinical accounting to estimate cost of services at the most atomic level is required which can be supported by advanced analytics. Most providers track cost of services at macro -level. In hospitals, cost-benefit tracking is done at department level. There is little visibility into the end to end cost of a particular healthcare service.
• Identifying the inter-dependencies of clinical, operational and financial performance metrics to define optimal cost reduction strategy with no adverse impact on clinical outcomes
• Predicting cost of care for beneficiary patient population. Based on demographic spread, race, ethnicity and existing case mix of chronic patients and seasonal variations, expected cost of care can be predicted.
• Identifying effective interventions for reducing cost of care and improving outcomes. Amongst the numerous case management and disease management programs that ACOs might undertake to reduce healthcare costs, it's important to evaluate which is delivering result and which is not.
• Comparative analysis of performance of participating providers and root cause analysis under-performing metrics is essential to ensure cost and clinical quality targets are met by all the participants of an ACO.
• Quantifying benefits and cost savings from various initiatives to reduce healthcare costs and improve clinical outcomes would require analytics. This is needed for bonus or penalty distribution that is commensurate with the participating provider's performance and their contributions to reducing cost of care and improving clinical outcomes.
• Implementing benefits sharing models would require analytics and business rules implementation
Key Business Intelligence (BI) capabilities required to support the above mentioned information needs of ACO would be statistical modeling, correlation analysis, predictive modeling, problem analysis and "what-if" analysis. ACOs would need an integrated data warehouse and a BI system across participating provider organizations. As there is only 3 years mandate to participate in an ACO, it remains to be seen if participating organizations will be open to making huge investments in advanced BI systems that, in my opinion, are essential for the long-term sustenance of the ACO model.
• Value scan to identify operational areas with significant potential for cost savings. By fine-tuning operations, cost of delivering care services can be reduced.
• True clinical accounting to estimate cost of services at the most atomic level is required which can be supported by advanced analytics. Most providers track cost of services at macro -level. In hospitals, cost-benefit tracking is done at department level. There is little visibility into the end to end cost of a particular healthcare service.
• Identifying the inter-dependencies of clinical, operational and financial performance metrics to define optimal cost reduction strategy with no adverse impact on clinical outcomes
• Predicting cost of care for beneficiary patient population. Based on demographic spread, race, ethnicity and existing case mix of chronic patients and seasonal variations, expected cost of care can be predicted.
• Identifying effective interventions for reducing cost of care and improving outcomes. Amongst the numerous case management and disease management programs that ACOs might undertake to reduce healthcare costs, it's important to evaluate which is delivering result and which is not.
• Comparative analysis of performance of participating providers and root cause analysis under-performing metrics is essential to ensure cost and clinical quality targets are met by all the participants of an ACO.
• Quantifying benefits and cost savings from various initiatives to reduce healthcare costs and improve clinical outcomes would require analytics. This is needed for bonus or penalty distribution that is commensurate with the participating provider's performance and their contributions to reducing cost of care and improving clinical outcomes.
• Implementing benefits sharing models would require analytics and business rules implementation
Key Business Intelligence (BI) capabilities required to support the above mentioned information needs of ACO would be statistical modeling, correlation analysis, predictive modeling, problem analysis and "what-if" analysis. ACOs would need an integrated data warehouse and a BI system across participating provider organizations. As there is only 3 years mandate to participate in an ACO, it remains to be seen if participating organizations will be open to making huge investments in advanced BI systems that, in my opinion, are essential for the long-term sustenance of the ACO model.
