Delivering effective health care to patients has two sides. Most people think of the clinical side—directly treating patients. The other side is financial—making sure the clinical side has the resources it needs while minimizing waste.
As health care payment models continue to change in the United States, the industry is moving from a classic fee-for-service payment model to one where payments to health care providers are based on groups or populations. This shift requires a large-scale change in how health care is managed both clinically and financially, which is not an easy change for existing provider organizations. The change presents many opportunities to improve patient care as well as financial outcomes. Old management methods need to change, and artificial intelligence is here to help.
In this context, AI doesn’t refer to robots in the surgery center or advanced diagnosis engines; rather, it is the application of machine learning and predictive analytics to clinical operations and financial decision making to better plan both in the future for different populations based on what has happened in the past.
Here are six ways AI is changing population health planning. The reality of the future is that there will be many more uses of AI in health care, including population health.
1. Clinical Risk Identification
The first AI area people think of is clinical risk. Getting people live healthier and get well faster is the goal of every treatment provider. Individual patients are just that: individual medical cases. Grouped together, those individuals become populations that have their own predictable mix of cases, diagnosis, hospitalization needs, and so on.
Using encounter and patient history data the provider already has, AI looks for segments of the population most at risk of needing future treatments. Obviously, that is just the starting point of improving care, but knowing better what the population is going to need facilitates better planning.
2. Predicting Clinical Department Needs
Individual providers cannot be everywhere. AI helps organizations plan where HCPs need to be based on the past history of need. As health care delivery is pushed from large, cost-centralized locations to more distributed, easier-to-access clinics, provider organizations can use AI to plan location specialties, hours, and staffing levels.
3. Treatment Adherence Assistance
After seeing an HCP, the patient needs to do what that provider has prescribed. Lack of adherence to medications, therapies, and lifestyle changes is an enormous contributor to increased cost and unnecessary future encounters. Identifying the characteristics of patients most at risk of nonadherence helps providers design follow-up programs to target those individuals based on the AI models.
4. Monitoring Process Changes
One of AI’s great promises is to point out future problems so that people can take actions to avoid those future problems. The very act of taking action based on predictive information changes future outcomes in an unpredictable way.
Seeing how improvements made to clinical processes and operations change future outcomes relative to predictions is a great use of AI. It enables organizations to place a monetary value on their improvement initiatives by providing a null case—that is, saying what would likely have happened had no action been taken.
5. Reducing Costs
Organizations need to avoid costly outcomes. Improving clinical effectiveness is the main way, but better planning for staffing, locations, facilities, and other indirect costs matters greatly. AI gives organization visibility into cost factors not possible with classic spreadsheet analysis. Knowing what contributes to cost is the first step in finding ways to reduce cost.
6. Budgeting and Forecast Assistance
AI helps organizations better predict costs at a granular level, and then roll them up into budgets and planning. Right now, most organizations use distributed spreadsheets brought together during meetings and over several weeks or months. All those conversations are costly. AI provides a centralized, single point of financial projections that all people and departments can work from to plan.
Date: April 16, 2019
Source: IT Toolbox