When AI meets value based care

The saying in clinical documentation goes if you didn't document it , you didn't do it and if you didn't do it, you can't bill for it.

Physicians today face increased pressure to produce more accurate, complete and compliant clinical documentation while simultaneously maintaining their focus on patient care and satisfaction. However, without better clinical documentation processes and technology in place, physicians and hospitals risk receiving inaccurate quality scores and lower reimbursement rates.

CMS continues to advance the level of reimbursement it ties to clinical performance. By 2018, CMS expects to base payment criteria for Medicare value-based purchasing programs wholly on clinical performance according to efficiency of care (25 percent), patient outcomes (25 percent), patient experience (25 percent) and safety (25 percent).

Bundled payment schemes also add another level of analysis, complexity and risk to executing a value based model at a profit. Doing so requires several skill sets, aided by AI, that are not as necessary in a fee for service environment. They are:

1) Compliance with quality standards established by reputable and valid third parties

2) Conversion of patients from potential patients to actual patients along the care pathway and continuum without referral leaks or dropped handoffs.

3) Communication between the surgical team, both internally and externally, referral sources and the patient team

4) Care coordination, particularly with patients who have co-morbid conditions, complications or specific needs, including patient education, engagement and activation before and after a given episode of care within the care continuum.

5) Cost accounting, coding, coverage and pricing that is fair, transparent and accurate. An increasingly important decision is who is responsible for paying for which services during a prescribed episode of care. In addition, more precise coding and documentation needs to be compliant with contract requirements.

6) Continuous value and behavioral improvement based on metrics, analytics and feedback to our care partners.

7) Continuity of care and information which means that surgeons and referral clinicians need to be sure there are adequate pre and post handoff arrangements, particularly for those patients who are traveling away from home for care.

8) Consistency in operations that is difficult given the required hand offs from one department to the next

9) Cash to seed and grow a sustainable business model

10) Caring about patient outcomes and experience above profitability when there are significant financial performance pressures that can place the ethics of medicine in conflict with the ethics or business.

11) Converting data to actionable information using analytics

12) A repeatable and scalable business model canvas

Consequently, AI offers the opportunity to provide data driven decisions about :

1. Care coordination
2. Risk stratification
3. Identifying and focusing on patient centric team needs
4. Managing risk
5. Pricing risk
6. Cost accounting specific episodes of care
7. Quality standards, compliance and stratification
8. Pricing a specific episode of care
9. Optimizing profit margins for a specific surgical procedure or other intervention where there are gross geographic disparities in quality and costs, when patients and payers are willing to travel for value
10. Meticulous documentation and coding

More data collection (from both patients and their telehealth practices) and more sharing of information (because of value-based health care) mean that there’s more information to sort through on a daily basis. More, in many cases, than humans could possibly review in their lifetime.

To help handle, sort, and utilize all this data, health centers are turning to artificial intelligence (AI) in droves, with 35 percent of health care institutions hoping to leverage AI within two years and 50 percent within the next five years. AI has already been adapted for health care in areas such as predictive analysis, population health management, clinical decision-making, and many other trend- or analytics-based solutions, and money spent on the technology is expected to reach nearly $8 billion by 2020.

AI has become the "Intel inside" of most value based care transactions. For most doctors, the less data and the more actionable information at the point of care we see, the better.

Arlen Meyers, MD, MBA is the President and CEO of the Society of Physician Entrepreneurs and Chief Medical Officer for Bridge Health and Cliexa