Some chiropractors may chose the wrong Key Performance Indicators (KPI) to measure the success of their clinics. Among the most frequently used metrics are charge growth, payment growth, patient visit growth, pay per visit, referrals per patient, no-shows, no future appointments, in addition to patient loyalty, and service quality. With this many options to choose from, the question begs just how do you select the right KPI?
But first let’s take a look at how not to measure success for your clinic.
Two of the most frequent business mistakes made by chiropractic clinic owners and managers when selecting a KPI:
- Measurement of the wrong thing
- Focus on the right things but in the wrong order
If you make such mistakes, the statistic you rely on to assess your office performance is disconnected from your overall objective. Consequently, your strategic and resource allocation decisions may not support your goal, driving poor decisions and undermining performance.
To determine cause and effect productively, always start with two key questions:
- What’s your objective?
- What factors help you achieve that objective?
If your objective is to increase value per visit, then you know that higher charges may result in higher payments. What procedures can you deliver to maximize your charges? What Point of Sale items can you offer your patients? How much added revenue can you expect from Point of Sale items?
If, on the other hand, your objective is to increase the number of visits, then you know that having more new patients will result in more visits. What can you do to increase your exposure to referring doctors and to get your patients to make patient referrals? Can you help organize and participate in community events? Can you stay in touch with your patients via email or use a patient portal? What can you do to instill a sense of expertise and office teamwork in the eyes of your patients?
Next, to determine the right metrics, we need to understand the cause-and-effect relationships between your objective and possible actions. If your objective is to improve patient satisfaction you need to understand its sources. If you do not understand what improves patient satisfaction, how can you decide what you need to measure? Intuitively, we rush to explain things, to find an easy cause-and-effect link in every situation. So our intuition makes it too easy for us to assign and measure the wrong cause to an outcome.
To be a useful and reliable link between cause and effect, our statistics need to be both persistent and predictive. Persistency means that an outcome of an action is independent of its timing. Predictability means that the value of the cause predicts the value of the effect.
Statisticians use the coefficient of correlation to quantify persistence and predictability: the closer the coefficient is to 1 or -1, the more persistent and predictive the link is. The closer the coefficient is to zero, the less related the two parameters are.