By Sue Altman
Data mining is an important tool used to measure the call center’s value as an information hub. How much more valuable can your call center be to your organization’s marketing and physician relations departments and the physicians you serve?
Let’s start with the obvious, analysis of consumer preferences. You may think of these attributes as “search criteria,” but in reality they are much more. The good news is that you already capture terrific data callers. They choose:
- Preferred location – usually by zip code of work or home
- Insurance accepted
These elements are fairly straight-forward. So if we take our minds off the “match” process (what the staff are focused on during a call or Internet request), the information can then be seen as “consumer demand” information. You probably have a report that gives you these statistics, but is it in a format that other departments can use for decision-making?
If you don’t use them already, a zero match or partial match report is invaluable. What expectations could not be fulfilled or were only partially met? What percent of the time did the agent ask the caller to “settle” for a second best match? This is great information for physician recruitment personnel. The call center cannot only support the category of need (what specialty), it can also quantify demand. You have the information to state, “If we have a female OBGYN in the Monte Vista area, we could send her 12 new patients per week.” This makes your information actionable. Get it to someone that can use it.
When generating this information, use your software to define “location” in a more meaningful way than zip code. Most software products have a “service area” field that is underused. Group geocodes, zip codes, and school districts, labeling them with the terms that your callers use. This is far more useful than a zip code.
What can you tell physicians about appointment wait times? Your staff has a gut feeling regarding how long people will wait for first available appointment; a day or a few for primary care, weeks for a specialist, and so forth. Although we cringe when we have to say, “They are scheduling about three months out,” this information states an important case that your physicians, physician relations, and senior team need to know. Customers will seek other options – which may mean other health systems.
How do you quantify it? Use your “first available appointment” field (or a user defined field, if your software is lacking). The “wait time” report will subtract the first available appointment date (for that specific practice being contacted) from the date of the appointment request. Data mining enters the picture when you run this report by individual practice and by specialty. Analysis will show whether this is a practice that doesn’t need new patients (and perhaps shouldn’t be on your referral list) or whether there is a real need for additional options within that specialty. Again, don’t keep this information secret. Getting it into the right hands, in a format that clearly identifies the need, is a valuable service that the call center can offer.
This information can also be used to diffuse physician complaints. For instance, say that Dr. Smith thinks she does not get as many patients from the call center as Dr. Jones. If that’s true, you can produce the report that shows her first available appointment (three weeks) versus that of Dr. Jones (one week). This gives Dr. Smith a choice, manage her schedule to accommodate new patients, or continue to see that, given the choice, consumers choose to be seen in a more timely manner.
Saint Anthony Medical Center in St. Louis, MO recently re-positioned its call center in just this way. The re-introduction letter to physicians explained that the priority of referrals will be based upon
- Caller preferences
- First availability of appointments (‘same day’ given preference; then short wait; then longer wait)
- Timeliness and helpfulness of response from office
This seems so simple, it is almost a given. For Saint Anthony Medical Center, it was an important message to shift perceptions of the call center’s role. They are going to be customer-centric. Practices that align with this strategy will be given priority; those that don’t will experience less new business.
This last topic should become a standard practice in your call center. “How heard,” or “lead source,” is a fundamental tool for tying call volume to specific marketing activities. Your staff may see this as a nuisance to track, but it’s essential data for your marketing managers. Few of their responsibilities have a definable return on investment. The call center is perhaps the most concrete vehicle for proving cause and effect. The best practices in this area go further than identifying “newspaper,” “yellow pages,” or “friend/family.” Build your tables to allow a drill down. Which newspaper? What article? This information, when paired with revenue reconciliation, allows a marketing executive to know the $1,500 ad placement for the new Endocrinologist resulted in 92 calls and 51 new patients through the diabetes center.
The analyses described above can be accomplished with a few brain-storming sessions. Consider inviting physician relations and marketing to participate. Be prepared to talk through call scenarios and what data you capture to get everyone on the same page. Contemplate the information that would be useful and what data must be pulled into accomplish it. As a last step, play with the report design and trial it with the audience that would benefit most.
[From the June/July 2006 issue of AnswerStat magazine]