Happy Anniversary to Wait Time & Delayed Care

They say that 3 months is some sort of watershed point for you're blog. Well today is the 3-month mark. 96 posts later I've gone from a rank of 8 billion, to about 200,000 and so far going strong. I'm not sure if this is having any impact on wait times but it's fun fighting the fight. Thanks to everyone that's reading the blog.

Ambulance Delays Continue

If you live in London, Ontario your 911 call may go unattended by ambulance because they've been drafted by the local emergency department. In a follow-up to my previous post about 911 wait times here's an article where the head of EMS reports 19/19 ambulances have been waiting in the ED to transfer patients. As I said before, there's no winner in this situation. The patient, the ED and the ambulance service are all in a bad place. Legislation needs to be passed to protect the hospital and let them accept patients without fear of litigation or persecution from their regulatory colleges. In the mean time, London needs to staff the ED with ambulance attendents.

The Value of an Administrative Manager

Two years ago our clinic made the leap of faith to hire an administrative manager. We are a group with 10 doctors, 50 staff and 4 sites. We have a General Manager but were finding that the duties of the GM were too large to keep tight control of the schedule. We decided to hire an administrative coordinator whose job it was to enforce the booking policies of the office (among other duties) by coordinating all administrative personnel and reporting to the GM.

What difference did it make? Take a look at the graph below:





In our case, the coordinator started in 2006. There is an immediate increase in the number of appointments. When we compare 2004/2005 to 2006/2007 the normal variation (controlling for season, surgeon and office) is about 3%. In the later two years (2006/2007) there is a 5% jump in the number of appointments, or 2% above the natural variation.



The value of the administrative coordinator is dependant on the size of the clinic. Assuming that more appointments will equate to greater revenue (and improved patient satisfaction by lowering health care & office wait times) a value can be assigned to the administrative coordinator. Divide the gross revenue by the number of appointments in a year. This will give an average value per appointment. Multiple the total appointments by the expected increase (2% if you're running lean already, 5% if not). Finally multiple the average revenue per appointment by the expected increase in appointments.



For instance, a clinic with 5,000,000 in gross revenue had 26,000 appointments in a given year. This equates to $192 average per appointment and an expected gain (at 2%) of 520 appointments. The increase in revenue is $100,000 which will not only pay for the position but lower office wait times and increase patient satisfaction.

Korner Wait Times

I had a request to define Korner Wait Times. Someone from the NHS in England may be better able to clarify this but it seems to be a definition of the amount of wait. In our practice we define wait as the current date to the time there is a day with two openings for a certain type of appointment. This seems to correlate well with the mean (and median) wait time for populations with a normal distribution.

The NHS uses "Korner Wait Times" defined as

"The monitoring of these targets is based on the number of patients waiting as defined by the “Körner wait” in the NHS Data Manual.

For inpatient and day case waiters this definition includes only those patients waiting on the live waiting list. This excludes those patients waiting on a planned list (typically where patients are waiting for admission as part of a planned care programme) and patients who are suspended from the waiting list (typically where their general health prevents them from being operable or where they are not available for admission due to holidays, etc.)

For outpatient waiters the reported number of patients includes only those patients who are waiting for their first outpatient appointment following a referral from a GP or a General Dental Practitioner (GDP). This excludes patients who are waiting for an outpatient follow-up appointment and appointments resulting in a referral from a hospital consultant (e.g. an appointment to a fracture clinic). "

A word of caution here -- the Korner wait starts at the time of referral. Referrals can be delayed (declined or discouraged) which will artificially lower the wait. Also, not all wait time populations follow a normal distribution. We frequently see a binodal distribution where a class of patients has an "urgent" subset that gets in quicker.

Richness and Reach Redux – Web 2.0 + Medicine

After posting on Richness and Reach I made the mistake of submitting the article to Grand Rounds at the Health Business Blog. I didn’t realize that David was a former Boston Consulting Group member and would run circles around my argument.

In short, people want you to believe that when your doctor (or primary care provider) embraces Web 2.0 (the socialization of the internet) a metamorphosis of medicine will occur. The argument goes that the internet will allow you’re doctor to reach more people with greater richness then ever before. Don’t believe them – it’s bullshit.

Technology and the internet have done a lot for primary care. I believe its improved outcomes, standards and the velocity at which primary care is provided. But the internet has done this in the traditional Web 1.0 way by increasing the resources at both the provider and patients’ disposal. Going away are the days of photocopied, index articles’ (that any doctor who graduated before 2000 likely has), hunting for x-rays, the latest textbook and lab coats full of plasticized cards and handbooks. They are being slowly replaced by information over the web. Even the much touted on-line personal health record (read more at KevinMD or Health Management Rx) is just another application of the Web 1.0 as a repository for you’re life’s medical history.

The pundits are trying to set up a scenario where there will be some sort of revolution that will never come. A world where you can input you’re symptoms in a database, or bounce thoughts off your doctor through a chat room, or go for a virtual CT scan. Check out the science roll for the top ten ways to apply Web 2.0 to your life or you can learn to do your own cervicofascial advancement flap. The problem is that satisfaction with one’s primary care physician is highly dependant on communication and the perception of respect. The relationship between you and your doctor is independent, fraught with variation from patient to patient and intensely personal. There is fantastic evidence that a good history is not created by just asking the correct questions but by doing so in an appropriate manner. That includes allowing time, overcoming language barriers, laughter, and empathy for the patient as well as structure to the information exchange. The effect of Web 2.0, however, is to broaden and generalize the human experience. Where a good historian creates a quick personal connection with the patient Web 2.0 relies on group think. The two are at odds with one another.

Aside from the philosophical debate, there is the question of finances. When patients arrive they expect answers and are paying dearly to have us find them. Even when histories are directed they can drag on. To exchange information in a haphazard way is not only foolhardy but it takes time. And in a world of skyrocketing costs, litigation conscious patients and physicians who are increasingly bankrupt of time the likelihood of adding a tool that slows and generalizes the process is remote. I’ve said it repeatedly about IT roll-outs in the clinic. A new process should improve quality and velocity. If it only does one or the other it’s an uphill battle. If it does neither, it’s doomed.

I have no idea if the blogosphere and the Web 2.0 are just this generation’s versions of public access television but I like to think it improves us by giving a broader perspective. A good doctor will make use of Web 2.0 as a tool for education, a means to bench mark their practices and a way to communicate with groups of patients or other clinicians. But make no mistake about it, the internet acting as a library of information is very different than it acting as a surrogate for access to your physician. When it’s all said and done there are certain fundamental laws to health care the greatest of which is that a good diagnosis is made by a great history and a good examination. And that can’t be done through a web-site.

Over to you David & Jen.

Grand Rounds

Grand Rounds is up today at the Health Business Blog at this link. Thanks to David for putting it all together.

Block Booking for Procedural Patients

For ENT, opthomology, oral surgery and other specialists whose practice are dependent on scheduling procedures here is a suggestion for block booking. I've previously posted on why block booking controls health care and surgical wait times and how it improves satisfaction. For more detailed infomration click here. Our practice is largely determined by the load of 3 or 4 different types of procedures. The patients are seen once prior to the procedure for 15-30minutes. The procedure is then scheduled for 15-60 minutes and 10-15% of them require a 15minute post-operative visit.

The first part of the equation is the easiest to solve – how many procedures should be booked in a single day. This may be dependent on wait time, resources or populational need. Or you may simply want to maximize one type of procedure

Determining the Number of Procedures

First specifically define the procedure type. To calculate the wait time for that procedure, count the number of people in the schedule going forward and dived by the number completed per day. Fifty people in the schedule divided by 5 per day equals a 10 day wait. You can adjust the number of procedures per day based on this.

Population need is difficult to calculate but we’ve found it to be a surprisingly static figure. Calculate the number of procedures completed per 10,000 people per year. For instance the need for dental implants in the US is about 40/10,000 per year. From this you can calculate the number of procedures per year assuming you’re the only specialist in a community. On a smaller scale, calculate the number of procedures completed per year for a community, the size of the community and the clinics “market share” of patients seen.

Finally, when there is greater need than resources and you need to maximize the number of procedures in a day its’ a bit of a balancing act. Start with the procedures using all of the available time then back-track the number of consultations and other visits that would be required (see below for details on this). Finally start backing down on the number of procedures until the total time used with consults, procedures and other visits fills the total time available.

Determining the Number of Consultations:

I have friends that book 1 day/ afternoon for consultations and the rest for procedures but there’s not a lot of logic to it. Either they see too few consults and the days open up or too many and the wait list becomes excessively long. I’d suggest an agreeable wait time be determined between the consult and the procedure. Depending on how involved the procedure is 2-3 weeks will fill the day and give people enough time to arrange for time off work. Next, look back at you’re schedule to determine the number of people that actually follow-through with recommended treatment. This could vary greatly depending on the procedure needed but I’ve seen it range from 55-95%. Let’s assume that 85% of people follow though from the consultation. If you can complete 5 procedures per day then you need to see 5 divided by 0.85 = 5.8 per day (29 per 5 days).

Follow-Up

Finally calculate how many people return for follow-up and include that in the calculations as well in the same way consultation time was determined. For this example let’s assume that 12% of patients need a follow-up or 25 x 0.12 = 3 follow-up appointments

Putting it All Together

Last but not least add up all the time required and see if it still fits in the schedule.

Procedures: 60 min
Consultation: 15 min
Follow Up: 15 min

Based on 25 procedures per week
Procedures: 25 x 60 = 1500 min
Consultations 29 x 15min = 435 min
Follow-Up 3 x 15 min = 45 min

So the total time requirement is 1500 + 435 + 45 minutes =1980 min = 33 hours per week

When you do these calculations for multiple procedures you can add or steal time from one procedure or another to balance the amount of wait from the time of referral to the time of procedure.

What's Happening with Chemotherapy?

Cancer care has been designated as a priority program across Canada and cancer care wait times for radiation and surgery have dropped because of increased resources. But according to a recent press release despite more than doubling the budget for systemic treatment (chemo) since 2003 wait times haven't changed. I'm not exactly sure why this is happening as they don't seem to have posted the report on-line at Cancer Care Ontario but the press release states that the lack of change is due to increased use of the system (more people receive multiple doses of chemo) and a lack of medical oncologists. I'd like to read more about this because doubling the budget should have some effect on the wait time?

How to Create a Pivot Table

The most powerful tool in Excel is the Pivot Table. They summarize data from a list of columns or from a database and are an easy way to create a digital dashboard. In case you've never created a Pivot Table before here is a quick video about how to do it. I'll post some other examples later about summarizing date's and data further but the following video is a good starting point if you're new to the idea.

Leveling a Process – Eat My Words

It’s time to eat my words. I finally got my hands on a process simulator to test out a hypothesis that decreasing the variation in a process has a more profound effect than decrease the average length a process takes to decrease office wait times

I used the data that I’d previous posted on how to create a process map and pumped in the numbers about waiting in the doctors office. The mean time of a process is the average of how long it took to complete a single task (e.g. the average exam was 12 minutes) and the standard deviation was the amount of variation in the time (for the math majors out there it’s a normal distribution). So the average exam by a doctor took 12 +/- 6 minutes. I then plugged the following numbers into the simulator:

Registration 3 +/- 2 minutes
Medical History Review with Nurse 11 +/- 5 minutes
Consultation with Doctor 12 +/- 6 minutes
Check Out (book next appt) 7 +/- 3 minutes

The front desk completed the first and last tasks and the bottle neck is the doctor.

The results showed that the doctor was utilized 100% of the time with the front desk and nurse being idle about 50% of the time and 30 patients could be seen in two 3.5 hour sessions (7 hour day).

If the average time each task took was decreased by 20% then you could see 13% more patients
If the average variation (standard deviation) was decreased by 20% then you could see 7% more patients.
If you decreased both average and standard deviation then you could see 20% more patients.

The variation only accounts for 1/3rd of the ability to see more patients and the average time is closer to 2/3rds. The end result is I have to eat my words that variation is more important than mean when calculating office wait times. But if you’re looking to improve a process it goes to show that decreasing the variation in the time a process takes is [almost] as important as decrease the average time it takes.