The Challenge of Evaluating Pain Relief Efficacy
Let’s face it, most people dealing with Chronic Pain take some type of pain relief medication – often multiple types. But do you know if they are really working? And when your doctor suggests trying a new medication to see if it is more effective than your current drug – how can you tell?
Unfortunately, most of the time you can’t objectively say whether one drug is working better than another, or even if either of the drugs is having a real impact on your pain levels. To get truly subjective data on the matter generally requires a laboratory like environment with rigorous data collection processes to ensure that medication intake and pain relief impact is captured on a regular basis. This is just not a realistic situation for most chronic pain folks.
Capturing the Data
However, using the latest analytical tools within Chronic Pain Tracker, you CAN document and analyze this type of data. You and your doctor can now see the statistics describing the reality of your medication and pain interaction over the past month(s), so that you can both make better informed decisions about how to best treat your condition. How does this work? Well, let’s take a look…
When we want to look at medication effectiveness, there are two main sets of data we need to capture:
- Medication History – what was taken, how much was taken, and when was it taken
- Pain Intensity – how badly are you hurting and when
Both of these data sets are easily recorded using Chronic Pain Tracker. Users are able to create their own customized lists of medications being taken which can record the name, dosage, and date/time of the med being taken. Similarly, recording a current pain level is as easy as selecting from the visual pain indicator scale.
Medication Analysis Window
Another important factor that needs to be considered is the time frame over which the drug is supposed to be effective. For example, many breakthrough pain meds should start to work within about 30 min and last 4-6 hours. Other types of meds may be effective for up to 12 or even 24 hours. And, if you’re dealing with something like a Fentanyl Patch, it may be several days that you need to evaluate.
You can now specify this effectiveness window period (hours) within the definition of your medication in CPT. You simply enter the number of hours over which you want to analyze the drug’s effectiveness. This value can vary for each medication entry and can be adjusted at any time. The screen image to the right shows the location of this field.
Now, considering the timeframe, it will be important to track your pain levels at the start of taking the medication and then several times over the course of the analysis window period. For example, let’s say that it is 1:00PM and you have just taken a Vicodin. So you create a Diary Entry that records the taking of 1 Vicodin pill and your current pain level (eg. 7). if the analysis window for the drug is 8 hours, then you should plan on creating additional Diary Entries at perhaps 1, 2, 4, 6, and 8 hours after the initial entry where the medication was recorded. There are no hard and fast rules on how many data points you need to capture each time, but its better to err on the side of too much data rather than too little.
The Summary Report Analysis
The magic of the process begins to happen when you run a Summary Report for a particular time period. Let’s say you’ve been testing out Vicodin for the last month and want to get an idea of how it has been working for you. So after following the steps above throughout the month, you’re now ready to produce the Summary Report to review with your doctor.
Before explaining what goes on behind the scenes, let’s jump straight to the end result – the Pain Reduction Efficacy graph shown in the Medication Tracker section of the report. You can see a sample of this report on the left. In a normal Summary Report, you would see one of these graphs for each medication listed. This one happens to be a sample for Vicodin 10mg over a 14 day period.
The graph is structured with Time (hours) as its x-axis. The Time represented is the time since the particular medication was taken. So you can see that it starts with 0 hours on the left and goes up to whatever number you plugged into for the Analysis Window – in this case 6 hours.
The vertical axis represents that relative increase/decrease of pain levels over the time period. Each time you take the medication and provide a starting pain level, the app will look for additional Diary Entries that fall within the analysis window timeframe and will check whether your pain level went up or down compared to the starting pain level. This is represented as a percentage value on the vertical axis. The actual data points are shown as the color diamonds on the chart. A green diamond is one where the pain level dropped from the starting point, a yellow represents no change in pain level, and a red shows an increased pain level since taking the medication.
The individual data points are connected by thin gray lines which are shown as a way to see the progression of pain levels for that particular medication cycle. You will also see several diamonds with a thick black border around them. These represent entries where an additional dosage of the same medication was taken. If you start to see clusters of these bordered markers earlier in the analysis window, it may indicate that your medication is wearing off earlier than it should be, and is a good time to raise the question with your doctor.
The thicker blue line shown on the graph is the aggregated pain reduction impact for the medication during the analysis timeframe. This is a great tool for seeing the average effect of the medication on your pain levels. The sample shown illustrates the effect we would expect to see with a medication like Vicodin. After a short period of being digested, the medication begins reducing pain levels over the course of hours 1 to 4. By about hour 5 or 6, pain levels have again returned to their original level and you’re seeing signs that the patient has taken another dose at that point (the bordered diamonds).
Not all of your graphs are going to follow this idealized curve, there are just too many variables that impact the efficacy of your medications. For example, if you pain normally gets worse towards the end of the day, then a medication taken mid-afternoon will probably show more of a steady-state pain level until it starts to wear off and pain levels rise.
Let’s take a look at a couple other samples based on real world data captured from one of our users. In this first graph, we’re looking at the short acting pain reliever Dilaudid with an analysis window set to 8 hours. As mentioned before, we don’t see the idealized curve from the Vicodin sample above, but that doesn’t mean there isn’t valuable information here.
If we look in the area (A) on the plot, we see that around hours 3 to 4 there is a large number of bordered markers which indicate that the patient is taking additional doses at those points. This suggests the relief from the medication is not lasting more than 4 hours for this patient. This is further verified with the area (B) where when the patient did go further into the analysis period without taking more medication, the pain levels began to steadily rise over time.
The next sample has a longer analysis window (12 hours) for the drug Robaxin. Again, we don’t see the idealized curve, but we can draw some valid conclusions from the graph. In area (A), we’re seeing a short-term increase in pain levels. However, there are very few data points within the first 4 hours of the drug being taken, so we may conclude that the increased pain levels are only due to a lack of data points in the area.
Unlike area (A), when we look at area (B), we see lots of data points which should suggest a more representative view of the drug impact on pain levels. In this period we’re seeing a gradual uptick in pain levels starting at about the six or seven hour mark. Given this increase and the quality of the data here, this probably suggests that the drug is working for roughly the first 6 hours for the patient, but not really beyond that point. It also looks like area (C) is demonstrating that the patient is taking more Robaxin at roughly the 10 hour point. Given the findings in area (B), it may make sense to move the next dose a bit closer say at the seven or eight-hour mark.
Again, you shouldn’t rely on a graph alone to make medical decisions. You should always review the graphs along with your other history factors with your doctor before making any medical decisions. However, we believe that the tools in Chronic Pain Tracker, like the Pain Reduction Analysis, can be an invaluable tool for you to use in your continued care. We hope you find these tools beneficial.