Sean offers some good points here and specially how the transfer and incorporation of data is not yet a perfect world. The good side of this is that we have found data bases all around healthcare that offer information that can be added to a personal health record, so stop and think a second, would you rather be a proof reader or have to sit down and write the novel yourself? I make that comment from a point of reality, in other words what data are we now able to access.
The medication records we get from Pharmacy Benefit Managers have been the result of tapping in to data bases originally created for marketing and selling drugs for the most part. When you think of what is available and sometimes even a 10 year trail appearing, that is not bad. Remember insurance companies tap into those too to qualify individuals for insurance coverage.
The touchy part comes down to the coding and as we have seen in the last few days, there’s a bit of work to be done here. We all remember perhaps an occasion to where a physician coded our visit as a problem as insurance companies at one time did not pay for physical exams, thus we ended up with a code in the record showing we came in for treatment for an illness or condition, again to get the bill paid. There’s a lot of this out there and the interesting part now is that as a consumer, it is open for you to view and if necessary, get it corrected. This is part of what Sean refers to as “dirty data”, and again it’s all over the place. It was not the bad patient or bad doctor at the root, just folks trying to get paid and now that we have the data, we go back to the origins to see where we all really stand here with insurance business models that did not revolve around better healthcare and prevention.
Insurance companies like PHRs and offer many themselves as they want you to see what is in file, with the age of transparency we live in today, but they are also placing the burden of proof on the patient to correct such items in doing so. Now that may be one big daunting task to go through and get items corrected and as a patient you will have resistance from the analytical sources at the insurance end to actually have to “prove” what occurred and can mean contacting doctors for letters, hospital, the same thing.
Again, this goes back to business models of health insurance here, healthcare even way back was not a focus, risk management and data ruled, so there will be a lot of this forthcoming and as a patient, it may not be easy. The next step here too in the MIB, the Medical Insurance Bureau, who has files on many of us whereby insurance companies have shared records for years. You may want to get your file and see what has been documented and put in file there too. Again, we are now speaking of potential “dirty data” once more. You can read here to see one woman and what she has gone through.
It is great now that these data sources of information are becoming available and in the course we will see many eye openers. The folks with the PHRs, Google and Microsoft Health Vault are making the effort to add alerts and truly create tools we can use, so in essence they didn’t create the “dirty data”, but can work with us to help get a true personal health record in place.
As mentioned, the mapping of such data to include can also help, in other words, where’s the actual text and not a code entered to secure payment. There are a lot of smart people in Health IT that are going to work to correct this, but again, remember it’s been many years in the making, so there is valuable data there for us to use, but getting the dirt out is the issue.
None of this data has been transparent until now, but has been in the files of many organizations that use it to make “business intelligence” type of decisions, thus me having an inquiring mind, I want to know. The 2 links below show some legal ramifications being challenged with how some of the data has been used, good reading and something to be aware of. The second link has information about the MIB, with a video that will explain how this portion of the healthcare data chain works.
Health Insurance Underwriting procedures – Data Mining to Cherry Pick and some are listed on the Web
Just yesterday I made a post about a potential hospital error and the the great length the doctor took to ensure it was not on his insurance records.
It’s also very easy to get confused with marketing as this PHR is ready to offer you insurance for your PHR, and maybe down the road it might have value but for right now, let’s get something accurate in place and worth insuring. We also need to educate ourselves better on healthcare so we can stamp out “Magpie Healthcare” too. When you begin developing your PHR, the education process will begin.
On good thing is that we can be assured of from today forward, is that accurate and needed information will be added for the most part if we take an active role here. Think of your PHR as your “back up” if you will, when perhaps there is nothing else available and it could stand to save your life too.
Long and short of all of this, I think it’s best to work with the PHR companies so we can find out what’s out there, and what records companies and health institutions have filed, so we can get an accurate accounting and have a true PHR without all the “dirty data” included. So let’s not blame the PHR folks for their efforts on bringing this information and transparency to us, but rather focus on the value of the information and in cases where it is erroneous, get things fixed and as mentioned the Health IT folks want to see this work as well and are doing their part to make it better. I too agree that we need patients like e-patient Dave to inquire and test the water, otherwise we can’t locate and repair some of the shortcomings and below you can see some of the solutions HealthVault has in place and working. BD
The folks at Google Health have been taking it on the chin this week, after the Boston Globe ran an article about a super-engaged patient named Dave who found a number of pretty nasty surprises when he imported his health information from Beth Israel into Google. From what I have read there were really three key issues at play:
Yes, there is great learning here as to what can be done better --- Dr. Halamka has already posted about steps they're taking at BIDMC to make things better (as an aside, how many other medical institutions out there display this kind of transparency? Kudos are deserved here.). But the reality is, there is a bunch of dirty data out there in the world, and it is being used not just for billing but to make clinical decisions. Providing transparency and letting people see the mess inside --- that is the first real step to getting it fixed.
The user then has another choice - they can "reconcile" the package by looking at the individual items and choosing which ones should be extracted into their record. Only those items that the user chooses to copy out become part of their canonical list of conditions, allergies, medications, and so forth. There are a few really nice things about this approach:
- Users have a well-defined place to make decisions about what elements they want to accept and which they believe are wrong. Right now our "reconciliation" process is pretty manual, but as we go forward we expect to do smarter things. One great idea that William Crawford put forth was --- in an interface like this, call out conditions that are associated with billing codes with a special warning icon --- to suggest that the user may want to take a closer look at these.
- It puts a fence around the "dirty data" problem so that users can benefit from all sources without worrying that their records are going to become polluted with errors.
- It turns out that retaining both the individual items and the package can be really useful - for some use cases the package itself is what a recipient really wants. For example, a referring doctor that wants to see the results of a surgery at NYP probably wants the digitally-signed CCR from that visit, not the user's all-up history.