Collecting ICD-10 data will be an act of faith
It's understandable that physicians are unimpressed by the granular data that will be collected from ICD-10 coding. Documenting so many conditions relating a patient's injury or illness doesn't affect that patient's care. Why bother?
Gregory Berg, associate vice president of research and outcomes at AxisPoint Health, makes the case for data and healthcare analytics without mentioning ICD coding. Each data point leads to predictions of who will need help. Then healthcare becomes about fixing problems before they occur.
You need to have faith that it will pay off down the road. As is much of the health advice that physicians give their patients.
Dike Drummond has these observations of what inadequate documentation will do to physicians after Oct. 1:
- "Your coder will probably bring every single chart back to you for clarification"
- "You will need to go back into the chart to change your documentation in addition to telling your coder what they need to do their job"
- "That double whammy will certainly tear your day to shreds if you don’t get started beefing up your documentation now."
Texas Medical Association President Dr. Tom Garcia has a couple interesting ideas of what will happen after the Oct. 1 ICD-10 deadline:
- Physicians will force patients to pay up front then seek reimbursement from healthcare payers.
- "These people are salivating to get this data, so they can mine this data to determine what is the best way to make money off the relationship between the doctor and the patient."
- Most medical practices have figured out they need to put resources into medical coder training and physician education.
- It's also important to get a handle on data analytics and the technology needed for ICD-10 implementation.
How ICD-10 will affect these key diagnoses:
- Ear infections
This is about allowing ICD-9 and ICD-10 codes to co-exist:
- Which would be technologically disruptive because systems weren't built to handle dual coding.
- Both sets of codes would weaken any statistical or quality analysis efforts.