We were recently asked to summarize our thoughts on the shortcomings of
ICD9 and billing data when used for diagnoses in clinical quality management systems. I thought I'd share our summary….
Specificity -
ICD9, for many diagnoses, does not provide the required level of specificity required for evidence-based care guidelines. An example is asthma.
ICD9 cannot differentiate between persistent asthma and intermittent asthma, an important distinction.
Scope – literature has documented that
ICD9 can accurately represent approximately 50% of the conditions a primary care provider will encounter. When a condition cannot be properly documented, a provider must choose the “best fit”. This can be a major problem for clinical research and also affects the use of this data for care guidelines.
Accuracy – the needs of documentation for reimbursement leads to incorrect problem documentation. A common example is the need to document a diagnosis of asthma for a patient presenting with wheezing. If the patient is ultimately not asthmatic (which is usually the case), there is no way to “go back” and change their diagnosis on the billing data record. Therefore, when that billing data file is used in a registry, it inaccurately represents the asthmatic patient population. This inaccuracy can exceed 50%.
Completeness - Billing data does not document lifestyle issues like smoking and cannot capture clinical modifiers such as family history and risk factors. These elements are important for care guidelines and can be important data elements for clinical research.
We believe that these shortcomings are solved through the use of
ICPC, the International Classification of Primary Care and through the use of
clinician-verified diagnoses. A few prior blog entries talk about this and we'll be talking a fair bit more about it in the months ahead.
Dave Morin
CEO and Co-Founder
Cielo MedSolutions LLCLabels: Billing Data, clinical groupware, clinical quality management system, coding, ICPC, patient registry
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