"Welcome to our company blog. Within these blog posts, we hope to share our insights on clinical quality management, the patient-centered medical home, chronic disease management in primary care, evidence-based medicine, and the use of technology in ambulatory care settings."

- David Morin, CEO and Donald Nease Jr., MD, Chief Medical Officer

AHRQ (Agency for Healthcare Research and Quality) recently published a wonderful paper entitled "Health Information Technology for Improving Quality of Care in Primary Care Settings". The paper looks at "the link between health information technology and quality improvement in a range of primary care settings"1. To see the document: http://healthit.ahrq.gov/portal/server.pt/gateway/PTARGS_0_1248_661809_0_0_18/AHRQ_HIT_Primary_Care_July07.pdf. There are many insights and recommendations documented in this piece; if you are looking into technology and best practices to support improving quality of care, it is a must-read. But, there is a specific issue highlighted in the report that "hits home" because we constantly talk about it. Specifically: 1. Page 18 - "another aspect of data structures that continues to restrict improvement activities is the billing and reimbursement coding mindset that permeates much of health care data. For example, in many health IT systems, patients with asthma do not have a diagnosis of asthma; they have a data history of billed visits with a billing diagnosis of asthma. For visits to the clinic that did not involve their asthma (and hence no billing code of asthma was issued), there is no way to relate that visit to their chronic condition of asthma. Additionally, an asthma billing code is often used for a patient who arrives wheezing (whether they have a diagnosis of asthma or not). This may not look like a data problem on the surface, but if you ask the health IT system how many asthmatics are in a panel, the numbers are far from reality." 2. Page 19 - "data structures for billing and documentation are often very different from the data structures that support improvement" 3. Page 13 - "data that are constrained to billing codes may make it very difficult to track the progress of a chronic diagnosis over time" The paper also discusses that it may be difficult to solve this problem - but we think we have solved it through the use of clinician-verified diagnoses built from a thesaurus of coded clinical terms. We do not rely on billing diagnoses; clinicians capture patient diagnoses at the point of care based on the true conditions of a patient and Cielo Clinic stores and utilizes these diagnoses. This capture is a very simple effort and has a very small time impact on a provider. Of course, it is quite simple for our system to take a billing file and use it to pre-populate a patient database with diagnoses; we offer to do this during every Cielo Clinic installation. But, we rarely do diagnoses pre-populations as most practices are not comfortable with these data sets for clinical quality improvement. We feel strongly that a quality program built on billing data will not be successful. Bottom line, billing data serves a different purpose than quality of care data. Billing data was never constructed to support quality of care initiatives. A different data set is needed, period. It needs to be coded, clinician-verified and uncoupled from billing diagnoses. It isn't difficult to build this data set, especially with a tool such as Cielo Clinic, and build it to the benefit of all stakeholders; providers, patients and payors. Dave Morin CEO Cielo MedSolutions 1: Langley J, Beasley C. Health Information Technology for Improving Quality of Care in Primary Care Settings. Prepared by the Institute for Healthcare Improvement for the National Opinion Research Center under contract No. 290-04-0016. AHRQ Publication No. 07-0079-EF. Rockville, MD: Agency for Healthcare Research and Quality. July 2007. Page 1.