C-C4-04: Development of a Measure Set for Routine, Comprehensive, Automated Assessment of Obesity Care Quality

Background We have developed a technology platform for scalable and routine measurement of care quality using comprehensive electronic medical record (EMR) data, including providers’ free-text notes documenting clinical encounters, and are applying this technology to assess the care delivered to obese and overweight patients in two distinct health systems. NHLBI’s evidence-based clinical guidelines for overweight and obesity provide a clear set of patient care procedures for the primary care setting. Using these treatment guidelines, we have developed a set of measures for automated assessment of obesity care quality using EMRs. Methods Development started with an iterative process to identify key quality measures for obesity care. This process was guided by project aims to (1) target primary care, (2) ensure scalable application of the measure set to multiple health systems and EMR implementations, (3) assess feasibility of using natural language processing technology to allow inclusion of information recorded in the free-text notes, and (4) prioritize existing NHLBI efforts to define best clinical practices for obese and overweight patients. Our development process involved a multi-disciplinary team (including data specialists, medical records technicians, clinicians, and obesity treatment experts) reviewing, vetting, and reaching consensus on translating each clinical step in the NHLBI guideline to measurable clinical events documented in the EMR. Results A comprehensive set of process measures have been identified and are in the process of being operationalized for routine automated assessment of obesity care in two distinct health systems caring for diverse patient populations. These measures provide capacity to assess actual care practices for their adherence to recommendations that patients (a) be assessed both for weight and waist circumference as well as for readiness to lose weight, (b) be advised to lose weight if they are overweight or obese, (c) be assisted with goal-setting and plans for diet and exercise activities, and (d) receive follow-up from their primary care clinicians regarding these activities. Conclusions For health information technology to impact obesity care, EMR-based automated quality measures must be subjected to a repeatable and rigorous process of refinement, revision, and validation.