OBJECTIVES: To develop an electronic registry of patients with chronic kidney disease (CKD) treated in a nephrology practice in order to provide clinically meaningful measurement and population management to improve rates of blood pressure (BP) control. METHODS: We combined data from multiple electronic sources: the billing system, structured fields in the electronic health record (EHR), and free text physician notes using natural language processing (NLP). We also used point-of-care worksheets to capture clinical rationale. RESULTS: Nephrologist billing accurately identified patients with CKD. Using an algorithm that incorporated multiple BP readings increased the measured rate of control (130/80 mm Hg) from 37.1% to 42.3%. With the addition of NLP to capture BP readings from free text notes, the rate was 52.6%. Data from point-of-care worksheets indicated that in 52% of visits in which patients were identified as not having controlled BP, patients were actually at goal based on BP readings taken at home or on that day in the office. CONCLUSIONS: Building a method for clinically meaningful continuous performance measurement of BP control is possible, but will require data from multiple sources. Electronic measurement systems need to grow to be able to capture and process performance data from patients as well as in real-time from physicians.
OBJECTIVES: To develop an electronic registry of patients with chronic kidney disease (CKD) treated in a nephrology practice in order to provide clinically meaningful measurement and population management to improve rates of blood pressure (BP) control. METHODS: We combined data from multiple electronic sources: the billing system, structured fields in the electronic health record (EHR), and free text physician notes using natural language processing (NLP). We also used point-of-care worksheets to capture clinical rationale. RESULTS: Nephrologist billing accurately identified patients with CKD. Using an algorithm that incorporated multiple BP readings increased the measured rate of control (130/80 mm Hg) from 37.1% to 42.3%. With the addition of NLP to capture BP readings from free text notes, the rate was 52.6%. Data from point-of-care worksheets indicated that in 52% of visits in which patients were identified as not having controlled BP, patients were actually at goal based on BP readings taken at home or on that day in the office. CONCLUSIONS: Building a method for clinically meaningful continuous performance measurement of BP control is possible, but will require data from multiple sources. Electronic measurement systems need to grow to be able to capture and process performance data from patients as well as in real-time from physicians.
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