Optimizing Display of Blood Pressure Data to Support Clinical Decision Making

点击翻译按钮获取中文摘要

 DESCRIPTION (provided by applicant): Seventy-eight million US adults have diagnosed hypertension, and nearly half of them have uncontrolled blood pressure. Physicians understand the risks of uncontrolled hypertension, and there are multiple drug classes available to treat the problem. Nevertheless, we struggle to appropriately control hypertension in diagnosed patients. One reason is that although the blood pressure measured in the ambulatory clinic is a known number, there is often a question of the adequacy of this measurement for determining treatment. Home blood pressure monitoring by the patient is often proposed as a means to address this problem and to better define the patient's blood pressure range outside the clinical setting. These home measurements bring yet more data to the question, without adding clarity to its answer. This lack of clarity may contribute to the phenomenon of clinical inertia, the delay of treatment intensification despite data, which support an increase in therapy. Lastly, treatment planning frequently involves negotiation between patient and physician. Successful negotiations of this nature are predicated on a shared understanding of control. We propose that improved graphic display of blood pressure data during the clinic visit will help physicians and patients better understand the scope of the patient's blood pressure problem and assist them in reaching a shared decision about the need for potential treatment or treatment modification. Therefore, we propose to address the important issue of blood pressure data display to satisfy the information needs of the physician and ambulatory patient at the point of care, which is one key facet of identifying and managing hypertension. We seek to understand how graphic displays of blood pressure are perceived by physicians and patients, and whether the form of the display influences perceptions and outcomes. We will also investigate what information should be included in these graphs, including both the amount and type of data (clinic blood pressure, home blood pressure, medications, and data summaries). Based on physician and patient input, in conjunction with usability and design principles, we will iteratively refine and then formally tst candidate displays. Finally, we will seek to understand how graphic presentation of blood pressure data influences shared decision making in patient visits with their physicians, including an investigation of shared perceptions of control, and of clinical outcomes.