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Health care has been transformed by computerization, and the use of electronic health record systems has become widespread. Anesthesia information management systems are commonly used in the operating room to maintain records of anesthetic care delivery. The perioperative environment and the practice of anesthesia generate a large volume of data that may be reused to support clinical decision-making, research, and process improvement. Anesthesiologists trained in clinical informatics, referred to as informaticists or informaticians, may help implement and optimize anesthesia information management systems. They may also participate in clinical research, management of information systems, and quality improvement in the operating room or throughout a health care system. Here, we describe the specialty of clinical informatics, how anesthesiologists may obtain training in clinical informatics, and the considerations particular to the subspecialty of anesthesia informatics. Management of perioperative information systems, implementation of computerized clinical decision support systems in the perioperative environment, the role of virtual visits and remote monitoring, perioperative informatics research, perioperative process improvement, leadership, and change management are described from the perspective of the anesthesiologist-informaticist.

OBJECTIVES/SPECIFIC AIMS: I would like to make clinicians aware about prescription opioid use and glycemic control among patients with diabetes. This is a quality of care issue that increases the disease burden for two conditions opioid dependence and diabetic complications. Big data analytics can bring out this quality of care issue and help in changing clinical practice through precision medicine METHODS/STUDY POPULATION: This is a population health study of patients on prescription opioid pain medications in Erie county medical center and local out patient clinic. The electronic data from the hospital records and Outpatient were collected, merged and de identified. The database was saved in a protected environment and made accessible to researchers through a secure login. The data was queried for the number of patients with diabetes. The glycohemoglobin levels were collected and then the analysis was made RESULTS/ANTICIPATED RESULTS: It was found that only 63 of the 89 patients with DPN and 156 of the 570 patients without DPN had any measurement of HbA1c in our data. It was found that 86 out of 156 patients without DPN had suboptimal glycemic control with a glycohemoglobin level > 7% while 36 out of 63 patients with DPN had a glycohemoglobin > 6.7%. The odds of patients with DPN having poor glycemic control is 0.57 while the odds of having poor glycemic control without DPN is.55. The relative risk being 1.03. DISCUSSION/SIGNIFICANCE OF IMPACT: Our population study revealed suboptimal glycemic control among a large set of patients in Western New York with a diagnosis of diabetes mellitus and a concurrent prescription for an opioid pain medication. A significant percentage of patients in our study population with a diagnosis of DPN might benefit in terms of decreased painful symptoms of neuropathy from monitoring and attempting to improve glycemic control. Additionally, in our patient population, there were no patients with diabetic peripheral neuropathy prescribed pregabalin or duloxetine, the first-line FDA-approved medications for painful DPN, Based on our population study, the quality of care for diabetic patients with DPN who are prescribed opioid pain medications should be monitored closely. First-line, FDA approved anticonvulsants and antidepressants should be considered for the treatment of painful symptoms when necessary. Attention should be directed towards monitoring and improving glycemic control in patients without DPN receiving opioid pain medications to attempt to prevent or delay the microvascular complications of diabetes, including the onset of painful peripheral neuropathy.

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