The investigators hypothesize that computer-assisted decision support will increase the percentage of women with a history of gestational diabetes who receive appropriate follow-up screening.

Specific Aim 1: Develop an algorithm to identify cases of gestational diabetes among patients in the Partners Health Care system using administrative and laboratory data.

Specific Aim 2: Assess primary care provider knowledge, attitudes, beliefs, and barriers to compliance regarding screening guidelines for women with a history of gestational diabetes.

Specific Aim 3: Test whether a computer-assisted decision support tool to identify patients with a GDM history and prompt screening will increase compliance with guidelines. The investigators hypothesize that decision support will significantly increase in the percentage of women screened.

Approximately 5 percent of women are diagnosed with gestational diabetes (GDM) during pregnancy. These women face an increased risk of progression to type 2 diabetes1 and may benefit from lifestyle interventions and screening to detect early disease. However, studies have shown that less than half of women are screened appropriately in the postpartum period. This performance gap may reflect both lack of communication between obstetric and primary care providers and lack of knowledge of appropriate screening guidelines. The investigators plan to assess a quality improvement initiative, using administrative and clinical data, to identify women with a history of GDM and implement decision support to enhance quality of care.

Inclusion:

• Primary care clinic (gynecology, internal medicine, community health center)
• Use longitudinal medical record (LMR) program for documentation
• Previously participated in rct of decision support intervention

Exclusion:

• None