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Heart failure is one of the serious cardiovascular diseases, which poses a global pandemic and places a heavy burden on health care systems worldwide. The incidence of this disease in Iran is higher than in other Asian countries. To reduce patients' complications, readmission rates, and health care expenditures, it is necessary to design interventions, which are culturally appropriate and based on community needs.

In a time-constrained clinical environment, physicians cannot feasibly document all aspects of an office visit in the electronic health record (EHR). This is especially true for patients with multiple chronic conditions requiring complex clinical reasoning. It is unclear how physicians prioritize the documentation of health information in the EHR.

With the widespread adoption of vendor-supplied electronic health record (EHR) systems, clinical decision support (CDS) customization efforts beyond those anticipated by the vendor may require the use of technologies external to the EHR such as web services. Pursuing such customizations, however, is not without risk. Validating the expected behavior of a customized CDS system in the high-volume, complex environment of the live EHR is a challenging problem.

The reduction and control over neonatal, infant, and maternal mortality is a collective mission of the World Health Organization under United Nations.

Thirty-day hospital readmissions are a quality metric for health care systems. Predictive models aim to identify patients likely to readmit to more effectively target preventive strategies. Many risk of readmission models have been developed on retrospective data, but prospective validation of readmission models is rare. To the best of our knowledge, none of these developed models have been evaluated or prospectively validated in a military hospital.

Visual cohort analysis utilizing electronic health record data has become an important tool in clinical assessment of patient outcomes. In this article, we introduce Composer, a visual analysis tool for orthopedic surgeons to compare changes in physical functions of a patient cohort following various spinal procedures. The goal of our project is to help researchers analyze outcomes of procedures and facilitate informed decision-making about treatment options between patient and clinician.

Patient-generated health data (PGHD) may help providers monitor patient status between clinical visits. Our objective was to describe our medical center's early experience with an electronic flowsheet allowing patients to upload self-monitored blood glucose to their provider's electronic health record (EHR).