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Succinct and timely discharge summaries (DSs) facilitate ongoing care for patients discharged from acute care settings. Many institutions have introduced electronic DS (eDS) templates to improve quality and timeliness of clinical correspondence. However, significant intrahospital and intraunit variability and application exists. A review of the literature and guidelines revealed 13 key elements that should be included in a best practice DS. This was compared against our pediatric institution's eDS template-housed [...]

Outpatient providers often do not receive discharge summaries from acute care providers prior to follow-up visits. These outpatient providers may use the after-visit summaries (AVS) that are given to patients to obtain clinical information. It is unclear how effectively AVS support care coordination between clinicians.

Holistic, ubiquitous support of patient-centered health care (eHealth) at all health care institutions and in patients' homes through information processing is increasingly supplementing institution-centered care. While eHealth indicators may measure the transition from institution-centered (e.g., hospital-centered) information processing to patient-centered information processing, collecting relevant and timely data for such indicators has been difficult.

Defining clinical conditions from electronic health record (EHR) data underpins population health activities, clinical decision support, and analytics. In an EHR, defining a condition commonly employs a diagnosis value set or "grouper." For constructing value sets, Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) offers high clinical fidelity, a hierarchical ontology, and wide implementation in EHRs as the standard interoperability vocabulary for problems.

Over the last decade, electronic health records (EHRs) have shaped clinical practice. In this article, we investigated the perceived effects of EHR use on clinical workflow and meaningful use (MU) performance metrics.

Inhospital pediatric trauma care typically spans multiple locations, which influences the use of resources, that could be improved by gaining a better understanding of the inhospital flow of patients and identifying opportunities for improvement.

Compared with medicine, less research has focused on adoption rates and factors contributing to the adoption of electronic dental records (EDRs) and certified electronic health records (EHRs) in the field of dentistry. We ran two multivariate models on EDR adoption and certification-capable EHR adoption to determine environmental and organizational factors associated with adoption.

Venous thromboembolism (VTE) prophylaxis is an important consideration for hospitalized older adults, and the Padua Prediction Score (PPS) is a risk prediction tool used to prioritize patient selection. We developed an automated PPS (APPS) algorithm using electronic health record (EHR) data. This study examines the accuracy of APPS and its individual components versus manual data extraction.