Applied clinical informatics
-
The Pulmonary Embolism (PE) Severity Index identifies emergency department (ED) patients with acute PE that can be safely managed without hospitalization. However, the Index comprises 11 weighted variables, complexity that can impede its integration into contextual workflow. ⋯ Our automated extraction of variables from the EHR for the e-Index demonstrates substantial accuracy, requiring a minimum of physician editing. This should increase user acceptability and implementation success of a computerized clinical decision support system built around the e-Index, and may serve as a model to automate other complex risk stratification instruments.
-
Nursing care is facing exponential growth of information from nursing documentation. This amount of electronically available data collected routinely opens up new opportunities for secondary use. ⋯ Following a systematic approach for planning and designing a solution for reusing routine care data appeared to be successful. The resulting nursing intelligence system is useful in practice now, but remains malleable for future changes.
-
The authors investigated the impact of computerized provider order entry (CPOE) on the delivery times of analgesia and subsequent patient outcomes. We hypothesized that patients would report less pain and use less pain medications compared with the previous paper-based system. ⋯ After implementation of CPOE, patients received their postoperative analgesia faster, had less pain, and required less medication.
-
Adoption of a common data model across health systems is a key infrastructure requirement to allow large scale distributed comparative effectiveness analyses. There are a growing number of common data models (CDM), such as Mini-Sentinel, and the Observational Medical Outcomes Partnership (OMOP) CDMs. ⋯ The data transformation to the CDM was time consuming and resources required were substantial, beyond requirements for collecting native source data. The need to manually code subsets of data limited the conversion. However, once the native data was converted to the CDM, both systems were then able to use the same queries to identify cohorts. Thus, the CDM minimized the effort to develop cohorts and analyze the results across the sites.
-
In the US, the new subspecialty of Clinical Informatics focuses on systems-level improvements in care delivery through the use of health information technology (HIT), data analytics, clinical decision support, data visualization and related tools. Clinical informatics is one of the first subspecialties in medicine open to physicians trained in any primary specialty. Clinical Informatics benefits patients and payers such as Medicare and Medicaid through its potential to reduce errors, increase safety, reduce costs, and improve care coordination and efficiency. ⋯ To maintain the value of HIT investments by the government and health care organizations, we must train sufficient leaders in Clinical Informatics. In the best interest of patients, payers, and the US society, it is therefore critical to find viable financial models for Clinical Informatics fellowship programs. To support the development of adequate training programs in Clinical Informatics, we request that the Centers for Medicare and Medicaid Services (CMS) issue clarifying guidance that would allow accredited ACGME institutions to bill for clinical services delivered by fellows at the fellowship program site within their primary specialty.