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Partnerships among patients, families, caregivers, and clinicians are critical to helping patients lead their best lives given their specific genetics, conditions, circumstances, and the environments in which they live, work, and play. These partnerships extend to the development of health information technology, including clinical decision support (CDS). Design of these technologies, however, often occurs without a profound understanding of the true needs, wants, and concerns of patients and family members [...]

Falls in community-dwelling older adults are common, and there is a lack of clinical decision support (CDS) to provide health care providers with effective, individualized fall prevention recommendations.

Health information exchange (HIE) allows healthcare providers to access a patient's medical information to improve patient care continuity. The standardized data realize the HIE values. Since the Health Level 7 Clinical Document Architecture (CDA) is flexible, implementation guides (IG) are needed for use cases. Although many CDA IGs have been developed, they did not describe how these CDA IGs were developed. A national CDA IG that meets the local requirements [...]

Over one-third of deaths recorded at health facilities in Zambia are brought in dead (BID) and the causes of death (CODs) are not fully analyzed. The use of automated verbal autopsy (VA) has reportedly determined the CODs of more BID cases than the death notification form issued by the hospital. However, the validity of automated VA is yet to be fully investigated.

Cancer staging information is an essential component of cancer research. However, the information is primarily stored as either a full or semistructured free-text clinical document which is limiting the data use. By transforming the cancer-specific data to the Observational Medical Outcome Partnership Common Data Model (OMOP CDM), the information can contribute to establish multicenter observational cancer studies. To the best of our knowledge, there have been no studies on OMOP [...]

The widespread adoption of electronic health records and a simultaneous increase in regulatory demands have led to an acceleration of documentation requirements among clinicians. The corresponding burden from documentation requirements is a central contributor to clinician burnout and can lead to an increased risk of suboptimal patient care.

Order sets are a clinical decision support (CDS) tool in computerized provider order entry systems. Order set use has been associated with improved quality of care. Particularly related to opioids and pain management, order sets have been shown to standardize and reduce the prescription of opioids. However, clinician-level barriers often limit the uptake of this CDS modality.

Provider prescribing practices contribute to an excess of opioid-related deaths in the United States. Clinical guidelines exist to assist providers with improving prescribing practices and promoting patient safety. Clinical decision support systems (CDSS) may promote adherence to these guidelines and improve prescribing practices. The aim of this project was to improve opioid guideline adherence, prescribing practices, and rates of opioid-related encounters through the implementation of an opioid CDSS.

A learning health care system (LHS) uses routinely collected data to continuously monitor and improve health care outcomes. Little is reported on the challenges and methods used to implement the analytics underpinning an LHS. Our aim was to systematically review the literature for reports of real-time clinical analytics implementation in digital hospitals and to use these findings to synthesize a conceptual framework for LHS implementation.