Featured

  • Fall 2017 Introduction

    The Fall 2017 issue of Perspectives in Health Information Management features the latest research on topics such as automated vaccine documentation, a review of usability issues in Australia PHR system, and repurposing EHR data to identify fall risks.

    Authors of the study, “An Electronic Health Record Data-driven Model for Identifying Older Adults at Risk of Unintentional Falls,” studied the use of de-identified EHR data to support fall prevention. The research revealed a list of facts (such as age, sex, and specific diagnoses) that could be useful in determining high-risk fall patients.  

  • Summer 2017 Introduction

    The Summer 2017 issue of Perspectives in Health Information Management features the latest research on topics such as the use of geographic information systems in healthcare and a research study designed to assess the main barriers of telestroke network implementation in rural hospitals.  

  • Spring 2017 Introduction

    The Spring 2017 issue of Perspectives in Health Information Management features the latest research on topics such as an analysis of mHealth interventions for adult obesity in the United States, as well as a study seeking to determine user’s motivators when playing an EHR simulation game.  

  • Winter 2017 Introduction

    The Winter 2017 issue of Perspectives in Health Information Management features the latest research on topics such as mobile device security, development of a web-based diabetes registry, and the use of secure clinical texting to issue patient care orders.  

  • Spring 2016 Introduction

    The Spring 2016 issue of Perspectives in Health Information Management features the latest research on topics such as a descriptive, mixed-methodology study examining HIM leadership through the lens of the Bowen theory; a survey examining the opinions of educators and employers related to graduate preparedness; and a study examining the underlying causes of duplicate records using a multisite data set of patient records with confirmed duplicates and analyzed multiple reasons for data discrepancies between those record matches.