Visualization of the IMIA Yearbook of Medical Informatics Publications over the Last 25 Years

BACKGROUND

The last 25 years have been a period of innovation in the area of medical informatics. The International Medical Informatics Association (IMIA) has published, every year for the last quarter century, the Yearbook of Medical Informatics, collating selected papers from various journals in an attempt to provide a summary of the academic medical informatics literature. The objective of this paper is to visualize the evolution of the medical informatics field over the last 25 years according to the frequency of word occurrences in the papers published in the IMIA Yearbook of Medical Informatics.

METHODS

A literature review was conducted examining the IMIA Yearbook of Medical Informatics between 1992 and 2015. These references were collated into a reference manager application to examine the literature using keyword searches, word clouds, and topic clustering. The data was considered in its entirety, as well as segregated into 3 time periods to examine the evolution of main trends over time. Several methods were used, including word clouds, cluster maps, and custom developed web-based information dashboards.

RESULTS

The literature search resulted in a total of 1210 references published in the Yearbook, of which 213 references were excluded, resulting in 997 references for visualization. Overall, we found that publications were more technical and methods-oriented between 1992 and 1999; more clinically and patient-oriented between 2000 and 2009; and noted the emergence of "big data", decision support, and global health in the past decade between 2010 and 2015. Dashboards were additionally created to show individual reference data, as well as, aggregated information.

CONCLUSION

Medical informatics is a vast and expanding area with new methods and technologies being researched, implemented, and evaluated. Determining visualization approaches that enhance our understanding of literature is an active area of research, and like medical informatics, is constantly evolving as new software and algorithms are developed. This paper examined several approaches for visualizing the medical informatics literature to show historical trends, associations, and aggregated summarized information to illustrate the state and changes in the IMIA Yearbook publications over the last quarter century.

Assessing the association between occupancy and outcome in critically Ill hospitalized patients with sepsis

BACKGROUND

Sepsis has a high prevalence, mortality-rate and cost. Sepsis patients usually enter the hospital through the Emergency Department (ED). Process or structural issues related to care may affect outcome.

METHODS

Multi-centered retrospective observational cohort study using administrative databases to identify adult patients (> = 18 years) with sepsis and severe sepsis admitted to Alberta Health Services Calgary zone adult multisystem intensive care units (ICU) through the ED between January 1, 2006 and September 30, 2009. We examined the association between ICU occupancy and hospital outcome. We explored other associations of hospital outcome including the effect of ED wait time, admission from ED during weekdays versus weekends and ED admission during the day versus at night.

RESULTS

One thousand and seven hundred seventy patients were admitted to hospital via ED, 1036 (58.5 %) with sepsis and 734 (41.5 %) with severe sepsis. In patients with sepsis, ICU occupancy > 90 % was associated with an increase in hospital mortality even after adjusting for age, sex, triage level, Charlson index, time of first ED physician assessment and ICU admission. No differences in hospital mortality were found for patients who waited more than 7 h, were admitted during the day versus night or weekdays versus weekends.

CONCLUSIONS

In patients with sepsis admitted via the ED, increased ICU occupancy was associated with higher in-hospital mortality.

Validity of administrative data in recording sepsis: a systematic review

Introduction

Administrative health data have been used to study sepsis in large population-based studies. The validity of these study findings depends largely on the quality of the administrative data source and the validity of the case definition used. We systematically reviewed the literature to assess the validity of case definitions of sepsis used with administrative data.

Methods

Embase and MEDLINE were searched for published articles with International Classification of Diseases (ICD) coded data used to define sepsis. Abstracts and full-text articles were reviewed in duplicate. Data were abstracted from all eligible full-text articles, including ICD-9- and/or ICD-10-based case definitions, sensitivity (Sn), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV).

Results

Of 2,317 individual studies identified, 12 full-text articles met all eligibility criteria. A total of 38 sepsis case definitions were tested, which included over 130 different ICD codes. The most common ICD-9 codes were 038.x, 790.7 and 995.92, and the most common ICD-10 codes were A40.x and A41.x. The PPV was reported in ten studies and ranged from 5.6% to 100%, with a median of 50%. Other tests of diagnostic accuracy were reported only in some studies. Sn ranged from 5.9% to 82.3%; Sp ranged from 78.3% to 100%; and NPV ranged from 62.1% to 99.7%.

Conclusions

The validity of administrative data in recording sepsis varied substantially across individual studies and ICD definitions. Our work may serve as a reference point for consensus towards an improved and harmonized ICD-coded definition of sepsis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-015-0847-3) contains supplementary material, which is available to authorized users.

An overview of the statistical methods reported by studies using the Canadian community health survey

BACKGROUND

The Canadian Community Health Survey (CCHS) is a cross-sectional survey that has collected information on health determinants, health status and the utilization of the health system in Canada since 2001. Several hundred articles have been written utilizing the CCHS dataset. Previous analyses of statistical methods utilized in the literature have focused on a particular journal or set of journals to understand the statistical literacy required for understanding the published research. In this study, we describe the statistical methods referenced in the published literature utilizing the CCHS dataset(s).

METHODS

A descriptive study was undertaken of references published in Medline, Embase, Web of Knowledge and Scopus associated with the CCHS. These references were imported into a Java application utilizing the searchable Apache Lucene text database and screened based upon pre-defined inclusion and exclusion criteria. Full-text PDF articles that met the inclusion criteria were then used for the identification of descriptive, elementary and regression statistical methods referenced in these articles. The identification of statistical methods occurred through an automated search of key words on the full-text articles utilizing the Java application.

RESULTS

We identified 4811 references from the 4 bibliographical databases for possible inclusion. After exclusions, 663 references were used for the analysis. Descriptive statistics such as means or proportions were presented in a majority of the articles (97.7%). Elementary-level statistics such as t-tests were less frequently referenced (29.7%) than descriptive statistics. Regression methods were frequently referenced in the articles: 79.8% of articles contained reference to regression in general with logistic regression appearing most frequently in 67.1% of the articles.

CONCLUSIONS

Our study shows a diverse set of analysis methods being referenced in the CCHS literature, however, the literature heavily relies on only a subset of all possible statistical tools. This information can be used in identifying gaps in statistical methods that could be applied to future analysis of public health surveys, insight into training and educational programs, and also identifies the level of statistical literacy needed to understand the published literature.