Patient characteristics associated with venous thromboembolic events: a cohort study using pooled electronic health record data

OBJECTIVE

To demonstrate the potential of de-identified clinical data from multiple healthcare systems using different electronic health records (EHR) to be efficiently used for very large retrospective cohort studies.

MATERIALS AND METHODS

Data of 959 030 patients, pooled from multiple different healthcare systems with distinct EHR, were obtained. Data were standardized and normalized using common ontologies, searchable through a HIPAA-compliant, patient de-identified web application (Explore; Explorys Inc). Patients were 26 years or older seen in multiple healthcare systems from 1999 to 2011 with data from EHR.

RESULTS

Comparing obese, tall subjects with normal body mass index, short subjects, the venous thromboembolic events (VTE) OR was 1.83 (95% CI 1.76 to 1.91) for women and 1.21 (1.10 to 1.32) for men. Weight had more effect then height on VTE. Compared with Caucasian, Hispanic/Latino subjects had a much lower risk of VTE (female OR 0.47, 0.41 to 0.55; male OR 0.24, 0.20 to 0.28) and African-Americans a substantially higher risk (female OR 1.83, 1.76 to 1.91; male OR 1.58, 1.50 to 1.66). This 13-year retrospective study of almost one million patients was performed over approximately 125 h in 11 weeks, part time by the five authors.

DISCUSSION

As research informatics tools develop and more clinical data become available in EHR, it is important to study and understand unique opportunities for clinical research informatics to transform the scale and resources needed to perform certain types of clinical research.

CONCLUSIONS

With the right clinical research informatics tools and EHR data, some types of very large cohort studies can be completed with minimal resources.

Clinical documentation: composition or synthesis?

OBJECTIVE

To understand the nature of emerging electronic documentation practices, disconnects between documentation workflows and computing systems designed to support them, and ways to improve the design of electronic documentation systems.

MATERIALS AND METHODS

Time-and-motion study of resident physicians' note-writing practices using a commercial electronic health record system that includes an electronic documentation module. The study was conducted in the general medicine unit of a large academic hospital.

RESULTS

During the study, 96 note-writing sessions by 11 resident physicians, resulting in close to 100 h of observations were seen. Seven of the 10 most common transitions between activities during note composition were between documenting, and gathering and reviewing patient data, and updating the plan of care.

DISCUSSION

The high frequency of transitions seen in the study suggested that clinical documentation is fundamentally a synthesis activity, in which clinicians review available patient data and summarize their impressions and judgments. At the same time, most electronic health record systems are optimized to support documentation as uninterrupted composition. This mismatch leads to fragmentation in clinical work, and results in inefficiencies and workarounds. In contrast, we propose that documentation can be best supported with tools that facilitate data exploration and search for relevant information, selective reading and annotation, and composition of a note as a temporal structure.

CONCLUSIONS

Time-and-motion study of clinicians' electronic documentation practices revealed a high level of fragmentation of documentation activities and frequent task transitions. Treating documentation as synthesis rather than composition suggests new possibilities for supporting it more effectively with electronic systems.

iDASH: integrating data for analysis, anonymization, and sharing

iDASH (integrating data for analysis, anonymization, and sharing) is the newest National Center for Biomedical Computing funded by the NIH. It focuses on algorithms and tools for sharing data in a privacy-preserving manner. Foundational privacy technology research performed within iDASH is coupled with innovative engineering for collaborative tool development and data-sharing capabilities in a private Health Insurance Portability and Accountability Act (HIPAA)-certified cloud. Driving Biological Projects, which span different biological levels (from molecules to individuals to populations) and focus on various health conditions, help guide research and development within this Center. Furthermore, training and dissemination efforts connect the Center with its stakeholders and educate data owners and data consumers on how to share and use clinical and biological data. Through these various mechanisms, iDASH implements its goal of providing biomedical and behavioral researchers with access to data, software, and a high-performance computing environment, thus enabling them to generate and test new hypotheses.

Development and preliminary evidence for the validity of an instrument assessing implementation of human-factors principles in medication-related decision-support systems--I-MeDeSA

BACKGROUND

Medication-related decision support can reduce the frequency of preventable adverse drug events. However, the design of current medication alerts often results in alert fatigue and high over-ride rates, thus reducing any potential benefits.

METHODS

The authors previously reviewed human-factors principles for relevance to medication-related decision support alerts. In this study, instrument items were developed for assessing the appropriate implementation of these human-factors principles in drug-drug interaction (DDI) alerts. User feedback regarding nine electronic medical records was considered during the development process. Content validity, construct validity through correlation analysis, and inter-rater reliability were assessed.

RESULTS

The final version of the instrument included 26 items associated with nine human-factors principles. Content validation on three systems resulted in the addition of one principle (Corrective Actions) to the instrument and the elimination of eight items. Additionally, the wording of eight items was altered. Correlation analysis suggests a direct relationship between system age and performance of DDI alerts (p=0.0016). Inter-rater reliability indicated substantial agreement between raters (κ=0.764).

CONCLUSION

The authors developed and gathered preliminary evidence for the validity of an instrument that measures the appropriate use of human-factors principles in the design and display of DDI alerts. Designers of DDI alerts may use the instrument to improve usability and increase user acceptance of medication alerts, and organizations selecting an electronic medical record may find the instrument helpful in meeting their clinicians' usability needs.

Development and validation of a survey instrument for assessing prescribers' perception of computerized drug-drug interaction alerts

OBJECTIVE

To develop a theoretically informed and empirically validated survey instrument for assessing prescribers' perception of computerized drug-drug interaction (DDI) alerts.

MATERIALS AND METHODS

The survey is grounded in the unified theory of acceptance and use of technology and an adapted accident causation model. Development of the instrument was also informed by a review of the extant literature on prescribers' attitude toward computerized medication safety alerts and common prescriber-provided reasons for overriding. To refine and validate the survey, we conducted a two-stage empirical validation study consisting of a pretest with a panel of domain experts followed by a field test among all eligible prescribers at our institution.

RESULTS

The resulting survey instrument contains 28 questionnaire items assessing six theoretical dimensions: performance expectancy, effort expectancy, social influence, facilitating conditions, perceived fatigue, and perceived use behavior. Satisfactory results were obtained from the field validation; however, a few potential issues were also identified. We analyzed these issues accordingly and the results led to the final survey instrument as well as usage recommendations.

DISCUSSION

High override rates of computerized medication safety alerts have been a prevalent problem. They are usually caused by, or manifested in, issues of poor end user acceptance. However, standardized research tools for assessing and understanding end users' perception are currently lacking, which inhibits knowledge accumulation and consequently forgoes improvement opportunities. The survey instrument presented in this paper may help fill this methodological gap.

CONCLUSION

We developed and empirically validated a survey instrument that may be useful for future research on DDI alerts and other types of computerized medication safety alerts more generally.

A multi-layered framework for disseminating knowledge for computer-based decision support

BACKGROUND

There are several challenges in encoding guideline knowledge in a form that is portable to different clinical sites, including the heterogeneity of clinical decision support (CDS) tools, of patient data representations, and of workflows.

METHODS

We have developed a multi-layered knowledge representation framework for structuring guideline recommendations for implementation in a variety of CDS contexts. In this framework, guideline recommendations are increasingly structured through four layers, successively transforming a narrative text recommendation into input for a CDS system. We have used this framework to implement rules for a CDS service based on three guidelines. We also conducted a preliminary evaluation, where we asked CDS experts at four institutions to rate the implementability of six recommendations from the three guidelines.

CONCLUSION

The experience in using the framework and the preliminary evaluation indicate that this approach has promise in creating structured knowledge, to implement in CDS systems, that is usable across organizations.

A partnership model for implementing electronic health records in resource-limited primary care settings: experiences from two nurse-managed health centers

OBJECTIVE

To present a partnership-based and community-oriented approach designed to ease provider anxiety and facilitate the implementation of electronic health records (EHR) in resource-limited primary care settings.

MATERIALS AND METHODS

The approach, referred to as partnership model, was developed and iteratively refined through the research team's previous work on implementing health information technology (HIT) in over 30 safety net practices. This paper uses two case studies to illustrate how the model was applied to help two nurse-managed health centers (NMHC), a particularly vulnerable primary care setting, implement EHR and get prepared to meet the meaningful use criteria.

RESULTS

The strong focus of the model on continuous quality improvement led to eventual implementation success at both sites, despite difficulties encountered during the initial stages of the project.

DISCUSSION

There has been a lack of research, particularly in resource-limited primary care settings, on strategies for abating provider anxiety and preparing them to manage complex changes associated with EHR uptake. The partnership model described in this paper may provide useful insights into the work shepherded by HIT regional extension centers dedicated to supporting resource-limited communities disproportionally affected by EHR adoption barriers.

CONCLUSION

NMHC, similar to other primary care settings, are often poorly resourced, understaffed, and lack the necessary expertise to deploy EHR and integrate its use into their day-to-day practice. This study demonstrates that implementation of EHR, a prerequisite to meaningful use, can be successfully achieved in this setting, and partnership efforts extending far beyond the initial software deployment stage may be the key.

Normalized names for clinical drugs: RxNorm at 6 years

OBJECTIVE

In the 6 years since the National Library of Medicine began monthly releases of RxNorm, RxNorm has become a central resource for communicating about clinical drugs and supporting interoperation between drug vocabularies.

MATERIALS AND METHODS

Built on the idea of a normalized name for a medication at a given level of abstraction, RxNorm provides a set of names and relationships based on 11 different external source vocabularies. The standard model enables decision support to take place for a variety of uses at the appropriate level of abstraction. With the incorporation of National Drug File Reference Terminology (NDF-RT) from the Veterans Administration, even more sophisticated decision support has become possible.

DISCUSSION

While related products such as RxTerms, RxNav, MyMedicationList, and MyRxPad have been recognized as helpful for various uses, tasks such as identifying exactly what is and is not on the market remain a challenge.