Methods for Addressing Technology-induced Errors: The Current State.

OBJECTIVES: The objectives of this paper are to review and discuss the methods that are being used internationally to report on, mitigate, and eliminate technology-induced errors. METHODS: The IMIA Working Group for Health Informatics for Patient Safety worked together to review and synthesize some of the main methods and approaches associated with technology- induced error reporting, reduction, and mitigation. The work involved a review of the evidence-based literature as well as guideline publications specific to health informatics. RESULTS: The paper presents a rich overview of current approaches, issues, and methods associated with: (1) safe HIT design, (2) safe HIT implementation, (3) reporting on technology-induced errors, (4) technology-induced error analysis, and (5) health information technology (HIT) risk management. The work is based on research from around the world. CONCLUSIONS: Internationally, researchers have been developing methods that can be used to identify, report on, mitigate, and eliminate technology-induced errors. Although there remain issues and challenges associated with the methodologies, they have been shown to improve the quality and safety of HIT. Since the first publications documenting technology-induced errors in healthcare in 2005, we have seen in a short 10 years researchers develop ways of identifying and addressing these types of errors. We have also seen organizations begin to use these approaches. Knowledge has been translated into practice in a short ten years whereas the norm for other research areas is of 20 years.

Effects of automated immunization registry reporting via an electronic health record deployed in community practice settings.

BACKGROUND: Among the expected benefits of electronic health records (EHRs) is increased reporting of public health information, such as immunization status. State and local immunization registries aid control of vaccine-preventable diseases and help offset fragmentation in healthcare, but reporting is often slow and incomplete. The Primary Care Information Project (PCIP), an initiative of the NYC Department of Health and Mental Hygiene, has implemented EHRs with immunization reporting capability in community settings. OBJECTIVE AND METHODS: To evaluate the effect of automated reporting via an EHR on use and efficiency of reporting to the NY Citywide Immunization Registry, we conducted a secondary analysis of 1.7 million de-identified records submitted between January 2007 and June 2011 by 217 primary care practices enrolled in PCIP, pre and post launch of automated reporting via an EHR. We examined differences in records submitted per day, lag time, and documentation of eligibility for subsidized vaccines. RESULTS: Mean submissions per day did not change. Automated submissions of new and historical records increased by 18% and 98% respectively. Submissions within 14 days increased from 84% to 87%, and within 2 days increased from 60% to 77%. Median lag time decreased from 13 to 10 days. Documentation of eligibility decreased. Results are significant at p<0.001. CONCLUSIONS: Significant improvements in registry use and efficiency of reporting were found after launch of automated reporting via an EHR. A decrease in eligibility documentation was attributed to EHR workflow. The limitations to comprehensive evaluation found in these data, which were extracted from a registry initiated prior to widespread EHR implementation suggests that reliable evaluation of immunization reporting via the EHR may require modifications to legacy registry databases.

Visual clustering analysis of CIS logs to inform creation of a user-configurable Web CIS interface.

BACKGROUND: In this paper, we describe a new method for the study of clinical information system (CIS) logfiles joined with information in the clinical data warehouse. This method uses heatmap representations and clustering techniques to examine clinicians' viewing patterns of laboratory test results. The context of our application of these techniques is to inform the creation of a widget-based interface to the CIS. OBJECTIVES: We address the rationale, feasibility, and usefulness of our method through examination of three hypotheses: 1) The frequency distribution of laboratory test viewing will follow a 'long tail' pattern, indicating that patterns are highly variable and supporting the rationale for a widget-based configurable system. 2) Patterns of laboratory testing viewing (by clinician, specialty, clinician/patient/day, and ICD-9-CM codes) can be distinguished by our methods. 3) The identified clusters will include more than 80% of the laboratory test elements found in 30 randomly selected patient records for one day. METHODS: The data were plotted as heatmaps and clustered using hierarchical clustering software. Various parameters were tested to give the optimal clusters. RESULTS: All the hypotheses were supported. For Hypothesis 3, 91.4% of information elements in the records were covered by the generated clusters. CONCLUSIONS: Study findings support the rationale, feasibility, and usefulness of our methods to examine patterns of information access among clinicians and to inform the creation of widget-based interfaces. The results also contribute to our general understanding of clinicians' CIS use.