Improving Evaluation to Address the Unintended Consequences of Health Information Technology:. a Position Paper from the Working Group on Technology Assessment & Quality Development

Human Healthcare and Its Pharmacy Component from a Safety Point of View

Healthcare plays a crucial role in public and national safety as a significant part of state activity and a component of national safety, whose mission is to organize and ensure affordable medical care for the population. The four stages of the genesis of healthcare safety development with the corresponding safety models of formation were defined: technical, human factor or security management, systemic security management, and cognitive complexity. It was established that at all stages, little attention is paid to the issues of the formation of the pharmaceutical sector's safety. Taking into account the development of safety models that arise during the four stages of the genesis of safety science, we have proposed a model of the evolution of pharmaceutical safety formation. At the same time, future research is proposed to focus on new holistic concepts of safety, such as "Safety II", evaluation and validation methods, especially in the pharmaceutical sector, where the development of this topic remained in the second stage of the evolution of science, the search for pharmaceutical errors related to drugs.

Unintended consequences of pharmacy information systems: A case study

BACKGROUND

Pharmacy information systems (PhIS) can cause medication errors that pharmacists may overlook due to their increased workload and lack of understanding of maintaining information quality. This study seeks to identify factors influencing unintended consequences of PhIS and how they affect the information quality, which can pose a risk to patient safety.

MATERIALS AND METHODS

This qualitative, explanatory case study evaluated PhIS in ambulatory pharmacies in a hospital and a clinic. Data were collected through observations, interviews, and document analysis. We applied the socio-technical interactive analysis (ISTA) framework to investigate the socio-technical interactions of pharmacy information systems that lead to unintended consequences. We then adopted the human-organization-process-technology-fit (HOPT-fit) framework to identify their contributing and dominant factors, misfits, and mitigation measures.

RESULTS

We identified 28 unintended consequences of PhIS, their key contributing factors, and their interrelations with the systems. The primary causes of unintended consequences include system rigidity and complexity, unclear knowledge, understanding, skills, and purpose of using the system, use of hybrid paper and electronic documentation, unclear and confusing transitions, additions and duplication of tasks and roles in the workflow, and time pressure, causing cognitive overload and workarounds. Recommended mitigating mechanisms include human factor principles in system design, data quality improvement for PhIS in terms of effective use of workspace, training, PhIS master data management, and communication by standardizing workarounds.

CONCLUSION

Threats to information quality emerge in PhIS because of its poor design, a failure to coordinate its functions and clinical tasks, and pharmacists' lack of understanding of the system use. Therefore, safe system design, fostering awareness in maintaining the information quality of PhIS and cultivating its safe use in organizations is essential to ensure patient safety. The proposed evaluation approach facilitates the evaluator to identify complex socio-technical interactions and unintended consequences factors, impact, and mitigation mechanisms.

Engaging the disability community in informatics research: rationales and practical steps

As the informatics community grows in its ability to address health disparities, there is an opportunity to expand our impact by focusing on the disability community as a health disparity population. Although informaticians have primarily catered design efforts to one disability at a time, digital health technologies can be enhanced by approaching disability from a more holistic framework, simultaneously accounting for multiple forms of disability and the ways disability intersects with other forms of identity. The urgency of moving toward this more holistic approach is grounded in ethical, legal, and design-related rationales. Shaped by our research and advocacy with the disability community, we offer a set of guidelines for effective engagement. We argue that such engagement is critical to creating digital health technologies which more fully meet the needs of all disabled individuals.

Evaluation in Life Cycle of Information Technology (ELICIT) framework: Supporting the innovation life cycle from business case assessment to summative evaluation

OBJECTIVE

Our objective was to develop an evaluation framework for electronic health record (EHR)-integrated innovations to support evaluation activities at each of four information technology (IT) life cycle phases: planning, development, implementation, and operation.

METHODS

The evaluation framework was developed based on a review of existing evaluation frameworks from health informatics and other domains (human factors engineering, software engineering, and social sciences); expert consensus; and real-world testing in multiple EHR-integrated innovation studies.

RESULTS

The resulting Evaluation in Life Cycle of IT (ELICIT) framework covers four IT life cycle phases and three measure levels (society, user, and IT). The ELICIT framework recommends 12 evaluation steps: (1) business case assessment; (2) stakeholder requirements gathering; (3) technical requirements gathering; (4) technical acceptability assessment; (5) user acceptability assessment; (6) social acceptability assessment; (7) social implementation assessment; (8) initial user satisfaction assessment; (9) technical implementation assessment; (10) technical portability assessment; (11) long-term user satisfaction assessment; and (12) social outcomes assessment.

DISCUSSION

Effective evaluation requires a shared understanding and collaboration across disciplines throughout the entire IT life cycle. In contrast with previous evaluation frameworks, the ELICIT framework focuses on all phases of the IT life cycle across the society, user, and IT levels. Institutions seeking to establish evaluation programs for EHR-integrated innovations could use our framework to create such shared understanding and justify the need to invest in evaluation.

CONCLUSION

As health care undergoes a digital transformation, it will be critical for EHR-integrated innovations to be systematically evaluated. The ELICIT framework can facilitate these evaluations.

Perceptual Gaps Between Clinicians and Technologists on Health Information Technology-Related Errors in Hospitals: Observational Study

BACKGROUND

Health information technology (HIT) has been widely adopted in hospital settings, contributing to improved patient safety. However, many types of medical errors attributable to information technology (IT) have negatively impacted patient safety. The continued occurrence of many errors is a reminder that HIT software testing and validation is not adequate in ensuring errorless software functioning within the health care organization.

OBJECTIVE

This pilot study aims to classify technology-related medical errors in a hospital setting using an expanded version of the sociotechnical framework to understand the significant differences in the perceptions of clinical and technology stakeholders regarding the potential causes of these errors. The paper also provides some recommendations to prevent future errors.

METHODS

Medical errors were collected from previous studies identified in leading health databases. From the main list, we selected errors that occurred in hospital settings. Semistructured interviews with 5 medical and 6 IT professionals were conducted to map the events on different dimensions of the expanded sociotechnical framework.

RESULTS

Of the 2319 identified publications, 36 were included in the review. Of the 67 errors collected, 12 occurred in hospital settings. The classification showed the "gulf" that exists between IT and medical professionals in their perspectives on the underlying causes of medical errors. IT experts consider technology as the source of most errors and suggest solutions that are mostly technical. However, clinicians assigned the source of errors within the people, process, and contextual dimensions. For example, for the error "Copied and pasted charting in the wrong window: Before, you could not easily get into someone else's chart accidentally...because you would have to pull the chart and open it," medical experts highlighted contextual issues, including the number of patients a health care provider sees in a short time frame, unfamiliarity with a new electronic medical record system, nurse transitions around the time of error, and confusion due to patients having the same name. They emphasized process controls, including failure modes, as a potential fix. Technology experts, in contrast, discussed the lack of notification, poor user interface, and lack of end-user training as critical factors for this error.

CONCLUSIONS

Knowledge of the dimensions of the sociotechnical framework and their interplay with other dimensions can guide the choice of ways to address medical errors. These findings lead us to conclude that designers need not only a high degree of HIT know-how but also a strong understanding of the medical processes and contextual factors. Although software development teams have historically included clinicians as business analysts or subject matter experts to bridge the gap, development teams will be better served by more immersive exposure to clinical environments, leading to better software design and implementation, and ultimately to enhanced patient safety.

Systems and Precision Medicine in Necrotizing Soft Tissue Infections

Necrotizing soft tissue infections (NSTI) are multifactorial and characterized by dysfunctional, time dependent, highly varying hyper- to hypo-inflammatory host responses contributing to disease severity. Furthermore, host-pathogen interactions are diverse and difficult to identify and characterize, due to the many different disease endotypes. There is a need for both refined bedside diagnostics as well as novel targeted treatment options to improve outcome in NSTI. In order to achieve clinically relevant results and to guide preclinical and clinical research the vast amount of fragmented clinical and experimental datasets, which often include omics data at different levels (transcriptomics, proteomics, metabolomics, etc.), need to be organized, harmonized, integrated, and analyzed taking into account the Big Data nature of these datasets. In this chapter, we address these matters from a systems perspective and yet personalized approach. The chapter provides an overview on the increasingly more frequent use of Big Data and Artificial Intelligence (AI) to aggregate and generate knowledge from burgeoning clinical and biochemical information, addresses the challenges to manage this information, and summarizes current efforts to develop robust computer-aided clinical decision support systems so to tackle the serious challenges in NSTI diagnosis, stratification, and optimized tailored therapy.

Systematic review of computerized prescriber order entry and clinical decision support

PURPOSE

Results of a systematic review of published data on the effect of computerized prescriber order entry (CPOE) with clinical decision support on medication error (ME) and adverse drug event (ADE) rates are presented.

METHODS

Literature searches of MEDLINE, Embase, and other databases were conducted to identify English- and Spanish-language articles on selected CPOE outcomes published from 1995 through 2016; in addition, 5 specific journals were searched for pertinent articles published during the period 2010-16. Publications on controlled prospective studies and before-and-after studies that assessed MEs and/or ADEs as main outcomes were selected for inclusion in the review.

RESULTS

Nineteen studies met the inclusion criteria. Data on MEs and ADEs could not be pooled, mainly due to heterogeneity in outcome definitions and study methodologies. The reviewed evidence indicated that CPOE implementation led to an overall reduction in errors at the prescription stage of the medication-use process (relative risk reduction, 0.29 [95% confidence interval, 0.10-0.85]; I ² = 99%) and reductions in most types of prescription errors, but CPOE also resulted in the emergence of other types of errors.

CONCLUSION

CPOE reduces the overall ME rate in the prescription process, as well as specific types of errors, such as wrong dose or strength, wrong drug, frequency, administration route, and drug-drug interaction errors. The implementation of CPOE can lead to new errors, such as wrong drug selection from drop-down menus.

Health Information Technology in Healthcare Quality and Patient Safety: Literature Review

Background

The area of healthcare quality and patient safety is starting to use health information technology to prevent reportable events, identify them before they become issues, and act on events that are thought to be unavoidable. As healthcare organizations begin to explore the use of health information technology in this realm, it is often unclear where fiscal and human efforts should be focused.

Objective

The purpose of this study was to provide a foundation for understanding where to focus health information technology fiscal and human resources as well as expectations for the use of health information technology in healthcare quality and patient safety.

Methods

A literature review was conducted to identify peer-reviewed publications reporting on the actual use of health information technology in healthcare quality and patient safety. Inductive thematic analysis with open coding was used to categorize a total of 41 studies. Three pre-set categories were used: prevention, identification, and action. Three additional categories were formed through coding: challenges, outcomes, and location.

Results

This study identifies five main categories across seven study settings. A majority of the studies used health IT for identification and prevention of healthcare quality and patient safety issues. In this realm, alerts, clinical decision support, and customized health IT solutions were most often implemented. Implementation, interface design, and culture were most often noted as challenges.

Conclusions

This study provides valuable information as organizations determine where they stand to get the most “bang for their buck” relative to health IT for quality and patient safety. Knowing what implementations are being effectivity used by other organizations helps with fiscal and human resource planning as well as managing expectations relative to cost, scope, and outcomes. The findings from this scan of the literature suggest that having organizational champion leaders that can shepherd implementation, impact culture, and bridge knowledge with developers would be a valuable resource allocation to consider.