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Cognitive task analysis of clinicians drug-drug interaction management during patient care and implications for alert design

Por: Russ-Jara · A. L. · Elkhadragy · N. · Arthur · K. J. · DiIulio · J. B. · Militello · L. G. · Ifeachor · A. P. · Glassman · P. A. · Zillich · A. J. · Weiner · M.
Background

Drug–drug interactions (DDIs) are common and can result in patient harm. Electronic health records warn clinicians about DDIs via alerts, but the clinical decision support they provide is inadequate. Little is known about clinicians’ real-world DDI decision-making process to inform more effective alerts.

Objective

Apply cognitive task analysis techniques to determine informational cues used by clinicians to manage DDIs and identify opportunities to improve alerts.

Design

Clinicians submitted incident forms involving DDIs, which were eligible for inclusion if there was potential for serious patient harm. For selected incidents, we met with the clinician for a 60 min interview. Each interview transcript was analysed to identify decision requirements and delineate clinicians’ decision-making process. We then performed an inductive, qualitative analysis across incidents.

Setting

Inpatient and outpatient care at a major, tertiary Veterans Affairs medical centre.

Participants

Physicians, pharmacists and nurse practitioners.

Outcomes

Themes to identify informational cues that clinicians used to manage DDIs.

Results

We conducted qualitative analyses of 20 incidents. Data informed a descriptive model of clinicians’ decision-making process, consisting of four main steps: (1) detect a potential DDI; (2) DDI problem-solving, sensemaking and planning; (3) prescribing decision and (4) resolving actions. Within steps (1) and (2), we identified 19 information cues that clinicians used to manage DDIs for patients. These cues informed their subsequent decisions in steps (3) and (4). Our findings inform DDI alert recommendations to improve clinicians’ decision-making efficiency, confidence and effectiveness.

Conclusions

Our study provides three key contributions. Our study is the first to present an illustrative model of clinicians’ real-world decision making for managing DDIs. Second, our findings add to scientific knowledge by identifying 19 cognitive cues that clinicians rely on for DDI management in clinical practice. Third, our results provide essential, foundational knowledge to inform more robust DDI clinical decision support in the future.

Statistical methods applied for the assessment of the HIV cascade and continuum of care: a systematic scoping review

Por: Kalinjuma · A. V. · Glass · T. R. · Masanja · H. · Weisser · M. · Msengwa · A. S. · Vanobberghen · F. · Otwombe · K.
Objectives

This scoping review aims to identify and synthesise existing statistical methods used to assess the progress of HIV treatment programmes in terms of the HIV cascade and continuum of care among people living with HIV (PLHIV).

Design

Systematic scoping review.

Data sources

Published articles were retrieved from PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL) Complete and Excerpta Medica dataBASE (EMBASE) databases between April and July 2022. We also strategically search using the Google Scholar search engine and reference lists of published articles.

Eligibility criteria

This scoping review included original English articles that estimated and described the HIV cascade and continuum of care progress in PLHIV. The review considered quantitative articles that evaluated either HIV care cascade progress in terms of the Joint United Nations Programme on HIV and AIDS targets or the dynamics of engagement in HIV care.

Data extraction and synthesis

The first author and the librarian developed database search queries and screened the retrieved titles and abstracts. Two independent reviewers and the first author extracted data using a standardised data extraction tool. The data analysis was descriptive and the findings are presented in tables and visuals.

Results

This review included 300 articles. Cross-sectional study design methods were the most commonly used to assess the HIV care cascade (n=279, 93%). In cross-sectional and longitudinal studies, the majority used proportions to describe individuals at each cascade stage (276/279 (99%) and 20/21 (95%), respectively). In longitudinal studies, the time spent in cascade stages, transition probabilities and cumulative incidence functions was estimated. The logistic regression model was common in both cross-sectional (101/279, 36%) and longitudinal studies (7/21, 33%). Of the 21 articles that used a longitudinal design, six articles used multistate models, which included non-parametric, parametric, continuous-time, time-homogeneous and discrete-time multistate Markov models.

Conclusions

Most literature on the HIV cascade and continuum of care arises from cross-sectional studies. The use of longitudinal study design methods in the HIV cascade is growing because such methods can provide additional information about transition dynamics along the cascade. Therefore, a methodological guide for applying different types of longitudinal design methods to the HIV continuum of care assessments is warranted.

Family caregiver readiness to adopt smart home technology to monitor care—Dependent older adults: A qualitative exploratory study

Abstract

Aims

The aim of this study was to explore factors that influence family caregiver readiness to adopt health smart home technology for their care-dependent older adult family member. Health smart homes are designed to remotely monitor the health and wellness of community-dwelling older adults supporting independent living for as long as possible. Accordingly, if the health smart home is deployed into the home of a care-depended older adult, it can potentially support family caregivers by facilitating workforce participation and give piece of mind to the family caregiver who may not live close to the older adult. However, wider adoption of health smart home technologies into the homes of community-older adults is low, and little is known about the factors that influence the readiness of family caregivers to adopt smart home technologies for their care-dependent older adults.

Design

A qualitative Descriptive study design was utilized.

Methods

Qualitative data were collected between 2019 and 2020 via semi-structured interviews. Thematic analysis of interviews was completed, and data were organized into themes.

Results

Study findings show that caregiver readiness (N = 10) to adopt smart home technology to monitor older adult family members were influenced by five primary themes including a ‘big brother effect’, ‘framing for acceptance’, ‘data privacy’, ‘burden’ and ‘cost.’

Conclusion

Family caregivers were open to adopting smart home technology to support the independent living of their older adult family members. However, the readiness of family caregivers was inextricably linked to the older adults' readiness for smart home adoption. The family caregiver's primary concern was on how they could frame the idea of the smart home to overcome what they viewed as hesitancy to adopt in the older adult. The findings suggest that family caregivers endeavour to balance the hesitancy in their older adult family members with the potential benefits of smart home technology.

Impact

Family caregivers could benefit if their care-dependent older adults adopt smart home technology. Recognizing the role of caregivers and their perspectives on using smart home technologies with their care-dependents is critical to the meaningful design, use and adoption.

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