scholarly journals Communication by Nurses in the Intensive Care Unit: Qualitative Analysis of Domains of Patient-Centered Care

2012 ◽  
Vol 21 (6) ◽  
pp. 410-418 ◽  
Author(s):  
C. G. Slatore ◽  
L. Hansen ◽  
L. Ganzini ◽  
N. Press ◽  
M. L. Osborne ◽  
...  
2012 ◽  
Vol 32 (2) ◽  
pp. 35-47 ◽  
Author(s):  
Michele C. Balas ◽  
Eduard E. Vasilevskis ◽  
William J. Burke ◽  
Leanne Boehm ◽  
Brenda T. Pun ◽  
...  

Imagine working in an environment where all patients undergoing mechanical ventilation are alert, calm, and delirium free. Envision practicing in an environment where nonvocal patients can effectively express their need for better pain control, repositioning, or emotional reassurance. Picture an intensive care unit where a nurse-led, interprofessional team practices evidence-based, patient-centered care focused on preserving and/or restoring their clients’ physical, functional, and neurocognitive abilities. A recently proposed bundle of practices for the intensive care unit could advance the current practice environment toward this idealized environment. The Awakening and Breathing Coordination, Delirium Monitoring and Management, and Early Mobility (ABCDE) bundle incorporates the best available evidence related to delirium, immobility, sedation/analgesia, and ventilator management in the intensive care unit for adoption into everyday clinical practice.


10.2196/13914 ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 13914
Author(s):  
Maryam Zolnoori ◽  
Joyce E Balls-Berry ◽  
Tabetha A Brockman ◽  
Christi A Patten ◽  
Ming Huang ◽  
...  

Background Patient narrative data in online health care forums (communities) are receiving increasing attention from the scientific community for implementing patient-centered care. Natural language processing (NLP) methods are gaining more and more attention because of the enormous data volume. However, state-of-the-art NLP still cannot meet the need of high-resolution analysis of patients’ narratives. Manual qualitative analysis still plays a pivotal role in answering complicated research questions from analyzing patient narratives. Objective This study aimed to develop a systematic framework for qualitative analysis of patient-generated narratives in online health care forums. Methods Our systematic framework consists of 4 phases: (1) data collection, (2) data preparation, (3) content analysis, and (4) interpretation of the results. Data collection and data preparation phases are constructed based on text mining methods for identifying appropriate online health forums for data collection, differentiating posts of patients from other stakeholders, protecting patients’ privacy, sampling, and choosing the unit of analysis. Content analysis phase is built on the framework method, which facilitates and accelerates the identification of patterns and themes by an interdisciplinary research team. In the end, the focus of interpretation of the results phase is to measure the data quality and interpret the findings regarding the dimensions and aspects of patients’ experiences and concerns in their original contexts. Results We demonstrated the usability of the proposed systematic framework using 2 case studies: one on determining factors affecting patients’ attitudes toward antidepressants and another on identifying the disease management strategies in patient with diabetes facing financial difficulties. The framework provides a clear step-by-step process for systematic content analysis of patient narratives and produces high-quality structured results that can be used for describing patterns or regularities in patients’ experiences, generating and testing hypotheses, and identifying areas of improvement in the health care systems. Conclusions The systematic framework is a rigorous and standardized method for qualitative analysis of patient narratives. Findings obtained through such a process indicate authentic dimensions and aspects of patient experiences and shed light on patients’ concerns, needs, preferences, and values, which are the core of patient-centered care. International Registered Report Identifier (IRRID) RR1-10.2196/13914


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