Abstracting ICU Nursing Care Quality Data From the Electronic Health Record

Abstract

The electronic health record is a potentially rich source of data for clinical research in the intensive care unit setting. We describe the iterative, multi-step process used to develop and test a data abstraction tool, used for collection of nursing care quality indicators from the electronic health record, for a pragmatic trial. We computed Cohen’s kappa coefficient (κ) to assess inter-rater agreement or reliability of data abstracted using preliminary and finalized tools. In assessing the reliability of study data (n=1440 cases) using the finalized tool, 108 randomly selected cases (10% of first half sample; 5% of last half sample) were independently abstracted by a second rater. We demonstrated mean κ values ranging from 0.61 to 0.99 for all indicators. Nursing care quality data can be accurately and reliably abstracted from the electronic health records of intensive care unit patients using a well-developed data collection tool and detailed training.

[Retracted] Optimization of Clinical Nursing Management System Based on Data Mining

“…is usually requires a requirement analysis to determine the entity type, the relationship between the entities, and their attribute set codes and finally build the E-R model. Because each entity has many attributes, only the main related attributes are listed in each entity [19]. e E-R model of the data mining model constructed in this research is shown in Figure 2.…”

Use of Electronic and Paper‐based Standardized Nursing Care Plans to Improve Nurses’ Documentation Quality in a Nigerian Teaching Hospital

“…Consensus exits among authors on the use of standardized and electronic documentation to support the nursing process and to improve the quality of nursing documentation (Hillestad et al., ; Mahler et al., ; Müller‐Staub, Needham, Odenbreit, Ann Lavin, & Van Achterberg, ; O'Brien et al., ; Seaman et al., ; Yu, Qiu, & Crookes, ). Nurses globally are embracing the advancement in Information and Communication Technology (ICT) to meet the changing needs of the society across culture through effective documentation which promotes accuracy of information and continuity of care (Habibi‐Koolaee, Safdari, & Bouraghi ; Kahouei, Mohammadi, Majdabadi, Solhi, Parsania, Oghani & Firozeh, ; Sockolow, Liao, Chittams, & Bowles, ; Yu, Hailey, & Li, ).…”

Identifying nursing sensitive indicators from electronic health records in acute cardiac care―Towards intelligent automated assessment of care quality

“…The first standpoint indicates the degree of readiness of nursingsensitive indicators to be used in care quality assessment. Previous research presents ample evidence of the use of nursing-sensitive indicators corresponding to the established expressions found in our study, such as experiences of pain or prevalence of pressure injuries (Seaman et al, 2017). These examples also include research focusing on extracting information related to pain management, ranging from risk identification to the evaluation of analgesic effect or pain prevalence (Nomura et al, 2021).…”

“…This indicates that increasing nurse competence and resources may improve the benefits of both primary and secondary use of EHR data. (Seaman et al, 2017). Automated data extraction methods would therefore highly benefit from the introduction of NLP to support the secondary use of EHR data.…”

“…In the intensive care setting, efforts to use EHR data when manually extracting information on care quality are showing encouraging results. A study by Seaman et al ( 2017 ) showed that combining structured and free text entries describing selected quality outcome measures provided accurate information on quality. The included measures were heavy sedation, use of physical restraints, presence and intensity of pain, unplanned extubation and pressure injuries.…”