Electronic Health Record Use in Swiss Nursing Homes and Its Association With Implicit Rationing of Nursing Care Documentation: Multicenter Cross-sectional Survey Study

Association between health literacy and nursing care in hospital: A retrospective study

AIMS

To describe the health literacy (HL) levels of hospitalised patients and their relationship with nursing diagnoses (NDs), nursing interventions and nursing measures for clinical risks.

DESIGN

Retrospective study.

METHODS

The study was conducted from December 2020 to December 2021 in an Italian university hospital. From 146 wards, 1067 electronic nursing records were randomly selected. The Single-Item Literacy Screener was used to measure HL. Measures for clinical risks were systematically assessed by nurses using Conley Index score, the Blaylock Risk Assessment Screening Score, Braden score, and the Barthel Index. A univariable linear regression model was used to assess the associations of HL with NDs.

RESULTS

Patients with low HL reported a higher number of NDs, interventions and higher clinical risks. HL can be considered a predictor of complexity of care.

CONCLUSIONS

The inclusion of standardised terms in nursing records can describe the complexity of care and facilitate the predictive ability on hospital outcomes.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

HL evaluation during the first 24 h. From hospital admission could help to intercept patients at risk of higher complexity of care. These results can guide the development of interventions to minimise needs after discharge.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution was required to design or undertake this research. Patients contributed only to the data collection.

Administrative burden in Swiss nursing homes and its association with care workers' outcomes-a multicenter cross-sectional study

BACKGROUND

Care workers in nursing homes often perform tasks that are rather related to organizational or management activities than 'direct patient care'. 'Indirect care activities', such as documentation or other administrative tasks are often considered by care workers as a burden, as they increase overall workload and keep them away from caring for residents. So far, there is little investigation into what kind of administrative tasks are being performed in nursing homes, by which type of care workers, and to which extent, nor how administrative burden is associated with care workers' outcomes.

PURPOSE

The objective of this study was to describe care workers' administrative burden in Swiss nursing homes and to explore the association with four care worker outcomes (i.e., job dissatisfaction, emotional exhaustion, intention to leave the current job and the profession).

METHODS

This multicenter cross-sectional study used survey data from the Swiss Nursing Homes Human Resources Project 2018. It included a convenience sample of 118 nursing homes and 2'207 care workers (i.e., registered nurses, licensed practical nurses) from Switzerland's German- and French-speaking regions. Care workers completed questionnaires assessing the administrative tasks and burden, staffing and resource adequacy, leadership ability, implicit rationing of nursing care and care worker characteristics and outcomes. For the analysis, we applied generalized linear mixed models, including individual-level nurse survey data and data on unit and facility characteristics.

RESULTS

Overall, 73.9% (n = 1'561) of care workers felt strongly or rather strongly burdened, with one third (36.6%, n = 787) reporting to spend 2 h or more during a "normal" day performing administrative tasks. Ratings for administrative burden ranged from 42.6% (n = 884; ordering supplies and managing stocks) to 75.3% (n = 1'621; filling out the resident's health record). One out of four care workers (25.5%, n = 561) intended to leave the profession, whereby care workers reporting higher administrative task burden (OR = 1.24; 95%CI: 1.02-1.50) were more likely to intend to leave the profession.

CONCLUSION

This study provides first insights on care workers' administrative burden in nursing homes. By limiting care workers' burdensome administrative tasks and/or shifting such tasks from higher to lower educated care workers or administrative personnel when appropriate, nursing home managers could reduce care workers' workload and improve their job satisfaction and retention in the profession.

The experience of nurses to reduce implicit rationing of nursing care: a phenomenological study

BACKGROUND

Implicit rationing of nursing care can adversely affect patient safety and the quality of care, and increase nurses' burnout and turnover tendency. Implicit rationing care occurs at the nurse-to-patient level (micro-level), and nurses are direct participants. Therefore, the strategies based on experience of nurses to reduce implicit rationing care have more reference value and promotion significance. The aim of the study is to explore the experience of nurses to reduce implicit rationing care, thereby to provide references for conducting randomized controlled trials to reduce implicit rationing care.

METHODS

This is a descriptive phenomenological study. Purpose sampling was conducted nationwide. There are 17 nurses were selected and semi-structured in-depth interviews were conducted. The interviews were recorded, transcribed verbatim and analyzed via thematic analysis.

RESULTS

Our study found that nurses' reported experience of coping with implicit rationing of nursing care contained three aspects: personal, resource, and managerial. Three themes were extracted from the results of the study: (1) improving personal literacy; (2) supplying and optimizing resources and (3) standardizing management mode. The improvement of nurses' own qualities are the prerequisites, the supply and optimization of resources is an effective strategy, and clear scope of work has attracted the attention of nurses.

CONCLUSION

The experience of dealing with implicit nursing rationing includes many aspects. Nursing managers should be grounded in nurses' perspectives when developing strategies to reduce implicit rationing of nursing care. Promoting the improvement of nurses' skills, improving staffing level and optimizing scheduling mode are promising measures to reduce hidden nursing rationing.

Defining the concepts of a smart nursing home and its potential technology utilities that integrate medical services and are acceptable to stakeholders: a scoping review

BACKGROUND AND OBJECTIVES

Smart technology in nursing home settings has the potential to elevate an operation that manages more significant number of older residents. However, the concepts, definitions, and types of smart technology, integrated medical services, and stakeholders' acceptability of smart nursing homes are less clear. This scoping review aims to define a smart nursing home and examine the qualitative evidence on technological feasibility, integration of medical services, and acceptability of the stakeholders.

METHODS

Comprehensive searches were conducted on stakeholders' websites (Phase 1) and 11 electronic databases (Phase 2), for existing concepts of smart nursing home, on what and how technologies and medical services were implemented in nursing home settings, and acceptability assessment by the stakeholders. The publication year was inclusive from January 1999 to September 2021. The language was limited to English and Chinese. Included articles must report nursing home settings related to older adults ≥ 60 years old with or without medical demands but not bed-bound. Technology Readiness Levels were used to measure the readiness of new technologies and system designs. The analysis was guided by the Framework Method and the smart technology adoption behaviours of elder consumers theoretical model. The results were reported according to the PRISMA-ScR.

RESULTS

A total of 177 literature (13 website documents and 164 journal articles) were selected. Smart nursing homes are technology-assisted nursing homes that allow the life enjoyment of their residents. They used IoT, computing technologies, cloud computing, big data and AI, information management systems, and digital health to integrate medical services in monitoring abnormal events, assisting daily living, conducting teleconsultation, managing health information, and improving the interaction between providers and residents. Fifty-five percent of the new technologies were ready for use in nursing homes (levels 6-7), and the remaining were proven the technical feasibility (levels 1-5). Healthcare professionals with higher education, better tech-savviness, fewer years at work, and older adults with more severe illnesses were more acceptable to smart technologies.

CONCLUSIONS

Smart nursing homes with integrated medical services have great potential to improve the quality of care and ensure older residents' quality of life.

Prevalence, type, and reasons for missed nursing care in municipality health care in Sweden – A cross sectional study

Background

With an ageing population, there is an increasing need for care, both as home care and in nursing homes. However, some needed care is not carried out for different reasons, which can affect patient safety. The aim of the study was to describe prevalence, type, and reasons for missed nursing care in home care and nursing homes, from nurses’ perspective.

Methods

A cross sectional design with quantitative and qualitative approach. A Swedish version of Basel Extent of Rationing of Nursing Care for nursing homes and 15 study specific questions were answered by 624 registered nurses, enrolled nurses, or nurse assistants. Both descriptive and analytical, independent-samples t-test, analyses were used. Qualitative content analysis was used for the open-ended question.

Results

The care activity most often missed in home care was: ‘set up or update care plans’ (41.8%), and in nursing homes: ‘scheduled group activity’ (22.8%). Reasons for missed nursing care were lack of preparedness for unexpected situations, obstacles in a deficient work environment, unsatisfactory planning in the organisation, and/or shortcomings related to the individual.

Conclusion

Not all care activities needed are performed, due to reasons such as lack of time or organisational issues. Missed nursing care can lead to adverse events and affect patient safety. It is important to be aware of missed nursing care and the reasons for it, which gives a possibility to initiate quality improvement work to ensure patient safety.

Stroke Outcome Measurements From Electronic Medical Records: Cross-sectional Study on the Effectiveness of Neural and Nonneural Classifiers

BACKGROUND

With the rapid adoption of electronic medical records (EMRs), there is an ever-increasing opportunity to collect data and extract knowledge from EMRs to support patient-centered stroke management.

OBJECTIVE

This study aims to compare the effectiveness of state-of-the-art automatic text classification methods in classifying data to support the prediction of clinical patient outcomes and the extraction of patient characteristics from EMRs.

METHODS

Our study addressed the computational problems of information extraction and automatic text classification. We identified essential tasks to be considered in an ischemic stroke value-based program. The 30 selected tasks were classified (manually labeled by specialists) according to the following value agenda: tier 1 (achieved health care status), tier 2 (recovery process), care related (clinical management and risk scores), and baseline characteristics. The analyzed data set was retrospectively extracted from the EMRs of patients with stroke from a private Brazilian hospital between 2018 and 2019. A total of 44,206 sentences from free-text medical records in Portuguese were used to train and develop 10 supervised computational machine learning methods, including state-of-the-art neural and nonneural methods, along with ontological rules. As an experimental protocol, we used a 5-fold cross-validation procedure repeated 6 times, along with subject-wise sampling. A heatmap was used to display comparative result analyses according to the best algorithmic effectiveness (F1 score), supported by statistical significance tests. A feature importance analysis was conducted to provide insights into the results.

RESULTS

The top-performing models were support vector machines trained with lexical and semantic textual features, showing the importance of dealing with noise in EMR textual representations. The support vector machine models produced statistically superior results in 71% (17/24) of tasks, with an F1 score >80% regarding care-related tasks (patient treatment location, fall risk, thrombolytic therapy, and pressure ulcer risk), the process of recovery (ability to feed orally or ambulate and communicate), health care status achieved (mortality), and baseline characteristics (diabetes, obesity, dyslipidemia, and smoking status). Neural methods were largely outperformed by more traditional nonneural methods, given the characteristics of the data set. Ontological rules were also effective in tasks such as baseline characteristics (alcoholism, atrial fibrillation, and coronary artery disease) and the Rankin scale. The complementarity in effectiveness among models suggests that a combination of models could enhance the results and cover more tasks in the future.

CONCLUSIONS

Advances in information technology capacity are essential for scalability and agility in measuring health status outcomes. This study allowed us to measure effectiveness and identify opportunities for automating the classification of outcomes of specific tasks related to clinical conditions of stroke victims, and thus ultimately assess the possibility of proactively using these machine learning techniques in real-world situations.