Designing paper-based records to improve the quality of nursing documentation in hospitals: A scoping review

A quality improvement initiative to reduce the time to initial maternal visit in the neonatal intensive care unit

OBJECTIVE

We aimed to reduce the time interval between an infant's admission to the Neonatal Intensive Care Unit (NICU) and first maternal interaction.

METHODS

We identified three key drivers: 1. Collaboration with Labor and Delivery, 2. Education of staff and parents, and 3. Improved documentation of maternal presence. We measured the time interval from NICU admission to the initial maternal presence. We followed length of stay as a balancing measure to assay whether use of remote televisitation impeded efficient parental teaching and delayed discharge.

RESULTS

We reduced the time interval from an average of 19.7 h in February 2020 to 12.3 h in June 2021. We expanded an already existing televisitation program as a surrogate to in-person interaction during COVID-19 pandemic. Televisitation did not affect in-person parental presence or LOS.

CONCLUSION

Our multidisciplinary efforts resulted in a significantly accelerated time to initial maternal presence and did not prolong LOS.

Scoping review of interventions to improve continuity of postdischarge care for newborns in LMICs

INTRODUCTION

Neonatal mortality remains significant in low-income and middle-income countries (LMICs) with in-hospital mortality rates similar to those following discharge from healthcare facilities. Care continuity interventions have been suggested as a way of reducing postdischarge mortality by better linking care between facilities and communities. This scoping review aims to map and describe interventions used in LMICs to improve care continuity for newborns after discharge and examine assumptions underpinning the design and delivery of continuity.

METHODS

We searched seven databases (MEDLINE, CINAHL, Scopus, Web of Science, EMBASE, Cochrane library and (Ovid) Global health). Publications with primary data on interventions focused on continuity of care for newborns in LMICs were included. Extracted data included year of publication, study location, study design and type of intervention. Drawing on relevant theoretical frameworks and classifications, we assessed the extent to which interventions adopted participatory methods and how they attempted to establish continuity.

RESULTS

A total of 65 papers were included in this review; 28 core articles with rich descriptions were prioritised for more in-depth analysis. Most articles adopted quantitative designs. Interventions focused on improving continuity and flow of information via education sessions led by community health workers during home visits. Extending previous frameworks, our findings highlight the importance of interpersonal continuity in LMICs where communication and relationships between family members, healthcare workers and members of the wider community play a vital role in creating support systems for postdischarge care. Only a small proportion of studies focused on high-risk babies. Some studies used participatory methods, although often without meaningful engagement in problem definition and intervention implementation.

CONCLUSION

Efforts to reduce neonatal mortality and morbidity should draw across multiple continuity logics (informational, relational, interpersonal and managerial) to strengthen care after hospital discharge in LMIC settings and further focus on high-risk neonates, as they often have the worst outcomes.

Standardized Comparison of Voice-Based Information and Documentation Systems to Established Systems in Intensive Care: Crossover Study

BACKGROUND

The medical teams in intensive care units (ICUs) spend increasing amounts of time at computer systems for data processing, input, and interpretation purposes. As each patient creates about 1000 data points per hour, the available information is abundant, making the interpretation difficult and time-consuming. This data flood leads to a decrease in time for evidence-based, patient-centered care. Information systems, such as patient data management systems (PDMSs), are increasingly used at ICUs. However, they often create new challenges arising from the increasing documentation burden.

OBJECTIVE

New concepts, such as artificial intelligence (AI)-based assistant systems, are hence introduced to the workflow to cope with these challenges. However, there is a lack of standardized, published metrics in order to compare the various data input and management systems in the ICU setting. The objective of this study is to compare established documentation and retrieval processes with newer methods, such as PDMSs and voice information and documentation systems (VIDSs).

METHODS

In this crossover study, we compare traditional, paper-based documentation systems with PDMSs and newer AI-based VIDSs in terms of performance (required time), accuracy, mental workload, and user experience in an intensive care setting. Performance is assessed on a set of 6 standardized, typical ICU tasks, ranging from documentation to medical interpretation.

RESULTS

A total of 60 ICU-experienced medical professionals participated in the study. The VIDS showed a statistically significant advantage compared to the other 2 systems. The tasks were completed significantly faster with the VIDS than with the PDMS (1-tailed t59=12.48; Cohen d=1.61; P<.001) or paper documentation (t59=20.41; Cohen d=2.63; P<.001). Significantly fewer errors were made with VIDS than with the PDMS (t59=3.45; Cohen d=0.45; P=.03) and paper-based documentation (t59=11.2; Cohen d=1.45; P<.001). The analysis of the mental workload of VIDS and PDMS showed no statistically significant difference (P=.06). However, the analysis of subjective user perception showed a statistically significant perceived benefit of the VIDS compared to the PDMS (P<.001) and paper documentation (P<.001).

CONCLUSIONS

The results of this study show that the VIDS reduced error rate, documentation time, and mental workload regarding the set of 6 standardized typical ICU tasks. In conclusion, this indicates that AI-based systems such as the VIDS tested in this study have the potential to reduce this workload and improve evidence-based and safe patient care.

Evaluating the documentation of vital signs following implementation of a new comprehensive newborn monitoring chart in 19 hospitals in Kenya: A time series analysis

Multi-professional teams care for sick newborns, but nurses are the primary caregivers, making nursing care documentation essential for delivering high-quality care, fostering teamwork, and improving patient outcomes. We report on an evaluation of vital signs documentation following implementation of the comprehensive newborn monitoring chart using interrupted time series analysis and a review of filled charts. We collected post-admission vital signs (Temperature (T), Pulse (P), Respiratory Rate (R) and Oxygen Saturation (S)) documentation frequencies of 43,719 newborns with a length of stay > 48 hours from 19 public hospitals in Kenya between September 2019 and October 2021. The primary outcome was an ordinal categorical variable (no monitoring, monitoring 1 to 3 times, 4 to 7 times and 8 or more times) based on the number of complete sets of TPRS. Descriptive analyses explored documentation of at least one T, P, R and S. The percentage of patients in the no-monitoring category decreased from 68.5% to 43.5% in the post-intervention period for TPRS monitoring. The intervention increased the odds of being in a higher TPRS monitoring category by 4.8 times (p<0.001) and increased the odds of higher monitoring frequency for each vital sign, with S recording the highest odds. Sicker babies were likely to have vital signs documented in a higher monitoring category and being in the NEST360 program increased the odds of frequent vital signs documentation. However, by the end of the intervention period, nearly half of the newborns did not have a single full set of TPRS documented and there was heterogenous hospital performance. A review of 84 charts showed variable documentation, with only one chart being completed as designed. Vital signs documentation fell below standards despite increased documentation odds. More sustained interventions are required to realise the benefits of the chart and hospital-specific performance data may help customise interventions.

Diagnostic accuracy study of the VALENF instrument in hospitalization units for adults: a study protocol

Recently, the VALENF instrument, Nursing Assessment by its acronym in Spanish, was developed as a meta-tool composed of only seven items with a more parsimonious approach for nursing assessment in adult hospitalization units. This meta-tool integrates the assessment of functional capacity, the risk of pressure injuries and the risk of falls. The general objective of this project is to validate the VALENF instrument by studying its diagnostic accuracy against the instruments commonly used in nursing to assess functional capacity, the risk of pressure injuries and the risk of falls. An observational, longitudinal, prospective study is presented, with recruitment and random selection based on admissions to six adult hospitalization units of the Hospital Universitario de La Plana. The study population will be made up of patients hospitalized in these units. The inclusion criteria will be patients over 18 years of age with a nursing assessment within the first 24 h of admission and an expected length of stay greater than 48 h and who sign the informed consent form. The exclusion criteria will be transfers from other units or centers. A sample of 521 participants is estimated as necessary. The evaluation test will be the VALENF instrument, and the reference tests will be the Barthel, Braden and Downton indices. Sociodemographic variables related to the care process and results such as functional loss, falls or pressure injuries will be collected. The evolution of functional capacity, the risk of falls and the risk of pressure injuries will be analyzed. The sensitivity, specificity and positive predictive values of the VALENF instrument will be calculated and compared to those of the usual instruments. A survival analysis will be performed for pressure injuries, falls and patients with functional loss. The VALENF instrument is expected to have at least the same diagnostic validity as the original instruments.Trial registration The study will be retrospectively registered (ISRCTN 17699562, 25/07/2023).

Improving Nursing Assessment in Adult Hospitalization Units: A Secondary Analysis

The main objective of this study was to analyze the impact of a multifaceted strategy to improve the assessment of functional capacity, risk of pressure injuries, and risk of falls at the time of admission of patients in adult hospitalization units. This was a secondary analysis of the VALENF project databases during two periods (October-December 2020, before the strategy, and October-December 2021, after the strategy). The quantity and quality of nursing assessments performed on patients admitted to adult hospitalization units were evaluated using the Barthel index, Braden index, and Downton scale. The number of assessments completed before the implementation of the new strategy was n = 686 (28.01%), versus n = 1445 (58.73%) in 2021 (p < 0.001). The strategy improved the completion of the evaluations of the three instruments from 63.4% (n = 435) to 71.8% (n = 1038) (p < 0.001). There were significant differences depending on the hospitalization unit and the assessment instrument (p < 0.05). The strategy employed was, therefore, successful. The nursing assessments show a substantial improvement in both quantity and quality, representing a noticeable improvement in nursing practice. This study was not registered.

'Paper care not patient care': Nurse and patient experiences of comprehensive risk assessment and care plan documentation in hospital

AIMS AND OBJECTIVES

To explore organisation-wide experiences of person-centred care and risk assessment practices using existing healthcare organisation documentation.

BACKGROUND

There is increasing emphasis on multidimensional risk assessments during hospital admission. However, little is known about how nurses use multidimensional assessment documentation in clinical practice to address preventable harms and optimise person-centred care.

DESIGN

A qualitative descriptive study reported according to COREQ.

METHODS

Metropolitan tertiary hospital and rehabilitation hospital servicing a population of 550,000. A sample of 111 participants (12 patients, 4 family members/carers, 94 nurses and 1 allied health professional) from a range of wards/clinical locations. Semi-structured interviews and focus groups were conducted at two time points. The audio recording was transcribed, and an inductive thematic analysis was used to provide insight from multiple perspectives.

RESULTS

Three main themes emerged: (1) 'What works well in practice' included: efficiency in the structure of the documentation; the Introduction, Situation, Background Assessment, Recommendation (ISBAR) framework and prompting for clinical decision-making were valued by nurses; and direct patient care is always prioritised. (2) 'What does not work well in practice': obtaining the patient's signature on daily care plans; multidisciplinary (MDT) involvement; duplication of paperwork and person-centred goals are not well-captured in care plan documentation. (3) 'Experience of care'; satisfaction of person-centred care; communication in the MDT was important, but sometimes insufficient; patients had variable involvement in their daily care plan; and inadequate integration of care between MDT team which negatively impacted patients.

CONCLUSIONS

Efficient and streamlined documentation systems should herald feedback from nurses to address their clinical workflow needs and can support, and capture, their decision-making that enables partnership with patients to improve the individualisation of care provision.

RELEVANCE TO CLINICAL PRACTICE

The integration of effective MDT involvement in clinical documentation was problematic and resulted in unmet supportive care from the patient's perspective.

Development and Validation of a Meta-Instrument for Nursing Assessment in Adult Hospitalization Units (VALENF Instrument) (Part I)

Nursing assessment is the basis for performing interventions that match patient needs, but nurses perceive it as an administrative load. This research aims to develop and validate a meta-instrument that integrates the assessment of functional capacity, risk of pressure ulcers and risk of falling with a more parsimonious approach to nursing assessment in adult hospitalization units. Specifically, this manuscript presents the results of the development of this meta-instrument (VALENF instrument). A cross-sectional study based on recorded data was carried out in a sample of 1352 nursing assessments. Socio-demographic variables and assessments of Barthel, Braden and Downton indices at the time of admission were included. The meta-instrument's development process includes: (i) nominal group; (ii) correlation analysis; (iii) multiple linear regressions models; (iv) reliability analysis. A seven-item solution showed a high predictive capacity with Barthel (R2adj = 0.938), Braden (R2adj = 0.926) and Downton (R2adj = 0.921) indices. Likewise, reliability was significant (p < 0.001) for Barthel (ICC = 0.969; τ-b = 0.850), Braden (ICC = 0.943; τ-b = 0.842) and Downton (ICC = 0.905; κ = 7.17) indices. VALENF instrument has an adequate predictive capacity and reliability to assess the level of functional capacity, risk of pressure injuries and risk of falls.

Clinical Coders' Perspectives on Pressure Injury Coding in Acute Care Services in Victoria, Australia

Pressure injuries (PIs) substantively impact quality of care during hospital stays, although only when they are severe or acquired as a result of the hospital stay are they reported as quality indicators. Globally, researchers have repeatedly highlighted the need to invest more in quality improvement, risk assessment, prevention, early detection, and care for PI to avoid the higher costs associated with treatment of PI. Coders' perspectives on quality assurance of the clinical coded PI data have never been investigated. This study aimed to explore challenges that hospital coders face in accurately coding and reporting PI data and subsequently, explore reasons why data sources may vary in their reporting of PI data. This article is based upon data collected as part of a multi-phase collaborative project to build capacity for optimizing PI prevention across Monash Partners health services. We have conducted 16 semi-structured phone interviews with clinical coders recruited from four participating health services located in Melbourne, Australia. One of the main findings was that hospital coders often lacked vital information in clinicians' records needed to code PI and report quality indicators accurately and highlighted the need for quality improvement processes for PI clinical documentation. Nursing documentation improvement is a vital component of the complex capacity building programs on PI prevention in acute care services and is relied on by coders. Coders reported the benefit of inter-professional collaborative workshops, where nurses and coders shared their perspectives. Collaborative workshops had the potential to improve coders' knowledge of PI classification and clinicians' understanding of what information should be included when documenting PI in the medical notes. Our findings identified three methods of quality assurance were important to coders to ensure accuracy of PI reporting: (1) training prior to initiation of coding activity and (2) continued education, and (3) audit and feedback communication about how to handle specific complex cases and complex documentation. From a behavioral perspective, most of the coders reported confidence in their own abilities and were open to changes in coding standards. Transitioning from paper-based to electronic records highlighted the need to improve training of both clinicians and coders.

[Artificial Intelligence: Challenges and Applications in Intensive Care Medicine]

The high workload in intensive care medicine arises from the exponential growth of medical knowledge, the flood of data generated by the permanent and intensive monitoring of intensive care patients, and the documentation burden. Artificial intelligence (AI) is predicted to have a great impact on ICU work in the near future as it will be applicable in many areas of critical care medicine. These applications include documentation through speech recognition, predictions for decision support, algorithms for parameter optimisation and the development of personalised intensive care medicine. AI-based decision support systems can augment human therapy decisions. Primarily through machine learning, a sub-discipline of AI, self-adaptive algorithms can learn to recognise patterns and make predictions. For actual use in clinical settings, the explainability of such systems is a prerequisite. Intensive care staff spends a large amount of their working hours on documentation, which has increased up to 50% of work time with the introduction of PDMS. Speech recognition has the potential to reduce this documentation burden. It is not yet precise enough to be usable in the clinic. The application of AI in medicine, with the help of large data sets, promises to identify diagnoses more quickly, develop individualised, precise treatments, support therapeutic decisions, use resources with maximum effectiveness and thus optimise the patient experience in the near future.

Using a human-centred design approach to develop a comprehensive newborn monitoring chart for inpatient care in Kenya

Introduction

Job aids such as observation charts are commonly used to record inpatient nursing observations. For sick newborns, it is important to provide critical information, intervene, and tailor treatment to improve health outcomes, as countries work towards reducing neonatal mortality. However, inpatient vital sign readings are often poorly documented and little attention has been paid to the process of chart design as a method of improving care quality. Poorly designed charts do not meet user needs leading to increased mental effort, duplication, suboptimal documentation and fragmentation. We provide a detailed account of a process of designing a monitoring chart.

Methods

We used a Human-Centred Design (HCD) approach to co-design a newborn monitoring chart between March and May 2019 in three workshops attended by 16–21 participants each (nurses and doctors) drawn from 14 hospitals in Kenya. We used personas, user story mapping during the workshops and observed chart completion to identify challenges with current charts and design requirements. Two new charts were piloted in four hospitals between June 2019 and February 2020 and revised in a cyclical manner.

Results

Challenges were identified regarding the chart design and supply, and how staff used existing charts. Challenges to use included limited staffing, a knowledge deficit among junior staff, poor interprofessional communication, and lack of appropriate and working equipment. We identified a strong preference from participants for one chart to capture vital signs, assessment of the baby, and feed and fluid prescription and monitoring; data that were previously captured on several charts.

Discussion

Adopting a Human-Centred Design approach, we designed a new comprehensive newborn monitoring chart that is unlike observation charts in the literature that only focus on vital signs. While the new chart does not address all needs, we believe that once implemented, it can help build a clearer picture of the care given to newborns.

Conclusion

The chart was co-designed and piloted with the user and context in mind resulting in a unique monitoring chart that can be adopted in similar settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07030-x.