We don't talk about communication: why technology alone cannot save clinically deteriorating patients

Listen to me, I really am sick! Patient and family narratives of clinical deterioration before and during rapid response system intervention

AIM

To explore patient and family narratives about their recognition and response to clinical deterioration and their interactions with clinicians prior to and during Medical Emergency Team (MET) activations in hospital.

BACKGROUND

Research on clinical deterioration has mostly focused on clinicians' roles. Although patients and families can identify subtle cues of early deterioration, little research has focused on their experience of recognising, speaking up and communicating with clinicians during this period of instability.

DESIGN

A narrative inquiry.

METHODS

Using narrative interviewing techniques, 33 adult patients and 14 family members of patients, who had received a MET call, in one private and one public academic teaching hospital in Melbourne, Australia were interviewed. Narrative analysis was conducted on the data.

RESULTS

The core story of help seeking for recognition and response by clinicians to patient deterioration yielded four subplots: (1) identifying deterioration, recognition that something was not right and different from earlier; (2) voicing concerns to their nurse or by family members on their behalf; (3) being heard, desiring a response acknowledging the legitimacy of their concerns; and (4) once concerns were expressed, there was an expectation of and trust in clinicians to act on the concerns and manage the situation.

CONCLUSION

Clinical deterioration results in an additional burden for hospitalised patients and families to speak up, seek help and resolve their concerns. Educating patients and families on what to be concerned about and when to notify staff requires a close partnership with clinicians.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

Clinicians must create an environment that enables patients and families to speak up. They must be alert to both subjective and objective information, to acknowledge and to act on the information accordingly.

REPORTING METHOD

The consolidated criteria for reporting qualitative research (COREQ) guidelines were used for reporting.

PATIENT OR PUBLIC CONTRIBUTION

The consumer researcher was involved in design, data analysis and publication preparation.

General ward nurses detection and response to clinical deterioration in three hospitals at the Kenyan coast: a convergent parallel mixed methods study

BACKGROUND

In low and middle-income countries like Kenya, critical care facilities are limited, meaning acutely ill patients are managed in the general wards. Nurses in these wards are expected to detect and respond to patient deterioration to prevent cardiac arrest or death. This study examined nurses' vital signs documentation practices during clinical deterioration and explored factors influencing their ability to detect and respond to deterioration.

METHODS

This convergent parallel mixed methods study was conducted in the general medical and surgical wards of three hospitals in Kenya's coastal region. Quantitative data on the extent to which the nurses monitored and documented the vital signs 24 h before a cardiac arrest (death) occurred was retrieved from patients' medical records. In-depth, semi-structured interviews were conducted with twenty-four purposefully drawn registered nurses working in the three hospitals' adult medical and surgical wards.

RESULTS

This study reviewed 405 patient records and found most of the documentation of the vital signs was done in the nursing notes and not the vital signs observation chart. During the 24 h prior to death, respiratory rate was documented the least in only 1.2% of the records. Only a very small percentage of patients had any vital event documented for all six-time points, i.e. four hourly. Thematic analysis of the interview data identified five broad themes related to detecting and responding promptly to deterioration. These were insufficient monitoring of vital signs linked to limited availability of equipment and supplies, staffing conditions and workload, lack of training and guidelines, and communication and teamwork constraints among healthcare workers.

CONCLUSION

The study showed that nurses did not consistently monitor and record vital signs in the general wards. They also worked in suboptimal ward environments that do not support their ability to promptly detect and respond to clinical deterioration. The findings illustrate the importance of implementation of standardised systems for patient assessment and alert mechanisms for deterioration response. Furthermore, creating a supportive work environment is imperative in empowering nurses to identify and respond to patient deterioration. Addressing these issues is not only beneficial for the nurses but, more importantly, for the well-being of the patients they serve.

Receive, Sustain, and Flow: A simple heuristic for facilitating the identification and treatment of critically ill patients during their hospital journeys

Background

Hospital patients can become critically ill anywhere in a hospital but their survival is affected by problems of identification and adequate, timely, treatment. This is issue of particular concern in lower middle-income countries' (LMICs) hospitals where specialised units are scarce and severely under-resourced. "Cross-sectional" approaches to improving narrow, specific aspects of care will not attend to issues that affect patients' care across the length of their experience. A simpler approach to understanding key issues across the "hospital journey" could help to deliver life-saving treatments to those patients who need it, wherever they are in the facility.

Methods

We carried out 31 narrative interviews with frontline health workers in five Kenyan and five Tanzanian hospitals from November 2020 to December 2021 during the COVID-19 pandemic and analysed using a thematic analysis approach. We also followed 12 patient hospital journeys, through the course of treatment of very sick patients admitted to the hospitals we studied.

Results

Our research explores gaps in hospital systems that result in lapses in effective, continuous care across the hospital journeys of patients in Tanzania and Kenya. We organise these factors according to the Systems Engineering Initiative for Patient Safety (SEIPS) approach to patient safety, which we extend to explore how these issues affect patients across the course of care. We discern three repeating, recursive phases we term Receive, Sustain, and Flow. We use this heuristic to show how gaps and weaknesses in service provision affect critically ill patients' hospital journeys.

Conclusion

Receive, Sustain, and Flow offers a heuristic for hospital management to identify and ameliorate limitations in human and technical resources for the care of the critically ill.

Vital signs-based deterioration prediction model assumptions can lead to losses in prediction performance

OBJECTIVE

Vital signs-based models are complicated by repeated measures per patient and frequently missing data. This paper investigated the impacts of common vital signs modeling assumptions during clinical deterioration prediction model development.

STUDY DESIGN AND SETTING

Electronic medical record (EMR) data from five Australian hospitals (1 January 2019-31 December 2020) were used. Summary statistics for each observation's prior vital signs were created. Missing data patterns were investigated using boosted decision trees, then imputed with common methods. Two example models predicting in-hospital mortality were developed, as follows: logistic regression and eXtreme Gradient Boosting. Model discrimination and calibration were assessed using the C-statistic and nonparametric calibration plots.

RESULTS

The data contained 5,620,641 observations from 342,149 admissions. Missing vitals were associated with observation frequency, vital sign variability, and patient consciousness. Summary statistics improved discrimination slightly for logistic regression and markedly for eXtreme Gradient Boosting. Imputation method led to notable differences in model discrimination and calibration. Model calibration was generally poor.

CONCLUSION

Summary statistics and imputation methods can improve model discrimination and reduce bias during model development, but it is questionable whether these differences are clinically significant. Researchers should consider why data are missing during model development and how this may impact clinical utility.