A Retrospective Study of Physiological Observation-reporting Practices and the Recognition, Response, and Outcomes Following Cardiopulmonary Arrest in a Low-to-middle-income Country

Health care workers' experiences of calling-for-help when taking care of critically ill patients in hospitals in Tanzania and Kenya

BACKGROUND

When caring for critically ill patients, health workers often need to 'call-for-help' to get assistance from colleagues in the hospital. Systems are required to facilitate calling-for-help and enable the timely provision of care for critically ill patients. Evidence around calling-for-help systems is mostly from high income countries and the state of calling-for-help in hospitals in Tanzania and Kenya has not been formally studied. This study aims to describe health workers' experiences about calling-for-help when taking care of critically ill patients in hospitals in Tanzania and Kenya.

METHODS

Ten hospitals across Kenya and Tanzania were visited and in-depth interviews conducted with 30 health workers who had experience of caring for critically ill patients. The interviews were transcribed, translated and the data thematically analyzed.

RESULTS

The study identified three thematic areas concerning the systems for calling-for-help when taking care of critically ill patients: 1) Calling-for-help structures: there is lack of functioning structures for calling-for-help; 2) Calling-for-help processes: the calling-for-help processes are innovative and improvised; and 3) Calling-for-help outcomes: the help that is provided is not as requested.

CONCLUSION

Calling-for-help when taking care of a critically ill patient is a necessary life-saving part of care, but health workers in Tanzanian and Kenyan hospitals experience a range of significant challenges. Hospitals lack functioning structures, processes for calling-for-help are improvised and help that is provided is not as requested. These challenges likely cause delays and decrease the quality of care, potentially resulting in unnecessary mortality and morbidity.

Recognising the deterioration of patients in acute care wards: a qualitative study

Background: Infrastructure, equipment and staff constraints are often cited as barriers to the recognition and rescue of deteriorating patients in resource-limited settings. The impact of health-system organisation, decision-making and organisational culture on recognition of deterioration is however poorly understood. This study explores how health care providers recognise deterioration of patients in acute care in Sri Lanka. Methods: In-depth interviews exploring decision making and care processes related to recognition of deterioration, were conducted with a purposive sample of 23 health care workers recruited from ten wards at a district hospital in Sri Lanka. Interviews were audio-recorded, transcribed and coded thematically, line-by-line, using a general inductive approach. Results: A legacy of initial assessment on admission and inimical organisational culture undermined recognition of deteriorating patients in hospital. Informal triaging at the time of ward admission resulted in patients presenting with red-flag diagnoses and vital sign derangement requiring resuscitation being categorised as "bad". The legacy of this categorisation was a series of decision-making biases anchored in the initial assessment, which remained with the patient throughout their stay. Management for patients categorised as "bad" was prioritised by healthcare workers coupled with a sense of fatalism regarding adverse outcomes. Health care workers were reluctant to deviate from the original plan of care despite changes in patient condition (continuation bias). Organisational culture - vertical hierarchy, siloed working and a reluctance to accept responsibility- resulted in omissions which undermined recognition of deterioration. Fear of blame was a barrier to learning from adverse events. Conclusions: The legacy of admission assessment and hospital organisational culture undermined recognition of deterioration. Opportunities for improving recognition of deterioration in this setting may include establishing formal triage and medical emergency teams to facilitate timely recognition and escalation.

Recognising the deterioration of patients in acute care wards: a qualitative study

Background: Infrastructure, equipment and staff constraints are often cited as barriers to the recognition and rescue of deteriorating patients in resource-limited settings. The impact of health-system organisation, decision-making and organisational culture on recognition of deterioration is however poorly understood. This study explores how health care providers recognise deterioration of patients in acute care in Sri Lanka. Methods: In-depth interviews exploring decision making and care processes related to recognition of deterioration, were conducted with a purposive sample of 23 health care workers recruited from ten wards at a district hospital in Sri Lanka. Interviews were audio-recorded, transcribed and coded thematically, line-by-line, using a general inductive approach. Results: A legacy of initial assessment on admission and inimical organisational culture undermined recognition of deteriorating patients in hospital. Informal triaging at the time of ward admission resulted in patients presenting with red-flag diagnoses and vital sign derangement requiring resuscitation being categorised as "bad". The legacy of this categorisation was a series of decision-making biases anchored in the initial assessment, which remained with the patient throughout their stay. Management for patients categorised as “bad” was prioritised by healthcare workers coupled with a sense of fatalism regarding adverse outcomes. Health care workers were reluctant to deviate from the original plan of care despite changes in patient condition (continuation bias). Organisational culture - vertical hierarchy, siloed working and a reluctance to accept responsibility- resulted in omissions which undermined recognition of deterioration. Fear of blame was a barrier to learning from adverse events. Conclusions: The legacy of admission assessment and hospital organisational culture undermined recognition of deterioration. Opportunities for improving recognition of deterioration in this setting may include establishing formal triage and medical emergency teams to facilitate timely recognition and escalation.

Addressing the information deficit in global health: lessons from a digital acute care platform in Sri Lanka

Lack of investment in low-income and middle-income countries (LMICs) in systems capturing continuous information regarding care of the acutely unwell patient is hindering global efforts to address inequalities, both at facility and national level. Furthermore, this of lack of data is disempowering frontline staff and those seeking to support them, from progressing setting-relevant research and quality improvement. In contrast to high-income country (HIC) settings, where electronic surveillance has boosted the capability of governments, clinicians and researchers to engage in service-wide healthcare evaluation, healthcare information in resource-limited settings remains almost exclusively paper based. In this practice paper, we describe the efforts of a collaboration of clinicians, administrators, researchers and healthcare informaticians working in South Asia, in addressing the inequality in access to patient information in acute care. Harnessing a clinician-led collaborative approach to design and evaluation, we have implemented a national acute care information platform in Sri Lanka that is tailored to priorities of frontline staff. Iterative adaptation has ensured the platform has the flexibility to integrate with legacy paper systems, support junior team members in advocating for acutely unwell patients and has made information captured accessible to diverse stakeholders to improve service delivery. The same platform is now empowering clinicians to participate in international research and drive forwards improvements in care. During this journey, we have also gained insights on how to overcome well-described barriers to implementation of digital information tools in LMIC. We anticipate that this north-south collaborative approach to addressing the challenges of health system implementation in acute care may provide learning and inspiration to other partnerships seeking to engage in similar work.

Evaluation of the feasibility and performance of early warning scores to identify patients at risk of adverse outcomes in a low-middle income country setting

OBJECTIVE

This study describes the availability of core parameters for Early Warning Scores (EWS), evaluates the ability of selected EWS to identify patients at risk of death or other adverse outcome and describes the burden of triggering that front-line staff would experience if implemented.

DESIGN

Longitudinal observational cohort study.

SETTING

District General Hospital Monaragala.

PARTICIPANTS

All adult (age >17 years) admitted patients.

MAIN OUTCOME MEASURES

Existing physiological parameters, adverse outcomes and survival status at hospital discharge were extracted daily from existing paper records for all patients over an 8-month period.

STATISTICAL ANALYSIS

Discrimination for selected aggregate weighted track and trigger systems (AWTTS) was assessed by the area under the receiver operating characteristic (AUROC) curve.Performance of EWS are further evaluated at time points during admission and across diagnostic groups. The burden of trigger to correctly identify patients who died was evaluated using positive predictive value (PPV).

RESULTS

Of the 16 386 patients included, 502 (3.06%) had one or more adverse outcomes (cardiac arrests, unplanned intensive care unit admissions and transfers). Availability of physiological parameters on admission ranged from 90.97% (95% CI 90.52% to 91.40%) for heart rate to 23.94% (95% CI 23.29% to 24.60%) for oxygen saturation. Ability to discriminate death on admission was less than 0.81 (AUROC) for all selected EWS. Performance of the best performing of the EWS varied depending on admission diagnosis, and was diminished at 24 hours prior to event. PPV was low (10.44%).

CONCLUSION

There is limited observation reporting in this setting. Indiscriminate application of EWS to all patients admitted to wards in this setting may result in an unnecessary burden of monitoring and may detract from clinician care of sicker patients. Physiological parameters in combination with diagnosis may have a place when applied on admission to help identify patients for whom increased vital sign monitoring may not be beneficial. Further research is required to understand the priorities and cues that influence monitoring of ward patients.

TRIAL REGISTRATION NUMBER

NCT02523456.

Simplified prognostic model for critically ill patients in resource limited settings in South Asia

BACKGROUND

Current critical care prognostic models are predominantly developed in high-income countries (HICs) and may not be feasible in intensive care units (ICUs) in lower- and middle-income countries (LMICs). Existing prognostic models cannot be applied without validation in LMICs as the different disease profiles, resource availability, and heterogeneity of the population may limit the transferability of such scores. A major shortcoming in using such models in LMICs is the unavailability of required measurements. This study proposes a simplified critical care prognostic model for use at the time of ICU admission.

METHODS

This was a prospective study of 3855 patients admitted to 21 ICUs from Bangladesh, India, Nepal, and Sri Lanka who were aged 16 years and over and followed to ICU discharge. Variables captured included patient age, admission characteristics, clinical assessments, laboratory investigations, and treatment measures. Multivariate logistic regression was used to develop three models for ICU mortality prediction: model 1 with clinical, laboratory, and treatment variables; model 2 with clinical and laboratory variables; and model 3, a purely clinical model. Internal validation based on bootstrapping (1000 samples) was used to calculate discrimination (area under the receiver operating characteristic curve (AUC)) and calibration (Hosmer-Lemeshow C-Statistic; higher values indicate poorer calibration). Comparison was made with the Acute Physiology and Chronic Health Evaluation (APACHE) II and Simplified Acute Physiology Score (SAPS) II models.

RESULTS

Model 1 recorded the respiratory rate, systolic blood pressure, Glasgow Coma Scale (GCS), blood urea, haemoglobin, mechanical ventilation, and vasopressor use on ICU admission. Model 2, named TropICS (Tropical Intensive Care Score), included emergency surgery, respiratory rate, systolic blood pressure, GCS, blood urea, and haemoglobin. Model 3 included respiratory rate, emergency surgery, and GCS. AUC was 0.818 (95% confidence interval (CI) 0.800-0.835) for model 1, 0.767 (0.741-0.792) for TropICS, and 0.725 (0.688-0.762) for model 3. The Hosmer-Lemeshow C-Statistic p values were less than 0.05 for models 1 and 3 and 0.18 for TropICS. In comparison, when APACHE II and SAPS II were applied to the same dataset, AUC was 0.707 (0.688-0.726) and 0.714 (0.695-0.732) and the C-Statistic was 124.84 (p < 0.001) and 1692.14 (p < 0.001), respectively.

CONCLUSION

This paper proposes TropICS as the first multinational critical care prognostic model developed in a non-HIC setting.