Usability of the surprise question by nurses to identify 12-month mortality in hospitalized older patients: A prospective cohort study

The Surprise Question and clinician-predicted prognosis: systematic review and meta-analysis

BACKGROUND

The Surprise Question, 'Would you be surprised if this person died within the next year?' is a simple tool that can be used by clinicians to identify people within the last year of life. This review aimed to determine the accuracy of this assessment, across different healthcare settings, specialties, follow-up periods and respondents.

METHODS

Searches were conducted of Medline, Embase, AMED, PubMed and the Cochrane Central Register of Controlled Trials, from inception until 01 January 2024. Studies were included if they reported original data on the ability of the Surprise Question to predict survival. For each study (including subgroups), sensitivity, specificity, positive and negative predictive values and accuracy were determined.

RESULTS

Our dataset comprised 56 distinct cohorts, including 68 829 patients. In a pooled analysis, the sensitivity of the Surprise Question was 0.69 ((0.64 to 0.74) I2=97.2%), specificity 0.69 ((0.63 to 0.74) I2=99.7%), positive predictive value 0.40 ((0.35 to 0.45) I2=99.4%), negative predictive value 0.89 ((0.87 to 0.91) I2=99.7%) and accuracy 0.71 ((0.68 to 0.75) I2=99.3%). The prompt performed best in populations with high event rates, shorter timeframes and when posed to more experienced respondents.

CONCLUSIONS

The Surprise Question demonstrated modest accuracy with considerable heterogeneity across the population to which it was applied and to whom it was posed. Prospective studies should test whether the prompt can facilitate timely access to palliative care services, as originally envisioned.

PROSPERO REGISTRATION NUMBER

CRD32022298236.

The utility of the surprise question by nurses to identify hospitalised older patients nearing the end-of-life and promotion of advance care planning: An interventional study

AIMS AND OBJECTIVES

To assess the prognostic accuracy of the surprise question (SQ) when used by nurses working in hospital wards to determine 1-year mortality in acutely hospitalised older patients.

BACKGROUND

The predictive accuracy of the SQ, when used by general nurses caring for older hospitalised patients, has not been comprehensively studied.

DESIGN

A prospective cohort study.

METHODS

This cohort study recruited consecutive 10,139 older patients (aged ≥65 years) who were admitted to Taipei City Hospital and were evaluated for the needs of palliative care in 2015. All patients were followed up for 12 months or until their death. The c-statistic value was calculated to indicate the predictive accuracy of the SQ and Palliative Care Screening Tool (PCST).

RESULTS

Of all participants, 18.8% and 18.6% had a SQ response of 'no' and a PCST score ≥4, respectively. After controlling for other covariates, an SQ response of 'no' (adjusted hazard ratio [aHR], 2.05; 95% confidence interval [CI], 1.83-2.31) and a PCST score ≥4 (AHR = 1.50; 95% CI: 1.29-1.75) were found to be the independent predictors for patients' 12-month mortality. The C-statistic values of the SQ and the PCST at recognising patients in their last year of life were .663 and .670, respectively. Moreover, there was moderate concordance (k = .44) between the SQ and the PCST in predicting 12-month mortality.

CONCLUSIONS

SQ response of 'no' and a PCST score ≥4 were independent predictors of 12-month mortality in older patients.

RELEVANCE TO CLINICAL PRACTICE

The SQ, when used by nurses working in hospital wards, is effective in identifying older patients nearing the end of life, as well as in providing advance care planning for patients.

PATIENT OR PUBLIC CONTRIBUTION

Patients' palliative care needs at admission were assessed by general nurses using the SQ and PCST.

More older adults died at their preferred place after implementation of a transmural care pathway for older adults at the end of life: a before-after study

BACKGROUND

To improve transmural palliative care for older adults acutely admitted to hospital, the PalliSupport intervention, comprising an educational programme and transmural palliative care pathway, was developed. This care pathway involves timely identification of palliative care needs, advance care planning, multidisciplinary team meetings, warm handover, and follow-up home visits. With this study, we evaluate changes in patient-related outcomes and transmural collaboration after implementation of the care pathway.

METHODS

We conducted a before-after study, in which we compared 1) unplanned hospital admission and death at place of preference and 2) transmural collaboration before implementation, up to six months, and six to 18 months after implementation. Data from palliative care team consultations were collected between February 2017 and February 2020 in a teaching hospital in the Netherlands.

RESULTS

The palliative care team held 711 first-time consultations. The number of consultation, as well as the number of consultations for patients with non-malignant diseases, and consultations for advance care planning increased after implementation. The implementation of the pathway had no statistically significant effect on unplanned hospitalization but associated positively with death at place of preference more than six months after implementation (during/shortly after adjusted OR: 2.12; 95% CI: 0.84-5.35; p-value: 0.11, long term after adjusted OR: 3.14; 95% CI: 1.49-6.62; p-value: 0.003). Effects on transmural collaboration showed that there were more warm handovers during/shortly after implementation, but not on long term. Primary care professionals attended multidisciplinary team meetings more often during and shortly after implementation, but did not more than six months after implementation.

CONCLUSIONS

The pathway did not affect unplanned hospital admissions, but more patients died at their place of preference after implementation. Implementation of the pathway increased attention to- and awareness for in-hospital palliative care, but did not improve transmural collaboration on long-term. For some patients, the hospital admissions might helped in facilitating death at place of preference.

The perspectives of in-hospital healthcare professionals on the timing and collaboration in advance care planning: A survey study

Background

Hospital admissions are common in the last phase of life. However, palliative care and advance care planning (ACP) are provided late or not at all during hospital admission.

Aim

To provide insight into the perceptions of in-hospital healthcare professionals concerning current and ideal practice and roles of in-hospital palliative care and advance care planning.

Methods

An electronic cross-sectional survey was send 398 in-hospital healthcare professionals in five hospitals in the Netherlands. The survey contained 48 items on perceptions of palliative care and ACP.

Results

We included non-specialists who completed the questions of interest, resulting in analysis of 96 questionnaires. Most respondents were nurses (74%). We found that current practice for initiating palliative care and ACP was different to what is considered ideal practice. Ideally, ACP should be initiated for almost every patient for whom no treatment options are available (96.2%), and in case of progression and severe symptoms (94.2%). The largest differences between current and ideal practice were found for patients with functional decline (Current 15.2% versus Ideal 78.5%), and patients with an estimated life expectancy <1 year (Current 32.6% versus ideal 86.1%). Respondents noted that providing palliative care requires collaboration, however, especially nurses noted barriers like a lack of inter-professional consensus.

Conclusions

The differences between current and ideal practice demonstrate that healthcare professionals are willing to improve palliative care. To do this, nurses need to increase their voice, a shared vision of palliative care and recognition of the added value of working together is needed.

'End of life': a concept analysis

BACKGROUND

The concept of end of life (EOL), as in the term end-of-life care, is used synonymously in both palliative and terminal care. Practitioners and researchers both require a clearer specification of the end-of-life concept to be able to provide appropriate care in this phase of life and to conduct robust research on a well-described theoretical basis.

AIMS

The aim of this study was to critically analyse the end-of-life concept and its associated terminology.

METHOD

A concept analysis was performed by applying Rodgers' evolutionary concept analysis method.

FINDINGS

Time remaining, clinical status/physical symptoms, psychosocial symptoms and dignity were identified as the main attributes of the concept. Transition into the end-of-life phase and its recognition were identified as antecedents. This study demonstrates that end-of-life care emerged following the application of the 'end-of-life concept' to clinical practice.

CONCLUSION

The early recognition of the end-of-life phase seems to be crucial to ensuring an individual has well-managed symptoms and a dignified death.

The utility of the surprise question: A useful tool for identifying patients nearing the last phase of life? A systematic review and meta-analysis

BACKGROUND

The surprise question is widely used to identify patients nearing the last phase of life. Potential differences in accuracy between timeframe, patient subgroups and type of healthcare professionals answering the surprise question have been suggested. Recent studies might give new insights.

AIM

To determine the accuracy of the surprise question in predicting death, differentiating by timeframe, patient subgroup and by type of healthcare professional.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Electronic databases PubMed, Embase, Cochrane Library, Scopus, Web of Science and CINAHL were searched from inception till 22nd January 2021. Studies were eligible if they used the surprise question prospectively and assessed mortality. Sensitivity, specificity, negative predictive value, positive predictive value and c-statistic were calculated.

RESULTS

Fifty-nine studies met the inclusion criteria, including 88.268 assessments. The meta-analysis resulted in an estimated sensitivity of 71.4% (95% CI [66.3-76.4]) and specificity of 74.0% (95% CI [69.3-78.6]). The negative predictive value varied from 98.0% (95% CI [97.7-98.3]) to 88.6% (95% CI [87.1-90.0]) with a mortality rate of 5% and 25% respectively. The positive predictive value varied from 12.6% (95% CI [11.0-14.2]) with a mortality rate of 5% to 47.8% (95% CI [44.2-51.3]) with a mortality rate of 25%. Seven studies provided detailed information on different healthcare professionals answering the surprise question.

CONCLUSION

We found overall reasonable test characteristics for the surprise question. Additionally, this study showed notable differences in performance within patient subgroups. However, we did not find an indication of notable differences between timeframe and healthcare professionals.

Measurement Properties of ID-PALL, A New Instrument for the Identification of Patients With General and Specialized Palliative Care Needs

CONTEXT

To improve access to palliative care, identification of patients in need of general or specialized palliative care is necessary. To our knowledge, no available identification instrument makes this distinction. ID-PALL is a screening instrument developed to differentiate between these patient groups.

OBJECTIVE

To assess the structural and criterion validity and the inter-rater agreement of ID-PALL.

METHODS

In this multicenter, prospective, cross-sectional study, nurses and physicians assessed medical patients hospitalized for 2 to 5 days in two tertiary hospitals in Switzerland using ID-PALL. For the criterion validity, these assessments were compared to a clinical gold standard evaluation performed by palliative care specialists. Structural validity, internal consistency and inter-rater agreement were assessed.

RESULTS

2232 patients were assessed between January and December 2018, 97% by nurses and 50% by physicians. The variances for ID-PALL G and S are explained by two factors, the first one explaining most of the variance in both cases. For ID-PALL G, sensitivity ranged between 0.80 and 0.87 and specificity between 0.56 and 0.59. ID-PALL S sensitivity ranged between 0.82 and 0.94, and specificity between 0.35 and 0.64. A cut-off value of 1 delivered the optimal values for patient identification. Cronbach's alpha was 0.78 for ID-PALL G and 0.67 for ID-PALL S. The agreement rate between nurses and physicians was 71.5% for ID-PALL G and 64.6% for ID-PALL S.

CONCLUSION

ID-PALL is a promising screening instrument allowing the early identification of patients in need of general or specialized palliative care. It can be used by nurses and physicians without a specialized palliative care training. Further testing of the finalized clinical version appears warranted.

The performance of the Dutch Safety Management System frailty tool to predict the risk of readmission or mortality in older hospitalised cardiac patients

Background

Early identification of older cardiac patients at high risk of readmission or mortality facilitates targeted deployment of preventive interventions. In the Netherlands, the frailty tool of the Dutch Safety Management System (DSMS-tool) consists of (the risk of) delirium, falling, functional impairment, and malnutrition and is currently used in all older hospitalised patients. However, its predictive performance in older cardiac patients is unknown.

Aim

To estimate the performance of the DSMS-tool alone and combined with other predictors in predicting hospital readmission or mortality within 6 months in acutely hospitalised older cardiac patients.

Methods

An individual patient data meta-analysis was performed on 529 acutely hospitalised cardiac patients ≥70 years from four prospective cohorts. Missing values for predictor and outcome variables were multiply imputed. We explored discrimination and calibration of: (1) the DSMS-tool alone; (2) the four components of the DSMS-tool and adding easily obtainable clinical predictors; (3) the four components of the DSMS-tool and more difficult to obtain predictors. Predictors in model 2 and 3 were selected using backward selection using a threshold of p = 0.157. We used shrunk c-statistics, calibration plots, regression slopes and Hosmer-Lemeshow p-values (P_HL) to describe predictive performance in terms of discrimination and calibration.

Results

The population mean age was 82 years, 52% were males and 51% were admitted for heart failure. DSMS-tool was positive in 45% for delirium, 41% for falling, 37% for functional impairments and 29% for malnutrition. The incidence of hospital readmission or mortality gradually increased from 37 to 60% with increasing DSMS scores. Overall, the DSMS-tool discriminated limited (c-statistic 0.61, 95% 0.56–0.66). The final model included the DSMS-tool, diagnosis at admission and Charlson Comorbidity Index and had a c-statistic of 0.69 (95% 0.63–0.73; P_HL was 0.658).

Discussion

The DSMS-tool alone has limited capacity to accurately estimate the risk of readmission or mortality in hospitalised older cardiac patients. Adding disease-specific risk factor information to the DSMS-tool resulted in a moderately performing model. To optimise the early identification of older hospitalised cardiac patients at high risk, the combination of geriatric and disease-specific predictors should be further explored.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02243-5.