Can we predict which hospitalised patients are in their last year of life? A prospective cross-sectional study of the Gold Standards Framework Prognostic Indicator Guidance as a screening tool in the acute hospital setting

Abstract

Background:

Screening to identify hospital inpatients with a short life expectancy may be a way to improve care towards the end of life. The Gold Standards Framework Prognostic Indicator Guidance is a screening tool that has recently been advocated for use in the hospital setting.

Aim:

To assess the clinical utility of the Gold Standards Framework Prognostic Indicator Guidance as a screening tool in an acute hospital setting.

Main outcome measures:

Mortality at 6 and 12 months and sensitivity, specificity and predictive value of the Gold Standards Framework Prognostic Indicator Guidance at 1 year.

Design, setting and participants:

Prospective cross-sectional study of 501 adult inpatients in a tertiary New Zealand teaching hospital screened utilising the Gold Standards Framework Prognostic Indicator Guidance.

Results:

A total of 99 patients were identified as meeting at least one of the Gold Standards Framework Prognostic Indicator Guidance triggers. In this group, 6-month mortality was 56.6% and 12-month mortality was 67.7% compared with 5.2% and 10%, respectively, for those not identified as meeting the criteria. The sensitivity and specificity of the Gold Standards Framework Prognostic Indicator Guidance at 1 year were 62.6% and 91.9%, respectively, with a positive predictive value of 67.7% and a negative predictive value of 90.0%.

Conclusion:

The sensitivity, specificity and predictive values of the Gold Standards Framework Prognostic Indicator Guidance in this study are comparable to, or better than, results of studies identifying patients with a limited life expectancy in particular disease states (e.g. heart failure and renal failure). Screening utilising the Gold Standards Framework Prognostic Indicator Guidance in the acute setting could be the first step towards implementing a more systematic way of addressing patient need – both current unrecognised and future anticipated – thereby improving outcomes for this population.

Keywords

Hospital end of life prognosis palliative screening Gold Standards Framework Prognostic Indicator Guidance Gold Standards Framework

Get full access to this article

View all access options for this article.

References

Steinhauser

Christakis

Clipp

. Factors considered important at the end of life by patients, family, physicians, and other care providers. JAMA 2000; 284(19): 2476–2482.

Lunney

Lynn

Hogan

. Profiles of older medicare decedents. J Am Geriatr Soc 2002; 50: 1108–1112.

Gwilliam

Keeley

Todd

. Development of prognosis in palliative care study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study. BMJ Support Palliat Care 2012; 2: 63–71.

Gott

Ingleton

Bennett

. Transitions to palliative care in acute hospitals in England: qualitative study. BMJ Support Palliat Care 2011; 1: 42–48.

Glare

Virik

Jones

. A systematic review of physicians’ survival predictions in terminally ill cancer patients. BMJ 2003; 327: 195–198.

Weissman

Meier

. Identifying patients in need of a palliative care assessment in the hospital setting: a consensus report from the center to advance palliative care. J Palliat Med 2011; 14: 17–23.

Thomas

. Gold Standards Framework: a programme for community palliative care. London: Department of Health, 2005.

Haga

Murray

Reid

. Identifying community based chronic heart failure patients in the last year of life: a comparison of the Gold Standards Framework Prognostic Indicator Guide and the Seattle Heart Failure Model. Heart 2012; 98: 579–583.

Moss

Lunney

Culp

. Prognostic significance of the ‘surprise’ question in cancer patients. J Palliat Med 2010; 13: 837–840.

10.

Pang

W-F

Kwan

BC-H

Chow

K-M

. Predicting 12-month mortality for peritoneal dialysis patients using the ‘surprise’ question. Perit Dial Int 2013; 33: 60–66.

11.

Thomas

. Prognostic Indicator Guidance (PIG). 4th ed. The Gold Standards Framework Centre in End of Life Care, http://www.goldstandardsframework.org.uk/cd-content/uploads/files/General%20Files/Prognostic%20Indicator%20Guidance%20October%202011.pdf (2011, accessed 20 September 2013).

12.

Thomas

Wilson

Corner

. Improving end of life care in acute hospitals using the GSF AH training programme phase 2: 2011–12. The National GSF Centre in End of Life Care, http://www.goldstandardsframework.org.uk/cd-content/uploads/files/Acute%20Hospitals/7.%20GSF%20%20AH%20Poster%20vs%208%20a.pdf (accessed 20 September 2013).

13.

Clark

Armstrong

Allan

. Imminence of death among hospital inpatients: prevalent cohort study. Palliat Med. Epub ahead of print 17 March 2014. DOI: 10.1177/0269216314526443.

14.

Dixon

Shaw

Frankel

. Hospital admissions age, and death: retrospective cohort study. BMJ 2004; 328: 1288–1290.

15.

Rosenwax

McNamara

Murray

. Hospital and emergency department use in the last year of life: a baseline for future modifications to end-of-life care. Med J Aust 2011; 194: 570–573.

16.

Finlay

Casarett

. Making difficult discussions easier: using prognosis to facilitate transitions to hospice. CA Cancer J Clin 2009; 59: 250–263.

17.

Reinke

Engelberg

Shannon

. Transitions regarding palliative and end-of-life care in severe chronic obstructive pulmonary disease or advanced cancer: themes identified by patients, families, and clinicians. J Palliat Med 2008; 11: 601–609.

18.

Glare

Virik

. Independent prospective validation of the pap score in terminally ill patients referred to a hospital-based palliative medicine consultation service. J Pain Symptom Manage 2001; 22: 891–898.

19.

Morita

Akechi

Ikenaga

. Late referrals to specialized palliative care service in Japan. J Clin Oncol 2005; 23: 2637–2644.

20.

Bruera

Hui

. Integrating supportive and palliative care in the trajectory of cancer: establishing goals and models of care. J Clin Oncol 2010; 28: 4013–4017.

21.

Dalal

Palla

Hui

. Association between a name change from palliative to supportive care and the timing of patient referrals at a comprehensive cancer center. Oncologist 2011; 16: 105–111.

22.

Boyd

Murray

. Recognising and managing key transitions in end of life care. BMJ 2010; 341: 649–652.

23.

Gardiner

Gott

Ingleton

. Extent of palliative care need in the acute hospital setting: a survey of two acute hospitals in the UK. Palliat Med 2013; 27(1): 76–83.

24.

Green

. How many hospital beds? Inquiry 2002; 39: 400–412.

25.

Gott

Frey

Raphael

. Palliative care need and management in the acute hospital setting: a census of one New Zealand hospital. BMC Palliat Care 2013; 12: 15.

26.

Christakis

Lamont

Smith

. Extent and determinants of error in doctors’ prognoses in terminally ill patients: prospective cohort study. BMJ 2000; 320: 469–473.

27.

Larson

Curtis

. Integrating palliative care for liver transplant candidates. JAMA 2006; 295: 2168–2176.

28.

Levy

Mozaffarian

Linker

. The Seattle Heart Failure Model: prediction of survival in heart failure. Circulation 2006; 113: 1424–1433.

29.

Celli

Cote

Marin

. The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. N Engl J Med 2004; 350: 1005–1012.

30.

Glare

Sinclair

. Palliative medicine review: prognostication. J Palliat Med 2008; 11: 84–103.

31.

Small

Gardiner

Barnes

. Using a prediction of death in the next 12 months as a prompt for referral to palliative care acts to the detriment of patients with heart failure and chronic obstructive pulmonary disease. Palliat Med 2010; 24: 740–741.

32.

Reticker

Nici

ZuWallack

. Pulmonary rehabilitation and palliative care in COPD: two sides of the same coin? Chron Respir Dis 2012; 9: 107–116.

33.

Medici

Rossaro

Wegelin

. The utility of the model for end-stage liver disease score: a reliable guide for liver transplant candidacy and, for select patients, simultaneous hospice referral. Liver Transpl 2008; 14: 1100–1106.

34.

Smith

White

Arnold

. Uncertainty – the other side of prognosis. New Engl J Med 2013; 368: 2448–2450.