Diagnosing Dying. Dr Rachel Wilkins Community Consultant in Geriatric Medicine Southern Health NHS Foundation Trust

Transcription

1 Diagnosing Dying Dr Rachel Wilkins Community Consultant in Geriatric Medicine Southern Health NHS Foundation Trust

2 Learning Objectives Barriers to diagnosing dying Predicting End of Life situations Gold standard frameworks Prognostic indicator guidance Disease specific Dying in Acute Care (AMBER Care Bundle) I told you I was ill Spike Milligan

3 Potential Barriers to Diagnosing Dying? I d live my life exactly the same again. Except three inches shorter Stephen Merchant

4 Potential Barriers to Diagnosing Dying? No diagnosis! Disagreement between professionals Failure to recognise key symptoms Lack of awareness of natural history of disease progression Hope! Unable to communicate with patient/relatives Continue futile and unrealistic interventions Unable to have the DNACPR discussion Knowledge/ experience around end of life prescribing Fear of shortening life or of litigation Concerns about with-holding or withdrawing treatment

5 Good medicine requires us to assist patients to make good decisions An understanding of the natural history of the disease An understanding of the person themselves (values, wishes, fears) So would you call THIS man flu? Louis Theroux

6 Psychological factors in dying Diagnosing dying: symptoms and signs of end-stage disease- Review Article Sue Haig End of Life Care, 2009, Vol 3, No 4

7 Exploring patient values It is much more important to know what sort of a patient has a disease than what sort of a disease a patient has William Osler 1900

8 Identifying end of life why predict? Patient and carers- deal with news Less likely to have unnecessary treatment Plan appropriate care Avoid crisis management Halve cost of hospital admission Increase numbers realising choice to die at home (70%) Dying Matters

9 So can we predict dying? Here lies EZEKIEL AIKLE Age 102 The Good Die Young

10 New York Nursing Home study 100,669 nursing home residents, , New York Long-stay residents (>1 year) OR Newly admitted residents Data from Minimum data set (MDS) Developed a predictive score of 1 year mortality Flacker JM, Kiely DK. Mortality-Related Factors and 1-Year Survival in Nursing Home Residents. Journal of the American Geriatrics Society 2003;51(2):213-21

11 New York Nursing Home study Key factors Shortness of breath Unstable conditions Male sex More than 25% of food uneaten Congestive heart failure Low functional ability BMI less than 23 kg/m2

12 The MDS Mortality Risk Index: The evolution of a method for predicting 6- month mortality in nursing home residents MMRI-R currently tested as part of a NIHR 5 year grant Designed to fit on two sides of a sheet of paper Easy to calculate Weighted for age/ cancer/ cognition/adls

13 Porock D, Parker-Oliver D, Petroski G, Rantz M. The MDS Mortality Risk Index: The evolution of a method for predicting 6-month mortality in nursing home residents. BMC Research Notes 2010;3(1):200

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15 What about Clinical Intuition? Q: I have a question about coding MDS item J5c, endstage disease. How would I know if a resident has less than six months to live? Even our hospice residents sometimes live much longer than our expectations. HCPro Website

16 Clinical Intuition - MDS J5c < 6/12 expected survival 50% died within first month 83% dead at 6 months >6/12 expected survival 5% dead in first month 15% dead at 6 months

17 Here lies HENRY BLAKE He stepped on the gas Instead of the brake

18 Deaths within primary care setting 1% practice population die in next year Usually older patients 63% all women >80 yrs 43% all men >80 yrs Cancer 25% all deaths 25% deaths residential and nursing homes (mean life expectancy 18mths)

19 Deaths within primary care setting Cannot predict genuinely unexpected deaths BUT 16% < 65 years 0.25% > 65 years external causes Deprivation= more deaths younger age groups

20 Trust clinical intuition The surprise question? Would I be surprised if this person were to die in the next 12 months? Accurate 7 out of 10 high priority for planning care etc.

21 So what do we do? No UK studies evaluating predictors in practice GSF Prognostic Indicator guidance

22 GSF Prognostic Indicator guidance

23 GSF Prognostic Indicator guidance

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27 GSF Prognostic indicator guidance remember these Bed/ chair 50% of the time Breathless at rest or minimal exertion Weight loss >10% 12 months Recurrent / persistent infections or pressure ulcers Cancer Metastases >50% bed/chair= less than 3/12 life expectancy In patients with advanced age and co-morbidity

28 Advance Care Planning I am ready to meet my Maker. Whether my Maker is prepared for the great ordeal of meeting me is another matter. Winston Churchill

29 Advance care planningtriggers for discussion Change in personal circumstances Clinical change Following secondary care input Following new diagnosis

30 GSF ten years on National GSF centre Not for profit social enterprise company Omega charity to support carers GSF Primary care GSF Hospitals

31 Secondary Care settings-amber care bundle Here lies Clyde Whose life was full Until he tried To milk a bull

32 The AMBER Care Bundle Assessment Management Best Practice Engagement Recovery uncertain Developed at Guys and St Thomas NHS Trust

33 The benefits of the AMBER Care bundle Patients being treated with greater dignity and respect Greater clarity around patients' preferences and plans about how these can be met Improved decision making A positive impact on multi-professional team communication and working Increased nurses confidence about when to approach medical colleagues to discuss treatment plans Lower emergency readmission rates Any member of the clinical multi-disciplinary team can identify patients suitable for the AMBER care bundle.

34 Learning Objectives Barriers to diagnosing dying Predicting End of Life situations Gold standard frameworks Prognostic indicator guidance Disease specific Dying in Acute Care (AMBER Care Bundle)

35 Questions and Discussion

36 References egsftoolkit.html