Marina Lupari Assistant Director of nursing- RD Northern Health Social Care Trust Funded by HSc Research Development f

1. Marina Lupari Assistant Director of nursing- R&D Northern Health &Social Care Trust Funded by HSc Research & Development fellowship Delivering care to older people with multiple chronic conditions 

3. Hidden Health Care System 2?

4. Predictive risk Ambulatory care sensitive conditions High continuity of care (GPs) Medication review/management in pts home Social care interventions Integrated health & social care Telemedicine/ self management COPD Personalised healthcare programme What evidence did we have ?

5. What is the Chronic illness case management service?

6. Nurse led generalist model across several chronic conditions– Continuing Care nurse Band 7 Least invasive care in the least intensive setting through patient case management Target group- patients most at risk of avoidable rehospitalisations Integrating and coordinating the individual’s journey through all parts of the health and social care systems through Integrated Care pathways Incorporates elements of disease management and self-care; Anticipatory care facilitated through proactive as opposed to reactive care model proactive interventions to enable health education (chronic illness maintenance) and reactive interventions for times of increased clinical need (chronic illness exacerbation). proactive interventions to enable health education (chronic illness maintenance) and reactive interventions for times of increased clinical need (chronic illness exacerbation).

7. Rethinking Care : 

8. Emerging Risk

11. Research question - is a case management approach for chronic conditions effective and cost-effective in relation to usual care for older patients with multiple chronic conditions? Therefore the principal objective is to determine whether case management as a service reduces hospital readmission rates amongst older people. Aims & Objectives

13. Frequently-admitted patients

14. Evaluation of Integrated Care

16. Address regression to the mean Problematic to examine changes over time and then attribute that change to an intervention Persons are not assigned randomly to groups so the groups are not equivalent Groups were made exactly equivalent on the matching variable (PARR score) Groups are more comparable on the outcome measure

17. Initial matching exercise (PARR)

25. 10% decrease in mean log bed-days

27. Latent growth analysis has become a common way for analyzing longitudinal data. It is a statistical technique used in the structural equation modeling (SEM) framework to estimate growth trajectory. It is a longitudinal analysis technique to estimate growth over a period of time. It is widely used in the field of behavioral science, education and social science. SEM software M-plus was used to estimate the growth trajectory. Latent Growth Models (Meredith & Tisak 1990) represent repeated measures of dependent variables as a function of time and other measures. The relative standing of an individual at a specific time point is modeled as a function of an underlying process, the parameter values of which vary randomly across individuals. Latent Growth Curve Methodology can be used to investigate systematic change, or growth, and interindividual variability in this change. A special topic of interest is the correlation of the growth parameters, the so-called initial status and growth rate, as well as their relation with time varying and time invariant covariates. Figure ? is a schematic representation of the dual process latent growth model used to analyse the EQ5D. It incorporates both the EQ5D visual analogue response by participants and the composite of the EQ5D. Latent growth analysis has become a common way for analyzing longitudinal data. It is a statistical technique used in the structural equation modeling (SEM) framework to estimate growth trajectory. It is a longitudinal analysis technique to estimate growth over a period of time. It is widely used in the field of behavioral science, education and social science. SEM software M-plus was used to estimate the growth trajectory. Latent Growth Models (Meredith & Tisak 1990) represent repeated measures of dependent variables as a function of time and other measures. The relative standing of an individual at a specific time point is modeled as a function of an underlying process, the parameter values of which vary randomly across individuals. Latent Growth Curve Methodology can be used to investigate systematic change, or growth, and interindividual variability in this change. A special topic of interest is the correlation of the growth parameters, the so-called initial status and growth rate, as well as their relation with time varying and time invariant covariates. Figure ? is a schematic representation of the dual process latent growth model used to analyse the EQ5D. It incorporates both the EQ5D visual analogue response by participants and the composite of the EQ5D.

31. Cost-Effectiveness measurements

37. Cost effectiveness plane

38. Cost acceptability curve

39. The intervention group Reduction of 59% across a nine month period. Across all time points there was a significant reduction at p=0.05 in lengths of stay for the intervention group. Accompanied by reduction in mean number of rehospitalisations (T3 2.23 SD 0.71, T6 1.91 SD 0.87, T9 1.76 SD 0.91) Control group which increases over time (T3 2.33 SD 0.79, T6 2.32 SD 0.99, T9 2.43 SD 0.91).

40. Patient related outcomes Intervention group report a significant improvement (values significant at p<0.5) in their perception of their health status overall health related quality of life over the period of the CICM intervention

41. Willingness to change is a strength, even if it means plunging part of the company into total confusion for a while.