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THE DREAMING PROJECT FINAL CONFERENCE Trieste, 14th June 2012 Presentation of the final results of the Project Wouter Keijser MD / (Reinhard Prior MD) Marco d ’ Angelantonio HIM SA ( Brussels – Belgium). Outline Presentation. Objectives Primary Outcomes Secondary Outcomes Results
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THE DREAMING PROJECT FINAL CONFERENCE Trieste, 14th June 2012 Presentation of the final results of the Project Wouter Keijser MD / (Reinhard Prior MD) Marco d’Angelantonio HIM SA (Brussels – Belgium)
Outline Presentation • Objectives • Primary Outcomes • Secondary Outcomes • Results • Considerations & Limitations • Initial conclusions • Next steps • Economic impact
Objectives RCT • The DREAMING real life trial has the objective to demonstrate that the DREAMING platform, with its integrated monitoring, alarm handling and videoconferencing services, produces clinical benefits to its users and economic benefits to the health authorities. (Trial Protocol, June 2009). • Participants: • Age > 65 years. • Chronic heart failure, Diabetes Mellitus, COPD.
Outcomes Clinical effect of DREAMING measured at: • Start • Mid-term • End … in terms of effect on: • Primary Outcome • Quality of Life (SF36: mental & physical health) • Secondary Outcome • Depression: risk factor morbidity and deterioration of QoL (HADS) • …
Secondary Outcomes • HADS • Time to permanent transfer to elderly homes • Total and average length of stay in hospital • Number of consultations with GPs • Number of consultations with specialists • Number of home visits by nurses • Number of home visits by social operators • Number of ambulance transports • Number of accesses to emergency rooms • Number of falls • Number of femur fractures • HbA1c change over time (participants with diabetes only) • Survival.
Trial Results • Quality of Life: SF-36: ‘physical’ & ‘mental’ • Depression: HADS • Secondary Outcomes.
Results: SF36 ‘MENTAL’ End Mid-term Start
Results: SF36 ‘PHYSICAL’ End Mid-term Start
Comments on SF36 • At start groups have exactly the same level on either score. • This analysis: only subjects included, which took SF-36 all 3 times. • Physical Component Summary (PCS): subjects with treatment score slightly better; no significant differences. • Mental Component Summary (PSC): subjects with treatment show significant increase (‘vitality’-score in particular; also ‘mental’-score): magnitude suggests clinical importance. End End Mid-term Mid-term Start Start
Results: HADS End Mid-term Start
Comments on HADS • Level at ‘Start’ is equal. • Statistically there is significant difference in depression score (not in anxiety). • Subjects who were slightly depressed dropped out to a higher degree in treatment than in control group. End Start Mid-term
Secondary Outcomes √HADS √ Total (a) and average length (b) of stay in hospital √ Number of accesses to emergency rooms √ Number of ambulance transports √ Total duration hospital stay √ Number of consultations with GPs √ Number of consultations with specialists √ Number (time) transfer to elderly homes √ Number of falls √ Number of femur fractures × HbA1c change over time (participants with diabetes only) × Number of home visits by nurses × Number of home visits by social operators TBD Survival.
Comments on Summary of Events • Higher occurrence of e.g. falls in treatment group mainly based on individual trial-site (Trieste). • No consistent overall trends. • Significant results in some of measures at individual sites might be of interest, e.g. number of hospitalization and aver. duration of stay. • Number of home visits by nurses and number of visits by social operators have not been considered. In these cases the structure of data suggests that there are no valid dependent variable.
Considerations & Limitations “Subjects who were slightly depressed dropped out to a higher degree in treatment than in control group.” • Perhaps, depressed mood had reduced compliance in the more complex situation of the treatment group? • Elderly having up to a certain level of HADS-related problems (depression), might very well be more prone to stress etc. of using AAL? • Should there be minimal mental requirement for AAL? • Should criteria and/or screening-tools for AAL-equipment be developed?
Initial Conclusions Based on these OVER ALL results: • DREAMING is found to result in a significant positive effect on depression-scores (HADS). • DREAMING results in a significant effect on QoL, in particular on vitality and mental health domains (SF36). • Our study suggest that (benefits of) screening of potential users of AAL-solutions like DREAMING on depression, should be further studied. • Per site analysis of data is ongoing and will reveal more results. • Current DREAMING data encloses a source of more information…
Next Steps • Short Term (June 2012) • In depth data- and process-analysis, e.g.: • Case-by-case analysis causes of drop-out; death; admission, … • Intermediate long term (end 2012) • Mutual scientific publication article (lead: Tallinn University) • Additional publications (book published by IOS Press of the Netherlands
Economic Impact Marco d’Angelantonio
Economic impactA few considerations • The DREAMING trials have been conducted in very unfavourable conditions: • Rigidity of the RCT model (strict inclusion rules, no rooms for changes during the trials) • New technology, rather expensive if compared to todays’ market cots • Relative small samples leading to diseconomies of scale
Additional Statistical Considerations • On SF36 PER SITE: For comparison of SF36 scores between sites, one should be aware that the number of subjects included is small at some of the sites. This makes significant tests for individual sites unlikely and leads to high standard errors. At two sites, Berlin and Trieste, the differences in MCS scores approach significance. The situation is a bit unusual in Berlin as the intervention group started from a very low level. At some sites there are interesting developments, which might require an explanation from the local researchers. For example, at Langeland PCS score in both groups go down at T=MIDTERM and strongly rise at T=END, remarkably in close parallel. Something must have happened here, which affected the whole setting. (Summary: A site-by-site analysis showed a significant effect at two sites. Regarding this, it has to be considered that some of the samples at individual sites contained about 10 or fewer sujects, making the detection of any effect unlikely, even in case of large effect sizes. In several data sets from individual sites there were striking patterns of parallel change in the control and intervention group, which were not present at other sites. A clarification of the reasons for such changes will be important.).
Additional Statistical Considerations • On SF36 Minimal Clinically important Difference (MID) of SF-36 in this graph was 2.4 at T=END. As a rule of thumb for the MCS three points are suggested as MID. Thus, regarding the MID findings are slightly below but close to the MID. Our findings suggest effects are there, but nor very strong.
Additional Statistical Considerations • On difference in HADS score at start If ALL subjects are compared, as they were recruited in the beginning, there is no difference. The tiny difference at T0 in the graph is statistically far from any difference (see also the error bars). This is proof that there was a random sample in the beginning with regard to this measure. For a valid comparison of how the subjects have developed over time, we have to focus on the subjects who have scores at all time points that are compared. If subjects are selected on this basis, the difference in the beginning becomes greater. Nevertheless, also in this selection of subjects there is a significant difference with slightly decreasing HADS scores in the intervention group and increasing scores in the control group. Thus, the change in the HAD score if all subjects are taken into account, results from two processes: (1) A statistically significant different in the development under the two different conditions; (2) A higher dropout rate of subjects with high HADs scores in the intervention group.
Additional Statistical Considerations • On screening for AAL ‘mental-applicability’ Maybe it would be of interest to look what happened with the subjects that dropped out. At least, one should be aware, and this is perhaps the most important message from this finding, that dropout rate can be influenced by the intervention, and that certain measure might be predictors of dropping out. Indeed, the findings may indicate that subjects with HADS values close to or above the critical threshold of 8 points are less compliant in such interventions. Thus, the a HADS screening in the beginning, as a preselection criterion, might be useful.
