Effectiveness of CDM-KT strategies addressing multiple high-burden chronic diseases affecting older adults: A systematic review Monika Kastner, Roberta Cardoso, Yonda Lai, Victoria Treister, Joyce Chan Scientist, Li Ka Shing Knowledge Institute of St. Michael s Hospital Toronto, ON CAHSPR Conference May 10, 2016
Background More than half of older adults have two or more chronic conditions (e.g., diabetes, COPD, depression) Older adults have greater health care needs and experience more hospitalizations, yet only 55% receive appropriate care In response, different chronic disease management and KT strategies (CDM-KT) have been created most are not developed for older adults or created for sustained use, and are primarily focused on a single disease As a result, the care of older adults remains suboptimal Public Health Agency of Canada.
Objectives Conduct a systematic review to identify effective CDM-KT interventions/tools that integrate two or more high-burden chronic diseases affecting older adults To determine which components of these interventions optimise their impact
Methods: Search strategy Search strategy: developed by an experienced information specialist; validated using PRESS checklist Data sources: Medline, Embase, Cinahl, AgeLine, and the Cochrane Library for studies in any language from 1990 to Jan 2015 Other sources: Searched the grey literature (Google Scholar and websites of relevant chronic disease organizations); scanned reference lists of included studies; expert-informed Filters: Applied a validated age-specific search filter to help focus studies on the older population (age 65 years) Kastner M et al. J. Med Internet Res 2006; 24:e25.
Methods: Eligibility criteria Population: Older adults age 60 years Intervention: Multi-chronic disease management knowledge translation interventions/tools (CDM-KT) across 11 high-burden chronic diseases We identified the components of CDM-KT interventions according to EPOC 2015 criteria Comparator: Other CDM-KT interventions, any control or usual care Effective Practice and Organisation of Care (EPOC). EPOC Taxonomy; 2015. Available at: https://epoc.cochrane.org/epoc-taxonomy.
Methods: Eligibility criteria Outcomes: Primary: Impact of CDM-KT strategies for improving disease specific chronic disease management as reported by primary studies (e.g., glycaemic control as part of diabetes care) Secondary: Quality of life, functional status (including cognitive, physical, social and psychological functioning; usability, health service utilization, and costs Study designs: All designs except for case-control, opinion reports and narrative reviews
Methods: Study selection & Data abstraction Study selection involved a calibration exercise to ensure reliability of screening Reviewer pairs independently applied eligibility criteria on a random sample of 25 citations (titles/abstracts) repeated until we reached 80% raw agreement Same procedure for selecting potentially relevant full-text articles Disagreements resolved through consensus at both levels Data abstraction in duplicate using standardized form To account for the wide range of chronic disease outcomes, we extracted data according to the Cochrane Consumer and Communication group taxonomy: Treatment outcomes; Health status and well-being; Health behaviour; Knowledge and understanding; Evaluation of care; Skills acquisition; Health service delivery Cochrane Consumers and Communication Group: Taxonomy of outcomes 2012.
Objectives: Methods: Intervention deconstruction To determine which intervention component or combination of components contributed to their impact; To identify studies that could potentially be pooled Process: Each MCD-KT intervention was deconstructed by reviewer pairs, who independently coded components using content analysis Codebook was developed iteratively with each additional intervention coding; final decisions through group discussion; Initial codes guided by EPOC 2015 criteria
Methods: Intervention deconstruction process Read through intervention description, and identify unique elements
Methods: Intervention deconstruction
Methods: Data synthesis Descriptive summary according to study, population, and intervention characteristics Given the anticipated complexity of interventions evaluated and composition of the different interventions, we expected a high level of heterogeneity amongst our studies We also performed a priori-determined subgroup analyses to assess outcomes: Different disease clusters Similar components or similar combinations of components
Methods: Data synthesis Decision to pool studies was based on exploration of the potential sources of statistical, methodological and clinical heterogeneity 1. Statistical heterogeneity: Assessed using the I 2 statistic (0%-40% = low; 30%-60% = moderate; 50%-90% = substantial; 75%-100% = considerable) 2. Clinical heterogeneity: Examined outcomes according to population characteristics (age, sex and disease cluster) Examined intervention components to determine those with similar or same components or combinations (e.g., ED + REM + FR) 3. Methodological heterogeneity: ROB factors (e.g., randomization process; blinding, outcomes); Duration and loss to of follow-up
Results: Study selection Identified 56,608 citations Duplicate screening of 46,802 titles and abstracts Duplicate screening of 1704 articles in full text 20 studies + 2 companion reports were included in the analysis
Results: Study characteristics 20 studies and 2 companion reports RCTs (n = 9); cluster RCTs (n = 5) Uncontrolled trial (n = 1) Mixed methods studies (n = 3) Qualitative studies (n = 2) Studies were conducted between 2002 and 2015 US (n = 9) Australia (n = 7) Europe (n = 4) Follow-up reported in 15 studies (75%) 2 to 52 weeks (mean 26 weeks)
Results: Population characteristics 11,783 older adults (mean age 67.3 years; 52% women) Chronic conditions of older adults occurring with different combinations of disease clusters: 12 studies: Diabetes (DM) 7 studies: Depression (DEP) 7 studies: Chronic Obstructive Pulmonary Disease (COPD) 5 studies: Cardiovascular disease (CVD) 5 studies: Congestive heart failure (CHF) 4 studies: Dementia (DEM) 2 studies: Arthritis (AT) or osteoarthritis (OA)
Results: Population characteristics Among different disease clusters, only one triad (DM + COPD + CHF); the remainder were dyads 60% of all disease clusters included at least Diabetes (DM) Disease dyad combinations were: DM + CVD (n = 5) DM + DEP (n = 3) CHF + COPD (n = 3) DEP + AT or OA (n = 2) DEP + DEM (n = 2) DEP + COPD (n = 2) DM + CHF (n = 1) DM + CKD (n = 1) DM + COPD (n = 1)
Results: Intervention characteristics Studies described interventions as: Collaborative care including case/care management (n = 8) Self-management with (n = 5) or without (n = 3) telecare or telemonitoring Computer-based (n = 2) Cognitive-behavioural (n = 2) Deconstruction of interventions revealed 9 unique components:
Results: Intervention characteristics
Results: Risk of bias (14 RCTs) Majority of studies had low risk of bias for random sequence generation (71%), and outcomes factors (93%) Majority of studies had unclear blinding of participants (71%), healthcare providers (71%), and outcome assessors (57%)
Results: Primary outcomes: Treatment Depression (n = 10) outcomes (n = 13) 7/10 interventions were collaborative care strategies The intervention components they had in common were: ED (n = 6) TEAM (n = 5) CPM + TEAM (n = 4) CM + ED (n = 4) 6/7 of collaborative care strategies (86%) showed significant reductions in depression symptoms or depression severity in older adults with: Depression + Arthritis or osteoarthritis (n = 2) Depression + Dementia (n = 1), Depression + Diabetes (n = 1) Depression + COPD (n = 1) Diabetes + CVD (n = 1)
Results: Primary outcomes: Treatment Hemoglobin A1c (n = 4) outcomes (n = 13) Two interventions were collaborative care; two interventions were selfmanagement strategies The most common component(s) they shared were: ED (n = 4) CPM + ED (n = 3) There was no difference between groups for HbA1c in any of these studies
Results: Primary outcomes: Treatment Pain (n = 2) outcomes (n = 13) Two collaborative care strategies investigated pain in older adults with Depression + Arthritis or Osteoarthritis The interventions shared the component combination: CM + DM + TEAM Both studies found significant impact: In the Depression + Osteoarthritis population, the intervention participants experienced significant reduction in pain intensity at follow-up: effect size 0.88 (CI 0.27 to 2.72; p = 0.021) In the Depression + Arthritis population, patients in the intervention group had significantly more reduction in pain than the control group (p = 0.004) and had less interference with daily activities due to pain (p = 0.002)
Results: Primary outcomes: Health behaviour (n = 6) Health enhancing lifestyle or behaviour: Exercise (n = 3) 2 studies of collaborative care and one study of a cognitive-behavioural strategy investigated exercise in older adults with: Diabetes + CVD (n = 2) Depression + COPD (n = 1) The most common intervention component(s) they shared were: ED (n = 3) ED + SM (n = 2) or CM (n = 2) All studies showed significant impact: increased exercise at follow-up; shortterm physical activity; reduction in dyspnea related disability as a result of exercise
Results: Secondary outcomes Analysis underway for: Health status and well-being (n = 7) Health service delivery (n = 5) Skill acquisition (n = 4) Knowledge and understanding (n = 4) Evaluation of care (n = 4)
Preliminary conclusions Collaborative care approaches that include any combination of ED, CM, CPM, and TEAMS appear to have positive impacts on treatment outcomes for patients with multiple chronic conditions In particular, older adults with: Depression + Diabetes had reduced depressive symptoms Depression + Arthritis or Osteoarthritis had reduced pain or less interference with daily activities due to pain Depression + Arthritis or Depression + Dementia had increased use of antidepressants Diabetes + CVD or Depression + COPD had increased physical activity
Implications & Next steps Significance: We have contributed to the current, limited knowledge of CDM-KT interventions that integrate the care of two or more chronic diseases affecting older adults Our findings highlight large gaps in the evidence: Relatively few studies include older adults with multimorbidity, and few interventions have been created and tested to address their needs yet they represent the fastest growing proportion of our population Very few interventions are actually developed for two or more chronic conditions Next steps: Complete remainder of analyses plan; Realist review alongside this systematic review to determine the mechanisms underpinning interventions Relevant findings from both SR and RR will be used to inform the development of a multi-chronic disease management tool
Acknowledgements Co-investigators: Sharon Straus Li Ka Shing Knowledge Institute (LKSKI) of St. Michael s Hospital Roberta Cardoso LKSKI of St. Michael s Hospital, Toronto, ON Yonda Lai LKSKI of St. Michael s Hospital, Toronto, ON Victoria Treister LKSKI of St. Michael s Hospital, Toronto, ON Jemila Hamid LKSKI of St. Michael s Hospital, Toronto, ON Geoff Wong University of London, UK Noah Ivers Women s College Hospital, Toronto, ON Jayna Holroyd-Leduc University of Calgary, Calgary, AB Barbara Liu Sunnybrook Health Sciences, Toronto ON Sharon Marr St. Peter s Hospital, Hamilton, ON Questions??