Chronic disease self management – a systematic review of proactive telephone applications Carly Muller Dean Schillinger Division of General Internal Medicine San Francisco General Hospital University of California San Francisco

Introduction Chronic disease leads mortality and morbidity Chronic disease leads mortality and morbidity Significant potential to reduce the burden Significant potential to reduce the burden Current system cant meet long term needs Current system cant meet long term needs

Proactive telephone support

RE-AIM Reach Reach Effectiveness Effectiveness Adoption Adoption Implementation Implementation Maintenance Maintenance

Overall objective Undertake a systematic literature of proactive use of the telephone to assist chronic disease self management to: 1. develop a conceptual schema 2. understand their effectiveness 3. understand population-level reach

Inclusion/Exclusion Inclusions All ages All ages individuals with one or more chronic diseases individuals with one or more chronic diseases PROACTIVE telephone self management applications PROACTIVE telephone self management applicationsExclusions Telephone solely for data collection interviews or solely for data shunting Telephone solely for data collection interviews or solely for data shunting Intervention groups comprising 10 or fewer participants Intervention groups comprising 10 or fewer participants Articles in languages other than English Articles in languages other than English

Search strategy + One of…. and One of…..

Overall intervention description 115 articles covering 92 studies. Median intervention sample size = 77 Median intervention duration = 4 months (range 1 day to 2 years). 82% of studies were conducted in the US

Intervention description – primary and secondary (N=92)

Conceptual schema Clinical Governance Corporate Governance Recruitment & Assessment Integration Quality Assurance & Monitoring Human resources Data and Analysis

Conceptual schema

Studies condition focus (N=92)

Effectiveness (N=75) Comparison groups – –37% multiple interventions, – –51% passive usual care – –12% active usual care 351 different health outcome measures Categories: access, self-efficacy, knowledge, behavior, functional outcomes, physiologic outcomes, clinical guidelines, hospital utilization, ED utilization, medical office visits, costs and other healthcare utilization

Effectiveness (N=75) Comparison groups – –37% multiple interventions, – –51% passive usual care – –12% active usual care 351 different health outcome measures Categories: access, self-efficacy, knowledge, behavior, functional outcomes, physiologic outcomes, clinical guidelines, hospital utilization, ED utilization, medical office visits, costs and other healthcare utilization

Effectiveness

Maintenance of effect

Representativeness Only 7% of articles sampled from a real world setting Only 7% of articles sampled from a real world setting Median sample size at intervention completion was only 77 Median sample size at intervention completion was only 77 Population vs sample characteristics? Population vs sample characteristics?

Engagement Very few studies reported on engagement Very few studies reported on engagement Median drop out rate was 12% Median drop out rate was 12% Median # successful calls/pt/month = 1.7 (N=32) Median # successful calls/pt/month = 1.7 (N=32) Median duration per interaction =20min (N=19). Median duration per interaction =20min (N=19).

Limitations Potential for publication bias not evaluated Potential for publication bias not evaluated English language only English language only No combined measure of effect size as a meta-analysis was not undertaken No combined measure of effect size as a meta-analysis was not undertaken

Conclusions Evidence insufficiently robust Evidence insufficiently robust Potentially these services may deliver superior - or at the very least equivalent – outcomes Potentially these services may deliver superior - or at the very least equivalent – outcomes Focus on patient outcomes Focus on patient outcomes

Policy implications Rigorous and larger scale pilots: $ Robust specifications Robust specifications Targeting Targeting Appropriate financing model Appropriate financing model Data collection and analysis Data collection and analysis

This work would not have been possible without the support of The Commonwealth Fund Assoc Prof Dean Schillinger Prof Andy Bindman Department of Internal Medicine San Francisco General Hospital University of California San Francisco Primary Health Branch Victorian Department of Human Services, Australia Thank-you

Research implications Future studies should ensure: Key information is included to allow assessment of the generalizability of results Key information is included to allow assessment of the generalizability of results Larger sample sizes Larger sample sizes Consistency and reporting on reach and effectiveness measures Consistency and reporting on reach and effectiveness measures Long-term monitoring Long-term monitoring Cost effectiveness Cost effectiveness