title: A Telephone Support Program to Reduce Costs and Hospital Admissions for Patients at Risk of Readmissions: Lessons from an Evaluation of a Complex Health Intervention.
abstract: This study aimed to evaluate the effectiveness of a telephone health coaching and support service provided to members of an Australian private health insurance fund-Telephonic Complex Care Program (TCCP)-on hospital use and associated costs. A case-control pre-post study design was employed using propensity score matching. Private health insurance members (n=273) who participated in TCCP between April and December 2012 (cases) were matched (1:1) to members who had not previously been enrolled in the program or any other disease management programs offered by the insurer (n=232). Eligible members were community dwelling, aged ≥65 years, and had 2 or more hospital admissions in the 12 months prior to program enrollment. Preprogram variables that estimated the propensity score included: participant demographics, diagnoses, and hospital use in the 12 months prior to program enrollment. TCCP participants received one-to-one telephone support, personalized care plan, and referral to community-based services. Control participants continued to access usual health care services. Primary outcomes were number of hospital admission claims and total benefits paid for all health care utilizations in the 12 months following program enrollment. Secondary outcomes included change in total benefits paid, hospital benefits paid, ancillary benefits paid, and total hospital bed days over the 12 months post enrollment. Compared with matched controls, TCCP did not appear to reduce health care utilization or benefits paid in the 12 months following program enrollment. However, program characteristics and implementation may have impacted its effectiveness. In addition, challenges related to evaluating complex health interventions such as TCCP are discussed. (Population Health Management 2016;19:187-195).
authors.affiliation: 1 Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University , Victoria, Australia .
authors.forename: Renata T
authors.initials: RT
authors.lastname: Morello
authors.affiliation: 1 Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University , Victoria, Australia .
authors.forename: Anna L
authors.initials: AL
authors.lastname: Barker
authors.affiliation: 2 Deakin Health Economics Population Health Strategic Research Centre, Deakin University , Victoria, Australia .
authors.forename: Jennifer J
authors.initials: JJ
authors.lastname: Watts
authors.affiliation: 3 Melbourne Epi Centre, The Royal Melbourne Hospital, The University of Melbourne , Victoria, Australia .
authors.forename: Megan A
authors.initials: MA
authors.lastname: Bohensky
authors.affiliation: 1 Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University , Victoria, Australia .
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Forbes
authors.affiliation: 1 Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University , Victoria, Australia .
authors.forename: Johannes
authors.initials: J
authors.lastname: Stoelwinder
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001315:Australia; D017046:Cost Savings; D005260:Female; D006760:Hospitalization / Q000639:trends*; D006801:Humans; D007348:Insurance, Health; D008297:Male; D008875:Middle Aged; D019370:Observation; D010359:Patient Readmission; D057216:Propensity Score; D012189:Retrospective Studies; D012944:Social Support; D013689:Telephone