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The American Journal of Managed Care February 2015
A Multidisciplinary Intervention for Reducing Readmissions Among Older Adults in a Patient-Centered Medical Home
Paul M. Stranges, PharmD; Vincent D. Marshall, MS; Paul C. Walker, PharmD; Karen E. Hall, MD, PhD; Diane K. Griffith, LMSW, ACSW; and Tami Remington, PharmD
Quality’s Quarter-Century
Margaret E. O'Kane, MHA, President, National Committee for Quality Assurance
How Pooling Fragmented Healthcare Encounter Data Affects Hospital Profiling
Amresh D. Hanchate, PhD; Arlene S. Ash, PhD; Ann Borzecki, MD, MPH; Hassen Abdulkerim, MS; Kelly L. Stolzmann, MS; Amy K. Rosen, PhD; Aaron S. Fink, MD; Mary Jo V. Pugh, PhD; Priti Shokeen, MS; and Michael Shwartz, PhD
Did Medicare Part D Reduce Disparities?
Julie Zissimopoulos, PhD; Geoffrey F. Joyce, PhD; Lauren M. Scarpati, MA; and Dana P. Goldman, PhD
Health Literacy and Cardiovascular Disease Risk Factors Among the Elderly: A Study From a Patient-Centered Medical Home
Anil Aranha, PhD; Pragnesh Patel, MD; Sidakpal Panaich, MD; and Lavoisier Cardozo, MD
Employers Should Disband Employee Weight Control Programs
Alfred Lewis, JD; Vikram Khanna, MHS; and Shana Montrose, MPH
Race/Ethnicity, Personal Health Record Access, and Quality of Care
Terhilda Garrido, MPH; Michael Kanter, MD; Di Meng, PhD; Marianne Turley, PhD; Jian Wang, MS; Valerie Sue, PhD; Luther Scott, MS
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Leveraging Remote Behavioral Health Interventions to Improve Medical Outcomes and Reduce Costs
Reena L. Pande, MD, MSc; Michael Morris; Aimee Peters, LCSW; Claire M. Spettell, PhD; Richard Feifer, MD, MPH; William Gillis, PsyD
Faster by a Power of 10: A PLAN for Accelerating National Adoption of Evidence-Based Practices
Natalie D. Erb, MPH; Maulik S. Joshi, DrPH; and Jonathan B. Perlin, MD, PhD, MSHA, FACP, FACMI
Differences in Emergency Colorectal Surgery in Medicaid and Uninsured Patients by Hospital Safety Net Status
Cathy J. Bradley, PhD; Bassam Dahman, PhD; and Lindsay M. Sabik, PhD
The Role of Behavioral Health Services in Accountable Care Organizations
Roger G. Kathol, MD; Kavita Patel, MD, MS; Lee Sacks, MD; Susan Sargent, MBA; and Stephen P. Melek, FSA, MAAA
Patients Who Self-Monitor Blood Glucose and Their Unused Testing Results
Richard W. Grant, MD, MPH; Elbert S. Huang, MD, MPH; Deborah J. Wexler, MD, MSc; Neda Laiteerapong, MD, MS; E. Margaret Warton, MPH; Howard H. Moffet, MPH; and Andrew J. Karter, PhD
The Use of Claims Data Algorithms to Recruit Eligible Participants Into Clinical Trials
Leonardo Tamariz, MD, MPH; Ana Palacio, MD, MPH; Jennifer Denizard, RN; Yvonne Schulman, MD; and Gabriel Contreras, MD, MPH
A Systematic Review of Measurement Properties of Instruments Assessing Presenteeism
Maria B. Ospina, PhD; Liz Dennett, MLIS; Arianna Waye, PhD; Philip Jacobs, DPhil; and Angus H. Thompson, PhD
Emergency Department Use: A Reflection of Poor Primary Care Access?
Daniel Weisz, MD, MPA; Michael K. Gusmano, PhD; Grace Wong, MBA, MPH; and John Trombley II, MPP

Leveraging Remote Behavioral Health Interventions to Improve Medical Outcomes and Reduce Costs

Reena L. Pande, MD, MSc; Michael Morris; Aimee Peters, LCSW; Claire M. Spettell, PhD; Richard Feifer, MD, MPH; William Gillis, PsyD
Successful patient engagement in a nationally available, remotely delivered behavioral health intervention can significantly improve medical outcomes and lower healthcare costs.
The baseline characteristics were very well balanced between the 2 study groups (Table 1). The average age was 56 years in both groups, and a similar proportion of both groups were male (70% in the intervention group and 67% in the comparison group). Although there were slightly more individuals in the intervention group from the northeast region and fewer from midwest (P = .04), the groups were well balanced with respect to the proportion of participants residing in rural, suburban, and urban community settings. The prevalence of baseline comorbid clinical conditions was similar in the 2 groups, including rates of diabetes, hypertension, and hyperlipidemia (Table 1). There were no significant differences in average baseline maximal DASS-21 scores for depression, anxiety, and stress (Table 1), and more than 60% of participants in each group fell into the normal subclinical depression range on the DASS-21 scale (Figure 2). In addition, there was a nonsignificant trend toward more individuals in the comparison group (43.3%) falling in the normal range on all 3 dimensions of the DASS-21 scale compared with the intervention group (32.2%). There was no significant difference in the prospective risk scores between the 2 groups (6.39 ± 5.2 in the intervention group vs 6.85 ± 6.2 in the control group; P = .43), and baseline medical utilization (in the 6-month period prior to clinical intake) showed no significant differences between the 2 groups with similar rates of pre-period total medical expenditures, total inpatient expenditures, inpatient admissions, cardiac-specific inpatient admissions, ED visits, and total outpatient services (Table 2). The only difference noted was higher utilization of outpatient behavioral health services in the comparison group at baseline (1544 per 1000 persons per year vs 842 per 1000 persons per year in the intervention group; P <.0001).


Individuals in the AbilTo intervention group had significant reductions in the severity of all components of the DASS-21 score, including depression, anxiety, and stress (Figure 3). During the 6-month follow-up period, the intervention group had 38% fewer total hospital admissions (386 admissions per 1000 persons per year vs 622 per 1000 persons per year in the comparison group) (Table 3). After multivariable adjustment for demographic variables, baseline risk score, and baseline depression score, as well as pre-period medical utilization, the intervention group had a statistically significantly 31% fewer hospital admissions (P = .03) during the 6-month followup period (Figure 4). Interestingly, a similar proportion of individuals in each group were hospitalized during the 6-month period (15% in the intervention group vs 21% in the comparison group; P = .19). However, there was a trend (P = .16) toward more individuals in the comparison group with multiple (2 or more) admissions (7.2%) compared with fewer multiple admissions in the intervention group (3.5%).

Individuals in the AbilTo intervention group had 63% fewer total inpatient hospital days in the 6-month follow-up period (1455 days per 1000 persons per year in the intervention group compared with 3933 days per 1000 persons per year in the comparison group). These data were statistically significant with an adjusted reduction of 48% (P = .01) even after accounting for demographics, baseline risk, baseline depression scores, and pre-period medical utilization.

There was no significant difference in utilization of ED services in the 2 groups, although there was a trend toward fewer ED visits in the intervention group (505 per 1000 persons per year vs 689 per 1000 persons per year in the comparison group; adjusted P = .40). The intervention group had significantly more behavioral health visits—almost entirely accounted for by participation in the AbilTo program itself (19,713 visits per 1000 persons per year vs 2822 per 1000 persons per year in the comparison group; adjusted P <.0001). Excluding behavioral health visits, there were no differences in utilization of all outpatient services (34,634 visits per 1000 persons per year vs 31,167 per 1000 persons per year; adjusted P = .19), nor were there any differences in cardiac-specific outpatient visits (P = .33).

Healthcare Expenditures

To determine the potential cost savings derived from program participation, we calculated the potential cost savings attributable to the significant reduction in total days in the hospital. To estimate the potential savings, we first determined the average total cost of an inpatient hospital day (including facility, professional, and ancillary charges) for the comparison group in the 6-month follow-up period using claims data for this population. Individuals in the comparison group averaged 1.88 inpatient hospital days in the 6-month follow-up period, and the average cost was $4500 per hospital day. Using the adjusted percent difference in total inpatient hospital days of 48% between the comparison group and the AbilTo intervention group, each individual completing the AbilTo program would be expected to avoid an average of 0.95 inpatient hospital days. Thus, the 202 individuals in the intervention group were estimated to have saved 191.9 hospital days. Applying the average cost per hospital day of $4500, we estimated that the individuals who fully participated in the AbilTo program saved $864,000 in the 6-month follow-up period. Comparing this cost saving with the estimated total program cost demonstrated an overall cost savings as early as 6 months.


We demonstrated that an 8-week remotely delivered behavioral change intervention was associated with cost savings, driven by an adjusted 48% reduction in total inpatient days and a 31% reduction in all-cause hospital admissions in the 6-month follow-up period. These substantial reductions in healthcare utilization and associated cost savings were attributable to the delivery of a high-quality behavioral health program for this high-risk group of patients with cardiovascular disease. This study shows that focused targeting of patients with highrisk clinical conditions, coupled with highly successful engagement strategies, can lead not only to meaningful behavioral health improvements, but also to improved medical outcomes and lower healthcare expenditures.

It has been long recognized that behavioral health issues can be both a cause and a consequence of medical disease.16 In individuals with cardiovascular disease, comorbid behavioral health concerns are common—affecting up to 25% of patients11,17—and result in poorer adherence to medications and lifestyle recommendations as well as worse overall clinical outcomes, including increased hospital readmissions and higher mortality.4-8,18-20 Taken together, inadequate management of behavioral health issues can lead to unnecessarily greater medical utilization and as much as a doubling in the cost of care.21

It stands to reason that a program that successfully influences behavioral health could have a profound impact on overall health, medical utilization, and total health expenditures. However, prior studies to assess the effect of behavioral health interventions in cardiovascular disease have met with mixed results. For example, the Enhancing Recovery in Coronary Heart Disease (ENRICHD) trial investigated the effects of CBT, with or without pharmacologic intervention, on post MI patients with depression, and found no difference in the primary end point of event-free survival at an average follow-up of 29 months.22 On the other hand, a follow-up evaluation of the ENRICHD study data showed that the intervention led to reduced late-term mortality with the benefits corresponding to the degree of improvement in depression.23 Other studies using a purely pharmacologic intervention for depression have not shown an impact on cardiovascular outcomes or mortality.24-26 A few recent studies have employed a remote or Internet-based approach to reach patients with cardiovascular disease and have demonstrated improvements in depression, adherence, and quality of life.27-29

Our study and our intervention differ from the existing literature in several important ways. First, we did not design our intervention to focus only on improvements in behavioral health or cardiac outcomes. Instead, our goal was to demonstrate that successful targeting and engagement of high-risk cardiac patients in a behavioral health intervention would impact 2 specific outcomes: 1) medical utilization, and 2) healthcare expenditures. The impact of treating behavioral health on these critical components of the healthcare continuum has not previously been well studied in cardiovascular disease.

Second, our intervention differs from usual behavioral healthcare or pharmacotherapy in several unique ways that promote greater engagement, and ultimately more successful outcomes. The studied intervention features a collaborative care model utilizing the expertise of a licensed clinical social worker and a behavioral coach. These providers work in partnership with one another in the care of each individual patient and also receive clinical oversight by a LCSW supervisor. Moreover, the protocoled nature of the intervention using “best practices” ensures high quality and consistent program content delivery across the United States.

Finally, acknowledging that engagement itself may be a barrier to care for patients with comorbid medical and behavioral health conditions, the program uses remote care delivery by phone or video to simplify engagement and maximize participation. The success of this approach is highlighted by a high completion rate (61%) among those who enroll in the program after initial clinical intake. The importance of ease of engagement is highlighted by recent studies demonstrating the value of home-based or phone-based support in improving quality of life in patients with cardiac disease.27-30 It has become increasingly clear that outcomes can be best optimized when utilizing a strategy that combines both successful engagement and high-quality care programs that focus on meaningful behavior change skills.

While prior studies have solely focused on individuals with depression and cardiovascular disease, our study is unique in that more than 60% of individuals in both the intervention and comparison groups had scores on the depression dimension of the DASS-21 scale below the clinical threshold for depression, and between 30% to 40% had normal scores in all 3 dimensions of the scale. This underscores the fact that even individuals who do not meet the formal criteria for clinical depression may benefit from a behavioral health intervention focused on addressing and overcoming barriers to change. As described above, this intervention utilizes a combination of evidence-based, rigorously evaluated approaches, including CBT, ACT, motivational interviewing, and mindfulness, among others. These approaches have significant benefit not only for individuals with clinical depression, but also for individuals with stress, anxiety/ panic, and medical health conditions, as is the case in this cardiac population, or a variety of other situations where therapy and coaching can help build the life skills needed for better self-care and improved overall health.

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