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The American Journal of Managed Care December 2019
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Association of Care Management Intensity With Healthcare Utilization in an All-Condition Care Management Program
Hussain S. Lalani, MD; Patti L. Ephraim, MPH; Arielle Apfel, MPH; Hsin-Chieh Yeh, PhD; Nowella Durkin; Lindsay Andon, MSPH; Linda Dunbar, PhD; Lawrence J. Appel, MD; and Felicia Hill-Briggs, PhD; for the Johns Hopkins Community Health Partnership

Association of Care Management Intensity With Healthcare Utilization in an All-Condition Care Management Program

Hussain S. Lalani, MD; Patti L. Ephraim, MPH; Arielle Apfel, MPH; Hsin-Chieh Yeh, PhD; Nowella Durkin; Lindsay Andon, MSPH; Linda Dunbar, PhD; Lawrence J. Appel, MD; and Felicia Hill-Briggs, PhD; for the Johns Hopkins Community Health Partnership
Higher intensity of care management in an all-condition program addressing care coordination and care barriers was associated with increased healthcare utilization among Medicaid and Medicare patients.

In this evaluation, higher J-CHiP care management program intensity was associated with increased healthcare utilization. In the crude analyses, hospitalization rates decreased among Medicaid patients and increased among Medicare patients compared with the 12 months prior to program enrollment, with no significant changes in rates of ED visits or readmissions. However, after adjusting for age, sex, ACG score, race, and rate of healthcare utilization in the 12 months prior to the program, higher intensity of contacts by CMs, CHWs, or both was not associated with a reduced risk of ED visits, hospitalizations, or readmissions among either Medicaid or Medicare patients.

These findings differ from those of other studies. For example, urban patients with diabetes who were randomized to an intensive CM–CHW intervention had a 23% reduction in ED visits at 24 months compared with patients receiving minimal intervention intensity (outreach once every 6 months), and the rate reduction in utilization was strongest for the patients who received the highest CM and CHW visit frequencies.12 Similarly, an integrated case management program among high-risk Virginia Medicaid patients showed a higher percentage reduction in ED visits as the number of monthly contacts increased.8

The disparate findings may be explained, in part, by differences in the J-CHiP care management program structure. First, whereas the successful programs mentioned previously utilized comprehensive, structured, disease-specific intervention protocols,12,13,17 J-CHiP was an all-condition intervention program without disease-specific interventions. CMs followed generalized processes, without a targeted clinical disease outcome focus. Second, the primary roles of CMs and CHWs in J-CHiP were focused on care coordination and barriers to care, whereas other studies have utilized personnel in expanded, more clinically oriented roles to address disease status.7,12,17 Third, J-CHiP was a health service occurring in real time, administered by a managed care organization, rather than a controlled research trial. Hence, J-CHiP likely experienced more variability, compared with a controlled trial, in aspects of intervention fidelity and personnel. Fourth, the average length of patient follow-up for J-CHiP was shorter on average than for the programs mentioned previously, which collected data for 2 years.

Strengths and Limitations

This evaluation has several strengths. It evaluated a population-based program in a high-risk setting. Baltimore City has a 30% higher mortality rate than the rest of the state of Maryland, and life expectancy varies up to 20 years between neighborhoods in the city.18 Additionally, it tested an all-condition care management approach, instead of implementing several disease-specific interventions, which has had appeal as an efficient means to deliver care management. Moreover, the evaluation utilized primary data sources and employed rigorous analytic methodologies not routinely applied to program evaluation.

This evaluation also has important limitations. First, there is not a control group that was unexposed to the intervention—an inherent difficulty in real-world healthcare delivery. Still, there are several limitations and considerations with use of control groups in this context.19 Second, we were unable to distinguish between avoidable and unavoidable healthcare utilization due to data limitations. Consequently, we cannot determine whether the increase in utilization following program implementation was a result of CM and CHW detection of increased appropriate need for ED visits and hospitalizations among patients receiving the higher intensity of CM and CHW contacts. Third, the program did not collect data to enable analysis of whether specific patient-level behavioral variables (eg, busy vs at home, adherence patterns) influenced contact frequency with CMs and CHWs.

Despite these limitations, we are reassured by our sensitivity analyses. The overall trends in RRs of healthcare utilization were consistent when comparing models with and without adjusting for baseline utilization rate, clinical site, and comorbidities (eAppendix Tables 7-9). We investigated additional cut points between high and low categories for both CHW and CM exposure. We found that results were consistent when using a 50th percentile cutoff for CHW contacts compared with the original 75th percentile threshold. Results remained consistent when using a 90th percentile cutoff for CM contacts compared with the NCQA standard, which was near the 50th percentile (eAppendix Tables 10-12).

We suspect that other care management programs employ similar intervention approaches. Therefore, future programs should test whether structured, evidence-based, disease-specific protocols within an all-condition model reduce healthcare utilization and cost of care. Such programs may benefit from incorporating standardized guidance on frequency of patient contact that is based on clinical disease state(s), barriers, and responsiveness to program intervention.


Evaluation of the J-CHiP care management program provides a meaningful addition to the literature as a real-world, all-condition program implemented in a high-risk population within a large healthcare organization. It raises new questions about the utility of a nonspecific, unstructured approach to care management among Medicaid and Medicare patients. The value of this evaluation is that the results can be used to inform decisions about program effectiveness and quality improvement opportunities.20


The authors would like to thank the patients and staff who participated in this program, and Sonia Munn, MSN, RN; Shannon Murphy, MA; and Eric Bass, MD, MPH, for their contributions.

Author Affiliations: Department of Epidemiology (HSL, PLE, HCY, LJA) and Department of Health, Behavior, and Society (PLE, HCY, FH-B), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University (HSL, PLE, HCY, ND, LJA, FH-B), Baltimore, MD; Division of General Internal Medicine, Johns Hopkins School of Medicine (AA, HCY, ND, LJA, FH-B), Baltimore, MD; Johns Hopkins HealthCare (LA, LD, FH-B), Glen Burnie, MD.

Source of Funding: The project was supported by funding from Johns Hopkins HealthCare and by grant number 1C1CMS331053-01-00 from HHS, CMS. Some contents of this publication were made possible by the Johns Hopkins Institute for Clinical and Translational Research, which is funded in part by grant number UL1 TR001079 from the National Center for Advancing Translational Sciences, a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. Dr Lalani received graduate tuition support from the Gates Millennium Scholars Program. Additional authors were supported by a National Institute of Diabetes and Digestive and Kidney Diseases Diabetes Research Center grant (P30DK079637).

The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of HHS or any of its agencies. The research presented was conducted by the awardee. Results may or may not be consistent with or confirmed by the findings of the independent evaluation contractor.

Author Disclosures: Ms Andon and Drs Dunbar and Hill-Briggs are employed by Johns Hopkins HealthCare, which received funding from the Center for Medicare and Medicaid Innovation for this program. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (PLE, HCY, LA, LD, FH-B); acquisition of data (PLE, ND, LA, FH-B); analysis and interpretation of data (HSL, PLE, AA, HCY, ND, FH-B); drafting of the manuscript (HSL, PLE, ND, FH-B); critical revision of the manuscript for important intellectual content (HSL, PLE, AA, HCY, LA, LJA, FH-B); statistical analysis (HSL, AA); obtaining funding (LD, FH-B); administrative, technical, or logistic support (LD, LJA); and supervision (PLE, LD, LJA, FH-B).

Address Correspondence to: Felicia Hill-Briggs, PhD, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, 2024 E Monument St, Ste 2-518, Baltimore, MD 21205. Email:

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