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Impact of Point-of-Care Case Management on Readmissions and Costs
Andrew Kolbasovsky, PsyD, MBA; Joseph Zeitlin, MD; and William Gillespie, MD

Impact of Point-of-Care Case Management on Readmissions and Costs

Andrew Kolbasovsky, PsyD, MBA; Joseph Zeitlin, MD; and William Gillespie, MD
Implementation of a point-of-care case management team consisting of a nurse, social worker, pharmacist, and health navigators reduced readmissions and associated costs.
Chi-square and independent samples t tests were utilized to test for differences between the baseline group and intervention group prior to intervention for each of the following variables: age, sex, type of insurance coverage (commercial, Medicare, Medicaid), index hospitalization length of stay, index hospitalization cost, and predictive risk score. The predictive risk score was calculated using a proprietary risk algorithm that predicts the prospective risk of hospitalized days in the future year. The higher the predictive risk score, the greater the number of predicted future hospitalized days. Poisson regression was conducted to examine differences in number of readmissions during the 30-day postdischarge outcome period.

Linear regression was conducted to examine differences in inpatient costs during the outcome period. Because these costs were not normally distributed, a log base 10 transformation was conducted. For all regression analyses the following independent variables were included: centered age; sex; type of insurance coverage (commercial, Medicare, Medicaid); length of stay of the index hospitalization (ie, the one where the member became eligible for the POC program); cost of index hospitalization; and condition (intervention group or baseline group). Commercial insurance coverage served as the reference category for type of insurance coverage. For all analyses, statistical significance was set at .05.


There were no statistically significant differences between the 244 baseline group members and the 298 intervention group members on any of the following variables: age, sex, type of insurance coverage, index hospitalization length of stay, index hospitalization cost, or predictive risk score. Descriptive data for all preintervention group comparisons are presented in Table 1.

Case Management Processes

A total of 278 of the 298 (93.29%) intervention group members were enrolled in the POC program, 17 (5.70%) were unreachable, and 3 (1.01%) refused to participate. The program met its goal of enrolling more than 75% of members. On average, members were enrolled within 4.99 days (standard deviation [SD] 7.49 days). This result met the goal of an average number of days to enrollment of fewer than 7. On average, members received services from the POC team for 30.78 days.

Impact of Point-of-Care Case Management on Readmissions

Of the baseline group members, 43 were readmitted (17.60%) with a total of 46 readmissions. This corresponds to 0.19 readmissions per member of the baseline group. A total of 36 intervention group members were readmitted (12.08%) with a total of 37 readmissions. This corresponds to 0.12 readmissions per member of the intervention group. The 0.07 reduction in readmissions per member is a 36.84% reduction.

Baseline group members were readmitted for a total of 338 days, or 1.39 days (SD 4.24 days) per baseline group member, whereas intervention group members were readmitted for a total of 236 days, or 0.79 days (SD 2.76 days) per intervention group member. This 0.6 reduction in the average number of readmitted days per member corresponds to a 43.17% reduction. The results of the Poisson regression model yielded 3 statistically significant variables: condition (Wald x2 = 4.82, degrees of freedom [df] = 1, P <.05); Medicaid (Wald x2 = 6.00, df = 1, P <.05); and index hospitalization cost (Wald x2 = 14.16, df =1, P <.001). Results of the regression model are

presented in Table 2.

Impact of Point-of-Care Case Management on Readmission Costs

The total cost of readmissions in the 30-day outcome period for baseline group members was $673,103.22. This corresponds to $2758.62 (SD $7710.87) per member. The average cost per readmission for baseline group members was $15,653.56 (SD $11,719.50). The minimum cost for a readmission in the baseline group was $2287.38 and the maximum was $50,679.47.

The total cost of readmissions in the 30-day outcome period for intervention group members was $640,505.50. This corresponds to $2149.35 (SD $9153.90) per member. The minimum cost for a readmission in the baseline group was $2287.38 and the maximum was $97,758.53. After removing 1 high-cost outlier, the average cost per readmission in the intervention group was $15,507.06 (SD $7286.34).

Results of the regression model yielded 3 statistically significant variables: condition (t = –2.27, df = 1, P <.05); Medicaid (t = 2.34, df = 1, P <.05); and index hospitalization cost (t = 4.15, df = 1, P <.001). Results of the regression model are presented in Table 3.

Program Savings

The average cost per readmission in the intervention group was $15,507.06. The baseline group had 0.19 readmissions per member. If the 298 intervention group members had readmissions at this rate, 56 readmissions would occur for a total cost of $868,395.36. Multiplying the 36 readmissions that occurred in the intervention group by the same average cost per readmission resulted in total costs of $558,254.16. The difference in these costs is $310,141.20, which corresponds to a $1040.74 savings per member. The total annual savings is $1,240,564.80. The annual cost of the program was $386,000, resulting in an annual return on investment of 3.2:1.


Results of this study demonstrate that integrating a POC team with diverse clinical specialties into the offices of a medical group was associated with significant reductions in 30-day readmissions and associated costs. The savings were more than sufficient to cover the cost of the program. By locating the team at the point of care rather than in the office of the MCO and by utilizing protocols designed to reach hospitalized members as soon as possible, the POC team was able to overcome many of the challenges commonly faced by managed care programs, as evidenced by the team’s ability to enroll 93% of identified members with an average time to enrollment of fewer than 5 days.

Location of the team at the point of care had additional benefits. Members were able to meet with the team in person, often just prior to their initial PCP appointment, allowing the team to deliver care transition interventions while preparing members for their postdischarge appointment. Also, in 1 simple visit or call, each member could access pharmacy, social work, nursing, and health navigator specialties. In addition, team members could easily communicate with and prepare physicians for the initial postdischarge appointment. Lastly, the team was able to arrange for needed preventive health screenings such as mammograms, colorectal screenings, and retinal eye exams.

Regression models identified predictive risk score and Medicaid insurance coverage as statistically significant predictors of readmissions and associated costs. The predicted risk score was expected to be identified as a statistically significant predictor, as it is an estimate of future inpatient utilization. The identification of Medicaid as a predictor underscores the importance of including Medicaid members in interventions aimed at reducing readmissions and associated costs. However, many managed care programs have focused exclusively on Medicare members.

This study has several limitations. Most notably, a randomized trial was not possible within the context of the study. Although the historical comparison group was similar in all assessed demographic and index hospitalization variables and had the same predictive risk scores for readmission, future randomized trials would be beneficial. Also, the intervention was implemented within a medical group with a capitated financial arrangement and a high volume of the MCO’s health plan members. The medical group was willing and able to provide a small space for the POC team in exchange for its services. Future studies should evaluate strategies for adapting this model to medical groups with fewer plan members and with other financial arrangements. In addition, the first 30 days following hospitalization were targeted in this study because it is a time of high rates of readmission. However, additional studies are needed to evaluate the impact of POC programs over longer time periods and to also assess the impact on emergency department, outpatient, and pharmacy utilization over time.

Healthcare reform has generated significant interest in new shared savings payment models such as accountable care organizations, in which medical groups, hospitals, and MCOs partner to lower costs, with each stakeholder sharing in the savings. This study was not completed within an accountable care organization. However, the model of an MCO providing an experienced case management team at the point of care, whose members work closely with both hospital and medical group physicians, is a highly applicable strategy that should enhance shared savings.

Typically, MCOs have the most experience with case management, and many of the traditional obstacles (eg, low enrollment rates, difficulty engaging physicians) can be overcome by integrating the team into the medical office. In addition, the POC intervention emphasizes collaboration between PCP and POC team members to prepare physicians prior to medical appointments to ensure that all member needs are met. This hallmark of patient-centered medical homes can help medical practices meet the standards for these homes.19

To achieve healthcare transformations that meaningfully address the triple aims of improving population health, enhancing the experience of care, and reducing costs, key stakeholders such as MCOs, medical groups, and hospitals will need to collaborate in new ways to best address the unique needs of health plan members at high risk for hospitalization. Integrating a case management team of diverse specialists at the point of care is a promising strategy for overcoming barriers to traditional telephone-based case management to reduce the number of readmissions and enhance member experience by providing services in a setting that is most convenient for members.

Author Affiliations: From EmblemHealth, New York, NY.

Funding: None.

Author Disclosures: The authors (AK, JZ, WG) 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 (AK, JZ, WG); acquisition of data (AK); analysis and interpretation of data (AK); drafting of the manuscript (AK); critical revision of the manuscript for important intellectual content (AK, JZ, WG); statistical analysis (AK); administrative, technical, or logistic support (JZ, WG); and supervision (JZ, WG).

Address correspondence to: Andrew Kolbasovsky, PsyD, MBA, 55 Water St, New York, NY 10041. E-mail:
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