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The American Journal of Managed Care December 2017
Chronic Disease Outcomes From Primary Care Population Health Program Implementation
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Evaluation of the Quality Blue Primary Care Program on Health Outcomes
Qian Shi, PhD, MPH; Thomas J. Yan, MS; Peter Lee, BS; Paul Murphree, MD, MHA; Xiaojing Yuan, MPH; Hui Shao, PhD, MHA; William H. Bestermann, MD; Selina Loupe, BS; Dawn Cantrell, BA; David Carmouche, MD; John Strapp, BA; and Lizheng Shi, PhD, MSPharm
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Evaluation of the Quality Blue Primary Care Program on Health Outcomes

Qian Shi, PhD, MPH; Thomas J. Yan, MS; Peter Lee, BS; Paul Murphree, MD, MHA; Xiaojing Yuan, MPH; Hui Shao, PhD, MHA; William H. Bestermann, MD; Selina Loupe, BS; Dawn Cantrell, BA; David Carmouche, MD; John Strapp, BA; and Lizheng Shi, PhD, MSPharm
Implementation of the Quality Blue Primary Care program in Louisiana was associated with a shift in primary care delivery and reductions in overall cost.
Total ED visits increased in both the QBPC and the control group by 13.86 and 1.84 per 1000 members, respectively, but the increase was significantly higher in the QBPC group (RR, 1.07; P = .0245). Ambulatory ED visits were significantly increased in the QBPC group compared with the control group (RR, 1.08; P = .0130). Admitted ED visits increased in both groups, but no significant difference was observed.

Allowed Amount

In the QBPC and control groups, total allowed amounts increased by $55.15 and $82.24 PMPM, respectively, but the QBPC group had a significantly lower increase compared with the control group (RR, 0.92; P ≤.0001) (Table 3). Total medical cost also increased in both groups, but again, the increase in the QBPC group was significantly less than in the control group (RR, 0.87; P ≤.0001). 

Total allowed amounts for office-based visits and specialists were both reduced in the QBPC group compared with the control group (RR, 0.97; P = .0047; and RR, 0.95; P = .0002, respectively). However, the difference of allowed amount for visits to PCPs/NPs was not significant between groups (RR, 1.01; P = .4595). 

Total costs for admissions decreased in the QBPC group and increased in the control group by $6.10 and $12.75 PMPM, respectively. The decrease in the QBPC group was significant compared with the control group (RR, 0.87; P = .0023), but the cost for admissions with chronic conditions was not significant between groups (P ≥.05).

The total allowed amount for ED visits increased in both the QBPC and control groups by $5.07 and $2.62 PMPM, respectively; however, the increase was significantly greater in the QBPC group compared with the control group (RR, 1.10; P = .0031). Cost for ambulatory ED visits increased significantly in the QBPC group compared with the control group (RR, 1.08; P = .0196). There was no significant difference between groups in the allowed amount for admitted ED visits (RR, 0.96; P = .6580).

The allowed amount per admission decreased by $35.63 in the QBPC group and increased by $91.24 in the control group. The decrease in the QBPC group was significant compared with the control group (RR, 0.92; P = .0484). The allowed amount per admission with chronic condition increased in both the QBPC and control groups, but the difference in increase was not significant between groups (RR, 1.08; P = .2988). 

Diabetes Management 

Screening test rates for A1C increased in the QBPC group by 3.92% and decreased in the control group by 1.66% (Figure 2). The increase in the QBPC group was significant

(P = .0019). Screening test rates for lipids increased in the QBPC group by 1.36% and decreased in the control group by 1.63%. The increase in the QBPC group was not significant compared with the control group (P = .1081). Screening test rates for microalbuminuria increased in the QBPC and control groups by 3.53% and 1.32%, respectively. The increase in the QBPC group was not significant compared with the control group (P = .2536). 

DISCUSSION

The QBPC program was associated with a shift in healthcare utilization toward proactive management and reductions in overall cost during the first year after implementation. These changes were associated with a significant difference in total cost savings between the QBPC and control groups of $27.09 PMPM (Table 3). Savings were derived largely through reductions in total admissions, where we observed a cost difference between the QBPC and control groups of $18.85 PMPM (Table 3). In addition, savings in expenditures were associated with shifts in healthcare utilization by QBPC enrollment toward cost-effective prevention practices. We observed increases in the QBPC group in visits to PCPs and NPs and decreases in visits to specialists (Table 2). We observed a cost reduction in total office-based visits, a difference between the QBPC and control group in total cost of $2.32 PMPM (Table 3). Furthermore, we observed increases in the QBPC group in screening test rates for chronic conditions like diabetes (Figure 2). 

The unexpected increase in overall ED visits observed in the QBPC group was associated with a significant increase in ambulatory ED visits (Table 2). QBPC enrollment was associated with a decrease in ED admissions, but this decrease was not significant (Table 2). An increase in ED use, especially for ambulatory ED visits, can be due to multiple factors. First, other study results have shown that recent changes in health insurance status under the Affordable Care Act for newly insured adults and newly uninsured adults were associated with greater ED use. As policy and economic forces create disruptions in health insurance status, new surges in ED usage should be anticipated.17 Second, increased access to primary care but failure to provide timely care has been shown to increase preventable ED visits (ie, visits for conditions likely preventable by timely outpatient care). By contrast, study findings have shown no significant change in emergent, nonpreventable visits.18 Delayed primary care, defined as a wait of more than 2 weekdays to access a PCP, has been observed to be associated with a higher rate of self-referred ED usage and subsequent discharge.19,20 These data suggest that the increase in ED visits observed in the QBPC group can be attributed to factors (eg, longer wait time to see PCP) beyond the scope of the QBPC program. Furthermore, these findings support our observed increase in ambulatory ED visits, although there was a decrease in total admissions.

Limitations

Our study has several limitations. It was designed as a retrospective database analysis using BCBSLA claims data, which include limited clinical information. Due to insufficient data in reference to partial attribution information for baseline characteristics, the attribution model of patients to providers was defined by the information attained in 2014, which was after the QBPC program was implemented. Baseline characteristics were comparable after adjusting for PS, with the exception of significant differences in age and product type. These differences may reflect imperfect weighting, and thus age and product type were also included in our regression models for utilization and costs. The evaluation of QBPC was limited to those early adopter providers in Louisiana. Therefore, the results may not be generalizable to other insurance policies (eg, Medicare/Medicaid population) or to other states. Results may also not be generalizable to the control group (ie, late adopters or providers that refused to adopt QBPC). Our cost analysis accounted solely for the amount paid by the primary payer (BCBSLA) and assumed that additional payer (out-of-pocket) behavior was independent of the QBPC program. Furthermore, we did not examine the details of each QBPC contract, which varied to some degree, or collect information on clinical procedures and outcomes of enrollees. Although we identified associated improvements and cost reductions, these measures do not consider qualitative feedback provided by enrollees and healthcare providers. The long-term effect of QBPC on improving the quality of care at a lower total cost remains contingent on future financial incentives toward preventive care and providers’ ability to further improve synergies between physicians and their chronic condition management teams. 

CONCLUSIONS

The QBPC program was associated with shifts in healthcare utilization toward proactive management and reductions in overall cost. During the first year of implementation in Louisiana, savings were achieved largely through reductions in office-based visits to specialists and inpatient care. The long-term implications of the QBPC program on improving primary care and patient outcomes at lower total costs warrant additional research.

Acknowledgments

This study expresses the opinions of the Tulane Research Team, including Drs Shi and Shao. Blue Cross Health Analytics Group provided their reviews on the results. Blue Cross Health Care Analytics Group provided members’ and providers’ claims data to Tulane. This study is funded by Blue Cross. In addition to research funding from Blue Cross, Dr Shi receives funding from Patient-Centered Outcomes Research Institute, Agency for Healthcare Research and Quality, National Institute of Health, Bristol-Myers Squibb, Chiasma, and Cepheid.

Author Affiliations: Department of Global Health Management and Policy, School of Public Health and Tropical Medicine (QS, LS), and School of Medicine (TJY), Tulane University, New Orleans, LA; Blue Cross and Blue Shield of Louisiana (PL, PM, XY, HS, WHB, SL, DCan, DCar, JS), Baton Rouge, LA.

Source of Funding: Blue Cross and Blue Shield of Louisiana (BCBSLA).

Author Disclosures: Ms Shi received payment for involvement in the preparation of this manuscript. Mr Lee is employed as vice president of healthcare analytics at BCBSLA, which is the payer for the QBPC program. Dr Murphree is medical director of BCBSLA. Ms Yuan works as a healthcare informatics consultant at BCBSLA. Dr Bestermann is a consultant for BCBSLA and works at the COSEHC Practice Transformation Network, a quality improvement organization. Ms Loupe is employed by BCBSLA. Dr Shi has received grants and honoraria from BCBSLA. 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 (QS, PL, PM, XY, WHB, SL, DCan, DCar, JS, LS); acquisition of data (QS, PL, PM, XY, WHB, SL); analysis and interpretation of data (QS, TJY, PL, XY, HS, WHB, SL, LS); drafting of the manuscript (QS, TJY, PM, WHB, JS, LS); critical revision of the manuscript for important intellectual content (TJY, PL, HS, WHB, DCan, LS); statistical analysis (QS, TJY, XY, HS, LS); provision of patients or study materials (PL, PM); obtaining funding (JS); administrative, technical, or logistic support (PL, PM, XY, SL, DCan, DCar, LS); and supervision (PL, PM, DCar). 

Address Correspondence to: Lizheng Shi, PhD, MSPharm, Tulane University, 1440 Canal St, Ste 1900, New Orleans, LA 70112. E-mail: lshi@tulane.edu.
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