Tacking upwind: reducing spending among high-risk commercially insured patients.

OBJECTIVES: The study examined a commercial accountable care organization (ACO) population and then assessed the impact of an integrated care management program on medical spending and clinical event rates. STUDY DESIGN: Retrospective cohort study of high-risk individuals (n = 487) in a population of 365,413 individuals aged 18 to 64 years within the Mass General Brigham health system who were part of commercial ACO contracts with 3 large insurers between 2015 and 2019. METHODS: Using medical spending claims and other enrollment data, the study assessed the demographic and clinical characteristics, medical spending, and clinical event rates of patients in the ACO and its high-risk care management program. The study then examined the impact of the program using a staggered difference-in-difference design with individual-level fixed effects and compared outcomes of those who had entered the program with those of similar patients who had not entered. RESULTS: The commercially insured ACO population was healthy on average but included several hundred high-risk patients (n = 487). After adjustment, patients within the ACO's integrated care management program for high-risk patients had lower monthly medical spending (by $1361 per person per month) as well as lower emergency department visit and hospitalization rates compared with similar patients who had yet to start the program. Accounting for early ACO departure decreased the magnitude of the program effects as expected. CONCLUSIONS: Commercial ACO populations may be healthy on average but still include some high-risk patients. Identifying which patients might benefit from more intensive care management could be critical for reaping the potential savings.

Population turnover and leakage in commercial ACOs.

OBJECTIVES: Commercial accountable care organization (ACO) contracts attempt to mitigate spending growth, but past evaluations have been limited to continuously enrolled ACO members in health maintenance organization (HMO) plans, excluding many members. The objective of this study was to examine the magnitude of turnover and leakage within a commercial ACO. STUDY DESIGN: A historical cohort study using detailed information from multiple commercial ACO contracts within a large health care system between 2015 and 2019. METHODS: Individuals insured through 1 of the 3 largest commercial ACO contracts during the study period, 2015-2019, were included. We examined patterns of entry and exit and the characteristics that predicted remaining in the ACO compared with leaving the ACO. We also examined predictors of the amount of care delivered in the ACO compared with outside the ACO. RESULTS: Among the 453,573 commercially insured individuals in the ACO, approximately half left the ACO within the initial 24 months after entry. Approximately one-third of spending was for care occurring outside the ACO. Patients who remained in the ACO differed from those who left earlier, including being older, having a non-HMO plan, having lower predicted spending at entry, and having more medical spending for care performed within the ACO during the initial quarter of membership. CONCLUSIONS: Both turnover and leakage hamper the ability of ACOs to manage spending. Modifications that address potentially intrinsic vs avoidable sources of population turnover and increase patient incentives for care within vs outside of ACOs could help address medical spending growth within commercial ACO programs.

When the Process Is the Problem: Racial/Ethnic and Language Disparities in Care Management.

OBJECTIVES: Achieving health equity requires addressing disparities at every level of care delivery. Yet, little literature exists examining racial/ethnic disparities in processes of high-risk care management, a foundational tool for population health. This study sought to determine whether race, ethnicity, and language are associated with patient entry into and service intensity within a large care management program. DESIGN: Retrospective cohort study. METHODS: Subjects were 23,836 adult patients eligible for the program between 2015 and 2018. Adjusting for demographics, utilization, and medical risk, we analyzed the association between race/ethnicity and language and outcomes of patient selection, enrollment, care plan completion, and care management encounters. RESULTS: Among all identified as eligible by an algorithm, Asian and Spanish-speaking patients had significantly lower odds of being selected by physicians for care management [OR 0.74 (0.58-0.93), OR 0.79 (0.64-0.97)] compared with White and English-speaking patients, respectively. Once selected, Hispanic/Latino and Asian patients had significantly lower odds compared to White counterparts of having care plans completed by care managers [OR 0.69 (0.50-0.97), 0.50 (0.32-0.79), respectively]. Patients speaking languages other than English or Spanish had a lower odds of care plan completion and had fewer staff encounters than English-speaking counterparts [OR 0.62 (0.44-0.87), RR 0.87 (0.75-1.00), respectively]. CONCLUSIONS: Race/ethnicity and language-based disparities exist at every process level within a large health system's care management program, from selection to outreach. These results underscore the importance of assessing for disparities not just in outcomes but also in program processes, to prevent population health innovations from inadvertently creating new inequities.

Improving care coordination and reducing ED utilization through patient navigation.

OBJECTIVES: Our study examines the impact of an emergency department (ED) patient navigation program for patients in a Medicaid accountable care organization across 3 hospitals in a large health system. Our program engages community health workers to (1) promote primary care engagement, (2) facilitate care coordination, and (3) identify and address patients' health-related social needs. STUDY DESIGN: Our study was a retrospective analysis of health care utilization and costs in the 30 days following the index ED visit, comparing individuals receiving ED navigation and matched controls. The primary outcome of interest was all-cause return ED visits, and our secondary outcomes were hospital admissions and completed primary care appointments. METHODS: Patients with ED visits who received navigation were matched to comparable patients with ED visits without an ED navigator interaction. Outcomes were analyzed using fixed effects logistic regression models adjusted for patient demographics, ED visit characteristics, and preceding utilization. Our primary outcome was odds of a return ED visit within 30 days, and our secondary outcomes were odds of a hospitalization within 30 days and odds of having primary care visit within 30 days. RESULTS: In our sample, there were 1117 ED visits by patients meeting our inclusion criteria with an ED navigator interaction, with 3351 matched controls. ED navigation was associated with 52% greater odds of a completed follow-up primary care appointment (odds ratio [OR], 1.52; 95% CI, 1.29-1.77). In patients with no ED visits in the preceding 6 months, ED navigation was associated with 32% decreased odds of repeat ED visits in the subsequent 30 days (OR, 0.68; 95% CI, 0.52-0.90). There was no statistically significant impact on return ED visits in those with higher baseline ED utilization. CONCLUSIONS: Our program demonstrates that high-intensity, short-term patient navigation in the ED can help reduce ED visits in those with low baseline ED utilization and facilitate stronger connections with primary care.

The essential role of population health during and beyond COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has fundamentally changed how health care systems deliver services and revealed the tenuousness of care delivery based on face-to-face office visits and fee-for-service reimbursement models. Robust population health management, fostered by value-based contract participation, integrates analytics and agile clinical programs and is adaptable to optimize outcomes and reduce risk during population-level crises. In this article, we describe how mature population health programs in a learning health system have been rapidly leveraged to address the challenges of the pandemic. Population-level data and care management have facilitated identification of demographic-based disparities and community outreach. Telemedicine and integrated behavioral health have ensured critical primary care and specialty access, and mobile health and postacute interventions have shifted site of care and optimized hospital utilization. Beyond the pandemic, population health can lead as a cornerstone of a resilient health system, better prepared to improve public health and mitigate risk in a value-based paradigm.

Enhancing employer coverage of smoking cessation treatment: A randomized trial of the Partners in Helping You Quit (PiHQ) program.

The workplace is a key channel for delivering tobacco cessation treatment to a population. Employers can provide workplace-based programs and/or financial incentives such as health insurance benefits that cover the cost of treatment accessed outside the workplace. Little is known about the effect of combining these strategies. We tested the benefit of adding a workplace cessation program, Partners in Helping You Quit (PiHQ), to comprehensive health insurance coverage of smoking cessation medications by Partners HealthCare, a large Boston-based healthcare delivery system. PiHQ offers biweekly telephone-based behavioral support, additional automated calls, and medication care coordination for 3 months then monthly telephone monitoring for 9 months. In a pragmatic randomized trial, employees who smoked were informed about the insurance benefit, then randomly assigned (2:1) to PiHQ or to active referral to a free 3-month phone-based community program, Massachusetts Quitline (QL). Outcomes were assessed at 3, 6, and 12 months. During 2015-2018, 106 smokers (n = 73 PiHQ, n = 33 QL) enrolled (64% female; 75% white, 21% black; mean age 46 years, mean cigarettes/day = 13). More PiHQ than QL participants made a quit attempt by 3 months (82 vs. 61%, p < .02) and achieved the primary outcome, verified past 7-day cigarette abstinence at 6 months (31 vs. 12%, odds ratio 3.34, 95% CI, 1.05-10.60). Among participants using behavioral support, PiHQ participants completed more scheduled calls and rated counseling helpfulness higher than did QL participants. These results suggest that employers can enhance the impact of providing comprehensive health insurance coverage of smoking cessation medication by adding a phone-based worksite cessation program.

Putting the puzzle pieces together: Adapting a population health infrastructure to Medicaid risk.

As Accountable Care Organizations (ACOs) become more common within state Medicaid programs, health systems are increasingly facing the challenge of developing a population health approach for this population. This case report considers how health systems with a mature population health infrastructure evolve, adapt, and expand programs to take on Medicaid risk and better serve the Medicaid population. Four key implementation lessons were garnered from Partners HealthCare's experience that may be relevant for organizations undergoing similar transformations: 1) A significant portion of a health system's existing population health strategy can be applied to the Medicaid risk population; 2) Leveraging existing population health infrastructure can assist in adapting and adding programs; 3) Additional attention needs to be paid to behavioral health, substance use, and social determinants of health needs across existing and new programing; 4) Patients need to be engaged outside of the traditional primary care setting, including in the emergency department, and through home and community based care.