Care Coordination in Primary Care: Mapping the Territory

ABSTRACT

Objective: To document the current approaches to care coordination among different types of care systems in Minnesota.

Study Design: Observational survey of leaders of most of the care systems in Minnesota that have implemented care coordination.

Methods: Survey questions about organizational structure, size, and approach to care coordination were sent to the leaders of 42 care systems with a total of 327 primary care clinics.

Results: Surveys were completed by leaders at every care system participating in this study (100% response rate); 16 small care systems (each with 1-2 clinics) had a total of 26 primary care clinics, 15 medium care systems (3-9 clinics) had 57 clinics, and 11 large care systems (> 9 clinics) had 244 clinics. The large care systems had larger clinics (clinicians per clinic, 8.6 in large vs 4.3 in small and 5.2 in medium; P = .03) and more clinicians per care coordinator (5.7 vs 3.3 and 4.0; P = .04). They also more frequently included a social worker in their care coordination team: 82% vs 25% of small and 40% of medium care systems (P = .01). However, the services provided and complexity tools used were similar. Nearly all reported addressing both medical and social needs for their complex patients with multiple chronic conditions.

Conclusions: Although there are large differences in resources and capabilities between large and small care systems, they were not associated with much difference in the approach taken to care coordination. This map of the care coordination territory in Minnesota has the potential to be valuable to researchers and care system leaders for understanding current implementation trends and directing further evaluations.

Am J Manag Care. 2023;29(10):e284-e291. https://doi.org/10.37765/ajmc.2023.89403

Takeaway Points

A survey completed by leaders of 100% of 42 diverse care systems in Minnesota with 327 primary care clinics participating in an observational study demonstrated the following:

• There was little difference in approach to care coordination between large and small care systems.
• Large care systems were more likely to have a social worker as part of clinic care teams.

This information should help care system leaders and researchers better understand how to improve and study care coordination.

Care coordination is commonly defined as “the deliberate organization of patient care activities between 2 or more participants involved in a patient’s care to facilitate the appropriate delivery of health care services.”¹ Although care coordination has been viewed for at least 20 years as a potentially important way to improve quality, costs, and patient experience of medical care, the findings of numerous primary studies and systematic reviews of its effectiveness have been inconclusive.^1-8 Although there is some evidence of benefits for some populations in some settings, it continues to be unclear what the key mechanisms are for program effectiveness and whether specific aspects of settings, programs, personnel, or patient populations are important for effectiveness. Part of that lack of clarity may be due to the overlapping use of coordination with terms such as disease management, case management, and care management in the literature. Disease management is usually focused on a particular condition, case management is often limited to a particular care setting, and care management seems to be used interchangeably with care coordination as defined earlier and can include either brief or continuous efforts to improve care for individuals with complex needs.⁹

Understandably, most of the literature has focused on whether care coordination can affect quality, cost, or experience rather than on what approaches to care coordination produce those outcomes, in which settings, and for which patients. An especially important question is whether having clinic personnel address the social needs of patients with multiple chronic conditions makes a difference in patient outcomes or utilization. In the absence of such information about what works best, and because payers have a similar problem in knowing what services to cover, most care systems have been reluctant to implement care coordination in a major way. An important initial step in clarifying this situation is to map the territory to learn what approaches and strategies are in use in what types of care systems and for which patients.

To provide such information, this article documents the overall targets and goals of existing care coordination programs at the care system level in a state where a state agency (the Minnesota Department of Health [MDH]) encourages care systems and their primary care clinics to implement care coordination services. In Minnesota, a place where patients receive outpatient medical services is usually called a clinic, without regard for the socioeconomic status of those patients or the extent to which care is covered by government programs. Most independent clinics providing primary care in Minnesota have merged or were purchased by larger care systems, so this article focuses primarily on the owner of clinics, whether that is an independent clinic or a larger care system. In 2008, the state legislature directed the establishment of a certification program for primary care clinics that wish to be identified as Health Care Homes (the Minnesota version of the national movement for patient-centered medical homes).^10-12 Five standards of care must be implemented for a clinic to be certified (1 of which is care coordination), but how a clinic chooses to meet these standards is mostly up to that clinic. The definition that the MDH uses in certification is that “care coordination is a team approach that engages the patient, the personal clinician or local trade area clinician, and other members of the Health Care Home team to enhance the patient’s well-being by organizing timely access to resources and necessary care that results in continuity of care and builds trust.”¹² The standard does not specify limiting coordination services to either short- or long-term patients, so most care systems use it for both purposes. Because reimbursement for care coordination services has been limited,¹³ we were particularly interested in whether smaller care systems would implement care coordination services differently from larger ones that have more resources.

METHODS

Context

The MDH has been certifying primary care clinics as Health Care Homes since the program was established in 2010.¹³ The goal was to encourage improvement in quality, costs, and patient experience by recognizing clinics that had achieved standards for 5 processes: care coordination, access and communication, patient tracking and registry, care plans, and performance reporting/quality improvement.¹² Certification was developed to allow such clinics to receive additional reimbursement from state payment programs and hopefully from private insurers as well.¹³ In reality, the coverage has been limited in amount and it is time-consuming to document services, so even with certification, many care systems reportedly do not bother to submit charges for care coordination services.¹³ Nevertheless, the program has grown to include approximately 45% of primary care organizations and 60% of primary care clinics in the state, even with the requirement for recertification every 3 years. Because there is substantial flexibility in how care systems meet the 5 standards for certification, there is substantial variability possible in how they approach the delivery of care coordination services.¹⁴ This study is intended to document that variation at the organizational or care system level.

Recruitment and Data Collection

Because the MDH was one of the primary partners for this study, we recruited from all clinics certified as Health Care Homes in Minnesota. Other inclusion criteria were that the clinic must serve adults, have at least 10 patients in care coordination, and report data to Minnesota Community Measurement (an independent nonprofit organization funded by the health plans) for public reporting on a variety of quality measures. Recruitment was directed at care system leaders who were able to decide on participation in the study on behalf of all their eligible sites. The MDH waived the next Health Care Homes recertification for participating clinics as a substantial incentive to participate. A senior physician researcher (L.I.S.) recruited large care systems, whereas systems with fewer than 10 eligible clinics were recruited by MDH staff, who often knew key leaders from their ongoing interactions for the Health Care Home program.

An initial step in participation required completion of an online survey by a leader from each care system in late 2021 that included questions about the care system structure and its approach to care coordination. In most cases, the respondent was the senior leader who had agreed or obtained leadership agreement to participate in the study and who served thereafter as liaison to the study team. The survey was novel and focused on organizational attributes; as such, no existing surveys with known psychometric properties could be used. We developed questions using best practices for question writing and then reviewed them for face validity and ease of completion with content experts and individuals similar to the intended audience.¹⁵

The final survey contained 53 questions. The questions asked about the size of the overall organization and its primary care clinics, the approach and staffing used for care coordination, and whether changes were made in care coordination during the COVID-19 pandemic or are planned for the future. The survey also asked open-ended questions about the following:

• How they measured whether care coordination was a success
• The main barriers or challenges to the effectiveness of care coordination
• What would make care coordination more effective
• The main benefits to the care system of providing care coordination
• The main benefits to the patients

One leader from each care system completed the survey online, although respondents were welcome to obtain information from their colleagues in doing so. The overall study was reviewed, approved, and monitored by the HealthPartners Institutional Review Board and review boards from those participating organizations that had their own review processes. However, this particular study activity was exempt from review because it was asking about the organization rather than about individuals’ personal data. The complete survey is available by request from the authors.

Analysis

The total number of reported primary care clinics operated by a care system allowed us to categorize care systems into small (1-2 clinics), medium (3-9 clinics), and large (> 9 clinics) systems as a rough measure of organizational resources. This count includes pediatric and uncertified primary care clinics—some of which were outside Minnesota—but does not include specialty clinics or inpatient sites. Each care system’s geographic location (rural or urban) was determined using the US Census Bureau Rural-Urban Commuting Area (RUCA) codes. Care systems were categorized as urban (RUCA codes 1-3) or rural (RUCA codes 4-10) depending on which area contained most of their clinics.

Survey items capturing a care system’s overall structure and staffing and care coordination services were summarized. To create comparable descriptive information on staffing, the reported number of care staff (eg, adult primary care physicians) was standardized using the total number of primary care clinics, resulting in data on number of staff per clinic. This allowed for comparison across care systems of different sizes. Counts of staff, patient panel size, and other continuous measures were summarized with medians and IQRs. The distributions of responses were compared among the 3 size categories using Wilcoxon tests for nonparametric data. Survey items with categorical responses were summarized by care system size and compared using Fisher exact tests. Responses to open-ended questions were coded by a single analyst (L.I.S.) for similar categories of responses and summarized in relation to care system size. Missing data were noted and described as part of the results. All quantitative analysis was performed in SAS version 9.4 (SAS Institute).

RESULTS

At the time of study recruitment, 73 care systems with 415 primary care clinics were certified Health Care Homes in Minnesota, but only 67 with 385 clinics fulfilled the study eligibility criteria for adult patients and at least 10 care coordination patients (Figure). Of these, 25 care systems with 58 clinics declined participation or were unresponsive to multiple invitations, mostly related to limited capacity from pandemic-related stresses. Thus, 42 care systems with 327 clinics (85% of the eligible clinics) were included in the study and eligible for the survey. Of these, all 42 care systems returned completed surveys, with 49% completed by administrative leaders, 37% by care coordination leaders, and 14% by other leaders.

The characteristics of the 42 participating care systems are described in Table 1 in relation to their size as measured by total number of primary care clinics. There were roughly similar numbers of care systems in each size grouping, but large care systems had the great majority of clinics (75%). Large care systems tended to be more urban, include more hospitals, and have larger individual clinics as measured by the number of physicians per clinic or adult primary care clinicians (including physicians, nurse practitioners, and physician assistants) per clinic. However, they had no more nurse practitioners, physician assistants, or specialty clinicians per clinic compared with small and medium care systems.

Most large care systems reported having a social worker as an integral member of the care coordination team, whereas this was much less frequent in smaller care systems (Table 2). Care systems of different sizes all had similar numbers of care coordinators per clinic, but small and medium care systems reported fewer adult primary care clinicians per coordinator (3.3 and 4.0 vs 5.7 in large care systems). Otherwise, staffing patterns, numbers of care coordinators or care coordination patients per clinic, and panel size per coordinator were similar regardless of care system size.

Table 3 demonstrates that there were also no statistical differences among different-sized care systems in either the types of patients they targeted for care coordination or the kinds of coordination services that they provided. Nearly all participants reported targeting each type of patient asked about and providing nearly all identified services, but assistance with finances (69%), employment (52%), and spiritual needs (50%) were less commonly reported by all care systems. Most care systems also used a tool to assess complexity for some or all patients. Only 5% of the care systems reported having considerably reduced their budget for care coordination during the disruptions brought on by the COVID-19 pandemic, and size was not significantly associated with that decision (P = .54). Finally, although many care systems had told us they did not find it worthwhile to bill for coordination services, 90% reported billing various payer types and half even billed patients.

In response to the open-ended questions, the leaders of these groups revealed more about their care systems’ thinking about care coordination (responses grouped and listed in order of frequency). We also provide Table 4 with quotations from survey respondents to illustrate these further:

1. How does your group measure whether your care coordination program is a success? Nearly all respondents reported that success was measured through some combination of utilization rates, quality measures, patient satisfaction surveys, care coordination process measures, and patient/staff stories. Most large systems appeared to rely on quantitative measures, and none mentioned the patient stories that one-third of the smaller group respondents did.
2. What are the main barriers or challenges to the effectiveness of care coordination? Staffing challenges were mentioned by 40% of care systems. Other barriers noted by 10% to 20% of care systems were lack of dedicated staff time for care coordination, community resource availability and knowledge, organizational finances, electronic health record issues, physician buy-in, patient engagement, and specialty access. Small systems less frequently reported staffing and dedicated staff time as barriers.
3. What other factors or strategies would make care coordination more effective? Small numbers of respondents identified a variety of factors for improving the effectiveness of care coordination, from more funding to additional dedicated staff time, additional social workers, measures of outcomes, better tech support, and more staff training.
4. What are the main benefits of providing care coordination for your medical group? Half the respondents and all but 1 large system thought that the main benefit of providing care coordination was improved patient outcomes. One-third reported that care coordination improved relationships with patients and patient-centeredness while reducing inpatient utilization.
5. What are the main benefits of providing care coordination for the patient? Having a trusted personal contact who will listen to their problems, provide feedback, and help them access the care system were noted as main benefits for patients by three-fourths of respondents.

Few of these answers differed among care system of different sizes, although large care systems were somewhat more likely to report financial barriers and to care about utilization reductions.

DISCUSSION

In a state where a majority of primary care clinics have agreed to provide care coordination services to their high-need, high-cost patients, these survey data provide a potentially generalizable picture of the way that these care systems have structured care coordination. Contrary to our expectations, the large, high-resource care systems do not seem to have set up care coordination in significantly different ways from smaller ones. A notable exception from this survey is that large system leaders more frequently reported including social workers as part of the care coordination team. Medium and small care systems just as frequently reported targeting their care coordination efforts toward patients with social or community resource needs and to providing services for those needs, despite usually lacking a social worker to help do so.

Few studies have addressed the question of whether the size or ownership of medical groups makes a substantive difference in the quality or cost of care provided. In a study of a very similar set of Minnesota primary care clinics, we recently demonstrated that large care systems had better performance on multiple measures of diabetes outcomes than either medium or small ones.¹⁶ That benefit may be related to finding that large care systems also had more care management processes (eg, clearly established care protocols) in place than smaller care systems.

Most studies of care coordination or care/case management have focused on whether it leads to improvements in the types of success measures that were also identified by care system leaders in this study.^6,8,17,18 However, those studies rarely provided much information about either patient characteristics or the care coordination process in relation to various outcomes, so systematic reviews mostly end up concluding that it is not clear what patient selection factors or care coordination model specifics are important. Although we do not yet have measures of outcomes, this description of approaches taken by diverse care systems provides a framework for understanding the current context of care coordination among Minnesota care systems. This information could facilitate further studies of the impact of care coordination processes on specific outcomes.

The most interesting aspect of this care coordination landscape is how nearly all care systems in Minnesota that provide care coordination report that they are assessing and providing services for social needs and that patients with such needs are a target for enrollment in care coordination. For all the attention this topic has drawn in the past decade, surprisingly little information exists in the literature about the comparative effectiveness of interventions that address both medical and social needs of complex patients.^19-21 A recent systematic review of this information gap by Albertson et al found that “needs assessment, in-person patient contact, and standardized care coordination protocols are common across programs that bridge health care and social services” but that there are limited program details described and no data on impacts.² A scoping review by Savitz et al did not find any evidence-based models for coordinating services for individuals with multiple chronic conditions, so the investigators went on to conduct structured interviews with experts on this topic.⁷ All those experts described the need to identify and address social risks as well as medical risks in caring for patients with multiple chronic conditions. The paper also concluded that “a greater reliance on pragmatic investigations from learning health systems along with mixed methods and observational studies is needed.” The larger study from which this information is reported is designed to provide such an investigation and information that can be used by other researchers (including those from the management field) as well as care system leaders.²²

A similar problem exists for care coordination more broadly. Duan-Porter et al conducted a systematic review of systematic reviews of the implementation and outcomes of various care coordination models.⁵ Only 2 of 16 systematic reviews identified any specific characteristics of care coordination models that were associated with effectiveness and those only found it important to select patients with specific risk factors or needs.^23-27 Other systematic reviews have noted a lack of literature that is able to causally associate key characteristics of care coordination models with patient outcomes.^4,5,7 As important, Ganguli, Powers, and others have pointed out that “the majority of care management programs remain under the purview of payers,” despite the fact that care management programs are “most effective when they are anchored in the practices where patients receive their care.”^28,29 Thus, we are hoping to learn what those specific effective features are for programs run by and in the primary care setting, although we recognize that other state or national programs such as California Advancing and​ Innovating Medi-Cal and the Camden Coalition may also identify such features in other contexts.

Limitations

One of the limitations of these findings is the self-selection bias introduced by care systems choosing to become Health Care Homes and then to participate in this study, so the findings are limited to primary care clinics and systems that are interested in providing and improving care coordination. However, the 100% response rate minimizes other biases. The survey was also conducted at a time when there was still some stress on care systems from the COVID-19 pandemic that might have distracted both respondents and care coordination programs. More importantly, we do not yet have outcome measures to compare with the identified characteristics and the functional strategies. The responses to the open-ended questions were subjective, based on what an organizational leader believes to be true.

CONCLUSIONS

This study is the first detailed description of the approach to care coordination among a large portion of the primary care organizations in a single US state. That description may be useful to researchers and policy makers and to care system leaders interested in developing or modifying their care coordination programs. Having this initial structural information could facilitate further analysis seeking to correlate specific structural features of care coordination with impact on outcomes. It also illustrates the extent to which care systems in Minnesota are trying to combine care for both medical and social needs, at least for their most complex patients. Individual clinics or very small care systems appear to be able to adopt care coordination programs that are very similar in scope and intensity to those of their much larger and better-resourced competitors, although we have yet to learn whether the outcomes produced are different.

Author Affiliations: HealthPartners Institute (LIS, AB, JYZ, MMJ, EAC, MSB, SPD), Minneapolis, MN; Morrison Family College of Health, School of Social Work, University of St. Thomas (RRW), St Paul, MN; Johns Hopkins University (KM), Baltimore, MD; Minnesota Department of Health, Health Care Homes Program (BL), St Paul, MN.

Source of Funding: This work was supported through a Patient-Centered Outcomes Research Institute (PCORI) Project Program Award (IHS-2019C1-15625). All statements in this report, including its findings and conclusions, are solely those of the authors and do not necessarily represent the official views of PCORI, its Board of Governors, or its Methodology Committee.

Author Disclosures: Drs Solberg and JaKa report being employees of HealthPartners Institute and receiving a grant from PCORI for this study. Ms Bergdall reports being an employee of HealthPartners Institute, which received the research funding. Dr McDonald received consulting fees for her participation in this project. 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 (LIS, AB, JYZ, MMJ, MSB, KM, BL, SPD); acquisition of data (LIS, AB, JYZ, MMJ, MSB, SPD); analysis and interpretation of data (LIS, JYZ, MMJ, RRW, EAC, MSB, KM, SPD); drafting of the manuscript (LIS, AB, RRW, EAC, BL); critical revision of the manuscript for important intellectual content (LIS, AB, MMJ, RRW, EAC, MSB, KM, BL, SPD); statistical analysis (EAC); provision of patients or study materials (AB); obtaining funding (LIS, MMJ, BL, SPD); administrative, technical, or logistic support (LIS, AB, BL); and supervision (LIS, JYZ, SPD).

Address Correspondence to: Leif I. Solberg, MD, HealthPartners Institute, PO Box 1524, Mail Stop 21112R, Minneapolis, MN 55440-1524. Email: Leif.I.Solberg@HealthPartners.com.

REFERENCES

1. McDonald KM, Sundaram V, Bravata DM, et al. Closing the quality gap: a critical analysis of quality improvement strategies (vol. 7: care coordination). Agency for Healthcare Research and Quality. June 2007. Accessed July 19, 2022. https://www.ncbi.nlm.nih.gov/books/NBK44015/

2. Albertson EM, Chuang E, O’Masta B, Miake-Lye I, Haley LA, Pourat N. Systematic review of care coordination interventions linking health and social services for high-utilizing patient populations. Popul Health Manag. 2022;25(1):73-85. doi:10.1089/pop.2021.0057

3. Conway A, O’Donnell C, Yates P. The effectiveness of the nurse care coordinator role on patient-reported and health service outcomes: a systematic review. Eval Health Prof. 2019;42(3):263-296. doi:10.1177/0163278717734610

4. Delaney RK, Sisco-Taylor B, Fagerlin A, Weir P, Ozanne EM. A systematic review of intensive outpatient care programs for high-need, high-cost patients. Transl Behav Med. 2020;10(5):1187-1199. doi:10.1093/tbm/ibaa017

5. Duan-Porter W, Ullman K, Majeski B, Miake-Lye I, Diem S, Wilt TJ. Care coordination models and tools—systematic review and key informant interviews. J Gen Intern Med. 2022;37(6):1367-1379. doi:10.1007/s11606-021-07158-w

6. Moe J, Kirkland SW, Rawe E, et al. Effectiveness of interventions to decrease emergency department visits by adult frequent users: a systematic review. Acad Emerg Med. 2017;24(1):40-52. doi:10.1111/acem.13060

7. Savitz LA, Bayliss EA. Emerging models of care for individuals with multiple chronic conditions. Health Serv Res. 2021;56(suppl 1):980-989. doi:10.1111/1475-6773.13774

8. Soril LJJ, Leggett LE, Lorenzetti DL, Noseworthy TW, Clement FM. Reducing frequent visits to the emergency department: a systematic review of interventions. PLoS One. 2015;10(4):e0123660. doi:10.1371/journal.pone.0123660

9. Ahmed OI. Disease management, case management, care management, and care coordination: a framework and a brief manual for care programs and staff. Prof Case Manag. 2016;21(3):137-146. doi:10.1097/NCM.0000000000000147

10. Soderberg K, Rajamani S, Wholey D, LaVenture M. Health reform in Minnesota: an analysis of complementary initiatives implementing electronic health record technology and care coordination. Online J Public Health Inform. 2016;8(3):e204. doi:10.5210/ojphi.v8i3.7094

11. Minnesota Health Care Homes. Health Care Homes: improving health for all—annual report to the legislature. Minnesota Department of Health. May 2018. Accessed July 19, 2022. https://www.health.state.mn.us/facilities/hchomes/legreport/docs/2017hchlegreport.pdf

12. Health Care Homes: redefining health | redesigning care. Minnesota Department of Health. Updated January 31, 2023. Accessed February 15, 2023. https://www.health.state.mn.us/facilities/hchomes

13. Lowen JT. Health Care Homes. home alone. Minn Med. 2011;94(2):8-9.

14. Minnesota Health Care Homes. Health Care Homes: celebrating 10 years of redefining health, redesigning care: 2019 year end report. Minnesota Department of Health. December 31, 2019. Accessed July 19, 2022. https://www.health.state.mn.us/facilities/hchomes/yrendreport/docs/2019hchyrendrpt.pdf

15. Dillman DA, Smyth JD, Christian LM. Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method. 4th ed. Wiley; 2014.

16. Solberg LI, Carlin CS, Peterson KA, Eder M. Diabetes care quality: do large medical groups perform better? Am J Manag Care. 2022;28(3):101-107. doi:10.37765/ajmc.2022.88836

17. Iovan S, Lantz PM, Allan K, Abir M. Interventions to decrease use in prehospital and emergency care settings among super-utilizers in the United States: a systematic review. Med Care Res Rev. 2020;77(2):99-111. doi:10.1177/1077558719845722

18. Joo JY, Liu MF. Case management effectiveness in reducing hospital use: a systematic review. Int Nurs Rev. 2017;64(2):296-308. doi:10.1111/inr.12335

19. Brown DM, Hernandez EA, Levin S, et al. Effect of social needs case management on hospital use among adult Medicaid beneficiaries: a randomized study. Ann Intern Med. 2022;175(8):1109-1117. doi:10.7326/M22-0074

20. Fichtenberg CM, Alley DE, Mistry KB. Improving social needs intervention research: key questions for advancing the field. Am J Prev Med. 2019;57(6 suppl 1):S47-S54. doi:10.1016/j.amepre.2019.07.018

21. National Academies of Sciences, Engineering, and Medicine. Integrating Social Care Into the Delivery of Health Care: Moving Upstream to Improve the Nation’s Health. The National Academies Press; 2019.

22. Mayo AT, Myers CG, Sutcliffe KM. Organizational science and health care. Acad Manag Ann. 2021;15(2):537-576. doi:10.5465/annals.2019.0115

23. Hudon C, Chouinard MC, Pluye P, et al. Characteristics of case management in primary care associated with positive outcomes for frequent users of health care: a systematic review. Ann Fam Med. 2019;17(5):448-458. doi:10.1370/afm.2419

24. Smith SM, Soubhi H, Fortin M, Hudon C, O’Dowd T. Managing patients with multimorbidity: systematic review of interventions in primary care and community settings. BMJ. 2012;345:e5205. doi:10.1136/bmj.e5205

25. Baker JM, Grant RW, Gopalan A. A systematic review of care management interventions targeting multimorbidity and high care utilization. BMC Health Serv Res. 2018;18(1):65. doi:10.1186/s12913-018-2881-8

26. Edwards ST, Peterson K, Chan B, Anderson J, Helfand M. Effectiveness of intensive primary care interventions: a systematic review. J Gen Intern Med. 2017;32(12):1377-1386. doi:10.1007/s11606-017-4174-z

27. Totten AM, White-Chu EF, Wasson N, et al. Home-based primary care interventions. Agency for Healthcare Research and Quality Comparative Effectiveness Review No. 164. February 2016. Accessed July 19, 2022. https://www.ncbi.nlm.nih.gov/books/NBK356253/

28. Ganguli I, Orav EJ, Weil E, Ferris TG, Vogeli C. What do high-risk patients value? perspectives on a care management program. J Gen Intern Med. 2018;33(1):26-33. doi:10.1007/s11606-017-4200-1

29. Powers BW, Chaguturu SK, Ferris TG. Optimizing high-risk care management. JAMA. 2015;313(8):795-796. doi:10.1001/jama.2014.18171