The Agency for Healthcare Research and Quality Multiple Chronic Conditions Research Network (AHRQ MCC RN) comprises 45 AHRQ-funded research teams all working on studies to advance our understanding of healthcare for persons with multiple chronic conditions (MCC). The AHRQ MCC RN represents one of the largest federal investments in MCC studies, and the research contributions are just coming to light. In this paper we outline the rationale for MCC research, briefly describe the genesis of the AHRQ MCC RN, and discuss selected areas of research pursued by the larger group of MCC investigators, in addition to those represented in this special issue. Finally, we suggest promising directions for future MCC research.
WHY INVEST IN MCC RESEARCH?
By 2030, 171 million Americans are expected to have >1 chronic condition.1 The cohort of individuals with MCC is growing, their healthcare needs are complex, and two thirds of healthcare costs for the US population are currently spent on the 20% of people who have MCC.2 Across diverse populations with MCC, there are significant racial inequalities in treatment and outcomes.3
As a nation, we are poorly equipped to address the complex care of persons with MCC. Historically, clinical trials have applied strict inclusion and exclusion criteria to focus on treatment of one condition in a homogenous study cohort, omitting or at best “controlling” for the presence of MCC. The COURAGE trial of interventions for coronary disease screened 35,539 patients with stable coronary artery disease and excluded 52% because of additional complicating conditions.4 To whom, then, are the results generalizable? Further, what does the primary care clinician recommend for those patients who have coronary artery disease with other complicating conditions?
Research on MCC is needed to answer these and other critical questions. For example, in common disease clusters (eg, heart disease, depression, and diabetes), which treatment strategy is most effective in achieving better whole-person health outcomes? Does adherence to multiple, single disease clinical guidelines improve outcomes or merely increase polypharmacy and side-effects, or decrease adherence? How should clinicians modify treatment protocols for individuals with new diagnoses of cancer, depression, or worsening pulmonary disease when they have a preexisting chronic condition? Single disease focused research will never answer these questions.
GENESIS OF THE AHRQ MCC RESEARCH NETWORK
In 2008, Health and Human Services (HHS) Office of the Assistant Secretary for Health established the HHS Interagency Workgroup on MCC to strengthen efforts directed at all aspects of care for persons with MCC. The Workgroup produced the HHS Strategic Framework on MCC, which is organized by 4 overarching goals, each with associated objectives and action strategies.5 Workgroup representatives collaborated to identify and align federal resources directed at MCC and compiled an inventory of over 100 HHS MCC-related projects and studies.6,7 For example, the Substance Abuse Mental Health Services Administration, the Health Resources and Service Administration, and the Agency for Healthcare Research and Quality each funded projects to better integrate primary and behavioral healthcare.8–11 More recently, the National Institutes of Health convened a national stakeholder meeting to discuss the context surrounding persons with MCC and to develop research, advocacy, clinical care, and data collection agendas.
One of HHS’s largest investments in MCC health services research was made by the Agency for Healthcare Research and Quality (AHRQ), which funded 45 grants between 2008 and 2010.12 Eighteen exploratory R21 grants addressed gaps in knowledge related to MCC patients and preventive services. AHRQ recognized that a barrier to studying individuals with MCC was a dearth of appropriate datasets and funded 14 infrastructure (R24) projects with the stipulation that investigators make their datasets publicly available for future research. An additional 13 R21 grants were funded to conduct comparative effectiveness research. Collectively, the 45 research teams formed the AHRQ MCC RN. Appendix A (Supplemental Digital Content 2, https://links.lww.com/MLR/A686) includes a list of the funded projects and principal investigators. Individual summaries of each grant are grouped according to the 3 categories and are posted at the following 3 links, respectively: http://www.ahrq.gov/professionals/prevention-chronic-care/decision/mcc/mccrn-18grants.html; http://www.ahrq.gov/professionals/prevention-chronic-care/decision/mcc/mccrn-r24grants.html; and http://www.ahrq.gov/professionals/prevention-chronic-care/decision/mcc/mccrn-r21grants.html.
AHRQ MCC RESEARCH NETWORK CONTRIBUTIONS
The body of research emerging from the AHRQ MCC Research Network includes over 70 peer-reviewed manuscripts in addition to those contained in this special journal issue. The studies not only contribute to knowledge but also raise new research questions and point to deficits in existing research methods and measures. Study results touch on important aspects of healthcare for people with MCC, such as comanagement of commonly co-occurring conditions, care for patients with low-prevalence combinations of MCC, the effect of patients with MCC on provider performance metrics, guidelines for preventive services, and medication management in individuals with MCC. AHRQ MCC RN investigators have also developed methods for modeling treatment interventions as well as other MCC-specific methodological and analytical techniques. Below, we elaborate on a subset of the published work by AHRQ MCC RN investigators in each of these categories and provide tables summarizing the implications of selected studies.
Comanagement of Commonly Co-occurring Conditions
Balancing and prioritizing treatment options for MCC is a challenge for patients, providers, and caregivers alike. The severity and number of conditions change over time and care plans need to be adjusted. Table 1 provides a list of studies from the AHRQ MCC RN that addressed disease comanagement and summarizes implications of each study. One study examined what happened to the treatment of persons with MCC who were newly diagnosed with cancer. In the face of poor cancer prognoses, providers continued prescribing statins for cardiovascular disease prevention despite a lack of evidence on statin use near the end of life.13 Similarly, researchers found that diabetes management appeared to be unchanged in the face of a new, potentially severe, comorbidity like a new diagnosis of cancer, depression, or worsening pulmonary disease.14 Applying technology to help patients and clinicians prioritize treatment, MCC investigators designed a computer simulation model to prioritize treatment for individuals diagnosed with diabetes and other MCC that was able to prescribe the most beneficial treatment, given the patient’s personal profile.15
Patients with MCC often rely on family and friends for help with activities of daily living and healthcare needs. One research team funded by AHRQ surveyed caregivers about the difficulty of the healthcare tasks they were undertaking, their personal self-efficacy, depression, and caregiver strain. Giovannetti and colleagues found that the more difficult the healthcare task, the more likely the caregiver was to experience strain and depression. Quality of relationship with the patients and self-efficacy were inversely related to the difficulty of the healthcare tasks. The investigators concluded that health system support for caregiver education and empowerment was needed.16
These findings speak to the importance of maintaining clinical flexibility and adapting treatment strategies to match potentially shifting patient priorities. They also suggest that this flexibility is not yet ingrained in current practice.
CARING FOR PATIENTS WITH LOW-PREVALENCE COMBINATIONS OF MCC
It is estimated that there are about 2 million unique disease combinations among approximately 32 million Medicare beneficiaries.17 Most of the disease constellations have low prevalence, and a challenge for practitioners is to provide the best treatment for those “rare” patients, a subset of whom will appear in any specific health plan or clinical practice. Table 2 summarizes AHRQ MCC RN studies focused on low-prevalence MCC. For example, a study of MCC patients with sickle cell disease found high rates of depression, suicidal ideation, and suicide attempts. Edwards et al concluded that providers need to consider co-occurring mental health indications in their care plans when treating individuals with sickle cell disease.18 Kim and colleagues published one of the first studies to investigate MCC patterns in HIV-infected persons, now that HIV is a chronic, rather than a terminal disease. They found that 65% of study participants (n=1844) had other chronic diseases, and both aging and obesity were risk factors for MCC in this population. The researchers identified 3 patterns of disease clustering, “metabolic,” “behavioral,” and “substance use,” and concluded that treatment guidelines need to be revised to include management of MCC and obesity to improve long-term outcomes of HIV-infected patients.19
THE EFFECT OF PATIENTS WITH MCC ON PROVIDER PERFORMANCE METRICS
Providers are increasingly measured on their performance in following recommended preventive service and clinical treatment guidelines as a means of assessing quality of care. One AHRQ MCC RN team, Thorpe and colleagues, demonstrated that performance metrics were affected by the sample of patients included, and patients with MCC complicated the process. The investigators recommended caution in linking provider performance and payment, especially when care is team-based.20 Another AHRQ MCC RN team, led by Blaum, conducted a longitudinal cohort study of 20,000 patients enrolled in a diabetes registry. The team found that for all age groups, except possibly the oldest men, blood pressure (BP) declined over time, however, the variability of BP measurements over time increased markedly with age. The researchers cautioned against using a one-time measure of BP control in patients with type-2 diabetes to assess quality of care and recommended development of longitudinal measures that demonstrate BP improvement over time in patients with poorly controlled BP.21
PREVENTIVE SERVICES FOR PERSONS WITH MCC
When are preventive services beneficial for patients with MCC? Further, do they receive the services? Ornstein and colleagues examined medical records from a practice-based research network to examine the association of MCC with receipt of 10 preventive services recommended by the US Preventive Services Task Force (USPSTF). They found that individuals with MCC were more likely to be up-to-date with prevention recommendations and, in some cases, the more MCC a person had, the more likely they were to have had a preventive test. It may be that providers with complex patients successfully follow USPSTF guidelines or that MCC patients with frequent visits have more opportunities for preventive interventions.22 Gross and colleagues examined how co-occurring chronic diseases, sex, and age affect the risks and benefits of screening colonoscopy and developed a framework for determining the likelihood that elderly patients with varying levels of chronic disease burden would benefit from screening. For both men and women aged 75 to 79 years with <3 chronic conditions, the procedure was likely to be beneficial. For patients without chronic conditions, screening colonoscopy was beneficial up to an age of 84 years. Conversely, among patients with ≥ 3 conditions, the expected benefits were uncertain for patients aged as young as 67 to 69 years, and the procedure had no expected benefit for men and women older than the ages of 75 and 80 years, respectively. The investigators concluded that substantial population-level health benefits could be achieved if current patterns of care were modified to ensure that the patients who are most likely to benefit from colonoscopy screening are the ones who receive the procedure, based on comorbidity burden as well as age.23Table 3 summarizes studies on preventive services by AHRQ MCC RN researchers.
INTEGRATING AND COORDINATING MENTAL AND PHYSICAL HEALTH
When MCC includes a mental health condition, care can become more complex and expensive.24 Prior research has shown that mental health problems can exacerbate the disability associated with physical health conditions, and patients with such comorbidities consume high levels of medical care services.25,26 Likewise, measures of quality of physical healthcare are often but not always lower among persons with MCC with comorbid mental health conditions.27 AHRQ MCC RN investigators, Druss and colleagues, compared quality of care across 50 states for Medicaid beneficiaries with diabetes and a mental health diagnosis. Mental health conditions were a risk factor for poor diabetes care and for both over and under use of health services. However, in states with higher reimbursement rates for mental health and higher overall spending rates for mental health, the effects were mitigated (Table 4).28
MEDICATION MANAGEMENT AMONG INDIVIDUALS WITH MCC
Medication management and coordination can be extremely challenging for patients with MCC (Table 5). One AHRQ MCC RN research team, Hansen and colleagues, conducted a study of 8000 veterans to examine the effect of coordination of care on medication management and found that patients with more prescribers (ie, less coordination) had greater medication nonadherence, more ER visits, and more hospital admissions. Continuity of medication management appears to be a measurable, but underappreciated, health system factor.29
Another team, Zhang and colleagues looked at the use of erythropoietin to prevent anemia in standard treatment of persons with end-stage renal disease compared with the same treatment for patients who had co-occurring diabetes and cardiovascular disease. They found that erythropoietin was overused in the group with MCC and in some cases led to increased risk of mortality, stroke, heart attack, and congestive heart failure.30 Other investigators examined the burden of medication management and suggested discontinuing medications that do not benefit patients (http://www.ahrq.gov/professionals/prevention-chronic-care/decision/mcc/tinetti_r21grant.pdf; http://www.ahrq.gov/professionals/prevention-chronic-care/decision/mcc/tjia_r21grant.pdf).
INNOVATIVE METHODS AND INTERVENTIONS
Research on MCC has required investigators to utilize methodological techniques appropriate for the complexity of the research questions and study populations. For example, to better prioritize interventions for people with type-2 diabetes who were at risk for hyperlipidemia and hypertension, Mason and colleagues used the Markov model to determine the best treatment plans and also examined the impact of medication adherence and nonadherence on treatment. About 25% of patients consistently took their statins (cholesterol medication) as directed, and adherence increased their expected quality adjusted life-years. However, the majority of patients did not consistently take their medication and, therefore, would not realize the health benefits. Therefore, researchers recommended delaying hypertension treatment for the group that could not consistently take medication. Their analytical techniques made it possible to stratify results by patients’ level of medication adherence.31
A direct care intervention studied by Fischer and colleagues involved the use of text messaging between MCC patients and providers in a safety net system. Patients successfully provided >6000 home measurements of health data (ie, blood sugar, blood pressure, and step counts), to their providers by text message, which were automatically transferred to the electronic medical record. Automated outreach to patients overdue for lab tests and medications was achieved, but gaps in pharmacy data required manual quality review. Participants reported improved awareness of their chronic disease status and enhanced self-management skills.32
MCC RESEARCH INFRASTRUCTURE DEVELOPMENT
AHRQ MCC RN teams created a variety of databases that can be used to study MCC and examples of data aggregation techniques that can be replicated. A unique stipulation of AHRQ’s 14 infrastructure development grants was that investigators attempt to make datasets publicly available, although specific data use agreements and other restrictions prevented some projects from fulfilling this goal. The datasets and related documentation are archived at: http://www.icpsr.umich.edu/icpsrweb/AHRQMCC/; Appendix Table B (Supplemental Digital Content 1 (https://links.lww.com/MLR/A687), contains a list of the Principal Investigators and project summaries. One team, led by Dubard, combined Medicaid claims and enrollment data with state psychiatric hospital data, state-funded mental health data, and data from a regional mental health and developmental disabilities carve-out to study medical home use by Medicaid beneficiaries. By linking 3 previously disconnected datasets, each of which contained information about overlapping groups of individuals, researchers gained greater precision in identifying persons with psychiatric diagnoses and examining the mental health services they used.33
Investigators working with the Collaborative Care Research Network wanted to better understand the integration of mental health providers into primary care practices. Miller and colleagues merged data from 2 large primary care networks and compared practices which had—and had not—integrated mental health providers on the practice’s ability to identify and then initiate treatment for mental health. In practices with integrated mental health providers, the prevalence of co-occurring mental health ranged from 18% to 30%, in contrast to practices without integrated mental health providers in which prevalence ranged from 5% to 48%, indicating substantial variance in practices’ ability to detect mental health conditions.34
The body of work from AHRQ’s unprecedented investment in MCC research will continue to bear fruit over the next few years. However, further investment is needed. There are few funding entities dedicated to MCC research; yet there are great research needs: new analytical methods that include rather than exclude complex individuals, evidence-based best MCC treatment guidelines, and datasets and systems to facilitate further study. Funders of single chronic disease research like diabetes, heart disease, and cancer may wish to consider sponsoring studies that incorporate persons with MCC. Individually and in aggregate, AHRQ MCC RN projects make an important contribution to the state of MCC knowledge and also point to the next set of research questions.
Thoughts on Future Research Priorities
Being at the forefront of an emerging field provides an opportunity to do things differently: to incorporate and understand complexity rather than reducing it. Ultimately, understanding persons with MCC as more than a collection of diseases will help us focus on holistic outcomes in humans who live meaningful lives in relationship with family and community. In doing so we suggest 3 principles to consider:
Include Person-centered and Person-driven Measures and Outcomes
Ultimately, the benefit of healthcare services is in the eyes of the beholder. The grandmother with arthritis and heart disease may prefer to take high doses of medication that allow her to bend down to play with her grandchildren and may not prioritize her heart disease. A family caregiver may feel it is not prudent to strive for tight glucose control in their elderly father with dementia. The busy single mother with hyperlipidemia, lupus, and depression may neglect her referral for colonoscopy screening. There are myriad value judgments, trade-offs, and practicalities that, in combination, affect a person’s healthcare-related goals and desired outcomes. Patient preferences and values need to be assimilated in achieving optimal healthcare.
Consider the Person in the Context of Their Relationships and Community
Clinical complexity is often enmeshed in social complexity, especially for those with MCC who experience challenges related to education, employability, insurability, and disability. Circumstances and personal values may lead individuals with MCC to rank health at varying levels among many other life priorities. Personal resources for self-care outside the health system—the most important factor in health—may be tied to education level, literacy, or socioeconomic status. Families can be a source of strength and resiliency or dysfunction, just as community context may bring risk factors (poverty, crime, etc.) as well as positive value (social support, spiritual community, etc.). Finding a culturally understanding provider or community-based services may not be possible in specific locations. Missing work for medical appointments offered between 9 AM and 5 PM may not be a viable option. The degree of support and help an individual enjoys outside of healthcare will inevitably affect their ability to utilize services.
Include Mental Healthcare as an Essential Part of Healthcare
Mental health conditions, like depression, anxiety, and schizophrenia can be significant sources of disability and must be considered every bit as important a part of healthcare as physical chronic conditions.35 The healthcare system typically segregates clinical care delivery (and payment) for mental health and substance use conditions from other chronic medical conditions, and this fragmentation can lead to increased cost and decreased outcomes.24,36 Mental health comorbidities affect quality of care for medical conditions, as well as overall (whole-person) healthcare expenditures.28,37 Integrating mental health providers into primary care is one way of redesigning health systems to better address the needs of patients whose MCC include mental health conditions.
The AHRQ MCC RN has made a substantial contribution to research on healthcare for those with MCC by creating an enhanced data infrastructure and numerous clinical and policy insights on the care received by persons with MCC. Further work and research is needed to guide evidence-based interventions that will achieve optimal and equitable health outcomes in the broad mix of patient populations characterized by diversity and heterogeneity of clinical and social complexity. Similarly, we need to develop and implement reimbursement strategies that reward multidimensional approaches to complex patient care and complex population management. It will take clinicians, researchers, policymakers, healthcare associations, and patients and families working together to get it done.
The authors thank the AHRQ MCC Research Network investigators. They also thank David Meyers, MD, Jayasree Basu, PhD, and Richard Ricciardi, PhD, NP, of the Agency for Healthcare Research and Quality for their guidance and leadership of the Network; Amy Rosen, PhD, for thoughtful review of the paper; and Jessica Levin and Emma Oppenheim for their assistance in preparing the manuscript.
1. .Chronic Care: Making the Case For Ongoing Care.2010.Princeton, NJ:Robert Wood Johnson Foundation.
2. Goodman RA, Parekh AK, Koh HK.Toward a more cogent approach to the challenges of multimorbidity.Ann Fam Med.2012;10:100–101.
3. Strothers HS III, Rust G, Minor P, et al..Disparities in antidepressant treatment in Medicaid elderly diagnosed with depression.J Am Geriatr Soc.2005;53:456–461.
4. Boden WE, O’Rourke RA, Teo KK, et al..Optimal medical therapy with or without PCI for stable coronary disease.N Engl J Med.2007;356:1503–1516.
5. Parekh AK, Goodman RA, Gordon C, et al..Managing multiple chronic conditions: a strategic framework for improving health outcomes and quality of life.Public Health Rep.2011;126:460–471.
6. .Multiple Chronic Conditions—A Strategic Framework: Optimum Health and Quality of Life For Individuals With Multiple Chronic Conditions.2010.Washington, DC:US Department of Health and Human Services.
7. .US Department of Health and Human Services Inventory of Programs, Activities and Initiatives Focused on Improving the Health of Individuals With Multiple Chronic Conditions.2011.Washington, DC:US Department of Health and Human Services.
8. .FY 2009 grant announcement—CMHS grants for primary and care integration. 2009. Available at: http://www.samhsa.gov/Grants/2009/sm_09_011.aspx
. Accessed October 2, 2013.
9. .Center for Integrated Health Solutions, 2013. Available at: http://www.thenationalcouncil.org/cs/center_for_integrated_health_solutions
. Accessed October 2, 2013.
10. .The Heart Truth, 2011. Available at: http://www.womenshealth.gov/heart-truth/
. Accessed October 2, 2013.
12. .HHS initiative on multiple chronic conditions. Available at: http://www.hhs.gov/ash/initiatives/mcc/
. Accessed October 2, 2013.
13. Bayliss EA, Bronsert MR, Reifler LM, et al..Statin prescribing patterns in a cohort of cancer patients with poor prognosis.J Palliat Med.2013;16:412–418.
14. Bayliss EA, Blatchford PJ, Newcomer SR, et al..The effect of incident cancer, depression and pulmonary disease exacerbations on type 2 diabetes control.J Gen Intern Med.2011;26:575–581.
15. Nichols GA, Gandra SR, Chiou CF, et al..Successes and challenges of insulin therapy for type 2 diabetes in a managed-care setting.Curr Med Res Opin.2010;26:9–15.
16. Giovannetti ER, Wolff JL, Xue QL, et al..Difficulty assisting with health care tasks among caregivers of multimorbid older adults.J Gen Intern Med.2012;27:37–44.
17. Sorace J, Wong HH, Worrall C, et al..The complexity of disease combinations in the Medicare population.Popul Health Manag.2011;14:161–166.
18. Edwards CL, Green M, Wellington CC, et al..Depression, suicidal ideation, and attempts in black patients with sickle cell disease.J Natl Med Assoc.2009;101:1090–1095.
19. Kim DJ, Westfall AO, Chamot E, et al..Multimorbidity patterns in HIV-infected patients: the role of obesity in chronic disease clustering.J Acquir Immune Defic Syndr.2012;61:600–605.
20. Thorpe CT, Flood GE, Kraft SA, et al..Effect of patient selection method on provider group performance estimates.Med Care.2011;49:780–785.
21. Rogers MA, Ward K, Gure TR, et al..Blood pressure trajectories prior to death in patients with diabetes.Diabetes Care.2011;34:1534–1539.
22. Ornstein SM, Jenkins RG, Litvin CB, et al..Preventive services delivery in patients with chronic illnesses: parallel opportunities rather than competing obligations.Ann Fam Med.2013;11:344–349.
23. Gross CP, Soulos PR, Ross JS, et al..Assessing the impact of screening colonoscopy on mortality in the Medicare population.J Gen Intern Med.2011;26:1441–1449.
24. Lurie IZ, Manheim LM, Dunlop DD.Differences in medical care expenditures for adults with depression compared to adults with major chronic conditions.J Ment Health Policy Econ.2009;12:87–95.
25. Merikangas KR, Ames M, Cui L, et al..The impact of comorbidity of mental and physical conditions on role disability in the US adult household population.Arch Gen Psychiatry.2007;64:1180–1188.
26. Kessler RC, Ormel J, Demler O, et al..Comorbid mental disorders account for the role impairment of commonly occurring chronic physical disorders: results from the National Comorbidity Survey.J Occup Environ Med.2003;45:1257–1266.
27. Domino ME, Beadles CA, Lichstein JC, et al..Heterogeneity in the quality of care for patients with multiple chronic conditions by psychiatric comorbidity.Med Care.2014;523 Suppl 2S101–S109.
28. Druss BG, Zhao L, Cummings JR, et al..Mental comorbidity and quality of diabetes care under Medicaid: a 50-state analysis.Med Care.2012;50:428–433.
29. Hansen R, Powers B, Sanders L, et al..Medication adherence and prescriber continuity for complex patients.Ann Pharmacother.2014
30. Zhang Y, Thamer M, Kaufman JS, et al..High doses of epoetin do not lower mortality and cardiovascular risk among elderly hemodialysis patients with diabetes.Kidney Int.2011;80:663–669.
31. Mason JE, England DA, Denton BT, et al..Optimizing statin treatment decisions for diabetes patients in the presence of uncertain future adherence.Med Decis Making.2012;32:154–166.
32. Fischer HH, Moore SL, Ginosar D, et al..Care by cell phone: text messaging for chronic disease management.Am J Manag Care.2012;18:e42–e47.
33. .North Carolina Integrated Data for Researchers (NCIDR). Available at: https://www.communitycarenc.org/informatics-center/ncidr/
. Accessed October 2, 2013.
34. Miller B.Collaborative National Networks Examining Comparative Effectiveness Trials (CoNNECT). 2010 R24 Expansion of Research Capability to Study Comparative Effectiveness in Complex Patients Grants.2013.Rockville, MD:Agency for Healthcare Research and QualityAvailable at: http://www.ahrq.gov/professionals/prevention-chronic-care/decision/mcc/mccrn-r24grants.html
. Accessed October 8, 2013.
35. Horton R.GBD 2010: understanding disease, injury, and risk.The Lancet.2012;380:2053–2054.
36. Petterson SM, Phillips RL Jr, Bazemore AW, et al..Why there must be room for mental health in the medical home.Am Fam Physician.2008;77:757.
37. Shen C, Sambamoorthi U, Rust G.Co-occurring mental illness and health care utilization and expenditures in adults with obesity and chronic physical illness.Dis Manag.2008;11:153–160.