Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness

Zulman, Donna M.; Asch, Steven M.; Martins, Susana B.; Kerr, Eve A.; Hoffman, Brian B.; Goldstein, Mary K.

doi:10.1007/s11606-013-2616-9

Cited by 149 publications

(143 citation statements)

References 67 publications

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“…Our findings add qualitative detail that supports and expands on the previous cohort study by Grant 13 The MCCRN model is a broad or "ecological" conceptual model based on a review of the literature. This model defines complexity as the gap between patient needs and the services available to them, and incorporates economic, social, and physical factors as "contextual factors" influencing patient needs, the services available, or both.…”

Section: Discussionsupporting

confidence: 83%

“…2,3 Newer models of complexity have been developed that incorporate mental health, social influences, and economic factors that substantially affect chronic disease outcomes. [4][5][6][7][8][9][10][11][12][13][14] For example, building on the work of Stiefel et al 10 with the INTERMED instrument, Peek et al 4 developed the Minnesota Complexity Assessment Method, which assesses 5 domains: illness (both medical and mental illness), readiness to engage, social, health system, and resources for care. It is unclear, however, whether PCPs' perceptions of complexity are aligned with these newer models.…”

Section: Introductionmentioning

confidence: 99%

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Primary Care Physician Insights Into a Typology of the Complex Patient in Primary Care

Loeb

Binswanger

Candrian

et al. 2015

The Annals of Family Medicine

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PURPOSE Primary care physicians play unique roles caring for complex patients, often acting as the hub for their care and coordinating care among specialists. To inform the clinical application of new models of care for complex patients, we sought to understand how these physicians conceptualize patient complexity and to develop a corresponding typology. METHODSWe conducted qualitative in-depth interviews with internal medicine primary care physicians from 5 clinics associated with a university hospital and a community health hospital. We used systematic nonprobabilistic sampling to achieve an even distribution of sex, years in practice, and type of practice. The interviews were analyzed using a team-based participatory general inductive approach. RESULTSThe 15 physicians in this study endorsed a multidimensional concept of patient complexity. The physicians perceived patients to be complex if they had an exacerbating factor-a medical illness, mental illness, socioeconomic challenge, or behavior or trait (or some combination thereof)-that complicated care for chronic medical illnesses.CONCLUSION This perspective of primary care physicians caring for complex patients can help refine models of complexity to design interventions or models of care that improve outcomes for these patients. INTRODUCTIONP rimary care physicians (PCPs) play unique roles caring for complex patients, often acting as the hub for their care and coordinating care among specialists. Algorithms that focus on numbers of conditions, medications, or both, however, may not align with clinicians' definitions of complexity.1,2 Early definitions of patient complexity focused on those factors.2,3 Newer models of complexity have been developed that incorporate mental health, social influences, and economic factors that substantially affect chronic disease outcomes. [4][5][6][7][8][9][10][11][12][13][14] For example, building on the work of Stiefel et al 10 with the INTERMED instrument, Peek et al 4 developed the Minnesota Complexity Assessment Method, which assesses 5 domains: illness (both medical and mental illness), readiness to engage, social, health system, and resources for care. It is unclear, however, whether PCPs' perceptions of complexity are aligned with these newer models.If endorsed by PCPs, newer models of complexity could potentially contribute to improving algorithms for risk adjustment for primary care patient panels, controlling for complexity in secondary database analysis, and designing interventions for complex patients. To inform the clinical application of new models of care for complex patients, we sought to understand how PCPs conceptualize patient complexity and to develop a corresponding typology. METHODSWe used a qualitative study design to conduct in-depth, open-ended interviews with PCPs. Using systematic nonprobabilistic sampling to achieve a 452balanced distribution of sex, years in practice, and type of practice, we recruited physicians from 2 university clinics and 3 community health clinics. 15 We limited o...

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Section: Discussionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Primary Care Physician Insights Into a Typology of the Complex Patient in Primary Care

Loeb

Binswanger

Candrian

et al. 2015

The Annals of Family Medicine

View full text Add to dashboard Cite

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“…Developing applications that synthesize information about multiple conditions and discuss potential interactions and conflicting recommendations is clearly a challenging task, one that is further complicated by a shortage of evidence about treatment in the setting of MCCs. 1,8,[39][40][41][42][43] In addition, insurers, employers, and other payers may be hesitant to reimburse eHealth technology until the effectiveness (and costeffectiveness) of these tools has been established. 44 While many patients currently purchase personal devices and technology, this will not cover the cost of developing and maintaining technology that integrates electronic health record data and facilitates information exchange among health care systems.…”

Section: Discussionmentioning

confidence: 99%

How Can eHealth Technology Address Challenges Related to Multimorbidity? Perspectives from Patients with Multiple Chronic Conditions

et al. 2015

Self Cite

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BACKGROUND: Patient eHealth technology offers potential support for disease self-management, but the value of existing applications for patients with multiple chronic conditions (MCCs) is unclear. OBJECTIVES: To understand self-management and health care navigation challenges that patients face due to MCCs and to identify opportunities to support these patients through new and enhanced eHealth technology. DESIGN: After administering a screening survey, we conducted 10 focus groups of 3-8 patients grouped by age, sex, and common chronic conditions. Patients discussed challenges associated with having MCCs and their use of (and desires from) technology to support self-management. Three investigators used standard content analysis methods to code the focus group transcripts. Emergent themes were reviewed with all collaborators, and final themes and representative quotes were validated with a sample of participants. PARTICIPANTS: Fifty-three individuals with≥3 chronic conditions and experience using technology for healthrelated purposes. KEY RESULTS: Focus group participants had an average of five chronic conditions. Participants reported using technology most frequently to search for health information (96 %), communicate with health care providers (92 %), track medical information (83 %), track medications (77 %), and support decision-making about treatment (55 %). Three themes emerged to guide eHealth technology development: (1) Patients with MCCs manage a high volume of information, visits, and self-care tasks; (2) they need to coordinate, synthesize, and reconcile health information from multiple providers and about different conditions; (3) their unique position at the hub of multiple health issues requires self-advocacy and expertise. Focus groups identified desirable eHealth resources and tools that reflect these themes. CONCLUSIONS:Although patients with multiple health issues use eHealth technology to support self-care for specific conditions, they also desire tools that transcend disease boundaries. By addressing the holistic needs of patients with MCCs, eHealth technology can advance health care from a disease-centered to a patientcentered model.

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“…8 These methods do not necessarily align with clinicians' definition of complexity, which includes behavioral, social, and economic needs. [9][10][11][12][13] Moreover, busy primary care practices may need longer than 1 year to create new workflows to review empaneled patients, categorize patients into different risk tiers, and establish care management services.…”

Section: Discussionmentioning

confidence: 99%

Risk Stratification Methods and Provision of Care Management Services in Comprehensive Primary Care Initiative Practices

et al. 2017

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PURPOSE Risk-stratified care management is essential to improving population health in primary care settings, but evidence is limited on the type of risk stratification method and its association with care management services. METHODSWe describe risk stratification patterns and association with care management services for primary care practices in the Comprehensive Primary Care (CPC) initiative. We undertook a qualitative approach to categorize risk stratification methods being used by CPC practices and tested whether these stratification methods were associated with delivery of care management services.RESULTS CPC practices reported using 4 primary methods to stratify risk for their patient populations: a practice-developed algorithm (n = 215), the American Academy of Family Physicians' clinical algorithm (n = 155), payer claims and electronic health records (n = 62), and clinical intuition (n = 52). CPC practices using practice-developed algorithm identified the most number of high-risk patients per primary care physician (282 patients, P = .006). CPC practices using clinical intuition had the most high-risk patients in care management and a greater proportion of high-risk patients receiving care management per primary care physician (91 patients and 48%, P = .036 and P = .128, respectively).CONCLUSIONS CPC practices used 4 primary methods to identify high-risk patients. Although practices that developed their own algorithm identified the greatest number of high-risk patients, practices that used clinical intuition connected the greatest proportion of patients to care management services. INTRODUCTIONT he Comprehensive Primary Care (CPC) initiative is a multipayer initiative of the Center for Medicare & Medicaid Innovation (CMMI) designed to improve primary care payment to and care delivery by more than 2,000 practitioners who serve approximately 2.5 million patients.1 Medicare and other CPC payer partners pay participating practices a population-based care management fee that supports enhanced services not traditionally paid for by fee for service, including care management. A key care delivery requirement in CPC is to provide risk-stratified care management. CPC requires practices to stratify their patient population into tiers of health care risk using an approach of their choice and then to provide care management to patients most likely to benefit. Implementation of risk-stratified care management can help target limited practice resources to patients most in need of services and potentially reduce costs and improve patient outcomes.2 This study describes the types of various risk stratification methods used in CPC practices and associates risk stratification methods with the provision of care management services. We conducted an analysis of risk stratification methods CPC practices adopted in the first year of the program (October 2012 to December 2013 452 METHODSIn early 2014, CPC practices submitted documentation describing their approach to risk stratification of their patient population a...

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Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness

Cited by 149 publications

References 67 publications

Primary Care Physician Insights Into a Typology of the Complex Patient in Primary Care

Primary Care Physician Insights Into a Typology of the Complex Patient in Primary Care

How Can eHealth Technology Address Challenges Related to Multimorbidity? Perspectives from Patients with Multiple Chronic Conditions

Risk Stratification Methods and Provision of Care Management Services in Comprehensive Primary Care Initiative Practices

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