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Janet H. Van Cleave, PhD, MBA, MSN, ACNP-BC Harleah G Buck, PhD, RN, CHPN Susan Lysaght, MA, MS, GNP-BC Melissa O’Connor, PhD, MBA, RN, COS-C Mary D. Naylor,

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Presentation on theme: "Janet H. Van Cleave, PhD, MBA, MSN, ACNP-BC Harleah G Buck, PhD, RN, CHPN Susan Lysaght, MA, MS, GNP-BC Melissa O’Connor, PhD, MBA, RN, COS-C Mary D. Naylor,"— Presentation transcript:

1 Janet H. Van Cleave, PhD, MBA, MSN, ACNP-BC Harleah G Buck, PhD, RN, CHPN Susan Lysaght, MA, MS, GNP-BC Melissa O’Connor, PhD, MBA, RN, COS-C Mary D. Naylor, PhD, RN, FAAN Janet H. Van Cleave, PhD, MBA, MSN, ACNP-BC Harleah G Buck, PhD, RN, CHPN Susan Lysaght, MA, MS, GNP-BC Melissa O’Connor, PhD, MBA, RN, COS-C Mary D. Naylor, PhD, RN, FAAN 1 NEWCOURTLAND CENTER FOR TRANSITIONS AND HEALTH University of Pennsylvania School of Nursing

2 Support University of Pennsylvania School of Nursing NewCourtland Center for Transitions and Health University of Pennsylvania Pre and Post-Doctoral Fellowships, National Institutes of Health, T32NR009356, Individualized Care for At-Risk Older Adults John A. Hartford Foundation Building Academic Geriatric Nursing Capacity Program

3 NewCourtland Center Comorbidity Research Teams Evolutionary Salimah Meghani (Chair) Leah Buck Eeeseung Byun Joan Davitt Michael Fachko Melissa O’Connor Janet Prvu Bettger Minkyoung Song Christine Tocchi Dimensional Analysis Rebecca Trotta (Chair) Janet Van Cleave (Co- Chair) Susan Lysaught Melinda Steis Becky Lorenz Sarah Kagan-Expert Consultant

4 Comorbidity is a Significant Health Problem Individuals with comorbidities – 28% of Americans – 3 out of 4 individuals over the age 65 Increasing number of persons living with comorbidities 1987: 31% Medicare beneficiaries with 5 or more comorbidities 2002: ~50% of all Medicare beneficiaries with 5 or more comorbidities (Anderson, 2010; MedPAC, 2010; U.S. Dept Health & Human Services, 2010)

5 Comorbidities Financially Challenge the Health Care System Driving force of the United States health care spending Individuals with comorbidities account for: – 98% of Medicare costs – Over 60% of total health care expenditures Expenditures increase with each additional comorbidity (Anderson, 2010; U. S. Dept of Health & Human Services, 2010)

6 Comorbidities Medically Challenge the Health Care System Increase mortality and limit function Inappropriate care unaligned with patient’s goals and preferences Fractured care in multiple health care sites (NQF, 2012; Dept of Health & Human Services, 2010)

7 Need for Research U.S. Department of Health and Human Services. Multiple Chronic Conditions—A Strategic Framework: Optimum Health and Quality of Life for Individuals with Multiple Chronic Conditions. Washington, DC. December 2010. Goal 4: Need for research to benefit individuals with comorbidities – Advance knowledge – Develop interventions – Develop systems

8 What is Comorbidity? Multiple terms used in health care to describe comorbidity(ies) Multiple outcomes Temporal components (Feinstein, 1970; Yancik et al., 2007; Vogeli et al., 2007; Wolff, Starfield, & Anderson, 2002; Karlamangla et al., 2007; Weiss, 2007)

9 Research Question What is the definition of comorbidity(ies) – Chronically ill adults – Transitioning through acute episodes of illness

10 Today’s Symposium The Science of Comorbidities: Current Quandaries and Future Recommendations Concept Analyses – Empirical Article Selection for Concept Analysis – Dimensional Analysis: Comorbidities in the Face of Transitions – Evolutionary Analysis: Comorbidity in Patients Undergoing Transitions Closing Remarks

11 Empirical Article Selection for Concept Analysis of Patients with Comorbidities Undergoing Care Transitions Janet H. Van Cleave 1 Harleah G. Buck 2 Salimah Meghani 3 Janet Prvu-Bettger 4 Mary D. Naylor 3 1 New York University, 2 Pennsylvania State University, 3 University of Pennsylvania, 4 Duke University

12 Purpose Decisions regarding search strategies and article selection influence concept analysis findings and impact knowledge development Careful planning and explicit criteria decrease the potential to introduce study bias The purpose of this presentation is to describe our methods to capture a heterogeneous, representative body of empirical literature for two concept analyses

13 Literature Search Goal: Transparent literature search Preliminary literature searches Developed and finalized literature search syntax Buck, H.G., Meghani, S., Bettger, J.P. et al., 2012. The use of comorbidities among adults experiencing care transitions: a systematic review and evolutionary analysis of empirical literature. Chronic Illness.

14 Initial Inclusion Criteria Years of publication: 1965-present Age: Adults 19+ Human English language Research Articles Transition: There should be an acute event with at least one transition from high to low or low to high acuity care. United States (both VA and non-VA)

15 Literature Search Four databases Medline Cinahl PsycINFO Web of Science - Social Science Uploaded into Refworks 5,917 references

16 Representative Heterogeneous Database Random selection of 650 articles (50 articles per working group member) Review articles according to inclusion criteria

17 Initial Review Selected 98 articles Refinement of definition of transition

18 Refinement of Parameters of Transitions An acute episode of chronic illness with at least one transition Transitional settings (i.e., in the context of low to high acuity or high to low acuity care) Related variables directly or indirectly accounted for in the analysis of transitional outcomes (cost, re- hospitalization, functional status, and QOL)

19 Continued Review of Articles Final review for uniformity and fidelity to inclusion criteria Final database: 60 articles

20 Selection of Empirical Articles

21 Empirical Articles Published between 1990 and 2009

22 Description of Empirical Articles

23 Empirical Articles 33 (55%) addressed higher to lower acuity transitions 27 (45%) featured lower to higher acuity transitions

24 Summary: Comorbidities in the Context of Care Transitions

25 New Approaches Patient focused – Loss of the voice of the individual – Individual experience Measuring risk for individuals – Predict or explain outcomes on individual, disease, and system levels – Risk over time – Co-existing vs. co-occurring

26 New Approaches Relationships – Among comorbidities – Among individuals, comorbidities, and consequences Complexity – Synergism vs. relative importance vs. patterns – Number, nature, and extent

27 New Approaches Importance of terminology – Nosology – Principality – Dynamicity

28 Questions Thank you NEWCOURTLAND CENTER FOR TRANSITIONS AND HEALTH University of Pennsylvania School of Nursing


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