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Chronic diseases negatively affect PH but can be identified and managed through the use of CPS .

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Chronic diseases negatively affect PH but can be identified and managed through the use of CPS .

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  1. 2012 State of the Science Congress on Nursing Research“Relationships between Moderators of Access and Clinical Preventive Services Use in Older Adults with Near Universal Health Coverage” Sandra Bibb, DNSc., RNAssociate Professor and Associate Dean for Faculty Affairs Graduate School of NursingUniformed Services University

  2. Improving access to high quality clinical preventive services (CPS) for a growing population of older adults is a major population health (PH) concern in the United States. The incidence of chronic diseases increases with age; 6 of the 7 leading causes of death in older adults are due to chronic diseases.(Federal Interagency Forum on Aging Related Statistics, 2010). • 1 in every 8 Americans (40.4 million) is 65 or older. The 65 and older population will increase to 55 million by the year 2020; 5.5 million adults are 85 and older; 6.6 million will be 85 or older by 2020. (Administration of Aging, 2011). • Chronic diseases negatively affect PH but can be identified and managed through the use of CPS. • (Federal Interagency Forum on Aging Related Statistics, 2010)

  3. Current Characterizations of the Relationships between Access and CPS Use are Inadequate in EXPLAINING Continuing Variations • Adults, 65 and older, with Medicare and a Medicare supplement are the only group in the United States with near universal health coverage (health insurance and a regular place of care), yet variations in the utilization of CPS continue to exist in older adults. (Agency of Healthcare Research and Quality [AHRQ] 2011)

  4. Purpose To identify the relationships between potential moderators (population characteristics, health status/ risks/behaviors) of access (financial, structural, personal) and utilization of clinical preventive services (CPS) in a homogeneous (race, income, education, place of residence) sample of older adults with near universal health coverage (health insurance, regular place of care).

  5. Multiple Factors Determine the Health of Older Adults Source: Older Americans Update. (2008 & 2010) Federal Interagency Forum on Aging Related Statistics

  6. Access is Multifaceted and the Health of Older Adults has Multiple Determinants • Population Health Framework for this study was based on concepts and definitions outlined in: • Baron & Kenny. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations, • Healthy People 2010: Understanding and Improving Health (DHHS, 2000), • The 2007and 2008 Behavioral Risk Factor Surveillance System (BRFSS) survey, and • Older Americans Update 2008: Key Indicators of Well-being (Federal Interagency Forum on Aging Related Statistics [FIFARS], 2008).

  7. Theorized Relationships between Potential Moderators and Utilization of Clinical Preventive Services in Older Adults with Universal Health Coverage

  8. Methodology • Design • Descriptive, exploratory • Human Subjects/Institutional Review Board Approval • Setting/Sample • Convenience sample;202 older adult residents of two privately owned/managed military independent living retirement communities • Community residents were: 1) 65 years of age or older; 2) eligible for Medicare; 3) likely to have health insurance coverage including pre-paid plans (as the result of military/government retirement) or Medicare and a supplement; 4) likely to have had health insurance coverage for at least 12 months; 5) had a regular source of income; and 6) lived in and maintained individual homes

  9. Methodology • Instrumentation • Behavioral Risk Factor Surveillance System (BRFSS) questions are in the public domain; permission to use questions is granted on the BFRSS web site. • The BRFSS Questionnaire has three parts: 1) the core component; 2) optional modules; and 3) state-added questions. The core includes queries about current health-related perceptions, conditions, and behaviors, as well as demographic questions. • Most of the core questions have been identified as at least moderately reliable and valid, and many have been identified as highly reliable and valid.

  10. Methodology • Data Collection • Data were collected: • across two years (2007 to 2009); each participant was interviewed once. • on site and without identifiers in a private room or in the participants’ homes. • Data collectors were part of the research team and were trained in data collection techniques by the principal investigator. • Each question on the questionnaire, was read out loud, to each participant. • Interviews averaged 45 to 60 minutes in length.

  11. Methodology • Data Analysis • Completed questionnaires were coded. • Nominal, ordinal, and scale level data entered into statistical spreadsheet. SPSS version 16.0 was used to conduct all analyses. • Descriptive statistics (frequencies, measures of central tendency) were used to describe and summarize the variables.

  12. Methodology • Data Analysis • Exploratory bivariate analyses…conducted to examine the relationships between moderating factors; and between moderating factors and utilization of CPS. • Hierarchical logistic regression…conducted on all personal access and moderating factor variables to explore the extent to which interactions between personal access variables and theorized moderating factor variables affected utilization of CPS . • Categorical independent and moderator variables… dummy coded for regression analysis. The dependent variables were coded as a dichotomous.

  13. Methodology • Sample Size • All residents at both communities were invited to participate in this exploratory study. • A total of 202 of 596 or 34% of the residents across both communities participated in the study. • For hierarchical logistic regression…models with one personal access variable and one moderating factor, were considered, yielding one interaction term for a total of three independent variables in each logistic regression model. • To achieve stable estimates, at least 10 “events” are required per independent variable where an event is defined as “absence” of the characteristic being measured. Our sample size estimates were based on the assumption that 30% of the observations would correspond to an event. The required sample size was 10x3/.3=100 (Peduzzi, et al. 1996).

  14. Limitations • Self Report • Selection Bias • Methodological Design • Limited Generalizability

  15. Conclusions • Evidence validating the need to differentiate between “having” and “using” access to care in older adults is mounting. • Findings from this study contribute to this mounting body of evidence and support that exploring the impact of non-socially determined moderators on utilization of CPS may yield more insight into variations between “having” and “using” access than could be explained by measurement of the direct effect of having near universal health coverage.

  16. Implications • Primary and secondary analyses studies should be conducted across various types of population groups with varying levels of financial and structural access to care to determine the extent to which the potential moderators identified in this study impact use of clinical preventive services.

  17. Acknowledgements • Acknowledge the support of: • Associate Investigator: Dr. Diane Padden; • Research Associate: Ms. Wakettia Ferguson; and • Research Assistants during Phase II Data Collection (Students in MSN Program): Jean Barido, Shawn Kelly, Linda Nunn-Pridgen, and Michelle Weddle • This research was supported by an Intramural Research Grant from the Uniformed Services University (C061JR). • Bibb, S. C., Padden, D., & Ferguson, W. (2012). Moderators of access and utilization of clinical preventive services in older adults. Journal of Advanced Nursing, 68(2), 335-348.

  18. QUESTIONS?Sandra Bibb, DNSc., RNAssociate Professor and Associate Dean for Faculty Affairs Graduate School of NursingUniformed Services University

  19. Selected References • Agency for Healthcare Research and Quality (AHRQ). (2011). 2010National healthcare disparities report. Rockville, MD: Author. • Baron, R. M. & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations, Journal of Personality and Social Psychology 51(6), pp. 173-1182. • Department of Health and Human Services, Administration on Aging. (2011). A profile of older Americans. Available at: http://www.aoa.gov/AoARoot/Aging_Statistics/Profile/2011/docs/2011profile.pdf • Department of Health and Human Services [DHHS], Centers for Disease Control and Prevention (CDC). (2010). Behavioral Risk factor Surveillance System survey. Available at: http://www.cdc.gov/brfss/questionnaires/questionnaires.htm

  20. Selected References • Department of Health and Human Services (DHHS). (2000). Healthy People 2010: Understanding and Improving Health (2nd ed.) Washington, DC: U.S. Government Printing Office. • Federal Interagency Forum on Aging Related Statistics. (2010). Older Americans update 2010: Key Indicators of well-being. Washington, DC: Author. Available at :http://www.agingstats.gov. • Peduzzi, P., Concato, J., Kemper, E., Holford, T. R., & Feinstein, A. R., 1996. A simulation study of the number of events per variable in logistic regression analysis, Journal of Clinical Epidemiology 49(12), pp. 1373-1379. • Young, T. K. (2005). Population health: concepts and methods, (2nded). New York: Oxford University Press.

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