The Implications of Increasing Primary Care Patient Comorbidity: A Methodological Framework for Nurse Researchers across the World

2.50
Hdl Handle:
http://hdl.handle.net/10755/153088
Type:
Presentation
Title:
The Implications of Increasing Primary Care Patient Comorbidity: A Methodological Framework for Nurse Researchers across the World
Abstract:
The Implications of Increasing Primary Care Patient Comorbidity: A Methodological Framework for Nurse Researchers across the World
Conference Sponsor:Sigma Theta Tau International
Conference Year:2009
Author:Corser, William D., PhD, RN, NEA-BC
P.I. Institution Name:Michigan State University
Title:Associate Professor
[Research Presentation] Purpose: The construct of patient "comorbidity:" is a growing phenomenon now seen in contemporary primary care nursing settings across the world.  As an inherently "messy" study factor, comorbidity must be thoughtfully measured and treated by nurse researchers when studying  patient health outcomes.  An outcomes data set from 247 heterogenous primary care patients in the Midwestern US was used to illustrate how the manner in which primary care patients' composite comorbidity was measured, calculated, or entered into predictive models could affect the highly significant levels of influence of comorbidity on different health outcomes. Methods: A series of multivariate and logit predictive models were first run with blocks of comorbidity, socio-demographic, and other patient data on several psychosocial, functional, and healthcare service use outcomes.  Predictive models were then run with, and without, varied groups of patient variables on the same set of health outcomes to determine how the measured predictive influence of comorbidity changed.  The qualitative remarks from a subset of highly comorbid sample patients were then thematically analyzed to investigate the complex elements of patient's perceived comorbidity burden. Results: The statistical significance of composite patient comorbidity on numerous health outcomes was consistently demonstrated.  Both multicollinear and likely confounded relationships of patient characteristics in conjunction with initially significant comorbidity levels were demonstrated for some, but not other, patient health outcomes.  Conclusion: The manner in which nurse researchers methodologically treat their study patients' composite comorbidity when studying their health outcomes must be carefully considered. A series of methodological implications for nurse researchers across the world striving to measure the influence of primary care patients' increasing comorbidity will be discussed. A methodological framework depicting the fundamental measurement, weighting, and analytic complexity of comorbidity measures for future primary care outcomes research designs will be presented.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Sigma Theta Tau International

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleThe Implications of Increasing Primary Care Patient Comorbidity: A Methodological Framework for Nurse Researchers across the Worlden_GB
dc.identifier.urihttp://hdl.handle.net/10755/153088-
dc.description.abstract<table><tr><td colspan="2" class="item-title">The Implications of Increasing Primary Care Patient Comorbidity:&nbsp;A Methodological Framework for Nurse Researchers across the World</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Sigma Theta Tau International</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2009</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Corser, William D., PhD, RN, NEA-BC</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">Michigan State University</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Associate Professor</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">Corser@msu.edu</td></tr><tr><td colspan="2" class="item-abstract">[Research Presentation] Purpose: The construct of patient &quot;comorbidity:&quot; is a growing phenomenon now seen in contemporary primary care nursing settings across the world.&nbsp; As an inherently &quot;messy&quot; study factor, comorbidity must be thoughtfully measured and treated by nurse researchers when studying &nbsp;patient health outcomes.&nbsp; An outcomes data set from 247 heterogenous primary care patients in the Midwestern US was used to illustrate how the manner in which primary care patients' composite comorbidity was measured, calculated, or entered into predictive models could affect the highly significant levels of influence of comorbidity on different health outcomes. Methods: A series of multivariate and logit predictive models were first run with blocks of comorbidity, socio-demographic, and other patient data on several psychosocial, functional, and healthcare service use outcomes.&nbsp; Predictive models were then run with, and without, varied groups of patient variables on the same set of health outcomes to determine how the measured predictive influence of comorbidity changed.&nbsp; The qualitative remarks from a subset of highly comorbid sample patients were then thematically analyzed to investigate the complex elements of patient's perceived comorbidity burden. Results: The statistical significance of composite patient comorbidity on numerous health outcomes was consistently demonstrated.&nbsp; Both multicollinear and likely confounded relationships of patient characteristics in conjunction with initially significant comorbidity levels were demonstrated for some, but not other,&nbsp;patient health&nbsp;outcomes.&nbsp; Conclusion: The manner in which nurse researchers methodologically treat their study patients'&nbsp;composite comorbidity when studying their health outcomes must be carefully considered. A series of methodological implications for nurse researchers across the world striving to measure the influence of primary care patients' increasing comorbidity will be discussed. A methodological framework depicting the fundamental measurement, weighting, and analytic complexity of comorbidity measures for future primary care outcomes research designs will be presented.</td></tr></table>en_GB
dc.date.available2011-10-26T12:02:05Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T12:02:05Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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