Literature DB >> 12363045

Understanding variation in chronic disease outcomes.

Paul E Johnson1, Peter J Veazie, Laura Kochevar, Patrick J O'Connor, Sandra J Potthoff, Devesh Verma, Pradyumna Dutta.   

Abstract

We propose an explanation for variation in disease outcomes based on patient adaptation to the conditions of chronic disease. We develop a model of patient adaptation using the example of Type 2 diabetes mellitus and assumptions about the process entailed in transforming self-care behaviors of compliance with treatment, compliance with glucose monitoring, and patient's knowledge seeking behavior into health outcomes of glycemic control and patient satisfaction. Using data from 609 adults with diagnosed Type 2 diabetes we develop an efficiency (fitness) frontier in order to identify best practice (maximally adapted) patients and forms (archetypes) of patient inefficiency. Outcomes of frontier patients are partitioned by categories of returns to scale. Outcomes for off-frontier patients are associated with disease severity and patient archetype. The model implicates strategies for improved health outcomes based on fitness and self-care behaviors.

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Year:  2002        PMID: 12363045     DOI: 10.1023/a:1019740401536

Source DB:  PubMed          Journal:  Health Care Manag Sci        ISSN: 1386-9620


  55 in total

Review 1.  Words without action? The production, dissemination, and impact of consensus recommendations.

Authors:  J Lomas
Journal:  Annu Rev Public Health       Date:  1991       Impact factor: 21.981

2.  Diagnosing congenital heart defects using the Fallot computational model.

Authors:  N E Reed; M Gini; P E Johnson; J H Moller
Journal:  Artif Intell Med       Date:  1997-05       Impact factor: 5.326

3.  Differences between diabetic patients who do and do not respond to a diabetes care intervention: a qualitative analysis.

Authors:  P J O'Connor; B F Crabtree; M K Yanoshik
Journal:  Fam Med       Date:  1997-06       Impact factor: 1.756

4.  Variations in the use of medical and surgical services by the Medicare population.

Authors:  M R Chassin; R H Brook; R E Park; J Keesey; A Fink; J Kosecoff; K Kahn; N Merrick; D H Solomon
Journal:  N Engl J Med       Date:  1986-01-30       Impact factor: 91.245

5.  Self-efficacy: toward a unifying theory of behavioral change.

Authors:  A Bandura
Journal:  Psychol Rev       Date:  1977-03       Impact factor: 8.934

6.  Evaluating relative efficiencies of Veterans Affairs Medical Centers using data envelopment, ratio, and multiple regression analysis.

Authors:  S Hao; C C Pegels
Journal:  J Med Syst       Date:  1994-04       Impact factor: 4.460

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Authors:  L I Solberg; L A Reger; T L Pearson; L M Cherney; P J O'Connor; S L Freemen; S L Lasch; D B Bishop
Journal:  Jt Comm J Qual Improv       Date:  1997-11

Review 8.  Social cognition: thinking categorically about others.

Authors:  C N Macrae; G V Bodenhausen
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9.  A new high-performance liquid chromatographic procedure to quantitate hemoglobin A1c and other minor hemoglobins in blood of normal, diabetic, and alcoholic individuals.

Authors:  T H Huisman; J B Henson; J B Wilson
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10.  Variation in office-based quality. A claims-based profile of care provided to Medicare patients with diabetes.

Authors:  J P Weiner; S T Parente; D W Garnick; J Fowles; A G Lawthers; R H Palmer
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