Literature DB >> 20009058

Heterogeneity is not always noise: lessons from improvement.

Frank Davidoff1.   

Abstract

Rigorous experimental methods suppress differences among study participants (noise) to detect true intervention effects (signals). But suppressing participants' heterogeneity obscures an essential dimension of biological and clinical knowledge. Medicine is therefore ambivalent about the influence of heterogeneity on outcomes and struggles to find ways to take it properly into account in both clinical practice and research. This analysis explores the roots of that ambivalence. Drawing on the evaluation of 2 health care improvement initiatives, this article examines the unique features of improvement that help to understand heterogeneity's influence on study methods, and suggests a variety of ways to assess the effect of heterogeneity on study outcome measures.

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Year:  2009        PMID: 20009058     DOI: 10.1001/jama.2009.1845

Source DB:  PubMed          Journal:  JAMA        ISSN: 0098-7484            Impact factor:   56.272


  40 in total

1.  Implementation science: how to jump‐start infection prevention.

Authors:  Sanjay Saint; Joel D Howell; Sarah L Krein
Journal:  Infect Control Hosp Epidemiol       Date:  2010-11       Impact factor: 3.254

2.  Evaluating large-scale health programmes at a district level in resource-limited countries.

Authors:  Theodore Svoronos; Kedar S Mate
Journal:  Bull World Health Organ       Date:  2011-08-23       Impact factor: 9.408

3.  Identification of Clinically Meaningful Plasma Transfusion Subgroups Using Unsupervised Random Forest Clustering.

Authors:  Che Ngufor; Matthew A Warner; Dennis H Murphree; Hongfang Liu; Rickey Carter; Curtis B Storlie; Daryl J Kor
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

Review 4.  Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects.

Authors:  David M Kent; Ewout Steyerberg; David van Klaveren
Journal:  BMJ       Date:  2018-12-10

5.  Explaining Michigan: developing an ex post theory of a quality improvement program.

Authors:  Mary Dixon-Woods; Charles L Bosk; Emma Louise Aveling; Christine A Goeschel; Peter J Pronovost
Journal:  Milbank Q       Date:  2011-06       Impact factor: 4.911

6.  A National Implementation Project to Prevent Catheter-Associated Urinary Tract Infection in Nursing Home Residents.

Authors:  Lona Mody; M Todd Greene; Jennifer Meddings; Sarah L Krein; Sara E McNamara; Barbara W Trautner; David Ratz; Nimalie D Stone; Lillian Min; Steven J Schweon; Andrew J Rolle; Russell N Olmsted; Dale R Burwen; James Battles; Barbara Edson; Sanjay Saint
Journal:  JAMA Intern Med       Date:  2017-08-01       Impact factor: 21.873

7.  What counts? An ethnographic study of infection data reported to a patient safety program.

Authors:  Mary Dixon-Woods; Myles Leslie; Julian Bion; Carolyn Tarrant
Journal:  Milbank Q       Date:  2012-09       Impact factor: 4.911

8.  A multi-institutional quality improvement initiative to transform education for chronic illness care in resident continuity practices.

Authors:  David P Stevens; Judith L Bowen; Julie K Johnson; Donna M Woods; Lloyd P Provost; Halsted R Holman; Constance S Sixta; Ed H Wagner
Journal:  J Gen Intern Med       Date:  2010-09       Impact factor: 5.128

9.  Defining and measuring the patient-centered medical home.

Authors:  Kurt C Stange; Paul A Nutting; William L Miller; Carlos R Jaén; Benjamin F Crabtree; Susan A Flocke; James M Gill
Journal:  J Gen Intern Med       Date:  2010-06       Impact factor: 5.128

10.  Treatment benefit and treatment harm rate to characterize heterogeneity in treatment effect.

Authors:  Changyu Shen; Jaesik Jeong; Xiaochun Li; Peng-Sheng Chen; Alfred Buxton
Journal:  Biometrics       Date:  2013-07-19       Impact factor: 2.571

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