Validation of consensus panel diagnosis in dementia.

BACKGROUND The clinical diagnosis of dementing diseases largely depends on the subjective interpretation of patient symptoms. Consensus panels are frequently used in research to determine diagnoses when definitive pathologic findings are unavailable. Nevertheless, research on group decision making indicates that many factors can adversely affect panel performance. OBJECTIVE To determine conditions that improve consensus panel diagnosis. DESIGN Comparison of neuropathologic diagnoses with individual and consensus panel diagnoses based on clinical scenarios only, fludeoxyglucose F 18 positron emission tomography images only, and scenarios plus images. SETTING Expert and trainee individual and consensus panel deliberations using a modified Delphi method in a pilot research study of the diagnostic utility of fludeoxyglucose F 18 positron emission tomography. PATIENTS Forty-five patients with pathologically confirmed Alzheimer disease or frontotemporal dementia. MAIN OUTCOME MEASURES Statistical measures of diagnostic accuracy, agreement, and confidence for individual raters and panelists before and after consensus deliberations. RESULTS The consensus protocol using trainees and experts surpassed the accuracy of individual expert diagnoses when clinical information elicited diverse judgments. In these situations, consensus was 3.5 times more likely to produce positive rather than negative changes in the accuracy and diagnostic certainty of individual panelists. A rule that forced group consensus was at least as accurate as majority and unanimity rules. CONCLUSIONS Using a modified Delphi protocol to arrive at a consensus diagnosis is a reasonable substitute for pathologic information. This protocol improves diagnostic accuracy and certainty when panelist judgments differ and is easily adapted to other research and clinical settings while avoiding the potential pitfalls of group decision making.

[1]  M. Folstein,et al.  Clinical diagnosis of Alzheimer's disease: Report of the NINCDS—ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease , 2011, Neurology.

[2]  M. O. Olde Rikkert,et al.  Consensus Statement on Genetic Research in Dementia , 2008, American journal of Alzheimer's disease and other dementias.

[3]  P. Scheltens,et al.  Development of quality indicators for memory clinics , 2008, International Journal of Geriatric Psychiatry.

[4]  C. DeCarli,et al.  FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer's disease. , 2007, Brain : a journal of neurology.

[5]  Charles R. Shipan,et al.  A social choice approach to expert consensus panels. , 2004, Journal of health economics.

[6]  M. Beers,et al.  Updating the Beers criteria for potentially inappropriate medication use in older adults: results of a US consensus panel of experts. , 2003, Archives of internal medicine.

[7]  B Miller,et al.  Clinical and pathological diagnosis of frontotemporal dementia: report of the Work Group on Frontotemporal Dementia and Pick's Disease. , 2001, Archives of neurology.

[8]  O L Lopez,et al.  Research evaluation and diagnosis of probable Alzheimer’s disease over the last two decades: I , 2000, Neurology.

[9]  S. Wisniewski,et al.  Research evaluation and diagnosis of possible Alzheimer’s disease over the last two decades: II , 2000, Neurology.

[10]  R. Faber,et al.  Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. , 1999, Neurology.

[11]  R. Milne,et al.  A Delphi study to establish national cost-effectiveness research priorities for positron emission tomography. , 1999, European journal of radiology.

[12]  J P Kahan,et al.  The reproducibility of a method to identify the overuse and underuse of medical procedures. , 1998, The New England journal of medicine.

[13]  A. Ott Risk of dementia: The Rotterdam Study , 1997 .

[14]  K. Ray Chaudhuri,et al.  What are the obstacles for an accurate clinical diagnosis of Pick's disease? A clinicopathologic study , 1997, Neurology.

[15]  J. Becker,et al.  The natural history of Alzheimer's disease. Description of study cohort and accuracy of diagnosis. , 1994, Archives of neurology.

[16]  Clinical and neuropathological criteria for frontotemporal dementia. The Lund and Manchester Groups. , 1994, Journal of neurology, neurosurgery, and psychiatry.

[17]  D. Andrews Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation , 1991 .

[18]  Y. Benjamini,et al.  More powerful procedures for multiple significance testing. , 1990, Statistics in medicine.

[19]  W. Newey,et al.  A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelationconsistent Covariance Matrix , 1986 .

[20]  R H Brook,et al.  A Method for the Detailed Assessment of the Appropriateness of Medical Technologies , 1986, International Journal of Technology Assessment in Health Care.

[21]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[22]  C. Huttin,et al.  The use of clinical guidelines to improve medical practice: main issues in the United States. , 1997, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[23]  D. Johnson,et al.  A difference. , 1990, Advancing clinical care : official journal of NOAADN.