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Patient Satisfaction as a Quality Metric Promotes Bad Medicine

Patient Satisfaction as a Quality Metric Promotes Bad Medicine Letters Table. Impact of Prevalence and Test Sensitivity on Screening Utility Total Disease Total Total TPs, FPs, TNs, FNs, Sensitivity, Specificity, PPV, NPV, Population, No. Prevalence, % Positive, No. Negative, No. No. No. No. No. % % % % 1000 50 500 500 475 15 485 25 95 97 97 95 1000 10 100 900 95 30 870 5 95 97 76 99 1000 10 100 900 80 30 870 20 80 97 73 98 1000 10 100 900 99 30 870 1 99 97 77 100 Abbreviations: FNs, false negatives; FPs, false positives; NPV, negative predictive value; PPV, positive predictive value; TNs, true negatives; TPs, true positives. influenced by disease prevalence in the screened population. The Centers for Medicare & Medicaid Services has Assuming the best reported performance of screening mam- begun using patient satisfaction as a quality metric, with 5 3 mography (95% sensitivity and 97% specificity), we can think financial implications as an end result. This is a perfect of 2 scenarios, each with 1000 screened patients. If we first as- example of good intentions leading to bad policy and result- sume a disease prevalence of 50%, mammography will yield ing in bad patient care. 475 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA Internal Medicine American Medical Association

Patient Satisfaction as a Quality Metric Promotes Bad Medicine

Wexler, Randy
JAMA Internal Medicine , Volume 174 (8) – Aug 1, 2014
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References (2)

Publisher
American Medical Association
Copyright
Copyright 2014 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.
ISSN
2168-6106
eISSN
2168-6114
DOI
10.1001/jamainternmed.2014.1624
pmid
25090185
Publisher site
See Article on Publisher Site

Abstract

Letters Table. Impact of Prevalence and Test Sensitivity on Screening Utility Total Disease Total Total TPs, FPs, TNs, FNs, Sensitivity, Specificity, PPV, NPV, Population, No. Prevalence, % Positive, No. Negative, No. No. No. No. No. % % % % 1000 50 500 500 475 15 485 25 95 97 97 95 1000 10 100 900 95 30 870 5 95 97 76 99 1000 10 100 900 80 30 870 20 80 97 73 98 1000 10 100 900 99 30 870 1 99 97 77 100 Abbreviations: FNs, false negatives; FPs, false positives; NPV, negative predictive value; PPV, positive predictive value; TNs, true negatives; TPs, true positives. influenced by disease prevalence in the screened population. The Centers for Medicare & Medicaid Services has Assuming the best reported performance of screening mam- begun using patient satisfaction as a quality metric, with 5 3 mography (95% sensitivity and 97% specificity), we can think financial implications as an end result. This is a perfect of 2 scenarios, each with 1000 screened patients. If we first as- example of good intentions leading to bad policy and result- sume a disease prevalence of 50%, mammography will yield ing in bad patient care. 475

Journal

JAMA Internal Medicine – American Medical Association

Published: Aug 1, 2014

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