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Table. Impact of Prevalence and Test Sensitivity on Screening Utility Total Population, No.

Disease Prevalence, %

Total Positive, No.

Total Negative, No.

TPs, No.

FPs, No.

TNs, No.

FNs, No.

1000

50

500

500

475

15

485

25

1000

10

100

900

95

30

870

5

1000

10

100

900

80

30

870

20

1000

10

100

900

99

30

870

1

Sensitivity, %

Specificity, %

PPV, %

NPV, %

95

97

97

95

95

97

76

99

80

97

73

98

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.4 Assuming the best reported performance of screening mammography (95% sensitivity and 97% specificity),5 we can think of 2 scenarios, each with 1000 screened patients. If we first assume a disease prevalence of 50%, mammography will yield 475 true-positive and 15 false-positive results for a PPV of 97% (Table). However, with a disease prevalence of 10%, the test will yield 95 true-positive and 30 false-positive results, for a PPV of only 76%. Increasing the sensitivity to 99% will only improve PPV by 1%. Thus the clinical utility of a screening test can be enhanced by improved selection of the screened population rather than by increased test sensitivity. We agree with Dr Keller that women be offered choices for breast cancer screening and that importantly, these choices be informed by potential benefits, limitations, and harms. E. Shelley Hwang, MD, MPH Author Affiliation: Duke University Health Systems, Duke Cancer Institute, Durham, North Carolina. Corresponding Author: E. Shelley Hwang, MD, MPH, Duke University Medical Center and Duke Comprehensive Cancer Institute, 465 Seeley Mudd Bldg, Durham, NC 27710 ([email protected]). Conflict of Interest Disclosures: None reported. 1. Mintzer D, Glassburn J, Mason BA, Sataloff D. Breast cancer in the very young patient: a multidisciplinary case presentation. Oncologist. 2002;7(6):547-554. 2. Kajihara M, Goto M, Hirayama Y, et al. Effect of the menstrual cycle on background parenchymal enhancement in breast MR imaging. Magn Reson Med Sci. 2013;12(1):39-45. 3. National Cancer Institute at the National Institutes of Health. Cancer screening overview (PDQ). http://www.cancer.gov/cancertopics/pdq/screening /overview/HealthProfessional/page1. Accessed March 15, 2014. 4. Feinstein AR. Clinical biostatistics XXXI: on the sensitivity, specificity, and discrimination of diagnostic tests. Clin Pharmacol Ther. 1975;17(1):104-116. 5. Humphrey LL, Helfand M, Chan BK, Woolf SH. Breast cancer screening: a summary of the evidence for the US Preventive Services Task Force. Ann Intern Med. 2002;137(5 Part 1):347-360.

The Centers for Medicare & Medicaid Services has begun using patient satisfaction as a quality metric, with financial implications as an end result.3 This is a perfect example of good intentions leading to bad policy and resulting in bad patient care. When a patient presents to an office for acute respiratory symptoms, many have done so with the predetermined belief that antibiotics are necessary. The physician not only must weigh the appropriateness of antibiotic use but must also consider how “satisfied” the patient is with their care. No antibiotics may be good medicine, but it can have a negative impact on patient satisfaction. I spent many years of my professional career providing patients the Centers for Disease Control and Prevention (CDC) handout on appropriate antibiotic use, reviewing each section of the document with them. My patient satisfaction rate was on average 88%. Because of the patient satisfaction as quality push that began a few years ago, I made one change to my 22 years in practice. If I was seeing a partner’s patient who made it clear they were seeing me to obtain an antibiotic prescription, “I get sinus infections all the time and Dr Jones always gives me an antibiotic,” I too gave them a prescription for an antibiotic, and not the CDC handout. My patient satisfaction score has not been below 93% since. Am I proud of my patient satisfaction score? No. I had to practice bad medicine to achieve it. But then, that is the point. It is imperative that stakeholders understand the unintended consequences of using patient satisfaction as a quality marker. In 2012, Fenton et al4 published an article that should be mandatory reading for all policy makers and stakeholders. They found that patient satisfaction was associated with less emergency department use but with greater inpatient use, higher overall health care and prescription drug expenditures, and increased mortality.4 Randy Wexler, MD, MPH

Patient Satisfaction as a Quality Metric Promotes Bad Medicine To the Editor The overuse of antibiotics is a well-known public health issue.1 The research by Meeker et al,2 “Nudging Guideline-Concordant Antibiotic Prescribing: A Randomized Clinical Trial,” is a simple yet elegant way to help combat the problem of inappropriate antibiotic use. As discussed in their report, there are many reasons that physicians overprescribe antibiotics. However, there is a more recent cause for such behavior that threatens to disrupt any progress made toward more appropriate prescribing: the use of patient satisfaction as a surrogate for quality. 1418

Author Affiliation: Department of Family Medicine, Wexner Medical Center, The Ohio State University, Columbus. Corresponding Author: Randy Wexler, MD, MPH, Department of Family Medicine, Wexner Medical Center, The Ohio State University, 2231 N High St, Columbus, OH 43210 ([email protected]). Conflict of Interest Disclosures: None reported. 1. US Department of Health and Human Services, Centers for Disease Control and Prevention. Antibiotic Resistance threats in the United States, 2013. http: //www.cdc.gov/drugresistance/threat-report-2013/pdf/ar-threats-2013-508 .pdf. Accessed January 28, 2014. 2. Meeker D, Knight TK, Friedberg MW, et al. Nudging guideline-concordant antibiotic prescribing: a randomized clinical trial. JAMA Intern Med. 2014;174(3): 425-431.

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3. Centers for Medicare & Medicaid Services. Medicare programs; hospital inpatient value-based purchasing program: proposed rule. 42 CFR Parts 422 and 480. Federal Register. 2011;76(9):2454-2491. http://www.gpo.gov/fdsys/pkg /FR-2011-01-13/pdf/2011-454.pdf. Accessed January 27, 2014. 4. Fenton JJ, Jerant AF, Bertakis KD, Franks P. The cost of satisfaction: a national study of patient satisfaction, health care utilization, expenditures, and mortality. Arch Intern Med. 2012;172(5):405-411.

In Reply Dr Wexler is concerned that efforts to curtail unnecessary antibiotic use may lead to lower patient satisfaction with care. Our study, which did not measure patients’ experiences of care, does not address this concern directly.1 However, the intent of our intervention was to influence clinicians and patients in a way that might improve both antibiotic stewardship and patient experience. By publicly posting clinicians’ personal commitments to provide evidence-based care, we sought to enlist patients and clinicians in support of a common goal. Public commitments justify our future actions to others, leading naturally to understanding rather than dissatisfaction.2 And, people who show consistency with their public commitments are evaluated more positively than those who do not.3 On the broader issue that Dr Wexler raises, we can offer some encouragement. First, most patients who seek care for acute respiratory tract infections state that they want a diagnosis, reassurance, and relief from symptoms—not an antibiotic.4 This is true even when patients request antibiotics discordant with guidelines. Second, even in the face of such demand, several studies have shown that satisfaction does not increase with receipt of antibiotics.5 Third, critical methodological flaws have plagued recent studies linking better patient experience to adverse health outcomes and additional costs.6 To date, the evidence suggests that efforts to improve antibiotic prescribing do not result in significantly lower patient experience ratings. Improving patients’ experiences of care need not require that we abandon sound antibiotic prescribing principles. Daniella Meeker, PhD Mark W. Friedberg, MD, MPP Jeffrey A. Linder, MD, MPH; for the Behavioral Economics and Acute Respiratory Infection Investigators Author Affiliations: RAND Corporation, Santa Monica, California (Meeker); RAND Corporation, Boston, Massachusetts (Friedberg); Division of General Medicine and Primary Care, Brigham and Women’s Hospital, Boston, Massachusetts (Friedberg, Linder); Harvard Medical School, Boston, Massachusetts (Friedberg, Linder). Corresponding Author: Daniella Meeker, PhD, RAND Corporation, 1776 Main St, PO Box 2138, Santa Monica, CA 90407-2138 ([email protected]). Conflict of Interest Disclosures: None reported. Funding/Support: This work was funded by grant 1RC4AG039115-01 from the National Institute on Aging (NIA) as part of the American Recovery and Reinvestment Act to the University of Southern California (principal investigator, Jason N. Doctor, PhD). Role of the Sponsor: The NIA had no role in the preparation, review, or approval of the manuscript or the decision to submit the manuscript for publication.

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Behavioral Economics and Acute Respiratory Infection Investigators: RAND Corporation, Santa Monica, California: Daniella Meeker, PhD; Clinical Pharmacy and Pharmaceutical Economics and Policy, University of Southern California, Los Angeles: Tara K. Knight, PhD, and Jason N. Doctor, PhD; RAND Corporation, Boston, Massachusetts: Mark W. Friedberg, MD, MPP; Division of General Medicine and Primary Care, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts: Mark W. Friedberg, MD, MPP, and Jeffrey A. Linder, MD, MPH; Anderson School of Management, University of California, Los Angeles: Noah J. Goldstein, PhD, and Craig R. Fox, PhD; COPE Health Solutions, Los Angeles, California: Alan Rothfeld, MD; QueensCare Family Clinics, Los Angeles, California: Guillermo Diaz, MD. 1. Meeker D, Knight TK, Friedberg MW, et al. Nudging guideline-concordant antibiotic prescribing: a randomized clinical trial. JAMA Intern Med. 2014;174(3): 425-431. 2. Cialdini RB. Influence: Science and Practice. Vol 4. 5th ed: Boston, MA: Allyn and Bacon; 2008. 3. Allgeier A, Byrne D, Brooks B, Revnes D. The waffle phenomenon: negative evaluations of those who shift attitudinally. J Appl Soc Psychol. 1979;9(2):170-182. 4. Linder JA, Singer DE. Desire for antibiotics and antibiotic prescribing for adults with upper respiratory tract infections. J Gen Intern Med. 2003;18(10): 795-801. 5. Sanchez-Menegay C, Hudes ES, Cummings SR. Patient expectations and satisfaction with medical care for upper respiratory infections. J Gen Intern Med. 1992;7(4):432-434. 6. Friedberg MW, Gelb Safran D, Schneider EC. Satisfied to death: a spurious result? Arch Intern Med. 2012;172(14):1112-1113.

CORRECTION Error in Text: In the Invited Commentary by Morgan and Harris titled “The Gap in Patient Protection for Outpatient Cosmetic Surgery,” published online May 26, 2014, in JAMA Internal Medicine (doi:10.1001/jamainternmed.2014.441), an error occurred in the fourth sentence of the first paragraph. The sentence should read as follows: “Each of the affected patients had surgery that was performed by a physician who was not board certified in plastic surgery and, as was later determined, was colonized with group A Streptococcus and likely experienced a Streptococcal hand cellulitis at the time procedures were performed on 3 patients.” This article was corrected online. Incorrect Follow-up Period: In the Original Investigation titled “Collaborative Care for Depression and Anxiety Disorders in Patients With Recent Cardiac Events: The Management of Sadness and Anxiety in Cardiology (MOSAIC) Randomized Clinical Trial” published in the June 1, 2014, issue of JAMA Internal Medicine (2014; 174[6]:927-936. doi:10.1001/jamainternmed.2014.739), incorrect information appeared. In the fifth paragraph of the Results, under the subheading “Additional Mental Health and Functional Outcomes,” the follow-up period was incorrectly stated in the first sentence of the paragraph, which read “Patients randomized to CC had significantly greater improvements in PHQ-9 scores (EMD, −2.05 [95% CI, −4.06 to −0.05]; P = .045; effect size, 0.45) but not in HADS-A scores (P = .55) (Table 2); there were no differences in rates of depression response (depressed patients only) or anxiety response (patients with GAD and/or PD only) at 24 months.” In this sentence, “24 months” should be replaced with “24 weeks.” This article was corrected online. Omitted Funding Source and Data Error: In the Original Investigation in this August 2014 issue of JAMA Internal Medicine titled “Systolic Blood Pressure Levels Among Adults With Hypertension and Incident Cardiovascular Events: The Atherosclerosis Risk in Communities Study,” first published online in the June 16, 2014, issue of JAMA Internal Medicine (doi:10.1001/jamainternmed.2014.2482), an author’s funding source was omitted. Carlos J. Rodriguez, MD, MPH, was partially supported by the SPRINT clinical trial, National Heart, Lung, and Blood Institute grant HHSN268200900048C. In addition, a data error appeared in Table 3. In the “No.” column under the “Elevated SBP 2” heading, the correct number of male patientswith stroke event type is 245. The errors have been corrected online, and the corrected version of the article appears in this issue.

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Patient satisfaction as a quality metric promotes bad medicine.

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