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      Hospital Advertising, Competition, and HCAHPS: Does It Pay to Advertise?

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          <div class="section"> <a class="named-anchor" id="hesr12549-sec-0001"> <!-- named anchor --> </a> <h5 class="section-title" id="d6369104e262">Objective</h5> <p id="d6369104e264">To test whether hospital advertising expenditures predict <span style="fixed-case">HCAHPS</span> global ratings. </p> </div><div class="section"> <a class="named-anchor" id="hesr12549-sec-0002"> <!-- named anchor --> </a> <h5 class="section-title" id="d6369104e270">Data Sources/Study Setting</h5> <p id="d6369104e272">We examined media advertising expenditures by 2,142 acute care hospitals in 209 markets in the United States. Data on hospital characteristics, location, and revenue came from <span style="fixed-case">CMS</span> reports; system ownership was obtained from the American Hospital Association. Advertising data came from Kantar Media. <span style="fixed-case">HCAHPS</span> data were obtained from HospitalCompare. </p> </div><div class="section"> <a class="named-anchor" id="hesr12549-sec-0003"> <!-- named anchor --> </a> <h5 class="section-title" id="d6369104e281">Study Design</h5> <p id="d6369104e283">Regression models examined whether hospitals’ advertising spending predicts <span style="fixed-case">HCAHPS</span> global measures and whether market concentration moderated this association. </p> </div><div class="section"> <a class="named-anchor" id="hesr12549-sec-0004"> <!-- named anchor --> </a> <h5 class="section-title" id="d6369104e289">Data Collection/Extraction Methods</h5> <p id="d6369104e291">Hospital advertising spending was calculated by adding each individual hospital's expenditures to the amount spent by its parent health system, proportionally allocated by hospital revenue. Health system market share was used to estimate market concentration. These data were compared to hospitals’ <span style="fixed-case">HCAHPS</span> measures. </p> </div><div class="section"> <a class="named-anchor" id="hesr12549-sec-0005"> <!-- named anchor --> </a> <h5 class="section-title" id="d6369104e297">Principal Findings</h5> <p id="d6369104e299">In competitive markets ( <span style="fixed-case">HHI</span> below 1,000), hospital advertising predicted <span style="fixed-case">HCAHPS</span> global measures. A 1‐percent increase in advertising was associated with a 1.173‐percent increase in patients rating the hospital a “9” or “10” on the <span style="fixed-case">HCAHPS</span> survey and a 1.540‐percent increase in patients who “definitely” would recommend the hospital. In concentrated markets, this association was not significant. </p> </div><div class="section"> <a class="named-anchor" id="hesr12549-sec-0006"> <!-- named anchor --> </a> <h5 class="section-title" id="d6369104e311">Conclusions</h5> <p id="d6369104e313">In competitive markets, hospitals that spend more on advertising earn higher <span style="fixed-case">HCAHPS</span> ratings on global measures. </p> </div>

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          Price and Advertising Signals of Product Quality

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            Consumer Learning: Advertising and the Ambiguity of Product Experience

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              Effects of survey mode, patient mix, and nonresponse on CAHPS hospital survey scores.

              To evaluate the need for survey mode adjustments to hospital care evaluations by discharged inpatients and develop the appropriate adjustments. A total of 7,555 respondents from a 2006 national random sample of 45 hospitals who completed the CAHPS Hospital (HCAHPS [Hospital Consumer Assessments of Healthcare Providers and Systems]) Survey. We estimated mode effects in linear models that predicted each HCAHPS outcome from hospital-fixed effects and patient-mix adjustors. Patients randomized to the telephone and active interactive voice response (IVR) modes provided more positive evaluations than patients randomized to mail and mixed (mail with telephone follow-up) modes, with some effects equivalent to more than 30 percentile points in hospital rankings. Mode effects are consistent across hospitals and are generally larger than total patient-mix effects. Patient-mix adjustment accounts for any nonresponse bias that could have been addressed through weighting. Valid comparisons of hospital performance require that reported hospital scores be adjusted for survey mode and patient mix.

                Author and article information

                Health Services Research
                Health Serv Res
                August 2017
                August 2017
                August 22 2016
                : 52
                : 4
                : 1590-1611
                [1 ]MBA Healthcare Management Program; Clarkson University; Capital Region Campus; Schenectady NY
                [2 ]School of Business; Clarkson University; Schenectady NY
                [3 ]Department of Psychology; Union College; Schenectady NY
                [4 ]Albany Medical College; Division of Cardiology; Albany Stratton VAMC and Albany Medical Center; Albany NY
                [5 ]Next Wave, Inc.; Albany NY
                © 2016





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