Where Would You Go for Your Next Hospitalization? Kyoungrae Jung Penn State University Roger Feldman University of Minnesota Dennis Scanlon Penn State University 1

Introduction Providers vary in diverse dimensions of quality (clinical skills, interpersonal quality, outcomes of patients) Consumers are likely to value each of these dimensions It is often difficult for consumers to observe provider quality in health care markets  Improve consumer information for better decisions and better-performing health care markets 2

Introduction (II) Recent efforts have focused on public release of comparative quality information  Often including clinical quality information  Response has been small  Consumers may not value such information or they already know about it prior to public reporting What types of quality information do consumers value and use in making health care decisions?  The answer can help to devise effective strategies to increase consumer information (Feldman et al., 2000; Harris & Buntin, 2008)  Few studies have examined this question 3

Research objective To examine the effects of different dimensions of hospital quality in the context of a future hospital choice. We focus on: 1)consumers’ perceptions of unobservable (to researchers) quality attributes, such as reputation 2)hospital clinical quality, whose indicators are often included in public reporting programs 3)consumers’ satisfaction ratings from their own recent experiences with hospitals 4

Literature on hospital choice Consumers choose closer hospitals (Porell and Adams, 1995) After release of report cards, consumers chose hospitals with mortality rates lower than expected (Mukamel et al., 2004/2005; Dranove and Sfekas, 2008) Financial incentive for using “safer” hospitals has mixed effects on hospital choice (Scanlon et al., 2008) 5

Hospital quality and choice Consumer’ perceptions about quality may play a significant role in hospital choice Goal has been to obtain unbiased estimates of the impact of public quality information on choices Research has relied on hospital fixed effects to control for consumers’ beliefs about unmeasured hospital quality  Captures multiple unmeasured quality attributes with a single variable  Can’t examine the relative contributions of different attributes to choice 6

Our approach We utilize stated preference data to infer consumers’ perceptions about unobservable hospital attributes (e.g. reputation) We estimate parameters representing consumers’ perceptions about several unmeasured hospital attributes Allows us to measure the amount of each unobserved attribute offered by each hospital Enables us to examine their relative contributions to consumer utility 7

Additional contribution We introduce individual-level satisfaction ratings from their own experience to the hospital choice model  Certain important features of hospital quality can be evaluated only by experience  Consumers report they use experience to make health care decisions (Feldman et al., 2000; Schultz et al., 2001)  “Bad experience” or dissatisfaction did not motivate consumers to switch health plans (Abraham et al., 2006)  We estimate the impact of individual satisfaction ratings on hospital choice in terms of a driving time trade-off 8

Study setting and data Survey of employees at a large self-insured employer  Administered twice: April/May 2004 and Spring 2005  Random sample stratified by union status and recent hospitalization  Observations on 16 hospitals chosen by more than 15 people  969 hospitalized and 790 non-hospitalized people Key variables from the survey  Future hospital choice from a hypothetical question  Stated preferences for four unobserved attributes: Overall reputation, medical services, amenities, and OOP costs  Future choice and preference data available for both users and non-users  Satisfaction with hospital for users on a 1 to 10 scale 9

Stated preferences Example of reputation: “On a scale of 1 to 10, with 1 being not at all valuable and 10 being extremely valuable, please rate each item.” “The next time you decide which hospital to use for inpatient services, how valuable would you find: The hospital's overall reputation?” Out-of-pocket cost Specialty medical services offered (e.g. cardiac bypass surgery) Amenities (e.g. private rooms and convenient parking) 10

Other data sources 2005 Hospital Quality Initiative (HQI)  Hospitals’ clinical quality scores released in April 2005  Not publicly available during our study period Compliance with Leapfrog safety standards (CPOE, IPS)  Publicly available on the Leapfrog website; posted on the TPA website during the 2 nd round of the survey Mapquest.com: driving time AHA: profit, teaching status 11

Conceptual Model Based on the expected utility theory of decision making (1) R j - hospital j’s clinical quality E ij – consumer i’s beliefs about hospital j’s unobservable attributes D ij - driving time X j – observable hospital characteristics (2) E j – hospital-specific beliefs before experience S ij – satisfaction rating I ij – indicator of use (1 if consumer i used hospital j; 0 otherwise) h – weight given to experiential signal 12

Model (2) By substitution, (3) A consumer will choose hospital j in the future if (4) for all k ≠ j Estimate equation (3) by conditional logit analysis 13

Estimation Two-stage estimation process:  Stage 1: Estimate hospital-specific beliefs (E j ) about unobserved hospital attributes, using stated preference data from non-hospitalized (naïve) people  Stage 2: Estimate equation (3) -- how different dimensions of hospital quality influence future choice among hospitalized people, using parameters of consumers’ beliefs obtained from first stage 14

Estimating consumers’ perceptions (1 st stage) Based on approach developed by Harris & Keane (1999); used by Harris, Schultz & Feldman (2002) Estimate choice model for non-hospitalized people that includes interactions between preference weights and hospital dummies Preference weights on reputation, medical services, amenities, and OOP cost are variables Coefficients represent average perceived amounts of unmeasured attributes possessed by each choice, relative to reference hospital 15

Other explanatory variables (1 st stage) Driving time Teaching status; Profit status Observed HQI quality score Compliance with the Leapfrog safety standards HQI score * 2005 survey Compliance * 2005 survey Compliance * 2005 survey * union 16

Estimation of future hospital choice (2 nd stage) Estimate conditional logit model among hospitalized people as function of:  Parameters of consumers’ beliefs about unobserved attributes  HQI score  Satisfaction with hospital used  Indicator for use of hospital  Other covariates as in 1 st stage  Compliance* 2005*union*used non-compliant hospital Standard errors based on bootstrapping 17

Descriptive statistics Driving time: 41.2 min (24.5 min) HQI scores: 72.1 Preference weights among non-hospitalized people  Reputation: 8.41  Medical services: 8.78  Amenities: 6.62  Out-of-pocket cost: 7.55 Satisfaction rating (among users): 8.11 Intention to use another hospital (among users): 31.7% 18

1 st stage model for non-users: Preference weights for unobserved attributes 19 CoefficientsStandard Errors Reputation Hospital *** Hospital ** Hospital *** Medical services Hospital *** Out-of-pocket costs Hospital *** Hospital ** Hospital ** Hospital *** **: p<0.05; **:p<0.01

2 nd stage future choice model for users Specification: I Measured Hosp. Char. Driving time *** For-profit *** Teaching0.587 *** Compliance0.304 ** Observed quality HQI score0.105 *** Perceptual parameters Reputation Medical services Out-of-pocket cost Experiential measures Satisfaction rating Use indicator 20 II *** *** *** *** *** *** ***

Impact of HQI score (Model II) Consumers perceive clinical quality as a distinctive feature of hospital quality Consumers correctly infer clinical quality before public disclosure. Marginal effect of HQI score:  4%-point increase in market share for 1 SD increase in score  Much smaller than those of beliefs about medical services (13% points) or reputation (18.4% points). 21

2 nd stage future choice model for users 22 III *** *** *** *** *** *** *** *** Specification: I Measured Hosp. Char. Driving time *** For-profit *** Teaching0.587 *** Compliance0.304 ** Observed quality HQI score0.105 *** Perceptual parameters Reputation Medical services Out-of-pocket cost Experiential measures Satisfaction rating Use indicator II *** *** *** *** *** *** ***

Our approach vs. Fixed effects 23 III Hospital Fixed Effects Driving time *** *** Perceptual parameters Reputation0.725 *** - Medical services0.833 *** - Out-of-pocket cost0.458 *** - Experiential measures Satisfaction rating0.817 *** *** Use indicator3.227 *** ***

Large impacts of consumers’ perceptions, satisfaction, and use (Model IV) 1.1 SD increases in medical services and reputation would increase a hospital’s market share from 20% to 33.3% and 31.6%, respectively 2.1 SD increase in satisfaction (2.17 on 1-10 scale) would increase the hospital’s market share from 20% to 33%  Consumer would drive 18.6 minutes farther to use a hospital with 1 SD better satisfaction rating 3.Marginal effect of use: 64 %-points 24

25 Weights on physician recommendation Admission through emergency room Top tertileBottomYesNo Perceptual parameters Reputation0.776 *** *** *** *** Medical services1.085 *** *** *** *** Out-of-pocket costs0.399 *** *** *** *** Experiential measures Satisfaction rating0.794 *** *** *** *** Use indicator3.528 *** *** *** *** Sensitivity Analysis

Summary of results: future hospital choice Naïve consumers perceive differences in reputation, medical services, and OOP costs across hospitals Large effects of consumers’ beliefs about unobservable attributes are consistent with a study on health plan choice Consumers may already know about hospital clinical quality prior to public reporting; its contribution to hospital choice is small Positive effect of satisfaction is inconsistent with a study of health plan choice Large effect of prior use is consistent with prior literature 26

Limitations Hypothetical future choices may differ from actual choices  But we avoid potential bias associated with repeated hospitalizations Stated preference data were collected from non-hospitalized people during a survey window  Did not control for “ever” use  May not be as naïve as we think  Data were obtained by prospective questions We can only estimate average, hospital-specific beliefs  We obtain average beliefs for each attribute  Use indicator may partially capture individual heterogeneity 27

Discussion Recent trend for “report cards” to include information about satisfaction  CMS initiated Hospital CAHPS in 2008  Inexperienced consumers may turn to report cards that contain quality measures based on others’ experience Consider publicizing information about hospital reputation or medical services  May represent what consumers would like to see  May increase consumers’ responses to “report cards.” 28

Discussion (II) Efforts are needed to increase awareness and use of public quality information to overcome effects of “use” and consumers’ beliefs  Employers’ initiatives  Ensure that physicians are informed about hospital quality and incorporate it in their recommendations What are effective strategies to increase consumer information and improve performance of health care markets? 29