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The Effect of a Hospital Safety Incentive in an Employed Population


Title: PowerPoint Presentation Author: Dennis Scanlon Last modified by: Dennis Scanlon Created Date: 11/8/2001 3:55:00 PM Document presentation format – PowerPoint PPT presentation

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Title: The Effect of a Hospital Safety Incentive in an Employed Population

  • The Effect of a Hospital Safety Incentive in an
    Employed Population
  • Dennis P. Scanlon
  • Colleen Lucas
  • Pennsylvania State University
  • Jon B. Christianson
  • University of Minnesota
  • Principal funding from the Agency for Healthcare
    Research Quality Partnership for Quality
    grant program, Grant 2U18 HS13680
  • Dr. Scanlons research is supported by an
    Investigator Award in Health Policy Research from
    the Robert Wood Johnson Foundation

Boeings Hospital Safety Incentive and Health
Consumerism Campaign
  • The Hospital Safety Incentive was one piece of
    the consumerism component of Boeings overall
    health care strategy
  • Standard hospital benefit (and out-patient
    surgery care) changed from 100 to 95 coverage
    for union employees on July 1, 2004
  • The safety incentive gave union employees the
    option to return to a 100 benefit for hospital
    care (and out-patient surgery care) if services
    were received at safe hospitals as measured by
    compliance with The Leapfrog Groups patient
    safety leaps
  • Boeing also engaged in a consumerism campaign
    to educate employees and beneficiaries about
    issues of health care cost, quality and safety,
    and to encourage employees and their dependents
    to be partners with Boeing

Traditional Medical Plan (TMP) Benefits
Before 7/1/2004 Before 7/1/2004 After 7/1/2004 After 7/1/2004
Non-Union Salaried Employees Union Hourly Employees Non-Union Salaried Employees Union Hourly Employees
Deductible (Individual -Family) 200 / 600 200 / 600 200 / 600 200 / 600
Hospital Coinsurance 0 0 0 5 with 0 HSI option
Annual Out-of-Pocket Maximum (Individual - Family) 5,000 / 15,000 2,000 / 4,000 5,000 / 15,000 2,000 / 4,000
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Research Questions
  • Were union employees and beneficiaries aware of
    the HSI? What characteristics predict awareness?
  • How do commercially insured beneficiaries weight
    attributes believed to be important in the
    hospital selection decision?
  • What (if any) impact has the HSI had on patients
    assessments regarding the need for hospital care?

Conceptual Framework for Studying Tiered
Hospital Benefit Programs
Our Approach
  • We collected detailed survey data about the
    process by which patients ended up at particular
    hospitals, and the degree to which patients were
    involved in the decision, as well as the relative
    importance of the various attributes in the
  • We assume some attributes are known with
    certainty while others are uncertain, and thus
    information about the HSI allows individuals to
    update their priors about uncertain attributes.
  • Cost is an example where a certain attribute
    became uncertain as a result of the HSI
  • We hypothesize that the HSI was meant to directly
    affect cost, quality and safety, while not
    directly affecting other attributes such as
    distance, amenities, etc.
  • If weights for cost, quality and safety change,
    then the weights of other attributes will also
    change if they must sum to one.
  • We estimate regressions for each attribute
    individually, using interaction terms to test
    whether the attribute weights were different for
    the union beneficiaries (relative to the
    non-union beneficiaries) in the post period.

Survey Design
  • 20 minute phone interviews, pre/post with a
    random sample of beneficiaries (employees or
  • 4 groups pre and post July 1, 2004
  • The survey focused on the following areas
  • Awareness of enrollment materials and online
    decision support tools
  • Opinions regarding the quality and safety of
    health care
  • Factors influencing hospital choice (for
    respondents with a recent hospitalization)
  • Factors important for future choice of hospital
    if inpatient care is needed
  • Factors related to health plan choice
  • Demographic characteristics
  • Cooperation rate was 69.1 and 70.1 in pre/post

Sampling Distribution (Pre/Post)
Received from Regence (Pre/Post) Sample Drawn (Pre/Post) Completed Interviews (Pre/Post)
1. Non-hospitalized, Union 35,490 / 29,883 749 / 829 296 / 305
2. Non-hospitalized, Non-Union 23,369 / 21,391 747 / 680 284 / 305
3. Hospitalized, Union 1,180 / 1,558 925 / 1,008 377 / 401
4. Hospitalized, Non-Union 654 / 929 654 / 624 275 / 269
Regression General Form
  • Yijt ßX a(Post) ?(Union) d(Hospital)
    ?(PostUnion) ?(HospitalPost)
    ?(HospitalUnion) t(HospitalUnionPost) eijt
  • X vector of demographic characteristics
  • Age, propensity to seek health info, health
    status, gender, race, education, income, active
    or early retiree, spouse, years with Boeing
  • Normalize Y - as a preference weight - to allow
    attribute tradeoff
  • Norm (Yijt) Yij / ?j1...10 Yijt

Timing of Awareness
  • We hypothesize that learning about the HSI does
    not occur until after a hospitalization, when
    individuals receive a bill from the hospital
    and/or the explanation of benefits from the
    insurance company
  • We test this by
  • Estimating the probability of awareness among
    union beneficiaries in the post-period as a
    function of individual characteristics, including
    hospitalization status
  • Asking questions about the need for a future
    hospitalization and comparing the importance of
    attributes for hospitalized, union respondents in
    the post period (relative to hospitalized
    non-union respondents)

Models Estimated
  • Awareness of HSI
  • union beneficiaries in the post period -Table 7
  • Attribute importance for previously
  • beneficiaries with recent hospital admission
    Table 8
  • Attribute importance if future hospitalization is
  • all beneficiaries Table 9
  • Attribute tradeoff willingness to go to a
    different hospital than first preference
  • all beneficiaries Table 10
  • Preference for same hospital if future
    hospitalization is required
  • beneficiaries with recent hospital admission
    Table 11

Hospital Attribute Importance Actual Future
Hospital Decisions
  • When deciding which hospital to use, how
    important was Your physicians recommendation of
    the hospital?
  • 1 not at all important, 10 extremely important
  • Hospitalized samples only
  • The next time you decide which hospital to use
    for inpatient services, how valuable would you
    find Your physicians recommendation of the
  • 1 not at all valuable, 10 extremely valuable
  • Entire sample

Normalized Attribute Weights from Survey
Respondents Actual Choice
Attribute Overall (Mean) Pre/Post (Mean) Union/Non-Union- (Mean)
Out-of-pocket costs 0.096 0.096/0.095 0.097/0.094
Quality 0.090 0.093/0.087 0.093/0.086
Physician Recommendation 0.114 0.115/0.114 0.115/0.114
Travel Time Distance 0.082 0.081/0.082 0.081/0.083
Plans Hospital Network 0.108 0.106/0.110 0.112/0.102
Family Friends 0.082 0.078/0.085 0.081/0.082
Amenities 0.099 0.099/0.099 0.099/0.099
Specialty Med Services 0.107 0.107/0.107 0.103/0.113
Prior Experience 0.099 0.104/0.093 0.098/0.099
Hospitals Overall Reputation 0.124 0.121/0.127 0.120/0.123
Within Person Response Variance
  • The HSI does not appear to have had an effect
  • Hospitalized union beneficiaries not more aware
    than non-hospitalized union beneficiaries
  • No systematic shift in attribute importance among
    the recently hospitalized union beneficiaries
  • No systematic differences in reported importance
    of attributes for future hospitalization among
    recently hospitalized union beneficiaries
  • The Why is important for policy insurance
  • If physician-patient relationships dominate and
    physician hospital privileges are limited, then a
    financial incentive geared towards consumers may
    have little impact (more effective alternative
    approaches may include hospital or physician
  • 5 may not have been enough to encourage
    shopping or behavior change
  • Recently hospitalized are less likely to consider
    a different hospital, suggesting the value of
  • Optimal timing of incentive program
    implementation when few providers meet the
    preferred tier initially?
  • Value of sending signals to the market to spur
    adoption vs. waiting until enough suppliers meet
    the preferred criteria?

  • Few hospitals met the safety standards to qualify
    for the HSI
  • So effect may have been larger if beneficiaries
    had more alternatives
  • Stated preference may not match revealed
  • Respondent recall and attribute tradeoff may have
    been cognitively challenging
  • Bad phone number information may limit
  • But probably would not affect the conclusion
    unless the HIS had a systematically different
    effect on those with bad phone numbers