Resolving heterogeneity between different expressions of inpatient satisfaction

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Resolving heterogeneitybetween different
expressions of inpatient satisfaction
International Forum on Quality and Safety in
Health Care Paris, April 24th 2008
C. Auclair, A. Giraud, MA Grondin, JY Boire, L
Gerbaud
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Introduction
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Inpatient satisfaction assessment

• An important outcome in quality management.
• Issue the manner in which satisfaction surveys
  results are presented.
• With the same results, different presentations
  may produce different incentives for quality
  improvement.

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• Mean satisfaction the most common way.
• ? Incites underscored wards to perform better.
• Bad results the proportion of very dissatisfied
  patients.
• ? Incites wards to identify and correct the
  weakest points.
• Excellence the proportion of very satisfied
  patients.
• ? Incites the non excellent wards to strive
  for excellence.

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• Classification is the most frequent way to
  compare hospitals or health wards quality.
• Ranking from the better to the worst.
• We studied the process of ranking wards by
  inpatient satisfaction, considering the 3 ways to
  express satisfaction (mean satisfaction, bad
  results, excellence).

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Objective
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• The ranking of wards remains the same across the
  3 ways
• no issue about which one to take as the main
  classification criteria.
• If not (different ranks for a ward)
• Use them all ?
• Or consider a composite indicator ?

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Materials and Methods
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• Results of 9-dimensions inpatient satisfaction
  questionnaire (QSH), used in 2005 in
  Clermont-Ferrand university hospital (France) .
• 2585 inpatients investigated 2 months after
  hospitalization (response rate gt 90).
• Comparison of 31 wards.
• Ranking for each ward, 3 ranks (mean, bad
  results, excellence).
• Agreement between the ranks of wards assessed by
  intraclass correlation coefficient (ICC).

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Results
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• Heterogeneity between the 3 expressions of
  satisfaction
• ? Wards ranked differently according mean
  satisfaction, bad results (proportions of very
  dissatisfied) and excellence (proportions of very
  satisfied).
• The 3 ways could not be interchangeable.
• Send back to the wards each score at the same
  time a too complex set of results.

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• Issuing the heterogeneity by creating a compound
  score using fuzzy logic techniques.
• Adjustment of the mean level of satisfaction by
  taking into account the proportions of very
  satisfied and dissatisfied patients.

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Rules

• Ward with high proportion of very satisfied
  increase of the mean satisfaction.
• ? The higher the proportion the higher the term
  added and the higher the Fuzzy score.
• Ward with high proportion of very dissatisfied
  decrease of the mean satisfaction.
• ? The higher the proportion the higher the term
  subtracted and the lower the Fuzzy score.

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Wards are ranked according to the Fuzzy score.
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Conclusion
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Our new Fuzzy score may reduce the marked
heterogeneities in the wards rankings

• Wards are better distinguished on the
  satisfaction continuum.
• Wards Fuzzy scores are more spread around the
  mean of these scores.
• Return of information to the wards with only one
  global indicator the most informative single
  expression of inpatient satisfaction.

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Thanks for your attention