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Developing Satisfaction Surveys: Integrating Qualitative and Quantitative Information David Cantor, Sarah Dipko, Stephanie Fry, Pamela Giambo and Vasudha.

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Presentation on theme: "Developing Satisfaction Surveys: Integrating Qualitative and Quantitative Information David Cantor, Sarah Dipko, Stephanie Fry, Pamela Giambo and Vasudha."— Presentation transcript:

1 Developing Satisfaction Surveys: Integrating Qualitative and Quantitative Information David Cantor, Sarah Dipko, Stephanie Fry, Pamela Giambo and Vasudha Naraynan Westat This material was prepared by Westat Inc., under contract with the Centers for Medicare & Medicaid Services (CMS), an agency of the U.S. Department of Health and Human Services. The contents presented do not necessarily reflect CMS policy.

2 Purpose of Paper Illustrate issues related to pre-testing and evaluating satisfaction surveys with establishments Integrating quantitative and qualitative methods

3 Opinion items on establishment surveys Not a great deal of information on opinion from establishments. Response is not reliant on record information, but knowledge of relevant experiences. Questionnaire design issues become more important than surveys related to factual items (e.g., context; order; wording).

4 Idiosyncrasies of satisfaction surveys Respondents tend to use upper end of the scale Items are correlated

5 Medicare Contractor Provider Satisfaction Survey (MCPSS) Survey sponsored by Centers for Medicare and Medicaid Services Respondents: Medical providers Topic: Satisfaction with Medicare contractors

6 Survey Procedures and Questionnaire Mixed mode survey: web and telephone Satisfaction items cover 7 different business areas

7 Scale used for ranking satisfaction Thinking about all your interactions with your contractor in the last 12 months, how satisfied are you with your contractors performance overall?

8 Objective of Analysis Pre-test and evaluate satisfaction items Recommend changes to the items add or delete items – concern especially with shortening the questionnaire Reword – Sharpen focus of attitude object Assess how respondents use the scale respondents using different criteria for scoring opinions

9 Testing procedures used were complementary Expert review Cognitive interviews Psychometric analysis: Review of frequencies, missing data Correlation and factor analysis Rasch Analysis

10 Cognitive Interviews: Procedures Conducted 2 rounds over the telephone Asked respondents to: Answer questions first Explain how they came up with their answer Probed on particular words or phrases Asked how the scale points were chosen Asked about items that were important for evaluating the contractor Asked about items that could be dropped

11 Cognitive interviews results: Procedures Reference Period – change from 6 months to 12 months Direct experiences were memorable enough to recall for 12 months Some respondents were not using direct recall for particular questions Respondent knowledge Audit and reimbursement difficult Other sections varied. Most respondent had at least some indirect, if not direct, experiences.

12 Cognitive interview results: Instructions and Introductions CMS communications vs. contractor communications In-person workshops vs. on-line material First vs higher level appeals

13 Cognitive Interviews Vague and/or imprecise wording Attitude object was not clear. The mechanisms that your contractor offers for exchanging information with them about inquiries. The accuracy of first level appeals decisions The consistency of your Contractors answers to questions throughout the Audit and Reimbursement process

14 Cognitive Interviews Identify redundant items Some items referred to overlapping domains: Receiving the correct information Consistency of responses from staff Knowledge of Contractors staff All three were viewed by respondent as being important.

15 Cognitive interviews Identify redundant items (2) Detail in which topics were covered Quality of education and training materials that you generally use Items were viewed as the same by some (but not all) of the respondents

16 Cognitive interviews results: Variation in how scale is used Respondents use different criteria Using absolute criteria – decide along an internal measure of satisfaction Using comparative criteria – compare experience with other contractors Respondents use different anchors Start with middle and move up or down Start at top point and move down

17 Psychometric Analysis - Methods Brings in additional external information Performance under real survey conditions Has large data-base to draw from Used to verify or point to qualitative results Item difficulty – how much missing data is there? Redundant items – examine correlations among items. What is the distance across scale points?

18 Deciding on Redundant Items: Using Psychometric Analysis Difficult to delete some items based on expert and respondent feedback Items were viewed as important How do items perform in practice Drew on correlation and factor analyses: Use prior year survey administration Deleted items that had highest correlations

19 Number of items added or deleted by method Expert Review Cognitive Interviews Psychometric Analysis Add items 206NA Delete Items 19102

20 Preliminary application of Rasch model Assess use of the scale Is distance between scale points the same? Analysis suggests that distance between scale points is not uniform Greater distance between upper end points (5 vs 6).

21 Summary: Establishment Surveys and Opinion items Opinion surveys for establishments need to consider respondent selection from a different perspective than for factual items Does the respondent have any direct experiences that are relevant? Does the respondent communicate with those the have the target experiences? Questionnaire design is important (instructions; item clarity; item relevance).

22 Summary: Pre-testing Methods Qualitative methods are useful for evaluating domains, instructions, item clarity For determining item relevance (importance), it is useful to have some quantitative measures of performance Having both qualitative and quantitative data is useful for diagnosing item performance Quantitative – what is redundant? Qualitative – why is it redundant?

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