Monitoring the Health Care Safety Net Doing Your Own Survey Institute for Health, Health Care Policy and Aging Research Joel Cantor Professor and Director.

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Presentation transcript:

Monitoring the Health Care Safety Net Doing Your Own Survey Institute for Health, Health Care Policy and Aging Research Joel Cantor Professor and Director Rutgers Center for State Health Policy September 24, 2003 Institute for Health, Health Care Policy, and Aging Research

2 Should you conduct a local survey?   Existing sources do not meet local needs   Check federal, state, and local sources   Surveys can be extrapolated to local areas   Useful for engaging stakeholders   Locale-specific questions   Population can provide needed information   Sufficient resources (time & $) are available

3 Set Clear Objectives Some Examples   Measure access to primary care.   Assess satisfaction.   Assess cultural and linguistic competency.   Determine timeliness of referrals for specialty care.   Assess adequacy of the supply of basic health services for the uninsured.

4 The Questionnaire   Refer to your survey objectives early & often   Use previously tested questions   Writing good questions is hard   Can provide benchmarks   Some good sources…   Medical Expenditure Panel Survey (MEPS)   Behavioral Risk Factor Surveillance Survey   Coordinated State Coverage Survey (SHADAC)

5 Safety Net Survey Topics Some Examples   Coverage   Health status   Access barriers   Utilization   Usual source of care   Attitudes   Jobs & employer characteristics   Socio-economic status and education   Demographics & language

6 Other Important Considerations   Sampling strategy and size   Confidentiality   Follow-up strategies   Interview mode (phone, in-person, mail)   Interviewer selection and training   Data management, editing, analysis   Reporting findings

7 Potential Pitfalls   Not working closely with the community   Running out of money, time, or steam   Not enough development time   Data quality & sampling problems   Lack of focus on how the data will be used   Not enough emphasis on analysis and reporting