disability statistics: using national surveys in the united states

Disability Surveillance using National Household Surveys in the United States: Where have we

been and where are we going?

Eric A. Lauer, MPH, PhD CandidateInstitute On DisabilityNew Hampshire, USA

Introduction

• Focus– The difficulties of defining disability. The concept

that disability is a state of being rather than a diagnosis.

– There are unintended consequences of measurement. We lose people in the national surveillance model in the United States.

Overview

• Challenges for evaluating data• Health & Disability Models• National Survey Methodology• Survey Administration• Introduction of the Six Question Sequence• Self-Reported Limitations• Disability Surveillance in the United States

Challenges

• What is the relationship between health and disability?– Distinct yet overlapping constructs– Function & Functional Limitations

Health & Disability Model

Molla, M.T., J. H. Madans, D. K. Wagener, and E. M. Crimmins. "Summary Measures of Population Health: Report of Findings on Methodologic and Data Issues.". Healthy People 2010 (2003).

International Classification of Functioning: Domains

ICF Applied

Challenges, cont.

• How do you evaluate the data collected?– Consider the historical context– Consider the implications of survey design,

sampling design and underlying constructs– Estimating validity, reliability and error– Strengths, weaknesses and limitations of data

Survey Method Overview

Challenges, continued

• Most importantly, how do we move forward???– Example, Cognitive Limitation & MEPS– Acknowledged model gaps– Discuss limitations in an open and transparent

manner

Model GapsThere are several concepts that are missed by models of disability:

• Individuals can be perceived as having a disability, or consider themselves to have a disability, but not have this evaluation based on any measurable phenomenon

• Disability can only be measured in the context of another domain or area. Some models do not take this into account and there is a loss of explanatory power.

• The construct of disability is not stable, 5000 people in 5000 different life circumstances will have difference rates of disability.

• That disability itself, as a distinct phenomenon, independent of any other factor (age or health), changes over time. It may not be constant. Duration of disability should be measured.– There is acute and chronic disability, intermittent, and relatively stable/unstable

• Systems that address/explain disability are often not practical enough and do not directly inform areas that could be targeted for the alleviation or prevention of disability (Ex. poorly defining the concept of the environment)

Areas of Discussion1.

2. 3.

4.

Constructs

Constructs, continued.

Construct

Error

Item

Malhotra & Grover, 1998

Survey Administration

Survey Administration, continued

• Sampling Design• Primary Sampling Units• Over- and Under- Sampling• High- and Low- Response Regions• Phone, Paper and In-Person Interviewing• Subpopulations missed• Non-response

Self-Report

Self-Report

• What does an individual consider a limitation?• What does an individual consider (un)healthy?• How does an individual interpret the actual

question?• Systematic issues of interpretation, known and

unknown• Proxy Response

Six Questions

• Is this person deaf or do they have serious difficulty hearing?

• Is this person blind or do they have serious difficulty seeing even when wearing glasses?

• Because of a physical, mental or emotional problem, do you have serious difficulty concentrating, remembering or making decisions?

• Do you have difficulty walking of climbing stairs?• Do you have difficulty dressing or bathing?• Do you have difficulty doing errands alone such as

shopping or visiting a doctor’s office?

Six Questions, continued

Quest Age

Y/Y Y/N or N/Y

Hearing 5+ 3.0% 3.0%Vision 5+ 1.2% 2.9%Mobility 5+ 5.4% 4.7%Cognitive 5+ 3.4% 3.9%Self-Care 5+ 1.4% 1.8%Independ

ent15+

3.5% 3.5%

Any 5+ 10.5% 8.3%

Interpretation

Estimation & Interpretation

• Appropriate Hypotheses• Appropriate statistics

– Rates versus ratios, multiplicative effects• Confidence Intervals & Standard Errors

– Iterative repeated, samples, formulas• Bias

– Underlying bias versus biased analysis• Limitations & Generalizability

– State versus national data• Weighting• Imputation

What is the overall state of

disability research?

Malhotra & Grover, 1998. An assessment of survey research in POM: from constructs toTheory. Journal of Operations Management 16, 407-425.

Where do we go from here?

Pick up from here…

Malhotra & Grover, 1998

ICF-AHRQ Recommended Health Outcomes

Butler M, Kane RL, Larson S, Jeffery MM, Grove M. Quality Improvement Measurement of Outcomes for People With Disabilities. Closing the Quality Gap: Revisiting the State of the Science. Evidence Report/Technology Assessment No. 208. (Prepared by theMinnesota Evidence-based Practice Center under Contract No. 290-2007-10064-I.) AHRQ Publication No. 12(13)-E013-EF. Rockville, MD: Agency for Healthcare Research and Quality; October 2012. www.effectivehealthcare.gov/reports/final.cfm.

What is it we are trying to measure?What matters most?

• Should be based on the outcomes of goals of the research

• Establish a relationship between the level of focus and outcomes of interest

• Distinguish between the following factors:– Interventions directed at a disability from specific

interventions directed at a given medical problem for a person with a disability

– Comprehensive programs designed to integrate medical and social services for people with disabilities.

What is it we are trying to measure?What matters most?

Butler M, Kane RL, Larson S, Jeffery MM, Grove M. Quality Improvement Measurement of Outcomes for People With Disabilities. Closing the Quality Gap: Revisiting the State of the Science. Evidence Report/Technology Assessment No. 208. (Prepared by theMinnesota Evidence-based Practice Center under Contract No. 290-2007-10064-I.) AHRQ Publication No. 12(13)-E013-EF. Rockville, MD: Agency for Healthcare Research and Quality; October 2012. www.effectivehealthcare.gov/reports/final.cfm.

Thank you!

• Contact InformationEric A. LauerEmail: eric.lauer@unh.eduPhone: 603-862-4320