Online Program

Gauging patience among patients: Integrating qualitative and quantitative measures to determine wait-day thresholds at which patients in a large urban Medicaid health plan, judge delays in access to be excessive

Monday, November 2, 2015 : 2:50 p.m. - 3:10 p.m.

Rae Starr, L.A. Care Health Plan, Santa Monica, CA
Health care reform has made timely access an increasingly pressing quality metric (more patients, finite doctors).  CAHPS surveys give the widest-used measures of access delay from patients’ perspectives.  Due to their nature and purpose, the questions are subjective, along these lines: “How often did you get care as soon as you needed?  (Never, Sometimes, Usually, Always).”  Patients’ differences in the meaning of “as-soon-as-you-needed” pose a challenge for root cause analysis in quality improvement.

(1) Analytic objective: This paper provides a statistical answer to that semantic problem.  By comparing numeric measures of wait time against those subjective measures, we calculate non-subjective thresholds (actual days of delay) associated with those four subjectively-determined response terms, to reveal respondents’ standards for timely care.

(2) Data: The study is set in a large urban Medicaid health plan in a populous and ethnically diverse county in the  southwestern United States.  The study uses patients’ self-reported recall data on access delays, from CAHPS surveys in 2011 (n=16,288) and related studies.

(3) Practical uses: Expressed numerically as days-of-wait, assessing whether patients’ expectations are clinically reasonable or not becomes feasible: Knowing patients’ expectations provides context for health education messaging.  Knowing how many days of delay triggers negative ratings by patients, gives administrators a way to calculate the costs of reducing delays toward patient’s expectations: (a) serving patients better, and (b) receiving better accreditation scores and Medicare revenue for improved service.  Other implications are discussed: demographic groups’ differences in assessing delay; impact on missed visits; impact on inappropriate ER use.

Learning Areas:

Biostatistics, economics
Conduct evaluation related to programs, research, and other areas of practice
Planning of health education strategies, interventions, and programs
Program planning
Social and behavioral sciences
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
Describe the principal barrier to using patients’ self-reported measures of access delays from common surveys of service quality, for root cause analysis in quality improvement. Explain two systemic reasons why reported access times for adults may differ from reported times for pediatric patients. Identify thresholds (wait days) for routine care, above which Medicaid patients deemed delay to be excessive. Identify thresholds (wait days) for urgent care, above which Medicaid patients deemed delay to be excessive. Analyze the association between wait time and health care organizations’ performance on two CAHPS measures of service quality. Compare differences in access delay between different demographics (gender, age, and ethnicity), to assess disparities. Compare differences in how different demographics (by gender, age, and ethnicity) rate service quality, for the same lengths of delay in access. Discuss one method for using the analysis to address patients’ expectations about the timeliness of care. Discuss one method for calculating the cost and feasibility of meeting patients’ expectations about the timeliness of care.

Keyword(s): Performance Measurement, Health Care Access

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: Have served 12 years as statistician at the largest public health plan in the United States, serving Medicaid and Medicare populations in an ethnically diverse urban county in the southwest United States. Managed CAHPS patient experience survey from 2006 to 2015, with a focus on making the survey results actionable in the design of quality improvement interventions. Designed supplemental questions for CAHPS to capture and analyze appointment wait days from patients.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.