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Table 3 Overview of data collection methods and analysis

From: MyPreventiveCare: implementation and dissemination of an interactive preventive health record in three practice-based research networks serving disadvantaged patients—a randomized cluster trial

Aim Data sources Analysis
Aim 1: Implementation: To field the IPHR and evaluate use in terms of: IPHR/PHR database to measure which patients use the IPHR or PHR, and when and how often they use it •Percent of approached practices that agree to use the IPHR (Adoption)
•Percent of patients age 18–75 with a visit who create an IPHR account in months 1–12 (Reach) and 13–36 (practice-level Maintenance) (monthly repeated measures analysis)
EHR database to measure the number of potential IPHR users (denominator)
- Adoption
- Implementation Field notes to gather quantitative and qualitative insights on practice-level Adoption •Percent of users who use the IPHR after 6 months (patient-level Maintenance)
- Maintenance •Mixed methods analysis of (quantitative) practice and clinician variation in Reach (two-level mixed-effects logistic regression) and (qualitative) consistency, variation, and fidelity of IPHR delivery (immersion/crystallization analysis of transcripts and diaries) (Implementation)
Network records to measure practice (e.g., size) and clinician characteristics (e.g., age)
Learning collaborative transcripts, practice survey, practice diaries, and patient interviews to assess IPHR implementation, including consistency and adaptation, and to qualitatively assess Reach, Effectiveness, and Maintenance
Scalability Data sources and analysis similar to phase 1 except phase 2 will not include collecting and analyzing learning collaborative transcripts, practice diaries, site visits, or patient interviews
Aim 2: To compare the Effectiveness of the IPHR vs. traditional PHR functions EHR database to measure delivery of recommended cancer screening tests •Percent of patients up-to-date with all indicated cancer screening for all practice patients (intention to treat) and for PHR users (sub-group) (two-level logistic regression)
IPHR/PHR database to identify users
•Shared decision-making outcomes (knowledge, communication, decisional conflict, and decision control) (three-level generalized mixed-effects regression)
Patient survey of 4,000 randomly selected patients to measure elements of shared decision-making
•Patient, practice, and clinician facilitators and barriers associated with Effectiveness (mixed-method analysis)
Learning collaborative transcripts, practice survey, practice diaries, and patient interviews to explore perceptions
Aim 3: Disparities Assessment: Difference in use, effect and perception of technology for disadvantaged populations EHR database to identify at risk patients (minorities and Medicaid beneficiaries) and to measure delivery of recommended cancer screening tests •Comparison of Reach and Effectiveness for the disadvantaged versus general population (two-level mixed-effects logistic regression)
•Patient interviews to understand technology barriers and needs; technology impact; and unique issues for disadvantaged patients
IPHR/PHR database to stratify levels of use by minority and Medicaid status
Patient interviews
  1. Italicized words are data collection methods.
  2. Bolded words are specific aim elements that will be assessed.