Factors Influencing Implementation of Evidence-based Cancer Prevention and

Control Practices in FQHCs: A Qualitative Study

CPCRN FQHC Qualitative Inquiry Subgroup

María E. Fernández, Ph.DAssociate Professor of Health Promotion and Behavioral

ScienceUniversity of Texas Health Science Center at Houston

School of Public Health

Outline

• Research Question

• Methods

- Data collection

- Analysis approach

• Preliminary results

• Timeline

Research Questions

• Primary question: What factors influence the implementation of evidence-based cancer prevention and control practices in FQHCs?

• Secondary question: How useful is the CFIR in assisting the analysis and interpretation of qualitative empirical data on implementation?

Methods

Used qualitative inquiry approaches (in-depth personal interviews and focus groups) to understand factors influencing the implementation of evidence-based cancer prevention and control programs and practices in FQHCs.

Instruments

• Focus group and in-depth interview guides were developed broadly informed by the Consolidated Framework for Implementation Research (CFIR)

• A modified Appreciative Inquiry (AI) approach was used to guide the discussions

• Open-ended questions and prompts about successful practice changes were included as well as questions that tap into a specific evidence-based cancer control practices (including tobacco cessation)

• A brief survey asking about FQHC size, patient population, EHR integration and participation in the Health Disparity  Collaboratives was administered.

Focus Group Guide Overview

Part I: Example of successful practice changes

Part II: Explore evidence-based cancer prevention and control strategy (Tobacco Cessation: Ask-Advise-Refer)

Part III: Inner setting—organizational characteristics and implementation climate and readiness for implementation

Part IV: Other domains of CFIR—intervention characteristics and outer settings

Sampling & Recruitment

• Sample: CEOs, CMOs (or Medical Directors), COOs (or Operation Managers), Quality Improvement managers, frontline project managers, etc. of FQHCs

• Recruited through partnerships with:

Data Collection

• Conducted focus groups and interviews at:o National conferences attended by FQHC leaders and staffs in

San Diego, California; Albuquerque, New Mexico; and Washington, D.C.

o Regional Primary Care Association (PCA) meetings in Denver, Colorado; Columbia, South Carolina; and Pine Mountain, Georgia.

• Five focus groups and 21 in-depth personal interviews; all were digitally recorded

• Data collection period: August, 2011—April, 2012

Data Analysis

Grounded Thematic Analytic Strategy

CFIR-

based

Coding

• Segment data into “meaning units”• Code all data using pre-existing codes developed based on the CFIR• Calculate frequency distribution of coded quotations

Data-

driven

Coding

• Identify barriers and facilitators to implementation based on respondents’ descriptions of successful and unsuccessful efforts at implementation

Themati

c Analysi

s

• Barriers and facilitators will be conceptually clustered to identify a small set of sub-themes

• Sub-themes will be clustered again to identify a smaller set of themes that comprise the main factors that influence implementation

Phase 1: CFIR-based Coding

• A list of pre- existing codes was developed based on the CFIR domains and constructs

• Each transcript is coded by a research team member using pre-existing codes and reviewed by another, followed by group reviews

• Additional codes were added as needed for responses that do not fit with the CFIR

Phase 1 (cont.): Frequency Distribution

• Frequencies of coded quotations among each CFIR domain and subdomains were calculated and organized by the three groups of respondents:

• CEOs or COOs (executives)

• CMOs or Medical Directors (medical managers)

• All others (other staff)

Phase 2: Data-driven Coding

• Phase 2 has three separate but inter-related activities that proceed in an iterative fashion

Identify barriers and facilitators to implementation that most accurately reflect the experience of the respondents (i.e. data-driven) without regard to the meaning and content of the CFIR

Naming barriers and facilitators at second level of abstraction from the data

Renaming and merging codes as they emerge

Phase 3: Thematic Analysis

• Clustering codes into a two-dimensional model for initial data reduction

• Further data reduction and exploration within and between each cell of the matrix

A Two-dimension Model for Initial Data Reduction

Functional areas

Actionable levels within the health centers

Individual Level Group Level

Organizational Level

Patients Personnel

Role of data

Dynamics of change

Effective leadership

Management of people and tasks

Phase 3: Further Data Reduction and Exploration

• Group themes and subthemes into a smaller number of categories

• Explore possible linkages among themes and subthemes

• Identify themes/subthemes that are most salient to each respondent group and compare them

• Compare identified themes (emergent from the data) with CFIR constructs

Current Progress

• We are currently engaged in Phase 3

• Finished coding 522 quotations (in Inner Setting and Individual Characteristics)

• Came up with 147 barriers and facilitators

Preliminary Results

Participants’ Roles

• 59 individuals (29 male & 30 female)

29 Chief Medical Officers (CMO) or Medical Directors

4 Chief Executive Officers (CEO) & 1 Executive vice president

9 Chief Operations Officers (COO)or Operations Manager

4 Quality managers (in different titles)

3 Director of nursing and 1 nursing supervisor

Others include nurse practitioner, physician’s assistants, director of health services, project managers, grant manager and medical interpreter

Participants’ Locations

• Participants represent FQHCs in 14 states and Washington, D.C.

Coded Quotations

• A total of 1, 213 coded quotations (meaning units)• 740 of them were coded to more than one CFIR code

46%

22%

10%

11%

11%

Distribution of Quotations among CFIR Domain

Inner Setting

Process

Individual Character-istics

Outer Setting

Intervention Charac-teristics

22%

45%

33%

Distribution of Quotations among Respondents

Executives

Medical Managers

Other staff

Examples of Data-driven Barriers and Facilitators

Barriers• Disinterest in prevention activities

• Lack of resources to implement change

• Staff lack of time to integrate change

• Patients resistant to change

• Limited functions of EMR

• Lack of staff follow through with patients

Facilitators• Change aligned with organization

mission and values

• Action and change oriented staff

• Designated Quality Improvement (QI) personnel

• Obtaining buy-in through feedback and recognition

• “Pilot team” to test new changes (low risk and important information)

Preliminary Highlights

• The use of EMRs is pivotal in cancer prevention practices and other quality improvement efforts in CHCs

• Federal regulations and requirements (UDS & PCMH) and national visionary goals (Meaningful Use incentives) drive changes

• Leadership engagement is essential for practice change

• Connections and partnerships with academics and other healthcare organizations are very important for CHCs’ cancer prevention efforts

• Providing sufficient training and resources for staff to implement change is very important

• Programs aligning with the goal of improving quality of care are more likely to be implemented

Significance

Findings will contribute to the understanding of the factors influencing the implementation of evidence-based cancer prevention and control programs in FQHCs serving disadvantaged populations and inform the design of interventions to increase the use of EBAs in FQHCs.

Proposed Timeline for Manuscript

• Receive feedback on analysis (Oct,2012)

• Complete analysis (Nov, 2012)

• Manuscript outline (Nov, 2012)

• Writing (Nov—Dec, 2012)

• Manuscript review and feedback (Jan, 2012)

• CDC approval (Jan 2012)

• Submission (Feb, 2012)

Acknowledgement — QIS Members

• UT Houston: Maria Fernandez (PI), Nick Woolf (Consultant), Lily Liang, Glenna Dawson, William Calo, Jenny Tektiridis, Barbara Kimmel, Glorili Alejandro, Patricia Mullen

• Emory University : Michelle Kegler (PI), Michelle Carvalho, Gillian Schauer

• University of South Carolina (SC): Vicki Young (Co-I), Dayna Campbell

• University of Colorado (UC): Betsy Risendal (PI), Andrea Dwyer, Yvonne Kellar-Guenther

• University of Washington (UW): Shin-Ping Tu (Co-I)

• National Association of Community Health Centers (NACHC): Michelle Proser

• National Center for Farmworker Health: Alicia Gonzales

Questions?

Thank You!