Roshan Bastani, PhD, Beth Glenn, PhD, Russ Glasgow, PhD CPCRN Spring Virtual Meeting
Shin-Ping Tu, MD, MPH ; Maria Fernandez, PhD, Vicki Young, PhD on behalf of the CPCRN FQHC...
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Transcript of Shin-Ping Tu, MD, MPH ; Maria Fernandez, PhD, Vicki Young, PhD on behalf of the CPCRN FQHC...
This presentation was supported by Cooperative Agreement Numbers U48-DP001909, U48-DP001946, U48-DP001924, U48-DP001934, U48-DP001938(03), U48-DP001944, U48-DP001936, U48-DP001949-02, U48–DP001911, & U48-DP001903 from the Centers for Disease Control and Prevention. The findings and conclusions in this presentation are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Shin-Ping Tu, MD, MPH ; Maria Fernandez, PhD, Vicki Young, PhDon behalf of the CPCRN FQHC Workgroup Investigators
Emory University University of California Los AngelesUniversity of Colorado University of South Carolina
University of Texas Houston University of WashingtonWashington University at St. Louis
CDCSeptember 24, 2013
The Cancer Prevention and Control Research Network:
Federally Qualified Health Centers Workgroup
CPCRN CHC Survey
FQHC Workgroup
Partnership Committee
Qualitative Inquiry
Subgroup
Data Subgroup
CHC Survey
Subgroup
Align with CHCs’ missions
Guided by real world
health policy
&health
care delivery
landscapes Health Care Reform
Meaningful Use of EHRPatient-Centered Medical Home
National Association of Community Health Centers (NACHC)
Primary Care Associations
Community Health Centers (CHCs)
CPCRN CHC Survey• Frameworks
• PCMH & Practice Change and Development Model• Consolidated Framework for Implementation Research (CFIR)
• SectionsA - Clinician Staff Questionnaire (Transformed’s NDP)
23 item Practice Adaptive Reserve (PAR) ScaleB - Primary CRC screening modality recommended at clinicC - 4 Community Guide EBIs to increase CRC screening:
Provider reminders, Patient reminders One-on-one education, Provider assessment and feedback
EBI specific CFIR itemsD - 8 CRC screening best practices - NCQA PCMH standards
How often performed best practices in past monthE - Age, gender, race and ethnicity, languages spoken,
number of hours/wk and years worked at clinic
CPCRN CHC Survey• Convenience sample of CHC clinics from 7 states• Completed May 30, 2013• 327 providers, nurses, MAs, QI/operations staff
Primary CRC Screening Test promoted in CHCs
Frequency Percent %
Colonoscopy 92 29.11
Fecal Occult Blood Test (FOBT) - at home 144 45.57
Fecal Immunochemical Test (FIT) - at home 74 23.42
Sigmoidoscopy 1 0.32
None 5 1.58
Total 316 100
Missing Frequencies =11
Clinic Characteristics Survey - Content
• Patients served • Uninsured, below poverty level, LEP, race/ethnicity
• Number of encounters• Staffing - FTEs & shortages• EHR• Ease to generate information & accuracy of data• PCMH best practices• 8 Community Guide EBAs• Provider reminder implementation
• Pressures, incentives, alignment with QI• Feedback on CRC screening• CDC funding of CRC screening program• CRC screening reporting to outside organization
• Scores well – additional income/reimbursements/other rewards
CHC Clinic CharacteristicsNumber of CHC Clinics (% Total)
Number patients served in 2012<5,0005,000-20,000>20,000-30,000>30,000
17 (36%)22 (47%)
3 (6%)5 (11%)
Number of clinics in CHC1-23-56-10>10
19 (38%)18 (36%)7 (14%)6 (12%)
Percent of patients uninsured<20%20-50%>50-70%>70%
6 (13%)21 (47%)10 (21%)10 (21%)
Percent of patients with limited English proficiency<10%10-40%>40-60%>60%
18 (38%)11 (23%)8 (17%)10 (21%)
Respondents - CEO (6); CMO/Med Director (8); CNO/Nursing Director (3); COO/Clinic Operations Director (3); QI Director/Manager (11); Others (19)
CHC Staffing Shortages
Provide
rs
Nurses
Medica
l Ass
istan
ts
Enabli
ng S
ervice
s0%
10%
20%
30%
40%
50%
60%
Percent of
clinics
Practice Change and Development Model
Miller et al. Primary Care Practice Development: A Relationship-Centered Approach. Ann Fam Med 2010;8(Suppl 1):s68-s79.
Robust Practice Core consistent performance & delivery of reliable primary care
Miller et al. Primary Care Practice Development: A Relationship-Centered Approach. Ann Fam Med 2010;8(Suppl 1):s68-s79.
Practice Adaptive Reserveenhances resilience & facilitates adaptation and development
Miller et al. Primary Care Practice Development: A Relationship-Centered Approach. Ann Fam Med 2010;8(Suppl 1):s68-s79.
Practice Adaptive Reserve Scores by State
Scores are scaled so as to range from 0.00 to 1.00; 1.00 = perfect score of agreement
State N Mean SD Min Q1 Q2 Q3 Max
California 28 0.60 0.23 0.02 0.46 0.65 0.78 0.96
Colorado 52 0.66 0.18 0.26 0.52 0.66 0.78 1.00
Georgia 25 0.71 0.19 0.24 0.63 0.73 0.83 1.00
Missouri 4 0.65 0.06 0.58 0.61 0.65 0.69 0.73
S. Carolina 19 0.68 0.17 0.21 0.60 0.65 0.77 1.00
Texas 79 0.66 0.18 0.07 0.54 0.70 0.79 0.98
Washington 89 0.66 0.15 0.21 0.57 0.68 0.75 0.95
Combined 296 0.66 0.18 0.02 0.55 0.67 0.77 1.00
National Demonstration Project - Highly-motivated practices w/ significant capability for change • Mean baseline PAR score 0.69 (s.d. 0.35)• Post intervention PAR score increased to 0.74
PCMH CRC Screening Best Practices (%)
Never Rarely Occasionally Usually Always
Daily huddles, huddle sheets or checklists to go over scheduled patients who need CRC screening.
175 (59.1) 8 (2.7) 16 (5.4) 54 (18.3) 43 (14.5)
Standing CRC screening orders or orders prepared by nurses/medical assistants then signed by providers.
167 (56.4) 3 (1.0) 17 (5.7) 62 (21.0) 47 (15.9)
Tracking of patients who had CRC screening orders. 140 (47.3) 20 (6.8) 22 (7.4) 59 (19.9) 55 (18.6)
Tracking of patients who completed CRC screening tests.
129 (43.6) 15 (5.1) 23 (7.8) 64 (21.6) 65 (21.9)
Tracking of abnormal CRC screening tests. 104 (35.1) 12 (4.0) 13 (4.4) 68 (23.0) 99 (33.5)
Referrals for diagnostic work-up of abnormal CRC screening tests.
57 (19.3) 6 (2.0) 23 (7.8) 66 (22.3) 144 (48.6)
Tracking of diagnostic work-up completed by patients with abnormal CRC screening tests.
96 (32.4) 9 (3.1) 21 (7.1) 69 (23.3) 101 (34.1)
Referrals to specialists for patients with abnormal colonoscopies.
52 (17.5) 10 (3.4) 26 (8.8) 55 (18.6) 153 (51.7)
Adjusted Regression Analysis PCMH Best Practices and PAR
PAR PCMH Best Practices (0-32)
Mean 95% CI
0.08 – 1.00 20.68 17.51, 23.86
0.60 - <0.80 15.84 13.31, 18.36
0.00 - <0.60 12.67 9.90, 15.44
PCMH Best Practices Mean Composite Score (0-32)
Adjusted for state, age, job type, years worked at the clinic, hours worked each week
Differences b/t PCMH BP Mean Composite Scores all statistically significant: 0.08 - 1.00 vs. 0.06 - <0.80 (p = 0.0013) 0.08 - 1.00 vs. 0.00 - <0.60 (p = <0.0001) 0.06 - <0.80 vs. 0.00 - <0.60 (p = 0.0155)
Adjusted Logistic Regression Frequency of PCMH Best Practices and PAR Scores
PAR Frequency of PCMH Best Practices (6-8 vs. 0-5)
OR 95% CI
0.08 – 1.00 5.49 2.31,13.06
0.60 - <0.80 2.23 1.11,4.47
0.00 - <0.60 Referent
PCMH Best Practices Dichotomized Score (6-8 vs. 0-5)Respondent reported performing PCMH best practices “usually” or “always”
Adjusted for state, age, job type, years worked at the clinic, hours worked each week
Levels of Community Guide EBI Implementation
No Plan
Planning to implement EBI in
the future
Level 3 Early stage of implementing EBI at
the clinicLevel 2
EBI implemented but inconsistently across the clinic
Level 1EBI implemented fully and systematically across the clinic
Implementation Levels of CRC Screening EBIs
Provider Reminders
Patient Reminders
One-on-one Education
Provider Assessment & Feedback
0%10%20%30%40%50%60%70%80%90%
100%
29.9720.52
30.62 25.08
20.20
13.36
27.0418.89
18.89
16.61
17.26
20.52
22.15
32.57
11.419.22
8.79 16.94 13.68 16.29
No planPlanningLevel 3Level 2Level 1
Missing Frequencies: 20
General Predictors of Implementation of Provider Reminders
General Organizational Factors Odds Ratio* P-value
Practice Adaptive Reserve 48.56 0.0088Patient-centeredness 2.35 0.0345
Organizational Resources 3.51 0.0003
Communication 2.05 0.0096
Innovation & Flexibility 4.53 0.0108
Leadership 1.90 0.0184
Reflection & Evaluation 2.33 0.0057
• *Odds ratio over 1 means associated with higher levels of provider reminder implementation• Adjusted for age, education, and state.• Number of respondents =296; Number of clinics: 75/62 Unit of Analysis: multilevel
PAR (Scaled 0-5) Odds Ratio=2.33; P value=0.0238
EBI-Specific Predictors of Implementation of Provider Reminders
EBI (Provider Reminders) -Specific Factors Odds Ratio* P-value
Compatibility with the clinic 3.10 0.0048
Learning Climate 2.13 0.0488
Relative advantage 2.33 0.0133
Engaging champions 1.88 0.0158
• *Odds ratio over 1 means associated with higher levels of provider reminder implementation• Adjusted for age, education, and state.• Number of respondents =296; Number of clinics: 75/62 Unit of Analysis: multilevel
Electronic Health Record Adoption
90%
10%
EHRNo EHR
N=50
Electronic Health Record Functionality
CHC clinics that use EHR data to (a)-(d)
CHC clinics that use EHR & can EASILY (a)-(d)
Number (%) (n=43 to 45)
Number (%)(n=37 or 30)
(a) Create list of patient panels by provider 37 (84%) 30 (81%)
(b) Identify patients due or overdue for CRC screening 37 (82%) 21 (57%)
(c) Send reminders to patients when they are due for CRC screening
30 (70%) 8 (27%)
(d) Estimate CRC screening rates 37 (82%) 23 (62%)
Electronic Health Record Accuracy
24.4%
68.9%
6.7%
Very accurate*Somewhat accu-rate**Not at all accu-rate***
*Primary source for reports or patient care decision **Need a secondary audit or cross check with additional documentation***Would not use for reports or patient care decision
Summary
• In 3 months since survey concluded, we have identified:• Positive associations of PAR with CRC
screening BPs • Room to go to fully and systematically
implement the CG EBIs at participating clinics• Associations of PAR and certain CFIR
constructs with implementation of Provider Reminders
• Limitations of EHR CRC screening data
Summary
• In 3 months since survey concluded, we have identified:• Positive associations of PAR with CRC
screening BPs • Room to go to fully and systematically
implement the CG EBIs at participating clinics• Associations of PAR and certain CFIR
constructs with implementation of Provider Reminders
• Limitations of EHR CRC screening data
FQHC Survey Subgroup: Manuscripts
MANUSCRIPT FOCUS LEADSITE U Co Emory UCLA USC UT-H UW WU
CFIR Measures/ Survey development* UTH x x x x X x xSurvey results – Practice Adaptive Reserve (PAR)/PCMH Best Practices UW x x x x x X x
Survey results – EHR/?PCMH Best Practices UW x x x x x X xSurvey results – Practice Adaptive Reserve/PCMH BP/Clinic characteristics ?UW
Survey results – CG EBAs/Practice Adaptive Reserve TBD
Survey results – CG EBA/CFIR measures UTH/UCo X x x x X x xSurvey results – CG generic EBAs/CFIR measures Emory x X x x x x x
? Survey results – CG EBAs/Clinic Characteristics TBD
Agreement b/t staff reports and clinic contact of CG EBAs/ PCMH Best Practices TBD
Acknowledgements
Special thanks to:CPCRN FQHC Workgroup Team
Alan Kuniyuki MS, Letoynia Coombs PhDAllison Cole, MD, MPH
Jim Hotz MDKathleen Clark CHC contacts
Survey respondents
Contact Information: [email protected]
This work was also supported by National Cancer Institute grants R21 CA 136460 and R01 CA124397