Shin-Ping Tu, MD, MPH ; Maria Fernandez, PhD, Vicki Young, PhD
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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
DenverOctober 4, 2013
The Cancer Prevention and Control Research Network:
Federally Qualified Health Centers Workgroup
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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)
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CPCRN CHC Survey• 3 Frameworks
• Patient Centered Medical Home (PCMH)• Practice Change and Development (PCD) 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
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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
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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
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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)
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CHC Staffing Shortages
Provid
ers
Nurse
s
Med
ical A
ssist
ants
Enabli
ng S
ervic
es0%
10%
20%
30%
40%
50%
60%
Percent of
clinics
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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.
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Practice Change and Development Model
Capability for Development
Practice core
Adaptive reserve
Attentiveness to local environment
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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.
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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.
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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
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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)
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PAR and PCMH Best Practices Score
Respondent reported performing PCMH best practices “usually” or “always”
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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)
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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
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Electronic Health Record Adoption
90%
10%
EHRNo EHR
N=50
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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%)
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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
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Summary
• In 3 months since survey concluded, we have identified:• Partner CHCs have significant staffing
shortages• Positive associations of PAR with PCMH CRC
screening best practices • Room to go to fully and systematically
implement Community Guide EBIs at participating clinics
• Associations of PAR and 10 CFIR constructs with implementation of Provider Reminders
• Limitations of EHR data
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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 x
Survey 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 x
Survey 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 x
Survey 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
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Acknowledgements
Special thanks to:CPCRN FQHC Workgroup Team
Alan Kuniyuki MS, Letoynia Coombs PhD
Allison Cole, MD, MPH
Jim Hotz MD
Kathleen 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