Implementing Practice Facilitation in Research: How Facilitators Spend Their Time Guiding Practices to Improve Blood Pressure Control

doi:10.21203/rs.3.rs-2617959/v1

Download PDF

Short report

Implementing Practice Facilitation in Research: How Facilitators Spend Their Time Guiding Practices to Improve Blood Pressure Control

https://doi.org/10.21203/rs.3.rs-2617959/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 31 Jul, 2023

Read the published version in Implementation Science Communications →

You are reading this latest preprint version

Background: Practice facilitators (PFs) oversee quality improvement (QI) initiatives aimed at enhancing patient outcomes and operational efficiencies. Little research has explored the amount of time PFs spend with practices on QI activities. This short report expands on previously published work which detailed a 12-month practice facilitation intervention focusing on improving hypertension control among people living in rural settings in the southeastern USA. This report analyzes data on the time PFs spent to guide 32 primary care practices in implementing QI activities to support enhanced outcomes in patients with high blood pressure.

Methods: As part of the parent study, the Southeastern Collaboration to Improve Blood Pressure Control trial, four PFs documented time spent: 1) driving to support practices; 2) working on-site with staff and clinicians; and 3) communicating remotely (phone, email, or video conference) with practice members. We analyzed the data using descriptive statistics to help understand time devoted to individual and aggregated tasks. Additionally, we explored correlations between practice characteristics and time spent with PFs.

Results: An average of 130 (SD 65) minutes was spent per visit driving to and from individual practices. The average time spent on-site per visit with practices was 87 (SD 37) minutes, while an average of 17 (SD 12) minutes was spent on individual remote communications. During the 12-month intervention, 1131 remote communications were conducted with practices. PFs spent most of their time with clinical staff members (n=886 instances) or with practice managers alone (n=670 instances) while relatively few on-site visits were conducted with primary care providers alone (n=15). In 19 practices, no communications were solely with providers. No significant correlations were found between time spent on PF activities and a practices’ percent of Medicaid and uninsured patients, staff-provider ratio, or FQHC status.

Conclusions: PFs working with practices serving rural patients with hypertension devote substantial time to driving, highlighting the importance of optimizing a balance between time spent on-site vs. communicating remotely. Most time spent was with clinical staff, not providers. These findings may be useful to researchers and business leaders who design, test, and implement efficient facilitation services.

Trial registration: NIH ClinicalTrials.gov. NCT number: NCT02866669. Registered 15 August 2016. https://clinicaltrials.gov/ct2/show/NCT02866669?term=NCT02866669&draw=2&rank=1.

NHLBI AWARD number: PCS-1UH3HL130691.

practice facilitation

primary care

quality improvement

hypertension

rural health

PFs documented time spent implementing QI activities in rural primary care practices, providing insights to implementation science researchers on how to operationalize efficient practice facilitation services.
These data illustrate how PFs organized the time spent to guide practices to implement key driver activities within a 12-month period.
This paper adds claritity to how PFs allocate their time and resources to support QI efforts. The lack of correlations with common practice characteristics supports engaging in future work to understand other variables that may impact the time facilitators spend to guide practices in change activities.

Practice facilitation is an especially promising approach to guiding care redesign in primary care settings and has been associated with improved outcomes for patients with a variety of health conditions (Parchman, 2013; Baskerville, 2012; Knox, 2011; Nagaykaldi, 2005). Practice facilitation methods vary (AHRQ, 2018), and the likelihood of an organization’s decision to offer and sustain these services depends on the value the services provide and associated costs to run such programs. Quantifying the amount of time practice facilitators (PFs) spend in support of the practices they serve is an important step in developing and implementing strategic planning processes for practice facilitation organizations. Additionally, understanding the variability in time invested by PFs in different tasks when supporting diverse practices is key to setting up business models to test, adapt, and refine practice facilitation over time.

Practice facilitation services support practices in efforts to enhance the quality and efficiency of their clinical services (AHRQ, 2014–2015). However, little is known about whether facilitation services are sufficiently resourced to support change activities. We leveraged the work of a research grant to add knowledge of what it takes to provide practice facilitation services to rural primary care practices and to provide information that may influence the creation of a formal practice facilitation practice support program in Alabama. The Southeastern Collaboration to Improve Blood Pressure Control (SEC) team members developed and implemented a practice facilitation intervention in rural primary care practices in Alabama (AL) and North Carolina (NC). PF mentors, employed by the NC Area Health Education Center’s (AHEC) practice support program, provided training and guidance on how to implement practice facilitation services in the context of controlling high blood presure in 32 primary care practices serving rural dwelling patients in AL and NC. Trained PFs then guided practice staff and providers, using a key driver framework, to implement QI processes and build practice capacity to support ongoing QI activities long after the end of the research study.

We previously published on the methods that PFs used to guide practices to implement QI activities (Sutton, 2021). In this current manuscript, we examined the amount of time SEC PFs spent performing such tasks with practice stakeholders, including time PFs spent traveling by car in support of practice-level work, working directly on-site with practices, and communicating with practice stakeholders via phone, email or other remote means. Our hope is that these data can help researchers and business leaders estimate the amount of time and resources that are necessary to optimize the delivery of facilitation services.

SEC Trial: The aim of the SEC trial was to understand if a practice- vs. patient-level intervention, alone or in combination, delivered in predominantly rural primary care settings in AL and NC, improved blood pressure control among more than 1,500 African American adult patients with uncontrolled hypertension. A total of 69 practices serving patients from rural areas were engaged in the trial, 32 of which received practice facilitation services for one year. The SEC was a 4-armed trial where practices were randomized to receive 1) practice-level facilitation; 2) peer coaching for 25 African American patients with uncontrolled hypertension; 3) both interventions together; or 4) enhanced usual care. Practices in all study arms received access to an online educational and self-management tool (PALS, 2017), home blood pressure monitors for 25 recruited participants, and other patient-facing educational materials.

Practice facilitation intervention: PFs were expected to visit each of their practices at least once per month over the 12-month intervention period. Facilitators followed a study-specific implementation resource manual to guide practice teams to implement at least one activity from each of 4 “key driver” domains with the goal of having all 4 activities completed within the 12-month time frame.

Four PFs (2 from each state) guided staff members from the practices to implement at least 4 improvement activities using a Plan, Do, Study, Act (PDSA) approach. Details related to how the practice facilitators were trained and how they guided practice level activities has been previously published (Sutton, 2021). Figure 1 includes examples of activities in which PFs engaged with their practices. The PFs used the key driver framework to assist practices in moving from knowledge to active learning and ultimately building internal capacity. The key activities strived to 1) use data to drive change; 2) optimize the use of teams to deliver care; 3) standardize care processes such that evidenced-based care was consistently provided to the right patient at the right time; and 4) engage patients in ongoing self-management support activities. One NC facilitator had a panel of 9 practices while the other had five. One AL facilitator carried 11 practices over time, while the other managed seven. NC PFs were generally assigned to practices in geographic regions of eastern and central NC, while the AL PFs covered south-central in the east and west of the state.

This study: We collected practice characteristics as part of the parent trial (Table 2). We asked PFs to document the time they spent 1) driving to and from practices; 2) visiting with practice personnel on-site; and 3) communicating with clinic personnel by phone, email, or video conference (remote communications time) (Figures 1 and 2 and Table 3). These data were entered as “minutes” per activity into the study database by the PFs after completing tasks. To understand “who” at the practices engaged with PFs, we captured the number of contacts PFs had with providers, staff, and other clinic personnel. Based upon feedback from our PFs regarding how phone and email communications were often used in tandem and synergistically, and that very little remote video conferencing was used, we aggregated these three items into one time category called “remote” communications. As the trial was ongoing during the early phases of the COVID-19 pandemic, when travel and engagement with practices was limited, we provide these data for all 32 practices but also provide this data limited to the 28 practices that had completed their 12-month practice facilitation intervention before March 2020 (Table 4).

Statistical Analysis: We used descriptive statistics to characterize the amount of time, in minutes and/or hours, spent by different PFs within their practices using the 3 different categories (travel, on-site activities, and remote communications). We used boxplots to visualize the distributions/shape and variability of the data. We also calculated the total amount of time spent in 12 months for each of the three time categories.

Additionally, we conducted paired t tests and calculated Pearson r correlation to explore possible correlations between time spent on PF activities (excluding travel time) and practice characteristics such as payer mix, numbers of staff that support individual clinicians, and if the practice was a federally qualified health center (FQHC) or not. To address provider support, we created a provider to staff support ratio measure. For payer correlations, we created a variable to capture the percent of a practice’s patients with Medicaid and those who were uninsured. The staff-provider ratio variable was dichotomized using median split of less than or equal to 3, and the percent of uninsured or with Medicaid variable was dichotomized using median split of less than or equal to 40 percent.

Fifteen of the 32 practices were community health centers, practices averaged 3.7 fulltime providers, just under a quarter of patients among all 32 practices were Medicaid beneficiaries, and 58% of the practices’ patients were identified as African American (Table 2). Time spent for the three activity categories are presented in Table 3 (all 32 practices) and Table 4 (28 practices not impacted by the COVID-19 pandemic). “Remote time” and “on-site time” are visualized as boxplots in Figures 1 and 2.

PFs made 416 trips to practices throughout the study and had 410 face-to-face visits with clinic personnel. The most common activity between PFs and clinic personnel was communicating via remote means (n=1,131). The number of encounters and average time spent on activities were similar when the four practices impacted by COVID-19 were excluded (Table 4).

PFs spent an average of just over 130 minutes (~2.2 hours) driving to practices in these rural regions for individual site visits. The average number of minutes spent per on-site visit was 87 (SD 37) minutes (range of 10 to 300 minutes) (Table 3). Over the course of the 12-month intervention, the mean number of hours spent on-site was 18.6 (SD 5.5) with a range from 6.6 to 31.4 hours. An average of 17 (SD 12) minutes was spent each time PFs communicated remotely with practices.

Regarding “who” PFs spent time with at practices, the majority of their time was dedicated to working with clinical staff (n=886 encounters) or practice managers alone (n=670 encounters). There were only 48 observations where the facilitator spent time solely with primary care providers (Figure 3). One-on-one provider-facilitator communications occurred in only 13 of the 32 practices and most of those communications (33 of 48) occurred via remote means.

Using a p<0.05 to define a statistically significant threshold for associations between practice characteristics and PF time spent (sans travel time), we did not find any statistically significant differences between the average number of minutes spent by PFs at practices with a staff-provider ratio less than 3 compared to those with a ratio higher than 3 (1,703.1 minutes vs. 1,779.3 minutes; p-value=0.7), practices with a percent of uninsured or Medicaid patients less than 40 vs. >40% (1,700.8 vs. 1,757.8 minutes; p-value=0.8), or whether a practice was an FQHC vs. not (1,748.8 minutes vs. 1,709.8 minutes; p-value=0.8). The Pearson correlation coefficients for the associations between time spent with facilitators and practices’ percent of Medicaid or uninsured patients and staff-provider ratios were r=0.02 and r=-0.05, respectively.

We leveraged the SEC trial to better understand the time PFs spent with practices to help decision makers consider how to support a practice facilitation program in Alabama using an NC-based program and mentorship as a model. More time was spent on driving than any other activity, indicating how proximity of PFs to practices is important when determining efficiencies. Conservative estimates based on our data suggest that interventions may need to include time travel of up to 300 minutes (5 hours) per round trip for a single practice visit and up to 60 hours per year for travel to support a single rural practice. Efficiencies may be enhanced if more than one practice can be visited in a single trip and or if a hybrid of on-site and remote communications can be organized in the same day. Real time data collection, using technologies like voice activation software, could optimize efficient data capture and data quality.

Although specific facilitation tasks and time required to complete such tasks may vary by project, we believe these data can inform decision-making as to how practice facilitation services are designed and budgeted even outside of a high blood pressure focus. We posit that it is wise to consider the high-end of time ranges when planning and budgeting PF interventions due to the many competing demands of facilitators and practices. For instance, one PF shared how she spent a relatively excessive amount of time on emails with one practice due to frequent leadership and staff turnover in the practice. She noted that email was the only reasonable option to store such information so that the newer practice stakeholders could have it available while people were transitioning on and off the QI team.

Time spent on-site was the second highest time category, which aligns with the study’s aim of having PFs interact with practice staff at least monthly on-site. Notably the PFs shared throughout the study that time spent on-site, especially in the early phases of the intervention’s implementation, was critical to successful relationship building and subsequent implementation of change activities. This observation has financial implications for practice facilitation programs, which may result in higher operating expenses in rural areas.

When not traveling to practices, PFs spent significant time communicating with practice staff to oversee the implementation of QI activities via phone, email, or video conference. Although anecdotally we have learned how skills with using remote communications were enhanced when practices needed to provide more remote care during the COVID-19 pandemic, how much time practices may want to participate in virtual facilitation going forward is unknown. One of our PFs noted that practices were more likely to cancel PF visits when they were scheduled as virtual vs. when the facilitator was known to be driving to engage with practice staff. It is possible that facilitation services may be able to leverage remote facilitation resources more going forward, but this requires further study.

Our results did not find any notable correlations between the average number of minutes PFs provided to a practice (excluding travel time) and common practice characteristics. These results may stimulate researchers and PF organizations to design studies to identify how other variables may be associated with time investments.

Limitations

These data are limited in that time spent was self-reported by PFs and often estimated retrospectively. Time tracking software such as Harvest or Timesheet could be useful in future projects to improve precision. A second limitation is that we did not collect the amount of time that practice staff worked on change activities in between contacts with their facilitators. Our work was focused mainly on activities to address hypertension, but based upon feedback from our facilitators who have worked with practices in improving outcomes for other conditions, we believe that these time estimates may apply reasonably to other conditions.

Finally, the onset of the COVID-19 pandemic occurred during the later years of the trial presented unanticipated challenges. However, during the course of this trial there were other significant events (hurricaines, ice storms, floods) that also impacted the cadence of facilitation work with practices. These realities only further support using ranges of data when anticipating budget and other resource needs to support facilitation interventions.

These time estimates captured by PFs working with 32 primary care practices that serve rural patients in the SEC trial may uniquely offer stakeholders guidance regarding PF trial design and program budgeting. Our data demonstrate that practice facilitation, as configured in the SEC trial, is a time-intensive activity. Attempts to increase the effectiveness of remote communications and reduce the time dedicated to driving should be considered in order to enable PFs to help practices implement change activities in a constantly changing environment. By sharing this work with other researchers and stakeholders interested in practice facilitation and QI, we hope to provide clarity regarding the resources needed to support facilitation services and to inspire others to investigate ways to optimize practice facilitation services and outcomes.

PF = Practice facilitator

PFs = Practice facilitators

QI = Quality Improvement

AL = Alabama

NC = North Carolina

PDSA = Plan, Do, Study, Act

SEC = Southeastern Collaboration to Improve Blood Pressure Control

FQHC = federally qualified health center

Ethics approval and consent to participate: This study was approved by the IRB at UNC-CH, ECU, UAB, and Weill Cornell. UNC-CH’s IRB number: 15-2687. UAB IRB number: 160722009. ECU IRB number: 16-002206. Weill Cornell Medicine IRB number: 1609017600.

Consent for publication: N/A

Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests: The authors declare that they have no competing interests.

Funding: NHLBI award number: PCS-1UH3HL130691

Authors’ contributions: KS contributed to data collection, data system monitoring, data analysis, and manuscript writing. ER served as the UNC site project manager and contributed to data collection, data system monitoring, data analysis, and manuscript writing. JR, LPN, MC, SH served as the practice facilitators. OS contributed to data analysis. MM served as a liaison for practice facilitation support. AC served as the UAB site principal investigator. DC served as the ECU site principal investigator. MS served as the overall study principal investigator. JH oversaw the practice facilitation arm of the study, served as the UNC site principal investigator, and contributed to data system monitoring, data analysis, and manuscript writing. All authors contributed to project protocol maintenance, data system monitoring, and manuscript writing. All authors read and approved the final manuscript.

Acknowledgements: The Southeastern Collaboration to Improve Blood Pressure Writing Group reviews manuscript proposals and submissions related to the SEC study.

Tip Sheet: How a Practice Facilitator Can Support Your Practice. Agency for Healthcare Research and Quality. 2015. http://www.pbgh.org/wp-content/uploads/2020/12/tip-sheet_-how-a-practice-facilitator-can-support-your-practice_ahrq_unknown.pdf
Training Program Summary: Practice Coach Training for the North Carolina AHEC Practice Support Program. Agency for Healthcare Research and Quality. 2014. https://www.ahrq.gov/ncepcr/tools/case-studies/ncahec.html
Practice Facilitation Handbook. Agency for Healthcare Research and Quality. 2018. https://archive.ahrq.gov/ncepcr/tools/pf-handbook/index.html
Patient Activated Learning System (PALS). https://palsforhealth.com (2017). Accessed 8 Aug 2022.
Sutton KF, Richman EL, Rees JR, Pugh-Nicholson LL, Craft MM, Peaden SH, Mackey M, Halladay JR. Successful Trial of Practice Facilitation for Plan, Do, Study, Act Quality Improvement. The Journal of the American Board of Family Medicine. 2021;34(5) 991-1002.
Parchman ML, Noel PH, Culler SD, et al. A randomized trial of practice facilitation to improve the delivery of chronic illness care in primary care: initial and sustained effects. Implement Sci. 2013;8:93.
Baskerville NB, Liddy C, Hogg W. Systematic Review and Meta-Analysis of Practice Facilitation Within Primary Care Settings. Annals of Family Medicine. 2012;10(1):63-74.
Knox L, Taylor EF, Geonnotti K, et al. Developing and Running a Primary Care Practice Facilitation Program: A How-to Guide. Mathematica Policy Research; 2011.
Nagykaldi Z, Mold JW, Aspy CB. Practice facilitators: a review of the literature. Family Medicine. 2005;37(8):581-588.
Houston TK, Delaughter KL, Ray MN, et al. Cluster-randomized trial of a web-assisted tobacco quality improvement intervention of subsequent patient tobacco product use: a National Dental PBRN study. BMC Oral Health. 2013;13:13.

Table 1. Examples of PDSA Activities by Key Driver Domain

Key Driver	Example Activities that facilitators guided practices to implement
Clinical Information Systems (CIS)	Developing a practice-level list and monthly reports of patients with HTN and uncontrolled HTN
Standard Care Processes (SCP)	Working with staff to document BP in EHRs such that the data would populate HTN reports Standardizing staff behaviors to repeat BP measurements for patients with SBP^± and DBP^±± values ≥ 140 and/or ≥ 90 mm Hg
Optimized Team Care processes (OTC)	Weekly huddles to identify patients with uncontrolled BP and those requiring extra support; instituting processes for making follow-up calls to check on patient wellbeing and reporting out-of-office BP measurements back to staff
Patient Self-Management Support (SMS)	Patient use of BP logs to document out-of-office BP’s and instructing clinical staff on how to address noted BP trends that may be related to stress, lack of medication adherence, etc. Use of “Teach Back” methods and goal setting with patients Providing a raffle in clinic waiting rooms to receive a home BP monitor as a way to promote home monitoring and self-management
^*BP = Blood Pressure,^±SBP= Systolic Blood Pressure, ^±±DBP=Diastolic Blood Pressure, HTN = hypertension

Table 2. Practice Characteristics

Practice Characteristics	N/mean (%, or range) ^a
Full-time providers MD/DO, NP, PA)	3.7 (0-21)
Part time providers (MD, DO, NP, PA)	0.9 (0-18)
Other (nurses, administrative/clinical support staff)	12.3 (2-53)
Practice Ownership Type
Private	11 (34.4%)
FQHC or similar	15 (46.9%)
Free Clinic	1 (3.1%)
Part of a Hospital/Health System	5 (15.6%)
Years practice has been in operation	16 (1-42)
Payer Mix
Medicare	22% (0-60%)
Medicaid	23% (0-50%)
Dual Medicare/Medicaid	8.5% (0-30%)
HMO, PPO, Commercial	21% (0-72%)
Uninsured	24% (0-100%)
Other	2% (0-17%)
Race/Ethnicity
% African American patients	57.5% (25-94%)
% Hispanic Latino patients	10% (0-60%)
^aData provided as absolute numbers or means for continuous variables and proportions.

Table 3. Time Spent by Facilitators Across Time Categories - All 32 Practices Randomized to Practice Facilitation

Type of Contact or Activity	Number of observations	Mean # of minutes per observation (SD^c)	Median # of minutes per observation	Range of minutes per observation	Mean time spent per practice in minutes & (hours)	Range of minutes & (hours)
Travel (round trip)	416^b	130 (65)	120	20 - 300	1,686 (28.1)	315 - 3,600 (5.3 – 60.0)
On Site visits	410	87 (37)	80	10 - 300	1,118 (18.6)	395 - 1,885 (6.6 - 31.4)
^aPhone/Email	1126	17 (12)	15	5 - 120	603 (10.0)	20 - 1,295 (0.3 - 21.6)
^aRemote access	5	55 (39)	45	25 - 120	69 (1.1)	25-180 (0.4-3.0)
^a Categories combined in the manuscript’s results, kept separate in table to provide detail ^b 416 round trips include 6 trips for supply management ^cStandard Deviation

Table 4. Time Spent by Facilitators - 28 Practices that Completed the PF Intervention by March 2020

Type of Contact	Number of observations	Mean # of minutes per observation (SD^b)	Median # of minutes per observation	Range of minutes per observation	Mean time in minutes & (hours) in one year	Range of minutes & (hours) in one year,
Travel (round trip)	386	134 (66)	120	20 - 300	1841 (30.7)	610-3600 (10.2 – 60.0)
On Site visits	380	88 (38)	90	10 - 300	1195 (19.9)	705-1885 (11.8 - 31.4)
^aPhone/Email	1061	17 (12)	15	5 - 120	643 (10.7)	95-1295 (1.6 - 21.6)
^aRemote access	5	55 (39)	45	25 - 120	69 (1.1)	25-180 (0.4 - 3.0)
^a categories combined in the manuscript’s results, kept separate in table to provide detail. ^b standard deviation

PFTimeTrackerTIDieRChecklist2.docx

Download PDF

Journal Publication

published 31 Jul, 2023

Read the published version in Implementation Science Communications →

Editorial decision: Major revision
30 May, 2023
Reviewers agreed at journal
14 Apr, 2023
Reviewers invited by journal
14 Apr, 2023
Submission checks completed at journal
15 Mar, 2023
Editor invited by journal
15 Mar, 2023
Editor assigned by journal
23 Feb, 2023
First submitted to journal
22 Feb, 2023

You are reading this latest preprint version

Implementing Practice Facilitation in Research: How Facilitators Spend Their Time Guiding Practices to Improve Blood Pressure Control

Status:

Journal Publication

Version 1

Abstract

Figures

Contributions To The Literature

Background

Methods

Results

Discussion

Conclusion

Abbreviations

Declarations

References

Tables

Supplementary Files

Status:

Journal Publication

Version 1