Гуманистический подход к совершенствованию: подход, основанный на постоянном склерозе и постоянном повышении качества сотрудничества в области координации.

Introduction

Multiple sclerosis (MS) impacts approximately 1 million people in the United States and 2.3 million worldwide. Most people are diagnosed between 20 and 50 years of age, and the annual cost of care ranges between $39,000 and $69,000.
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MS qualifies as a costly, complex, and chronic (“3C”) condition, similar to other chronic conditions such as cystic fibrosis and irritable bowel disease. Many 3C conditions have benefited from a focus on quality and system improvement through coordination of care, reducing unwarranted variation, and improving population outcomes.
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The authors’ goal is to describe an embedded improvement intervention employed within the MS continuous quality improvement (MS-CQI) Collaborative, which was the first learning health system (LHS) improvement research study for MS (2018–2022). Although the outcomes of MS-CQI are described elsewhere,
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the authors focus in this article on the humanistic approach that engaged the care team and patients, using a coach-supported improvement intervention. This utilized study-level data and local-level autonomy and ownership of the work critical to QI activities, which prioritized capability building in the people involved in the work.
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Methods

The authors employed a coach-supported QI approach within an LHS-supported improvement model developed for MS-CQI, which was informed by a registry-enabled feedback information environment to facilitate the improvement intervention.

The coach-supported LHS improvement model

The authors applied a practical adaptation of Peek’s “ Three Worlds Model. ”
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This suggested that the authors examine health care systems from clinical, operational, and financial perspectives. The basic questions of Peek’s model included: 1) “What care is called for and is it high quality?” This was the clinical perspective. 2) “What will it take to accomplish care and is it well executed?” This was the operational perspective. 3) “How will care best use resources and is it a good value? This was the financial perspective . The authors used this framework to structure a 12-step standard improvement process. This utilized aspects of QI coaching and medical approaches commonly used in health care,
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and to help the QI teams more broadly consider their QI efforts, and embedded them in the LHS structure of MS-CQI. This was influenced by a coproduction LHS model.
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The result was the MS-CQI coach-supported LHS intervention, which integrated coach-supported improvement activity informed by patient-reported outcomes and clinical data ( Figure 1 ).

Multiple sclerosis continuous quality improvement coach-supported learning health system. EMR = electronic medical record; MS = multiple sclerosis; MS-CQI = multiple sclerosis continuous quality improvement; PRO = patient-reported outcome; QI = quality improvement.

The information environment

The MS-CQI LHS registry provided feedback data to sites on a monthly basis. This informed improvement teams on clinical, functional, and patient-reported outcomes for their site populations, benchmarked against the overall collaborative. In addition, “QI readiness” assessments were used to inform the coaching intervention by targeting specific needs improvement teams. A baseline assessment utilizing 4 different tools was performed using a secure online HIPAA-compliant survey tool. This included a Quality Improvement Knowledge Application Tool (QIKAT), modified for MS with 8 questions,
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to assess QI knowledge. It also included the Institute for Healthcare Improvement (IHI) Monthly Progress Scale
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to assess team progress on QI work. The QI Experience Leaders and Teams surveys
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were administered to the site investigator and QI team members to assess their views about QI in health care and in their clinical practices. These assessments evaluated each participating site individually on its progress and collectively for MS-CQI overall.

Coach-supported improvement intervention

The coaching intervention began with a site visit conducted by the improvement coach with a team from the MS clinical site, including the site investigator and a coordinator. This included meetings with clinic leaders and staff to learn about their clinic’s context, their experience with QI, what they thought was working well, and what their opportunities might be for improvement. The coach also observed clinical processes, including checkin/checkout and rooming processes, and observed clinic staff and practitioners engaged in care with people with MS (PwMS). Data from the MS-CQI information environment supplemented coaching observations. The coach met with teams twice monthly to guide them through a QI process using a standard QI Toolkit developed specifically for MS-CQI. The QI Toolkit outlined 12 steps the clinic team could follow and included worksheets to facilitate team planning and QI work at each step of the process ( Figure 2 ). QI meetings also included reviews of MS-CQI registry data and local data collected by the improvement teams related to the QI work.

Quality improvement Toolkit process outline. PDSA = Plan-Do-Study-Act; QI = quality improvement.

Coaching actions were aligned with each step in the QI Toolkit. This provided a semistructured approach and a degree of standardization to the approach. However, local autonomy of the teams and ownership of their work were also emphasized within the bounds set by the standard process. Sites could customize their local work, as long as it was focused on improving MS care quality and outcomes. The coach did not “tell” the teams what to do but instead supported teams in exploring their context and improvement needs. This led to identifying and testing change ideas, exemplifying the humanistic approach.

Data Collection

The authors used descriptive data from the MS-CQI Collaborative data registry to define the population characteristics for the participating sites in the study. The authors also collected a modified QIKAT 13 survey (described subsequently) from participating improvement team members before and after exposure to the coaching intervention. This was designed to assess changes in perceived knowledge and skills in QI key competencies.

Ethics Review

This study was reviewed and approved by the Dartmouth College Committee for Protection of Human Subjects as a minimal risk research study.

Results

MS-CQI enrolled 2736 PwMS, who participated over a 3-year period in the overarching MS-CQI program. Per the prospective step-wedge cluster-randomized design used in MS-CQI, following a baseline year (year 1), 1 of the 4 participating MS clinics was randomized to the substudy QI intervention in the first year (year 2), and 2 additional sites were randomized to intervention in the following year (year 3). The characteristics of the study population aligned well overall with the characteristics of a general PwMS population but varied substantially at the site (system) level ( Table 1 ).

Table 1: Population characteristics by center and multiple sclerosis continuous quality improvement overall (year 1) Characteristics Concord MGH UVM Orlando MS-CQI Collaborative Patients: n (%)
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955 (35) 417 (15) 740 (27) 624 (23) 2736 (100) Sex: % female
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79 73 74 77 76 Age, y: mean (SD)
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52.1 (11.9) 49.1 (13.2) 52.2 (12.7) 49.8 (12.5) 51.1 (12.5) MS type: % RRMS 84 77 74 91 82 Proportion on at least 1 DMT: n (%)
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748 (78) 328 (79) 465 (63) 530 (85) 2071 (76) Proportion with brain MRI: n (%)
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620 (65) 302 (72) 387 (52) 380 (61) 1689 (62) Hospitalization: mean (SD)
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0.08 (0.40) 0.06 (0.26) 0.21 (0.63) 0.13 (0.43) 0.12 (0.47) ED visit: mean (SD)
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0.19 (0.74) 0.13 (0.41) 0.21 (0.78) 0.06 (0.26) 0.15 (0.63) UC visit: mean (SD)
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0.03 (0.21) 0.04 (0.26) 0.06 (0.33) 0.01 (0.13) 0.04 (0.24) Relapse rate: mean (SD)
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0.08 (0.32) 0.12 (0.34) 0.05 (0.24) 0.18 (0.43) 0.10 (0.34) a Differences between groups significant at P < .05. DMT, disease-modifying treatment; ED, emergency department; MGH, Massachusetts General Hospital; MRI, magnetic resonance imaging; MS, multiple sclerosis; MS-CQI, multiple sclerosis continuous quality improvement; RRMS, relapsing-remitting multiple sclerosis; SD, standard deviation; UC, urgent care; UVM, University of Vermont.

Population characteristics by center and multiple sclerosis continuous quality improvement overall (year 1)

Differences between groups significant at P < .05.

DMT, disease-modifying treatment; ED, emergency department; MGH, Massachusetts General Hospital; MRI, magnetic resonance imaging; MS, multiple sclerosis; MS-CQI, multiple sclerosis continuous quality improvement; RRMS, relapsing-remitting multiple sclerosis; SD, standard deviation; UC, urgent care; UVM, University of Vermont.

Team assessment results

The QI Experience Leaders and QI team surveys were applied to the lead investigators and QI team members only. Survey results revealed that 64% (n = 3) of respondents stated QI was very important in health care; 18% (n = 1) stated it was important; and 18% (n = 1) stated it was somewhat important (80% response rate). Their views on the importance of QI in their own clinical practice were more positive, as 82% stated it was very important and 8% stated it was important. Perceived barriers to QI included competing demands, lack of knowledge, resistance to change, and “negative persons” in their organizations in positions capable of blocking change. At baseline, teams were strongest in learning together and planning, and they were weakest in QI technical skills. The modified QIKAT assessments of team QI skills and knowledge revealed low capability preintervention and improved capability postintervention ( Figure 3 ).

Quality improvement skills and team experience pre– and post–quality improvement. PDSA = Plan-Do-Study-Act; QI = quality improvement; QIKAT = Quality Improvement Knowledge Application Tool.

Improvement activities described

Table 2 describes key characteristics of QI activities undertaken by participating MS centers randomized to intervention during the MS-CQI study. All 3 QI teams completed the study and participated in coaching meetings, utilized the Toolkit appropriately, and engaged in QI work with good fidelity. At the beginning of the study, the teams had an average IHI progress score of 1.0, and by the close of the study, they had an average IHI progress score of 3.0, indicating substantial improvement progress ( Figure 4 ).

Table 2: Quality improvement themes, aims, and accomplishments by site Clinic Theme Global aim Specific aim(s) Accomplishments
Orlando Neurology Associates
(large urban private practice) Establish a recognized MS center

Identify the MS center inside the neurology practice.


Expectations:
Identified as an asset to the larger practice Improve and streamline MS patient care processes Improve staff satisfaction Improve patient satisfaction
The authors will improve the number of times they have patient records at the time of visit from 50% to 80% by June 2019. Recognized as an MS Center of Excellence (asset to practice). Created a specific MS intake process for newly diagnosed PwMS. Formal satisfaction surveys not administered prior to COVID and end of program.
MGH
(urban academic medical center) Patient access

Improve patient care access at the MGH MS clinic.


Expectations:
Improve time of referral to scheduled first visit Improve communication with patients, patient care access Reduce ER visits Improved patient satisfaction
The authors will decrease the percentage of ER visits by PwMS in the clinic by July 2020. The authors will decrease the amount of time from referral to first visit for PwMS by July 2020. Created a new patient welcome packet to include team contact information and instructions to call if not feeling well before going to the ER. No formal assessment on success of the welcome packer was accomplished before COVID-19 and end of program.
UVM
(rural academic medical center) Previsit planning

Improve quality of appointments by having all testing done and results available before visits to the UVMMC MS clinic.

Expectations:
Update scheduling process Improve previsit planning Establish a network of community resources
The authors will decrease the percentage of missing test results at patient visits from > 20/mo to < 2/mo in 3 mo. Created a new process of previsit planning and patient visit and test scheduling to improve the number of times patients have all tests needed at the time of the visit. Data were being collected just prior to COVID-19 and at end of the program. ER, emergency room; MGH, Massachusetts General Hospital; MS, multiple sclerosis; PwMS, people with MS; UVM, University of Vermont; UVMMC, University of Vermont Medical Center.

Quality improvement themes, aims, and accomplishments by site

Identified as an asset to the larger practice

Improve and streamline MS patient care processes

Improve staff satisfaction

Improve patient satisfaction

Improve time of referral to scheduled first visit

Improve communication with patients, patient care access

Reduce ER visits

Improved patient satisfaction

Update scheduling process

Improve previsit planning

Establish a network of community resources

ER, emergency room; MGH, Massachusetts General Hospital; MS, multiple sclerosis; PwMS, people with MS; UVM, University of Vermont; UVMMC, University of Vermont Medical Center.

Institute for Healthcare Improvement Collaborative progress scale. Reproduced with permission from Institute for Healthcare Improvement. Source: Institute for Healthcare Improvement. Assessment Scale for Collaboratives. https://www.ihi.org/resources/tools/assessment-scale-collaboratives . PDSA = Plan-Do-Study-Act.

Orlando Neurology Associates, which is a large private practice MS center in the southeastern United States, was the first site to be randomized to intervention. Orlando followed a general neurologic population of 16,861 patients, with 1310 (7.7%) being PwMS (15,429 MS visits in year 1). After reviewing the data noted previously and their quarterly data, the MS Center of Greater Orlando determined that they should focus on improving the identity of the MS clinic inside their larger neurology practice, streamlining patient care processes, and improving patient and staff satisfaction. During the intervention period, they introduced a new MS intake tool and process, an MS previsit survey, and a new rooming and assessment process in the clinic. By the close of the study, these changes contributed to them being identified as an MS Center of Excellence by the Consortium of Multiple Sclerosis Centers.
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Massachusetts General Hospital and University of Vermont were randomized to intervention in the following year. Massachusetts General Hospital (a large academic MS center in the northeastern United States) focused on access, with an emphasis on reducing the time from referral to first appointment, improving communication with patients, increasing the role of the registered nurse, and reducing emergency room visits by addressing more MS issues during MS clinic visits. University of Vermont (a large rural academic MS center in the northeastern United States) focused on improving previsit planning processes so that they have all of the information they need about a patient at the time of the visit. This was designed to improve visit efficiency and quality and also to reduce the number of canceled and rescheduled visits.

The improvement experience

At the outset, based on the initial modified QIKAT results noted previously and field notes, teams randomized to intervention had little knowledge of, or prior exposure to, QI. They were therefore somewhat skeptical about being involved in a QI intervention. In some settings, initial organizational resistance to QI was observed. For example, a site leader advised that the QI coach speak only with the people directly linked to the MS-CQI study and not “interfere with the work of the staff.” Others initially viewed engaging in QI as extra work on top of their current workload and were hesitant to commit. However, as the teams began to meet regularly and engage in QI work together, they realized they were making decisions about what they wanted to improve based on their data and their ideas. They then began to take ownership of their work and became more willing to make the time to focus on improving their systems of care.
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Site research coordinators were also key factors in the success of the teams. Each of the coordinators took a lead role in collecting information, as well as in working with the QI coach, the team members, and the larger clinic staff, along with practitioners, leaders, and patients. This was in an effort to help the teams stay organized and reach their shared goals. A critical moment occurred at the annual MS-CQI Collaborative meeting, when the Orlando team reported on the first year of its work and their positive experience, as they began to see changes in their systems and processes. This is often observed in improvement collaboratives
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using an “all teach/all learn” format such as the one employed in MS-CQI. The other teams began to see the value of the work and how it had an energizing effect, as they learned more about their own programs and utilized the collaborative and site-specific data to improve their systems of care.

Limitations

In this brief report, the authors have described the components, characteristics, general observations, and basic descriptive outcomes of the MS-CQI coach-supported improvement intervention. The intent was to illustrate the humanistic design of the approach in engaging and supporting the QI team, along with the trade-off balance between standardization of the exposure at the study level and local level autonomy and ownership of the work that is critical to QI activities. Although the findings suggest basic feasibility, acceptability, and utility of the QI intervention, further study would be required to rigorously examine the approach using a formal evaluation and an implementation science framework. This study was part of a larger study that was designed to evaluate outcome variation at the systems level and to improve those outcomes. It was not designed to promote the use of any particular disease-modifying treatments produced by any manufacturer.

Conclusion

MS-CQI has made a strategic investment in a humanistic improvement approach by employing an improvement intervention relying on team development and coaching rather than a rigidly protocolized implementation top-down strategy. To the authors’ knowledge, this is the first documented attempt to introduce an approach of this kind as an intervention in a multicenter improvement research study of MS. The authors strove in MS-CQI to employ structure and standardization through the frequency and type of coaching employed and the use of a standard 12-step process, including a QI Toolkit. This was balanced with an equal prioritization of local team context autonomy, their need to “own” their work, and a focus on developing QI knowledge and skills in the people and teams involved. The teams varied in the focus of their work but developed along a similar trajectory, monitored and guided by the improvement coach. The teams demonstrated basic feasibility (use of QI Toolkit), acceptability, utility, and improved skills and QI knowledge (improved QIKAT performance and improvement progress). Perhaps most important, however, was the community and the team engagement in the work that was realized (humanistic) in its application by the teams themselves. The capability built within them by that effort was also notable. This has the potential to far outlast the conclusion of the formal MS-CQI study, and it has been observed as a key characteristic in communities of practice.
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Finally, it is interesting to note that MS-CQI was the first documented LHS design improvement study of MS featuring the use of feedback data for simultaneous improvement and research. This is not unique, as many other LHS efforts exist that have these capabilities. The differentiating aspect, perhaps, is that MS-CQI designed the LHS approach with the direct primary intention to inform the people in the MS centers participating in improvement. Meanwhile, the intention was not to inform operations or financial management. This may seem at first like a basic observation. However, it has actually been cited in recent LHS reviews to be among the most prevalent factors missing in modern LHS designs, which are technically getting stronger, but they are also increasingly getting less humanistic.
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Perhaps as the future marches boldly forward into a technologically sophisticated realm of advanced LHS designs powered by artificial intelligence, attention should be given to approaches like MS-CQI. These types of approaches were intentionally designed to put people first, as per Donabedian,
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by the structure, process, and outcomes of their design and interventions.

Acknowledgments

The authors thank the persons with multiple sclerosis who participated in the parent MS-CQI study for contributing clinical information from their electronic health records and through completing patient-reported outcome measures. The authors also thank health professionals participating in this coaching study for completing interviews and questionnaires about their perceived knowledge and skills, and their experience participating in the MS-CQI coaching approach.

Footnotes

Author Contributions: Randall Scott Messier, MT, PCMH CCE, led the development of the study documented in this article and developed the improvement coaching program described in the manuscript, conducted data analyses, and participated in drafting and revising the manuscript. Brant J Oliver, PhD, MPH, FNP-BC, PMHNP-BC, CPXP, served as the MS-CQI principal investigator overseeing the multicenter study in which the coaching intervention described in this manuscript was employed, and participated in reviews and revisions of the manuscript.

Conflicts of Interest: None declared

Funding: This work was supported as part of the MS-CQI Collaborative study, which was funded by Biogen.

Data-Sharing Statement: Data available upon request. Readers may contact the corresponding author to request the underlying data.

References