Abstract
Objectives:
Physician practices are increasingly owned by health systems, which may support innovation adoption for adults with chronic conditions. We examined health system and physician practice-level capabilities associated with adoption of 1) patient engagement strategies and 2) chronic care management processes for adult patients with diabetes and/or cardiovascular disease (CVD).
Study Design:
We analyzed data collected from the National Survey of Healthcare Organizations and Systems (NSHOS), a nationally representative survey of physician practices (n=796) and health systems (n=247) (2017–2018).
Methods:
Multivariable multilevel linear regression models estimated health system and physician practice characteristics associated with practice-level adoption of patient engagement strategies and chronic care management processes.
Results:
Health systems with processes in place to assess clinical evidence (β=6.79, p=0.004) and with more advanced health information technology (HIT) functions (β=2.85, p=0.03) adopted more practice-level chronic care management processes, but not patient engagement strategies, compared to systems lacking these capabilities. Physician practices with cultures oriented to innovation, more advanced HIT functions, and with a process in place to assess clinical evidence adopted more patient engagement strategies and chronic care management processes.
Conclusions:
Health systems may support the adoption of practice-level chronic care management processes, which have a strong evidence base for practice implementation compared to patient engagement strategies, which have less evidence to guide effective implementation. Health systems have an opportunity to advance patient-centered care by expanding practice-level advanced HIT functions and developing processes to appraise clinical evidence for physician practices.
Keywords: Patient engagement, chronic care management, health systems, diabetes, cardiovascular disease
Precis:
System-owned practices with more robust local cultural and technical capabilities adopted more patient engagement strategies and chronic care management processes.
Objectives/Introduction
Physician practices in the United States are increasingly owned by health care systems.1,2 Health care system ownership of physician practices has been associated with higher prices and spending,3,4 but systems also have the potential to improve practice capabilities to manage chronic conditions.5 Improving practice capabilities to manage diabetes and cardiovascular disease (CVD) is a high priority for population health because CVD is the leading cause of death in the U.S. and patients with diabetes are at increased risk of CVD.6
Organizational capabilities central to improving care for adults with diabetes and/or CVD include chronic care management processes and patient engagement strategies. Chronic care management processes are evidence-based processes, such as use of electronic health record (EHR) decision support tools and patient registries, with demonstrated benefit to improved outcomes for patients with diabetes and CVD.7,8 Health care system-owned physician practices have incentives through risk-based payment arrangements to better engage patients in their health and health care.9 Past research highlighted that patients with high confidence in managing their own health and health care, known as patient activation, can achieve better outcomes.10 Patient engagement strategies aim to activate patients to improve their participation in managing their own health and health care through shared decision-making, shared medical appointments, and motivational interviews.11–13 Shared medical appointments enable patients to learn from peers during visits where clinicians meet with multiple patients simultaneously.23–26 Shared decision-making is used to assist informed patients in making choices that are aligned with their goals and values.3,9,13,14 Motivational interviewing involves patient-centered prioritization techniques to support patients with goal-setting for behavior change.5,20
Despite increased recognition of patient engagement strategies and chronic care management processes as important practice capabilities, they are not consistently adopted. On average, fewer than half of recommended chronic care management processes have been adopted by physician practices.14 Further, only one-third of family physicians work in practices with a patient advisory council or patient volunteers in quality improvement activities.15
Health care systems that own physician practices can provide implementation support to aid practice-level adoption of care delivery innovations through HIT infrastructure support and support for local champions to assist with change management.16,17 The relative association of health care system versus physician practice characteristics on adoption of patient engagement strategies remains unexplored. This study examines the extent to which capabilities of systems and practices are differentially associated with the adoption of chronic care management processes and patient engagement strategies.
Conceptual Model
Health care systems can influence physician practice adoption of patient engagement strategies and chronic care management processes. Our conceptual model depicts how advancing capabilities of health care systems and their owned physician practices can improve chronic care delivery (Figure 1). We integrated concepts from diffusion of innovation,18 organizational change management,19 and previous studies of chronic care management and patient engagement strategy adoption14,20–22 to inform our study hypotheses.
Figure 1:
Logic Model of Health Care System Influences on Practice Adoption of Patient Engagement and Chronic Care Management Capabilities
Arrows represent the predicted direction and magnitude of influences on the adoption of chronic care management processes and patient engagement strategies for patients with diabetes and/or cardiovascular disease in health care system-owned physician practices. Thick lines represent a relatively larger predicted influence compared to thin lines.
We posit that health care systems can support practice adoption of innovations differently depending on the strength of evidence about implementation strategies to improve uptake and fidelity. Studies assessing implementation strategies provide actionable evidence about how interventions can be adapted to fit local practice needs, culture, and resources.23 Systems can develop central capabilities when innovations have evidence-based implementation strategies or are conducive to standardization throughout the system.
Adopters of chronic care chronic care management processes may benefit from robust practice-based evidence to support effective implementation, as the adoption and implementation of these capabilities have been well-documented as part of Patient-Centered Medical Home (PCMH) implementation and the expansion of HIT in physician practices.16,24,25 In contrast, there are fewer large-scale efforts to integrate patient engagement strategies into routine care.15,26,27 Consequently, health care systems may be less likely to support the adoption of patient engagement strategies if they are disruptive to operations or compete with other priorities.
The degree to which health care systems standardize administrative and financial processes across physician practices (e.g., physician compensation and performance measurement) may influence how consistently innovations are adopted in constituent practices. Diffusion of innovations theory posits that an innovation’s compatibility to organizational structure, routines, and resources can promote uptake.18 Systems with strong standardized processes may promote compatible capabilities that can be similarly deployed throughout practices consistently, such as chronic care management processes. Conversely, patient engagement typically demands extensive local customization. For example, shared medical appointments require idiosyncratic scheduling and physical space considerations.28 Consequently, health care systems may have less influence on patient engagement strategies because centralized resources are less useful for adopting innovations that require local tailoring. We hypothesize that health care system standardization of administrative functions and processes, including physician compensation and strategic planning, will be positively associated with practice-level adoption of chronic care management processes for diabetes and/or CVD, but not patient engagement strategies (Hypothesis 1).
Health care systems can influence practice-level adoption of innovations beyond establishing standardized administrative processes. For example, systems can help practices establish processes to appraise clinical evidence, provide financial resources to support infrastructure investments, and foster organizational cultures oriented to innovation and learning. Systems can also provide instrumental support through guidance and facilitation to help practices address their unique needs, including reaching priority patient populations and supporting the expansion of practice-level capabilities such as HIT and chronic care management processes.29 Past research indicates that physician practices with more advanced HIT functions in place adopt more chronic care management processes.20,21 Further, systems can support practice cultures oriented to innovation and risk-taking, which can equip practices with the motivation and capabilities to test care delivery innovations.30,31 Accordingly, we hypothesize that health care systems and physician practices with processes in place to assess new clinical evidence, more advanced HIT functions, and cultures oriented to innovation will adopt more patient engagement strategies and chronic care management processes for diabetes and/or CVD compared to practices without these capabilities (Hypothesis 2).
Methods
Data Source
This study analyzed data from the National Survey of Healthcare Organizations and Systems (NSHOS), a nationally representative survey administered between 2017–2018 to U.S. primary care practice sites (N= 2,190, Response Rate=48.6%), and health care systems that owned or managed at least two primary care multi-specialty medical practices or acute care hospitals (N=325, Response Rate=60.9%). A knowledgeable key informant at each organization responded to the survey questions, including physician practice administrators/managers and health care system Chief Executive Officers or Chief Medical Officers. We linked NSHOS surveys with IQVIA One Key Data on health care system and physician practice characteristics. We integrated a subset of system-owned physician practice surveys (n=820) with responses from their corresponding health care systems (n=253). We excluded six systems with missing data on key covariates, resulting in an analytic sample of 796 physician practices and 247 health care systems. The research study was approved by the UC Berkeley Office of Human Subject Protections (2015-04-7420).
Dependent Variables
Measures of patient engagement strategies and chronic care management processes were developed based on past survey research assessing these practice capabilities.14,20,22,32 Psychometric analyses indicated that patient engagement strategies and chronic care management processes were distinct constructs. Exploratory factor analyses demonstrated high Eigenvalues (range: 2.39–5.79) for both constructs, high internal consistency reliability (alphas=0.82–0.86), and low correlation (r=0.38) between the measures.33
A composite measure of physician practice-level adoption of twelve patient engagement strategies was calculated and transformed to a 0–100 scale (internal consistency reliability, α=0.87). Patient engagement strategies assessed included shared medical appointments (diabetes, CVD), motivational interviewing (smoking cessation, weight loss/diet, increase in physical activity, medication adherence, training staff or clinicians), decision aids for selecting diabetes medication, and shared decision-making (physician/staff formally trained in shared decision-making, routinely engage in shared decision-making, routinely use decisions aids, and follow-up after shared decision-making).
A composite measure of practice-level adoption of eight chronic care management processes was calculated and transformed to a 0–100 scale (α=0.82). Chronic care management processes included use of evidence-based protocol guidelines, EHR-based clinical decision-support tools, disease registries, and individual feedback on clinician performance. The appendix includes detailed descriptions of survey items and descriptive statistics.
Health Care System Variables
Health care systems reported the degree to which seven processes were standardized (“done the same way”) across their physician practices. Processes included physician compensation, performance management of primary care physicians, primary care processes and team structure, hospital discharge planning, human resources functions, financial arrangements between the larger system and individual practices, data elements included in the EHR, and strategic planning. Responses were coded as “Not at all” 0, “Somewhat,” 33.3, “Mostly” 67.7, and “Full” 100, then we calculated a composite scale based on the average of all item responses (range=0–100; α=0.88).
We included a dichotomous variable for whether systems had a process in place to assess new clinical evidence (Yes/No), such as internal evaluation committees to identify and review research evidence or an organized program to pilot novel interventions. Health care system culture was assessed from questions based on the Competing Values Framework, which categorized culture based on focus level (internal or external) and the degree of influence they exert on operations (controlling or flexible).34 We measured culture of innovation based on points allocated to developmental/innovative culture type (range=0–100). Advanced HIT functions included patients’ ability to access and comment on their medical records and communicate via secure message (range=0–100; α=0.70).
Physician Practice Independent Variables
We included a dichotomous variable indicating whether practices had a process in place to assess new clinical evidence (Yes/No). A composite scale assessed practice-level innovation culture based on five items describing practice culture, including successful care delivery innovations are highly publicized, and team members openly share patient care challenges and failures with each other (range=0–100; α=0.80). Advanced HIT functions were assessed using a 5-item index (0–5).35
Control Variables
Physician practice-level control variables included physician practice size (number of physicians), participation in delivery or payment reform initiatives, and geographic region. Health care system-level control variables included system size (number of physician practices), and participation in delivery or payment reform initiatives.
Statistical Analysis
Descriptive analyses on physician practice and health care system characteristics were conducted, as well as the unadjusted analyses of adoption rates of each patient engagement strategy and chronic care management process.
Multivariable linear regression models estimated the association of health care system and physician practice characteristics on practice-level adoption of patient engagement strategies and chronic care management processes. Random system effects were used to account for the clustering of physician practices in health care systems. To aid in comparison of regression coefficients, continuous measures were standardized with a mean of 0 and a variance of 1.
We calculated the Akaike information criterion (AIC) to compare the goodness of fit of the full multivariable model to two reduced form regression models containing: 1) only health care system-level variables, and 2) only physician practice-level variables, for both patient engagement strategies and chronic care management processes.
We conducted robustness checks for our final multivariable model specifications, including calculating collinearity and model overfit diagnostics. We computed the Variance Inflation Factor for each independent variable to determine whether multicollinearity was present. We checked covariates for high correlation and dropped those with correlation above 0.60. All analyses were completed using STATA 15.0.
Results
Half of health care systems owned between 1–22 physician practices (45.3%) (Table 1). Patient engagement strategies were not widely adopted by system-owned physician practices (mean=41.4, standard deviation (SD)=28.5) (Table 2). Formal training in shared decision-making (38.2%) was less available than their routine use in shared decision-making (54.3%). On average, chronic care management processes were adopted more than patient engagement strategies (mean=69.7, SD=29.9). The most adopted capability was collecting physician performance data for diabetes (85.8%).
Table 1:
Descriptive Statistics for Health Care Systems and System-Owned Physician Practices (2017/2018)
| Total | ||
|---|---|---|
| Mean (Standard Deviation) Frequency (Percentage) |
||
| Parent Health Care System Characteristics | N=247 | |
| Process to Assess New Evidence | 139 (56.3%) | |
| Culture of Innovation | 25.1 (15.2) | |
| Advanced Health Information Technology | 53.7 (23.7) | |
| Participation in Delivery Reform | 144 (58.3%) | |
| Participation in Payment Reform | 0.9 (1.1) | |
| Health Care System Standardization | 73.6 (19.8) | |
| Size (Number of Physician Practices) | 1–22 Practices | 112 (45.3%) |
| 22–68 Practices | 73 (29.6%) | |
| 69–165 Practices | 46 (18.6%) | |
| 166+ Practices | 16 (6.5%) | |
| For-Profit Status | 62 (25.1%) | |
| System Ownership of a Health Plan | 72 (29.1%) | |
| System-Owned Physician Practice Characteristics | N=796 | |
| Process to Assess New Evidence | 395 (49.6%) | |
| Culture of Innovation | 52.6 (20.7) | |
| Advanced Health Information Technology Index | 3.1 (1.2) | |
| Size (Number of Physicians) | 1–9 Physicians | 555 (69.7%) |
| 10–20 Physicians | 141 (17.7%) | |
| 21+ Physicians | 100 (12.6%) | |
| Primary Care Physicians (% of Total Physicians) | <33% | 57 (7.2%) |
| 33–99% | 611 (76.8%) | |
| 100% | 128 (16.1%) | |
| Medicaid Revenue (% of Total Revenue) | None | 68 (8.5%) |
| Low (1–29%) | 540 (67.8%) | |
| High (30%+) | 188 (23.6%) | |
| U.S. Census Region | West | 209 (26.3%) |
| South | 295 (37.1%) | |
| Northeast | 118 (14.8%) | |
| Midwest | 174 (21.9%) | |
Data are presented as mean (standard deviation) for continuous measures, and n (%) for categorical measures. Source: National Survey of Healthcare Organizations and Systems (NSHOS).
Table 2:
Adoption of Chronic Care Management and Patient Engagement Capabilities for Diabetes and Cardiovascular Disease in System-owned Physician Practices (2017/18)
| Total N=796 |
|
|---|---|
| Mean (Standard Deviation) Frequency (Percentage) |
|
| Chronic Care Management Capabilities Composite | 69.7 (29.9) |
| Written Guidelines: Diabetes | 574 (72.1%) |
| Written Guidelines: Hypertension | 523 (65.7%) |
| Electronic Health Record Decision Support: Diabetes | 549 (69.0%) |
| Electronic Health Record Decision Support: Hypertension | 467 (58.7%) |
| Registry: Diabetes | 586 (73.6%) |
| Registry: Hypertension | 461 (57.9%) |
| Collect Physician Performance: Diabetes | 683 (85.8%) |
| Collect Physician Performance: Hypertension | 598 (75.1%) |
| Patient Engagement Capabilities Composite | 41.4 (28.5) |
| Shared Medical Appointment: Cardiovascular Disease | 34 (4.3%) |
| Shared Medical Appointment: Diabetes | 92 (11.6%) |
| Motivational Interviewing: Smoking Cessation | 475 (59.7%) |
| Motivational Interviewing: Weight Loss/Diet | 477 (59.9%) |
| Motivational Interviewing: Increase in Physical Activity | 460 (57.8%) |
| Motivational Interviewing: Medication Adherence | 448 (56.3%) |
| Motivational Interviewing Training (Staff or Clinicians) | 397 (49.9%) |
| Decision Aid: Selecting Medication for Diabetes | 221 (27.8%) |
| Physician/Staff Routinely Use Decision Aids | 256 (32.2%) |
| Physician/Staff Formally Trained in Shared Decision Making | 304 (38.2%) |
| Physician/Staff Routinely Engage in Shared Decision Making | 432 (54.3%) |
| Physician/Staff Follow-up After Shared Decision Making | 354 (44.5%) |
Composite scale values are presented as mean (standard deviation). Individual items are presented as the frequency (percentage) of sampled physician practices that report adopting that strategy. Source: National Survey of Healthcare Organizations and Systems (NSHOS).
Health care systems with a process in place to assess new clinical evidence (β=6.79 points on a 0–100 scale, p=0.004), and more advanced HIT functions (β=2.85 points on a 0–100 scale, p=0.028) had greater practice-level adoption of chronic care management processes, controlling for all model covariates (Table 3). There was no significant association between health care system characteristics and practice-level adoption of patient engagement strategies. Having a process in place to assess new clinical evidence at the physician practice level was positively associated with the adoption of patient engagement strategies (β=4.44, p=0.01) and chronic care management processes (β=7.37, p<0.001). More advanced practice-level HIT functions was positively associated with adoption of patient engagement strategies (β=3.18, p<0.001) and chronic care management processes (β=5.59, p<0.001). Practices with cultures oriented to innovation adopted more patient engagement strategies (β=10.73, p<0.001) and chronic care management processes (β=9.70, p<0.001).
Table 3:
Health Care System and Physician Practice Characteristics Associated with Patient Engagement and Chronic Care Management Capabilities for Adults with Diabetes and/or Cardiovascular Disease (2017/2018)
| Patient Engagement Capabilities | Chronic Care Management Capabilities | ||
|---|---|---|---|
| Coefficient (Robust Standard Error) | |||
| Health Care System Characteristics | |||
| Process to Assess New Evidence | 1.36 (2.45) | 6.79** (2.35) | |
| Culture of Innovation | −1.05 (1.12) | −1.18 (1.36) | |
| Advanced Health Information Technology | 0.30 (1.15) | 2.85* (1.30) | |
| Participation in Delivery Reform | −1.67 (2.48) | −0.26 (2.56) | |
| Participation in Payment Reform | 0.83 (1.21) | −1.32 (1.21) | |
| Health Care System Standardization | −0.65 (1.19) | 1.54 (1.42) | |
| Size (Number of Physician Practices) | 1–22 | Ref. | Ref. |
| 22–68 | −3.51 (2.80) | 4.16 (3.15) | |
| 69–165 | −3.57 (3.24) | −0.39 (2.96) | |
| 166+ | −0.54 (3.82) | 1.65 (3.95) | |
| Physician Practice Characteristics | |||
| Process to Assess New Evidence | 4.44* (1.97) | 7.37*** (1.88) | |
| Culture of Innovation | 10.73*** (0.89) | 9.70*** (0.97) | |
| Advanced Health Information Technology | 3.18*** (0.87) | 5.59*** (1.08) | |
| Size (Number of Physicians) | 1–9 | Ref. | Ref. |
| 10–20 | −2.11 (2.39) | 0.40 (2.67) | |
| 21+ | −4.55 (2.80) | −3.09 (2.90) | |
| Proportion Primary Care Physicians | <33% | Ref. | Ref. |
| 33–99% | −0.74 (3.25) | −5.61 (3.88) | |
| 100% | 6.14 (4.09) | −4.05 (4.58) | |
| Medicaid Percentage | None | Ref. | Ref. |
| Low (1–29%) | 1.00 (3.55) | 6.09 (3.90) | |
| High (30%+) | 1.85 (4.02) | 5.23 (4.22) | |
| Census Region | West | Ref. | Ref. |
| South | −3.96 (3.05) | −1.93 (2.96) | |
| Northeast | −5.68 (3.99) | −8.41 (4.52) | |
| Midwest | −4.67 (3.52) | −6.97* (3.35) | |
| Constant | 44.36*** (6.05) | 63.78*** (6.19) | |
| sd(Health System) | 8.58*** (2.02) | 8.77*** (2.19) | |
| sd(Constant) | 23.83*** (0.74) | 24.25*** (0.91) | |
P < 0.001;
P < 0.01;
P < 0.05.
Source: National Survey of Healthcare Organizations and Systems (NSHOS). Sample consists of 796 physician practices nested within 247 parent health care systems.
Model fit for patient engagement strategies was better (lower AIC) in the full model (AIC=7204) compared to a model with only health care system-level variables (AIC=7351), and similar to a model with only physician practice-level variables (AIC=7189). Likewise, model fit for chronic care management capabilities was better in the full model (AIC=7460) compared to a model with only health care system-level variables (AIC=7653), and similar to a model with only physician practice-level variables (AIC=7462).
Discussion
Given limited evidence about how health care systems support physician practice adoption of disruptive innovations, this study highlights several modifiable health care system and physician practice capabilities associated with practice adoption of chronic care management processes and patient engagement strategies for adults with diabetes and/or CVD. Greater adoption of chronic care management processes compared to patient engagement strategies is consistent with diffusion of innovation theory, which highlights that innovation adoption can be facilitated when there is established practice-based evidence focused on effective implementation, scaling, and sustainment of the innovation,18 compared to innovations for which there is limited evidence about implementation. In this case, implementers of chronic care management processes may benefit from robust practice-based evidence, including PCMH and HIT implementation research.16,24,25
Our results are also consistent with past research that underscored the role of health care systems as sources of guidance for practices, but not direct implementers of care delivery innovations,17 and as a result, local leadership and frontline team acceptance are essential to implement disruptive care delivery innovations.16,28 It is possible that systems opt to devote limited resources to support chronic care management processes because evidence-based implementation strategies are well developed. Patient engagement strategies that rely on high local readiness for change and a supportive implementation climate, in contrast, may be less influenced by systems because implementation strategies are not well established.36
Consistent with hypothesis 1, system standardization was not associated with practice-level adoption of patient engagement strategies. However, contrary to hypothesis 1, there was no significant association of system standardization with practice adoption of chronic care management processes. Lack of associations may be due to the relatively high level of standardization of processes reported by systems (mean=73.6 out of 100, SD=19.8) or that the standardized items measured (e.g., physician compensation and performance measurement) were too distal to impact the adoption of these care delivery innovations.
We find partial support for hypothesis 2. Systems with more advanced HIT functions and processes in place to assess new clinical evidence had greater adoption of chronic care management processes, but not patient engagement strategies. The HIT functionalities assessed directly related to patient engagement, including providing patients the ability to access their medical records. Our results suggest that these patient-focused technical capabilities may provide a foundation to support broad implementation of chronic care management processes. While physician practice cultures oriented toward innovation adopted more patient engagement strategies and chronic care management processes, health care system culture was not associated with practice-level adoption. Cultures oriented to risk-taking might aid local practice stakeholders in overcoming uncertainty when adopting care delivery innovations without the benefit of having evidence-based implementation strategies.
As pressures to improve patient engagement continue to increase, our results suggest that local practice-level capabilities are essential to the implementation of patient-centered health care delivery innovations. Our observation of no significant association between health care system characteristics and patient engagement strategy adoption suggests that health care systems resources might be most impactful if used to nurture practice-level cultural and technical capabilities. We observed that formal training for motivational interviewing and shared decision-making was not widely available. This training gap will be important to fill, as these capabilities are difficult to implement with high fidelity without training and leadership facilitation.37,38 Health care system resources might be leveraged to provide training resources and to identify, appraise, and disseminate implementation strategies for constituent practices to deploy locally.
Limitations
Our findings should be considered in light of the study limitations. First, while motivational interviewing, shared decision-making, and shared medical appointments are core patient engagement strategies that aim to activate patients to participate in their treatment decisions, we did not assess important organizational strategies, such as inclusion of patients on advisory councils and quality improvement committees. Second, NSHOS is a single informant survey, but respondents were selected for their knowledge of internal processes and encouraged to consult with others. Third, we were unable to account for sociodemographic characteristics of the patient populations, but included Medicaid revenue to partially account for case-mix. Fourth, we did not have data to address individual physician or patient variability in the adoption of patient engagement strategies. Given high variation in the use of patient engagement strategies, future studies should examine physician-level variation in patient engagement strategies to elucidate how best to disseminate these strategies. Finally, the cross-sectional design does not allow for casual claims to be made. For example, we did not observe ownership changes, so practice capabilities could have pre-dated system ownership. Policies to advance shared decision-making after the passing of the Affordable Care Act39 may have also influenced capabilities and we could not consider these factors. Future research should examine how physician practices modify their capabilities as a result of health care system acquisition.
Conclusion
In conclusion, physician practices with cultures oriented to innovation and strong technical capabilities adopted more patient engagement strategies and chronic care management processes than practices with more limited capabilities. Health care systems with processes in place to assess clinical evidence and with more advanced HIT functions had greater practice-level adoption of chronic care management processes compared to practices with more limited capabilities. In contrast, there was no association between these capabilities and patient engagement strategies. Practice-level adoption of patient engagement strategies may be less influenced by health care systems because implementation strategies to scale and sustain shared decision-making, motivational interviewing, and shared medical appointments are less established.36 Health care systems should invest in processes to identify, test, and disseminate new evidence across their physician practices and leverage these processes to support the adoption of evidence-based and patient-centered care delivery innovations.
Supplementary Material
Takeaway Points:
This national study examines health system and physician practice capabilities associated with adoption of patient engagement strategies and chronic care management processes.
Health systems with processes to assess clinical evidence and with more advanced health information technology (IT) functions were associated with greater adoption of chronic care management processes in constituent physician practices, but not patient engagement strategies.
Physician practices with processes to assess clinical evidence, cultures oriented to innovation, and more advanced health IT functionality, adopted more patient engagement strategies and chronic care management processes.
Practice-level capabilities are essential for implementing disruptive innovations like patient engagement strategies.
Funding:
This study was supported by the Agency for Healthcare Research and Quality’s (AHRQ’s) Comparative Health System Performance Initiative under Grant # 1U19HS024075, which examines how health care delivery systems promote evidence-based practices and patient-centered outcomes research in delivering care. The statements, findings, conclusions, views, and opinions contained and expressed in this article are based in part on data obtained under license from IQVIA information services: OneKey subscription information services 2010–2017, IQVIA incorporated all rights reserved. The statements, findings, conclusions, views, and opinions contained and expressed herein are not necessarily those of IQVIA Incorporated or any of its affiliated or subsidiary entities.
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