The Effect of Implementing a Care Coordination Program on Team Dynamics and the Patient Experience

ABSTRACTObjectives: Care coordination programs are frequently implemented in the redesign of primary care systems, focused on improving patient outcomes and reducing utilization. However, redesign can be disruptive, affect patient experiences, and undermine elements in the patient-centered medical home, such as team-based care.

Study Design: Case-controlled study with difference-in-differences (DID) and cross-sectional analyses.

Methods: The phased implementation of a care coordination program permitted evaluation of a natural experiment to compare measures of patient experience and teamwork in practices with and without care coordinators. Patient experience scores were compared before and after the introduction of care coordinators, using DID analyses. Cross-sectional data were used to compare teamwork, based on the relational coordination survey, and physician-perceived barriers to coordinated care between clinics with and without care coordinators.

Results: We evaluated survey responses from 459 staff and physicians and 13,441 patients in 26 primary care practices. Practices with care coordinators did not have significantly different relational coordination scores compared with practices without care coordinators, and physicians in these practices did not report reduced barriers to coordinated care. After implementation of the program, patients in practices with care coordinators reported a more positive experience with staff over time (DID, 2.6 percentage points; P = .0009).

Conclusions: A flexible program that incorporates care coordinators into the existing care team was minimally disruptive to existing team dynamics, and the embedded care coordinators were associated with a small increase in patient ratings that reflected a more positive experience with staff.

Am J Manag Care. 2017;23(8):494-500Take-Away Points

A care coordinator program was implemented as part of primary care redesign. This study examined the intervention’s effects on patients’ experiences and team dynamics.

• Teamwork scores in practices with care coordinators were not significantly different than scores in practices without care coordinators.
• Overall patient experience with staff in practices with care coordinators improved significantly after program implementation, although the care coordinators worked with only a fraction of patients.
• Our findings suggest that embedded care coordinators improved the primary care experience for patients; they integrated themselves in the care teams without disruption of the existing team’s function.

Healthcare systems transitioning toward value-based models of healthcare delivery often focus on redesigning primary care as a means of achieving better access and quality at a lower cost.^1-3 The patient-centered medical home, a common model that aims to revamp the role of primary care, emphasizes population health and integration across the care continuum.^4,5 Coordination of care is one of the key tenets of the patient-centered medical home, and practices adopting the model frequently implement a care coordination program as part of their practice transformation. These programs, which typically empanel high-risk patients based on prior utilization or comorbidities,^6,7 can result in significant reductions in acute care utilization.^8-10

The health system for the University of California, Los Angeles (UCLA Health) implemented an innovative care coordination program as part of its primary care redesign. The intervention embeds nonlicensed care coordinators (CCs) in primary care practices to work with physicians in real time. Program details including coordinators’ backgrounds, the program’s training processes, and operations are described elsewhere.¹⁰ Although other components of the redesign focused on technology or ancillary services across all practices, the introduction of the care coordination program was the most significant and potentially disruptive change in the operations of the existing primary care system, and it was applied differentially to practices over time. The CCs focus on patients discharged from an acute care episode, high-complexity patients, and patients referred by physicians, totaling approximately 10% of patients in a primary care physicians’ panel. The primary purpose of the CCs was to improve care and reduce utilization for the most complex patients. Practices in the health system with CCs have been shown to be associated with a 20% reduction in emergency department visits compared with practices without CCs in the health system.¹⁰

However, practice redesign is disruptive, and the mixed results of primary care transformation efforts^11,12 suggest that one size does not fit all.¹³ As a result, it is important to understand how CCs and other “transformative” interventions impact patients’ experiences and the overall structure and function of the team.

Team-based care, another central tenet of the medical home, facilitates primary care’s expanded role as a medical home.^6,14-16 At a minimum, practice redesign should support the team’s ability to provide cohesive care. Relational coordination has emerged as a dominant method of measuring how various actors in a healthcare setting work together¹⁷ and focuses on the relationships between team participants fulfilling specified roles.¹⁸

Practice redesign efforts must also consider the impact on patients’ experiences as a health-related outcome. Furthermore, patient experience scores are a common feature of quality metrics used in various accountable care payment models, directly affecting the redesign’s return on investment. The scores also indirectly reflect the success of primary care redesign: patients with better experiences are more adherent to physician recommendations, more loyal to their physicians, and more engaged in their care, all desirable outcomes in value-based models of care.^19,20 Finally, publicly reported patient experience scores can affect a health system’s reputation.

In this study, we sought to expand the understanding of CC interventions by evaluating the downstream effects on patients and other members of the care team. Because this program affected only a small number of patients, we hypothesized that the overall set of patients in practices with CCs would report no change in access to care, care coordination, and their overall rating of their experience compared with patients in practices without CCs. Regarding team dynamics, we hypothesized that CCs would not change the relational coordination within a practice and that physicians in practices with CCs would perceive a lower burden of coordinating care for their patients.

METHODS

A phased implementation of the UCLA Health Care Coordinator Program within UCLA Health allowed for a natural experiment comparing practices with CCs already embedded (CC practices) with the practices that had not yet introduced CCs (non-CC practices). Because the health system continuously collects patient experience data for all practices, we used a difference-in-differences (DID) approach to compare preintervention and postintervention patient experience between the 2 cohorts. Data on relational coordination and physician-perceived barriers to care were collected only in the postintervention period and were compared between CC practices and non-CC practices.

Description of Health System and Primary Care Practices

UCLA Health is an urban academic system that had 26 primary care practices caring for adult patients at the time of the study encompassing internal medicine, family medicine, and geriatrics. Primary care practices within UCLA Health are primarily traditional community-based practices with full time physicians; 4 practices also have trainees. The first CCs were introduced into 5 practices in May 2012, and another 9 were introduced in November 2012; half of all practices had CCs by December 2012. The other half of primary care practices incorporated CCs starting in March 2014. The rollout of the primary care redesign was set up to represent the wide range of practices within the UCLA Health System: practices belonged to 1 of 4 “pods” corresponding to the management structure of the ambulatory care network. Each pod had semi-autonomous management. The first practices to receive CCs were selected by UCLA Health System leadership to encompass a representative sample from each pod and to include sites with, and without, trainees.

The CCs were embedded members of the primary care team, working with all physicians within their assigned practice, and were tasked with addressing nonmedical barriers to care. Our prior work showed that the majority of the work of the CCs related to transitions of care, including such physician-directed tasks as scheduling appointments, providing self-management support services, and monitoring and following up with patients between visits.¹⁰ As a result, a CC served as a dependable point person for a subset of patients in order to complete tasks that were typically done by a variety of receptionists and clerks, or not performed at all.

Patient experience survey. The health system used the Clinician and Group Survey by Consumer Assessment of Healthcare Providers and Systems 12-Month Survey to measure and track patient experience.²¹ The survey evaluated 6 categories of each patient’s experience, detailed in eAppendix A (eAppendices available at ajmc.com). Four categories used multiple questions to form composite measures: quality of patient—doctor interaction, access to care, care coordination, and courteous and helpful office staff (defined as clerks and receptionists). The last 2 categories covered 2 global rating questions: 1) overall rating of the doctor and 2) whether the respondent would be willing to recommend the doctor to their family and friends.

Patient experience data were split into 2 periods: the preintervention period ranged from May 2011 through February 2012 and the postintervention period ranged from May 2013 through February 2014. Because the last CC in the intervention group was introduced in December 2012, this allowed a minimum of 4 months for CCs to become established team members of their primary care practice. Two CC practices were excluded because they were in a transition period between CCs at the time of the study, and the newly hired CCs had not had time to form relationships with their colleagues.

Relational coordination and physician burden surveys. Relational coordination is a tool initially developed in the airline industry²² that was, subsequently validated in multiple healthcare settings.^18,23,24 It is defined as a mutually reinforcing web of communication and relationships carried out for the purpose of task integration.¹⁸ In primary care, higher relational coordination has been associated with higher-quality chronic care delivery,^25,26 and improvement in relational coordination predicts improvements in chronic care delivery.²⁷ The measure is computed by having respondents rate the quality of working relationships with their colleagues based on 3 relational dimensions (shared goals, shared knowledge, and mutual respect) and 4 dimensions of communication: frequency, accuracy, timeliness, and whether the communication seeks to solve problems or assign blame (see eAppendix B for details).

In order to assess physician-perceived burdens of coordinating care, we asked primary care physicians within the health system and not directly involved in this research to describe the tasks that do not require clinical training or licensure but are needed for patients to receive well-coordinated care. We overlaid these responses with tasks documented by CCs as part of their workflow to identify areas in which CCs might reduce the physician burden of care coordination. Five questions assessed physicians’ perceived burden of nonmedical care coordination tasks; each was scored on a 5-point scale where 5 was the lowest perceived burden.

The survey was pilot tested in a non—primary care practice. All staff and physicians in non-CC practices were instructed to fill out the survey between January 2014 and April 2014 (prior to adding a CC). Staff and physicians in CC practices completed their surveys between May 2014 and August 2014. The project received institutional review board exemption as a quality improvement initiative.

Statistical Methods

For the patient experience survey data, χ² tests were used to evaluate differences in categorical variables between patients in the CC practices and non-CC practices. The Wilcoxon Rank Sum test was used to evaluate differences in the number of staff, number of MDs, and percent of full-time physicians between CC and non-CC practices. Because some physicians did not practice full time, potentially affecting their coordination with other team members, we determined the mean “percent clinical time” for physicians in a practice. This was defined as the sum of clinical half-days worked by all physicians in the practice divided by a total possible 10 clinical half-days per week (eg, if a practice had 2 physicians and 1 worked 3 half-days and the other worked 8 half-days, the practice’s percent clinical time would be 11/20, or 55%).

The pre- and post differences in the 6 patient experience outcomes between the CC practices and non-CC practices were compared using a linear mixed-effects model with fixed effects for the presence of a CC, time period (pre- or post), and CC by time interaction, and a random clinic effect. Models were adjusted by age group, race/ethnicity, gender, self-health rating, and education level; whether the clinic was a training site; total number of clinic staff; and average percent of full-time physicians at each clinic. Estimates were produced using modeled contrasts.

For the provider surveys, χ² and Fisher exact tests were used to evaluate differences in the respondent characteristics between CC practices and non-CC practices, as appropriate. Based on summary statistics, physician age was collapsed into 3 categories (aged <35 years, 35-54 years, or >55 years) and physician work experience was collapsed into 3 categories (<5 years, 5-10 years, >10 years).

A composite measure of relational coordination was computed as the mean of the individual relational coordination survey questions. Composite relational coordination was compared between CC practices and non-CC practices using a linear mixed-effects model with a practice-level random effect and a fixed effect for the presence of a CC. Models were adjusted by job role, gender, age, experience working at the site, and total number of employees (including physicians) at that site.

Differences in scores of the barriers to coordinated care between the CC practices and non-CC practices were compared using a linear mixed-effects model, with a clinic random effect and a clinic having a CC as the fixed effect. Models were adjusted for physician age, gender, number of years working at the clinic, number of years of total experience; number of doctors at the clinic, total staff at the clinic, and average percent of physician clinical time. SAS version 9.4 (SAS Institute; Cary, North Carolina) was used for all statistical analyses.

RESULTS

Patient, Physician, and Practice Characteristics

Of 13,441 patient experience surveys, 40% were from patients surveyed during the baseline (preintervention) period, and the remainder were after the introduction of CCs (postintervention period) (Table 1). Out of the entire group, most were female (64%) and predominantly white (66%), and 12% reported a Hispanic or Latino ethnicity. Patient characteristics between the pre- and postintervention cohorts did not differ significantly in self-reported overall health rating, or proportion with hypertension (43%), diabetes (13%), or depression (19%). Several variables (age, gender, race, and education) were statistically different between these relatively large cohorts, but absolute differences between the temporal cohorts were small.

The 12 CC practices and the 12 non-CC practices were similar across the variables examined, with the exception of the number of physicians (Table 2). Physicians were about equally split by gender, age range, and work experience, although experience at their practice site differed between cohorts (Table 2).

Patient experience. After adjusting patient experience scores for patient- and clinic-level factors, there was a decline in all 6 scales of the patient experience for the non-CC practices between the preintervention and postintervention periods, whereas change over time was mixed in the CC practices. Although changes in scores were small in absolute terms, some were statistically significant. For example, among non-CC practices, patient ratings of access decreased by 1.6 points (P = .03) and coordinated care decreased by 2.7 points (P = .002); for the CC practices, ratings of coordinated care decreased by 2.2 points (P = .01) (Table 3). DID analysis was not statistically significant. Patient perception of staff, which asks patients about experience with clerks and receptionists, increased by 1.9 points in CC practices (P = .0005), and there was a statistically significant interaction between CC and time, with a net adjusted difference of 2.6 percentage points regarding experience with clerks and receptionists favoring CC practices compared with non-CC practices (P <.001).

Relational coordination. Response rates were 86% for nonphysicians (327 of 382) and 75% for physicians (132 of 177), for an overall response rate of 82%. Relational coordination scores, measured on a 1-to-5 scale, ranged from 3.8 in the lowest-scoring practice to 4.5 in the highest-scoring practice (mean = 4.1; standard deviation [SD] = 0.20). After adjusting for respondent- and clinic-level factors, relational coordination was not significantly different in practices with a CC compared with those without a CC (mean scores = 4.06 and 4.00, respectively; P = .39). Subset analysis of physician responses using the same method, and further adjusting for years of work experience, found that physicians in practices with CCs reported a small but significantly higher relational coordination (difference = 0.27; P = .01).

Nonmedical care coordination tasks. Physicians working with CCs did not report a different level of burden concerning tasks associated with coordinating care compared with physicians without CCs (Table 4). Physicians reported the greatest burden being filling out forms, and 4 of the 5 measures had group estimates below 3.0 for both CC- and non-CC practices (Table 4).

DISCUSSION

This study evaluated the effects of a care coordination program beyond its effect on utilization. In addition to reducing acute care utilization, the CC intervention we studied also preserved patient experience amid a downward trend within the health system. The lack of statistically significant association in relational coordination with the addition of CCs suggests that intercalation of a CC into primary care practices does not produce a disruptive effect on teamwork. Practice redesign is a long, difficult process, and these secondary outcomes ensured attention to the broader impact of the transformation beyond utilization.

The lack of a statistically significant change in relational coordination may have reflected the design of the UCLA Health Care Coordinator Program as a flexible intervention to improve the care of the most complex patients. Although one may have expected improvement in relational coordination with the addition of the CC, interrupted teamwork was also possible. Disruptions to workflow and team dynamics can be barriers to primary care practice transformation.^28,29 These findings suggest that the integration of the CCs into the existing primary care team was minimally disruptive to the existing team’s function. Furthermore, a baseline measure of relational coordination can serve as a benchmark to monitor continuous efforts to improve team-based care, a frequently cited goal of the medical home, but a component rarely measured directly.

The positive association between CC practices and patient ratings of experience with office staff has several possible explanations. First, patients may have perceived the CCs as part of the staff in their medical home. The integration of the CCs in the medical home team was an intentional goal of the program’s design, and built on prior research supporting the effectiveness of embedded CCs.⁸ Second, CCs worked on nonmedical tasks for patients, the completion of which was often communicated to patients by clerks and receptionists, who remained the patient’s touchpoint to the practice. Finally, the CCs focused on complex nonmedical tasks that may have otherwise fallen to the clerks and receptionists, thereby unburdening them to provide a better patient experience for the full complement of their patients. These hypotheses require further evaluation to understand the link between the observed improvement in patient ratings of staff and the implementation of CCs.

Overall, in the studied health system, patient-reported access and care coordination decreased by a small, but statistically significant, amount over time. The cause of this trend is unclear, but may have reflected difficulties experienced at the time in which the health system implemented an electronic health record system,, which occurred during the observed period.³⁰

Finally, the low scores in all measures of physician-perceived burden of care coordination underscored the well-established difficulties in the daily work of primary care physicians.^31-34 This survey did not find a reduction in perceived barriers in practices with CCs compared with those without, but CCs only worked with a minority of each physician’s patient panel, and these questions may not have adequately captured the impact of CCs on physician practice patterns. More research is needed to identify practice design features that improve physician-perceived burdens of care coordination.

Limitations

This study has several limitations. Only 1 health system was evaluated, although 12 practices had CCs and 12 practices did not. The relational coordination and primary care burdens surveys were conducted only in a cross-sectional fashion, limiting inference of causality, but generating hypotheses for future research (eg, potential interactions between practice size and adding a CC). Furthermore, the power to detect changes in relational coordination (beta = 0.8 to detect a difference of 0.07 points in mean relational coordination at alpha = 0.05) and the physician-perceived burden of care coordination (beta = 0.8 to detect a difference of 0.50 points for all of the questions at alpha = 0.05) limited our ability to state with certainty that teamwork or physician-perceived barriers of care coordination were not improved in the CC practices compared with non-CC practices.

CONCLUSIONS

Inertia and the barriers to change too often stymie primary care redesign. On the other hand, piecemeal solutions to individual problems without regard to the preexisting structure and function of practice are not sustainable, and can ultimately result in a chimeric system that is confusing for patients, complicated for physicians and staff, and costly to the system as a whole.³⁵ Although this care coordination program primarily sought to reduce utilization, primary care redesign must maintain a broader vision of population health through team-based care. The results of this study suggest that the flexible design of this program is minimally disruptive to overall teamwork and modestly improved the patient experience with staff for patients in CC practices. The findings support a sustainable transformation of primary care and an empirical benchmark for measuring improvement into the future.Author Affiliations: David Geffen School of Medicine, UCLA (PD, RC, CHT, HW, SS, NW); Los Angeles, CA; UCLA Fielding School of Public Health (RS) Los Angeles, CA; Center for Health Policy and the Center for Primary Care and Outcomes Research, Stanford University School of Medicine (KM); Stanford, CA.

Source of Funding: Dr Di Capua received support from HRSA Institutional National Research Service Award (NRSA) T32-HP-19001.

Author Disclosures: Drs Wenger, Clarke, and Skootsky were employees of the UCLA Medical Group during the time of this study. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (RC, PD, HW, SS, RS, NW); acquisition of data (RC, PD, RS); analysis and interpretation of data (RC, PD, HW, KM, CHT, SS, NW); drafting of the manuscript (PD RS, NW); critical revision of the manuscript for important intellectual content (RC, PD, KM, CHT, SS); statistical analysis (PD); provision of patients or study materials (PD, HW, CHT); administrative, technical, or logistic support (PD, KM, RS); supervision (SS).

Address Correspondence to: Paul Di Capua, MD, MBA, MSHPM, 1500 San Remo Ave, Ste 360, Coral Gables, FL 33143. E-mail: dr.dicapua@gmail.com.REFERENCES

1. Starfield B, Shi L, Macinko J. Contribution of primary care to health systems and health. Milbank Quarterly. 2005;83(3):457-502. doi:10.1111/j.1468-0009.2005.00409.x.

2. Homer CJ, Baron RJ. How to scale up primary care transformation: what we know and what we need to know? J Gen Int Med. 2010;25(6):625-629. doi:10.1007/s11606-010-1260-x.

3. Grumbach K, Bodenheimer T. A primary care home for Americans: putting the house in order. JAMA. 2002;288(7):889-893.

4. Stange KC, Nutting PA, Miller WL, et al. Defining and measuring the patient-centered medical home. J Gen Int Med. 2010;25(6):601-612. doi:10.1007/s11606-010-1291-3.

5. American Academy of Family Physicians, American Academy of Pediatrics, American College of Physicians, American Osteopathic Association. Joint principles of the patient-centered medical home. American Academy of Family Physicians website. http://www.aafp.org/dam/AAFP/documents/practice_management/pcmh/initiatives/PCMHJoint.pdf. Published March 2007. Accessed July 12, 2017.

6. Friedman A, Hahn KA, Etz R, et al. A typology of primary care workforce innovations in the United States since 2000. Med Care. 2014;52(2):101-111. doi:10.1097/MLR.0000000000000043.

7. Powers BW, Chaguturu SK, Ferris TG. Optimizing high-risk care management. JAMA. 2015;313(8):795-796. doi: 10.1001/jama.2014.18171.

8. Peikes D, Chen A, Schore J, Brown R. Effects of care coordination on hospitalization, quality of care, and health care expenditures among Medicare beneficiaries: 15 randomized trials. JAMA. 2009;301(6):603-618. doi: 10.1001/jama.2009.126.

9. Huntley A, Lasserson D, Wye L, et al. Which features of primary care affect unscheduled secondary care use? a systematic review. BMJ Open. 2014;4(5):e004746. doi: 10.1136/bmjopen-2013-004746.

10. Clarke RM, Bharmal N, Di Capua P, et al. Innovative approach to patient-centered care coordination in primary care practices. Am J Manag Care. 2015;21(9):623-630.

11. Nelson, L. Lessons from Medicare’s demonstration projects on disease management and care coordination. Congressional Budget Office website. https://www.cbo.gov/sites/default/files/112th-congress-2011-2012/workingpaper/WP2012-01_Nelson_Medicare_DMCC_Demonstrations_1.pdf. Published January 2012. Accessed July 12, 2017.

12. Friedberg MW, Schneider EC, Rosenthal MB, Volpp KG, Werner RM. Association between participation in a multipayer medical home intervention and changes in quality, utilization, and costs of care. JAMA. 2014;311(8):815-825. doi: 10.1001/jama.2014.353.

13. Schwenk TL. The patient-centered medical home: one size does not fit all. JAMA. 2014;311(8):802-803. doi: 10.1001/jama.2014.352.

14. Altschuler J, Margolius D, Bodenheimer T, Grumbach K. Estimating a reasonable patient panel size for primary care physicians with team-based task delegation. Ann Fam Med. 2012;10(5):396-400. doi: 10.1370/afm.1400.

15. Shipman SA, Sinsky CA. Expanding primary care capacity by reducing waste and improving the efficiency of care. Health Aff (Millwood).2013;32(11):1990-1997. doi: 10.1377/hlthaff.2013.0539.

16. Ghorob A, Bodenheimer T. Sharing the care to improve access to primary care. N Engl J Med. 2012;366(21):1955-1957. doi: 10.1056/NEJMp1202775.

17. Valentine MA, Nembhard IM, Edmondson AC. Measuring teamwork in health care settings: a review of survey instruments. Med Care. 2015;53(4):e16-30. doi: 10.1097/MLR.0b013e31827feef6.

18. Gittell JH. Coordinating mechanisms in care provider groups: relational coordination as mediator and input uncertainty as a moderator of performance effects. Management Science. 2002;48(11):1408-1426. doi: 10.1287/mnsc.48.11.1408.268.

19. Safran DG, Montgomery JE, Chang H, Murphy J, Rogers WH. Switching doctors: predictors of voluntary disenrollment from a primary physician’s practice. J Fam Pract. 2001;50(2):130-136.

20. Zolnierek KBH, Dimatteo MR. Physician communication and patient adherence to treatment: a meta-analysis. Med Care. 2009;47(8):826-834. doi: 10.1097/MLR.0b013e31819a5acc.

21. Dyer N, Sorra JS, Smith SA, Cleary PD, Hays RD. Psychometric properties of the consumer assessment of healthcare providers and systems (CAHPS) clinician and group adult visit survey. Med Care. 2012;5(S28-S34). doi: 10.1097/MLR.0b013e31826cbc0d.

22. Gittell JH, Fairfiled KM, Bierbaum B, et al. Organizing work to support relational coordination. The Int J Hum Resour Man. 2000;11(3):517-539. doi: 10.1080/095851900339747.

23. Gittell JH, Fairfield KM, Bierbaum B, et al. Impact of relational coordination on quality of care, postoperative pain and functioning, and length of stay: a nine-hospital study of surgical patients. Med Care. 2000;38(8):807-819.

24. Gittell JH, Logan C. The impact of relational coordination on performance, and how organizations shape its development: a review of the evidence. Brandeis University working paper. In press.

25. Cramm JM, Nieboer AP. Relational coordination promotes quality of chronic care delivery in Dutch disease-management programs. Health Care Manage Rev. 2012;37(4):301-309. doi: 10.1097/HMR.0b013e3182355ea4.

26. Noel PH, Lanham HJ, Palmer RF, Leykum LK, Parchman ML. The importance of relational coordination and reciprocal learning for chronic illness care within primary care teams. Health Care Manage Rev. 2013;38(1):20-28. doi: 10.1097/HMR.0b013e3182497262.

27. Cramm JM, Nieboer AP. In the Netherlands, rich interaction among professionals conducting disease management led to better chronic care. Health Aff (Millwood). 2012;31(11):2493-2500. doi:10.1377/hlthaff.2011.1304.

28. Grace SM, Rich J, Chin W, Rodriguez HP. Flexible implementation and integration of new team members to support patient-centered care. Healthc (Amst.) 2014;2(2):145-151. doi: 10.1016/j.hjdsi.2014.02.003.

29. Crabtree BF, Nutting PA, Miller WL, et al. Primary care practice transformation is hard work: insights from a 15-year developmental program of research. Med Care. 2011;49(suppl):S28-S35. doi: 10.1097/MLR.0b013e3181cad65c.

30. Irani JS, Middleton JL, Marfatia R, Omana ET, D’Amico F. The use of electronic health records in the exam room and patient satisfaction: a systematic review. J Am Board Fam Med. 2009;22(5):553-562. doi: 10.3122/jabfm.2009.05.080259.

31. Dyrbye LN, Shanafelt TD. Physician burnout: a potential threat to successful health care reform. JAMA. 2011;305(19):2009-2010. doi: 10.1001/jama.2011.652.

32. Shanafelt TD, Boone S, Tan L, et al. Burnout and satisfaction with work-life balance among US physicians relative to the general US population. Arch Int Med. 2012;172(18):1377-1385. doi:10.1001/archinternmed.2012.3199.

33. Sinsky CA, Willard-Grace R, Schutzbank AM, Sinsky TA, Margolius D, Bodenheimer T. In search of joy in practice: a report of 23 high-functioning primary care practices. Ann Fam Med. 2013;11(3):272-278. doi:10.1370/afm.1531.

34. Chen MA, Hollenberg JP, Michelen W, Peterson JC, Casalino LP. Patient care outside of office visits: a primary care physician. J Gen Intern Med. 2011;26(1):58-63. doi: 10.1007/s11606-010-1494-7.

35. Hoffman A, Emanuel EJ. Reengineering US health care. JAMA. 2013;309(7):661-662. doi:10.1001/jama.2012.214571.

Download PDF: The Effect of Implementing a Care Coordination Program on Team Dynamics and the Patient Experience