Patient experience, such as a provider’s communication with patients in health care organizations, has become a commonly used indicator to measure the performance of health care providers and organizations. Studies have suggested that better patient experience is associated with higher patient adherence, better clinical outcomes, and better patient safety (Price et al., 2014). Furthermore, patient experience has been adopted as a key component of many value-based reimbursement programs. As of 2013, Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores also constitute 30% of incentive-based payments from Medicare’s Value-Based Purchasing Program (Blumenthal & Jena, 2013).
Incentives for the creation of accountable care organizations (ACOs) were included in the 2010 Patient Protection and Affordable Care Act, with the aim of improving quality while controlling costs of health care through the formation of coordinated health delivery networks (Berwick, 2011). An ACO is a group of physicians, hospitals, and other health care providers or organizations who work together to deliver coordinated health care to patients (Fisher & Shortell, 2010). Centers for Medicare & Medicaid Services (CMS) implemented two ACO programs—the Pioneer ACO program, which started in January 2012 with 32 ACOs, nine of which were still in operation by 2016, and the Shared Savings Program (SSP), which started in April of the same year and has approximately 400 ACOs as of 2016. ACOs are rewarded financially if, among other things, they demonstrate they satisfy the cost benchmarks and quality standards set by CMS. Given the rapid implementation of ACOs across the country, there is a growing body of literature examining the effects of ACOs on patient experience, cost, quality, and utilization of health care. Early studies demonstrated positive changes in patient experience among Medicare ACOs. For example, Pioneer and SSP ACO beneficiaries reported that they have more timely access to care, their primary care physicians were better informed about specialty care, and they have a greater utilization of preventive services for beneficiaries with diabetes as compared with non-ACO beneficiaries (McWilliams, Landon, Chernew, & Zaslavsky, 2014). Pioneer ACO beneficiaries also reported higher mean scores for timely care and for clinician communication (Nyweide et al., 2015).
Previous evidence found that hospitals have been one of the key components of ACOs. Yeager et al. identified 431 hospitals that were participating in the 252 Medicare ACOs established as of January 2013 (Yeager, Zhang, & Diana, 2015). Another study found that 20% of U.S. hospitals were part of a Medicare, Medicaid, or a commercial ACO by 2014 (Colla, Lewis, Tierney, & Muhlestein, 2016). A more recent study by Bazzoli and colleagues developed a taxonomy with five cluster solutions for the SSP and Pioneer ACO hospitals separately, and they found that health information technology and physician linkages are particularly important features in ACO hospitals (Bazzoli, Harless, & Chukmaitov, 2017).
The purpose of this study is to examine the association between hospital ACO participation and patient experience. Specifically, we use panel data collected from the HCAHPS survey, the American Hospital Association (AHA) Annual Survey of Hospitals, the 2013 AHA Survey of Care Systems and Payment, and primary data on hospital ACO participation to evaluate the impact of ACO involvement on patient experience scores. Findings of this study have the potential to provide insight regarding the impact of the ACO model on patient experience for policymakers and health care leaders considering ACO participation.
Organizational theorists have been concerned with coordination since Henri Fayol first proposed his principles of administrative theory (Scott & Davis, 2007). In fact, coordination is a central aspect of contingency theory. Contingency theory proposes that there are major connections between an organization’s technology and structure, including, among other things, that the greater the technical interdependence present, the more resources must be allocated to coordination activities (Scott & Davis, 2007). Contingency theory proposes that the better the fit between structure, technology, and the environment, the better the organization’s performance will be. Thompson described three types of technical interdependence in increasing levels of complexity: pooled, sequential, and reciprocal (Thompson, 1967).
Although hospitals are generally considered to be autonomous professional organizations, requiring all three levels of interdependence, and where physicians have a high degree of discretion, it is also well recognized that physicians have lost a certain amount of power and legitimacy and are therefore increasingly subject to corporate and managerial control (Robinson, 1999). The ACO program is the latest policy effort to encourage improvements in care coordination based on the contingency theory proposition that structure influences performance. Specifically, the ACO program is designed to reward providers that are better able to coordinate care provision and improve performance on both cost and quality measures.
Health care providers and organizations have been the subject of much investigation around the benefits of increased care coordination (Argote, 1982 ; Young et al., 1998). Continuity of care is often used interchangeably with care coordination (Saultz, 2003 ; Shortell, 1976), but although there are certainly subtle differences, continuity is fundamentally about the individual patient experience of care over time. Furthermore, continuity can be divided into three types: informational, managerial, and relationship. The first two are classically understood aspects of care coordination, that is, the ability to share information across providers, contexts, and events and the ability to manage providers that may inadvertently work across purposes so that they are instead acting in a complementary fashion. The third type of continuity is relationship continuity, which speaks to the establishment of an ongoing therapeutic relationship between the patient and his or her care providers. In many ways, ACOs can be viewed as a structural response that is aimed to improve care coordination across provider settings. Thus, when patients experience improved continuity of care or care coordination, it is reasonable to assume that their overall experience of care should also improve.
Inpatient spending is an essential focus of the Medicare program to reduce cost growth. It is widely recognized that considerable waste and inefficiency exist within inpatient settings (Berwick & Hackbarth, 2012). Previous studies reported ACOs are making efforts to improve care management in hospitals to eliminate unnecessary services and generate savings. For example, some ACOs have strengthened infection control to reduce hospital stays (Silow-Carroll & Edwards, 2013). Furthermore, for high-risk patients who may incur higher Medicare spending, ACOs are known to assign them care managers to coordinate care delivery and manage medications (Kroch et al., 2012 ; Silow-Carroll & Edwards, 2013). These care managers could fully access patients’ medical information, which help them communicate with patients effectively and provide timely support according to patients’ needs. Therefore, we expect that communication with care providers and communication about medications would improve in hospitals participating in ACOs compared to those that are not. This overall focus on improved communication and quality in general is expected to result in improved responsiveness of hospital staff as well.
Hospital readmissions are also associated with increased Medicare costs (Kocher & Adashi, 2011). Reducing hospital readmissions through improved care coordination represents an opportunity for ACOs to meet the cost benchmark. In addition, risk standardized all condition readmission measure is one of the 33 quality metrics of the Pioneer and SSP ACO programs. Previous studies found that ACOs are conducting predischarge assessment and patient education before discharge, providing discharge instructions to patients, and making postdischarge follow-ups to reduce or prevent avoidable readmissions (Lewis, Schoenherr, Fraze, & Cunningham, 2016 ; Silow-Carroll & Edwards, 2013). These efforts provide better support for patients before and after they are discharged from hospitals and help to establish an ongoing therapeutic relationship between the patients and providers. Therefore, we expect discharge information to be improved in hospitals that are participating in ACOs compared to those that are not.
ACOs are making important progress to engage patients and their family in care delivery (Shortell et al., 2015). Engaging patients and their families within the ACO network can help ACO providers coordinate care delivery through the continuum of care, creating more opportunities to adopt interventions at the point of care to improve quality and control costs. Previous studies suggest that ACOs improve patient and family engagement through improved patient–provider communication. For example, good communication with patients would help providers understand their real needs and deliver patient-centered health care (Levinson, Lesser, & Epstein, 2010). In addition, ACOs are involving patients and families in making clinical decisions (Kroch et al., 2012 ; Silow-Carroll & Edwards, 2013). This shared decision-making requires that providers empower patients, explain treatment options, and understand patient preferences through effective communications (Stiggelbout et al., 2012). Therefore, patients’ experiences with provider communication could be improved through ACO participation.
The Pioneer ACO model and the SSP ACO model differ in some ways. Overall, the Pioneer ACO program was designed for health care organizations and providers that are already experienced in coordinating care for patients across care settings, whereas the SSP ACO model has no explicit requirement that providers and organizations have prior experience (Boyarsky & Parke, 2012). In addition, these two models have differences in the minimum number of beneficiaries, payment arrangement, and risk adjustment, among other things (Boyarsky & Parke, 2012). Health care providers and organizations may have different responses to these two models, which may have different implications for patient experience. Therefore, we test hospitals participating in Pioneer ACOs and SSP ACOs separately.
Overview of the Study
This study examines the impact of hospitals’ participation in Medicare ACOs on inpatient experience between 2010 and 2015. We include hospitals participating in the Pioneer ACOs established in January 2012 and the SSP ACOs established in 2012–2015. We matched hospitals’ ACO participation status with the corresponding year’s HCAHPS data.
ACO Hospital Identification
We used three sources to identify hospitals participating in ACOs. Hospital participating in Pioneer ACOs and SSP ACOs of 2012 and 2013 were identified in a previous study (Yeager et al., 2015). Specifically, we first identified all Medicare ACOs established in 2012 and 2013 using fact sheets that were publicly available on CMS’s website. Second, because these fact sheets did not specify ACO composition, we examined ACO websites to identify participating hospitals within each ACO. This review was conducted throughout December of 2013 and early January of 2014. Five ACOs did not have websites during the data collocation period, so we contacted them directly through telephone or e-mail to inquire about their participating hospital(s). Third, to verify the list of ACO hospitals generated in Step 1, we cross-referenced the list with ACO participant taxpayer identification numbers and names available in an additional document released by CMS (CMS, 2013 ; Yeager et al., 2015).
Given the possibility that ACOs may not update their list of participants regularly, we used the 2013 AHA Survey of Care Systems and Payment to supplement the identification of ACO hospitals. This survey covers hospitals’ involvement in various payment (e.g., bundled payment, global capitation) and delivery models (e.g., ACO). For the ACO model, hospitals reported whether they participated in ACOs, the name of the ACO, and the types of ACOs they are participating in (i.e., Medicare, Medicaid, or commercial) in 2013 and previous years. We used this information to update our findings in the first stage. Hospitals participating in 2014 and 2015 SSP ACOs were identified using the SSP ACO participant lists from CMS. We cross-referenced the names and locations of ACO participants in these lists with the name and locations in the AHA annual survey.
Patient Experience and Hospital Characteristics
We matched two secondary data sets with the data on ACO hospitals. Patient experience data are from the Hospital Compare website (CMS, 2014). Ten patient experience measures extracted from the HCAHPS survey are publicly available from the Hospital Compare website. HCAHPS is updated quarterly. Each quarter’s release presents the average scores across values updated by that quarter and the previous three quarters. In this study, we used the data released in the fourth quarter of each year from 2011 to 2016, providing hospitals’ average patient experience scores across the four quarters of the years 2010–2015. These data represent hospitals’ performance 2 years before the Pioneer ACO program was initiated and 1 year after the third wave of the Medicare SSP started. Finally, we obtained data on hospitals’ general organizational characteristics from the AHA Annual Survey from 2010 to 2015.
We considered all hospitals included in the Hospital Compare data set for this study. The total number of hospitals contained in the Hospital Compare data set varies by releases, from 4,439 at minimum (fourth quarter of 2011) to 4,818 at maximum (fourth quarter of 2016). We excluded hospitals with missing values on any patient experience measures and those that were not included in the AHA Annual Survey. We also excluded federal hospitals and hospitals in Puerto Rico, Guam, and the Virgin Islands. Therefore, our balanced analytic sample comprised 3,462 hospitals with 20,772 hospital-year observations.
Given the possibility that high-quality hospitals may not have room for further improvement and low-quality hospitals could have more opportunities for improvement in patient experience, we implemented a subgroup analysis. We grouped hospitals into the bottom tertile, middle tertile, and the top tertile based on each patient experience measure in 2010. We then examined the effects of ACO participation on patient experience for each subgroup.
The independent variable of interest is hospital ACO participation in each year (2012–2015). We used a categorical variable to indicate whether a hospital participated in a Pioneer ACO or an SSP ACO or did not participate in any ACO.
The dependent variables of interest are 10 patient experience measures, including communication with nurses, communication with doctors, responsiveness of hospital staff, pain management, communication about medications, discharge information, cleanliness of hospital environment, quietness of hospital environment, overall hospital rating, and a measure of the patient’s intention to recommend the hospital. The HCAHPS survey generally uses three categories for each variable. We used the percentage of patients who ranked their experience in the highest category for that variable as the indicator of experience score. For example, when asked about their experience with communication with doctors, patients of a given hospital will choose one item from “doctor always communicated well,” “doctors usually communicated well,” and “doctors sometimes or never communicated well.” In this case, the percentage of patients who chose “doctor always communicated well” was treated as the experience score about communication with doctors and used as the dependent variable of interest. Patient experience scores were scaled from 0 to 100. We focused on the percentage of the highest category for two reasons. First, previous studies have measured patient experience this way using the HCAHPS data (Kazley, Diana, Ford, & Menachemi, 2012). Using the same method for the outcome will make the results more comparable to other studies testing similar hypotheses (e.g., Hospital Value-Based Purchasing and patient experience). Second, CMS evaluates performance of hospitals using this method, such as the Hospital Value-Based Purchasing program. Therefore, it makes more sense to examine hospitals’ improvement for the highest categories.
We controlled for several hospital-level organizational attributes in the analyses because they have been associated with patient experience or some other hospital performance metrics. Specifically, we used the number of hospital staffed beds, teaching status, health care system membership, hospital ownership, electronic health record (EHR) implementation, and proportion of Medicaid discharges (Finkelstein, Singh, Silvers, Neuhauser, & Rosenthal, 1998 ; Kazley et al., 2012 ; Mark, Harless, McCue, & Xu, 2004). Our econometric model only captures the impacts of time-variant factors. For some time-invariant factors frequently used in other analyses, including rural or urban location, geographical location, and hospital type, we do not control for them in the multivariate analyses. We did use these variables for descriptive analysis.
Descriptive statistics are presented along with bivariate findings of the relationship between patient experience and ACO participation. We were concerned that some unobservable factors, such as leadership and culture, are associated with both ACO participation and patient experience. To account for this, we implemented hospital-level fixed-effects models to control for time-invariant endogeneity and to examine the effects of ACO participation on patient experience. Specifically, we estimate:
where i refers to the hospital and t refers to the year of the measure. The term acoit indicates hospital i’s ACO participation status at year t; λi represents the hospital fixed effects; tt is the year fixed effects; Xit is a vector of time-varying covariates, including number of hospital staffed beds, teaching status, health care system membership, hospital ownership, EHR implementation, and proportion of Medicaid discharges; and εit is the error term. As we were concerned that hospitals within a single state may face similar regulatory climates, we clustered our standard errors at the state level. All analyses were conducted in STATA Version 13, and statistical significance was considered at the alpha level of p < .05, p < .01, and p < .001.
We conducted two sensitivity analyses. First, we used logit link function and probit link function with generalized linear model to estimate the association between ACO participation and patient experience. Second, we performed propensity score matching and conducted a difference-in-difference analysis with the matched sample. Findings from these models are similar to the linear probability model.
We identified 615 hospitals that ever participated in the Medicare ACOs established as of January 2015 among our analytic sample. Specifically, 122 (19.84%) hospitals were involved in the Pioneer ACOs, and 495 (80.16%) joined SSP ACOs. Two hospitals transferred from Pioneer ACOs to SSP ACOs. There were 24 hospitals in 2014 and 32 additional hospitals in 2015 that dropped from the Pioneer ACO program. We used the 2010 AHA Annual Survey to compare the characteristics of ACO hospitals with non-ACO hospitals (Table 1).
Compared with non-ACO hospitals, more ACO hospitals are affiliated with a medical school and have Council of Teaching Hospitals and Health Systems membership. ACO hospitals are more likely to be nongovernment, not-for-profit hospitals. Hospitals participating in ACOs are more likely to belong to a centralized health care system. ACO hospitals are more likely to operate in urban areas and to be in the northeast. In addition, ACO hospitals are larger in terms of the number of staffed beds. Finally, more ACO hospitals have fully implemented their EHR systems than non-ACO-affiliated hospitals.
Table 2 presents the patient experience scores by hospital ACO participation status based on patient experience measures in 2015. Results indicate that non-ACO hospitals had higher scores in communication with doctors and responsiveness of hospital staff. In addition, ACO hospitals had significantly lower scores in cleanliness of hospital environment and quietness of hospital environment. The ACO hospitals did better in providing discharge information, and more patients from ACO hospitals would like to recommend these hospitals. There was no difference in communication with nurses, pain management, and overall hospital rating between ACO and non-ACO hospitals.
Multivariate Findings and Subgroup Analyses
Table 3 presents the multivariate relationship between hospital ACO participation and the patient experience measures including all the hospitals. We found that the Pioneer ACO participation was significantly associated with improved score in nursing communication (β = 0.53, p < .05) and doctor communication (β = 0.72, p < .05). We found no association between the Pioneer ACO participation and other patient experience measures. The SSP ACO participation had no effects on any patient experience measures.
Table 4 presents the subgroup analyses. For hospitals in the bottom tertile, Pioneer ACO participation and SSP ACO participation had no association with patient experience. For hospitals in the middle tertile, we found Pioneer ACO participation had positive effects on discharge information (β = 0.68, p < .01) and recommendation of the hospital (β = 1.32, p < .05). SSP ACO participation had no association with patient experience. For hospitals in the top tertile, Pioneer ACO participation was positively associated with responsiveness of hospital staff (β = 1.69, p < .01), pain management (β = 1.11, p < .001), medication communication (β = 1.05, p < .05), and recommendation of the hospital (β = 0.99, p < .01).
This study provides an evaluation on whether hospitals participating in Medicare ACOs (i.e., Pioneer ACOs and SSP ACOs) are likely to provide better health care, as measured by patient experience scores, compared to those of nonparticipants. In general, hospitals participating in Pioneer ACOs had significantly improved scores on nursing communication and doctor communication. SSP ACO participation did not show significant improvements in any measure of patient experience. However, the subgroup analyses indicated that ACO hospitals in the bottom third of baseline experience scores had no significant changes on their patient experience. On the other hand, ACO participation was associated with higher patient experience for hospitals in the middle and top thirds. These findings are consistent with previous studies using individual physician or physician group data, which indicated that participation in an ACO improves at least some aspects of the patient experience (McWilliams et al., 2014 ; Nyweide et al., 2015).
One plausible explanation for these results is that higher-quality hospitals have more experience with care coordination, case management, or patient engagement, which are essential to the success of ACOs (Diana, Walker, Mora, & Zhang, 2015 ; Silow-Carroll & Edwards, 2013). This may explain in part why we find Pioneer ACOs to have improved scores on provider communication measures, that is, hospitals participating in Pioneer ACOs are more likely to have more experience in these areas. By participating in an ACO, individual physicians, physician groups, hospitals, and other health care providers are supposed to develop partnership skills, alliance-building skills, and other skills that are necessary to coordinate care delivery effectively (Shortell, 2013). However, achieving care coordination appears to remain a challenge for many providers (Barnes, Unruh, Chukmaitov, & van Ginneken, 2014). Historically high-quality hospitals are likely experienced in care management and quality improvement, providing team-based care, and coordinating health care with other providers. Given the challenges providers face after joining an ACO, higher-quality hospitals could be more readily adapted to the way that an ACO works and achieve even better patient experience, especially for those metrics where ACOs are tested (e.g., getting timely care, appointments, and information). On the other hand, hospitals with low initial quality may face challenges in developing care coordination capabilities when participating in an ACO. Patient experience, in this case, may be degraded if providers are struggling with care coordination and other elements required by the ACO model (e.g., cost control).
Our results indicate that hospitals participating in the Medicare ACO program largely focus on improvement in discharge processes, providing timely patient support and care management. These findings are consistent with previous studies indicating ACOs’ major efforts for cost control and quality improvement. Readmissions among Medicare beneficiaries are prevalent and costly (Jencks, Williams, & Coleman, 2009). However, a considerable number of readmissions are preventable though appropriate predischarge and postdischarge interventions (Kripalani, Theobald, Anctil, & Vasilevskis, 2014). ACOs have adopted various strategies to improve health delivery in hospitals to avoid unnecessary readmissions, including comprehensive discharge planning, patient education, medication reconciliation, and appointment scheduled before discharge (Dupree et al., 2014 ; Lewis et al., 2016 ; Silow-Carroll & Edwards, 2013). These strategies could improve patients’ experience about discharge processes and medication use. In addition, ACOs improve care management in hospital settings (Dupree et al., 2014 ; Lewis et al., 2016). For high-risk patients (e.g., patients with multiple chronic conditions), ACOs have designed clinical protocols to provide proactive care for these patients, keep them healthy, and avoid potential health care overuse (Dupree et al., 2014 ; Silow-Carroll & Edwards, 2013). These interventions could avoid unnecessary hospital stays, reduce costs, and improve patients’ experience.
Previous studies also found not every aspect of care delivery is targeted by ACOs. Although interventions targeting discharge processes and care management are adopted by many ACOs, inpatient care is not a major focus among ACOs as compared with primary care (Dupree et al., 2014 ; Lewis et al., 2016). Therefore, patient experience with inpatient care may not have improvement or even be degraded if ACOs need to focus on other care deliver settings. These may explain our null or even negative findings on many patient experience measures.
Our results indicate that the improvement in patient experience largely accrued among hospitals participating in Pioneer ACOs. As discussed above, the Pioneer ACO program was designed for those providers and organizations who are already experienced in care coordination. Their previous experiences may help them accommodate the ACO model and improve patient experience. In addition, a study also reported ACOs employing formal quality improvement were typically more advanced existing health care systems with prior quality improvement experience. However, formal quality improvement strategies were not identified among ACOs consisted of smaller practices or clinics with less experience with quality improvement or risk-based contracts (Lewis et al., 2016). Hospitals participating in Pioneer ACOs may have well-developed interventions and strategies to have better patient experience.
This study has several limitations. First, patient experience is associated with various factors, some of which are not controlled in this study, such as leadership and culture. Fixed-effects models generate causal, unbiased estimates under the assumption that omitted variables are time-invariant. However, it is difficult to test this assumption, and biased results could occur due to time-varying endogeneity. Furthermore, the direction of this bias is difficult to predict. Our patient experience results could be biased upward if participation in an ACO coincided with an improvement in leadership. The reverse would be true if ACO participation coincided with a negative leadership change. Therefore, results of this study are not necessarily causal. Second, patient experience measures used in this study may not represent real health care quality influenced by ACO participation, even though better experience is highly related with clinical quality (Doyle, Lennox, & Bell, 2013). The use of clinical quality measures would be desirable for future research. Third, the HCAHPS survey covers a broad scope of patients, including non-Medicare patients. Therefore, any changes in the patient experience scores observed in this study may not reflect the changes among Medicare patients. Although spillover effects—Medicare policy changes the quality among non-Medicare patients—are possible, it could also suggest potential bias of the results. A related concern is that hospitals may implement differential care coordination strategies for ACO and non-ACO patients. Although this is certainly possible, we believe it unlikely, for two reasons. Although CMS uses a hybrid approach, patients in the SSP are retrospectively attributed to the ACO, so hospitals would not be able to identify these patients with certainty. Also, a strong case can be made that it is more complicated and resource intensive to design a program for a specific subset of patients, particularly when there are certainly other similar patients that could benefit from the same program.
Our study has important implications for hospitals participating in or considering participating in an ACO. First, although ACOs and other new delivery and payments models hold promise to improve health care quality, participating in these models may not necessarily lead to better patient experience or other quality metrics. Hospital leaders need to be aware of the potential negative consequences of ACO participation, especially for those without rich experience in care management or care coordination. Second, hospitals differ in terms of preexisting capabilities that are related to ACO development and quality improvement from ACO participation. Hospitals leaders may want to conduct a self-evaluation to examine their preparedness for ACO participation (Diana et al., 2015). Third, hospitals with historically poor patient experience may need to develop competencies in coordinated care delivery to achieve benefits from their participation in ACOs. These competencies may include hiring new staff (e.g., care coordinator or care manager), advanced use of health information technology, and development of new clinical protocols. In addition, hospital leaders need to know that developing these capacity and skills could be time-consuming and resource-intensive, including labor and financial support needed to participate in an ACO. However, such effort could have important spillover effects that lead to other improvements in the quality of care delivery.
Hospital participation in ACOs does not, by itself, lead to improvement in overall patient experience. It appears that hospitals with previous experience in care coordination activities are more likely to benefit from participating in an integrated care delivery model such as ACOs. Hospitals with little experience in care coordination may want to consider focusing its efforts on such activities prior to ACO participation.
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