PI name and affiliations: Marisha A. Burden, MD, Denver Health and Hospital Authority, University of Colorado School of Medicine; Angela Keniston, MSPH, Denver Health and Hospital Authority

Site PI name and affiliations: Flora Kisuule, MD, MPH, Johns Hopkins School of Medicine; David Paje, MD, MPH, University of Michigan; Keri Holmes-Maybank, MD, Medical University of South Carolina; Hemali Patel, MD, University of Colorado Hospital, University of Colorado School of Medicine; Jeremy Schwartz, MD, Yale School of Medicine

Potential co-investigators: Jason Stein, MD, 1Unit; Katarzyna Mastalerz, MD, Presbyterian St. Luke's Hospital, University of Colorado School of Medicine; Jon Manheim, MD, Presbyterian St. Luke's Hospital, University of Colorado School of Medicine; Ed Havranek, MD, Denver Health and Hospital Authority, University of Colorado School of Medicine; John Rice, PhD, ACCORDS, University of Colorado School of Medicine

Patient partner: Michelle Archuleta

Program overview/introduction:

The purpose of this proposal is to evaluate a continuum of existing inpatient hospital care models ranging from the traditional care model to the accountable care unit model (ACU) by conducting a pragmatic observational, comparative effectiveness study.

Key clinical questions or evidence gaps:

Fragmented hospital care is common and leads to medical errors, increased utilization of health care and affects many stakeholders including patients, front line staff, and hospital leadership and administration. Currently, the optimal model of care on inpatient medical units is not known. One proposed model of care is the accountable care unit model (ACU) which consists of geographically based teams, structured interdisciplinary bedside rounding, nurse physician leadership dyad, and unit level data (1). Single center observational studies of components of this framework have suggested improved patient-centered outcomes such as patient and family experience of care (2), team communication and collaboration (3), and clinical outcomes (4).  However, there have been no head to head multisite comparisons published on accountable care unit models compared to traditional care.

The proposed study is designed to test the extent to which and for whom the ACU model will be more effective at engaging patients, improving communication across care teams and with patients, and improving clinical outcomes compared to traditional care model. Clinical stakeholders, administrative leaders and healthcare systems need to know which model (and which parts of the models) improves patient centered outcomes and the outcomes of interest to the key stakeholders. We propose a multi-hospital, pragmatic, observational, comparative effectiveness study in which we first assess the fidelity to the ACU care model on a particular unit or by a particular team, followed by observational data collection for the comparative effectiveness study of traditional care models versus accountable care unit models (high versus low fidelity to the components of the ACU).

Aims and Hypotheses:

Specific Aim 1. To assess fidelity to the accountable care unit model with differing levels of ACU model implementation to further refine protocol and prepare for the comparative effectiveness trial.

Aim 1a. Engage patients, families, and caregivers, clinical staff (nursing, providers, other clinical staff), health system administrators and clinical leaders to refine characterization of low and high fidelity ACU units and plan data utilization, collection procedures, and reporting.

Aim 1b. Assess the fidelity of participating sites to the ACU model by measuring through direct observation and at regular intervals, the specific structure and processes and elements present in both the ACU and traditional care model units/teams.

Specific Aim 2. To conduct a pragmatic, observational, comparative effectiveness study on a continuum of existing care models from the traditional care model (with 2 or less of ACU criterion) to the accountable care unit model (with all four criteria)

Aim 2a. Compare patient-centered outcomes such as shared decision-making and patient-reported anxiety and depression levels

Aim 2b. Compare clinical staff outcomes, including interprofessional collaboration amongst care teams and staff assessment of patient safety and quality of care

Aim 2c. Evaluate unit/team level quality outcomes important to patients, clinical care teams, and institutional leadershiputilizing data available through CDRN's and EHRs

Aim 2d. Compare engagement of patients, families, and caregivers, clinical staff, and hospital administrators through qualitative interview process and focus groups about their experiences with traditional care model and ACU model.

Hypotheses (Quantitative): Patients hospitalized in units with high fidelity to ACUs will experience better patient centered outcomes, interprofessional team outcomes, and clinical outcomes compared to traditional care models.

Any preliminary data:

As a part of our current and past work, we have engaged our patient stakeholders, patient partners, clinical staff stakeholders (including nursing, providers, social workers, physical therapists and occupational therapists, and pharmacists), and administrative and clinical leaders. We have conducted multiple focus groups with patients and families, clinical staff, and administrative leaders to better understand what patients want and need in their care and similarly how care teams perceive and experience the way patients are cared for. We have also engaged our local Patient and Family Advisory Council and members of the Colorado Patient Partners in Research network (CoPPiR) along with national experts in ACU model to help us choose the outcome metrics and develop the study methodology. We have also submitted a comparative effectiveness study to PCORI to study mentored implementation of accountable care units compared to traditional care, which is under review and will be complementary to this proposed study.

Study design, including study subjects (patients and/or providers) and setting, comparator groups, data sources, outcomes, analysis plan, power and sample size, limitations, and timeline:

Study design. This is a multi-hospital, within-hospital, pragmatic observational comparative effectiveness trial. A mixed-methods evaluation will include quantitative (patient and frontline clinical staff surveys, data collection via electronic health records, and participation and intervention fidelity tracking data) and qualitative (individual interviews and focus groups of patients, families, and care providers, staff, and leadership).

Study Population and Setting: Adult Spanish and English-speaking patients admitted to a Medicine service and being cared for in participating hospital inpatient units. All CRG sites would be invited to submit applications to participate. Hospitals will be selected to ensure sufficient variability between low and high fidelity units across selected sites.

Comparators: Because of the evolving nature of the care of patients who are hospitalized, our research team and stakeholders felt that in most cases some components of the ACU model are already employed in many hospitals thus we chose as the comparator to have two or less of the ACU components.

1. Traditional care model. For the existing care model to be considered traditional, no more than two ACU characteristics can be in place in the participating hospital inpatient unit.

2. Accountable care unit model. For an existing model to be considered an ACU, the four key characteristics must be in place including geographically located teams, standardized interdisciplinary bedside rounding, nurse-physician dyad leadership model, and unit level reporting.

Outcomes: The primary outcomes, as selected in conjunction with our stakeholders, are patient-reported experience of shared decision-making, clinician-reported perception of interprofessional collaboration, and hospital length of stay. Secondary outcomes include patient-reported symptoms of anxiety and depression, clinician assessment of patient safety and quality, ICU length of stay, rapid response calls, patient falls, inpatient mortality, time of discharge, unexpected returns to the hospital within 30 days of discharge, and HCAHPS survey results (including the nurse and physician communication composites and pain control composite).

Data Sources: Data will come in a variety of formats including patient surveys, care team member surveys. Additional data sources will be from the electronic health record and CDRN databases including PCORnet. Data will include but will not be limited to: hospital length of stay, intensive care unit length of stay, rapid response calls, patient falls, inpatient mortality, time of discharge, and unexpected return to the hospital within 30 days of discharge. All clinical effectiveness outcomes data will be obtained from hospital EHRs and CDRN databases and thus availability of data will not be dependent on patient participation, allowing for estimates of effectiveness among all patients who received care in specific types of care models as well as sub-analyses among those patients who were willing and able to complete patient-centered outcomes surveys with the research assistant. EHR extracts will include patient demographics, patient clinical history data, quality outcomes, and HCAPHS survey results.

In addition to better understanding quantitatively the types of existing care models, we hope to also utilize a qualitative approach as well. By utilizing purposive sampling techniques to recruit perspectives from a variety of stakeholders we hope to hold several focus groups and individual interviews to better understand how a wide variety of stakeholders experience the care model being utilized by their hospital.

Analytic Plan: We will compare our primary outcomes among models of care across all hospital units using linear mixed models, assuming these scores are approximately Gaussian distributed. We will include a parameter to represent the random effect of hospital unit, as patients in the same hospital unit will likely have correlated outcomes. We will include a fixed binary effect for model type and other patient- and hospital-level factors that we presume will be associated with the outcomes, such as age, gender, race, primary language and discharge diagnoses. All analyses will be performed in a statistical software program, such as R or SAS.

Sample Size and Power Calculations. N (total) = 15 hospitals, 7,500 patients (1 unit per hospital and 500 patients per unit), allowing for 30% attrition (leaving approximately 5,250 patients or 350 patients per unit per hospital).

Limitations: We will be studying an array of care models with the foundation for the comparison being whether the model utilized is high versus low fidelity to the ACU model harnessing the power of a natural experiment. Sites that have adopted the ACU model of care may be more progressive or more focused on improvement and thus results may be biased by those inherent traits. If funded, we plan on having a robust process to solicit applications for participation and will prospectively assess both current and past improvement efforts as well as models of care previously utilized. We hope to select a wide array of institutions that are diverse including hospital settings such as community hospitals, academic medical centers and centers that care for underserved populations like safety net institutions. This research is also observational in nature and thus there could be unmeasured and unknown causes of variance because the study does not include randomization. Healthcare systems are dynamic and continually working on improvement efforts, which could also affect findings.

Timeline: 3-5 years

Characteristics of sites who might participate: We have developed a rich network of research partners across the country, including six sites with who we previously submitted an Improving Healthcare Systems PCORI grant together. We anticipate that these sites, along with additional hospitals with whom we have partnered for other projects, will participate in this study. We would also have a larger call to other healthcare systems across the country to recruit sites that are as diverse as possible and also having implemented the ACU model to varying degrees.

Potential funders with RFA/RFP and due dates:

1. Pragmatic Clinical Studies to Evaluate Patient-Centered Outcomes - Cycle 2 2017 – letter of intent due 7/25/2017

2. AHRQ Health Services Research Projects (R01) (PA-14-291) – expiration date July 6, 2018

References:

1. Stein J, Payne C, Methvin A, et al. Reorganizing a hospital ward as an accountable care unit. J Hosp Med 2015;10:36-40.

2. Landry MA, Lafrenaye S, Roy MC, Cyr C. A randomized, controlled trial of bedside versus conference-room case presentation in a pediatric intensive care unit. Pediatrics 2007;120:275-80.

3. Gonzalo JD, Kuperman E, Lehman E, Haidet P. Bedside interprofessional rounds: perceptions of benefits and barriers by internal medicine nursing staff, attending physicians, and housestaff physicians. J Hosp Med 2014;9:646-51.

4. Kara A, Johnson CS, Nicley A, Niemeier MR, Hui SL. Redesigning inpatient care: Testing the effectiveness of an accountable care team model. J Hosp Med 2015;10:773-9.