High Value Healthcare Collaborative Research Articles

Are patients really getting what they want? The routine implementation of decision aids for patients with hip or knee osteoarthritis in the high value healthcare collaborative and alignment between patient treatment choice and receipt

Alignment between patients' treatment choices and treatments received is acknowledged as an important outcome of shared decision-making (SDM), yet recent research suggests that patients' choices do not always align with their actual treatment trajectories. This paper explores the alignment of patient-expressed treatment choices (for surgery or medical management) after exposure to decision aids and treatments received among patients with hip or knee osteoarthritis within High Value Healthcare Collaborative (HVHC) systems as the collaborative integrated decision aids intended to support SDM into routine clinical practice. This retrospective cohort study examines data from adult (≥18 years) patients with hip or knee osteoarthritis who received decision aids as part of orthopaedic consultations within HVHC systems between 2012 and 2015. Multivariable logistic regression explored the association between patient-level characteristics with the odds of treatment choice-receipt alignment. The majority of patients with knee osteoarthritis (68.3%) and hip osteoarthritis (71.9%) received treatments aligned with their choices following exposure to decision aids, but analyses reveal important differences in the odds of such alignment across patient characteristics. In adjusted models, African American patients with knee osteoarthritis had 50% lower odds of receiving treatment aligned with their choices compared with Caucasian patients (OR=0.52, P < .05). Medicare- or Medicaid-insured knee patients had 49% and 59% lower odds (respectively) of receiving choice-aligned treatments relative to privately insured patients. Patients with knee (OR=0.40, P < .01) or hip (OR=0.75, P < .05) osteoarthritis at earlier decision-making stages had lower odds of receiving treatments congruent with their choices. This work elucidates the odds of treatment choice-aligned care for patients within health care systems attempting to routinely integrate decision aids to support SDM into clinical practice and underscores the gaps in achieving this alignment among African American patients, those with public insurance and those at early decision-making stages.

Improvement in Mortality With Early Fluid Bolus in Sepsis Patients With a History of Congestive Heart Failure.

ObjectiveTo determine whether rapid administration of a crystalloid bolus of 30 mL/kg within 3 hours of presentation harms or benefits hypotensive patients with sepsis with a history of congestive heart failure (CHF).Patients and MethodsA retrospective cohort study using Medicare claims data enhanced by medical record data from members of the High Value Healthcare Collaborative from July 1, 2013, to June 30, 2015, examining patients with a history of CHF who did (fluid bundle compliant [FBC]) or did not (NFBC) receive a volume bolus of 30 mL/kg within 3 hours of presentation to the emergency department. A proportional Cox hazard model was used to evaluate the association of FBC with 1-year survival.ResultsOf the 211 patients examined, 190 were FBC and 21 were NFBC. The FBC patients had higher average hierarchical condition category scores but were otherwise similar to NFBC patients. The NFBC patients had higher adjusted in-hospital and postdischarge mortality rates. The risk-adjusted 1-year mortality rate was higher for NFBC patients (hazard ratio, 2.18; 95% CI, 1.2 to 4.0; P=.01) than for FBC patients.ConclusionIn a retrospective claim data-based study of elderly patients with a history of CHF presenting with severe sepsis or septic shock, there is an association of improved mortality with adherence to the initial fluid resuscitation guidelines as part of the 3-hour sepsis bundle.

Decision Aid Implementation and Patients' Preferences for Hip and Knee Osteoarthritis Treatment: Insights from the High Value Healthcare Collaborative.

BackgroundShared decision making (SDM) research has emphasized the role of decision aids (DAs) for helping patients make treatment decisions reflective of their preferences, yet there have been few collaborative multi-institutional efforts to integrate DAs in orthopedic consultations and primary care encounters.ObjectiveIn the context of routine DA implementation for SDM, we investigate which patient-level characteristics are associated with patient preferences for surgery versus medical management before and after exposure to DAs. We explored whether DA implementation in primary care encounters was associated with greater shifts in patients’ treatment preferences after exposure to DAs compared to DA implementation in orthopedic consultations.DesignRetrospective cohort study.Setting10 High Value Healthcare Collaborative (HVHC) health systems.Study participantsA total of 495 hip and 1343 adult knee osteoarthritis patients who were exposed to DAs within HVHC systems between July 2012 to June 2015.ResultsNearly 20% of knee patients and 17% of hip patients remained uncertain about their treatment preferences after viewing DAs. Older patients and patients with high pain levels had an increased preference for surgery. Older patients receiving DAs from three HVHC systems that transitioned DA implementation from orthopedics into primary care had lower odds of preferring surgery after DA exposure compared to older patients in seven HVHC systems that only implemented DAs for orthopedic consultations.ConclusionPatients’ treatment preferences were largely stable over time, highlighting that DAs for SDM largely do not necessarily shift preferences. DAs and SDM processes should be targeted at older adults and patients reporting high pain levels. Initiating treatment conversations in primary versus specialty care settings may also have important implications for engagement of patients in SDM via DAs.

The Impact Of Decision Aids On Adults Considering Hip Or Knee Surgery.

Trials of decision aids developed for use in shared decision making find that patients engaged in that process tend to choose more conservative treatment for preference-sensitive conditions. Shared decision making is a collaborative process in which clinicians and patients discuss trade-offs and benefits of specific treatment options in light of patients' values and preferences. Decision aids are paper, video, or web-based tools intended to help patients match personal preferences with available treatment options. We analyzed data for 2012-15 about patients within the ten High Value Healthcare Collaborative member systems who were exposed to condition-specific decision aids in the context of consultations for hip and knee osteoarthritis, with the intention that the aids be used to support shared decision making. Compared to matched patients not exposed to the decision aids, those exposed had two-and-a-half times the odds of undergoing hip replacement surgery and nearly twice the odds of undergoing knee replacement surgery within six months of the consultation. These findings suggest that health care systems adopting decision aids developed for use in shared decision making, and used in conjunction with hip and knee osteoarthritis consultations, should not expect reduced surgical utilization.

Identifying high-cost episodes in lower extremity joint replacement.

To evaluate the ability of claims-based risk adjustment and incremental components of clinical data to identify 90-day episode costs among lower extremity joint replacement (LEJR) patients according to the Centers for Medicare & Medicaid Services (CMS) Comprehensive Care for Joint Replacement (CJR) program provisions. Medicare fee-for-service (FFS) data for qualifying CJR episodes in the United States, and FFS data linked with clinical data from CJR-qualifying LEJR episodes performed at High Value Healthcare Collaborative (HVHC) and Mayo Clinic in 2013. HVHC and Mayo Clinic populations are subsets of the total FFS population to assess the additive value of additional pieces of clinical data in correctly assigning patients to cost groups. Multivariable logistic models identified high-cost episodes. Clinical data from participating health care systems merged with Medicare FFS data. Our three populations consisted of 363621 patients in the CMS population, 4881 in the HVHC population, and 918 in the Mayo population. When modeling per CJR specifications, we observed low to moderate model performance (CMS C-Stat=0.714; HVHC C-Stat=0.628; Mayo C-Stat=0.587). Adding CMS-HCC categories improved identification of patients in the top 20% of episode costs (CMS C-Stat=0.758, HVHC C-Stat=0.692, Mayo C-Stat=0.677). Clinical variables, particularly functional status in the population for which this was available (Mayo C-Stat=0.783), improved ability to identify patients within cost groups. Policy makers could use these findings to improve payment adjustments for bundled LEJR procedures and in consideration of new data elements for reimbursement.

Wednesday, September 26, 2018 10:35 AM – 12:00 PM Understanding Lumbar Stenosis/Spondylolisthesis: 16. Association of surgical invasiveness with readmission following surgery for lumbar spondylolisthesis

BACKGROUND CONTEXT Surgical treatment for lumbar spondylolisthesis is often considered for those who have failed nonoperative care, especially with persistent or recurrent symptoms, progressive displacement, or worsening functional decline. Criteria for selecting surgical candidates are variable, and decisions about what type of operation to perform is discretionary. Wide heterogeneity in surgical procedure invasiveness reflects a lack of evidence on effectiveness and highlights the need to expand comparative effectiveness research that incorporates patient-reported outcomes. PURPOSE To examine the association of repeat spine operation (1-year), wound problem (90-day), and all-cause re-hospitalization (90-day) with surgical invasiveness in the treatment of lumbar spondylolisthesis. STUDY DESIGN/SETTING Retrospective analysis of spondylolisthesis data from the High Value Healthcare Collaborative, a network of diverse U.S. health systems. PATIENT SAMPLE We included patients (n=884) undergoing decompression or fusion for lumbar spondylolisthesis, excluding those with significant comorbidity or device removal/revision procedures. OUTCOME MEASURES The Surgical Invasiveness Index was calculated using a previously validated method based on Current Procedural Terminology codes. Safety outcomes reported in the High Value Healthcare Collaborative network including rate of repeat lumbar surgery, readmission, and wound problems were also analyzed. METHODS Logistic regression with site-specific robust standard errors were used to identify the association between the surgical invasiveness and safety outcomes, controlling for patient age, sex and Elixhauser (v3.7) comorbidity. RESULTS The adjusted mean adverse event rates were 2.0% for repeat surgery within 1 year, 1.3% for 90-day wound problems, and 4.2% for 90-day readmission. Surgical invasiveness was associated with wound problems (OR 1.10, p CONCLUSIONS Greater use of complex spine operations in treating spondylolisthesis might reflect surgeons’ intention to provide additional stability, even in cases of mild spondylolisthesis. However, we found that greater surgical invasiveness is associated with increased risk for wound problems and readmissions, even after controlling for patient characteristics and comorbidity. Therefore, in planning surgical interventions, surgeons must engage patients in shared decision making, balancing benefits of more complex procedures with these associated increased risks for harm. FDA DEVICE/DRUG STATUS This abstract does not discuss or include any applicable devices or drugs.

A Data Driven Approach to Achieving High Value Healthcare.

The purpose of this special issue is to disseminate learning from the High Value Healthcare Collaborative (HVHC). The HVHC is a voluntary, member-led organization based on trusted, working relationships among delivery system leaders. HVHC’s mission is to be a provider-based learning health system committed to improving healthcare value through data, evidence, and collaboration. We begin by describing the organization and structure of HVHC in order to lay the context for a series of papers that feature work from this learning health system. HVHC was awarded a grant from the John and Laura Arnold Foundation to develop a generalizable model for dissemination and implementation. Implementation of the 3-hour sepsis bundle was used as a prototypic, complex intervention with an in-depth mixed methods evaluation across 16 member sites. The first four articles in this issue describe, in detail, various data and methodological challenges encountered together with strategies for overcoming these (see Knowlton et al., von Recklinghausen et al., Welch et al., and Taenzer et al.). Next, we illustrate how the Data Trust can support emerging questions relevant to member organizations. The paper by Albritton et al., explores the impact of observation stays on readmission rates. Knighton et al., explore the use of an area-based measure for health literacy to assess risk in disadvantaged populations. Two final papers illustrate the importance of fundamental data sources needed to support advanced data science.

Dissemination and Implementation of Evidence Based Best Practice Across the High Value Healthcare Collaborative (HVHC) Using Sepsis as a Prototype - Rapidly Learning from Others.

The dissemination of evidence-based best practice through the entire health care system remains an elusive goal, despite public pressure and regulatory guidance. Many patients do not receive the same quality of care at different hospitals across the same health care system. We describe the role of a data driven learning collaborative, the High Value Healthcare Collaborative (HVHC), in the dissemination of best practice using adherence to the 3-hour-bundle for sepsis care. Compliance with and adoption of sepsis bundle care elements comparing sites with mature vs non-mature care delivery processes were measured during the improvement effort for a cohort of 20,758 patients. Non-mature sites increased their bundle compliance from 71.0 to 86.7 percent (p < 0.005). This compliance increase was primarily based on increased compliance with the fluid element of the bundle that improved for non-mature locations from 76.4 to 94.0 percent (p < 0.005).

A Framework for Aligning Data from Multiple Institutions to Conduct Meaningful Analytics.

Introduction:Health systems can be supported by collaborative networks focused on data sharing and comparative analytics to identify and rapidly disseminate promising care practices. Standardized data collection, quality assessment, and cleansing is a necessary process to facilitate meaningful analytics for operations, quality improvement, and research. We developed a framework for aligning data from health care delivery systems using the High Value Healthcare Collaborative central registry.Framework:The centralized data registry model allows for multiple layers of data quality assessment. Our framework uses an iterative approach, starting with clear specifications, maintaining ongoing dialogue with diverse stakeholders, and regular checkpoints to assess data conformance, completeness, and plausibility.Lessons Learned:We found that an iterative communication process is critical for a central registry to ensure: 1) clarity of data specifications, 2) appropriate data quality, and 3) thorough understanding of data source, purpose, and context. Engaging teams from all participating institutions and incorporating diverse stakeholders of clinicians, information technologists, data analysts, operations managers, and health services researchers in all decision making processes supports development of high quality datasets for comparative analytics across multiple institutions.Conclusion:A standard data specification and submission process alone does not guarantee aligned data for a collaborative registry. Implementing an iterative data quality improvement framework with extensive communication proved to be effective for aligning data from multiple institutions to support meaningful analytics.

The Effect of the Hospital Readmission Reduction Program on the Duration of Observation Stays: Using Regression Discontinuity to Estimate Causal Effects

Research Objective:Determine whether hospitals are increasing the duration of observation stays following index admission for heart failure to avoid potential payment penalties from the Hospital Readmission Reduction Program.Study Design:The Hospital Readmission Reduction Program applies a 30-day cutoff after which readmissions are no longer penalized. Given this seemingly arbitrary cutoff, we use regression discontinuity design, a quasi-experimental research design that can be used to make causal inferences.Population Studied:The High Value Healthcare Collaborative includes member healthcare systems covering 57% of the nation’s hospital referral regions. We used Medicare claims data including all patients residing within these regions. The study included patients with index admissions for heart failure from January 1, 2012 to June 30, 2015 and a subsequent observation stay within 60 days. We excluded hospitals with fewer than 25 heart failure readmissions in a year or fewer than 5 observation stays in a year and patients with subsequent observation stays at a different hospital.Principal Findings:Overall, there was no discontinuity at the 30-day cutoff in the duration of observation stays, the percent of observation stays over 12 hours, or the percent of observation stays over 24 hours. In the sub-analysis, the discontinuity was significant for non-penalized.Conclusion:The findings reveal evidence that the HRRP has resulted in an increase in the duration of observation stays for some non-penalized hospitals.

The High Value Healthcare Collaborative: Observational Analyses of Care Episodes for Hip and Knee Arthroplasty Surgery

BackgroundBroader use of value-based reimbursement models will require providers to transparently demonstrate health care value. We sought to determine and report cost and quality data for episodes of hip and knee arthroplasty surgery among 13 members of the High Value Healthcare Collaborative (HVHC), a consortium of health care systems interested in improving health care value. MethodsWe conducted a retrospective, cross-sectional observational cohort study of 30-day episodes of care for hip and knee arthroplasty in fee-for-service Medicare beneficiaries aged 65 or older who had hip or knee osteoarthritis and used 1 of 13 HVHC member systems for uncomplicated primary hip arthroplasty (N = 8853) or knee arthroplasty (N = 16,434), respectively, in 2012 or 2013. At the system level, we calculated: per-capita utilization rates; postoperative complication rates; standardized total, acute, and postacute care Medicare expenditures for 30-day episodes of care; and the modeled impact of reducing episode expenditures or per-capita utilization rates. ResultsAdjusted per-capita utilization rates varied across HVHC systems and postacute care reimbursements varied more than 3-fold for both types of arthroplasty in both years. Regression analysis confirmed that total episode and postacute care reimbursements significantly differed across HVHC members after considering patient demographic differences. Potential Medicare cost savings were greatest for knee arthroplasty surgery and when lower total reimbursement targets were achieved. ConclusionThe substantial variation that we found offers opportunities for learning and collaboration to collectively improve outcomes, reduce costs, and enhance value. Ceteris paribus, reducing per-episode reimbursements would achieve greater Medicare cost savings than reducing per-capita rates.

A Collaborative Of Leading Health Systems Finds Wide Variations In Total Knee Replacement Delivery And Takes Steps To Improve Value

Members of a consortium of leading US health care systems, known as the High Value Healthcare Collaborative, used administrative data to examine differences in their delivery of primary total knee replacement. The goal was to identify opportunities to improve health care value by increasing the quality and reducing the cost of that procedure. The study showed substantial variations across the participating health care organizations in surgery times, hospital lengths-of-stay, discharge dispositions, and in-hospital complication rates. The study also revealed that higher surgeon caseloads were associated with shorter lengths-of-stay and operating time, as well as fewer in-hospital complications. These findings led the consortium to test more coordinated management for medically complex patients, more use of dedicated teams, and a process to improve the management of patients' expectations. These innovations are now being tried by the consortium's members to evaluate whether they increase health care value.