Jillian B. Harvey

Turning readmission reduction policies into results: some lessons from a multistate initiative to reduce readmissions.

Efforts are under way nationally to reduce avoidable hospital readmissions by changing payments to hospitals, but it is unclear how well or how quickly these policy changes will produce widespread reductions in hospital readmissions. To examine some of the challenges to implementing such approaches, the authors analyzed the early experiences of 3 statewide programs to reduce preventable readmissions that began in 2009. Based on interviews with program participants in 2011, the authors identified 3 key obstacles to progress: the difficulty of developing collaborative relationships across care settings, gaps in evidence for effective interventions, and deficits in quality improvement capabilities among some organizations. These findings underscore the uncertainty of success of current readmissions policies and suggest that immediate improvement in readmission rates through a change in reimbursement may be unlikely unless these other obstacles are addressed expeditiously. In particular, cultivation of productive collaboration across care settings will be critical because these kinds of relationships are not well established or naturally occurring in most communities.

Trends in bariatric surgery, 2002-2012: do changes parallel the obesity trend?

BACKGROUND It is well documented that bariatric surgery is an effective weight loss intervention, and bariatric procedure rates have increased over time. However, there was a period of plateau in procedure rates in the mid to late 2000s. Recent literature has not identified current trends in procedure rates or associations between bariatric surgery and population factors, such as obesity and diabetes. OBJECTIVES The purpose of this study was to determine trends in statewide rates of bariatric operations, obesity, and diabetes over an 11-year period and to determine if population factors are associated with procedure rates. SETTING Data from the Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP) State Inpatient Database (SID) were utilized to identify a study sample population of patients who underwent bariatric procedures from 2002-2012. METHODS State level population characteristics were obtained from the Behavioral Risk Factor Surveillance System and Census Bureau Data for the 11-year period. Statistical analyses determined rates of surgery, obesity, and diabetes over time, as well as associations between surgery rates and population factors. RESULTS From 2002-2012, bariatric procedure rates increased, with an exponential rise in laparoscopic surgical methods. Procedure rates reached a peak value in 2009 and then plateaued. Statewide obesity and diabetes rates increased over time, although there was no association between these population factors and procedure rates. Women had consistently higher rates of bariatric operations. CONCLUSION Although bariatric procedures are an evidenced-based effective treatment for obesity, procedure rates were not associated with the increasing obesity and diabetes rates in the United States. Further research is needed to identify factors that affect the adoption and diffusion of bariatric operations to increase diffusion of beneficial innovations and improve overall quality of care and health outcomes.

Bariatric surgery implementation trends in the USA from 2002 to 2012

BackgroundMany beneficial health care interventions are either not put into practice or fail to diffuse over time due to complex contextual factors that affect implementation and diffusion. Bariatric surgery is an example of an effective intervention that recently experienced a plateau and decrease in rates, with minimal documented justification for this trend. While there are conceptual models that provide frameworks of general innovation implementation and diffusion, few studies have tested these models with data to measure the relative effects of factors that affect diffusion of specific health care interventions.MethodsA literature review identified factors associated with implementation and diffusion of health care innovations. These factors were utilized to construct a conceptual model of diffusion to explain changes in bariatric surgery over time. Six data sources were used to construct measures of the study population and factors in the model that may affect diffusion of surgery. The population included obese and morbidly obese patients from 2002 to 2012 who had bariatric surgery in 15 states. Multivariable models were used to identify environmental, population, and medical practice factors that facilitated or impeded diffusion of bariatric surgery over time.ResultsIt was found that while bariatric surgery rates increased over time, the speed of growth in surgeries, or diffusion, slowed. Higher cumulative number of surgeries and higher proportion of the state population in age group 50–59 slowed surgery growth, but presence of Medicare centers of excellence increased the speed of surgery diffusion. Over time, the factors affecting the diffusion of bariatric surgery fluctuated, indicating that diffusion is affected by temporal and cumulative effects.ConclusionsThe primary driver of diffusion of bariatric surgery was the extent of centers of excellence presence in a state. Higher cumulative surgery rates and higher proportions of older populations in a state slowed diffusion. Surprisingly, measures of the presence of champions were not significant, perhaps because these are difficult to measure in the aggregate. Our results generally support the conceptual model of diffusion developed from the literature, which may be useful for examining other innovations, as well as for designing interventions to support rapid diffusion of innovations to improve health outcomes and quality of care.

Building The Scaffold To Improve Health Care Quality In Western New York

Many health policy leaders are promoting the community as a place to try out new ideas for improving the quality of health care. Alliances with multiple stakeholders are moving forward with communitywide efforts to improve the quality of care without the benefit of an established evidence base or guiding framework. This article presents a profile of one communitys attempt to facilitate and coordinate quality improvement in its geographic area. The P(2) Collaborative of Western New York is one of sixteen sites supported by the Robert Wood Johnson Foundations national Aligning Forces for Quality initiative. The strategy and vision of the collaborative has evolved as it has tried to capitalize on opportunities and overcome barriers in its work. The article concludes with a discussion of eight tasks that community alliances may consider undertaking when establishing an infrastructure for improving the quality of health care, such as convening area stakeholders to develop a strategy and finding ways to monitor health outcomes at the local level on an ongoing basis.

Measuring the Dose of Quality Improvement Initiatives

Although intervention dose—defined as the quality and quantity of an intervention and participation—might be key to understanding why some multisite quality improvement (QI) initiatives work and others do not, evaluations rarely consider dose, and there is no widely accepted method for measuring it. In this exploratory study, the authors examined the literature on QI dose, identified four methods for measuring QI dose, applied them to 14 communities participating in a QI initiative, examined whether the dose scores aligned with perceptions of QI dose among individuals knowledgeable of the initiative, and report on lessons learned. They conclude it is feasible to measure QI dose and found a high level of concordance between scores on a comprehensive dose measure and knowledgeable informants’ perceptions. However, measuring QI dose presents many challenges, including subjective decisions about the elements of dose to include in a measure and the need for extensive data collection.

Community‐Level Quality Improvement and the Patient Experience for Chronic Illness Care

OBJECTIVE To determine whether chronically ill adults from communities participating in a community-level quality improvement effort reported greater improvement on four domains of patient experience: care coordination, patient satisfaction, provider interaction and support, and receipt of recommended care for diabetes. STUDY SETTING The Robert Wood Johnson Foundations Aligning Forces for Quality (AF4Q) initiative provides multistakeholder alliances with funding and technical assistance to improve quality in their communities. STUDY DESIGN This is a quasi-experimental, pre-post study. We used a difference-in-difference approach to detect relative changes over time on 16 survey-based outcome measures representing the four patient experience domains. DATA COLLECTION We surveyed adults with chronic illness(es) in 14 AF4Q communities and a national comparison group. Wave 1 was completed in 2008 (8,140 respondents) and wave 2 in 2012 (9,565 respondents). PRINCIPAL FINDINGS Respondents from AF4Q communities reported modestly greater improvement on patient satisfaction and receipt of recommended care for diabetes. CONCLUSIONS Results suggest that community-level QI efforts led by multistakeholder alliances hold the potential to improve patient satisfaction and receipt of recommended care for diabetes, but the magnitude of the effect may be limited. However, there is less evidence that community-level QI can improve patient perceptions of care coordination or provider interaction and support.

Stroke Administrative Severity Index: using administrative data for 30-day poststroke outcomes prediction

Aim: Current stroke severity scales cannot be used for archival data. We develop and validate a measure of stroke severity at hospital discharge (Stroke Administrative Severity Index [SASI]) for use in billing data. Methods: We used the NIH Stroke Scale (NIHSS) as the theoretical framework and identified 285 relevant International Classification of Diseases, 9th Revision diagnosis and procedure codes, grouping them into 23 indicator variables using cluster analysis. A 60% sample of stroke patients in Medicare data were used for modeling risk of 30-day postdischarge mortality or discharge to hospice, with validation performed on the remaining 40% and on data with NIHSS scores. Results: Model fit was good (p > 0.05) and concordance was strong (C-statistic = 0.76–0.83). The SASI predicted NIHSS at discharge (C = 0.83). Conclusion: The SASI model and score provide important tools to control for stroke severity at time of hospital discharge. It can be used as a risk-adjustment variable in administrative data analyses to measure postdischarge outcomes.

Capsule Commentary on Luo et al., A Comparison of Health Plan- and Provider-Delivered Chronic Care Management Models on Patient Clinical Outcomes.

C hronic diseases are costly to the health care system, highly prevalent, and result in seven of the top ten leading causes of death. Improving chronic disease care and outcomes is a national priority. For healthcare stakeholders seeking to better manage chronic disease, there are numerous approaches and the evidence on which model is most effective at improving outcomes remains unclear. Given the negative impact of chronic disease on healthcare outcomes and the substantial investments in care management interventions, it is important to understand the potential effectiveness of strategies. The study by Luo et al. uses a difference-in-differences approach to compare the effectiveness of two care management approaches on improving clinical outcomes. Commercially insured patients were part of either a provider-delivered care management (PDCM) or health-plan–delivered care management (HPDCM) program. The study examines seven outcomes for patients with at least one of five chronic diseases (congestive heart failure, chronic obstructive pulmonary disease, coronary artery disease, diabetes, or asthma). The actual effect of the care management programs was small and improvements were found in only a few outcomes after 12 months. The study found no significant differences between the two care management programs. Care management programs may not be the cure-all for improving chronic disease outcomes. However, within 12months, small gains weremade in several clinical outcomes and further research is warranted. This is the first study to compare the HPDCM and PDCM models. Given that it can take several years to see improvements in population-level outcomes, future research should build upon this work. In addition, the authors note that the implementations of the provider-driven approaches were highly variable across practices. Physician practices implementing care management programs should be mindful of the intervention dose and fidelity. Finally, both care management models are promising options to improve care for patients with chronic diseases. Providers should consider implementation of the approach that best meets the patients’ needs, contextual needs of the practices, and most efficiently utilizes resources.