CMS changes in reimbursement for HAIs: setting a research agenda.

BACKGROUND: The Centers for Medicare and Medicaid Services (CMS) promulgated regulations commencing October 1, 2008, which deny payment for selected conditions occurring during the hospital stay and are not present on admission. Three of the 10 hospital-acquired conditions covered by the new CMS policy involve healthcare-associated infections, which are a common, expensive, and often preventable cause of inpatient morbidity and mortality. OBJECTIVE: To outline a research agenda on the impact of CMS's payment policy on the healthcare system and the prevention of healthcare-associated infections. METHODS: An invitational day-long conference was convened in April 2009. Including the planning committee and speakers there were 41 conference participants who were national experts and senior researchers. RESULTS: Building upon a behavioral model and organizational theory and management research a conceptual framework was applied to organize the wide range of issues that arose. A broad array of research topics was identified. Thirty-two research agenda items were organized in the areas of incentives, environmental factors, organizational factors, clinical outcomes, staff outcomes, and financial outcomes. Methodological challenges are also discussed. CONCLUSIONS: This policy is a first significant step to move output-based inpatient funding to outcome-based funding, and this agenda is applicable to all hospital-acquired conditions. Studies beginning soon will have the best hope of capturing data for the years preceding the policy change, a key element in non-experimental research. The CMS payment policy offers an excellent opportunity to understand and influence the use of financial incentives for improving patient safety.

Hospital characteristics, rather than surgical volume, predict length of stay following colorectal cancer surgery.

OBJECTIVE: Length of hospital stay (LOS) is considered a vital component for successful colorectal surgery treatment. Evidence of an association between hospital surgery volume and LOS has been mixed. Data modelling techniques may give inconsistent results that adversely impact conclusions. This study applied techniques to overcome possible modelling drawbacks. METHOD: An additive quantile regression model formulated to isolate hospital contextual effects was applied to every colorectal surgery for cancer conducted in Victoria, Australia, between 2005 and 2015, involving 28,343 admissions in 90 Victorian hospitals. The model compared hospitals' operational efficiencies regarding LOS. RESULTS: Hospital LOS operational efficiencies for colorectal cancer surgery varied markedly between the 90 hospitals and were independent of volume. This result was adjusted for pertinent patient and hospital characteristics. CONCLUSION: No evidence was found that higher annual surgery volume was associated with lower LOS for patients undergoing colorectal cancer surgery. Our model showed strong evidence that differences in LOS efficiency between hospitals was driven by hospital contextual effects that were not predicted by provider volume. Further study is required to elucidate these inherent differences between hospitals. Implications for public health: Our model indicated improved efficiency would benefit the patient and medical system by lowering LOS and reducing expenditure by more than $3 million per year.

Development and Implementation of ExPLORE Clinical Practice, a Web-accessible Comparative Outcomes Tool for California Hospitals and Physicians.

BACKGROUND: Hospital-based clinicians have little information about the outcomes of their care, much less how those outcomes compare with those of their peers. A variety of care quality indicators have been developed, but comparisons tend to be hospitalwide, and often irrelevant to the practice and patient group of many hospital clinicians. Moreover, information is not enough to transform clinical practice, as the human response to such comparisons is, "I'm doing the best I know how." What is needed is granular, clinically specific feedback with peer-mediated advice about how "positive deviants" achieve better results. OBJECTIVE: This case study reports on the development and implementation of a web-accessible comparative outcomes tool, ExPLORE Clinical Practice, for hospitals and clinicians in California. METHODS: We use iterative development and refinement of web tools to report comparative outcomes; incremental development of suites of procedure-patient outcome pairs specific to particular medical specialty groups; testing and refinement of response time metrics to reduce delays in report generation; and introduction of a comments section for each measure that assists with interpretation and ties results to strategies found to lead to better clinical outcomes. RESULTS: To date, 76 reports, each with 115 to 251 statistically evaluated outcomes, are available electronically to compare individual hospitals in California to statewide outcomes. DISCUSSION AND CONCLUSIONS: ExPLORE Clinical Practice is one of a number of emerging systems that attempt to lever available data to improve patient outcomes. The ExPLORE Clinical Practice system combines a clinical focus on highly specific outcome measures with attention to technical issues such as crafting an intuitive user interface and graphic presentation. This case study illustrates the important advances made in using data to support clinicians to improve care for patients. We see this information as a way to start local conversations about quality improvement, and as a means of generating peer advice for improving patient outcomes.

Enhancing Medicare's hospital-acquired conditions policy to encompass readmissions.

BACKGROUND: The current Medicare policy of non-payment to hospitals for Hospital-Acquired Conditions (HAC) seeks to avoid payment for preventable complications identified within a single admission. The financial impact ($1 million-$50 million/yr) underestimates the true financial impact of HACs when readmissions are taken into account. OBJECTIVE: Define and quantify acute inpatient readmissions arising directly from, or completing the definition of, the current HACs. RESEARCH DESIGN: Observational study. SUBJECTS: All non-federal inpatient admissions to California hospitals, July 2006 to June 2007 with a recorded Social Security number. MEASURES: Readmission to acute care within 1 day for acute complications of poor glycemic control; 7 days for iatrogenic air emboli, incompatible blood transfusions, catheter-associated urinary tract infections and vascular catheter-associated infections; 30 days for deep vein thromboses or pulmonary emboli following hip or knee replacement surgery; and 183 days for foreign objects retained after surgery, mediastinitis following coronary artery bypass grafts, injuries sustained during inpatient care, infections following specific joint or bariatric surgery procedures, and pressure ulcers stages III & IV. RESULTS: An additional estimated $103 million in payments would be withheld if Medicare expands the policy to include non-payment for HAC related readmissions. The majority (90%) of this impact involves mediastinitis, post-orthopedic surgery infection, or fall related injury. CONCLUSIONS: Limiting the current HAC policy focus to complications identified during the index admission omits consideration of many complications only identified in a subsequent admission. Non-payment for HAC-related readmissions would enhance incentives for prevention by increasing the frequency with which hospitals are held accountable for HACs.

The US Medicare policy of not reimbursing hospital-acquired conditions: what impact would such a policy have in Victorian hospitals?

OBJECTIVE: To model the effect of excluding payment for eight hospital-acquired conditions (HACs) on hospital payments in Victoria, Australia. DESIGN, SETTING AND PARTICIPANTS: Retrospective ecological study using the Victorian Admitted Episodes Dataset. The analysis involved all acute inpatient admissions to Victorian public and private hospitals between 1 July 2007 and 30 June 2008. INTERVENTIONS: Each admission record includes up to 40 diagnosis and procedure codes from which payments are calculated. The model deleted diagnosis codes for eight HACs from all records, then recalculated payments to estimate the impact of a policy of non-payment for HACs. MAIN OUTCOME MEASURE: The effect on hospital payments of excluding diagnosis codes for eight HACs. RESULTS: 2,047,133 cases with total estimated payments of $4902 million were identified; 994 cases (0.05%) had one or more diagnoses meeting the code definition for a definable HAC, representing total payments of $24.1 million. In-hospital falls and pressure ulcers were the most commonly coded HACs. Applying a model that excluded HAC diagnosis codes changed the diagnosis-related group for 134 cases (13.5%), thereby generating a $448,630 reduction in payments. CONCLUSIONS: Introducing a non-payment for HACs policy similar to that introduced by Medicare in the United States would have little direct financial impact in the Australian context, although additional savings would accrue if HAC rates were reduced. Such a policy could add further incentive to current initiatives aimed at reducing HACs.

Medicare's policy not to pay for treating hospital-acquired conditions: the impact.

In 2008 Medicare stopped reimbursing hospitals for treating eight avoidable hospital-acquired conditions. Using 2006 California data, we modeled the financial impact of this policy on six such conditions. Hospital-acquired conditions were present in 0.11 percent of acute inpatient Medicare discharges; only 3 percent of these were affected by the policy. Payment reductions were negligible (0.001 percent, or $0.1 million-equivalent to $1.1 million nationwide) and are unlikely to encourage providers to improve quality. Options to strengthen the incentives include further payment modifications for hospital-acquired conditions or expanding the hospital-acquired condition policy to exclude payment for consequences, additional procedures, and readmissions.

Development of autoantibodies to islet antigens during childhood: implications for preclinical type 1 diabetes screening.

OBJECTIVE: Serum islet antibodies signify increased risk for type 1 diabetes (T1D). Knowledge of the relationship between age and seroconversion would guide screening for at-risk individuals. We aimed to determine the effectiveness of islet antibody screening in early childhood, in particular the proportion of negative children who subsequently seroconverted. METHODS: We identified 554 children with a first-degree relative with T1D who had tested negative for islet cell antibodies (ICA) and insulin autoantibodies (IAA) when first screened at a mean age of 7.2 yr. Of 423 who were eligible, 350 consented to re-testing for ICA and IAA and antibodies to glutamic acid decarboxylase (GADAb) and tyrosine phosphatase-like insulinoma antigen IA-2 (IA2Ab) at a mean age of 11.1 yr. GADAb and IA2Ab were measured in 239 of the initial stored samples. RESULTS: Of the 350 children who tested negative at first screening, 12 (3.4%) subsequently seroconverted, becoming positive for ICA (n = 4), IAA (n = 7), GADAb (n = 6) or IA2Ab (n = 2). Of 239 initially negative for ICA and IAA, 8/239 (3.3%) now tested positive for GADAb (n = 7) or IA2Ab (n = 1). Four of these children were positive for GADAb in both tests; the one child initially positive for IA2Ab only was positive for all four antibodies 4.6 yr later and developed diabetes. CONCLUSION: Screening for ICA and IAA failed to identify 2-3% of genetically at-risk children who subsequently developed islet antibodies. Testing for GADAb and IA2Ab would not have avoided this. Maximizing the sensitivity of detecting risk for T1D requires repeat screening for islet antibodies throughout childhood.