The business case for quality: estimating lives saved and harms avoided in a value-based purchasing model.

Ever-increasing concern about the cost and burden of quality measurement and reporting raises the question: How much do patients benefit from provider arrangements that incentivize performance improvements? We used national performance data to estimate the benefits in terms of lives saved and harms avoided if US health plans improved performance on 2 widely used quality measures: blood pressure control and colorectal cancer screening. We modeled potential results both in California Marketplace plans, where a value-based purchasing initiative incentivizes improvement, and for the US population across 4 market segments (Medicare, Medicaid, Marketplace, commercial). The results indicate that if the lower-performing health plans improve to 66th percentile benchmark scores, it would decrease annual hypertension and colorectal cancer deaths by approximately 7% and 2%, respectively. These analyses highlight the value of assessing performance accountability initiatives for their potential lives saved and harms avoided, as well as their costs and efforts.

Trends in Adverse Event Rates in Hospitalized Patients, 2010-2019.

Importance: Patient safety is a US national priority, yet lacks a comprehensive assessment of progress over the past decade. Objective: To determine the change in the rate of adverse events in hospitalized patients. Design, Setting, and Participants: This serial cross-sectional study used data from the Medicare Patient Safety Monitoring System from 2010 to 2019 to assess in-hospital adverse events in patients. The study included 244 542 adult patients hospitalized in 3156 US acute care hospitals across 4 condition groups from 2010 through 2019: acute myocardial infarction (17%), heart failure (17%), pneumonia (21%), and major surgical procedures (22%); and patients hospitalized from 2012 through 2019 for all other conditions (22%). Exposures: Adults aged 18 years or older hospitalized during each included calendar year. Main Outcomes and Measures: Information on adverse events (abstracted from medical records) included 21 measures across 4 adverse event domains: adverse drug events, hospital-acquired infections, adverse events after a procedure, and general adverse events (hospital-acquired pressure ulcers and falls). The outcomes were the total change over time for the observed and risk-adjusted adverse event rates in the subpopulations. Results: The study sample included 190 286 hospital discharges combined in the 4 condition-based groups of acute myocardial infarction, heart failure, pneumonia, and major surgical procedures (mean age, 68.0 [SD, 15.9] years; 52.6% were female) and 54 256 hospital discharges for the group including all other conditions (mean age, 57.7 [SD, 20.7] years; 59.8% were female) from 3156 acute care hospitals across the US. From 2010 to 2019, the total change was from 218 to 139 adverse events per 1000 discharges for acute myocardial infarction, from 168 to 116 adverse events per 1000 discharges for heart failure, from 195 to 119 adverse events per 1000 discharges for pneumonia, and from 204 to 130 adverse events per 1000 discharges for major surgical procedures. From 2012 to 2019, the rate of adverse events for all other conditions remained unchanged at 70 adverse events per 1000 discharges. After adjustment for patient and hospital characteristics, the annual change represented by relative risk in all adverse events per 1000 discharges was 0.94 (95% CI, 0.93-0.94) for acute myocardial infarction, 0.95 (95% CI, 0.94-0.96) for heart failure, 0.94 (95% CI, 0.93-0.95) for pneumonia, 0.93 (95% CI, 0.92-0.94) for major surgical procedures, and 0.97 (95% CI, 0.96-0.99) for all other conditions. The risk-adjusted adverse event rates declined significantly in all patient groups for adverse drug events, hospital-acquired infections, and general adverse events. For patients in the major surgical procedures group, the risk-adjusted rates of events after a procedure declined significantly. Conclusions and Relevance: In the US between 2010 and 2019, there was a significant decrease in the rates of adverse events abstracted from medical records for patients admitted for acute myocardial infarction, heart failure, pneumonia, and major surgical procedures and there was a significant decrease in the adjusted rates of adverse events between 2012 and 2019 for all other conditions. Further research is needed to understand the extent to which these trends represent a change in patient safety.

Variation in Risk-standardized Rates and Causes of Unplanned Hospital Visits Within 7 Days of Hospital Outpatient Surgery.

OBJECTIVES: The objectives of this study were to compare risk-standardized hospital visit ratios of the predicted to expected number of unplanned hospital visits within 7 days of same-day surgeries performed at US hospital outpatient departments (HOPDs) and to describe the causes of hospital visits. SUMMARY OF BACKGROUND DATA: More than half of procedures in the US are performed in outpatient settings, yet little is known about facility-level variation in short-term safety outcomes. METHODS: The study cohort included 1,135,441 outpatient surgeries performed at 4058 hospitals between October 1, 2015 and September 30, 2016 among Medicare Fee-for-Service beneficiaries aged ≥65 years. Hospital-level, risk-standardized measure scores of unplanned hospital visits (emergency department visits, observation stays, and unplanned inpatient admissions) within 7 days of hospital outpatient surgery were calculated using hierarchical logistic regression modeling that adjusted for age, clinical comorbidities, and surgical procedural complexity. RESULTS: Overall, 7.8% of hospital outpatient surgeries were followed by an unplanned hospital visit within 7 days. Many of the leading reasons for unplanned visits were for potentially preventable conditions, such as urinary retention, infection, and pain. We found considerable variation in the risk-standardized ratio score across hospitals. The 203 best-performing HOPDs, at or below the 5th percentile, had at least 22% fewer unplanned hospital visits than expected, whereas the 202 worst-performing HOPDs, at or above the 95th percentile, had at least 29% more post-surgical visits than expected, given their case and surgical procedure mix. CONCLUSIONS: Many patients experience an unplanned hospital visit within 7 days of hospital outpatient surgery, often for potentially preventable reasons. The observed variation in performance across hospitals suggests opportunities for quality improvement.

Admission diagnoses among patients with heart failure: Variation by ACO performance on a measure of risk-standardized acute admission rates.

BACKGROUND: A key quality metric for Accountable Care Organizations (ACOs) is the rate of hospitalization among patients with heart failure (HF). Among this patient population, non-HF-related hospitalizations account for a substantial proportion of admissions. Understanding the types of admissions and the distribution of admission types across ACOs of varying performance may provide important insights for lowering admission rates. METHODS: We examined admission diagnoses among 220 Medicare Shared Savings Program ACOs in 2013. ACOs were stratified into quartiles by their performance on a measure of unplanned risk-standardized acute admission rates (RSAARs) among patients with HF. Using a previously validated algorithm, we categorized admissions by principal discharge diagnosis into: HF, cardiovascular/non-HF, and noncardiovascular. We compared the mean admission rates by admission type as well as the proportion of admission types across RSAAR quartiles (Q1-Q4). RESULTS: Among 220 ACOs caring for 227,356 patients with HF, the median (IQR) RSAARs per 100 person-years ranged from 64.5 (61.7-67.7) in Q1 (best performers) to 94.0 (90.1-99.9) in Q4 (worst performers). The mean admission rates by admission types for ACOs in Q1 compared with Q4 were as follows: HF admissions: 9.8 (2.2) vs 14.6 (2.8) per 100 person years (P < .0001); cardiovascular/non-HF admissions: 11.1 (1.6) vs 15.9 (2.6) per 100 person-years (P < .0001); and noncardiovascular admissions: 42.7 (5.4) vs 69.6 (11.3) per 100 person-years (P < .0001). The proportion of admission due to HF, cardiovascular/non-HF, and noncardiovascular conditions was 15.4%, 17.5%, and 67.1% in Q1 compared with 14.6%, 15.9%, and 69.4% in Q4 (P < .007). CONCLUSIONS: Although ACOs with the best performance on a measure of all-cause admission rates among people with HF tended to have fewer admissions for HF, cardiovascular/non-HF, and noncardiovascular conditions compared with ACOs with the worst performance (highest admission rates), the largest difference in admission rates were for noncardiovascular admission types. Across all ACOs, two-thirds of admissions of patients with HF were for noncardiovascular causes. These findings suggest that comprehensive approaches are needed to reduce the diverse admission types for which HF patients are at risk.

Hospital Characteristics Associated With Risk-standardized Readmission Rates.

BACKGROUND: Safety-net and teaching hospitals are somewhat more likely to be penalized for excess readmissions, but the association of other hospital characteristics with readmission rates is uncertain and may have relevance for hospital-centered interventions. OBJECTIVE: To examine the independent association of 8 hospital characteristics with hospital-wide 30-day risk-standardized readmission rate (RSRR). DESIGN: This is a retrospective cross-sectional multivariable analysis. SUBJECTS: US hospitals. MEASURES: Centers for Medicare and Medicaid Services specification of hospital-wide RSRR from July 1, 2013 through June 30, 2014 with race and Medicaid dual-eligibility added. RESULTS: We included 6,789,839 admissions to 4474 hospitals of Medicare fee-for-service beneficiaries aged over 64 years. In multivariable analyses, there was regional variation: hospitals in the mid-Atlantic region had the highest RSRRs [0.98 percentage points higher than hospitals in the Mountain region; 95% confidence interval (CI), 0.84-1.12]. For-profit hospitals had an average RSRR 0.38 percentage points (95% CI, 0.24-0.53) higher than public hospitals. Both urban and rural hospitals had higher RSRRs than those in medium metropolitan areas. Hospitals without advanced cardiac surgery capability had an average RSRR 0.27 percentage points (95% CI, 0.18-0.36) higher than those with. The ratio of registered nurses per hospital bed was not associated with RSRR. Variability in RSRRs among hospitals of similar type was much larger than aggregate differences between types of hospitals. CONCLUSIONS: Overall, larger, urban, academic facilities had modestly higher RSRRs than smaller, suburban, community hospitals, although there was a wide range of performance. The strong regional effect suggests that local practice patterns are an important influence. Disproportionately high readmission rates at for-profit hospitals may highlight the role of financial incentives favoring utilization.

Differences in Colonoscopy Quality Among Facilities: Development of a Post-Colonoscopy Risk-Standardized Rate of Unplanned Hospital Visits.

BACKGROUND & AIMS: Colonoscopy is a common procedure, yet little is known about variations in colonoscopy quality among outpatient facilities. We developed an outcome measure to profile outpatient facilities by estimating risk-standardized rates of unplanned hospital visits within 7 days of colonoscopy. METHODS: We used a 20% sample of 2010 Medicare outpatient colonoscopy claims (331,880 colonoscopies performed at 8140 facilities) from patients ≥65 years or older, and developed a patient-level logistic regression model to estimate the risk of unplanned hospital visits (ie, emergency department visits, observation stays, and inpatient admissions) within 7 days of colonoscopy. We then used the patient-level risk model variables and hierarchical logistic regression to estimate facility rates of risk-standardized unplanned hospital visits using data from the Healthcare Cost and Utilization Project (325,811 colonoscopies at 992 facilities), from 4 states containing 100% of colonoscopies per facility. RESULTS: Outpatient colonoscopies were followed by 5412 unplanned hospital visits within 7 days (16.3/1000 colonoscopies). Hemorrhage, abdominal pain, and perforation were the most common causes of unplanned hospital visits. Fifteen variables were independently associated with unplanned hospital visits (c = 0.67). A history of fluid and electrolyte imbalance (odds ratio [OR] = 1.43; 95% confidence interval [CI]: 1.29-1.58), psychiatric disorders (OR = 1.34; 95% CI: 1.22-1.46), and, in the absence of prior arrhythmia, increasing age past 65 years (aged >85 years vs 65-69 years: OR = 1.87; 95% CI: 1.54-2.28) were most strongly associated. The facility risk-standardized unplanned hospital visits calculated using Healthcare Cost and Utilization Project data showed significant variation (median 12.3/1000; 5th-95th percentile, 10.5-14.6/1000). Median risk-standardized unplanned hospital visits were comparable between ambulatory surgery centers and hospital outpatient departments (each was 10.2/1000), and ranged from 16.1/1000 in the Northeast to 17.2/1000 in the Midwest. CONCLUSIONS: We calculated a risk-adjusted measure of outpatient colonoscopy quality, which shows important variation in quality among outpatient facilities. This measure can make transparent the extent to which patients require follow-up hospital care, help inform patient choices, and assist in quality-improvement efforts.

Association of hospital volume with readmission rates: a retrospective cross-sectional study.

OBJECTIVE: To examine the association of hospital volume (a marker of quality of care) with hospital readmission rates. DESIGN: Retrospective cross-sectional study. SETTING: 4651 US acute care hospitals. STUDY DATA: 6,916,644 adult discharges, excluding patients receiving psychiatric or medical cancer treatment. MAIN OUTCOME MEASURES: We used Medicare fee-for-service data from 1 July 2011 to 30 June 2012 to calculate observed-to-expected, unplanned, 30 day, standardized readmission rates for hospitals and for specialty cohorts medicine, surgery/gynecology, cardiorespiratory, cardiovascular, and neurology. We assessed the association of hospital volume by quintiles with 30 day, standardized readmission rates, with and without adjustment for hospital characteristics (safety net status, teaching status, geographic region, urban/rural status, nurse to bed ratio, ownership, and cardiac procedure capability. We also examined associations with the composite outcome of 30 day, standardized readmission or mortality rates. RESULTS: Mean 30 day, standardized readmission rate among the fifth of hospitals with the lowest volume was 14.7 (standard deviation 5.3) compared with 15.9 (1.7) among the fifth of hospitals with the highest volume (P<0.001). We observed the same pattern of lower readmission rates in the lowest versus highest volume hospitals in the specialty cohorts for medicine (16.6 v 17.4, P<0.001), cardiorespiratory (18.5 v 20.5, P<0.001), and neurology (13.2 v 14.0, p=0.01) cohorts; the cardiovascular cohort, however, had an inverse association (14.6 v 13.7, P<0.001). These associations remained after adjustment for hospital characteristics except in the cardiovascular cohort, which became non-significant, and the surgery/gynecology cohort, in which the lowest volume fifth of hospitals had significantly higher standardized readmission rates than the highest volume fifth (difference 0.63 percentage points (95% confidence interval 0.10 to 1.17), P=0.02). Mean 30 day, standardized mortality or readmission rate was not significantly different between highest and lowest volume fifths (20.4 v 20.2, P=0.19) and was highest in the middle fifth of hospitals (range 20.6-20.8). CONCLUSIONS: Standardized readmission rates are lowest in the lowest volume hospitals-opposite from the typical association of greater hospital volume with better outcomes. This association was independent of hospital characteristics and was only partially attenuated by examining mortality and readmission together. Our findings suggest that readmissions are associated with different aspects of care than mortality or complications.

Development and use of an administrative claims measure for profiling hospital-wide performance on 30-day unplanned readmission.

BACKGROUND: Existing publicly reported readmission measures are condition-specific, representing less than 20% of adult hospitalizations. An all-condition measure may better measure quality and promote innovation. OBJECTIVE: To develop an all-condition, hospital-wide readmission measure. DESIGN: Measure development study. SETTING: 4821 U.S. hospitals. PATIENTS: Medicare fee-for-service beneficiaries aged 65 years or older. MEASUREMENTS: Hospital-level, risk-standardized unplanned readmissions within 30 days of discharge. The measure uses Medicare fee-for-service claims and is a composite of 5 specialty-based, risk-standardized rates for medicine, surgery/gynecology, cardiorespiratory, cardiovascular, and neurology cohorts. The 2007-2008 admissions were randomly split for development and validation. Models were adjusted for age, principal diagnosis, and comorbid conditions. Calibration in Medicare and all-payer data was examined, and hospital rankings in the development and validation samples were compared. RESULTS: The development data set contained 8 018 949 admissions associated with 1 276 165 unplanned readmissions (15.9%). The median hospital risk-standardized unplanned readmission rate was 15.8 (range, 11.6 to 21.9). The 5 specialty cohort models accurately predicted readmission risk in both Medicare and all-payer data sets for average-risk patients but slightly overestimated readmission risk at the extremes. Overall hospital risk-standardized readmission rates did not differ statistically in the split samples (P = 0.71 for difference in rank), and 76% of hospitals' validation-set rankings were within 2 deciles of the development rank (24% were more than 2 deciles). Of hospitals ranking in the top or bottom deciles, 90% remained within 2 deciles (10% were more than 2 deciles) and 82% remained within 1 decile (18% were more than 1 decile). LIMITATION: Risk adjustment was limited to that available in claims data. CONCLUSION: A claims-based, hospital-wide unplanned readmission measure for profiling hospitals produced reasonably consistent results in different data sets and was similarly calibrated in both Medicare and all-payer data. PRIMARY FUNDING SOURCE: Centers for Medicare & Medicaid Services.

Development of a clinical registry-based 30-day readmission measure for coronary artery bypass grafting surgery.

BACKGROUND: Reducing readmissions is a major healthcare reform goal, and reimbursement penalties are imposed for higher-than-expected readmission rates. Most readmission risk models and performance measures are based on administrative rather than clinical data. METHODS AND RESULTS: We examined rates and predictors of 30-day all-cause readmission following coronary artery bypass grafting surgery by using nationally representative clinical data (2008-2010) from the Society of Thoracic Surgeons National Database linked to Medicare claims records. Among 265 434 eligible Medicare records, 226 960 (86%) were successfully linked to Society of Thoracic Surgeons records; 162 572 (61%) isolated coronary artery bypass grafting admissions constituted the study cohort. Logistic regression was used to identify readmission risk factors; hierarchical regression models were then estimated. Risk-standardized readmission rates ranged from 12.6% to 23.6% (median, 16.8%) among 846 US hospitals with ≥30 eligible cases and ≥90% of eligible Centers for Medicare and Medicaid Services records linked to the Society of Thoracic Surgeons database. Readmission predictors (odds ratios [95% confidence interval]) included dialysis (2.02 [1.87-2.19]), severe chronic lung disease (1.58 [1.49-1.68]), creatinine (2.5 versus 1.0 or lower:1.49 [1.41-1.57]; 2.0 versus 1.0 or lower: 1.37 [1.32-1.43]), insulin-dependent diabetes mellitus (1.45 [1.39-1.51]), obesity in women (body surface area 2.2 versus 1.8: 1.44 [1.35-1.53]), female sex (1.38 [1.33-1.43]), immunosuppression (1.38 [1.28-1.49]), preoperative atrial fibrillation (1.36 [1.30-1.42]), age per 10-year increase (1.36 [1.33-1.39]), recent myocardial infarction (1.24 [1.08-1.42]), and low body surface area in men (1.22 [1.14-1.30]). C-statistic was 0.648. Fifty-two hospitals (6.1%) had readmission rates statistically better or worse than expected. CONCLUSIONS: A coronary artery bypass grafting surgery readmission measure suitable for public reporting was developed by using the national Society of Thoracic Surgeons clinical data linked to Medicare readmission claims.

Variation in hospital-level risk-standardized complication rates following elective primary total hip and knee arthroplasty.

BACKGROUND: Little is known about the variation in complication rates among U.S. hospitals that perform elective total hip arthroplasty (THA) and total knee arthroplasty (TKA) procedures. The purpose of this study was to use National Quality Forum (NQF)-endorsed hospital-level risk-standardized complication rates to describe variations in, and disparities related to, hospital quality for elective primary THA and TKA procedures performed in U.S. hospitals. METHODS: We conducted a cross-sectional analysis of national Medicare Fee-for-Service data. The study cohort included 878,098 Medicare fee-for-service beneficiaries, sixty-five years or older, who underwent elective THA or TKA from 2008 to 2010 at 3479 hospitals. Both medical and surgical complications were included in the composite measure. Hospital-specific complication rates were calculated from Medicare claims with use of hierarchical logistic regression to account for patient clustering and were risk-adjusted for age, sex, and patient comorbidities. We determined whether hospitals with higher proportions of Medicaid patients and black patients had higher risk-standardized complication rates. RESULTS: The crude rate of measured complications was 3.6%. The most common complications were pneumonia (0.86%), pulmonary embolism (0.75%), and periprosthetic joint infection or wound infection (0.67%). The median risk-standardized complication rate was 3.6% (range, 1.8% to 9.0%). Among hospitals with at least twenty-five THA and TKA patients in the study cohort, 103 (3.6%) were better and seventy-five (2.6%) were worse than expected. Hospitals with the highest proportion of Medicaid patients had slightly higher but similar risk-standardized complication rates (median, 3.6%; range, 2.0% to 7.1%) compared with hospitals in the lowest decile (3.4%; 1.7% to 6.2%). Findings were similar for the analysis involving the proportion of black patients. CONCLUSIONS: There was more than a fourfold difference in risk-standardized complication rates across U.S. hospitals in which elective THA and TKA are performed. Although hospitals with higher proportions of Medicaid and black patients had rates similar to those of hospitals with lower proportions, there is a continued need to monitor for disparities in outcomes. These findings suggest there are opportunities for quality improvement among hospitals in which elective THA and TKA procedures are performed.

Mortality and readmission for patients with heart failure among U.S. News & World Report's top heart hospitals.

BACKGROUND: The rankings of "America's Best Hospitals" by U.S. News & World Report are influential, but the performance of ranked hospitals in caring for patients with routine cardiac conditions such as heart failure is not known. METHODS AND RESULTS: Using hierarchical regression models based on medical administrative data from the period July 1, 2005, to June 30, 2006, we calculated risk-standardized mortality rates and risk-standardized readmission rates for ranked and nonranked hospitals in the treatment of heart failure. The mortality analysis examined 14 813 patients in 50 ranked hospitals and 409 806 patients in 4761 nonranked hospitals. The readmission analysis included 16 641 patients in 50 ranked hospitals and 458 473 patients in 4627 nonranked hospitals. Mean 30-day risk-standardized mortality rates were lower in ranked versus nonranked hospitals (10.1% versus 11.2%, P<0.01), whereas mean 30-day risk-standardized readmission rates were no different between ranked and nonranked hospitals (23.6% versus 23.8%, P=0.40). The 30-day risk-standardized mortality rates varied widely for both ranked and nonranked hospitals, ranging from 7.9% to 12.4% for ranked hospitals and from 7.1% to 17.5% for nonranked hospitals. The 30-day risk-standardized readmission rates also spanned a large range, from 18.7% to 29.3% for ranked hospitals and from 19.2% to 29.8% for nonranked hospitals. CONCLUSIONS: Hospitals ranked by U.S. News & World Report as "America's Best Hospitals" in "Heart & Heart Surgery" are more likely than nonranked hospitals to have a significantly lower than expected 30-day mortality rate, but there was much overlap in performance. For readmission, the rates were similar in ranked and nonranked hospitals.

Expression of angiogenic VEGF-A (soluble isoforms 121, 165) and lymphangiogenic VEGF-C in colorectal cancers with micro-satellite instability.

BACKGROUND AND OBJECTIVES: Colorectal cancers (CRC) with high-level micro-satellite instability (MSI-H) show reduced metastatic potential and better prognosis compared to stage-matched stable (MSS) cancers. Angiogenesis/lymphangiogenesis, central to tumour growth and spread, is mediated by vascular endothelial growth factor (VEGF) cytokines, but little is known of their relationship to MSI. METHODS: In this study, 67 sporadic CRC with identified MSI status, and 8 samples of normal colon were analysed for VEGF-A soluble isoforms (VEGF-121/VEGF-165) and VEGF-C gene transcription (by RT-PCR and scanning densitometry), and blood vessel density (BVD; measuring angiogenesis) and VEGF-C protein expression (measuring lymphangiogenesis). RESULTS: Compared to normal colon, VEGF-165 transcription was reduced (P < 0.05), but VEGF-121 transcription was higher in MSS (P < 0.06) and MSI-L (P < 0.01) cancers (but similar in MSI-H). VEGF-165 transcription was unrelated to MSI, but VEGF-121 transcription was elevated in MSI-L (P < 0.06). There was a weak inverse correlation with VEGF-121 transcription and Dukes stage (P < 0.09), and with BVD and MSI (P < 0.09). With a singular di-nucleotide loci mutation (MSI-L), VEGF-121 (P < 0.03) and VEGF-C (P < 0.04) transcription was elevated. CONCLUSIONS: MSI-H cancers have reduced angiogenic/lymphangiogenic potential, and transcription of VEGF-121 may be important in early growth and spread of CRC. Elevated VEGF-121 and VEGF-C transcription with singular di-nucleotide mutations may aid in the identification of distinct MSI-L cancers.