The Impact of COVID-19 on Postdischarge Outcomes for Dialysis Patients in the United States: Evidence from Medicare Claims Data.

Background: Recent investigations have shown that, on average, patients hospitalized with coronavirus disease 2019 (COVID-19) have a poorer postdischarge prognosis than those hospitalized without COVID-19, but this effect remains unclear among patients with end-stage kidney disease (ESKD) who are on dialysis. Methods: Leveraging a national ESKD patient claims database administered by the US Centers for Medicare and Medicaid Services, we conducted a retrospective cohort study that characterized the effects of in-hospital COVID-19 on all-cause unplanned readmission and death within 30 days of discharge for patients on dialysis. Included in this study were 436,745 live acute-care hospital discharges of 222,154 Medicare beneficiaries on dialysis from 7871 Medicare-certified dialysis facilities between January 1 and October 31, 2020. Adjusting for patient demographics, clinical characteristics, and prevalent comorbidities, we fit facility-stratified Cox cause-specific hazard models with two interval-specific (1-7 and 8-30 days after hospital discharge) effects of in-hospital COVID-19 and effects of prehospitalization COVID-19. Results: The hazard ratios due to in-hospital COVID-19 over the first 7 days after discharge were 95% CI, 1.53 to 1.65 for readmission and 95% CI, 1.38 to 1.70 for death, both with P<0.001. For the remaining 23 days, the hazard ratios were 95% CI, 0.89 to 0.96 and 95% CI, 0.86 to 1.07, with P<0.001 and P=0.50, respectively. Effects of prehospitalization COVID-19 were mostly nonsignificant. Conclusions: In-hospital COVID-19 had an adverse effect on both postdischarge readmission and death over the first week. With the surviving patients having COVID-19 substantially selected from those hospitalized, in-hospital COVID-19 was associated with lower rates of readmission and death starting from the second week.

The profile inter-unit reliability.

To assess the quality of health care, patient outcomes associated with medical providers (eg, dialysis facilities) are routinely monitored in order to identify poor (or excellent) provider performance. Given the high stakes of such evaluations for payment as well as public reporting of quality, it is important to assess the reliability of quality measures. A commonly used metric is the inter-unit reliability (IUR), which is the proportion of variation in the measure that comes from inter-provider differences. Despite its wide use, however, the size of the IUR has little to do with the usefulness of the measure for profiling extreme outcomes. A large IUR can signal the need for further risk adjustment to account for differences between patients treated by different providers, while even measures with an IUR close to zero can be useful for identifying extreme providers. To address these limitations, we propose an alternative measure of reliability, which assesses more directly the value of a quality measure in identifying (or profiling) providers with extreme outcomes. The resulting metric reflects the extent to which the profiling status is consistent over repeated measurements. We use national dialysis data to examine this approach on various measures of dialysis facilities.

Reevaluation of the Kidney Donor Risk Index.

BACKGROUND: The Kidney Donor Risk Index (KDRI) is a score applicable to deceased kidney donors which reflects relative graft failure risk associated with deceased donor characteristics. The KDRI is widely used in kidney transplant outcomes research. Moreover, an abbreviated version of KDRI is the basis, for allocation purposes, of the "top 20%" designation for deceased donor kidneys. Data upon which the KDRI model was based used kidney transplants performed between 1995 and 2005. Our purpose in this report was to evaluate the need to update the coefficients in the KDRI formula, with the objective of either (a) proposing new coefficients or (b) endorsing continued used of the existing formula. METHODS: Using data obtained from the Scientific Registry of Transplant Recipients, we analyzed n = 156069 deceased donor adult kidney transplants occurring from 2000 to 2016. Cox regression was used to model the risk of graft failure. We then tested for differences between the original and updated regression coefficients and compared the performance of the original and updated KDRI formulas with respect to discrimination and predictive accuracy. RESULTS: In testing for equality between the original and updated KDRIs, few coefficients were significantly different. Moreover, the original and updated KDRI yielded very similar risk discrimination and predictive accuracy. CONCLUSIONS: Overall, our results indicate that the original KDRI is robust and is not meaningfully improved by an update derived through modeling analogous to that originally employed.

Risk Adjustment and the Assessment of Disparities in Dialysis Mortality Outcomes.

Standardized mortality ratios (SMRs) reported by Medicare compare mortality at individual dialysis facilities with the national average, and are currently adjusted for race. However, whether the adjustment for race obscures or clarifies disparities in quality of care for minority groups is unknown. Cox model-based SMRs were computed with and without adjustment for patient race for 5920 facilities in the United States during 2010. The study population included virtually all patients treated with dialysis during this period. Without race adjustment, facilities with higher proportions of black patients had better survival outcomes; facilities with the highest percentage of black patients (top 10%) had overall mortality rates approximately 7% lower than expected. After adjusting for within-facility racial differences, facilities with higher proportions of black patients had poorer survival outcomes among black and non-black patients; facilities with the highest percentage of black patients (top 10%) had mortality rates approximately 6% worse than expected. In conclusion, accounting for within-facility racial differences in the computation of SMR helps to clarify disparities in quality of health care among patients with ESRD. The adjustment that accommodates within-facility comparisons is key, because it could also clarify relationships between patient characteristics and health care provider outcomes in other settings.

Variation in access to the liver transplant waiting list in the United States.

BACKGROUND: We sought to compare liver transplant waiting list access by demographics and geography relative to the pool of potential liver transplant candidates across the United States using a novel metric of access to care, termed a liver wait-listing ratio (LWR). METHODS: We calculated LWRs from national liver transplant registration data and liver mortality data from the Scientific Registry of Transplant Recipients and the National Center for Healthcare Statistics from 1999 to 2006 to identify variation by diagnosis, demographics, geography, and era. RESULTS: Among patients with ALF and CLF, African Americans had significantly lower access to the waiting list compared with whites (acute: 0.201 versus 0.280; pre-MELD 0.201 versus 0.290; MELD era: 0.201 versus 0.274; all, P<0.0001) (chronic: 0.084 versus 0.163; pre-MELD 0.085 versus 0.179; MELD 0.084 versus 0.154; all, P<0.0001). Hispanics and whites had similar LWR in both eras (both P>0.05). In the MELD era, female subjects had greater access to the waiting list compared with male subjects (acute: 0.428 versus 0.154; chronic: 0.158 versus 0.140; all, P<0.0001). LWRs varied by three-fold by state (pre-MELD acute: 0.122-0.418, chronic: 0.092-0.247; MELD acute: 0.121-0.428, chronic: 0.092-0.243). CONCLUSIONS: The marked inequity in early access to liver transplantation underscores the need for local and national policy initiatives to affect this disparity.

Life-course socioeconomic position and incidence of dementia and cognitive impairment without dementia in older Mexican Americans: results from the Sacramento area Latino study on aging.

There have been few investigations of the link between changes in life-course socioeconomic position (SEP) and cognitive decline or incidence of dementia. The authors examined the impact of changes in life-course SEP on incidence of dementia and cognitive impairment but not dementia (CIND) over a decade of follow-up. Participants of Mexican origin (n = 1,789) were members of the Sacramento Area Latino Study on Aging cohort. Incidence of dementia/CIND was ascertained by using standard diagnostic criteria. SEP indicators at 3 life stages (childhood, adulthood, and midlife) were used to derive a measure of cumulative SEP (range, 0 to 8) and SEP mobility. Nearly 24% of the sample maintained a low SEP throughout life. Hazard ratios and 95% confidence intervals were computed from Cox proportional hazards regression models. In fully adjusted models, participants with a continuously high SEP had lower hazard ratios for dementia/CIND compared with those with a continuously low SEP at all 3 life stages (hazard ratio = 0.49, 95% confidence interval: 0.24, 0.98; P = 0.04). In age-adjusted models, participants experienced a 16% greater hazard of dementia/CIND with every 1-unit increase in cumulative SEP disadvantage across the life course (hazard ratio = 1.16, 95% confidence interval: 1.01, 1.33; P = 0.04). Early exposures to social disadvantage may increase the risk of late-life dementia.

A shared random effects model for censored medical costs and mortality.

In this paper, we propose a model for medical costs recorded at regular time intervals, e.g. every month, as repeated measures in the presence of a terminating event, such as death. Prior models have related monthly medical costs to time since entry, with extra costs at the final observations at the time of death. Our joint model for monthly medical costs and survival time incorporates two important new features. First, medical cost and survival may be correlated because more 'frail' patients tend to accumulate medical costs faster and die earlier. A joint random effects model is proposed to account for the correlation between medical costs and survival by a shared random effect. Second, monthly medical costs usually increase during the time period prior to death because of the intensive care for dying patients. We present a method for estimating the pattern of cost prior to death, which is applicable if the pattern can be characterized as an additive effect that is limited to a fixed time interval, say b units of time before death. This 'turn back time' method for censored observations censors cost data b units of time before the actual censoring time, while keeping the actual censoring time for the survival data. Time-dependent covariates can be included. Maximum likelihood estimation and inference are carried out through a Monte Carlo EM algorithm with a Metropolis-Hastings sampler in the E-step. An analysis of monthly outpatient EPO medical cost data for dialysis patients is presented to illustrate the proposed methods.

Career disaffection among surgeons in the era of managed care.

The purpose of this paper is to assess career satisfaction of surgeons in the era of managed care. The method of this assessment is by membership survey of the Southeastern Surgical Congress and the Western Surgical Association. Members were queried about their demographic characteristics, some aspects of the business of their practices, their attitudes toward retirement, their perception of the effectiveness of organized medicine as a socioeconomic advocate, and a comparison of each surgeon's career satisfaction before and during the era of managed care. Three hundred seventy-three usable surveys were returned, computerized, and analyzed statistically. Summaries of categorical variables are presented as percentages for various groupings of the categorical set. Results reveal a broad-based career disaffection in all areas queried, most notably in the business of surgical practice, attitude toward retirement and retirement alternatives, and the advocacy role of organized medicine for their issues. There is an almost unanimous desire for the American College of Surgeons to become their aggressive socioeconomic advocate. The data support a conclusion that surgeons perceive they are not represented in a realistic manner with the insurance companies and the government when their core issues are decided.