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Background: The Risk Stratification Index was developed from 35 million Medicare hospitalizations from 2001 to 2006 but has yet to be externally validated on an independent large national data set, nor has it been calibrated. Finally, the Medicare Analysis and Provider Review file now allows 25 rather than 9 diagnostic codes and 25 rather than 6 procedure codes and includes present-on-admission flags. The authors sought to validate the index on new data, test the impact of present-on-admission codes, test the impact of the expansion to 25 diagnostic and procedure codes, and calibrate the model.Methods: The authors applied the original index coefficients to 39,753,036 records from the 2007-2012 Medicare Analysis data set and calibrated the model. The authors compared their results with 25 diagnostic and 25 procedure codes, with results after restricting the model to the first 9 diagnostic and 6 procedure codes and to codes present on admission.Results: The original coefficients applied to the 2007-2012 data set yielded C statistics of 0.83 for 1-yr mortality, 0.84 for 30-day mortality, 0.94 for in-hospital mortality, and 0.86 for median length of stay-values nearly identical to those originally reported. Calibration equations performed well against observed outcomes. The 2007-2012 model discriminated similarly when codes were restricted to nine diagnostic and six procedure codes. Present-on-admission models were about 10% less predictive for in-hospital mortality and hospital length of stay but were comparably predictive for 30-day and 1-yr mortality.Conclusions: Risk stratification performance was largely unchanged by additional diagnostic and procedure codes and only slightly worsened by restricting analysis to codes present on admission. The Risk Stratification Index, after calibration, thus provides excellent discrimination and calibration for important health services outcomes and thus appears to be a good basis for making hospital comparisons. [ABSTRACT FROM AUTHOR]

Objective: The validity of risk-adjustment methods based on administrative data has been questioned because hospital referral regions with higher diagnosis frequencies report lower case-fatality rates, implying that diagnoses do not track the underlying health risk. The objective of this study is to test the hypothesis that regional variation of diagnostic frequency in inpatient records is not associated with different coding practices but a reflection of the underlying health risks., Design: We applied two stratification methods to Medicare Analysis and Provider Review data from 2009 through 2014: (1) the number of chronic conditions; and, (2) quartiles of Risk Stratification Index (RSI)-defined risk. After sorting hospital referral regions into quintiles of diagnostic frequency, we examined all-cause mortality., Setting: Medicare Analysis and Provider Review administrative database., Participants: 18 126 301 hospitalised Medicare fee-for-service beneficiaries aged 65 or older who had at least one hospital-based procedure between 2009 and 2014., Exposure: Coding frequency and baseline regional population risk factors by hospital referral region., Primary and Secondary Outcomes and Measures: One year all-cause mortality in patients having the same number of chronic conditions or within the same RSI score quartile across US health referral regions, grouped by diagnostic frequency., Results: No consistent relationship between diagnostic frequency and mortality in the risk stratum defined by number of chronic conditions was detected. In the strata defined by RSI quartile, there was no decrease in mortality as a function of diagnostic frequency. Instead, adjusted mortality was positively correlated with socioeconomic risk factors., Conclusions: Using present-on-admission codes only, diagnostic frequency among inpatients with at least one hospital-based procedure appears to be consequent to differences in baseline population health status, rather than diagnostic coding practices. In this population, claims-based risk-adjustment using RSI appears to be useful for assessing hospital outcomes and performance., Competing Interests: Competing interests: LL, GFC, NGC and VG report no conflicts of interest. DS and VS have stock options in HDAI. DS also received consulting payments from HDAI and funding support to attend a work meeting at the Lown Institute., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

To investigate whether elements of Chinese culture, such as son preference, influence women's mode of child delivery, this paper analyzes how fetal sex affects C-section rates among Chinese mothers compared with Japanese mothers in the United States. It uses birth certificate data from 1990 to 2000, a period when women were routinely able to learn the sex of the fetus during pregnancy. Compared with Japanese mothers, Chinese mothers were 1 percentage point more likely to undergo C-section when giving birth to boys than when giving birth to girls. This result is robust to the addition of a rich set of controls and the restriction of the sample to infants without congenital diseases or anomalies at birth. The effects are concentrated in subgroups that are more likely to prefer sons-specifically, where both parents are Asian or where mothers are first-generation immigrants. The findings offer valuable insights for health professionals into culturally driven pregnancy behaviors among Chinese women, potentially enabling them to offer more culturally appropriate healthcare as they support women in making a healthy transition to motherhood., (Copyright © 2019 Elsevier B.V. All rights reserved.)