Background
While health-related social needs (HRSN) are known to compromise health, work to date has not clearly demonstrated the relationship between clinically acknowledged social needs, via ICD-10 ...Z-codes, and readmission.
Objective
Assess the rate of 30-, 60-, and 90-day readmission by the level of ICD-10-identified social need. In addition, we examined the associations between demographics, social need, hospital characteristics, and comorbidities on 30-day readmission.
Design
Retrospective study using the 2017 Nationwide Readmission Database
Participants
We identified 5 domains of HRSN from ICD-10 diagnosis codes including employment, family, housing, psychosocial, and socioeconomic status (SES) and identified how many and which an individual was coded with during the year.
Main Measures
The proportion of patients with 30-, 60-, and 90-day readmission stratified by the number of HRSN domains with a multivariable logistic regression to examine the relationship between the number/type of and readmission adjusting for sex, age, payer, hospital characteristics, functional limitations, and comorbidities.
Key Results
From 13,217,506 patients, only 2.4% had at least one HRSN diagnosis. Among patients without HRSN, 11.5% had a 30-day readmission, compared to 27.0% of those with 1 domain, increasing to 63.5% for patients with codes in 5 domains. Similar trends were observed for 60- and 90-day readmission; 78.7% of patients with documented HRSN in all 5 domains were hospitalized again within 90 days. The adjusted odds ratio for readmission for individuals with all 5 domains was 12.55 (95% CI: 9.04, 17.43). Housing and employment emerged as two of the most commonly documented HRSN, as well as having the largest adjusted odds ratio.
Conclusions
There is a dose-response relationship between the number of HRSN diagnoses and hospital readmission. This work calls attention to the need to develop interventions to reduce readmissions for those at social risk and demonstrates the significance of ICD-10 Z-codes in health outcomes studies.
Summary
Objective
To examine national trends of pediatric epilepsy surgery usage in the United States between 1997 and 2009.
Methods
We performed a serial cross‐sectional study of pediatric epilepsy ...surgery using triennial data from the Kids’ Inpatient Database from 1997 to 2009. The rates of epilepsy surgery for lobectomies, partial lobectomies, and hemispherectomies in each study year were calculated based on the number of prevalent epilepsy cases in the corresponding year. The age‐race‐sex adjusted rates of surgeries were also estimated. Mann‐Kendall trend test was used to test for changes in the rates of surgeries over time. Multivariable regression analysis was also performed to estimate the effect of time, age, race, and sex on the annual incidence of epilepsy surgery.
Results
The rates of pediatric epilepsy surgery increased significantly from 0.85 epilepsy surgeries per 1,000 children with epilepsy in 1997 to 1.44 epilepsy surgeries per 1,000 children with epilepsy in 2009. An increment in the rates of epilepsy surgeries was noted across all age groups, in boys and girls, all races, and all payer types. The rate of increase was lowest in blacks and in children with public insurance. The overall number of surgical cases for each study year was lower than 35% of children who were expected to have surgery, based on the estimates from the Connecticut Study of Epilepsy.
Significance
In contrast to adults, pediatric epilepsy surgery numbers have increased significantly in the past decade. However, epilepsy surgery remains an underutilized treatment for children with epilepsy. In addition, black children and those with public insurance continue to face disparities in the receipt of epilepsy surgery.
The Affordable Care Act (ACA) removed copayments for screening mammography and colonoscopy in Medicare beneficiaries, but its clinical impact is unknown.
Using a 5% random sample of Medicare claims ...from 2009 through 2012 in individuals age 70 years or older who were due for screening, we examined claims for screening mammography and screening or surveillance colonoscopy for two years prior to ACA (2009-2010) and two years post-ACA (2011-2012). Receipt of the procedures at the patient level was compared across years using generalized estimating equations. Statistical tests were two-sided.
Compared with 2009, we found an increase in mammography uptake during the ACA coverage period, with multivariable odds ratios (MOR) of 1.22 (95% confidence interval CI = 1.20 to 1.25, P < .001) for 2011 and 1.17 (95% CI = 1.15 to 1.20, P < .001) for 2012 and less change in 2010 (OR = 1.03, 95% CI = 1.01 to 1.05, P = .01). In contrast to mammography, uptake of screening or surveillance colonoscopy decreased in 2012 (MOR = 0.95, 95% CI = 0.92 to 0.98, P = .002) compared with 2009, with no change in 2010 (MOR = 1.01, 95% CI = 0.99 to 1.04, P = .47) or 2011 (MOR = 1.01, 95% CI = 0.99 to 1.04, P = .34). Other factors associated with procedure receipt included younger age and prior preventive health visits. In an analysis restricted to patients age 70 to 74 years, colonoscopy use increased slightly in 2011 but was unchanged in 2012, and the findings by year for mammography were consistent with the main analysis.
Following ACA implementation with concomitant reduction in out-of-pocket expenditures, there was a statistically significant increment in mammography uptake but not colonoscopy. This suggests that affordability is a necessary but not sufficient facilitator of preventive services.
Background
Black men and men with end‐stage kidney disease have lower rates of treatment and higher mortality for prostate cancer. We studied the interaction of end‐stage kidney disease (ESKD) with ...Black race for treatment rates and mortality for men with prostate cancer.
Methods and Results
We included 516 Black and 551 White men with ESKD before prostate cancer 22,299 Black men, and 141,821 White men without ESKD who were 40 years or older from the Surveillance, Epidemiology, and End‐Results‐Medicare data (2004–2016). All Black men with or without ESKD and White men with ESKD had higher prostate‐specific antigen levels at diagnosis than White men without ESKD. Black men with ESKD had the lowest rates for treatment in both local and advanced stages of prostate cancer (age‐adjusted risk ratio: 0.76, 95% Confidence Interval (CI): 0.71–0.82 for local stage and age‐adjusted risk ratio: 0.82, 95% CI: 0.76–0.9 for advanced stages) compared to White men without ESKD. Compared to White men without ESKD, prostate cancer‐specific mortality was higher in White men with ESKD for both local and advanced stages (age‐adjusted hazard ratio: 1.8, 95% CI: 1.2–2.8 and HR: 1.6, 95% CI: 1.2–2.2) and it was higher for ESKD Black men only in advanced stage prostate cancer (age‐adjusted hazard ratio: 2.4, 95% CI: 1.5–3.6).
Conclusion
Our findings suggest that having a comorbidity such as ESKD makes Black men more vulnerable to racial disparities in prostate cancer treatment and mortality.
Men with end‐stage kidney disease (ESKD) present with higher prostate specific antigen at the time of prostate cancer. An interaction between Black race and ESKD was noted for receipt of treatment and prostate cancer‐specific mortality as Black men with ESKD before cancer diagnosis had the lowest probability of receiving treatment and highest prostate cancer‐specific mortality, compared to White men without ESKD. If men with prostate cancer have a severe comorbidity such as ESKD, more intense efforts are needed to reduce racial disparities.
Health-related social needs are known drivers of health and health outcomes, yet work to date to examine health-related social needs using ICD-10 Z-codes remains limited. This study seeks to evaluate ...the differences in the prevalence of conditions as well as utilization and cost between patients with and without health-related social needs.
Using the 2017 Florida State Emergency Department and State Inpatient Databases, this study identified patients with documented health-related social needs using ICD-10 Z-codes. The prevalence ratio was calculated for 14 conditions that are the leading causes of mortality and economic costs. In addition, ratios for the median total number of negative health events and total annual costs between patients with health-related social needs and those without health-related social needs across these conditions were calculated. Data analysis was conducted in 2021.
Of 4,477,772 patients, 46,081 (1.0%) had documented health-related social needs and had 4 times the negative health events and 9.3 times the total annual costs. Trends of increased negative health events and costs were seen across all examined conditions; patients with health-related social needs had 2.5–3.5 times the negative health events and 2–18 times greater total costs. The biggest difference in negative health events was seen in patients with unintentional injuries and depression and psychoses (3.5 times for patients with health-related social needs), whereas the biggest difference in total costs was for unintentional injuries (18.4 times for patients with health-related social needs).
This study shows the increased prevalence of numerous high-priority conditions as well as increased utilization and costs among patients with documented health-related social needs.
The Surgical Care Improvement Project (SCIP) aims to reduce surgical infectious complication rates through measurement and reporting of 6 infection-prevention process-of-care measures. However, an ...association between SCIP performance and clinical outcomes has not been demonstrated.
To examine the relationship between SCIP infection-prevention process-of-care measures and postoperative infection rates.
A retrospective cohort study, using Premier Inc's Perspective Database for discharges between July 1, 2006 and March 31, 2008, of 405 720 patients (69% white and 11% black; 46% Medicare patients; and 68% elective surgical cases) from 398 hospitals in the United States for whom SCIP performance was recorded and submitted for public report on the Hospital Compare Web site. Three original infection-prevention measures (S-INF-Core) and all 6 infection-prevention measures (S-INF) were aggregated into 2 separate all-or-none composite scores. Hierarchical logistical models were used to assess process-of-care relationships at the patient level while accounting for hospital characteristics.
The ability of reported adherence to SCIP infection-prevention process-of-care measures (using the 2 composite scores of S-INF and S-INF-Core) to predict postoperative infections.
There were 3996 documented postoperative infections. The S-INF composite process-of-care measure predicted a decrease in postoperative infection rates from 14.2 to 6.8 per 1000 discharges (adjusted odds ratio, 0.85; 95% confidence interval, 0.76-0.95). The S-INF-Core composite process-of-care measure predicted a decrease in postoperative infection rates from 11.5 to 5.3 per 1000 discharges (adjusted odds ratio, 0.86; 95% confidence interval, 0.74-1.01), which was not a statistically significantly lower probability of infection. None of the individual SCIP measures were significantly associated with a lower probability of infection.
Among hospitals in the Premier Inc Perspective Database reporting SCIP performance, adherence measured through a global all-or-none composite infection-prevention score was associated with a lower probability of developing a postoperative infection. However, adherence reported on individual SCIP measures, which is the only form in which performance is publicly reported, was not associated with a significantly lower probability of infection.
Disparities in the stage at diagnosis for breast cancer have been independently associated with various contextual characteristics. Understanding which combinations of these characteristics indicate ...highest risk, and where they are located, is critical to targeting interventions and improving outcomes for patients with breast cancer.
The study included women diagnosed with invasive breast cancer between 2009 and 2018 from 680 U.S. counties participating in the Surveillance, Epidemiology, and End Results program. We used a machine learning approach called Classification and Regression Tree (CART) to identify county "phenotypes," combinations of characteristics that predict the percentage of patients with breast cancer presenting with late-stage disease. We then mapped the phenotypes and compared their geographic distributions. These findings were further validated using an alternate machine learning approach called random forest.
We discovered seven phenotypes of late-stage breast cancer. Common to most phenotypes associated with high risk of late-stage diagnosis were high uninsured rate, low mammography use, high area deprivation, rurality, and high poverty. Geographically, these phenotypes were most prevalent in southern and western states, while phenotypes associated with lower percentages of late-stage diagnosis were most prevalent in the northeastern states and select metropolitan areas.
The use of machine learning methods of CART and random forest together with geographic methods offers a promising avenue for future disparities research.
Local interventions to reduce late-stage breast cancer diagnosis, such as community education and outreach programs, can use machine learning and geographic modeling approaches to tailor strategies for early detection and resource allocation.
A study was undertaken to compare survival and 5-year mortality by Medicaid status in adults diagnosed with 8 select cancers.
Linking records from the Ohio Cancer Incidence Surveillance System ...(OCISS) with Ohio Medicaid enrollment data, the authors identified Medicaid and non-Medicaid patients aged 15 to 54 years and diagnosed with the following incident cancers in the years 1996-2002: cancer of the testis; Hodgkin and non-Hodgkin lymphoma; early stage melanoma, colon, lung, and bladder cancer; and pediatric malignancies (n = 12,703). Medicaid beneficiaries were placed in the pre-diagnosis group if they were enrolled in Medicaid at least 3 months before cancer diagnosis, and in the peri/post-diagnosis group if they enrolled in Medicaid upon or after being diagnosed with cancer. The authors also linked the OCISS with death certificates and data from the US Census. By using Cox and logistic regression analysis, they examined the association between Medicaid status and survival and 5-year mortality, respectively, after adjusting for patient covariates.
Nearly 11% of the study population were Medicaid beneficiaries. Of those, 45% were classified in the peri/post-diagnosis group. Consistent with higher mortality, findings from the Cox regression model indicated that compared with non-Medicaid, patients in the Medicaid pre-diagnosis and peri/post-diagnosis groups experienced unfavorable survival outcomes (adjusted hazard ratio AHR, 1.52; 95% confidence interval CI, 1.27-1.82 and AHR, 2.01; 95% CI, 1.70-2.38, respectively).
Medicaid status was associated with unfavorable survival, even after adjusting for confounders. The findings reflect the vulnerability of Medicaid beneficiaries and possible inadequacies in the process of care.
ABSTRACT
BACKGROUND
The strategic framework on multiple chronic conditions released by the US Department of Health and Human Services calls for identifying homogeneous subgroups of older adults to ...effectively target interventions aimed at improving their health.
OBJECTIVE
We aimed to identify combinations of chronic conditions, functional limitations, and geriatric syndromes that predict poor health outcomes.
DESIGN, SETTING AND PARTICIPANTS
Data from the 2010–2012 Health and Retirement Study provided a representative sample of U.S. adults 50 years of age or older (
n
= 16,640).
MAIN MEASURES
Outcomes were: Self-reported fair/poor health, self-rated worse health at 2 years, and 2-year mortality. The main independent variables included self-reported chronic conditions, functional limitations, and geriatric syndromes. We conducted tree-based classification and regression analysis to identify the most salient combinations of variables to predict outcomes.
KEY RESULTS
Twenty-nine percent and 23 % of respondents reported fair/poor health and self-rated worse health at 2 years, respectively, and 5 % died in 2 years. The top combinations of conditions identified through our tree analysis for the three different outcome measures (and percent respondents with the outcome) were: a) for fair/poor health status: difficulty walking several blocks, depressive symptoms, and severe pain (> 80 %); b) for self-rated worse health at 2 years: 68.5 years of age or older, difficulty walking several blocks and being in fair/poor health (60 %); and c) for 2-year mortality: 80.5 years of age or older, and presenting with limitations in both ADLs and IADLs (> 40 %).
CONCLUSIONS
Rather than chronic conditions, functional limitations and/or geriatric syndromes were the most prominent conditions in predicting health outcomes. These findings imply that accounting for chronic conditions alone may be less informative than also accounting for the co-occurrence of functional limitations and geriatric syndromes, as the latter conditions appear to drive health outcomes in older individuals.