Prospective evaluation of social risks, physical function, and cognitive function in prediction of non-elective rehospitalization and post-discharge mortality.

BACKGROUND: Increasing evidence suggests that social factors and problems with physical and cognitive function may contribute to patients' rehospitalization risk. Understanding a patient's readmission risk may help healthcare providers develop tailored treatment and post-discharge care plans to reduce readmission and mortality. This study aimed to evaluate whether including patient-reported data on social factors; cognitive status; and physical function improves on a predictive model based on electronic health record (EHR) data alone. METHODS: We conducted a prospective study of 1,547 hospitalized adult patients in 3 Kaiser Permanente Northern California hospitals. The main outcomes were non-elective rehospitalization or death within 30 days post-discharge. Exposures included patient-reported social factors and cognitive and physical function (obtained in a pre-discharge interview) and EHR-derived data for comorbidity burden, acute physiology, care directives, prior utilization, and hospital length of stay. We performed bivariate comparisons using Chi-square, t-tests, and Wilcoxon rank-sum tests and assessed correlations between continuous variables using Spearman's rho statistic. For all models, the results reported were obtained after fivefold cross validation. RESULTS: The 1,547 adult patients interviewed were younger (age, p = 0.03) and sicker (COPS2, p < 0.0001) than the rest of the hospitalized population. Of the 6 patient-reported social factors measured, 3 (not living with a spouse/partner, transportation difficulties, health or disability-related limitations in daily activities) were significantly associated (p < 0.05) with the main outcomes, while 3 (living situation concerns, problems with food availability, financial problems) were not. Patient-reported cognitive (p = 0.027) and physical function (p = 0.01) were significantly lower in patients with the main outcomes. None of the patient-reported variables, singly or in combination, improved predictive performance of a model that included acute physiology and longitudinal comorbidity burden (area under the receiver operator characteristic curve was 0.716 for both the EHR model and maximal performance of a random forest model including all predictors). CONCLUSIONS: In this insured population, incorporating patient-reported social factors and measures of cognitive and physical function did not improve performance of an EHR-based model predicting 30-day non-elective rehospitalization or mortality. While incorporating patient-reported social and functional status data did not improve ability to predict these outcomes, such data may still be important for improving patient outcomes.

Equitably Allocating Resources during Crises: Racial Differences in Mortality Prediction Models.

Rationale: Crisis standards of care (CSCs) guide critical care resource allocation during crises. Most recommend ranking patients on the basis of their expected in-hospital mortality using the Sequential Organ Failure Assessment (SOFA) score, but it is unknown how SOFA or other acuity scores perform among patients of different races. Objectives: To test the prognostic accuracy of the SOFA score and version 2 of the Laboratory-based Acute Physiology Score (LAPS2) among Black and white patients. Methods: We included Black and white patients admitted for sepsis or acute respiratory failure at 27 hospitals. We calculated the discrimination and calibration for in-hospital mortality of SOFA, LAPS2, and modified versions of each, including categorical SOFA groups recommended in a popular CSC and a SOFA score without creatinine to reduce the influence of race. Measurements and Main Results: Of 113,158 patients, 27,644 (24.4%) identified as Black. The LAPS2 demonstrated higher discrimination (area under the receiver operating characteristic curve [AUC], 0.76; 95% confidence interval [CI], 0.76-0.77) than the SOFA score (AUC, 0.68; 95% CI, 0.68-0.69). The LAPS2 was also better calibrated than the SOFA score, but both underestimated in-hospital mortality for white patients and overestimated in-hospital mortality for Black patients. Thus, in a simulation using observed mortality, 81.6% of Black patients were included in lower-priority CSC categories, and 9.4% of all Black patients were erroneously excluded from receiving the highest prioritization. The SOFA score without creatinine reduced racial miscalibration. Conclusions: Using SOFA in CSCs may lead to racial disparities in resource allocation. More equitable mortality prediction scores are needed.

Assessment of Value of Neighborhood Socioeconomic Status in Models That Use Electronic Health Record Data to Predict Health Care Use Rates and Mortality.

Importance: Prediction models are widely used in health care as a way of risk stratifying populations for targeted intervention. Most risk stratification has been done using a small number of predictors from insurance claims. However, the utility of diverse nonclinical predictors, such as neighborhood socioeconomic contexts, remains unknown. Objective: To assess the value of using neighborhood socioeconomic predictors in the context of 1-year risk prediction for mortality and 6 different health care use outcomes in a large integrated care system. Design, Setting, and Participants: Diagnostic study using data from all adults age 18 years or older who had Kaiser Foundation Health Plan membership and/or use in the Kaiser Permantente Northern California: a multisite, integrated health care delivery system between January 1, 2013, and June 30, 2014. Data were recorded before the index date for each patient to predict their use and mortality in a 1-year post period using a test-train split for model training and evaluation. Analyses were conducted in fall of 2019. Main Outcomes and Measures: One-year encounter counts (doctor office, virtual, emergency department, elective hospitalizations, and nonelective), total costs, and mortality. Results: A total of 2 951 588 patients met inclusion criteria (mean [SD] age, 47.2 [17.4] years; 47.8% were female). The mean (SD) Neighborhood Deprivation Index was -0.32 (0.84). The areas under the receiver operator curve ranged from 0.71 for emergency department use (using the LASSO method and electronic health record predictors) to 0.94 for mortality (using the random forest method and electronic health record predictors). Neighborhood socioeconomic status predictors did not meaningfully increase the predictive performance of the models for any outcome. Conclusions and Relevance: In this study, neighborhood socioeconomic predictors did not improve risk estimates compared with what is obtainable using standard claims data regardless of model used.

Developing a template matching algorithm for benchmarking hospital performance in a diverse, integrated healthcare system.

Template matching is a proposed approach for hospital benchmarking, which measures performance based on matching a subset of comparable patient hospitalizations from each hospital. We assessed the ability to create the required matched samples and thus the feasibility of template matching to benchmark hospital performance in a diverse healthcare system.Nationwide Veterans Affairs (VA) hospitals, 2017.Observational cohort study.We used administrative and clinical data from 668,592 hospitalizations at 134 VA hospitals in 2017. A standardized template of 300 hospitalizations was selected, and then 300 hospitalizations were matched to the template from each hospital.There was substantial case-mix variation across VA hospitals, which persisted after excluding small hospitals, hospitals with primarily psychiatric admissions, and hospitalizations for rare diagnoses. Median age ranged from 57 to 75 years across hospitals; percent surgical admissions ranged from 0.0% to 21.0%; percent of admissions through the emergency department, 0.1% to 98.7%; and percent Hispanic patients, 0.2% to 93.3%. Characteristics for which there was substantial variation across hospitals could not be balanced with any matching algorithm tested. Although most other variables could be balanced, we were unable to identify a matching algorithm that balanced more than ∼20 variables simultaneously.We were unable to identify a template matching approach that could balance hospitals on all measured characteristics potentially important to benchmarking. Given the magnitude of case-mix variation across VA hospitals, a single template is likely not feasible for general hospital benchmarking.

Multiyear Rehospitalization Rates and Hospital Outcomes in an Integrated Health Care System.

Importance: Since the introduction of the rehospitalization rate as a quality measure, multiple changes have taken place in the US health care delivery system. Interpreting rehospitalization rates without taking a global view of these changes and new data elements from comprehensive electronic medical records yields a limited assessment of the quality of care. Objective: To examine hospitalization outcomes from a broad perspective, including the implications of numerator and denominator definitions, all adult patients with all diagnoses, and detailed clinical data. Design, Setting, and Participants: This cohort study obtained data from 21 hospitals in Kaiser Permanente Northern California (KPNC), an integrated health care delivery system that serves patients with Medicare Advantage plans, Medicaid, and/or Kaiser Foundation Health Plan. The KPNC electronic medical record system was used to capture hospitalization data for adult patients who were 18 years of age or older; discharged from June 1, 2010, through December 31, 2017; and hospitalized for reasons other than childbirth. Hospital stays for transferred patients were linked using public and internal sources. Exposures: Hospitalization type (inpatient, for observation only), comorbidity burden, acute physiology score, and care directives. Main Outcomes and Measures: Mortality (inpatient, 30-day, and 30-day postdischarge), nonelective rehospitalization, and discharge disposition (home, home with home health assistance, regular skilled nursing facility, or custodial skilled nursing facility). Results: In total, 1 384 025 hospitalizations were identified, of which 1 155 034 (83.5%) were inpatient and 228 991 (16.5%) were for observation only. These hospitalizations involved 679 831 patients (mean [SD] age, 61.4 [18.1] years; 362 582 female [53.3%]). The number of for-observation-only hospitalizations increased from 16 497 (9.4%) in the first year of the study to 120 215 (20.5%) in the last period of the study, whereas inpatient hospitalizations with length of stay less than 24 hours decreased by 33% (from 12 008 [6.9%] to 27 108 [4.6%]). Illness burden measured using administrative data or acute physiology score increased significantly. The proportion of patients with a Comorbidity Point Score of 65 or higher increased from 20.5% (range across hospitals, 18.4%-26.4%) to 28.8% (range, 22.3%-33.0%), as did the proportion with a Charlson Comorbidity Index score of 4 or higher, which increased from 28.8% (range, 24.6%-35.0%) to 38.4% (range, 31.9%-43.4%). The proportion of patients at or near critical illness (Laboratory-based Acute Physiology Score [LAPS2] ≥110) increased by 21.4% (10.3% [range across hospitals, 7.4%-14.7%] to 12.5% [range across hospitals, 8.3%-16.6%]; P < .001), reflecting a steady increase of 0.07 (95% CI, 0.04-0.10) LAPS2 points per month. Unadjusted inpatient mortality in the first year of the study was 2.78% and in the last year was 2.71%; the corresponding numbers for 30-day mortality were 5.88% and 6.15%, for 30-day postdischarge mortality were 3.94% and 4.22%, and for nonelective rehospitalization were 12.00% and 12.81%, respectively. All outcomes improved after risk adjustment. Compared with the first month, the final observed to expected ratio was 0.79 (95% CI, 0.73-0.84) for inpatient mortality, 0.86 (95% CI, 0.82-0.89) for 30-day mortality, 0.90 (95% CI, 0.85-0.95) for 30-day nonelective rehospitalization, and 0.87 (95% CI, 0.83-0.92) for 30-day postdischarge mortality. The proportion of nonelective rehospitalizations meeting public reporting criteria decreased substantially over the study period (from 58.0% in 2010-2011 to 45.2% in 2017); most of this decrease was associated with the exclusion of observation stays. Conclusions and Relevance: This study found that in this integrated system, the hospitalization rate decreased and risk-adjusted hospital outcomes improved steadily over the 7.5-year study period despite worsening case mix. The comprehensive results suggest that future assessments of care quality should consider the implications of numerator and denominator definitions, display multiple metrics concurrently, and include all hospitalization types and detailed data.

Comparing Hospital Processes and Outcomes in California Medicare Beneficiaries: Simulation Prompts Reconsideration.

INTRODUCTION: This article is not a traditional research report. It describes how conducting a specific set of benchmarking analyses led us to broader reflections on hospital benchmarking. We reexamined an issue that has received far less attention from researchers than in the past: How variations in the hospital admission threshold might affect hospital rankings. Considering this threshold made us reconsider what benchmarking is and what future benchmarking studies might be like. Although we recognize that some of our assertions are speculative, they are based on our reading of the literature and previous and ongoing data analyses being conducted in our research unit. We describe the benchmarking analyses that led to these reflections. OBJECTIVES: The Centers for Medicare and Medicaid Services' Hospital Compare Web site includes data on fee-for-service Medicare beneficiaries but does not control for severity of illness, which requires physiologic data now available in most electronic medical records.To address this limitation, we compared hospital processes and outcomes among Kaiser Permanente Northern California's (KPNC) Medicare Advantage beneficiaries and non-KPNC California Medicare beneficiaries between 2009 and 2010. METHODS: We assigned a simulated severity of illness measure to each record and explored the effect of having the additional information on outcomes. RESULTS: We found that if the admission severity of illness in non-KPNC hospitals increased, KPNC hospitals' mortality performance would appear worse; conversely, if admission severity at non-KPNC hospitals' decreased, KPNC hospitals' performance would appear better. CONCLUSION: Future hospital benchmarking should consider the impact of variation in admission thresholds.

Adaptation of the Acute Organ Failure Score for Use in a Medicare Population.

OBJECTIVES: Without widely available physiologic data, a need exists for ICU risk adjustment methods that can be applied to administrative data. We sought to expand the generalizability of the Acute Organ Failure Score by adapting it to a commonly used administrative database. DESIGN: Retrospective cohort study. SETTING: One hundred fifty-one hospitals in Pennsylvania. PATIENTS: A total of 90,733 ICU admissions among 77,040 unique patients between January 1, 2009, and December 1, 2009, in the Medicare Provider Analysis and Review database. MEASUREMENTS AND MAIN RESULTS: We used multivariable logistic regression on a random split cohort to predict 30-day mortality, and to examine the impact of using different comorbidity measures in the model and adding historical claims data. Overall 30-day mortality was 17.6%. In the validation cohort, using the original Acute Organ Failure Score model's ß coefficients resulted in poor discrimination (C-statistic, 0.644; 95% CI, 0.639-0.649). The model's C-statistic improved to 0.721 (95% CI, 0.711-0.730) when the Medicare cohort was used to recalibrate the ß coefficients. Model discrimination improved further when comorbidity was expressed as the COmorbidity Point Score 2 (C-statistic, 0.737; 95% CI, 0.728-0.747; p < 0.001) or the Elixhauser index (C-statistic, 0.748; 95% CI, 0.739-0.757) instead of the Charlson index. Adding historical claims data increased the number of comorbidities identified, but did not enhance model performance. CONCLUSIONS: Modification of the Acute Organ Failure Score resulted in good model discrimination among a diverse population regardless of comorbidity measure used. This study expands the use of the Acute Organ Failure Score for risk adjustment in ICU research and outcomes reporting using standard administrative data.

Prediction of Recurrent Clostridium Difficile Infection Using Comprehensive Electronic Medical Records in an Integrated Healthcare Delivery System.

BACKGROUND Predicting recurrent Clostridium difficile infection (rCDI) remains difficult. METHODS: We employed a retrospective cohort design. Granular electronic medical record (EMR) data had been collected from patients hospitalized at 21 Kaiser Permanente Northern California hospitals. The derivation dataset (2007-2013) included data from 9,386 patients who experienced incident CDI (iCDI) and 1,311 who experienced their first CDI recurrences (rCDI). The validation dataset (2014) included data from 1,865 patients who experienced incident CDI and 144 who experienced rCDI. Using multiple techniques, including machine learning, we evaluated more than 150 potential predictors. Our final analyses evaluated 3 models with varying degrees of complexity and 1 previously published model. RESULTS Despite having a large multicenter cohort and access to granular EMR data (eg, vital signs, and laboratory test results), none of the models discriminated well (c statistics, 0.591-0.605), had good calibration, or had good explanatory power. CONCLUSIONS Our ability to predict rCDI remains limited. Given currently available EMR technology, improvements in prediction will require incorporating new variables because currently available data elements lack adequate explanatory power. Infect Control Hosp Epidemiol 2017;38:1196-1203.

Individual and health system variation in rehospitalizations the year after pneumonia.

Little is known about variation in patterns of recovery among patients discharged alive from hospitalizations for pneumonia.The aim of the is observational cohort study was to characterize the variation in patterns of hospital readmission and survival in the year after discharge for pneumonia in 3 different health systems.The 3 cohorts consisted of (1) the Health and Retirement Study participants enrolled in Fee-for-service Medicare (FFS), (2) Veterans Administration (VA) Healthcare system, and (3) Kaiser Permanente of Northern California (KPNC). The 365-day survival and re-hospitalizations were determined for each cohort. Multinomial logistic regression was used to identify potential contributors to the different patterns.We identified 2731, 23,536, and 39,147 hospitalizations for pneumonia in FFS Medicare, VA, and KPNC, respectively, of whom 88.1%, 92.8%, and 89.7% survived to hospital discharge. The median patient survived to 1 year and was rehospitalized twice in FFS (9.0%), once in VA (14.1%) and KPNC (9.1%). Of the patients who survived the hospitalization, 33.3% (FFS), 30.2% (VA), and 26.8% (KPNC) died during the subsequent year. Of those who survived, 29.8% (FFS), 35.9% (VA), and 46.1% (KPNC) were never rehospitalized. 11.9% (FFS), 11.9% (VA), and 11.7% (KPNC) had greater than 3 hospitalizations. Age, race, gender, comorbidity, ICU use, and hospital length stay collectively explained little (5-7%) of the variation in the recovery pattern.There is significant variation in the year after the hospitalization for pneumonia across individuals, but less so across health systems. There may be important opportunities to better classify these heterogeneous individual-level pathways.

Respiratory syncytial virus immunoprophylaxis in high-risk infants and development of childhood asthma.

BACKGROUND: Respiratory syncytial virus (RSV) lower respiratory tract infection is implicated in asthma development. RSV immunoprophylaxis during infancy is efficacious in preventing RSV-related hospitalizations and has been associated with decreased wheezing in the first years of life. OBJECTIVE: We investigated whether greater adherence to immunoprophylaxis in infants at high risk for severe RSV would be associated with decreased childhood asthma. METHODS: We conducted a retrospective cohort investigation including children born from 1996-2003 who were enrolled in Kaiser Permanente Northern California or Tennessee Medicaid and eligible to receive RSV immunoprophylaxis. Asthma was defined at 4.5 to 6 years of age by using asthma-specific health care visits and medication fills. We classified children into immunoprophylaxis eligibility groups and calculated adherence (percentage receipt of recommended doses). We used a set of statistical strategies (multivariable logistic regression and propensity score [PS]-adjusted and PS-matched analyses) to overcome confounding by medical complexity because infants with higher adherence (≥70%) have higher prevalence of chronic lung disease, lower birth weight, and longer nursery stays. RESULTS: By using multivariable logistic regression and PS-adjusted models in the combined group, higher adherence to RSV immunoprophylaxis was not associated with decreased asthma. However, in PS-matched analysis, treated children with 70% or greater adherence had decreased odds of asthma compared with those with 20% or less adherence (odds ratio, 0.62; 95% CI, 0.50-0.78). CONCLUSIONS: This investigation of RSV immunoprophylaxis in high-risk children primarily found nonsignificant associations on prevention of asthma in specific preterm groups. Our findings highlight the need for larger studies and prospective cohorts and provide estimates of potential preventive effect sizes in high-risk children.

Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).

IMPORTANCE: The Third International Consensus Definitions Task Force defined sepsis as "life-threatening organ dysfunction due to a dysregulated host response to infection." The performance of clinical criteria for this sepsis definition is unknown. OBJECTIVE: To evaluate the validity of clinical criteria to identify patients with suspected infection who are at risk of sepsis. DESIGN, SETTINGS, AND POPULATION: Among 1.3 million electronic health record encounters from January 1, 2010, to December 31, 2012, at 12 hospitals in southwestern Pennsylvania, we identified those with suspected infection in whom to compare criteria. Confirmatory analyses were performed in 4 data sets of 706,399 out-of-hospital and hospital encounters at 165 US and non-US hospitals ranging from January 1, 2008, until December 31, 2013. EXPOSURES: Sequential [Sepsis-related] Organ Failure Assessment (SOFA) score, systemic inflammatory response syndrome (SIRS) criteria, Logistic Organ Dysfunction System (LODS) score, and a new model derived using multivariable logistic regression in a split sample, the quick Sequential [Sepsis-related] Organ Failure Assessment (qSOFA) score (range, 0-3 points, with 1 point each for systolic hypotension [≤100 mm Hg], tachypnea [≥22/min], or altered mentation). MAIN OUTCOMES AND MEASURES: For construct validity, pairwise agreement was assessed. For predictive validity, the discrimination for outcomes (primary: in-hospital mortality; secondary: in-hospital mortality or intensive care unit [ICU] length of stay ≥3 days) more common in sepsis than uncomplicated infection was determined. Results were expressed as the fold change in outcome over deciles of baseline risk of death and area under the receiver operating characteristic curve (AUROC). RESULTS: In the primary cohort, 148,907 encounters had suspected infection (n = 74,453 derivation; n = 74,454 validation), of whom 6347 (4%) died. Among ICU encounters in the validation cohort (n = 7932 with suspected infection, of whom 1289 [16%] died), the predictive validity for in-hospital mortality was lower for SIRS (AUROC = 0.64; 95% CI, 0.62-0.66) and qSOFA (AUROC = 0.66; 95% CI, 0.64-0.68) vs SOFA (AUROC = 0.74; 95% CI, 0.73-0.76; P < .001 for both) or LODS (AUROC = 0.75; 95% CI, 0.73-0.76; P < .001 for both). Among non-ICU encounters in the validation cohort (n = 66 522 with suspected infection, of whom 1886 [3%] died), qSOFA had predictive validity (AUROC = 0.81; 95% CI, 0.80-0.82) that was greater than SOFA (AUROC = 0.79; 95% CI, 0.78-0.80; P < .001) and SIRS (AUROC = 0.76; 95% CI, 0.75-0.77; P < .001). Relative to qSOFA scores lower than 2, encounters with qSOFA scores of 2 or higher had a 3- to 14-fold increase in hospital mortality across baseline risk deciles. Findings were similar in external data sets and for the secondary outcome. CONCLUSIONS AND RELEVANCE: Among ICU encounters with suspected infection, the predictive validity for in-hospital mortality of SOFA was not significantly different than the more complex LODS but was statistically greater than SIRS and qSOFA, supporting its use in clinical criteria for sepsis. Among encounters with suspected infection outside of the ICU, the predictive validity for in-hospital mortality of qSOFA was statistically greater than SOFA and SIRS, supporting its use as a prompt to consider possible sepsis.

Nonelective Rehospitalizations and Postdischarge Mortality: Predictive Models Suitable for Use in Real Time.

BACKGROUND: Hospital discharge planning has been hampered by the lack of predictive models. OBJECTIVE: To develop predictive models for nonelective rehospitalization and postdischarge mortality suitable for use in commercially available electronic medical records (EMRs). DESIGN: Retrospective cohort study using split validation. SETTING: Integrated health care delivery system serving 3.9 million members. PARTICIPANTS: A total of 360,036 surviving adults who experienced 609,393 overnight hospitalizations at 21 hospitals between June 1, 2010 and December 31, 2013. MAIN OUTCOME MEASURE: A composite outcome (nonelective rehospitalization and/or death within 7 or 30 days of discharge). RESULTS: Nonelective rehospitalization rates at 7 and 30 days were 5.8% and 12.4%; mortality rates were 1.3% and 3.7%; and composite outcome rates were 6.3% and 14.9%, respectively. Using data from a comprehensive EMR, we developed 4 models that can generate risk estimates for risk of the combined outcome within 7 or 30 days, either at the time of admission or at 8 AM on the day of discharge. The best was the 30-day discharge day model, which had a c-statistic of 0.756 (95% confidence interval, 0.754-0.756) and a Nagelkerke pseudo-R of 0.174 (0.171-0.178) in the validation dataset. The most important predictors-a composite acute physiology score and end of life care directives-accounted for 54% of the predictive ability of the 30-day model. Incorporation of diagnoses (not reliably available for real-time use) did not improve model performance. CONCLUSIONS: It is possible to develop robust predictive models, suitable for use in real time with commercially available EMRs, for nonelective rehospitalization and postdischarge mortality.

Trends in red blood cell transfusion and 30-day mortality among hospitalized patients.

BACKGROUND: Blood conservation strategies have been shown to be effective in decreasing red blood cell (RBC) utilization in specific patient groups. However, few data exist describing the extent of RBC transfusion reduction or their impact on transfusion practice and mortality in a diverse inpatient population. STUDY DESIGN AND METHODS: We conducted a retrospective cohort study using comprehensive electronic medical record data from 21 medical facilities in Kaiser Permanente Northern California. We examined unadjusted and risk-adjusted RBC transfusion and 30-day mortality coincident with implementation of RBC conservation strategies. RESULTS: The inpatient study cohort included 391,958 patients who experienced 685,753 hospitalizations. From 2009 to 2013, the incidence of RBC transfusion decreased from 14.0% to 10.8% of hospitalizations; this change coincided with a decline in pretransfusion hemoglobin (Hb) levels from 8.1 to 7.6 g/dL. Decreased RBC utilization affected broad groups of admission diagnoses and was most pronounced in patients with a nadir Hb level between 8 and 9 g/dL (n = 73,057; 50.8% to 19.3%). During the study period, the standard deviation of risk-adjusted RBC transfusion incidence across hospitals decreased by 44% (p < 0.001). Thirty-day mortality did not change significantly with declines in RBC utilization in patient groups previously studied in clinical trials nor in other subgroups. CONCLUSIONS: After the implementation of blood conservation strategies, RBC transfusion incidence and pretransfusion Hb levels decreased broadly across medical and surgical patients. Variation in RBC transfusion incidence across hospitals decreased from 2010 to 2013. Consistent with clinical trial data, more restrictive transfusion practice did not appear to impact 30-day mortality.

Maternal acculturation and the prenatal care experience.

BACKGROUND: Acculturation may influence women's perceptions of health care experiences and may explain the epidemiologic paradox, whereby foreign-born women have lower rates of adverse birth outcomes than United States (US)-born women. We evaluated the relationship between maternal acculturation and specific dimensions of prenatal interpersonal processes of care (IPC) in ethnically diverse women. METHODS: Cross-sectional analysis of 1243 multiethnic, postpartum women who delivered at Kaiser Permanente Medical Center in Walnut Creek or San Francisco General Hospital. Women retrospectively reported on their experiences in seven domains of IPC during their pregnancy pertaining to communication, decision making, and interpersonal style. The primary independent variables were four measures of maternal acculturation: birthplace, English language proficiency, the number of years residing in the US, and age at immigration to the US. Generalized linear models, stratified by infant outcome, measured the association between each maternal acculturation measure and specific IPC domains while adjusting for type of health insurance, demographic, and reproductive factors. RESULTS: Approximately 60% of the sample was foreign-born, 36% reported low English proficiency, 43% had resided in the US <10 years, and 35% were age 20 years or older when they immigrated to the US. Over 64% of the women reported having public insurance during pregnancy. In adjusted analyses among women who delivered term and normal birth weight infants, less acculturated women and women with non-private health insurance were more likely to have higher mean IPC scores when compared to more acculturated or US-born women and women with private health insurance, respectively. CONCLUSION: In a large and ethnically diverse sample of childbearing women in Northern California, less acculturated pregnant women reported better prenatal care experiences than more acculturated and US-born women, another dimension of the "epidemiologic paradox." However, the relationship between acculturation and IPC, as reported during the postpartum period, differed according to infant outcomes.

Increased 1-year healthcare use in survivors of severe sepsis.

RATIONALE: Hospitalizations for severe sepsis are common, and a growing number of patients survive to hospital discharge. Nonetheless, little is known about survivors' post-discharge healthcare use. OBJECTIVES: To measure inpatient healthcare use of severe sepsis survivors compared with patients' own presepsis resource use and the resource use of survivors of otherwise similar nonsepsis hospitalizations. METHODS: This is an observational cohort study of survivors of severe sepsis and nonsepsis hospitalizations identified from participants in the Health and Retirement Study with linked Medicare claims, 1998-2005. We matched severe sepsis and nonsepsis hospitalizations by demographics, comorbidity burden, premorbid disability, hospitalization length, and intensive care use. MEASUREMENTS AND MAIN RESULTS: Using Medicare claims, we measured patients' use of inpatient facilities (hospitals, long-term acute care hospitals, and skilled nursing facilities) in the 2 years surrounding hospitalization. Severe sepsis survivors spent more days (median, 16 [interquartile range, 3-45] vs. 7 [0-29]; P < 0.001) and a higher proportion of days alive (median, 9.6% [interquartile range, 1.4-33.8%] vs. 1.9% [0.0-7.9%]; P < 0.001) admitted to facilities in the year after hospitalization, compared with the year prior. The increase in facility-days was similar for nonsepsis hospitalizations. However, the severe sepsis cohort experienced greater post-discharge mortality (44.2% [95% confidence interval, 41.3-47.2%] vs. 31.4% [95% confidence interval, 28.6-34.2%] at 1 year), a steeper decline in days spent at home (difference-in-differences, -38.6 d [95% confidence interval, -50.9 to 26.3]; P < 0.001), and a greater increase in the proportion of days alive spent in a facility (difference-in-differences, 5.4% [95% confidence interval, 2.8-8.1%]; P < 0.001). CONCLUSIONS: Healthcare use is markedly elevated after severe sepsis, and post-discharge management may be an opportunity to reduce resource use.

Interpersonal processes of care and cesarean delivery in two health care settings.

OBJECTIVES: We examined whether interpersonal processes of care (IPC) were associated with cesarean delivery. METHODS: We performed a cross-sectional study of 1308 postpartum women at Kaiser Permanente Medical Center in Walnut Creek, CA (KP-WC), and San Francisco General Hospital (SFGH) from 2004 to 2006. Using interview and medical record data, logistic regression analyses estimated the odds of cesarean delivery as a function of IPC domains. RESULTS: After adjustment for demographic and reproductive factors, women at KP-WC who reported higher scores for their provider's "elicitation of patient concerns and responsiveness" were less likely to have delivered by cesarean, whereas women who reported higher scores for "empowerment and self-care" were more likely. At KP-WC, women who reported low English proficiency were less likely to have delivered by cesarean than women who reported high proficiency. At SFGH, none of the IPC measures were significant; however, younger age was associated with a lower risk of cesarean delivery, whereas higher educational attainment was associated with an increased risk. CONCLUSIONS: To reduce record-high rates of cesarean delivery, more emphasis should be placed on addressing the nonmedical factors associated with operative delivery.

The Kaiser Permanente inpatient risk adjustment methodology was valid in an external patient population.

OBJECTIVES: Accurately predicting hospital mortality is necessary to measure and compare patient care. External validation of predictive models is required to truly prove their utility. This study assessed the Kaiser Permanente inpatient risk adjustment methodology for hospital mortality in a patient population distinct from that used for its derivation. STUDY DESIGN AND SETTING: Retrospective cohort study at two hospitals in Ottawa, Canada, involving all inpatients admitted between January 1998 and April 2002 (n=188,724). Statistical models for inpatient mortality were derived on a random half of the cohort and validated on the other half. RESULTS: Inpatient mortality was 3.3%. The model using original parameter estimates had excellent discrimination (c-statistic 89.4, 95% confidence interval [CI] 0.891-0.898) but poor calibration. Using data-based parameter estimates, discrimination was excellent (c-statistic 0.915, 95% CI 0.912-0.918) and remained so when patient comorbidity was expressed in the model using the Elixhauser Index (0.901, 0.898-0.904) or the Charlson Index (0.894, 0.891-0.897). These models accurately predicted the risk of hospital death. CONCLUSION: The Kaiser Permanente inpatient risk adjustment methodology is a valid model for predicting hospital mortality risk. It performed equally well regardless of methods used to summarize patient comorbidity.

Time to send the preemie home? Additional maturity at discharge and subsequent health care costs and outcomes.

OBJECTIVE: To determine whether longer stays of premature infants allowing for increased physical maturity result in subsequent postdischarge cost savings that help counterbalance increased inpatient costs. DATA SOURCES: One thousand four hundred and two premature infants born in the Northern California Kaiser Permanente Medical Care Program between 1998 and 2002. STUDY DESIGN/METHODS: Using multivariate matching with a time-dependent propensity score we matched 701 "Early" babies to 701 "Late" babies (developmentally similar at the time the earlier baby was sent home but who were discharged on average 3 days later) and assessed subsequent costs and clinical outcomes. PRINCIPAL FINDINGS: Late babies accrued inpatient costs after the Early baby was already home, yet costs after discharge through 6 months were virtually identical across groups, as were clinical outcomes. Overall, after the Early baby went home, the Late-Early cost difference was $5,016 (p<.0001). A sensitivity analysis suggests our conclusions would not easily be altered by failure to match on some unmeasured covariate. CONCLUSIONS: In a large integrated health care system, if a baby is ready for discharge (as defined by the typical criteria), staying longer increased inpatient costs but did not reduce postdischarge costs nor improve postdischarge clinical outcomes.

Correlates of prescription drug use during pregnancy.

PURPOSE: To evaluate the extent of prescription drug use and the use of category D or X drugs during pregnancy and examine the maternal characteristics associated with use. METHODS: Medical record and survey data from an observational cohort of pregnant women from 2001 to 2003 (n=1626) were analyzed to examine the use of prescription drugs and the use of category D or X drugs. RESULTS: A majority of these pregnant women were prescribed a prescription drug (56%), and 4% of women were prescribed a category D or X drug. The most common classes of medications prescribed were antibiotics (62%), analgesics (18%), asthma medications (18%), and antiemetics (17%). After adjustment for sociodemographic and clinical characteristics, African American women were more likely to use a prescription drug than white women. Lower levels of educational attainment were also associated with greater use of prescription drugs compared with women who had graduated from college. Women with a chronic health condition, gestational diabetes, a prenatal hospitalization, a history of infertility, or symptoms of acid reflux were also more likely to use a prescription drug than women without these conditions. Nulliparous women and women who were married or living with a partner were less likely to use category D or X drugs during pregnancy than women without these characteristics. Women with a history of infertility and those with a chronic health condition were more likely to use a category D or X drugs during pregnancy than those without these conditions. CONCLUSIONS: The common use of prescription drugs during pregnancy supports the importance of expanding the evidence about the risks and benefits of prescription drug use during pregnancy and suggests the need for systems to safeguard prescribing practices for women of reproductive age.