Evaluation of an outreach programme for patients with COVID-19 in an integrated healthcare delivery system: a retrospective cohort study.

OBJECTIVES: In the first year of the COVID-19 pandemic, health systems implemented programmes to manage outpatients with COVID-19. The goal was to expedite patients' referral to acute care and prevent overcrowding of medical centres. We sought to evaluate the impact of such a programme, the COVID-19 Home Care Team (CHCT) programme. DESIGN: Retrospective cohort. SETTING: Kaiser Permanente Northern California. PARTICIPANTS: Adult members before COVID-19 vaccine availability (1 February 2020-31 January 2021) with positive SARS-CoV-2 tests. INTERVENTION: Virtual programme to track and treat patients with 'CHCT programme'. OUTCOMES: The outcomes were (1) COVID-19-related emergency department visit, (2) COVID-19-related hospitalisation and (3) inpatient mortality or 30-day hospice referral. MEASURES: We estimated the average effect comparing patients who were and were not treated by CHCT. We estimated propensity scores using an ensemble super learner (random forest, XGBoost, generalised additive model and multivariate adaptive regression splines) and augmented inverse probability weighting. RESULTS: There were 98 585 patients with COVID-19. The majority were followed by CHCT (n=80 067, 81.2%). Patients followed by CHCT were older (mean age 43.9 vs 41.6 years, p<0.001) and more comorbid with COmorbidity Point Score, V.2, score ≥65 (1.7% vs 1.1%, p<0.001). Unadjusted analyses showed more COVID-19-related emergency department visits (9.5% vs 8.5%, p<0.001) and hospitalisations (3.9% vs 3.2%, p<0.001) in patients followed by CHCT but lower inpatient death or 30-day hospice referral (0.3% vs 0.5%, p<0.001). After weighting, there were higher rates of COVID-19-related emergency department visits (estimated intervention effect -0.8%, 95% CI -1.4% to -0.3%) and hospitalisation (-0.5%, 95% CI -0.9% to -0.1%) but lower inpatient mortality or 30-day hospice referral (-0.5%, 95% CI -0.7% to -0.3%) in patients followed by CHCT. CONCLUSIONS: Despite CHCT following older patients with higher comorbidity burden, there appeared to be a protective effect. Patients followed by CHCT were more likely to present to acute care and less likely to die inpatient.

Risk of severe COVID-19 infection among adults with prior exposure to children.

Susceptibility and severity of COVID-19 infection vary widely. Prior exposure to endemic coronaviruses, common in young children, may protect against SARS-CoV-2. We evaluated risk of severe COVID-19 among adults with and without exposure to young children in a large, integrated healthcare system. Adults with children 0-5 years were matched 1:1 to adults with children 6-11 years, 12-18 years, and those without children based upon a COVID-19 propensity score and risk factors for severe COVID-19. COVID-19 infections, hospitalizations, and need for intensive care unit (ICU) were assessed in 3,126,427 adults, of whom 24% (N = 743,814) had children 18 years or younger, and 8.8% (N = 274,316) had a youngest child 0-5 years. After 1:1 matching, propensity for COVID-19 infection and risk factors for severe COVID-19 were well balanced between groups. Rates of COVID-19 infection were slightly higher for adults with exposure to older children (incident risk ratio, 1.09, 95% confidence interval, [1.05-1.12] and IRR 1.09 [1.05-1.13] for adults with children 6-11 and 12-18, respectively), compared to those with children 0-5 years, although no difference in rates of COVID-19 illness requiring hospitalization or ICU admission was observed. However, adults without exposure to children had lower rates of COVID-19 infection (IRR 0.85, [0.83-0.87]) but significantly higher rates of COVID-19 hospitalization (IRR 1.49, [1.29-1.73]) and hospitalization requiring ICU admission (IRR 1.76, [1.19-2.58]) compared to those with children aged 0-5. In a large, real-world population, exposure to young children was associated with less severe COVID-19 illness. Endemic coronavirus cross-immunity may play a role in protection against severe COVID-19.

Evaluation of Incident 7-Day Infection and Sepsis Hospitalizations in an Integrated Health System.

Rationale: Prehospital opportunities to predict infection and sepsis hospitalization may exist, but little is known about their incidence following common healthcare encounters. Objectives: To evaluate the incidence and timing of infection and sepsis hospitalization within 7 days of living hospital discharge, emergency department discharge, and ambulatory visit settings. Methods: In each setting, we identified patients in clinical strata based on the presence of infection and severity of illness. We estimated number needed to evaluate values with hypothetical predictive model operating characteristics. Results: We identified 97,614,228 encounters, including 1,117,702 (1.1%) hospital discharges, 4,635,517 (4.7%) emergency department discharges, and 91,861,009 (94.1%) ambulatory visits between 2012 and 2017. The incidence of 7-day infection hospitalization varied from 37,140 (3.3%) following inpatient discharge to 50,315 (1.1%) following emergency department discharge and 277,034 (0.3%) following ambulatory visits. The incidence of 7-day infection hospitalization was increased for inpatient discharges with high readmission risk (10.0%), emergency department discharges with increased acute or chronic severity of illness (3.5% and 4.7%, respectively), and ambulatory visits with acute infection (0.7%). The timing of 7-day infection and sepsis hospitalizations differed across settings with an early rise following ambulatory visits, a later peak following emergency department discharges, and a delayed peak following inpatient discharge. Theoretical number needed to evaluate values varied by strata, but following hospital and emergency department discharge, were as low as 15-25. Conclusions: Incident 7-day infection and sepsis hospitalizations following encounters in routine healthcare settings were surprisingly common and may be amenable to clinical predictive models.

Development and Validation of an Obstetric Comorbidity Risk Score for Clinical Use.

Background: A comorbidity summary score may support early and systematic identification of women at high risk for adverse obstetric outcomes. The objective of this study was to conduct the initial development and validation of an obstetrics comorbidity risk score for automated implementation in the electronic health record (EHR) for clinical use. Methods: The score was developed and validated using EHR data for a retrospective cohort of pregnancies with delivery between 2010 and 2018 at Kaiser Permanente Northern California, an integrated health care system. The outcome used for model development consisted of adverse obstetric events from delivery hospitalization (e.g., eclampsia, hemorrhage, death). Candidate predictors included maternal age, parity, multiple gestation, and any maternal diagnoses assigned in health care encounters in the 12 months before admission for delivery. We used penalized regression for variable selection, logistic regression to fit the model, and internal validation for model evaluation. We also evaluated prenatal model performance at 18 weeks of pregnancy. Results: The development cohort (n = 227,405 pregnancies) had an outcome rate of 3.8% and the validation cohort (n = 41,683) had an outcome rate of 2.9%. Of 276 candidate predictors, 37 were included in the final model. The final model had a validation c-statistic of 0.72 (95% confidence interval [CI] 0.70-0.73). When evaluated at 18 weeks of pregnancy, discrimination was modestly diminished (c-statistic 0.68 [95% CI 0.67-0.70]). Conclusions: The obstetric comorbidity score demonstrated good discrimination for adverse obstetric outcomes. After additional appropriate validation, the score can be automated in the EHR to support early identification of high-risk women and assist efforts to ensure risk-appropriate maternal care.

Evaluation of an intervention targeted with predictive analytics to prevent readmissions in an integrated health system: observational study.

OBJECTIVES: To determine the associations between a care coordination intervention (the Transitions Program) targeted to patients after hospital discharge and 30 day readmission and mortality in a large, integrated healthcare system. DESIGN: Observational study. SETTING: 21 hospitals operated by Kaiser Permanente Northern California. PARTICIPANTS: 1 539 285 eligible index hospital admissions corresponding to 739 040 unique patients from June 2010 to December 2018. 411 507 patients were discharged post-implementation of the Transitions Program; 80 424 (19.5%) of these patients were at medium or high predicted risk and were assigned to receive the intervention after discharge. INTERVENTION: Patients admitted to hospital were automatically assigned to be followed by the Transitions Program in the 30 days post-discharge if their predicted risk of 30 day readmission or mortality was greater than 25% on the basis of electronic health record data. MAIN OUTCOME MEASURES: Non-elective hospital readmissions and all cause mortality in the 30 days after hospital discharge. RESULTS: Difference-in-differences estimates indicated that the intervention was associated with significantly reduced odds of 30 day non-elective readmission (adjusted odds ratio 0.91, 95% confidence interval 0.89 to 0.93; absolute risk reduction 95% confidence interval -2.5%, -3.1% to -2.0%) but not with the odds of 30 day post-discharge mortality (1.00, 0.95 to 1.04). Based on the regression discontinuity estimate, the association with readmission was of similar magnitude (absolute risk reduction -2.7%, -3.2% to -2.2%) among patients at medium risk near the risk threshold used for enrollment. However, the regression discontinuity estimate of the association with post-discharge mortality (-0.7% -1.4% to -0.0%) was significant and suggested benefit in this subgroup of patients. CONCLUSIONS: In an integrated health system, the implementation of a comprehensive readmissions prevention intervention was associated with a reduction in 30 day readmission rates. Moreover, there was no association with 30 day post-discharge mortality, except among medium risk patients, where some evidence for benefit was found. Altogether, the study provides evidence to suggest the effectiveness of readmission prevention interventions in community settings, but further research might be required to confirm the findings beyond this setting.

Development of a healthcare system COVID Hotspotting Score in California: an observational study with prospective validation.

OBJECTIVE: To examine the value of health systems data as indicators of emerging COVID-19 activity. DESIGN: Observational study of health system indicators for the COVID Hotspotting Score (CHOTS) with prospective validation. SETTING AND PARTICIPANTS: An integrated healthcare delivery system in Northern California including 21 hospitals and 4.5 million members. MAIN OUTCOME MEASURES: The CHOTS incorporated 10 variables including four major (cough/cold calls, emails, new positive COVID-19 tests, COVID-19 hospital census) and six minor (COVID-19 calls, respiratory infection and COVID-19 routine and urgent visits, and respiratory viral testing) indicators assessed with change point detection and slope metrics. We quantified cross-correlations lagged by 7-42 days between CHOTS and standardised COVID-19 hospital census using observational data from 1 April to 31 May 2020 and two waves of prospective data through 21 March 2021. RESULTS: Through 30 September 2020, peak cross-correlation between CHOTS and COVID-19 hospital census occurred with a 28-day lag at 0.78; at 42 days, the correlation was 0.69. Lagged correlation between medical centre CHOTS and their COVID-19 census was highest at 42 days for one facility (0.63), at 35 days for nine facilities (0.52-0.73), at 28 days for eight facilities (0.28-0.74) and at 14 days for two facilities (0.73-0.78). The strongest correlation for individual indicators was 0.94 (COVID-19 census) and 0.90 (new positive COVID-19 tests) lagged 1-14 days and 0.83 for COVID-19 calls and urgent clinic visits lagged 14-28 days. Cross-correlation was similar (0.73) with a 35-day lag using prospective validation from 1 October 2020 to 21 March 2021. CONCLUSIONS: Passively collected health system indicators were strongly correlated with forthcoming COVID-19 hospital census up to 6 weeks before three successive COVID-19 waves. These tools could inform communities, health systems and public health officials to identify, prepare for and mitigate emerging COVID-19 activity.

Racial Disparities in COVID-19 Testing and Outcomes : Retrospective Cohort Study in an Integrated Health System.

BACKGROUND: Racial disparities exist in outcomes after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. OBJECTIVE: To evaluate the contribution of race/ethnicity in SARS-CoV-2 testing, infection, and outcomes. DESIGN: Retrospective cohort study (1 February 2020 to 31 May 2020). SETTING: Integrated health care delivery system in Northern California. PARTICIPANTS: Adult health plan members. MEASUREMENTS: Age, sex, neighborhood deprivation index, comorbid conditions, acute physiology indices, and race/ethnicity; SARS-CoV-2 testing and incidence of positive test results; and hospitalization, illness severity, and mortality. RESULTS: Among 3 481 716 eligible members, 42.0% were White, 6.4% African American, 19.9% Hispanic, and 18.6% Asian; 13.0% were of other or unknown race. Of eligible members, 91 212 (2.6%) were tested for SARS-CoV-2 infection and 3686 had positive results (overall incidence, 105.9 per 100 000 persons; by racial group, White, 55.1; African American, 123.1; Hispanic, 219.6; Asian, 111.7; other/unknown, 79.3). African American persons had the highest unadjusted testing and mortality rates, White persons had the lowest testing rates, and those with other or unknown race had the lowest mortality rates. Compared with White persons, adjusted testing rates among non-White persons were marginally higher, but infection rates were significantly higher; adjusted odds ratios [aORs] for African American persons, Hispanic persons, Asian persons, and persons of other/unknown race were 2.01 (95% CI, 1.75 to 2.31), 3.93 (CI, 3.59 to 4.30), 2.19 (CI, 1.98 to 2.42), and 1.57 (CI, 1.38 to 1.78), respectively. Geographic analyses showed that infections clustered in areas with higher proportions of non-White persons. Compared with White persons, adjusted hospitalization rates for African American persons, Hispanic persons, Asian persons, and persons of other/unknown race were 1.47 (CI, 1.03 to 2.09), 1.42 (CI, 1.11 to 1.82), 1.47 (CI, 1.13 to 1.92), and 1.03 (CI, 0.72 to 1.46), respectively. Adjusted analyses showed no racial differences in inpatient mortality or total mortality during the study period. For testing, comorbid conditions made the greatest relative contribution to model explanatory power (77.9%); race only accounted for 8.1%. Likelihood of infection was largely due to race (80.3%). For other outcomes, age was most important; race only contributed 4.5% for hospitalization, 12.8% for admission illness severity, 2.3% for in-hospital death, and 0.4% for any death. LIMITATION: The study involved an insured population in a highly integrated health system. CONCLUSION: Race was the most important predictor of SARS-CoV-2 infection. After infection, race was associated with increased hospitalization risk but not mortality. PRIMARY FUNDING SOURCE: The Permanente Medical Group, Inc.

Evaluation of Vaccination Strategies to Compare Efficient and Equitable Vaccine Allocation by Race and Ethnicity Across Time.

Importance: Identifying the most efficient COVID-19 vaccine allocation strategy may substantially reduce hospitalizations and save lives while ensuring an equitable vaccine distribution. Objective: To simulate the association of different vaccine allocation strategies with COVID-19-associated morbidity and mortality and their distribution across racial and ethnic groups. Design Setting and Participants: We developed and internally validated the risk of COVID-19 infection and risk of hospitalization models on randomly split training and validation data sets. These were used in a computer simulation study of vaccine prioritization among adult health plan members who were drawn from an integrated health care delivery system. The study was conducted from January 3, 2021, to June 1, 2021, in Oakland, California, and the data were analyzed during the same period. Main Outcomes and Measures: We simulated the association of different vaccine allocation strategies, including (1) random, (2) a US Centers for Disease Control and Prevention (CDC) proxy, (3) age based, and (4) combinations of models for the risk of adverse outcomes (CRS) and COVID-19 infection (PROVID), with COVID-19-related hospitalizations between May 1, 2020, and December 31, 2020, that were randomly permuted by month across 250 simulations and assessed vaccine allocation by race and ethnicity and the neighborhood deprivation index across time. Results: The study included 3 202 679 adult patients (mean [SD] age, 48.2 [18.0] years; 1 677 637 women [52.4%]; 1 525 042 men [47.6%]; 611 154 Asian [19.1%], 206 363 Black [6.4%], 642 344 Hispanic [20.1%], and 1 390 638 White individuals [43.4%]), of whom 36 137 (1.1%) were positive for SARS-CoV-2. A risk-based strategy (CRS/PROVID) showed the largest avoidable hospitalization estimates (4954; 95% CI, 3452-5878) followed by age-based (4362; 95% CI, 2866-5175) and CDC proxy (4085; 95% CI, 2805-5109) strategies. Random vaccination showed substantially lower reductions in adverse outcomes. Risk-based strategies also showed the largest number of avoidable COVID-19 deaths (joint CRS/PROVID) and household transmissions. Risk-based (PROVID) and CDC proxy strategies were estimated to vaccinate the highest percentage of Hispanic and Black patients in 8 months (joint CRS/PROVID: 642 570 [100%] Hispanic, 185 530 [90%] Black; PROVID: 642 570 [100%] Hispanic, 198 480 [96%] Black; CDC proxy: 605 770 [95%] Hispanic and 151 772 [74%] Black) compared with an age-based approach (438 423 [68%] Hispanic, 154 714 [75%] Black). Overall, the PROVID and joint CRS/PROVID risk-based strategies were estimated to be followed by the most patients from areas with high neighborhood deprivation index being vaccinated early. Conclusions and Relevance: In this simulation modeling study of adults from a large integrated health care delivery system, risk-based strategies were associated with the largest estimated reductions in COVID-19 hospitalizations, deaths, and household transmissions compared with the CDC proxy and age-based strategies, with a higher proportion of Hispanic and Black patients were estimated to be vaccinated early in the process compared with the CDC strategy.

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.

The Impact of Step-Down Unit Care on Patient Outcomes After ICU Discharge.

OBJECTIVES: To examine whether and how step-down unit admission after ICU discharge affects patient outcomes. DESIGN: Retrospective study using an instrumental variable approach to remove potential biases from unobserved differences in illness severity for patients admitted to the step-down unit after ICU discharge. SETTING: Ten hospitals in an integrated healthcare delivery system in Northern California. PATIENTS: Eleven-thousand fifty-eight episodes involving patients who were admitted via emergency departments to a medical service from July 2010 to June 2011, were admitted to the ICU at least once during their hospitalization, and were discharged from the ICU to the step-down unit or the ward. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Using congestion in the step-down unit as an instrumental variable, we quantified the impact of step-down unit care in terms of clinical and operational outcomes. On average, for ICU patients with lower illness severity, we found that availability of step-down unit care was associated with an absolute decrease in the likelihood of hospital readmission within 30 days of 3.9% (95% CI, 3.6-4.1%). We did not find statistically significant effects on other outcomes. For ICU patients with higher illness severity, we found that availability of step-down unit care was associated with an absolute decrease in in-hospital mortality of 2.5% (95% CI, 2.3-2.6%), a decrease in remaining hospital length-of-stay of 1.1 days (95% CI, 1.0-1.2 d), and a decrease in the likelihood of ICU readmission within 5 days of 3.6% (95% CI, 3.3-3.8%). CONCLUSIONS: This study shows that there exists a subset of patients discharged from the ICU who may benefit from care in an step-down unit relative to that in the ward. We found that step-down unit care was associated with statistically significant improvements in patient outcomes especially for high-risk patients. Our results suggest that step-down units can provide effective transitional care for ICU patients.

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.

Red blood cell transfusions for emergency department patients with gastrointestinal bleeding within an integrated health system.

STUDY OBJECTIVE: To assess trends over time in red blood cell (RBC) transfusion practice among emergency department (ED) patients with gastrointestinal (GI) bleeding within an integrated healthcare system, inclusive of 21 EDs. METHODS: Retrospective cohort of ED patients diagnosed with GI bleeding between July 1st, 2012 and September 30th, 2016. The primary outcome was receipt of an RBC transfusion in the ED. Secondary outcomes included 90-day rates of RBC transfusion, repeat ED visits, rehospitalization, and all-cause mortality. Logistic regression was used to obtain confounder-adjusted outcome rates. RESULTS: A total of 24,868 unique patient encounters were used for the primary analysis. The median hemoglobin level in the ED prior to RBC transfusion decreased from 7.5 g/dl to 6.9 g/dl in the first versus last twelve months of the study period (p < 0.0001). A small trend was observed in the overall adjusted rate of ED RBC transfusion (absolute quarterly change of -0.1%, R2 = 0.18, p = 0.0001) largely attributable to the subgroup of patients with hemoglobin nadirs between 7.0 and 9.9 g/dl (absolute quarterly change of -0.4%, R2 = 0.38, p < 0.0001). Rates of RBC transfusions through 90 days likewise decreased (absolute quarterly change of -0.4%, R2 = 0.85, p < 0.0001) with stable to decreased corresponding rates of repeat ED visits, rehospitalizations and mortality. CONCLUSION: Rates of ED RBC transfusion decreased over time among patients with GI bleeding, particularly in those with hemoglobin nadirs between 7.0 and 9.9 g/dl. These findings suggest that ED providers are willing to adopt evidence-based restrictive RBC transfusion recommendations for patients with GI bleeding.

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.

Long-Term Outcomes Among Patients Discharged From the Hospital With Moderate Anemia: A Retrospective Cohort Study.

Background: Randomized clinical trial findings support decreased red blood cell (RBC) transfusion and short-term tolerance of in-hospital anemia. However, long-term outcomes related to changes in transfusion practice have not been described. Objective: To describe the prevalence of anemia at and after hospital discharge and associated morbidity and mortality events. Design: Retrospective cohort study. Setting: Integrated health care delivery system with 21 hospitals serving 4 million members. Participants: 445 371 surviving adults who had 801 261 hospitalizations between January 2010 and December 2014. Measurements: Hemoglobin levels and RBC transfusion, rehospitalization, and mortality events within 6 months of hospital discharge. Generalized estimating equations were used to examine trends over time, accounting for correlated observations and patient-level covariates. Results: From 2010 to 2014, the prevalence of moderate anemia (hemoglobin levels between 7 and 10 g/dL) at hospital discharge increased from 20% to 25% (P < 0.001) and RBC transfusion declined by 28% (39.8 to 28.5 RBC units per 1000 patients; P < 0.001). The proportion of patients whose moderate anemia had resolved within 6 months of hospital discharge decreased from 42% to 34% (P < 0.001), and RBC transfusion and rehospitalization within 6 months of hospital discharge decreased from 19% to 17% and 37% to 33%, respectively (P < 0.001 for both). During this period, the adjusted 6-month mortality rate decreased from 16.1% to 15.6% (P = 0.004) in patients with moderate anemia, in parallel with that of all others. Limitation: Possible unmeasured confounding. Conclusion: Anemia after hospitalization increased in parallel with decreased RBC transfusion. This increase was not accompanied by a rise in subsequent RBC use, rehospitalization, or mortality within 6 months of hospital discharge. Longitudinal analyses support the safety of practice recommendations to limit RBC transfusion and tolerate anemia during and after hospitalization. Primary Funding Source: National Heart, Lung, and Blood Institute.

Impact of emergency physician-provided patient education about alternative care venues.

OBJECTIVES: Interventions that focus on educating patients appear to be the most effective in directing healthcare utilization to more appropriate venues. We sought to evaluate the effects of mailed information and a brief scripted educational phone call from an emergency physician (EP) on subsequent emergency department (ED) utilization by low-risk adults with a recent treat-and-release ED visit. STUDY DESIGN: Patients were randomized into 3 groups for post-ED follow-up: EP phone call with mailed information, mailed information only, and no educational intervention. Each intervention group was compared with a set of matched controls. METHODS: We undertook this study in 6 EDs within an integrated healthcare delivery system. Overall, 9093 patients were identified; the final groups were the phone group (n = 609), mail group (n = 771), and matched control groups for each (n = 1827 and n = 1542, respectively). Analysis was stratified by age (<65 and ≥65 years). Patients were educated about available venues of care delivery for their future medical needs. The primary outcome was the rate of 6-month ED utilization after the intervention compared with the 6-month utilization rate preceding the intervention. RESULTS: Compared with matched controls, subsequent ED utilization decreased by 22% for patients 65 years or older in the phone group (P = .04) and by 27% for patients younger than 65 years in the mail group (P = .03). CONCLUSIONS: ED utilization subsequent to a low-acuity ED visit decreased after a brief post-ED education intervention by an EP explaining alternative venues of care for future medical needs. Response to the method of communication (phone vs mail) varied significantly by patient age.

Risk Adjustment for Hospital Characteristics Reduces Unexplained Hospital Variation in Pressure Injury Risk.

BACKGROUND: Research investigating risk factors for hospital-acquired pressure injury (HAPI) has primarily focused on the characteristics of patients and nursing staff. Limited data are available on the association of hospital characteristics with HAPI. OBJECTIVE: We aimed to quantify the association of hospital characteristics with HAPI and their effect on residual hospital variation in HAPI risk. METHODS: We employed a retrospective cohort study design with split validation using hierarchical survival analysis. This study extends the analysis "Hospital-Acquired Pressure Injury (HAPI): Risk Adjusted Comparisons in an Integrated Healthcare Delivery System" by Rondinelli et al. (2018) to include hospital-level factors. We analyzed 1,661 HAPI episodes among 728,266 adult hospitalization episodes across 35 California Kaiser Permanente hospitals, an integrated healthcare delivery system between January 1, 2013, and June 30, 2015. RESULTS: After adjusting for patient-level and hospital-level variables, 2 out of 12 candidate hospital variables were statistically significant predictors of HAPI. The hazard for HAPI decreased by 4.8% for every 0.1% increase in a hospital's mean mortality ([6.3%, 2.6%], p < .001), whereas every 1% increase in a hospital's proportion of patients with a history of diabetes increased HAPI hazard by 5% ([-0.04%, 10.0%], p = .072). Addition of these hierarchical variables decreased unexplained hospital variation of HAPI risk by 35%. DISCUSSION: We found hospitals with higher patient mortality had lower HAPI risk. Higher patient mortality may decrease the pool of patients who live to HAPI occurrence. Such hospitals may also provide more resources (specialty staff) to care for frail patient populations. Future research should aim to combine hospital data sets to overcome power limitations at the hospital level and should investigate additional measures of structure and process related to HAPI care.

The Impact of Acute Organ Dysfunction on Long-Term Survival in Sepsis.

OBJECTIVES: To estimate the impact of each of six types of acute organ dysfunction (hepatic, renal, coagulation, neurologic, cardiac, and respiratory) on long-term mortality after surviving sepsis hospitalization. DESIGN: Multicenter, retrospective study. SETTINGS: Twenty-one hospitals within an integrated healthcare delivery system in Northern California. PATIENTS: Thirty thousand one hundred sixty-three sepsis patients admitted through the emergency department between 2010 and 2013, with mortality follow-up through April 2015. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Acute organ dysfunction was quantified using modified Sequential Organ Failure Assessment scores. The main outcome was long-term mortality among sepsis patients who survived hospitalization. The estimates of the impact of each type of acute organ dysfunction on long-term mortality were based on adjusted Cox proportional hazards models. Sensitivity analyses were conducted based on propensity score-matching and adjusted logistic regression. Hospital mortality was 9.4% and mortality was 31.7% at 1 year. Median follow-up time among sepsis survivors was 797 days (interquartile range: 384-1,219 d). Acute neurologic (odds ratio, 1.86; p < 0.001), respiratory (odds ratio, 1.43; p < 0.001), and cardiac (odds ratio, 1.31; p < 0.001) dysfunction were most strongly associated with short-term hospital mortality, compared with sepsis patients without these organ dysfunctions. Evaluating only patients surviving their sepsis hospitalization, acute neurologic dysfunction was also most strongly associated with long-term mortality (odds ratio, 1.52; p < 0.001) corresponding to a marginal increase in predicted 1-year mortality of 6.0% for the presence of any neurologic dysfunction (p < 0.001). Liver dysfunction was also associated with long-term mortality in all models, whereas the association for other organ dysfunction subtypes was inconsistent between models. CONCLUSIONS: Acute sepsis-related neurologic dysfunction was the organ dysfunction most strongly associated with short- and long-term mortality and represents a key mediator of long-term adverse outcomes following sepsis.

Incorporating Longitudinal Comorbidity and Acute Physiology Data in Template Matching for Assessing Hospital Quality: An Exploratory Study in an Integrated Health Care Delivery System.

OBJECTIVE: We sought to build on the template-matching methodology by incorporating longitudinal comorbidities and acute physiology to audit hospital quality. STUDY SETTING: Patients admitted for sepsis and pneumonia, congestive heart failure, hip fracture, and cancer between January 2010 and November 2011 at 18 Kaiser Permanente Northern California hospitals. STUDY DESIGN: We generated a representative template of 250 patients in 4 diagnosis groups. We then matched between 1 and 5 patients at each hospital to this template using varying levels of patient information. DATA COLLECTION: Data were collected retrospectively from inpatient and outpatient electronic records. PRINCIPAL FINDINGS: Matching on both present-on-admission comorbidity history and physiological data significantly reduced the variation across hospitals in patient severity of illness levels compared with matching on administrative data only. After adjustment for longitudinal comorbidity and acute physiology, hospital rankings on 30-day mortality and estimates of length of stay were statistically different from rankings based on administrative data. CONCLUSIONS: Template matching-based approaches to hospital quality assessment can be enhanced using more granular electronic medical record data.

Accuracy of international classification of diseases, ninth revision, codes for postpartum hemorrhage among women undergoing cesarean delivery.

BACKGROUND: Determining the accuracy of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9) codes for postpartum hemorrhage (PPH) is vital for reaching valid conclusions about the epidemiology of PPH. Our primary objectives were to assess the performance characteristics of ICD-9 PPH codes against a reference standard using estimated blood loss (EBL) among a cohort undergoing Cesarean delivery. STUDY DESIGN AND METHODS: We analyzed maternal discharge and EBL data from women who underwent Cesarean delivery at Kaiser Permanente Northern California facilities between 2010 and 2013. We defined PPH as an EBL of at least 1000 mL. In a secondary analysis, ICD-9 performance characteristics were assessed using an EBL of at least 1500 mL to classify severe PPH. RESULTS: We identified 35,614 hospitalizations for Cesarean delivery. Using EBL of at least 1000 mL as the "gold standard," PPH codes had a sensitivity of 27.8%, specificity of 97%, positive predictive value (PPV) of 74.5%, and a negative predictive value (NPV) of 80.9%. The prevalence of a PPH code (9%) was lower than the prevalence using a blood loss of at least 1000 mL (24%). Using a reference standard of EBL of at least 1500 mL, PPH codes had a sensitivity of 61.7%, specificity of 93.8%, PPV of 34.2%, and NPV of 97.9%. CONCLUSION: PPH ICD-9 codes have high specificity, moderately high PPVs and NPVs, and low sensitivity. An EBL of at least 1500 mL as a reference standard has higher sensitivity. Our findings suggest that, for women undergoing Cesarean delivery, quality improvement efforts are needed to enhance PPH ICD-9 coding accuracy in administrative data sets.