Hospital Readmissions Among Patients Experiencing Homelessness: An Electronic Health Record Data Study.

BACKGROUND: Population-level tracking of hospital use patterns with integrated care organizations in patients experiencing homelessness has been difficult. A California law implemented in 2019 (Senate Bill 1152) aimed to ensure safety for this population after discharge from the hospital by requiring additional documentation for patients experiencing homelessness, which provides an opportunity to evaluate hospital use by this population. METHODS: In a large integrated health system in California, patients experiencing homelessness were identified through documentation change requirements associated with this law and compared with a matched group from the general population. RESULTS: Patients experiencing homelessness had increased rates of hospital readmission after discharge compared to the general population matched on demographics and medical comorbidity in 2019 and 2020. Any address change in the prior year for patients was associated with increased odds of emergency department readmission. Patients experiencing homelessness, both enrolled in an integrated delivery system and not, were successfully identified as having higher readmission rates compared with their housed counterparts. CONCLUSION: Documentation of housing status following Senate Bill 1152 has enabled improved study of hospital use among those with housing instability. Understanding patterns of hospital use in this vulnerable group will help practitioners identify timely points of intervention for further social and health care support.

Identifying Predictors of Homelessness Among Adults in a Large Integrated Health System in Northern California.

Introduction Homelessness contributes to worsening health and increased health care costs. There is little published research that leverages rich electronic health record (EHR) data to predict future homelessness risk and inform interventions to address it. The authors' objective was to develop a model for predicting future homelessness using individual EHR and geographic data covariates. Methods This retrospective cohort study included 2,543,504 adult members (≥ 18 years old) from Kaiser Permanente Northern California and evaluated which covariates predicted a composite outcome of homelessness status (hospital discharge documentation of a homeless patient, medical diagnosis of homelessness, approved medical financial assistance application for homelessness, and/or "homeless/shelter" in address name). The predictors were measured in 2018-2019 and included prior diagnoses and demographic and geographic data. The outcome was measured in 2020. The cohort was split (70:30) into a derivation and validation set, and logistic regression was used to model the outcome. Results Homelessness prevalence was 0.35% in the overall sample. The final logistic regression model included 26 prior diagnoses, demographic, and geographic-level predictors. The regression model using the validation set had moderate sensitivity (80.4%) and specificity (83.2%) for predicting future cases of homelessness and achieved excellent classification properties (area under the curve of 0.891 [95% confidence interval = 0.884-0.897]). Discussion This prediction model can be used as an initial triage step to enhance screening and referral tools for identifying and addressing homelessness, which can improve health and reduce health care costs. Conclusions EHR data can be used to predict chance of homelessness at a population health level.

Association of Cardiovascular Outcomes and Mortality With Sustained Long-Acting Insulin Only vs Long-Acting Plus Short-Acting Insulin Treatment.

Importance: Cardiovascular events and mortality are the principal causes of excess mortality and health care costs for people with type 2 diabetes. No large studies have specifically compared long-acting insulin alone with long-acting plus short-acting insulin with regard to cardiovascular outcomes. Objective: To compare cardiovascular events and mortality in adults with type 2 diabetes receiving long-acting insulin who do or do not add short-acting insulin. Design, Setting, and Participants: This retrospective cohort study emulated a randomized experiment in which adults with type 2 diabetes who experienced a qualifying glycated hemoglobin A1c (HbA1c) level of 6.8% to 8.5% with long-acting insulin were randomized to continuing treatment with long-acting insulin (LA group) or adding short-acting insulin within 1 year of the qualifying HbA1c level (LA plus SA group). Retrospective data in 4 integrated health care delivery systems from the Health Care Systems Research Network from January 1, 2005, to December 31, 2013, were used. Analysis used inverse probability weighting estimation with Super Learner for propensity score estimation. Analyses took place from April 1, 2018, to June 30, 2019. Exposures: Long-acting insulin alone or with added short-acting insulin within 1 year from the qualifying HbA1c level. Main Outcomes and Measures: Mortality, cardiovascular mortality, acute myocardial infarction, stroke, and hospitalization for heart failure. Results: Among 57 278 individuals (39 279 with data on cardiovascular mortality) with a mean (SD) age of 60.6 (11.5) years, 53.6% men, 43.5% non-Hispanic White individuals, and 4 years of follow-up (median follow-up of 11 [interquartile range, 5-20] calendar quarters), the LA plus SA group was associated with increased all-cause mortality compared with the LA group (hazard ratio, 1.27; 95% CI, 1.05-1.49) and a decreased risk of acute myocardial infarction (hazard ratio, 0.89; 95% CI, 0.81-0.97). Treatment with long-acting plus short-acting insulin was not associated with increased risks of congestive heart failure, stroke, or cardiovascular mortality. Conclusions and Relevance: Findings of this retrospective cohort study suggested an increased risk of all-cause mortality and a decreased risk of acute myocardial infarction for the LA plus SA group compared with the LA group. Given the lack of an increase in major cardiovascular events or cardiovascular mortality, the increased all-cause mortality with long-acting plus short-acting insulin may be explained by noncardiovascular events or unmeasured confounding.

Smoking cessation treatment for individuals with comorbid diabetes and serious mental illness in an integrated health care delivery system.

INTRODUCTION: Smoking is a significant modifiable risk factor for mortality for persons with serious mental illness (SMI), who have a life expectancy 15-20 years shorter than the general population. Individuals with SMI and comorbid diabetes who are smokers face an even higher risk of cardiovascular complications and early death. Yet despite high rates of smoking among people with SMI, tobacco cessation interventions have not been broadly offered to this population. METHODS: We conducted a retrospective cohort study using electronic health records from 2014 in a large integrated care delivery system to examine whether use of smoking cessation pharmacotherapy among smokers with type 2 diabetes varies by serious mental illness (SMI) diagnosis. We analyzed smoking cessation medication prescription fills among adult smokers with diabetes, comparing those with SMI (N = 634) and without SMI (N = 18,021). Risk ratios were adjusted for age, gender, race, urban area type, and medical facility. RESULTS: Of the SMI group, 19.09% filled at least one smoking cessation prescription compared to 9.73% of the non-SMI group (adjusted risk ratio 1.80 [95% CI 1.52-2.13]; p < .001). For the SMI group, primary care providers wrote 80.24% of prescriptions, while psychiatrists wrote 8.81% of prescriptions. CONCLUSIONS: These findings offer an example of a delivery system with higher uptake of smoking cessation pharmacotherapy among people with SMI than without SMI, and highlight the opportunity to provide more smoking cessation interventions in mental health care settings.

Racial and Ethnic Disparities in Diabetes Care Quality among Women of Reproductive Age in an Integrated Delivery System.

BACKGROUND: Diabetes is increasingly prevalent among women of reproductive age, yet little is known about quality of diabetes care for this population at increased risk of diabetes complications and poor maternal and infant health outcomes. Previous studies have identified racial/ethnic disparities in diabetes care, but patterns among women of reproductive age have not been examined. METHODS: This retrospective cohort study analyzed 2016 data from Kaiser Permanente Northern California, a large integrated delivery system. Outcomes were quality of diabetes care measures-glycemic testing, glycemic control, and medication adherence-among women ages 18 to 44 with type 1 or type 2 diabetes (N = 9,923). Poisson regression was used to estimate the association between patient race/ethnicity and each outcome, adjusting for other patient characteristics and health care use. RESULTS: In this cohort, 83% of participants had type 2 diabetes; 31% and 36% of women with type 2 and type 1 diabetes, respectively, had poor glycemic control (hemoglobin A1c of ≥9%), and approximately one-third of women with type 2 diabetes exhibited nonadherence to diabetes medications. Compared with non-Hispanic White women with type 2 diabetes, non-Hispanic Black women (adjusted risk ratio, 1.2; 95% confidence interval, 1.1-1.3) and Hispanic women (adjusted risk ratio, 1.2; 95% confidence interval, 1.1-1.3) were more likely to have poor control. Findings among women with type 1 diabetes were similar. CONCLUSIONS: Our findings indicate opportunities to decrease disparities and improve quality of diabetes care for reproductive-aged women. Elucidating the contributing factors to poor glycemic control and medication adherence in this population, particularly among Black, Hispanic, and Asian women, should be a high research and practice priority.

Comorbid Diabetes and Severe Mental Illness: Outcomes in an Integrated Health Care Delivery System.

BACKGROUND: Diabetes prevalence is twice as high among people with severe mental illness (SMI) when compared to the general population. Despite high prevalence, care outcomes are not well understood. OBJECTIVE: To compare diabetes health outcomes received by people with and without comorbid SMI, and to understand demographic factors associated with poor diabetes control among those with SMI. DESIGN: Retrospective cohort study PARTICIPANTS: 269,243 adults with diabetes MAIN MEASURES: Primary outcomes included optimal glycemic control (A1c < 7) or poor diabetes control (A1c > 9) in 2014. Secondary outcomes included control of other cardiometabolic risk factors (hypertension, dyslipidemia, smoking) and recommended diabetes monitoring. KEY RESULTS: Among this cohort, people with SMI (N = 4,399), compared to those without SMI (N = 264,844), were more likely to have optimal glycemic control, adjusting for various covariates (adjusted relative risk (aRR) 1.25, 95% CI 1.21-1.28, p < .001) and less likely to have poor control (aRR 0.92, 95% CI 0.87-0.98, p = 0.012). Better blood pressure and lipid control was more prevalent among people with SMI when compared to those without SMI (aRR 1.03; 95% CI 1.02-1.05, p < .001; aRR 1.02; 95% CI 1.00-1.05, p = 0.044, respectively). No differences were observed in recommended A1c or LDL testing, but people with SMI were more likely to have blood pressure checked (aRR 1.02, 95% CI 1.02-1.03, p < .001) and less likely to receive retinopathy screening (aRR 0.80, 95% CI 0.71-0.91, p < .001) than those without SMI. Among people with diabetes and comorbid SMI, younger adults and Hispanics were more likely to have poor diabetes control. CONCLUSIONS: Adults with diabetes and comorbid SMI had better cardiometabolic control than people with diabetes who did not have SMI, despite lower rates of retinopathy screening. Among those with comorbid SMI, younger adults and Hispanics were more vulnerable to poor A1c control.

Identifying Common Predictors of Multiple Adverse Outcomes Among Elderly Adults With Type-2 Diabetes.

OBJECTIVE: As part of a multidisciplinary team managing patients with type-2 diabetes, pharmacists need a consistent approach of identifying and prioritizing patients at highest risk of adverse outcomes. Our objective was to identify which predictors of adverse outcomes among type-2 diabetes patients were significant and common across 7 outcomes and whether these predictors improved the performance of risk prediction models. Identifying such predictors would allow pharmacists and other health care providers to prioritize their patient panels. RESEARCH DESIGN AND METHODS: Our study population included 120,256 adults aged 65 years or older with type-2 diabetes from a large integrated health system. Through an observational retrospective cohort study design, we assessed which risk factors were associated with 7 adverse outcomes (hypoglycemia, hip fractures, syncope, emergency department visit or hospital admission, death, and 2 combined outcomes). We split (50:50) our study cohort into a test and training set. We used logistic regression to model outcomes in the test set and performed k-fold validation (k=5) of the combined outcome (without death) within the validation set. RESULTS: The most significant predictors across the 7 outcomes were: age, number of medicines, prior history of outcome within the past 2 years, chronic kidney disease, depression, and retinopathy. Experiencing an adverse outcome within the prior 2 years was the strongest predictor of future adverse outcomes (odds ratio range: 4.15-7.42). The best performing models across all outcomes included: prior history of outcome, physiological characteristics, comorbidities and pharmacy-specific factors (c-statistic range: 0.71-0.80). CONCLUSIONS: Pharmacists and other health care providers can use models with prior history of adverse event, number of medicines, chronic kidney disease, depression and retinopathy to prioritize interventions for elderly patients with type-2 diabetes.

Diabetes Screening among Antipsychotic-Treated Adults with Severe Mental Illness in an Integrated Delivery System: A Retrospective Cohort Study.

BACKGROUND: Severe mental illness (SMI) is associated with increased risk for type 2 diabetes, partly due to adverse metabolic effects of antipsychotic medications. In public health care settings, annual screening rates are 30%. We measured adherence to national diabetes screening guidelines for patients taking antipsychotic medications. OBJECTIVE: To estimate diabetes screening prevalence among patients with SMI within an integrated health care system, and to assess characteristics associated with lack of screening. DESIGN: Retrospective cohort study. PARTICIPANTS: Antipsychotic-treated adults with SMI. We excluded participants with known diabetes. MAIN MEASURES: Primary outcome was screening via fasting glucose test or hemoglobin A1c during a 1-year period. KEY RESULTS: In 2014, 16,754 patients with SMI diagnoses were receiving antipsychotics. Seventy-four percent of these patients' providers ordered diabetes screening tests that year, but only 55% (9247/16,754) received screening. When the observation time frame was extended to 2 years, 73% (12,250/16,754) were screened. Adjusting for sex and race/ethnicity, young adults (aged 18-29 years) were less likely to receive screening than older age groups [adjusted RR (aRR) 1.23-1.57, p < 0.0001]. Compared to whites, screening was more common for Asians (aRR 1.141, 95% CI 1.089-1.195, p < 0.0001), less common for blacks (aRR 0.946, 95% CI 0.898-0.997, p < 0.0375), and no different for Hispanics (aRR 1.030, 95% CI 0.988-1.074, p = 0.165). Smokers were less likely to be screened than non-smokers (aRR 0.93, 95% CI 0.89-0.97, p < 0.0008). Utilization of either mental health or primary care services increased the likelihood of screening. CONCLUSIONS: While almost three-fourths of adults with SMI taking antipsychotic medications received a lab order for diabetes screening, only 55% received screening within a 12-month period. Young adults and smokers were less likely to be screened, despite their disproportionate metabolic risk. Future studies should assess the barriers and facilitators with regard to diabetes screening in this vulnerable population at the patient, provider, and system levels.

Opportunities to Reduce Diabetes Risk in Women of Reproductive Age: Assessment and Treatment of Prediabetes within a Large Integrated Delivery System.

BACKGROUND: Preventing diabetes before pregnancy may be important to improve maternal and infant outcomes. Although the preconception period is a crucial time to focus on chronic disease prevention, little is known about preventive services for reproductive-aged women at risk of developing diabetes. METHODS: Using electronic health record data from patients at Kaiser Permanente Northern California, we identified 21,965 nonpregnant women aged 18 to 44 with incident prediabetes (PDM; fasting plasma glucose [FPG] = 100-125 or glycated hemoglobin A1c = 5.7%-6.4%) between 2007 and 2010. We looked for evidence of a "clinical response" to PDM in the 6 months after laboratory testing, defined as retesting of blood glucose levels, referral or attendance to health education, diagnosis of PDM, metformin initiation, or a clinical note of discussion of PDM. Multilevel models were used to examine the relationship between patient characteristics and clinical response, and to assess provider-level variation. RESULTS: Fewer than one-half of women had a documented clinical response to the PDM-range laboratory result. Women with higher FPG values and body mass indexes were more likely to have a PDM diagnosis (FPG 120-125 vs. 100-119: OR, 1.96; 95% CI, 1.78-2.17; body mass index, 30-34 kg/m2 vs. <25 kg/m2: OR, 1.30; 95% CI, 1.13-1.48) and have 'PDM' recorded in the notes (FPG 120-125 vs. 100-119: OR, 1.15; 95% CI, 1.06-1.26; body mass index: 30-34 kg/m2 vs. <25 kg/m2: OR, 1.58; 95% CI, 1.44-1.74). Provider-level variation was modest, except for metformin initiation (intraclass correlation coefficient, 0.8; p < .01). CONCLUSIONS: Low clinical response to PDM among women of reproductive age suggests there are missed opportunities for diabetes prevention among this vulnerable population.

Prescription medication burden in patients with newly diagnosed diabetes: a SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) study.

OBJECTIVE: To understand the burden of medication use for patients with newly diagnosed diabetes both before and after diabetes diagnosis and to identify subpopulations of patients with newly diagnosed diabetes who face a relatively high drug burden. DESIGN: Retrospective cohort study. SETTING: 11 integrated health systems in the United States. PARTICIPANTS: 196,654 insured adults 20 years of age or older newly diagnosed with type 1 or type 2 diabetes from January 2005 through December 2009. MAIN OUTCOME MEASURES: Number of unique therapeutic classes of drugs dispensed in the 12 months before and 12 months after diagnosis of diabetes in five categories: overall, antihypertensive agents, antihyperlipidemic agents, mental health agents, and antihyperglycemic agents (in the postdiagnosis period only). RESULTS: The mean number of drug classes used by newly diagnosed patients with diabetes is high before diagnosis (5.0) and increases significantly afterward (6.6). Of this increase, 81% is due to antihyperglycemic initiation and increased use of medications to control hypertension and lipid levels. Multivariate analyses showed that overall drug burden after diabetes diagnosis was higher in women, older, white, and obese patients, as well as among those with higher glycosylated hemoglobin concentrations and comorbidity levels (significant for all comparisons). The overall number of drug classes used by newly diagnosed patients with diabetes after diagnosis decreased slightly but significantly between 2005 and 2009. CONCLUSION: Patients newly diagnosed with diabetes face a substantially increased burden of medications used to control diabetes and other comorbidities. This study shows an increased focus on cardiovascular disease risk factor control after diagnosis of diabetes. However, total drug burden may be slightly decreasing over time.