The electronic health record Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) Brain Health Trial: Protocol for an embedded, pragmatic clinical trial of a low-cost dementia detection algorithm.

BACKGROUND: About half of people living with dementia have not received a diagnosis, delaying access to treatment, education, and support. We previously developed a tool, eRADAR, which uses information in the electronic health record (EHR) to identify patients who may have undiagnosed dementia. This paper provides the protocol for an embedded, pragmatic clinical trial (ePCT) implementing eRADAR in two healthcare systems to determine whether an intervention using eRADAR increases dementia diagnosis rates and to examine the benefits and harms experienced by patients and other stakeholders. METHODS: We will conduct an ePCT within an integrated healthcare system and replicate it in an urban academic medical center. At primary care clinics serving about 27,000 patients age 65 and above, we will randomize primary care providers (PCPs) to have their patients with high eRADAR scores receive targeted outreach (intervention) or usual care. Intervention patients will be offered a "brain health" assessment visit with a clinical research interventionist mirroring existing roles within the healthcare systems. The interventionist will make follow-up recommendations to PCPs and offer support to newly-diagnosed patients. Patients with high eRADAR scores in both study arms will be followed to identify new diagnoses of dementia in the EHR (primary outcome). Secondary outcomes include healthcare utilization from the EHR and patient, family member and clinician satisfaction assessed through surveys and interviews. CONCLUSION: If this pragmatic trial is successful, the eRADAR tool and intervention could be adopted by other healthcare systems, potentially improving dementia detection, patient care and quality of life.

Association Between Diabetes Severity and Risks of COVID-19 Infection and Outcomes.

BACKGROUND: Little is known about whether diabetes increases the risk of COVID-19 infection and whether measures of diabetes severity are related to COVID-19 outcomes. OBJECTIVE: Investigate diabetes severity measures as potential risk factors for COVID-19 infection and COVID-19 outcomes. DESIGN, PARTICIPANTS, MEASURES: In integrated healthcare systems in Colorado, Oregon, and Washington, we identified a cohort of adults on February 29, 2020 (n = 1,086,918) and conducted follow-up through February 28, 2021. Electronic health data and death certificates were used to identify markers of diabetes severity, covariates, and outcomes. Outcomes were COVID-19 infection (positive nucleic acid antigen test, COVID-19 hospitalization, or COVID-19 death) and severe COVID-19 (invasive mechanical ventilation or COVID-19 death). Individuals with diabetes (n = 142,340) and categories of diabetes severity measures were compared with a referent group with no diabetes (n = 944,578), adjusting for demographic variables, neighborhood deprivation index, body mass index, and comorbidities. RESULTS: Of 30,935 patients with COVID-19 infection, 996 met the criteria for severe COVID-19. Type 1 (odds ratio [OR] 1.41, 95% CI 1.27-1.57) and type 2 diabetes (OR 1.27, 95% CI 1.23-1.31) were associated with increased risk of COVID-19 infection. Insulin treatment was associated with greater COVID-19 infection risk (OR 1.43, 95% CI 1.34-1.52) than treatment with non-insulin drugs (OR 1.26, 95% 1.20-1.33) or no treatment (OR 1.24; 1.18-1.29). The relationship between glycemic control and COVID-19 infection risk was dose-dependent: from an OR of 1.21 (95% CI 1.15-1.26) for hemoglobin A1c (HbA1c) < 7% to an OR of 1.62 (95% CI 1.51-1.75) for HbA1c ≥ 9%. Risk factors for severe COVID-19 were type 1 diabetes (OR 2.87; 95% CI 1.99-4.15), type 2 diabetes (OR 1.80; 95% CI 1.55-2.09), insulin treatment (OR 2.65; 95% CI 2.13-3.28), and HbA1c ≥ 9% (OR 2.61; 95% CI 1.94-3.52). CONCLUSIONS: Diabetes and greater diabetes severity were associated with increased risks of COVID-19 infection and worse COVID-19 outcomes.

External Validation of the eRADAR Risk Score for Detecting Undiagnosed Dementia in Two Real-World Healthcare Systems.

BACKGROUND: Fifty percent of people living with dementia are undiagnosed. The electronic health record (EHR) Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) was developed to identify older adults at risk of having undiagnosed dementia using routinely collected clinical data. OBJECTIVE: To externally validate eRADAR in two real-world healthcare systems, including examining performance over time and by race/ethnicity. DESIGN: Retrospective cohort study PARTICIPANTS: 129,315 members of Kaiser Permanente Washington (KPWA), an integrated health system providing insurance coverage and medical care, and 13,444 primary care patients at University of California San Francisco Health (UCSF), an academic medical system, aged 65 years or older without prior EHR documentation of dementia diagnosis or medication. MAIN MEASURES: Performance of eRADAR scores, calculated annually from EHR data (including vital signs, diagnoses, medications, and utilization in the prior 2 years), for predicting EHR documentation of incident dementia diagnosis within 12 months. KEY RESULTS: A total of 7631 dementia diagnoses were observed at KPWA (11.1 per 1000 person-years) and 216 at UCSF (4.6 per 1000 person-years). The area under the curve was 0.84 (95% confidence interval: 0.84-0.85) at KPWA and 0.79 (0.76-0.82) at UCSF. Using the 90th percentile as the cut point for identifying high-risk patients, sensitivity was 54% (53-56%) at KPWA and 44% (38-51%) at UCSF. Performance was similar over time, including across the transition from International Classification of Diseases, version 9 (ICD-9) to ICD-10 codes, and across racial/ethnic groups (though small samples limited precision in some groups). CONCLUSIONS: eRADAR showed strong external validity for detecting undiagnosed dementia in two health systems with different patient populations and differential availability of external healthcare data for risk calculations. In this study, eRADAR demonstrated generalizability from a research sample to real-world clinical populations, transportability across health systems, robustness to temporal changes in healthcare, and similar performance across larger racial/ethnic groups.

Identifying hypertensive disorders of pregnancy, a comparison of two epidemiologic definitions.

Introduction: Studies of hypertension in pregnancy that use electronic health care data generally identify hypertension using hospital diagnosis codes alone. We sought to compare results from this approach to an approach that included diagnosis codes, antihypertensive medications and blood pressure (BP) values. Materials and methods: We conducted a retrospective cohort study of 1,45,739 pregnancies from 2009 to 2014 within an integrated healthcare system. Hypertensive pregnancies were identified using the "BP-Inclusive Definition" if at least one of three criteria were met: (1) two elevated outpatient BPs, (2) antihypertensive medication fill plus an outpatient hypertension diagnosis, or (3) hospital discharge diagnosis for preeclampsia or eclampsia. The "Traditional Definition" considered only delivery hospitalization discharge diagnoses. Outcome event analyses compared rates of preterm delivery and small for gestational age (SGA) between the two definitions. Results: The BP-Inclusive Definition identified 14,225 (9.8%) hypertensive pregnancies while the Traditional Definition identified 13,637 (9.4%); 10,809 women met both definitions. Preterm delivery occurred in 20.9% of BP-Inclusive Definition pregnancies, 21.8% of Traditional Definition pregnancies and 6.6% of non-hypertensive pregnancies; for SGA the numbers were 15.6, 16.3, and 8.6%, respectively (p < 0.001 for all events compared to non-hypertensive pregnancies). Analyses in women meeting only one hypertension definition (21-24% of positive cases) found much lower rates of both preterm delivery and SGA. Conclusion: Prevalence of hypertension in pregnancy was similar between the two study definitions. However, a substantial number of women met only one of the study definitions. Women who met only one of the hypertension definitions had much lower rates of adverse neonatal events than women meeting both definitions.

Maternal and neonatal outcomes of antihypertensive treatment in pregnancy: A retrospective cohort study.

OBJECTIVE: To compare maternal and infant outcomes with different antihypertensive medications in pregnancy. DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente, a large healthcare system in the United States. POPULATION: Women aged 15-49 years with a singleton birth from 2005-2014 treated for hypertension. METHODS: We identified medication exposure from automated pharmacy data based on the earliest dispensing after the first prenatal visit. Using logistic regression, we calculated weighted outcome prevalences, adjusted odds ratios (aORs) and 95% confidence intervals, with inverse probability of treatment weighting to address confounding. MAIN OUTCOME MEASURES: Small for gestational age, preterm delivery, neonatal and maternal intensive care unit (ICU) admission, preeclampsia, and stillbirth or termination at > 20 weeks. RESULTS: Among 6346 deliveries, 87% with chronic hypertension, the risk of the infant being small for gestational age (birthweight < 10th percentile) was lower with methyldopa than labetalol (prevalence 13.6% vs. 16.6%; aOR 0.77, 95% CI 0.63 to 0.92). For birthweight < 3rd percentile the aOR was 0.57 (0.39 to 0.80). Compared with labetalol (26.0%), risk of preterm delivery was similar for methyldopa (26.5%; aOR 1.10 [0.95 to 1.27]) and slightly higher for nifedipine (28.5%; aOR 1.25 [1.06 to 1.46]) and other ß-blockers (31.2%; aOR 1.58 [1.07 to 2.23]). Neonatal ICU admission was more common with nifedipine than labetalol (25.9% vs. 23.3%, aOR 1.21 [1.02 to 1.43]) but not elevated with methyldopa. Risks of other outcomes did not differ by medication. CONCLUSIONS: Risk of most outcomes was similar comparing labetalol, methyldopa and nifedipine. Risk of the infant being small for gestational age was substantially lower for methyldopa, suggesting this medication may warrant further consideration.

Use of a mobile app to capture supplemental health information during pregnancy: Implications for clinical research.

PURPOSE: Mobile applications ("apps") may be efficient tools for improving the quality of clinical research among pregnant women, but evidence is sparse. We assess the feasibility and generalizability of a mobile app for capturing supplemental data during pregnancy. METHODS: In 2017, we conducted a pilot study of the FDA MyStudies mobile app within a pregnant population identified through Kaiser Permanente Washington (KPWA), an integrated healthcare delivery system. We ascertained health conditions, medications, and substance use through app-based questionnaires. In a post-hoc analysis, we utilized electronic health records (EHR) to summarize sociodemographic and health characteristics of pilot participants and, for comparison, a pregnant population identified using similar methods. RESULTS: Six percent (64/1070) of contacted women enrolled in the pilot study. Nearly half (23/53) reported taking medication for headaches and one-fourth for constipation (13/53) and nausea (12/53) each. Few instances (2/92) of over-the-counter medication use were identified in electronic dispensing records. One-quarter to one-third of participants with depression and anxiety/panic, respectively, reported recently discontinuing medications for these conditions. Eighty-eight percent of pilot participants reported White race (95%CI: 81-95%), versus 67% of the comparison population (N = 2065). More pilot participants filled ≥1 prescription for antianxiety medication (22% [95%CI: 13-35%]) and antidepressants (19% [95%CI 10-31%]) pre-pregnancy than the comparison population (10 and 9%, respectively). CONCLUSIONS: Mobile apps may be a feasible tool for capturing health data not routinely available in EHR. Pregnant women willing to use a mobile app for research may differ from the general pregnant population, but confirmation is needed.

Patient and caregiver perspectives on a tool to increase recognition of undiagnosed dementia: a qualitative study.

BACKGROUND: Early detection of dementia may improve patient care and quality of life, yet up to half of people with dementia are undiagnosed. Electronic health record (EHR) data could be used to help identify individuals at risk of having undiagnosed dementia for outreach and assessment, but acceptability to people with dementia and caregivers is unknown. METHODS: We conducted five focus groups at Kaiser Permanente Washington (KPWA), an integrated healthcare system in Washington State, to explore people's feelings about timing of dementia diagnosis, use of EHR-based tools to predict risk of undiagnosed dementia, and communication about risk. We recruited people enrolled in KPWA who had dementia or mild cognitive impairment, people enrolled in KPWA who had neither diagnosis, and caregivers (i.e., loved ones of people with dementia who assist with various tasks of daily life). People who were non-white or Hispanic were oversampled. Two team members analyzed transcripts using thematic coding. RESULTS: Forty people (63% women; 59% non-white or Hispanic) participated in the focus groups. Themes that arose included: perceived pros and cons of early dementia diagnosis; questions and concerns about a potential tool to assess risk of undiagnosed dementia; and preferences related to patient-provider conversations disclosing that a person was at high risk to have undiagnosed dementia. Participants supported early diagnosis, describing benefits such as time to adjust to the disease, plan, involve caregivers, and identify resources. They also acknowledged the possible psychosocial toll of receiving the diagnosis. Participants supported use of an EHR-based tool, but some people worried about accuracy and privacy. Participants emphasized that information about risk of undiagnosed dementia should be communicated thoughtfully by a trusted provider and that the conversation should include advice about prognosis, treatment options and other resources when a new dementia diagnosis was made. CONCLUSION: People with dementia or mild cognitive impairment, people with neither diagnosis, and caregivers of people with dementia supported using EHR-based tools to help identify individuals at risk of having undiagnosed dementia. Such tools must be implemented carefully to address concerns and ensure that people living with dementia and their caregivers are adequately supported.

Renin-Angiotensin-Aldosterone System Inhibitors and COVID-19 Infection or Hospitalization: A Cohort Study.

BACKGROUND: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may increase the risk of coronavirus disease 2019 (COVID-19) infection or affect disease severity. Prior studies have not examined risks by medication dose. METHODS: This retrospective cohort study included people aged ≥18 years enrolled in a US integrated healthcare system for at least 4 months as of 2/29/2020. Current ACEI and ARB use was identified from pharmacy data, and the estimated daily dose was calculated and standardized across medications. COVID-19 infections and hospitalizations were identified through 6/14/2020 from laboratory and hospitalization data. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for race/ethnicity, obesity, and other covariates. RESULTS: Among 322,044 individuals, 826 developed COVID-19 infection. Among people using ACEI/ARBs, 204/56,105 developed COVID-19 (3.6 per 1,000 individuals) compared with 622/265,939 without ACEI/ARB use (2.3 per 1,000), yielding an adjusted OR of 0.91 (95% CI 0.74-1.12). For use of <1 defined daily dose (DDD) vs. nonuse, the adjusted OR for infection was 0.92 (95% CI 0.66-1.28); for 1 to <2 DDDs, 0.89 (95% CI 0.66-1.19); and for ≥2 DDDs, 0.92 (95% CI 0.72-1.18). The OR was similar for ACEIs and ARBs and in subgroups by age and sex. 26% of people with COVID-19 infection were hospitalized; the adjusted OR for hospitalization in relation to ACEI/ARB use was 0.98 (95% CI 0.63-1.54), and there was no association with dose. CONCLUSIONS: These findings support current recommendations that individuals on these medications continue their use.

Maternal Gestational Weight Gain in Relation to Antidepressant Continuation in Pregnancy.

OBJECTIVE: Both excessive and inadequate gestational weight gain (GWG) are associated with adverse health outcomes for the woman and her child. Antidepressant use in pregnancy could affect GWG, based on evidence in nonpregnant women that some antidepressants may cause weight gain and others weight loss. Previous studies of antidepressant use and GWG were small with limited ability to account for confounding, including by maternal mental health status and severity. We assessed the association of antidepressant continuation in pregnancy with GWG among women using antidepressants before pregnancy. STUDY DESIGN: Our retrospective cohort study included singleton livebirths from 2001 to 2014 within Kaiser Permanente Washington, an integrated health care system. Data were obtained from electronic health records and linked Washington State birth records. Among women with ≥1 antidepressant fill within 6 months before pregnancy, women who filled an antidepressant during pregnancy were considered "continuers;" women without a fill were "discontinuers." We calculated mean differences in GWG and relative risks (RR) of inadequate and excessive weight gain based on Institute of Medicine guidelines. Using inverse probability of treatment weighting with generalized estimating equations, we addressed differences in maternal characteristics, including mental health conditions. RESULTS: Among the 2,887 births, 1,689 (59%) were to women who continued antidepressants in pregnancy and 1,198 (42%) were to discontinuers. After accounting for confounding, continuers had similar weight gain to those who discontinued (mean difference: 1.3 lbs, 95% confidence interval [CI]: -0.1 to 2.8 lbs) and similar risks of inadequate and excessive GWG (RR: 0.95, 95% CI: 0.80-1.14 and RR: 1.06, 95% CI: 0.98-1.14, respectively). Findings were comparable for specific antidepressants and trimesters of exposure. CONCLUSION: We did not find evidence that continuation of antidepressants in pregnancy led to differences in GWG. KEY POINTS: · Antidepressant use is associated with weight change in nonpregnant populations.. · Prior evidence on whether antidepressant use in pregnancy affects gestational weight gain is sparse.. · We accounted for confounding by characteristics such as mental health conditions and their severity.. · We found no association between pregnancy antidepressant continuation and gestational weight gain..

Gestational weight gain and adverse pregnancy outcomes by pre-pregnancy BMI category in women with chronic hypertension: A cohort study.

OBJECTIVES: It is important to understand relationships of gestational weight gain with adverse pregnancy outcomes in women with chronic hypertension, given their high baseline risk of adverse outcomes. We assessed associations of gestational weight gain with adverse pregnancy outcomes in women with chronic hypertension by pre-pregnancy body mass index categories. STUDY DESIGN: We identified 14,369 women with chronic hypertension using electronic health records from 3 integrated health care delivery systems (2005-2014). Gestational weight gain-for-gestational age charts were used to calculate gestational weight gain z-scores, which account for gestational age. Modified Poisson regression models using generalized estimating equations were used to calculate relative risks and 95% confidence intervals, adjusted for sociodemographic and medical characteristics. MAIN OUTCOME MEASUREMENTS: Preeclampsia, preterm delivery, cesarean delivery, neonatal intensive care unit admission, birthweight (extracted from the electronic health record). RESULTS: In women with normal weight or overweight, low gestational weight gain (z-score < -1) was associated with 27-28% greater risk of preterm delivery and 48-82% greater risk of small-for-gestational age birthweight, while high gestational weight gain (z-score > 1) was associated with 40-90% greater risk of preeclampsia and 59-113% greater risk of large-for-gestational age birthweight. In women with obesity, low gestational weight gain was associated with 27-54% lower risk of several adverse pregnancy outcomes, including preeclampsia and cesarean delivery. CONCLUSIONS: In women with chronic hypertension and normal weight or overweight, moderate gestational weight gain may confer the lowest risk of adverse outcomes. In women with chronic hypertension and obesity, low gestational weight gain may be necessary for the lowest risk of adverse pregnancy outcomes.

Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury.

BACKGROUND: Efforts to minimize harms from opioid drug interactions may be hampered by limited evidence on which drugs, when taken concomitantly with opioids, result in adverse clinical outcomes. OBJECTIVE: To identify signals of opioid drug interactions by identifying concomitant medications (precipitant drugs) taken with individual opioids (object drugs) that are associated with unintentional traumatic injury DESIGN: We conducted pharmacoepidemiologic screening of Optum Clinformatics Data Mart, identifying drug interaction signals by performing confounder-adjusted self-controlled case series studies for opioid + precipitant pairs and injury. SETTING: Beneficiaries of a major United States-based commercial health insurer during 2000-2015 PATIENTS: Persons aged 16-90 years co-dispensed an opioid and ≥1 precipitant drug(s), with an unintentional traumatic injury event during opioid therapy, as dictated by the case-only design EXPOSURE: Precipitant-exposed (vs. precipitant-unexposed) person-days during opioid therapy. OUTCOME: Emergency department or inpatient International Classification of Diseases discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to generate confounder adjusted rate ratios. We accounted for multiple estimation via semi-Bayes shrinkage. RESULTS: We identified 25,019, 12,650, and 10,826 new users of hydrocodone, tramadol, and oxycodone who experienced an unintentional traumatic injury. Among 464, 376, and 389 hydrocodone-, tramadol-, and oxycodone-precipitant pairs examined, 20, 17, and 16 (i.e., 53 pairs, 34 unique precipitants) were positively associated with unintentional traumatic injury and deemed potential drug interaction signals. Adjusted rate ratios ranged from 1.23 (95 % confidence interval: 1.05-1.44) for hydrocodone + amoxicillin-clavulanate to 4.21 (1.88-9.42) for oxycodone + telmisartan. Twenty (37.7 %) of 53 signals are currently reported in a major drug interaction knowledgebase. LIMITATIONS: Potential for reverse causation, confounding by indication, and chance CONCLUSIONS: We identified previously undescribed and/or unappreciated signals of opioid drug interactions associated with unintentional traumatic injury. Subsequent etiologic studies should confirm (or refute) and elucidate these potential drug interactions.

Renin-angiotensin-aldosterone system inhibitors and COVID-19 infection or hospitalization: a cohort study.

There are plausible mechanisms by which angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may increase the risk of COVID-19 infection or affect disease severity. To examine the association between these medications and COVID-19 infection or hospitalization, we conducted a retrospective cohort study within a US integrated healthcare system. Among people aged ≥18 years enrolled in the health plan for at least 4 months as of 2/29/2020, current ACEI and ARB use was identified from pharmacy data, and the estimated daily dose was calculated and standardized across medications. COVID-19 infections were identified through 6/14/2020 from laboratory and hospitalization data. We used logistic regression to estimate adjusted odds ratios (ORs) and 95% confidence intervals. Among 322,044 individuals, 720 developed COVID-19 infection. Among people using ACEI/ARBs, 183/56,105 developed COVID-19 (3.3 per 1000 individuals) compared with 537/265,939 without ACEI/ARB use (2.0 per 1000), yielding an adjusted OR of 0.94 (95% CI 0.75-1.16). For use of < 1 defined daily dose vs. nonuse, the adjusted OR for infection was 0.89 (95% CI 0.62-1.26); for 1 to < 2 defined daily doses, 0.97 (95% CI 0.71-1.31); and for ≥2 defined daily doses, 0.94 (95% CI 0.72-1.23). The OR was similar for ACEIs and ARBs and in subgroups by age and sex. 29% of people with COVID-19 infection were hospitalized; the adjusted OR for hospitalization in relation to ACEI/ARB use was 0.92 (95% CI 0.54-1.57), and there was no association with dose. These findings support current recommendations that individuals on these medications continue their use.

Identifying hypertension in pregnancy using electronic medical records: The importance of blood pressure values.

OBJECTIVE: To incorporate blood pressure (BP), diagnoses codes, and medication fills from electronic medical records (EMR) to identify pregnant women with hypertension. STUDY DESIGN: A retrospective cohort study of singleton pregnancies at three US integrated health delivery systems during 2005-2014. MAIN OUTCOME MEASURES: Women were considered hypertensive if they had any of the following: (1) ≥2 high BPs (≥140/90 mmHg) within 30 days during pregnancy (High BP); (2) an antihypertensive medication fill in the 120 days before pregnancy and a hypertension diagnosis from 1 year prior to pregnancy through 20 weeks gestation (Treated Chronic Hypertension); or (3) a high BP, a hypertension diagnosis, and a prescription fill within 7 days during pregnancy (Rapid Treatment). We described characteristics of these pregnancies and conducted medical record review to understand hypertension presence and severity. RESULTS: Of 566,624 pregnancies, 27,049 (4.8%) met our hypertension case definition: 24,140 (89.2%) with High BP, 5,409 (20.0%) with Treated Chronic Hypertension, and 5,363 (19.8%) with Rapid Treatment (not mutually exclusive). Of hypertensive pregnancies, 19,298 (71.3%) received a diagnosis, 9,762 (36.1%) received treatment and 11,226 (41.5%) had a BP ≥ 160/110. In a random sample (n = 55) of the 7,559 pregnancies meeting the High BP criterion with no hypertension diagnosis, clinical statements about hypertension were found in medical records for 58% of them. CONCLUSION: Incorporating EMR BP identified many pregnant women with hypertension who would have been missed by using diagnosis codes alone. Future studies should seek to incorporate BP to study treatment and outcomes of hypertension in pregnancy.

The FDA MyStudies app: a reusable platform for distributed clinical trials and real-world evidence studies.

We developed a mobile application and secure patient data storage platform, FDA MyStudies, to address privacy, engagement, and extensibility challenges in mobile clinical research. The system extends the capabilities of the mobile frameworks Apple ResearchKit and ResearchStack through an intuitive front-end application and secure storage environment that can support health research studies. The platform supports single or multisite studies via role-based access and can be implemented within highly secure data environments. As a proof-of-concept, pregnant women participated in a descriptive study via the app in which data not routinely captured in electronic health records (EHR) were collected and linked with existing patient data to provide a more wholistic view of the patient and illustrate how patient data combined with EHR data could be used to support public health research.

Development and Validation of eRADAR: A Tool Using EHR Data to Detect Unrecognized Dementia.

OBJECTIVES: Early recognition of dementia would allow patients and their families to receive care earlier in the disease process, potentially improving care management and patient outcomes, yet nearly half of patients with dementia are undiagnosed. Our aim was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia (EHR Risk of Alzheimer's and Dementia Assessment Rule [eRADAR]). DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente Washington (KPWA), an integrated healthcare delivery system. PARTICIPANTS: A total of 16 665 visits among 4330 participants in the Adult Changes in Thought (ACT) study, who undergo a comprehensive process to detect and diagnose dementia every 2 years and have linked KPWA EHR data, divided into development (70%) and validation (30%) samples. MEASUREMENTS: EHR predictors included demographics, medical diagnoses, vital signs, healthcare utilization, and medications within the previous 2 years. Unrecognized dementia was defined as detection in ACT before documentation in the KPWA EHR (ie, lack of dementia or memory loss diagnosis codes or dementia medication fills). RESULTS: Overall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 498 (49%) were unrecognized in the KPWA EHR. The final 31-predictor model included markers of dementia-related symptoms (eg, psychosis diagnoses, antidepressant fills), healthcare utilization pattern (eg, emergency department visits), and dementia risk factors (eg, cerebrovascular disease, diabetes). Discrimination was good in the development (C statistic = .78; 95% confidence interval [CI] = .76-.81) and validation (C statistic = .81; 95% CI = .78-.84) samples, and calibration was good based on plots of predicted vs observed risk. If patients with scores in the top 5% were flagged for additional evaluation, we estimate that 1 in 6 would have dementia. CONCLUSION: The eRADAR tool uses existing EHR data to detect patients with good accuracy who may have unrecognized dementia. J Am Geriatr Soc 68:103-111, 2019.

Antidepressant continuation in pregnancy and risk of gestational diabetes.

PURPOSE: Previous studies observed modestly higher risk of gestational diabetes (GDM) associated with antidepressant use in pregnancy, potentially due to confounding by indication. We assessed the association of antidepressant continuation in pregnancy with GDM, as well as blood glucose levels, after accounting for confounding. METHODS: We conducted a retrospective cohort study of singleton live births from 2001 to 2014 to women enrolled in Kaiser Permanente Washington, an integrated health care delivery system, utilizing electronic health data and linked Washington State birth records. We required that women have ≥1 antidepressant prescription fills ≤6 months before pregnancy. Women with an antidepressant fill during pregnancy were categorized as "continuers" (n = 1634); those without a fill were "discontinuers" (n = 1211). We calculated relative risks (RRs) for GDM and mean differences in screening blood glucose levels using generalized estimating equations with inverse probability of treatment weighting to account for baseline characteristics, including mental health conditions and indicators of mental health severity. RESULTS: Compared with discontinuers, antidepressant continuers had comparable risk of GDM (RR: 1.10; 95% confidence interval [CI], 0.84-1.44) and blood glucose levels (mean difference: 2.3 mg/dL; 95% CI, -1.5 to 6.1 mg/dL). We observed generally similar results for specific antidepressants, with the potential exceptions of risk of GDM associated with sertraline (RR: 1.30; 95% CI, 0.90-1.88) and venlafaxine (RR: 1.52; 95% CI, 0.87-2.68), but neither association was statistically significant. CONCLUSIONS: Our study suggests that overall, women who continue antidepressants in pregnancy are not at increased risk for GDM or higher blood glucose, although further study may be warranted for sertraline and venlafaxine.

Patterns of antihypertensive and statin adherence prior to dementia: findings from the adult changes in thought study.

BACKGROUND: Detecting patients with undiagnosed dementia is an important clinical challenge. Changes in medication adherence might represent an early sign of cognitive impairment. We sought to examine antihypertensive and statin adherence trajectories in community-dwelling older adults, comparing people who went on to develop dementia to those who did not. METHODS: We analyzed data from Adult Changes in Thought (ACT), a population-based cohort study embedded within an integrated healthcare delivery system. Analyses included 4368 participants aged ≥65 years who had at least one follow-up visit. Research-quality dementia diagnoses were used to identify cases. We selected non-dementia control visits matched on age, sex, and study cohort that occurred at similar ACT follow-up time as the case's dementia onset; we treated this as the index date. Participants were included if they were prevalent users of either a statin or antihypertensive medication on the first day of follow up - 3 years prior to the index date. Using prescription fill dates and days supply, we calculated daily binary medication availability measures for each participant ('days covered') over 3 years leading up to the index date. We used group-based trajectory models to identify patterns of antihypertensive and statin adherence, and used conditional logistic regression to examine associations between adherence trajectories and dementia. RESULTS: Four trajectories were identified for antihypertensive users (292 cases, 3890 control visits), including near perfect (n = 1877, 36.6% cases, 45.5% controls), high (n = 1840, 43.2% cases, 44.1% controls), moderate (n = 365, 18.5% cases, 8.0% controls) and early poor adherence (n = 100, 1.7% cases, 2.4% controls). Odds of dementia was 3 times greater for those with moderate antihypertensive adherence compared to those with near perfect adherence (adjusted OR 3.0, 95% CI 2.0, 4.3). Four trajectories were identified for statin users (148 cases, 1131 control visits), including high (n = 1004, 75.0% cases, 79.0% controls), moderate (n = 192, 19.6% cases, 14.4% controls), early poor (n = 43, 2.0% cases, 3.5% controls), and delayed poor adherence (n = 40, 3.4% cases, 3.1% controls). No association was detected between statin adherence trajectories and dementia. CONCLUSIONS: Patterns of medication adherence may be useful to identify a subset of people at higher likelihood of developing dementia.

Systematic Multi-Domain Alzheimer's Risk Reduction Trial (SMARRT): Study Protocol.

This article describes the protocol for the Systematic Multi-domain Alzheimer's Risk Reduction Trial (SMARRT), a single-blind randomized pilot trial to test a personalized, pragmatic, multi-domain Alzheimer's disease (AD) risk reduction intervention in a US integrated healthcare delivery system. Study participants will be 200 higher-risk older adults (age 70-89 years with subjective cognitive complaints, low normal performance on cognitive screen, and ≥ two modifiable risk factors targeted by our intervention) who will be recruited from selected primary care clinics of Kaiser Permanente Washington, oversampling people with non-white race or Hispanic ethnicity. Study participants will be randomly assigned to a two-year Alzheimer's risk reduction intervention (SMARRT) or a Health Education (HE) control. Randomization will be stratified by clinic, race/ethnicity (non-Hispanic white versus non-white or Hispanic), and age (70-79, 80-89). Participants randomized to the SMARRT group will work with a behavioral coach and nurse to develop a personalized plan related to their risk factors (poorly controlled hypertension, diabetes with evidence of hyper or hypoglycemia, depressive symptoms, poor sleep quality, contraindicated medications, physical inactivity, low cognitive stimulation, social isolation, poor diet, smoking). Participants in the HE control group will be mailed general health education information about these risk factors for AD. The primary outcome is two-year cognitive change on a cognitive test composite score. Secondary outcomes include: 1) improvement in targeted risk factors, 2) individual cognitive domain composite scores, 3) physical performance, 4) functional ability, 5) quality of life, and 6) incidence of mild cognitive impairment, AD, and dementia. Primary and secondary outcomes will be assessed in both groups at baseline and 6, 12, 18, and 24 months.

Impact of initiatives to reduce prescription opioid risks on medically attended injuries in people using chronic opioid therapy.

PURPOSE: The purpose of the study is to determine whether initiatives to improve the safety of opioid prescribing decreased injuries in people using chronic opioid therapy (COT). METHODS: We conducted an interrupted time series analysis using data from Group Health (GH), an integrated health care delivery system in the United States. In 2007, GH implemented initiatives which substantially reduced daily opioid dose and increased patient monitoring. Among GH members age 18 or older receiving COT between 2006 and 2014, we compared injury rates for patients in GH's integrated group practice (IGP; exposed to the initiatives) vs patients cared for by contracted providers (not exposed). Injuries were identified using a validated algorithm. We calculated injury incidence during the baseline (preintervention) period from 2006 to 2007; the dose reduction period, 2008 to 2010; and the risk stratification and monitoring period, 2010 to 2014. Using modified Poisson regression, we estimated adjusted relative risks (RRs) representing the relative change per year in injury rates. RESULTS: Among 21 853 people receiving COT in the IGP and 8260 in contracted care, there were 2679 injuries during follow-up. The baseline injury rate was 1.0% per calendar quarter in the IGP and 0.9% in contracted care. Risk reduction initiatives did not decrease injury rates: Within the IGP, the RR in the dose reduction period was 1.01 (95% CI, 0.95-1.07) and in the risk stratification and monitoring period, 0.99 (95% CI, 0.95-1.04). Injury trends did not differ between the two care settings. CONCLUSIONS: Risk reduction initiatives did not decrease injuries in people using COT.

Proton pump inhibitor use and the risk of fractures among an older adult cohort.

PURPOSE: The purpose of the study is to determine if the use of a proton pump inhibitor (PPI) is associated with an increased fracture risk, as some prior studies have suggested. METHODS: This retrospective cohort study included data on 4438 participants aged 65 and older who had no fracture in the year prior to baseline and had ≥5 years of enrollment history in Kaiser Permanente Washington, an integrated healthcare delivery system in Seattle, WA, during 1994 to 2014. Time-varying cumulative exposure to PPIs was determined from automated pharmacy data by summing standard daily doses (SDDs) across fills, and patients were categorized as no use (reference group, ≤30 SDD), light use (31-540 SDD), moderate use (541-1080 SDD), and heavy use (≥1081 SDD). Incident fractures were assessed using International Classification of Diseases, Ninth Revision codes from electronic medical records. Potential confounders, chosen a priori, were assessed at baseline and at each 2-year follow-up visit. Fracture risk was analyzed using a Cox proportional hazards model. RESULTS: Over a mean follow-up of 6.1 years, 802 (18.1%) participants experienced a fracture. No overall association was found between PPI use and fracture risk. Adjusted hazard ratios comparing users to the referent category were 1.08 (95% CI 0.83-1.40) for light users, 1.31 (95% CI 0.86-1.95) for moderate users, and 0.95 (95% CI 0.68-1.34) for heavy users. Among patients with SSD > 30, no appreciable increase in fracture risk was present in persons with recent versus distant use (adjusted hazard ratio of 1.14 [95% CI 0.91-1.42]). CONCLUSIONS: No association was observed between PPI use and fracture risk among older adults.