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The article examines barriers to identifying residents with dementia for embedded pragmatic trials. Topics discussed include contemporary efforts to create more equitable and ethical algorithms, possible interventions for people living with Alzheimer's disease or other dementias (ADRD), and methods used for conducting the research at hand.

Development of evidence‐based practice requires practice‐based evidence, which can be acquired through analysis of real‐world data from electronic health records (EHRs). The EHR contains volumes of information about patients—physical measurements, diagnoses, exposures, and markers of health behavior—that can be used to create algorithms for risk stratification or to gain insight into associations between exposures, interventions, and outcomes. But to transform real‐world data into reliable real‐world evidence, one must not only choose the correct analytical methods but also have an understanding of the quality, detail, provenance, and organization of the underlying source data and address the differences in these characteristics across sites when conducting analyses that span institutions. This manuscript explores the idiosyncrasies inherent in the capture, formatting, and standardization of EHR data and discusses the clinical domain and informatics competencies required to transform the raw clinical, real‐world data into high‐quality, fit‐for‐purpose analytical data sets used to generate real‐world evidence. [ABSTRACT FROM AUTHOR]

Objective: To review evidence regarding the use of Health Information Technology (health IT) interventions aimed at improving care for people living with multiple chronic conditions (PLWMCC) in order to identify critical knowledge gaps. Data Sources: We searched MEDLINE, CINAHL, PsycINFO, EMBASE, Compendex, and IEEE Xplore databases for studies published in English between 2010 and 2020. Study Design: We identified studies of health IT interventions for PLWMCC across three domains as follows: self‐management support, care coordination, and algorithms to support clinical decision making. Data Collection/Extraction Methods: Structured search queries were created and validated. Abstracts were reviewed iteratively to refine inclusion and exclusion criteria. The search was supplemented by manually searching the bibliographic sections of the included studies. The search included a forward citation search of studies nested within a clinical trial to identify the clinical trial protocol and published clinical trial results. Data were extracted independently by two reviewers. Principal Findings: The search yielded 1907 articles; 44 were included. Nine randomized controlled trials (RCTs) and 35 other studies including quasi‐experimental, usability, feasibility, qualitative studies, or development/validation studies of analytic models were included. Five RCTs had positive results, and the remaining four RCTs showed that the interventions had no effect. The studies address individual patient engagement and assess patient‐centered outcomes such as quality of life. Few RCTs assess outcomes such as disability and none assess mortality. Conclusions: Despite a growing body of literature on health IT interventions or multicomponent interventions including a health IT component for chronic disease management, current evidence for applying health IT solutions to improve care for PLWMCC is limited. The body of literature included in this review provides critical information on the state of the science as well as the many gaps that need to be filled for digital health to fulfill its promise in supporting care delivery that meets the needs of PLWMCC. [ABSTRACT FROM AUTHOR]

Embedded pragmatic clinical trials (ePCTs) are embedded in healthcare systems as well as their data environments. For people living with dementia (PLWD), settings of care can be different from the general population and involve additional people whose information is also important. The ePCT designs have the opportunity to leverage data that becomes available through the normal delivery of care. They may be particularly valuable in Alzheimer's disease and Alzheimer's disease‐related dementia (AD/ADRD), given the complexity of case identification and the diversity of care settings. Grounded in the objectives of the Data and Technical Core of the newly established National Institute on Aging Imbedded Pragmatic Alzheimer's Disease and AD‐Related Dementias Clinical Trials Collaboratory (IMPACT Collaboratory), this article summarizes the state of the art in using existing data sources (eg, Medicare claims, electronic health records) in AD/ADRD ePCTs and approaches to integrating them in real‐world settings. J Am Geriatr Soc 68:S49–S54, 2020. [ABSTRACT FROM AUTHOR]

Medication-prescribing errors generated at interfaces-in-care are the most common cause of preventable health care errors and contribute substantially to adverse patient outcomes. For this reason, standardized medication reconciliation (MR) processes need to be inserted at these interfaces. However, MR is an inherently complex task, and little data exist to inform system-based operationalization. The Portland Informatics Center addressed this challenge by creating an electronic patient-directed multimedia survey to automate the medication history collection. This article describes a research protocol designed to compare the software's medication discrepancy detection rate with traditional history collection strategies. For this randomized, controlled, single-blind trial, participants are randomly allocated into one of two groups: the control group reviews a paper list printed from the electronic record, whereas the intervention group uses a computer-assisted reconciliation survey that includes display of visual data (i.e., medication pictures). © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To explore changes in mortality and hospital usage for chronically ill seniors enrolled in a multidisease care management program, Care Management Plus (CMP). DESIGN: Controlled clinical trial with seven intervention and six control clinics with additional patient-level matching. SETTING: Intermountain Health Care, a large health system in Utah; seven intervention and six control clinics. PARTICIPANTS: Three thousand four hundred thirty-two senior patients (≥65) enrolled in Medicare. INTERVENTION: The intervention employed nurse care managers supported by specialized information technology in primary care to manage chronically ill patients (2002–2005). MEASUREMENTS: Mortality and hospitalization data were collected from clinical records and Medicare billing. RESULTS: One thousand one hundred forty-four intervention patients were matched to 2,288 controls. Average age was 76.2; average comorbidity score was 2.3±1.1; 75% of patients had two or more chronic diseases. Survival analyses showed lower mortality and slightly more emergency department visits for care managed patients than for controls. In patients with diabetes mellitus, the intervention resulted in significantly lower mortality at 1 year (6.2%, vs 10.6% for controls) and at 2 years (12.9% vs 18.2%). Hospitalization rate was lower (21.0%, vs. 24.2% for controls) at 1 year and substantially more so at the 2-year follow-up. CONCLUSION: CMP was successful in reducing death for all patients. For complex patients with diabetes mellitus in the intervention group, death and hospital usage were lower. Per clinic, hypothesized savings from decreased hospitalizations was $17,384 to $70,349. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To investigate whether health-related quality-of-life (HRQoL) scores in a primary care population can be used as a predictor of future hospital utilization and mortality. DESIGN: Prospective cohort study measuring Short Form 12 (SF-12) scores obtained using a mailed survey. SF-12 scores, age, and a comorbidity score were used to predict hospitalization and mortality rate using multivariable logistic regression and Cox proportional hazards during the ensuing 28-month period for elderly patients. SETTING: Intermountain Health Care, a large integrated-delivery network serving a population of more than 150,000 seniors. PARTICIPANTS: Participants were senior patients who had one or more chronic diseases, were community dwelling, and were initially treated in primary care clinics. MEASUREMENTS: SF-12 survey Version 1. RESULTS: Seven thousand seventy-six surveys were sent to eligible participants; 3,042 (43%) were returned. Of the returned surveys, 2,166 (71%) were complete and scoreable. For the respondent group, a multivariable analysis demonstrated that older age, male sex, higher comorbidity score, and lower mental and physical summary measures of SF-12 predicted higher mortality and hospitalization. On average, nonresponders were older and had higher comorbidity scores and mortality rates than responders. CONCLUSION: The SF-12 survey provided additional predictive ability for future hospitalizations and mortality. Such predictive ability might facilitate preemptive interventions that would change the course of disease in this segment of the population. However, nonresponder bias may limit the utility of mailed SF-12 surveys in certain populations. [ABSTRACT FROM AUTHOR]

Objective. To determine how the addition of generalist care managers and collaborative information technology to an ambulatory team affects the care of patients with diabetes. Study Setting. Multiple ambulatory clinics within Intermountain Health Care (IHC), a large integrated delivery network. Study Design. A retrospective cohort study comparing diabetic patients treated by generalist care managers with matched controls was completed. Exposure patients had one or more contacts with a care manager; controls were matched on utilization, demographics, testing, and baseline glucose control. Using role-specific information technology to support their efforts, care managers assessed patients' readiness for change, followed guidelines, and educated and motivated patients. Data Collection. Patient data collected as part of an electronic patient record were combined with care manager-created databases to assess timely testing of glycosylated hemoglobin (HbA1c) and low-density lipoprotein (LDL) levels and changes in LDL and HbA1c levels. Principal Findings. In a multivariable model, the odds of being overdue for testing for HbA1c decreased by 21 percent in the exposure group ( n=1,185) versus the control group ( n=4,740). The odds of being tested when overdue for HbA1c or LDL increased by 49 and 26 percent, respectively, and the odds of HbA1c <7.0 percent also increased by 19 percent in the exposure group. The average HbA1c levels decreased more in the exposure group than in the controls. The effect on LDL was not significant. Conclusions. Generalist care managers using computer-supported diabetes management helped increase adherence to guidelines for testing and control of HbA1c levels, leading to improved health status of patients with diabetes. [ABSTRACT FROM AUTHOR]

To examine potential cost savings from decreased adverse resident outcomes versus additional wages of nurses when nursing homes have adequate staffing.A retrospective cost study using differences in adverse outcome rates of pressure ulcers (PUs), urinary tract infections (UTIs), and hospitalizations per resident per day from low staffing and adequate staffing nursing homes. Cost savings from reductions in these events are calculated in dollars and compared with costs of increasing nurse staffing.Eighty-two nursing homes throughout the United States.One thousand three hundred seventy-six frail elderly long-term care residents at risk of PU development.Event rates are from the National Pressure Ulcer Long-Term Care Study. Hospital costs are estimated from Medicare statistics and from charges in the Healthcare Cost and Utilization Project. UTI costs and PU costs are from cost-identification studies. Time horizon is 1 year; perspectives are societal and institutional.Analyses showed an annual net societal benefit of$3,191 per resident per year in a high-risk, long-stay nursing home unit that employs sufficient nurses to achieve 30 to 40 minutes of registered nurse direct care time per resident per day versus nursing homes that have nursing time of less than 10 minutes. Sensitivity analyses revealed a robust set of estimates, with no single or paired elements reaching the cost/benefit equality threshold.Increasing nurse staffing in nursing homes may create significant societal cost savings from reduction in adverse outcomes. Challenges in increasing nurse staffing are discussed. [ABSTRACT FROM AUTHOR]