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Indianapolis, United States

Abrahamson K.,Western Kentucky University | Clark D.,Indiana University | Perkins A.,Regenstrief Institute | Arling G.,Indiana University
Gerontologist | Year: 2012

Purpose: We investigated the relationship between cognitive status and quality of life (QOL) of Minnesota nursing home (NH) residents and the relationship between conventional or Alzheimer's special care unit (SCU) placement and QOL. The study may inform development of dementia-specific quality measures. Design and Methods: Data for analyses came from face-to-face interviews with a representative sample of 13,130 Minnesota NH residents collected through the 2007 Minnesota NH Resident Quality of Life and Consumer Satisfaction survey. We examined 7 QOL domains: comfort, meaningful activities, privacy, environment, individuality, autonomy, relationships, and a positive mood scale. We applied multilevel models (resident and facility) to examine the relationship between the resident's score on each QOL domain and the resident's cognitive impairment (CI) level and SCU placement after controlling for covariates, such as activities of daily living dependency, pain, depression or psychiatric diagnosis, and length of stay. Results: Residents with more severe CI reported higher QOL in the domains of comfort and environment and lower QOL in activities, individuality, privacy and meaningful relationships, and the mood scale. Residents on SCU reported higher QOL in the meaningful activities, comfort, environment, and autonomy domains but had lower mood scores. Implications: Our findings point to QOL domains that show significant variation by CI and thus may be of greatest interest to consumers, providers, advocacy groups, and other stakeholders committed to improving dementia care. Findings are particularly applicable to the development of NH quality indicators that more accurately represent the QOL of NH residents with CI. © 2012 The Author 2012. Source


Murray M.D.,Regenstrief Institute
Pharmacy World and Science | Year: 2010

It stands to reason that pharmacists would have a benefic role in the treatment of patients with chronic illnesses wherein complicated pharmacotherapies are required to reduce the risk of acute exacerbation. For chronic heart failure, recent evidence bears this out. When pharmacists take time to provide self-care instructions for patients with heart failure or take part in collaborative healthcare teams, the need for costly urgent healthcare decreases with corresponding decreases in healthcare costs. Further research is needed to address the key supportive roles of pharmacists in the treatment of patients with heart failure. © 2010 Springer Science+Business Media B.V. Source


Duke J.D.,Regenstrief Institute
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium | Year: 2011

Evaluating the potential harm of a drug-drug interaction (DDI) requires knowledge of a patient's relevant co-morbidities and risk factors. Current DDI alerts lack such patient-specific contextual data. In this paper, we present an efficient model for integrating pertinent patient data into DDI alerts. This framework is designed to be interoperable across multiple drug knowledge bases and clinical information systems. To evaluate the model, we generated a set of contextual DDI data using our local drug knowledge base then conducted an evaluation study of a prototype contextual alert design. The alert received favorable ratings from study subjects, who agreed it was an improvement over traditional alerts and was likely to support clinical management and save physician time. This framework may ultimately help reduce alert fatigue through the dynamic display of DDI alerts based on patient risk. Source


Kroenke K.,Regenstrief Institute
Annals of Internal Medicine | Year: 2014

Physical symptoms account for more than half of all outpatient visits, yet the predominant disease-focused model of care is inadequate for many of these symptom-prompted encounters. Moreover, the amount of clinician training dedicated to understanding, evaluating, and managing common symptoms is disproportionally small relative to their prevalence, impairment, and health care costs. This narrative review regarding physical symptoms addresses 4 common epidemiologic questions: cause, diagnosis, prognosis, and therapy. Important findings include the following: First, at least one third of common symptoms do not have a clear-cut, disease-based explanation (5 studies in primary care, 1 in specialty clinics, and 2 in the general population). Second, the history and physical examination alone contribute 73% to 94% of the diagnostic information, with costly testing and procedures contributing much less (5 studies of multiple types of symptoms and 4 of specific symptoms). Third, physical and psychological symptoms commonly co-occur, making a dualistic approach impractical. Fourth, because most patients have multiple symptoms rather than a single symptom, focusing on 1 symptom and ignoring the others is unwise. Fifth, symptoms improve in weeks to several months in most patients but become chronic or recur in 20% to 25%. Sixth, serious causes that are not apparent after initial evaluation seldom emerge during long-term follow-up. Seventh, certain pharmacologic and behavioral treatments are effective across multiple types of symptoms. Eighth, measuring treatment response with valid scales can be helpful. Finally, communication has therapeutic value, including providing an explanation and probable prognosis without "normalizing" the symptom. © 2014 American College of Physicians. Source


Imler T.D.,Indiana University | Imler T.D.,Regenstrief Institute | Morea J.,Indiana University | Imperiale T.F.,Indiana University
Clinical Gastroenterology and Hepatology | Year: 2014

Background & Aims: With an increased emphasis on improving quality and decreasing costs, new tools are needed to improve adherence to evidence-based practices and guidelines in endoscopy. We investigated the ability of an automated system that uses natural language processing (NLP) and clinical decision support (CDS) to facilitate determination of colonoscopy surveillance intervals. Methods: We performed a retrospective study at a single Veterans Administration medical center of patients age 40 years and older who had an index outpatient colonoscopy from 2002 through 2009 for any indication except surveillance of a previous colorectal neoplasia. We analyzed data from 10,798 reports, with 6379 linked to pathology results and 300 randomly selected reports. NLP-based CDS surveillance intervals were compared with those determined by paired, blinded, manual review. The primary outcome was adjusted agreement between manual review and the fully automated system. Results: κ statistical analysis produced a value of 0.74 (P < .001) for agreement between the full text annotation and the NLP-based CDS system. Fifty-five reports (18.3%; 95% confidence interval, 14.1%-23.2%) differed between manual review and CDS recommendations. Of these, NLP error accounted for 30 (54.5%), incomplete resection of adenomatous tissue accounted for 14 (25.5%), and masses observed without biopsy findings of cancer accounted for 4 (7.2%). NLP-based CDS surveillance intervals had higher levels of agreement with the standard (81.7%) than the level agreement between experts (72% agreement between paired reviewers). Conclusions: A fully automated system that uses NLP and a guideline-based CSD system can accurately facilitate guideline-recommended adherence surveillance for colonoscopy. © 2014 AGA Institute. Source

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