Publications by authors named "Stuart Speedie"

We developed a method of using the Clinically Aligned Pain Assessment (CAPA) measures to reconstruct the Numeric Rating System (NRS). We used an observational retrospective cohort study design with prospective validation using de-identified adult patient data derived from a major health system. Data between 2011-2017 were used for development and 2018-2020 for validation.

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Multiple factors potentially influence pain intensity or frequency, and consequently the need for an opioid prescription. This study aims to identify factors associated with being discharged with an outpatient opioid prescription. We constructed a database containing clinical, non-clinical, and organizational variables from the EHR that are potentially relevant for ordering an opioid at discharge.

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Background: The use of personal health care management (PHM) is increasing rapidly within the United States because of implementation of health technology across the health care continuum and increased regulatory requirements for health care providers and organizations promoting the use of PHM, particularly the use of text messaging (short message service), Web-based scheduling, and Web-based requests for prescription renewals. Limited research has been conducted comparing PHM use across groups based on chronic conditions.

Objective: This study aimed to describe the overall utilization of PHM and compare individual characteristics associated with PHM in groups with no reported chronic conditions, with 1 chronic condition, and with 2 or more such conditions.

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Background: Cardiac Resynchronization Therapy (CRT) is an established pacing therapy for heart failure patients. The New York Heart Association (NYHA) class is often used as a measure of a patient's response to CRT. Identifying NYHA class for heart failure (HF) patients in an electronic health record (EHR) consistently, over time, can provide better understanding of the progression of heart failure and assessment of CRT response and effectiveness.

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Cardiac Resynchronization Therapy (CRT) is an established pacing therapy for heart failure patients. The New York Heart Association (NYHA) classification is often used as a measure of a patient's response to CRT. Identifying NYHA class for heart failure patients in an electronic health record (EHR) consistently, over time, can provide better understanding of the progression of heart failure and assessment of CRT response and effectiveness.

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Purpose: Hypertension (HTN) is significantly under-treated in stroke survivors. We examined usability and efficacy of a mHealth -based care model for improving post-stroke HTN control (Funding: AHRQ R21HS021794).

Methods: We used a RCT design.

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Objective The objective of this study was to demonstrate the utility of a healthcare data quality framework by using it to measure the impact of synthetic data quality issues on the validity of an eMeasure (CMS178—urinary catheter removal after surgery). Methods Data quality issues were artificially created by systematically degrading the underlying quality of EHR data using two methods: independent and correlated degradation. A linear model that describes the change in the events included in the eMeasure quantifies the impact of each data quality issue.

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The purpose of this study was to create information models from flowsheet data using a data-driven consensus-based method. Electronic health records contain a large volume of data about patient assessments and interventions captured in flowsheets that measure the same "thing," but the names of these observations often differ, according to who performs documentation or the location of the service (eg, pulse rate in an intensive care, the emergency department, or a surgical unit documented by a nurse or therapist or captured by automated monitoring). Flowsheet data are challenging for secondary use because of the existence of multiple semantically equivalent measures representing the same concepts.

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Emerging issues of team-based care, precision medicine, and big data science underscore the need for health information technology (HIT) tools for integrating complex data in consistent ways to achieve the triple aims of improving patient outcomes, patient experience, and cost reductions. The purpose of this study was to demonstrate the feasibility of creating a hierarchical flowsheet ontology in i2b2 using data-derived information models and determine the underlying informatics and technical issues. This study is the first of its kind to use information models that aggregate team-based care across time, disciplines, and settings into 14 information models that were integrated into i2b2 in a hierarchical model.

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Objective: The goal of this study is to apply an ontology based assessment process to electronic health record (EHR) data and determine its usefulness in characterizing data quality for calculating an example eMeasure (CMS178).

Methods: The process uses a data quality ontology that references separate data quality, domain and task ontologies to compute measures based on proportions of constraints that are satisfied. These quantities indicate how well the data conforms to the domain and how well it fits the task.

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Background: An increasing number of clinical trials are conducted in primary care settings. Making better use of existing data in the electronic health records to identify eligible subjects can improve efficiency of such studies. Our study aims to quantify the proportion of eligibility criteria that can be addressed with data in electronic health records and to compare the content of eligibility criteria in primary care with previous work.

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Context: Underscreening and problematic repeat lead testing in children.

Objective: Identify proportion of underscreening for elevated blood-lead levels in children. For children who receive a lead test, measure the level of problematic repeat lead tests, defined as those with a high probability of not meeting recommended guidelines for lead testing in children measured using a combination of patients' age, test type and sequencing, days between tests, and encounter diagnosis coding.

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Health care data included in clinical data repositories (CDRs) are increasingly used for quality reporting, business analytics and research; however, extended clinical data from interprofessional practice are seldom included. With the increasing emphasis on care coordination across settings, CDRs need to include data from all clinicians and be harmonized to understand the impact of their collaborative efforts on patient safety, effectiveness and efficiency. This study characterizes the extended clinical data derived from EHR flowsheet data that is available in the University of Minnesota's CDR and describes a process for creating an ontology that organizes that data so that it is more useful and accessible to researchers.

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The use of patient focused technology has been proclaimed as a means to improve patient satisfaction and improve care outcomes. The Center for Medicaid/Medicare Services, through its EHR Incentive Program, has required eligible hospitals and professionals to send and receive secure messages from patients in order to receive financial incentives and avoid reimbursement penalties. Secure messaging between providers and patients has the potential to improve communication and care outcomes.

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Repetition by clinicians of the same tests for a given patient is common. However, not all repeat tests are necessary for optimal care and can result in unnecessary hardship. Limited evidence suggests that an electronic health record may reduce redundant laboratory testing and imaging by making previous results accessible to physicians.

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The secondary use of EHR data for research is expected to improve health outcomes for patients, but the benefits will only be realized if the data in the EHR is of sufficient quality to support these uses. A data quality (DQ) ontology was developed to rigorously define concepts and enable automated computation of data quality measures. The healthcare data quality literature was mined for the important terms used to describe data quality concepts and harmonized into an ontology.

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Patients are increasingly using the Internet and other technologies to engage in their own healthcare, but little research has focused on the determinants of consumer eHealth behaviors related to Internet use. This study uses data from 115,089 respondents to four years of the National Health Interview Series to identify the associations between one consumer eHealth behavior (information seeking) and demographics, health measures, and Personal Health Information Management (PHIM) (messaging, scheduling, refills, and chat). Individuals who use PHIM are 7.

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Background: Patient data from general practices is already used for many types of epidemiological research and increasingly, primary care systems to facilitate randomized clinical trials. The EU funded project TRANSFoRm aims to create a "Learning Healthcare System" at a European level that is able to support all types of research using primary care data, to recruit patients and follow patients in clinical studies and to improve diagnosis and therapy. The implementation of such a Learning Healthcare System needs an information model for clinical research (CRIM), as an informational backbone to integrate aspects of primary care with clinical trials and database searches.

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Large amounts of personal health data are being collected and made available through existing and emerging technological media and tools. While use of these data has significant potential to facilitate research, improve quality of care for individuals and populations, and reduce healthcare costs, many policy-related issues must be addressed before their full value can be realized. These include the need for widely agreed-on data stewardship principles and effective approaches to reduce or eliminate data silos and protect patient privacy.

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Background: Time is a measurable and critical resource that affects the quality of services provided in clinical practice. There is limited insight into the effects of time restrictions on clinicians' cognitive processes with the electronic health record (EHR) in providing ambulatory care.

Objective: To understand the impact of time constraints on clinicians' synthesis of text-based EHR clinical notes.

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Objective: To evaluate if electronic health records (EHR) with prior clinical information have observable effects for patients with diabetes presenting to emergency departments (ED), we examined measures of quality and resource utilization.

Materials And Methods: Retrospective observational studies of patients in three ED (A=5510; B=4393; C=3324) were conducted comparing patients with prior information in the EHR to those without such information. Differences with respect to hospitalization, mortality, length of stay (LOS), and numbers of ED orders for tests, procedures and medications were examined after adjusting for age, gender, race, marital status, comorbidities and for acuity level within each ED.

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An increasing amount of electronic health data is being collected for patient care, and with it the opportunity to explore reusing this data, for example to support clinical research. We explore how researchers can be supported in identifying potential study participants using a semi-automated approach to query anonymised datasets remotely. This paper describes the socio-technical considerations when answering this question in a central England case study.

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Objectives: Accountable care puts pressure on hospitals to manage care episodes. Initial length of stay (ILOS) and readmission risk are important elements of a care episode and measures of care quality. Understanding the association between these two measures can guide hospital efforts in managing care episodes.

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Purpose: The principal goal of the electronic Primary Care Research Network (ePCRN) is to enable the development of an electronic infrastructure to support clinical research activities in primary care practice-based research networks (PBRNs). We describe the model that the ePCRN developed to enhance the growth and to expand the reach of PBRN research.

Methods: Use cases and activity diagrams were developed from interviews with key informants from 11 PBRNs from the United States and United Kingdom.

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Objectives: The objective of this paper is to describe the Health Insurance Review and Assessment Service (HIRA)'s payment request (PARE) system that plays the role of the gateway for all health insurance claims submitted to HIRA, and the claim review support (CRS) system that supports the work of claim review experts in South Korea.

Methods: This study describes the two systems' information technology (IT) infrastructures, their roles, and quantitative analysis of their work performance. It also reports the impact of these systems on claims processing by analyzing the health insurance claim data submitted to HIRA from April 1 to June 30, 2011.

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