National Healthcare Quality and Disparities Report
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Topics
- Adverse Drug Events (ADE) (2)
- Adverse Events (3)
- Alcohol Use (1)
- Back Health and Pain (1)
- Cancer (1)
- Cancer: Lung Cancer (1)
- Cardiovascular Conditions (1)
- Children/Adolescents (4)
- Chronic Conditions (3)
- Clinical Decision Support (CDS) (2)
- Clostridium difficile Infections (1)
- Communication (2)
- Comparative Effectiveness (11)
- COVID-19 (1)
- (-) Data (63)
- Decision Making (1)
- Diagnostic Safety and Quality (1)
- Elderly (2)
- Electronic Health Records (EHRs) (11)
- Emergency Department (2)
- Emergency Medical Services (EMS) (1)
- Evidence-Based Practice (2)
- Healthcare-Associated Infections (HAIs) (2)
- Healthcare Cost and Utilization Project (HCUP) (5)
- Healthcare Costs (4)
- Healthcare Delivery (2)
- Health Information Exchange (HIE) (3)
- Health Information Technology (HIT) (16)
- Health Insurance (2)
- Health Services Research (HSR) (5)
- Health Systems (1)
- Heart Disease and Health (3)
- Hospital Discharge (5)
- Hospital Readmissions (1)
- Hospitals (4)
- Human Immunodeficiency Virus (HIV) (1)
- Imaging (1)
- Inpatient Care (1)
- Intensive Care Unit (ICU) (1)
- Low-Income (1)
- Maternal Care (1)
- Medicaid (1)
- Medical Devices (1)
- Medical Errors (3)
- Medical Expenditure Panel Survey (MEPS) (1)
- Medicare (1)
- Medication (2)
- Mortality (3)
- Newborns/Infants (1)
- Nursing (2)
- Nursing Homes (1)
- Outcomes (5)
- Patient-Centered Healthcare (2)
- Patient-Centered Outcomes Research (3)
- Patient Safety (7)
- Policy (2)
- Practice Patterns (2)
- Pregnancy (1)
- Provider (2)
- Provider: Physician (2)
- Public Health (2)
- Public Reporting (1)
- Quality Improvement (5)
- Quality Indicators (QIs) (1)
- Quality of Care (5)
- Racial and Ethnic Minorities (4)
- Registries (5)
- Research Methodologies (15)
- Respiratory Conditions (1)
- Risk (3)
- Screening (1)
- Sepsis (2)
- Surgery (6)
- Teams (1)
- Vitamins and Supplements (2)
- Web-Based (1)
AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 25 of 63 Research Studies DisplayedZuvekas SH, Kashihara D
AHRQ Author: Zuvekas SH
The impacts of the COVID-19 pandemic on the Medical Expenditure Panel Survey.
The COVID-19 pandemic caused substantial disruptions in the field operations of all 3 major components of the Medical Expenditure Panel Survey (MEPS). In this study, the investigators described how the MEPS program successfully responded to these challenges by reengineering field operations, including survey modes, to complete data collection and maintain data release schedules.
AHRQ-authored.
Citation: Zuvekas SH, Kashihara D .
The impacts of the COVID-19 pandemic on the Medical Expenditure Panel Survey.
Am J Public Health 2021 Dec;111(12):2157-66. doi: 10.2105/ajph.2021.306534..
Keywords: Medical Expenditure Panel Survey (MEPS), COVID-19, Healthcare Costs, Data
Saldanha IJ, Smith BT, Ntzani E
The Systematic Review Data Repository (SRDR): descriptive characteristics of publicly available data and opportunities for research.
Funded by the US Agency for Healthcare Research and Quality (AHRQ), the Systematic Review Data Repository (SRDR) is a free, web-based, open-source, data management and archival platform for reviews. The objectives of this study were to describe (1) the current extent of usage of SRDR and (2) the characteristics of all projects with publicly available data on the SRDR website.
AHRQ-funded; HHSA290201500002I_HHSA29032012T.
Citation: Saldanha IJ, Smith BT, Ntzani E .
The Systematic Review Data Repository (SRDR): descriptive characteristics of publicly available data and opportunities for research.
Syst Rev 2019 Dec 20;8(1):334. doi: 10.1186/s13643-019-1250-y..
Keywords: Evidence-Based Practice, Data, Research Methodologies, Registries
Boudreaux M, Gangopadhyaya A, Long SK
AHRQ Author: Karaca Z
Using data from the Healthcare Cost and Utilization Project for state health policy research.
Investigators describe the opportunities and challenges of using HCUP data to conduct state health policy research and to provide empirical examples of what can go wrong when using the national HCUP data inappropriately. Analyzing cesarean delivery rates, discharges per capita, and discharges by the payer, they found that state-level estimates are volatile and often provide misleading policy conclusions. They conclude that the Nationwide Inpatient Sample should not be used for state-level research and specified that AHRQ provides resources to assist analysts with state-specific studies using State Inpatient Database files.
AHRQ-authored.
Citation: Boudreaux M, Gangopadhyaya A, Long SK .
Using data from the Healthcare Cost and Utilization Project for state health policy research.
Med Care 2019 Nov;57(11):855-60. doi: 10.1097/mlr.0000000000001196..
Keywords: Healthcare Cost and Utilization Project (HCUP), Policy, Health Services Research (HSR), Healthcare Costs, Data, Research Methodologies
Shen NT, Salajegheh A, Brown RS
A call to standardize definitions, data collection, and outcome assessment to improve care in alcohol-related liver disease.
Alcohol-related liver disease (ALD) is highly prevalent and appears to be increasingly reported with worsening mortality; thus, optimizing care in this patient population is imperative. This requires a multidisciplinary, multifaceted approach that includes recognizing alcohol use disorder (AUD) and existing treatments for AUD. In this paper, the authors call for standardizing definitions, data collection, and outcome assessment to improve care in alcohol-related liver disease.
AHRQ-funded; HS000066.
Citation: Shen NT, Salajegheh A, Brown RS .
A call to standardize definitions, data collection, and outcome assessment to improve care in alcohol-related liver disease.
Hepatology 2019 Sep;70(3):1038-44. doi: 10.1002/hep.30587..
Keywords: Data, Alcohol Use, Outcomes
Bacon E, Budney G, Bondy J
Developing a regional distributed data network for surveillance of chronic health conditions: the Colorado Health Observation Regional Data Service.
This article describes attributes of regional distributed data networks using electronic health records (EHR) data and the history and design of Colorado Health Observation Regional Data Service as an emerging public health surveillance tool for chronic health conditions. The authors indicate that while benefits from EHR-based surveillance are described, a number of technology, partnership, and value proposition challenges remain.
AHRQ-funded; HS0122143.
Citation: Bacon E, Budney G, Bondy J .
Developing a regional distributed data network for surveillance of chronic health conditions: the Colorado Health Observation Regional Data Service.
J Public Health Manag Pract 2019 Sep/Oct;25(5):498-507. doi: 10.1097/phh.0000000000000810..
Keywords: Chronic Conditions, Data, Electronic Health Records (EHRs), Health Information Technology (HIT), Public Health
Liu L, Ni Y, Zhang N
Mining patient-specific and contextual data with machine learning technologies to predict cancellation of children's surgery.
The objectives of this study were: 1) to develop predictive models of last-minute surgery cancellation, utilizing machine learning technologies, from patient-specific and contextual data from two distinct pediatric surgical sites of a single institution; and 2) to identify specific key predictors that impact children's risk of day-of-surgery cancellation. The study demonstrated the capacity of machine learning models for predicting pediatric patients at risk of last-minute surgery cancellation and providing useful insight into root causes of cancellation. The author’s approach offers the promise of targeted interventions to significantly decrease both healthcare costs and families' negative experiences.
AHRQ-funded; HS024983.
Citation: Liu L, Ni Y, Zhang N .
Mining patient-specific and contextual data with machine learning technologies to predict cancellation of children's surgery.
Int J Med Inform 2019 Sep;129:234-41. doi: 10.1016/j.ijmedinf.2019.06.007..
Keywords: Children/Adolescents, Data, Electronic Health Records (EHRs), Health Information Technology (HIT), Surgery
Wang E, Kang H, Gong Y
Generating a health information technology event database from FDA MAUDE reports.
This study examined using a health information technology (HIT) event database to identify patient safety events (PSEs) or medical errors. The study used the FDA Manufacturer and User Facility Device Experience (MAUDE) database to extract HIT events. Classic and CNN models were utilized on a test set. The model was capable of identifying HIT event with about a 90% accuracy.
AHRQ-funded; HS022895.
Citation: Wang E, Kang H, Gong Y .
Generating a health information technology event database from FDA MAUDE reports.
Stud Health Technol Inform 2019 Aug 21;264:883-87. doi: 10.3233/shti190350..
Keywords: Health Information Technology (HIT), Medical Devices, Adverse Events, Data, Medical Errors, Patient Safety
Yao B, Kang H, Gong Y
Data quality assessment of narrative medication error reports.
This study examined the data quality of patient safety event (PSE) reports that are used to analyze the root causes of PSE. If the data quality is poor then the reporting and root cause analysis (RCA) will also be poor. Incomplete or missing data is the most prevalent problem in these reports. The researchers used an adapted taxonomy to assess the data quality of PSE reports, and extracted sample reports based on eight error types. The extracts were scored by experts. They found that most structured fields were ignored by reporters, but the narrative parts of the reports contained rich and valuable information. The results show that the adapted taxonomy could be a promising tool for report quality assessment and improvement.
AHRQ-funded; HS022895.
Citation: Yao B, Kang H, Gong Y .
Data quality assessment of narrative medication error reports.
Stud Health Technol Inform 2019 Aug 9;265:101-06. doi: 10.3233/shti190146..
Keywords: Adverse Drug Events (ADE), Medication, Medical Errors, Adverse Events, Data, Patient Safety
Polubriaginof FCG, Ryan P, Salmasian H
Challenges with quality of race and ethnicity data in observational databases.
This study assessed the quality of race and ethnicity information in observational health databases as well as electronic health records (EHRs) and to propose patient self-recording as a way to improve accuracy. Data from the Healthcare Cost and Utilization Project (HCUP) and Optum Labs, and from a single New York City healthcare system’s EHR was compared. Among 160 million patients in the HCUP database, no race or ethnicity data was recorded for 25% of the records. Among the 2.4 million patients in the New York City HER, race or ethnicity was unknown for 57%. However, when patients were allowed to directly record their race and ethnicity, percentages rose to 86%.
AHRQ-funded; HS021816; HS023704; HS024713.
Citation: Polubriaginof FCG, Ryan P, Salmasian H .
Challenges with quality of race and ethnicity data in observational databases.
J Am Med Inform Assoc 2019 Aug;26(8-9):730-36. doi: 10.1093/jamia/ocz113..
Keywords: Healthcare Cost and Utilization Project (HCUP), Data, Racial and Ethnic Minorities, Electronic Health Records (EHRs), Health Information Technology (HIT), Health Services Research (HSR)
Lewis VA, Joynet Maddox K, Austin AM
Developing and validating a measure to estimate poverty in Medicare administrative data.
The purpose of this study was to develop and validate a measure that estimates individual level poverty in Medicare administrative data that can be used in studies of Medicare claims. The investigators indicate that a poverty score can be calculated using Medicare administrative data for use as a continuous or binary measure and that this measure can improve researchers' ability to identify poverty in Medicare administrative data.
AHRQ-funded; HS024075.
Citation: Lewis VA, Joynet Maddox K, Austin AM .
Developing and validating a measure to estimate poverty in Medicare administrative data.
Med Care 2019 Aug;57(8):601-07. doi: 10.1097/mlr.0000000000001154..
Keywords: Medicare, Data, Low-Income, Research Methodologies
Li X, Fireman BH, Curtis JR
Validity of privacy-protecting analytical methods that use only aggregate-level information to conduct multivariable-adjusted analysis in distributed data networks.
Researchers analyzed the impact of using distributed data networks to conduct large-scale epidemiologic studies on protecting privacy of the subjects. Three aggregate-level data-sharing approaches were tested (risk-set, summary-table, and effect-estimate). Four confounding adjustment methods (matching, stratification, inverse probability matching, and matching weighting) and 2 summary scores (propensity and disease risk) for binary and time-to-event-outcomes were assessed. Risk-set data sharing generally performed better than summary-table and effect-estimate data-sharing which often produced discrepancies in settings with rare outcomes and small sample sizes.
AHRQ-funded; HS026214.
Citation: Li X, Fireman BH, Curtis JR .
Validity of privacy-protecting analytical methods that use only aggregate-level information to conduct multivariable-adjusted analysis in distributed data networks.
Am J Epidemiol 2019 Apr;188(4):709-23. doi: 10.1093/aje/kwy265..
Keywords: Data, Research Methodologies
Tong BC, Kim S, Kosinski A
Penetration, completeness, and representativeness of the Society of Thoracic Surgeons General Thoracic Surgery Database for lobectomy.
Not all surgeons performing lobectomy in the United States report outcomes to The Society of Thoracic Surgeons General Thoracic Surgery Database (STS GTSD). In this study, the investigators examined penetration, completeness, and representativeness of the STS GTSD for lobectomy in the Centers for Medicare and Medicaid Services (CMS) patient population. The investigators concluded that participation in the STS GTSD increased over time, but penetration lagged behind that of the other STS National Databases.
AHRQ-funded; HS022279.
Citation: Tong BC, Kim S, Kosinski A .
Penetration, completeness, and representativeness of the Society of Thoracic Surgeons General Thoracic Surgery Database for lobectomy.
Ann Thorac Surg 2019 Mar;107(3):897-902. doi: 10.1016/j.athoracsur.2018.07.059..
Keywords: Surgery, Cancer: Lung Cancer, Cancer, Data, Provider: Physician, Provider
Lindell RB, Nishisaki A, Weiss SL
Comparison of methods for identification of pediatric severe sepsis and septic shock in the Virtual Pediatric Systems Database.
This study compared the use of Virtual Pediatric Systems with traditional use of International Classification of Diseases, 9th edition (ICD) to identify children with severe sepsis or septic shock in PICU settings. Two different systems were compared “Martin” and “Angus”. Both showed good agreement, but ICD9 identified a smaller more accurate cohort of children. Additional analysis of discrepancies between the reference standard the two virtual systems showed that prospective screening missed 66 patients who were diagnosed with severe sepsis or severe shock. Once they were included in the standard cohort, agreement improved with a positive predictive value of 70%.
AHRQ-funded; HS024511; HS022464.
Citation: Lindell RB, Nishisaki A, Weiss SL .
Comparison of methods for identification of pediatric severe sepsis and septic shock in the Virtual Pediatric Systems Database.
Crit Care Med 2019 Feb;47(2):e129-e35. doi: 10.1097/ccm.0000000000003541..
Keywords: Children/Adolescents, Intensive Care Unit (ICU), Data, Sepsis
Hsu YJ, Kosinski AS, Wallace AS
Using a society database to evaluate a patient safety collaborative: the Cardiovascular Surgical Translational Study.
The authors assessed the utility of using external databases for quality improvement (QI) evaluations in the context of an innovative QI collaborative aimed to reduce three infections and improve patient safety across the cardiac surgery service line. They compared changes in each outcome between 15 intervention hospitals and 52 propensity score-matched hospitals, and found that improvement trends in several outcomes among the studied intervention hospitals were not statistically different from those in comparison hospitals. They conclude that using external databases may permit comparative effectiveness assessment by providing concurrent comparison groups, additional outcome measures, and longer follow-up.
AHRQ-funded; HS019934.
Citation: Hsu YJ, Kosinski AS, Wallace AS .
Using a society database to evaluate a patient safety collaborative: the Cardiovascular Surgical Translational Study.
J Comp Eff Res 2019 Jan;8(1):21-32. doi: 10.2217/cer-2018-0051..
Keywords: Patient Safety, Quality Improvement, Quality Indicators (QIs), Quality of Care, Surgery, Cardiovascular Conditions, Comparative Effectiveness, Data, Hospitals, Research Methodologies, Patient-Centered Outcomes Research
Hartling L, Guise JM, Kato E
AHRQ Author: Kato, E, Berliner E
A taxonomy of rapid reviews links report types and methods to specific decision-making contexts.
The researchers described characteristics of rapid reviews and examined the impact of methodological variations on their reliability and validity. They concluded that rapid products have tremendous methodological variation and that categorization based on timeframe or type of synthesis reveals patterns. The similarity across rapid products lies in the close relationship with the end user to meet time-sensitive decision-making needs.
AHRQ-authored; AHRQ-funded; 290201200013I; 290201200010I; 290201200011I; 290201200015I; 290201200007I; 290201200004C.
Citation: Hartling L, Guise JM, Kato E .
A taxonomy of rapid reviews links report types and methods to specific decision-making contexts.
J Clin Epidemiol 2015 Dec;68(12):1451-62.e3. doi: 10.1016/j.jclinepi.2015.05.036.
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Keywords: Decision Making, Evidence-Based Practice, Data, Research Methodologies
Kuehl DR, Berdahl CT, Jackson TD
Advancing the use of administrative data for emergency department diagnostic imaging research.
This article summarizes the discussions of the breakout session on the use of administrative data for emergency imaging research at the May 2015 Academic Emergency Medicine consensus conference, "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization." The authors describe the areas where administrative data have been applied to research evaluating the use of diagnostic imaging in the ED, the common sources for these data, and the strengths and limitations of administrative data.
AHRQ-funded; HS023498.
Citation: Kuehl DR, Berdahl CT, Jackson TD .
Advancing the use of administrative data for emergency department diagnostic imaging research.
Acad Emerg Med 2015 Dec;22(12):1417-26. doi: 10.1111/acem.12827.
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Keywords: Data, Emergency Department, Health Services Research (HSR), Imaging
Liang C, Gong Y
Enhancing patient safety event reporting by K-nearest neighbor classifier.
The debate on structured or unstructured data entry reveals not only a trade-off problem among data accuracy, completeness, and timeliness, but also a technical gap on text mining. The reesarchers suggested a text classification method for predicting subject categories. Their results demonstrated the feasibility of their system and indicated the advantage of such an application to raise data quality and clinical decision support in reporting patient safety events.
AHRQ-funded; HS022895.
Citation: Liang C, Gong Y .
Enhancing patient safety event reporting by K-nearest neighbor classifier.
Stud Health Technol Inform 2015;218:40603.
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Keywords: Adverse Events, Medical Errors, Patient Safety, Public Reporting, Clinical Decision Support (CDS), Health Information Technology (HIT), Data
Swain MJ, Kharrazi H
Feasibility of 30-day hospital readmission prediction modeling based on health information exchange data.
The researchers conducted a semi-systematic review of readmission predictive factors published prior to March 2013. They found that mapping of these variables with common HL7 segments resulted in an 89.2 percent total coverage, with the DG1 (diagnosis) segment having the highest coverage of 39.4 percent. The PID (patient identification) and OBX (observation results) segments cover 13.9 percent and 9.1 percent of the variables.
AHRQ-funded; HS022578.
Citation: Swain MJ, Kharrazi H .
Feasibility of 30-day hospital readmission prediction modeling based on health information exchange data.
Int J Med Inform 2015 Dec;84(12):1048-56. doi: 10.1016/j.ijmedinf.2015.09.003.
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Keywords: Health Information Exchange (HIE), Hospital Readmissions, Health Information Technology (HIT), Data
Neprash HT, Wallace J, Chernew ME
Measuring prices in health care markets using commercial claims data.
The objective of this study was to compare methods of price measurement in health care markets. It concluded that market-level price measures reflecting broad sets of services are likely to rank markets similarly. Price indices relying on individual sentinel services may be more appropriate for examining specialty- or service-specific drivers of prices.
AHRQ-funded; HS000055.
Citation: Neprash HT, Wallace J, Chernew ME .
Measuring prices in health care markets using commercial claims data.
Health Serv Res 2015 Dec;50(6):2037-47. doi: 10.1111/1475-6773.12304..
Keywords: Data, Healthcare Costs, Health Insurance, Health Services Research (HSR)
Panahiazar M, Taslimitehrani V, Pereira NL
Using EHRs for heart failure therapy recommendation using multidimensional patient similarity analytics.
The authors developed a multidimensional patient similarity assessment technique that leverages multiple types of information from the electronic health records and predicts a medication plan for each new patient based on prior knowledge and data from similar patients.Their findings suggest that it is feasible to harness population-based information for an individual patient-specific assessment.
AHRQ-funded; HS023077.
Citation: Panahiazar M, Taslimitehrani V, Pereira NL .
Using EHRs for heart failure therapy recommendation using multidimensional patient similarity analytics.
Stud Health Technol Inform 2015;210:369-73.
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Keywords: Clinical Decision Support (CDS), Data, Electronic Health Records (EHRs), Heart Disease and Health, Patient-Centered Healthcare
Zhang R, Manohar N, Arsoniadis E
Evaluating term coverage of herbal and dietary supplements in electronic health records.
Some supplements can interact with prescription medications, potentially leading to clinically important and potentially preventable adverse reactions. Clinical notes and corresponding medication lists from an integrated healthcare system were extracted and compared with online databases. The authors found that, overall, about 40% of listed medications are supplements, most of which are included in medication lists as nutritional or miscellaneous products. They found gaps between supplement and standard medication terminologies and identified supplements which were not mentioned in the medication lists.
AHRQ-funded; HS022085.
Citation: Zhang R, Manohar N, Arsoniadis E .
Evaluating term coverage of herbal and dietary supplements in electronic health records.
AMIA Annu Symp Proc 2015 Nov 5;2015:1361-70.
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Keywords: Adverse Drug Events (ADE), Data, Electronic Health Records (EHRs), Medication, Vitamins and Supplements
Meeker D, Jiang X, Matheny ME
A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research.
The authors’ objective was to implement infrastructure that supports the functionality of some existing research networks (e.g., cohort discovery, workflow management, and estimation of multivariate analytic models on centralized data) while adding additional important new features. They were able to implement massively parallel (map-reduce) computation methods and a new policy management system to enable each study initiated by network participants to define the ways in which data may be processed, managed, queried, and shared.
AHRQ-funded; HS019913.
Citation: Meeker D, Jiang X, Matheny ME .
A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research.
J Am Med Inform Assoc 2015 Nov;22(6):1187-95. doi: 10.1093/jamia/ocv017..
Keywords: Communication, Comparative Effectiveness, Data, Health Information Technology (HIT), Policy, Research Methodologies
Bhattacharyya S, Gesteland PH, Korgenski K
Cross-immunity between strains explains the dynamical pattern of paramyxoviruses.
The researchers used long-term incidence data on Respiratory Syncytial Virus (RSV), three serotypes of Human Parainfluenza Virus (HPIV), and Human Metapneumovirus to study mathematical models of different mechanisms of pathogen interaction. Their results showed a strong signal of cross-protection from RSV in controlling the timing and magnitude of HPIV outbreaks, and a stronger interaction with more closely related serotypes.
AHRQ-funded; HS018538.
Citation: Bhattacharyya S, Gesteland PH, Korgenski K .
Cross-immunity between strains explains the dynamical pattern of paramyxoviruses.
Proc Natl Acad Sci U S A 2015 Oct 27;112(43):13396-400. doi: 10.1073/pnas.1516698112..
Keywords: Data, Public Health, Respiratory Conditions
Haukoos JS, Lewis RJ
The propensity score.
The authors discuss studies by Rozé et al and Huybrechts et al that used propensity score matching and propensity score stratification, respectively. They argue that although both methods are more valid in terms of balancing study groups than simple matching or stratification based on baseline characteristics, they vary in their ability to minimize bias. In general, propensity score matching minimizes bias to a greater extent than propensity score stratification.
AHRQ-funded; HS021749.
Citation: Haukoos JS, Lewis RJ .
The propensity score.
JAMA 2015 Oct 20;314(15):1637-8. doi: 10.1001/jama.2015.13480..
Keywords: Research Methodologies, Data, Risk
Hazlehurst BL, Kurtz SE, Masica A
CER Hub: An informatics platform for conducting comparative effectiveness research using multi-institutional, heterogeneous, electronic clinical data.
The authors describe the CER Hub, a web-based informatics platform for developing and conducting research studies that combine comprehensive electronic clinical data from multiple health care organizations. They conclude that CER requires coordinated and scalable methods for extracting, aggregating, and analyzing complex, multi-institutional clinical data.
AHRQ-funded; HS019828.
Citation: Hazlehurst BL, Kurtz SE, Masica A .
CER Hub: An informatics platform for conducting comparative effectiveness research using multi-institutional, heterogeneous, electronic clinical data.
Int J Med Inform 2015 Oct;84(10):763-73. doi: 10.1016/j.ijmedinf.2015.06.002..
Keywords: Comparative Effectiveness, Health Information Technology (HIT), Data, Web-Based