The role of the electronic medical record in the assessment of health related quality of life.
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ABSTRACT:
SUBMITTER: Pakhomov SV
PROVIDER: S-EPMC3243229 | biostudies-literature | 2011
REPOSITORIES: biostudies-literature
Publications
The role of the electronic medical record in the assessment of health related quality of life.
Pakhomov Serguei V S SV Shah Nilay D ND Van Houten Holly K HK Hanson Penny L PL Smith Steven A SA
AMIA ... Annual Symposium proceedings. AMIA Symposium 20111022
We applied a hybrid Natural Language Processing (NLP) and machine learning (ML) approach (NLP-ML) to assessment of health related quality of life (HRQOL). The approach uses text patterns extracted from HRQOL inventories and electronic medical records (EMR) as predictive features for training ML classifiers. On a cohort of 200 patients, our approach agreed with patient self-report (EQ5D) and manual audit of the EMR 65-74% of the time. In an independent cohort of 285 patients, we found no associat ...[more]
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Project description:BACKGROUND:The increased use of electronic medical records (EMRs) in Canadian primary health care practice has resulted in an expansion of the availability of EMR data. Potential users of these data need to understand their quality in relation to the uses to which they are applied. Herein, we propose a basic model for assessing primary health care EMR data quality, comprising a set of data quality measures within four domains. We describe the process of developing and testing this set of measures, share the results of applying these measures in three EMR-derived datasets, and discuss what this reveals about the measures and EMR data quality. The model is offered as a starting point from which data users can refine their own approach, based on their own needs. METHODS:Using an iterative process, measures of EMR data quality were created within four domains: comparability; completeness; correctness; and currency. We used a series of process steps to develop the measures. The measures were then operationalized, and tested within three datasets created from different EMR software products. RESULTS:A set of eleven final measures were created. We were not able to calculate results for several measures in one dataset because of the way the data were collected in that specific EMR. Overall, we found variability in the results of testing the measures (e.g. sensitivity values were highest for diabetes, and lowest for obesity), among datasets (e.g. recording of height), and by patient age and sex (e.g. recording of blood pressure, height and weight). CONCLUSIONS:This paper proposes a basic model for assessing primary health care EMR data quality. We developed and tested multiple measures of data quality, within four domains, in three different EMR-derived primary health care datasets. The results of testing these measures indicated that not all measures could be utilized in all datasets, and illustrated variability in data quality. This is one step forward in creating a standard set of measures of data quality. Nonetheless, each project has unique challenges, and therefore requires its own data quality assessment before proceeding.
| S-EPMC6373085 | biostudies-other
Project description:Introduction:The adoption of electronic health records (EHRs) presents new challenges for information gathering, documentation, and patient care. Medical students spend a significant amount of time using the EHR during their clerkship experiences and will continue to do so as they progress to residency. However, formal training varies between institutions and leaves gaps in data-gathering skills, documentation skills, and order entry-these three skills formed the basis for our learning objectives. We designed a workshop using a simulated EHR to teach these skills. Methods:We offered the workshop during a class-wide transition-to-internship course for senior medical students. After a brief didactic, students worked in small groups using a simulated EHR to complete cases addressing each of the three learning objectives. Faculty facilitators assisted groups and then guided a large-group discussion of the challenges encountered during the cases. Results:Twenty-five senior medical students attended the first optional workshop. Of these students, 66.7% recommended that the workshop continue to be included in the curriculum. Comments from those who recommended otherwise suggested that many of them would recommend the workshop if it used our local EHR (Epic). Correct answers to the factual questions increased for most questions between the pretest and the posttest. Confidence to perform all skills targeted in the learning objectives increased between the pretest and the posttest. Discussion:This EHR workshop was well received by senior medical students and increased confidence in EHR skills, including data gathering, documentation, and handling unsolicited information with a plan including order entry.
| S-EPMC6946580 | biostudies-literature
Project description:BackgroundThe rapid expansion in the use of electronic health records (EHR) has increased the number of medical errors originating in health information systems (HIS). The sociotechnical approach helps in understanding risks in the development, implementation, and use of EHR and health information technology (HIT) while accounting for complex interactions of technology within the health care system.ObjectiveThis study addresses two important questions: (1) "which of the common EHR error types are associated with perceived high- and extreme-risk severity ratings among EHR users?", and (2) "which variables are associated with high- and extreme-risk severity ratings?"MethodsThis study was a quantitative, non-experimental, descriptive study of EHR users. We conducted a cross-sectional web-based questionnaire study at the largest hospital district in Finland. Statistical tests included the reliability of the summative scales tested with Cronbach's alpha. Logistic regression served to assess the association of the independent variables to each of the eight risk factors examined.ResultsA total of 2864 eligible respondents provided the final data. Almost half of the respondents reported a high level of risk related to the error type "extended EHR unavailability". The lowest overall risk level was associated with "selecting incorrectly from a list of items". In multivariate analyses, profession and clinical unit proved to be the strongest predictors for high perceived risk. Physicians perceived risk levels to be the highest ( P<.001 in six of eight error types), while emergency departments, operating rooms, and procedure units were associated with higher perceived risk levels ( P<.001 in four of eight error types). Previous participation in eLearning courses on EHR-use was associated with lower risk for some of the risk factors.ConclusionsBased on a large number of Finnish EHR users in hospitals, this study indicates that HIT safety hazards should be taken very seriously, particularly in operating rooms, procedure units, emergency departments, and intensive care units/critical care units. Health care organizations should use proactive and systematic assessments of EHR risks before harmful events occur. An EHR training program should be compulsory for all EHR users in order to address EHR safety concerns resulting from the failure to use HIT appropriately.
| S-EPMC4890731 | biostudies-literature
Project description:ImportanceCardiovascular disease is the leading cause of death in the United States. To improve cardiovascular outcomes, primary care must have valid methods of assessing performance on cardiovascular clinical quality measures, including aspirin use (aspirin measure), blood pressure control (BP measure), and smoking cessation counseling and intervention (smoking measure).ObjectiveTo compare observed performance scores measured using 2 imperfect reference standard data sources (medical record abstraction [MRA] and electronic health record [EHR]-generated reports) with misclassification-adjusted performance scores obtained using bayesian latent class analysis.Design, setting, and participantsThis cross-sectional study used a subset of the 2016 aspirin, BP, and smoking performance data from the Healthy Hearts for Oklahoma Project. Each clinical quality measure was calculated for a subset of a practice's patient population who can benefit from recommended care (ie, the eligible population). A random sample of 380 eligible patients were included for the aspirin measure; 126, for the BP measure; and 115, for the smoking measure. Data were collected from 21 primary care practices belonging to a single large health care system from January 1 to December 31, 2018, and analyzed from February 21 to April 17, 2019.Main outcomes and measuresThe main outcomes include performance scores for the aspirin, BP, and smoking measures using imperfect MRA and EHRs and estimated through bayesian latent class models.ResultsA total of 621 eligible patients were included in the analysis. Based on MRA and EHR data, observed aspirin performance scores were 76.0% (95% bayesian credible interval [BCI], 71.5%-80.1%) and 74.9% (95% BCI, 70.4%-79.1%), respectively; observed BP performance scores, 80.6% (95% BCI, 73.2%-86.9%) and 75.1% (95% BCI, 67.2%-82.1%), respectively; and observed smoking performance scores, 85.7% (95% BCI, 78.6%-91.2%) and 75.4% (95% BCI, 67.0%-82.6%), respectively. Misclassification-adjusted estimates were 74.9% (95% BCI, 70.5%-79.1%) for the aspirin performance score, 75.0% (95% BCI, 66.6%-82.5%) for the BP performance score, and 83.0% (95% BCI, 74.4%-89.8%) for the smoking performance score.Conclusions and relevanceEnsuring valid performance measurement is critical for value-based payment models and quality improvement activities in primary care. This study found that extracting information for the same individuals using different data sources generated different performance score estimates. Further research is required to identify the sources of these differences.
| S-EPMC7388024 | biostudies-literature
Project description:Several measures of oral health-related quality of life have been developed for children. The most frequently used are the Child Perceptions Questionnaire (CPQ), the Child Oral Impacts on Daily Performances (C-OIDP) and the Child Oral Health Impact Profile (COHIP). The aim of this study was to assess the methodological quality of the development and testing of these three measures.A systematic search strategy was used to identify eligible studies published up to December 2012, using both MEDLINE and Web of Science. Titles and abstracts were read independently by two investigators and full papers retrieved where the inclusion criteria were met. Data were extracted by two teams of two investigators using a piloted protocol. The data were used to describe the development of the measures and their use against existing criteria. The methodological quality and measurement properties of the measures were assessed using standards proposed by the Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) group.The search strategy yielded 653 papers, of which 417 were duplicates. Following analysis of the abstracts, 119 papers met the inclusion criteria. The majority of papers reported cross-sectional studies (n?=?117) with three of longitudinal design. Fifteen studies which had used the original version of the measures in their original language were included in the COSMIN analysis. The most frequently used measure was the CPQ. Reliability and construct validity appear to be adequate for all three measures. Children were not fully involved in item generation which may compromise their content validity. Internal consistency was measured using classic test theory with no evidence of modern psychometric techniques being used to test unidimensionality of the measures included in the COSMIN analysis.The three measures evaluated appear to be able to discriminate between groups. CPQ has been most widely tested and several versions are available. COHIP employed a rigorous development strategy but has been tested in fewer populations. C-OIDP is shorter and has been used successfully in epidemiological studies. Further testing using modern psychometric techniques such as item response theory is recommended. Future developments should also focus on the development of measures which can evaluate longitudinal change.
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Project description:Background and study aims
The Federal Ministry of Education and Research (BMBF) has funded the development of a patient controlled “Personal Electronic Health Record” (PEPA) as part of their current INFOPAT project. PEPA allows for the exchange of medical data between all interested groups, including the patients thenselves. A PEPA contains medical reports and findings including, for example, x-rays, CT scans and MRIs. The patients can safeguard their information and access all content. The aim of this study is to test the PEPA-prototype for cancer patients being treated at the National Center for Tumor Diseases (NCT) in Heidelberg.
Who can participate?
Adult colorectal cancer patients being treated at the National Center for Tumor Diseases (NCT) in Heidelberg.
What does the study involve?
There are two part to this study. The first part involves focus groups, in which a group of people are asked their opinion and attitudes towards, for example, an idea, product or service. Here, focus groups are set up that involve the patients, doctors and other health professionals to discuss current problems with the coordination of care offered to cancer patients, as well as discuss what people want to get from using PEPA (i.e. user requirements). The PEPA-prototype is then developed taking into account the conclusions from the focus groups. In the second part of the study, patients are encouraged to use the PEPA-prototype to prepare and follow up meetings with their physicians.
| 2424890 | ecrin-mdr-crc
Project description:ObjectiveAmerican College of Graduate Medical Education (ACGME) recommends ongoing care of 10 patients per resident however its implication is unclear. We hypothesized EMR quality to vary based on patient load and call status.MethodsWe conducted a double-blind, single-center, retrospective observational study between 2017 and 2019 to investigate the quality and accuracy of resident documentation using the Responsible Electronic Documentation (RED) Checklist, a validated scoring system.ResultsA total of 234 independent charts were analyzed and 80 met scoring criteria. Average patients per residents was 4, 9.1, 7.2, and 5.5 on "call" day (D0), "post-call" day (D1), "mid-call" day (D2), and "pre-call" day (D3), respectively. Mean RED checklist scores were 68.1%, 57%, 68.6%, and 72.1% on the above call status. The difference in score between D3 and D1 was statistically significant (P = .00042). There was a negative correlation between score and number of patients per resident (r = -0.286, P = .010).ConclusionEMR documentation quality is directly impacted by patient load and resident call status with the lowest documentation quality on post-call day, correlating with patient load.
| S-EPMC7940739 | biostudies-literature
Project description:ObjectivesThe objective of this study was twofold: (1) to determine how best to measure adherence with time-dependent quality indicators (QIs) related to laboratory monitoring, and (2) to assess the accuracy and efficiency of gathering QI adherence information from an electronic medical record (EMR).MethodsA random sample of 100 patients were selected who had at least three visits with the diagnosis of rheumatoid arthritis (RA) at Brigham and Women's Hospital Arthritis Center in 2005. Using the EMR, it was determined whether patients had been prescribed a disease-modifying antirheumatic drug (DMARD) (QI #1) and if patients starting therapy received appropriate baseline laboratory testing (QI #2). For patients consistently prescribed a DMARD, adherence with follow-up testing (QI #3) was calculated using three different methods, the Calendar, Interval and Rolling IntervalMethod.ResultsIt was found that 97% of patients were prescribed a DMARD (QI #1) and baseline tests were completed in 50% of patients (QI #2). For follow-up testing (QI #3), mean adherence was 60% for the Calendar Method, 35% for the Interval Method, and 48% for the Rolling Interval Method. Using the Rolling Interval Method, adherence rates were similar across drug and laboratory testing type.ConclusionsResults for adherence with laboratory testing QIs for DMARD use differed depending on how the QIs were measured, suggesting that care must be taken in clearly defining methods. While EMRs will provide important opportunities for measuring adherence with QIs, they also present challenges that must be examined before widespread adoption of these data collection methods.
| S-EPMC2924631 | biostudies-literature
Project description:Usability testing is increasingly being recognized as a way to increase the usability and safety of health information technology (HIT). Medical simulation centers can serve as testing environments for HIT usability studies. We integrated the quality assurance version of our emergency department (ED) electronic health record (EHR) into our medical simulation center and piloted a clinical care scenario in which emergency medicine resident physicians evaluated a simulated ED patient and documented electronically using the ED EHR. Meticulous planning and close collaboration with expert simulation staff was important for designing test scenarios, pilot testing, and running the sessions. Similarly, working with information systems teams was important for integration of the EHR. Electronic tools are needed to facilitate entry of fictitious clinical results while the simulation scenario is unfolding. EHRs can be successfully integrated into existing simulation centers, which may provide realistic environments for usability testing, training, and evaluation of human-computer interactions.
| S-EPMC3994869 | biostudies-other