Implementation of a mobile health clinic framework for Hepatitis C virus screening and treatment: a descriptive study.

Background: Although treatment for Hepatitis C Virus (HCV) is effective, individuals face access barriers. The utility of mobile health clinics (MHC), effective mechanisms for providing healthcare to underserved populations, is understudied for HCV-related interventions. We aimed to describe implementation of, and factors associated with, screening and treatment via MHCs. Methods: Clemson Rural Health implemented a novel MHC program to reach and treat populations at-risk for HCV with a focus on care for uninsured individuals. We examined HCV screening and treatment initiation/completion indicators between May 2021 and January 2023. Findings: Among 607 individuals screened across 31 locations, 94 (15.5%) tested positive via antibody and viral load testing. Treatment initiation and completion rates were 49.6% and 86.0%, respectively. Among those screened, the majority were male (57.5%), White (61.3%; Black/Hispanic: 28.2%/7.7%), and without personal vehicle as primary transportation mode (54.4%). Injection drug use (IDU) was 27.2% and uninsured rate was 42.8%. Compared to HCV-negative, those infected included more individuals aged 30-44 (52.1% vs. 36.4%, p = 0.023), male (70.2% vs. 55.2%, p = 0.009), White (78.5% vs. 60.2%, p < 0.0001), without personal vehicle (58.5% vs. 43.5%, p = 0.028), IDU (83.7% vs. 21.0%, p < 0.0001), and uninsured (61.2% vs. 48.8%, p = 0.050). Uninsured rates were higher among those initiating compared to not initiating treatment (74.5% vs. 45.3%, p = 0.004). Interpretation: The MHC framework successfully reaching its target population: at-risk individuals with access barriers to healthcare. The high HCV screening and treatment initiation/completion rates demonstrate the utility of MHCs as effective and acceptable intervention settings among historically difficult-to-treat populations. Funding: Gilead Sciences, Inc., and SC Center for Rural and Primary Healthcare.

Interventional Radiologists Achieve Equivalent Outcomes and Lower Costs for Totally Implantable Venous Access Device Placement Compared to Operating Room Placement.

PURPOSE: To compare the cost and outcomes of surgical and interventional radiology (IR) placement of totally implantable venous access devices (TIVADs) within a large regional health system to determine the service line with better outcomes and lower costs to the health system. MATERIALS AND METHODS: A retrospective review of all chest port placements performed in the operating room (OR) and IR suite over 12 months was conducted at a large, integrated health system with 6 major hospitals. Secondary electronic health record and cost data were used to identify TIVAD placements, follow-up procedures indicating port malfunction, early adverse events (within 1 month after the surgery), late adverse events (2-12 months after the procedure), and health system cost of TIVAD placement and management. RESULTS: For 799 total port placements included in this analysis, the rate of major adverse events was 1.3% and 1.9% for the IR and OR groups, respectively, during the early follow-up (P = .5655) and 4.9% and 2.8% for the IR and OR groups, respectively, during the late follow-up (P = .5437). Malfunction-related follow-up procedure rates were 1.8% and 2.6% for the IR and OR groups, respectively, during the early follow-up (P = .4787) and 12.4% and 10.5% for the IR and OR groups, respectively, during the late follow-up (P = .4354). The mean cost of port placement per patient was $4,509 and $5,247 for the IR and OR groups, respectively. The difference in per-patient cost of port placement was $1,170 greater for the OR group (P = .0074). CONCLUSIONS: The similar rates of adverse events and follow-up procedures and significant differences in insertion cost suggest that IR TIVAD placement may be more cost effective than surgical placement without affecting the quality.

Health Indicators as Measures of Individual Health Status and Their Public Perspectives: Cross-sectional Survey Study.

BACKGROUND: Disease status (eg, cancer stage) has been used in routine clinical practice to determine more accurate treatment plans. Health-related indicators, such as mortality, morbidity, and population group life expectancy, have also been used. However, few studies have specifically focused on the comprehensive and objective measures of individual health status. OBJECTIVE: The aim of this study was to analyze the perspectives of the public toward 29 health indicators obtained from a literature review to provide evidence for further prioritization of the indicators. The difference between health status and disease status should be considered. METHODS: This study used a cross-sectional design. Online surveys were administered through Ohio University, ResearchMatch, and Clemson University, resulting in three samples. Participants aged 18 years or older rated the importance of the 29 health indicators. The rating results were aggregated and analyzed as follows (in each case, the dependent variables were the individual survey responses): (1) to determine the agreement among the three samples regarding the importance of each indicator, where the independent variables (IVs) were the three samples; (2) to examine the mean differences between the retained indicators with agreement across the three samples, where the IVs were the identified indicators; and (3) to rank the groups of indicators into various levels after grouping the indicators with no mean differences, where the IVs were the groups of indicators. RESULTS: In total, 1153 valid responses were analyzed. Descriptive statistics revealed that the top five-rated indicators were drug or substance abuse, smoking or tobacco use, alcohol abuse, major depression, and diet and nutrition. Among the 29 health indicators, the three samples agreed upon the importance of 13 indicators. Inferential statistical analysis indicated that some of the 13 indicators held equal importance. Therefore, the 13 indicators were categorized by rank into seven levels: level 1 included blood sugar level and immunization and vaccination; level 2 included LDL cholesterol; level 3 included HDL cholesterol, blood triglycerides, cancer screening detection, and total cholesterol; level 4 included health literacy rate; level 5 included personal care needs and air quality index greater than 100; level 6 included self-rated health status and HIV testing; and level 7 included the supply of dentists. Levels 1 to 3 were rated significantly higher than levels 4 to 7. CONCLUSIONS: This study provides a baseline for prioritizing 29 health indicators, which can be used by electronic health record or personal health record system designers or developers to determine what can be included in the systems to capture an individual's health status. Currently, self-rated health status is the predominantly used health indicator. Additionally, this study provides a foundation for tracking and measuring preventive health care services more accurately and for developing an individual health status index.

Complete and Resilient Documentation for Operational Medical Environments Leveraging Mobile Hands-free Technology in a Systems Approach: Experimental Study.

BACKGROUND: Prehospitalization documentation is a challenging task and prone to loss of information, as paramedics operate under disruptive environments requiring their constant attention to the patients. OBJECTIVE: The aim of this study is to develop a mobile platform for hands-free prehospitalization documentation to assist first responders in operational medical environments by aggregating all existing solutions for noise resiliency and domain adaptation. METHODS: The platform was built to extract meaningful medical information from the real-time audio streaming at the point of injury and transmit complete documentation to a field hospital prior to patient arrival. To this end, the state-of-the-art automatic speech recognition (ASR) solutions with the following modular improvements were thoroughly explored: noise-resilient ASR, multi-style training, customized lexicon, and speech enhancement. The development of the platform was strictly guided by qualitative research and simulation-based evaluation to address the relevant challenges through progressive improvements at every process step of the end-to-end solution. The primary performance metrics included medical word error rate (WER) in machine-transcribed text output and an F1 score calculated by comparing the autogenerated documentation to manual documentation by physicians. RESULTS: The total number of 15,139 individual words necessary for completing the documentation were identified from all conversations that occurred during the physician-supervised simulation drills. The baseline model presented a suboptimal performance with a WER of 69.85% and an F1 score of 0.611. The noise-resilient ASR, multi-style training, and customized lexicon improved the overall performance; the finalized platform achieved a medical WER of 33.3% and an F1 score of 0.81 when compared to manual documentation. The speech enhancement degraded performance with medical WER increased from 33.3% to 46.33% and the corresponding F1 score decreased from 0.81 to 0.78. All changes in performance were statistically significant (P<.001). CONCLUSIONS: This study presented a fully functional mobile platform for hands-free prehospitalization documentation in operational medical environments and lessons learned from its implementation.

Diabetes Patient Surveillance in the Emergency Department: Proof of Concept and Opportunities.

INTRODUCTION: The purpose of this study was to characterize the at-risk diabetes and prediabetes patient population visiting emergency department (ED) and urgent care (UC) centers in upstate South Carolina. METHODS: We conducted this retrospective study at the largest non-profit healthcare system in South Carolina, using electronic health record (EHR) data of patients who had an ED or UC visit between February 2, 2016-July 31, 2018. Key variables including International Classification of Diseases, 10th Revision codes, laboratory test results, family history, medication, and demographic characteristics were used to classify the patients as healthy, having prediabetes, having diabetes, being at-risk for prediabetes, or being at-risk for diabetes. Patients who were known to have diabetes were classified further as having controlled diabetes, management challenged, or uncontrolled diabetes. Population analysis was stratified by the patient's annual number of ED/UC visits. RESULTS: The risk stratification revealed 4.58% unique patients with unrecognized diabetes and 10.34% of the known patients with diabetes considered to be suboptimally controlled. Patients identified as diabetes management challenged had more ED/UC visits. Of note, 33.95% of the patients had unrecognized prediabetes/diabetes risk factors identified during their ED/UC with 87.95% having some form of healthcare insurance. CONCLUSION: This study supports the idea that a single ED/UC unscheduled visit can identify individuals with unrecognized diabetes and an at-risk prediabetes population using EHR data. A patient's ED/UC visit, regardless of their primary reason for seeking care, may be an opportunity to provide early identification and diabetes disease management enrollment to augment the medical care of our community.

Deep learning for semi-automated unidirectional measurement of lung tumor size in CT.

BACKGROUND: Performing Response Evaluation Criteria in Solid Tumor (RECISTS) measurement is a non-trivial task requiring much expertise and time. A deep learning-based algorithm has the potential to assist with rapid and consistent lesion measurement. PURPOSE: The aim of this study is to develop and evaluate deep learning (DL) algorithm for semi-automated unidirectional CT measurement of lung lesions. METHODS: This retrospective study included 1617 lung CT images from 8 publicly open datasets. A convolutional neural network was trained using 1373 training and validation images annotated by two radiologists. Performance of the DL algorithm was evaluated 244 test images annotated by one radiologist. DL algorithm's measurement consistency with human radiologist was evaluated using Intraclass Correlation Coefficient (ICC) and Bland-Altman plotting. Bonferroni's method was used to analyze difference in their diagnostic behavior, attributed by tumor characteristics. Statistical significance was set at p < 0.05. RESULTS: The DL algorithm yielded ICC score of 0.959 with human radiologist. Bland-Altman plotting suggested 240 (98.4 %) measurements realized within the upper and lower limits of agreement (LOA). Some measurements outside the LOA revealed difference in clinical reasoning between DL algorithm and human radiologist. Overall, the algorithm marginally overestimated the size of lesion by 2.97 % compared to human radiologists. Further investigation indicated tumor characteristics may be associated with the DL algorithm's diagnostic behavior of over or underestimating the lesion size compared to human radiologist. CONCLUSIONS: The DL algorithm for unidirectional measurement of lung tumor size demonstrated excellent agreement with human radiologist.

Intervention to Reduce Interobserver Variability in Computed Tomographic Measurement of Cancer Lesions Among Experienced Radiologists.

While a growing number of research studies have reported the inter-observer variability in computed tomographic (CT) measurements, there are very few interventional studies performed. We aimed to assess whether a peer benchmarking intervention tool may have an influence on reducing interobserver variability in CT measurements and identify possible barriers to the intervention. In this retrospective study, 13 board-certified radiologists repeatedly reviewed 10 CT image sets of lung lesions and hepatic metastases during 3 noncontiguous time periods (T1, T2, T3). Each preselected case contained normal anatomy cephalad and caudal to the lesion of interest. Lesion size measurement under RECISTS 1.1 guidelines, choice of CT slice, and time spent on measurement were captured. Prior to their final measurements, the participants were exposed to the intervention designed to reduce the number of measurements deviating from the median. Chi-square test was performed to identify radiologist-dependent factors associated with the variability. The percent of deviating measurements during T1 and T2 were 20.0% and 23.1%, respectively. There was no statistically significant change in the number of deviating measurements upon the presentation of the intervention despite the decrease in percent from 23.1% to 17.7%. The identified barriers to the intervention include clinical disagreements among radiologists. Specifically, the inter-observer variability was associated with the controversy over the choice of CT image slice (P = 0.045) and selection of start-point, axis, and end-point (P = 0.011). Clinical disagreements rather than random errors were barriers to reducing interobserver variability in CT measurement among experienced radiologists. Future interventions could aim to resolve the disagreement in an interactive approach.

Retrospective comparison of approaches to evaluating inter-observer variability in CT tumour measurements in an academic health centre.

BACKGROUND: A growing number of research studies have reported inter-observer variability in sizes of tumours measured from CT scans. It remains unclear whether the conventional statistical measures correctly evaluate the CT measurement consistency for optimal treatment management and decision-making. We compared and evaluated the existing measures for evaluating inter-observer variability in CT measurement of cancer lesions. METHODS: 13 board-certified radiologists repeatedly reviewed 10 CT image sets of lung lesions and hepatic metastases selected through a randomisation process. A total of 130 measurements under RECIST 1.1 (Response Evaluation Criteria in Solid Tumors) guidelines were collected for the demonstration. Intraclass correlation coefficient (ICC), Bland-Altman plotting and outlier counting methods were selected for the comparison. The each selected measure was used to evaluate three cases with observed, increased and decreased inter-observer variability. RESULTS: The ICC score yielded a weak detection when evaluating different levels of the inter-observer variability among radiologists (increased: 0.912; observed: 0.962; decreased: 0.990). The outlier counting method using Bland-Altman plotting with 2SD yielded no detection at all with its number of outliers unchanging regardless of level of inter-observer variability. Outlier counting based on domain knowledge was more sensitised to different levels of the inter-observer variability compared with the conventional measures (increased: 0.756; observed: 0.923; improved: 1.000). Visualisation of pairwise Bland-Altman bias was also sensitised to the inter-observer variability with its pattern rapidly changing in response to different levels of the inter-observer variability. CONCLUSIONS: Conventional measures may yield weak or no detection when evaluating different levels of the inter-observer variability among radiologists. We observed that the outlier counting based on domain knowledge was sensitised to the inter-observer variability in CT measurement of cancer lesions. Our study demonstrated that, under certain circumstances, the use of standard statistical correlation coefficients may be misleading and result in a sense of false security related to the consistency of measurement for optimal treatment management and decision-making.

Factors influencing lung cancer screening completion following participation in shared decision-making: A retrospective study in a U.S. academic health system.

PURPOSE: Shared decision making (SDM) between patients and designated health professionals is recommended by several professional organizations prior to lung cancer screening by low dose CT (LDCT). This study seeks to identify factors, including characteristics of patients and referring clinicians, that influence LDCT screening completion following participation in SDM. MATERIALS AND METHODS: This retrospective study consisted of n = 171 patients eligible for LDCT screening and who participated in SDM between 2016 and 2017 in one of two sites in Prisma Health, an academic health care delivery system in South Carolina. Patient characteristics included age, sex, race, body mass index, marital status, insurance, smoking status and history, family history of lung cancer, SDM site, and distance to screening site. Characteristics of referred clinicians included age, sex, race, specialty, years of practice, education, and residency. Descriptive statistics and multivariable generalized linear mixed models were used to compare effects of patient and referring clinician characteristics on LDCT completion. RESULTS: A total of 152 patients (89%) completed LDCT screening after participation in SDM. SDM site (p = 0.02), longer distances to the screening site (p = 0.03), referrals from internal medicine clinicians (p = 0.03), and referrals from younger clinicians (p = 0.01) and from those with less years of experience (p = 0.02) were significantly associated with a lower likelihood of screening completion. CONCLUSIONS: Several factors significantly associated with screening completion were identified. This information can assist with development of interventions to improve communication and decision-making between patients, clinicians, and SDM health professionals, and inform design of targeted decision aids embedded into SDM procedures.

Enhancing Patient Activation and Self-Management Activities in Patients With Type 2 Diabetes Using the US Department of Defense Mobile Health Care Environment: Feasibility Study.

BACKGROUND: Past mobile health (mHealth) efforts to empower type 2 diabetes (T2D) self-management include portals, text messaging, collection of biometric data, electronic coaching, email, and collection of lifestyle information. OBJECTIVE: The primary objective was to enhance patient activation and self-management of T2D using the US Department of Defense's Mobile Health Care Environment (MHCE) in a patient-centered medical home setting. METHODS: A multisite study, including a user-centered design and a controlled trial, was conducted within the US Military Health System. Phase I assessed preferences regarding the enhancement of the enabling technology. Phase II was a single-blinded 12-month feasibility study that randomly assigned 240 patients to either the intervention (n=123, received mHealth technology and behavioral messages tailored to Patient Activation Measure [PAM] level at baseline) or the control group (n=117, received equipment but not messaging. The primary outcome measure was PAM scores. Secondary outcome measures included Summary of Diabetes Self-Care Activities (SDSCA) scores and cardiometabolic outcomes. We used generalized estimating equations to estimate changes in outcomes. RESULTS: The final sample consisted of 229 patients. Participants were 61.6% (141/229) male, had a mean age of 62.9 years, mean glycated hemoglobin (HbA1c) of 7.5%, mean BMI of 32.7, and a mean duration of T2D diagnosis of 9.8 years. At month 12, the control group showed significantly greater improvements compared with the intervention group in PAM scores (control mean 7.49, intervention mean 1.77; P=.007), HbA1c (control mean -0.53, intervention mean -0.11; P=.006), and low-density lipoprotein cholesterol (control mean -7.14, intervention mean 4.38; P=.01). Both groups showed significant improvement in SDSCA, BMI, waist size, and diastolic blood pressure; between-group differences were not statistically significant. Except for patients with the highest level of activation (PAM level 4), intervention group patients exhibited significant improvements in PAM scores. For patients with the lowest level of activation (PAM level 1), the intervention group showed significantly greater improvement compared with the control group in HbA1c (control mean -0.09, intervention mean -0.52; P=.04), BMI (control mean 0.58, intervention mean -1.22; P=.01), and high-density lipoprotein cholesterol levels (control mean -4.86, intervention mean 3.56; P<.001). Significant improvements were seen in AM scores, SDSCA, and waist size for both groups and in diastolic and systolic blood pressure for the control group; the between-group differences were not statistically significant. The percentage of participants who were engaged with MHCE for ≥50% of days period was 60.7% (68/112; months 0-3), 57.4% (62/108; months 3-6), 49.5% (51/103; months 6-9), and 43% (42/98; months 9-12). CONCLUSIONS: Our study produced mixed results with improvement in PAM scores and outcomes in both the intervention and control groups. Structural design issues may have hampered the influence of tailored behavioral messaging within the intervention group. TRIAL REGISTRATION: ClinicalTrials.gov NCT02949037; https://clinicaltrials.gov/ct2/show/NCT02949037. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/resprot.6993.

A Patient-Centered Mobile Phone App (iHeartU) With a Virtual Human Assistant for Self-Management of Heart Failure: Protocol for a Usability Assessment Study.

BACKGROUND: Heart failure (HF) causes significant economic and humanistic burden for patients and their families, especially those with a low income, partly due to high hospital readmission rates. Optimal self-care is considered an important nonpharmacological aspect of HF management that can improve health outcomes. Emerging evidence suggests that self-management assisted by smartphone apps may reduce rehospitalization rates and improve the quality of life of patients. We developed a virtual human-assisted, patient-centered mobile health app (iHeartU) for patients with HF to enhance their engagement in self-management and improve their communication with health care providers and family caregivers. iHeartU may help patients with HF in self-management to reduce the technical knowledge and usability barrier while maintaining a low cost and natural, effective social interaction with the user. OBJECTIVE: With a standardized systematic usability assessment, this study had two objectives: (1) to determine the obstacles to effective and efficient use of iHeartU in patients with HF and (2) to evaluate of HF patients' adoption, satisfaction, and engagement with regard to the of iHeartU app. METHODS: The basic methodology to develop iHeartU systems consists of a user-centric design, development, and mixed methods formative evaluation. The iterative design and evaluation are based on the guidelines of the American College of Cardiology Foundation and American Heart Association for the management of heart failure and the validated "Information, Motivation, and Behavioral skills" behavior change model. Our hypothesis is that this method of a user-centric design will generate a more usable, useful, and easy-to-use mobile health system for patients, caregivers, and practitioners. RESULTS: The prototype of iHeartU has been developed. It is currently undergoing usability testing. As of September 2018, the first round of usability testing data have been collected. The final data collection and analysis are expected to be completed by the end of 2019. CONCLUSIONS: The main contribution of this project is the development of a patient-centered self-management system, which may support HF patients' self-care at home and aid in the communication between patients and their health care providers in a more effective and efficient way. Widely available mobile phones serve as care coordination and "no-cost" continuum of care. For low-income patients with HF, a mobile self-management tool will expand their accessibility to care and reduce the cost incurred due to emergency visits or readmissions. The user-centered design will improve the level of engagement of patients and ultimately lead to better health outcomes. Developing and testing a novel mobile system for patients with HF that incorporates chronic disease management is critical for advancing research and clinical practice of care for them. This research fills in the gap in user-centric design and lays the groundwork for a large-scale population study in the next phase. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13502.

Effect of clinical decision rules, patient cost and malpractice information on clinician brain CT image ordering: a randomized controlled trial.

BACKGROUND: The frequency of head computed tomography (CT) imaging for mild head trauma patients has raised safety and cost concerns. Validated clinical decision rules exist in the published literature and on-line sources to guide medical image ordering but are often not used by emergency department (ED) clinicians. Using simulation, we explored whether the presentation of a clinical decision rule (i.e. Canadian CT Head Rule - CCHR), findings from malpractice cases related to clinicians not ordering CT imaging in mild head trauma cases, and estimated patient out-of-pocket cost might influence clinician brain CT ordering. Understanding what type and how information may influence clinical decision making in the ordering advanced medical imaging is important in shaping the optimal design and implementation of related clinical decision support systems. METHODS: Multi-center, double-blinded simulation-based randomized controlled trial. Following standardized clinical vignette presentation, clinicians made an initial imaging decision for the patient. This was followed by additional information on decision support rules, malpractice outcome review, and patient cost; each with opportunity to modify their initial order. The malpractice and cost information differed by assigned group to test the any temporal relationship. The simulation closed with a second vignette and an imaging decision. RESULTS: One hundred sixteen of the 167 participants (66.9%) initially ordered a brain CT scan. After CCHR presentation, the number of clinicians ordering a CT dropped to 76 (45.8%), representing a 21.1% reduction in CT ordering (P = 0.002). This reduction in CT ordering was maintained, in comparison to initial imaging orders, when presented with malpractice review information (p = 0.002) and patient cost information (p = 0.002). About 57% of clinicians changed their order during study, while 43% never modified their imaging order. CONCLUSION: This study suggests that ED clinician brain CT imaging decisions may be influenced by clinical decision support rules, patient out-of-pocket cost information and findings from malpractice case review. TRIAL REGISTRATION: NCT03449862 , February 27, 2018, Retrospectively registered.

Outdoor Environment and Pediatric Asthma: An Update on the Evidence from North America.

Introduction. The evidence about the association between asthma and outdoor environmental factors has been inadequate for certain allergens. Even less is known about how these associations vary across seasons and climate regions. We reviewed recent literature from North America for research related to outdoor environmental factors and pediatric asthma, with attention to spatial-temporal variations of these associations. Method. We included indexed literature between years 2010 and 2015 on outdoor environmental factors and pediatric asthma, by searching PubMed. Results. Our search resulted in 33 manuscripts. Studies about the link between pediatric asthma and traffic-related air pollutants (TRAP) consistently confirmed the correlation between TRAP and asthma. For general air pollution, the roles of PM2.5 and CO were consistent across studies. The link between asthma and O3 varied across seasons. Regional variation exists in the role of SO2. The impact of pollen was consistent across seasons, whereas the role of polycyclic aromatic hydrocarbon was less consistent. Discussion. Recent studies strengthened the evidence about the roles of PM2.5, TRAP, CO, and pollen in asthma, while the evidence for roles of PM10-2.5, PM10, O3, NO2, SO2, and polycyclic aromatic hydrocarbon in asthma was less consistent. Spatial-temporal details of the environment are needed in future studies of asthma and environment.

The adoption of an electronic health record did not improve A1c values in Type 2 diabetes.

BACKGROUND: A major justification for the clinical adoption of electronic health records (EHRs) was the expectation that it would improve the quality of medical care. No longitudinal study has tested this assumption. OBJECTIVE: We used hemoglobin A1c, a recognized clinical quality measure directly related to diabetes outcomes, to assess the effect of EHR use on clinical quality. METHODS: We performed a five-and-one-half-year multicentre longitudinal retrospective study of the A1c values of 537 type 2 diabetic patients. The same patients had to have been seen on at least three occasions: once approximately six months prior to EHR adoption (before-EHR), once approximately six monthsafter EHR adoption (after-EHR) and once approximately five years after EHR adoption (five-years), for a total of 1,611 notes. RESULTS: The overall mean confidence interval (CI) A1c values for the before- EHR, after-EHR and five-years were 7.07 (6.91 - 7.23), 7.33 (7.14 - 7.52) and 7.19 (7.06 - 7.32), respectively. There was a small but significant increase in A1c values between before-EHR and after-EHR, p = .04; there were no other significant differences. There was a significant decrease in notes missing at least one A1c value, from 42% before-EHR to 16% five-years (p < .001). CONCLUSION: We found that based on patient's A1c values, EHRs did not improve the clinical quality of diabetic care in six months and five years after EHR adoption. To our knowledge, this is the first longitudinal study to directly assess the relationshipbetween the use of an EHR and clinical quality.

Point-of-Care Estimated Radiation Exposure and Imaging Guidelines Can Reduce Pediatric Radiation Burden.

INTRODUCTION: The steady increase in the use of computed tomography (CT) has particular concerns for children. Family physicians must often select pediatric imaging without any decision support. We hypothesized that point-of-care decision support would lead to the selection of imaging that lowered radiation exposure and improved guideline congruence. METHODS: Our double-blind, randomized simulation included family physicians in the Military Health System. Participants initially reviewed a pediatric hematuria scenario and selected imaging without decision support. Participants were subsequently randomized to either receive imaging-appropriateness guidelines and then estimated radiation exposure information or receive estimated radiation information then guidelines; imaging selections were required after each step. The primary outcome was the selected imaging modality with point-of-care decision support. RESULTS: The first arm increased CT ordering after viewing the guidelines (P = .008) but then decreased it after reviewing radiation exposure information (P = .007). In the second arm radiation information decreased CT and plain film use (P = not significant), with a subsequent increase in ultrasound and CT after the guideline presentation (P = .05). CONCLUSIONS: Decision support during a simulated pediatric scenario helped family physicians select imaging that lowered radiation exposure and was aligned with current guidelines, especially when presented with radiation information after guideline review. This information could help inform electronic medical record design.

Electronic health records improve clinical note quality.

BACKGROUND AND OBJECTIVE: The clinical note documents the clinician's information collection, problem assessment, clinical management, and its used for administrative purposes. Electronic health records (EHRs) are being implemented in clinical practices throughout the USA yet it is not known whether they improve the quality of clinical notes. The goal in this study was to determine if EHRs improve the quality of outpatient clinical notes. MATERIALS AND METHODS: A five and a half year longitudinal retrospective multicenter quantitative study comparing the quality of handwritten and electronic outpatient clinical visit notes for 100 patients with type 2 diabetes at three time points: 6 months prior to the introduction of the EHR (before-EHR), 6 months after the introduction of the EHR (after-EHR), and 5 years after the introduction of the EHR (5-year-EHR). QNOTE, a validated quantitative instrument, was used to assess the quality of outpatient clinical notes. Its scores can range from a low of 0 to a high of 100. Sixteen primary care physicians with active practices used QNOTE to determine the quality of the 300 patient notes. RESULTS: The before-EHR, after-EHR, and 5-year-EHR grand mean scores (SD) were 52.0 (18.4), 61.2 (16.3), and 80.4 (8.9), respectively, and the change in scores for before-EHR to after-EHR and before-EHR to 5-year-EHR were 18% (p<0.0001) and 55% (p<0.0001), respectively. All the element and grand mean quality scores significantly improved over the 5-year time interval. CONCLUSIONS: The EHR significantly improved the overall quality of the outpatient clinical note and the quality of all its elements, including the core and non-core elements. To our knowledge, this is the first study to demonstrate that the EHR significantly improves the quality of clinical notes.

QNOTE: an instrument for measuring the quality of EHR clinical notes.

BACKGROUND AND OBJECTIVE: The outpatient clinical note documents the clinician's information collection, problem assessment, and patient management, yet there is currently no validated instrument to measure the quality of the electronic clinical note. This study evaluated the validity of the QNOTE instrument, which assesses 12 elements in the clinical note, for measuring the quality of clinical notes. It also compared its performance with a global instrument that assesses the clinical note as a whole. MATERIALS AND METHODS: Retrospective multicenter blinded study of the clinical notes of 100 outpatients with type 2 diabetes mellitus who had been seen in clinic on at least three occasions. The 300 notes were rated by eight general internal medicine and eight family medicine practicing physicians. The QNOTE instrument scored the quality of the note as the sum of a set of 12 note element scores, and its inter-rater agreement was measured by the intraclass correlation coefficient. The Global instrument scored the note in its entirety, and its inter-rater agreement was measured by the Fleiss κ. RESULTS: The overall QNOTE inter-rater agreement was 0.82 (CI 0.80 to 0.84), and its note quality score was 65 (CI 64 to 66). The Global inter-rater agreement was 0.24 (CI 0.19 to 0.29), and its note quality score was 52 (CI 49 to 55). The QNOTE quality scores were consistent, and the overall QNOTE score was significantly higher than the overall Global score (p=0.04). CONCLUSIONS: We found the QNOTE to be a valid instrument for evaluating the quality of electronic clinical notes, and its performance was superior to that of the Global instrument.

Family nurse practitioner student perception of journal abstract usefulness in clinical decision making: a randomized controlled trial.

PURPOSE: To assess family nurse practitioner (FNP) student perception of research abstract usefulness in clinical decision making. DATA SOURCES: A randomized controlled trial conducted in a simulated environment with graduate FNP students of the Graduate School of Nursing, Uniformed Services University of the Health Sciences. Given a clinical case study and modified MEDLINE search tool accessible via an iPad device, participants were asked to develop a treatment plan and complete a data collection form. The primary measure was perceived usefulness of the research abstracts in clinical decision making regarding a simulated obese patient seeking to prevent type 2 diabetes. Secondary measures related to participant demographics and accessibility and usefulness of full-text manuscripts. CONCLUSIONS: The majority of NP students identified readily available research abstracts as useful in shaping their clinical decision making. The presence or absence of full-text manuscripts associated with the abstracts did not appear to influence the perceived abstract usefulness. The majority of students with full-text manuscript access in the timed simulated clinical encounter read at least one paper, but cited insufficient time to read full-text as a constraint. IMPLICATIONS FOR PRACTICE: Research abstracts at point of care may be valuable to FNPs if easily accessible and integrated into clinical workflow.

Radiation exposure and cost influence physician medical image decision making: a randomized controlled trial.

BACKGROUND: It is estimated that 20%-40% of advanced medical imaging in the United States is unnecessary, resulting in patient overexposure to radiation and increasing the cost of care. Previous imaging utilization studies have focused on clinical appropriateness. An important contributor to excessive use of advanced imaging may be a physician "knowledge gap" regarding the safety and cost of the tests. OBJECTIVES: To determine whether safety and cost information will change physician medical image decision making. RESEARCH DESIGN: Double-blinded, randomized controlled trial. Following standardized case presentation, physicians made an initial imaging choice. This was followed by the presentation of guidelines, radiation exposure and health risk, and cost information. RESULTS: Approximately half (57 of 112, 50.9%) of participants initially selected computed tomography (CT). When presented with guideline recommendations, participants did not modify their initial imaging choice (P=0.197). A significant reduction (56.3%, P<0.001) in CT ordering occurred after presentation of radiation exposure/health risk information; ordering changed to magnetic resonance imaging or ultrasound (US). A significant reduction (48.3%, P<0.001) in CT and magnetic resonance imaging ordering occurred after presentation of Medicare reimbursement information; ordering changed to US. The majority of physicians (31 of 40, 77.5%) selecting US never modified their ordering. No significant relationship between physician demographics and decision making was observed. CONCLUSIONS: This study suggests that physician decision making can be influenced by safety and cost information and the order in which information is provided to physicians can affect their decisions.