Opioid and Antimicrobial Prescription Patterns During Emergency Medicine Encounters Among Uninsured Patients.

The purpose of this study was to characterize opioid and antimicrobial prescribing among uninsured patients seeking emergency medical care and to build predictive machine learning models. Uninsured patients were less likely to receive an opioid medication, more likely to receive non-opioid alternatives, and less likely to receive an antimicrobial prescription. The most impactful contributing factors were housing status, comorbidities, and recidivism.

Playing in the clinical decision support sandbox: tools and training for all.

Objectives: Introduce the CDS-Sandbox, a cloud-based virtual machine created to facilitate Clinical Decision Support (CDS) developers and implementers in the use of FHIR- and CQL-based open-source tools and technologies for building and testing CDS artifacts. Materials and Methods: The CDS-Sandbox includes components that enable workflows for authoring and testing CDS artifacts. Two workshops at the 2020 and 2021 AMIA Annual Symposia were conducted to demonstrate the use of the open-source CDS tools. Results: The CDS-Sandbox successfully integrated the use of open-source CDS tools. Both workshops were well attended. Participants demonstrated use and understanding of the workshop materials and provided positive feedback after the workshops. Discussion: The CDS-Sandbox and publicly available tutorial materials facilitated an understanding of the leading-edge open-source CDS infrastructure components. Conclusion: The CDS-Sandbox supports integrated use of the key CDS open-source tools that may be used to introduce CDS concepts and practice to the clinical informatics community.

Coding Disparity and Specificity during Emergency Department Visits after Transitioning to the Tenth Version of the International Classification of Diseases.

The purpose of this study was to examine coding changes using the International Classification of Diseases (ICD) after the transition from ICD-9 to ICD-10. We studied a national cohort of emergency department visits from the Veterans Health Administration (VHA) before and after the transition, focusing on coding disparity and coding specificity. The cohort accounted for 2 million emergency department visits by 1.2 million patients. There were no statistical differences between the groups with respect to demographics, comorbidities, diagnoses, or use of medical services. While ICD-10 offered significantly more codes as well as more specific coding options, the ICD-10 encounters continued to use a small number of codes, were less likely to use multiple codes, and did not consistently exploit the more unique codes to create more specific diagnoses. These findings within the VHA system corresponded to similar challenges that have been documented with Medicare claims and in the private sector.

Improving the benefits of HIV testing and referrals in large household surveys through active linkages to care: lessons and recommendations from the Namibia population-based HIV impact assessment (NAMPHIA), 2017.

In household-based surveys that include rapid HIV testing services (HTS), passive referral systems that give HIV-positive participants information about how and where to access ART but minimal follow-up support from survey staff may result in suboptimal linkage. In the 2017 Namibia Population-based HIV Impact Assessment (NAMPHIA), we piloted a system of active linkage to care and ART (ALCART) that utilized the infrastructure of existing community-based partner organizations (CBPOs). All HIV-positive participants age 15-64 years not on ART were given standard passive referrals to ART plus the option to participate in ALCART. Cases were assigned to CBPOs in participants' localities. Healthcare workers from the CBPO's contacted cases and facilitated their linkage to facility-based ART. A total of 510 participants were eligible and consented to ALCART. The majority were new diagnoses (80.8%), while the remainder were previously diagnosed but not on ART (19.2%). Of the 510, 473 (92.7%) were successfully linked into care. Of these, all but one initiated ART. Our ALCART system used existing CBPOs and contributed to >90% linkage-to-care and >99% ART-initiation among linked participants in a large, nationally-representative survey. This approach can be used to improve the potential benefits of HTS in other large population-based surveys.

Estimating the Population Size of Female Sex Workers in Three South African Cities: Results and Recommendations From the 2013-2014 South Africa Health Monitoring Survey and Stakeholder Consensus.

BACKGROUND: Robust population size estimates of female sex workers and other key populations in South Africa face multiple methodological limitations, including inconsistencies in surveillance and programmatic indicators. This has, consequently, challenged the appropriate allocation of resources and benchmark-setting necessary to an effective HIV response. A 2013-2014 integrated biological and behavioral surveillance (IBBS) survey from South Africa showed alarmingly high HIV prevalence among female sex workers in South Africa's three largest cities of Johannesburg (71.8%), Cape Town (39.7%), and eThekwini (53.5%). The survey also included several multiplier-based population size estimation methods. OBJECTIVE: The objective of our study was to present the selected population size estimation methods used in an IBBS survey and the subsequent participatory process used to estimate the number of female sex workers in three South African cities. METHODS: In 2013-2014, we used respondent-driven sampling to recruit independent samples of female sex workers for IBBS surveys in Johannesburg, Cape Town, and eThekwini. We embedded multiple multiplier-based population size estimation methods into the survey, from which investigators calculated weighted estimates and ranges of population size estimates for each city's female sex worker population. Following data analysis, investigators consulted civil society stakeholders to present survey results and size estimates and facilitated stakeholder vetting of individual estimates to arrive at consensus point estimates with upper and lower plausibility bounds. RESULTS: In total, 764, 650, and 766 female sex workers participated in the survey in Johannesburg, Cape Town, and eThekwini, respectively. For size estimation, investigators calculated preliminary point estimates as the median of the multiple estimation methods embedded in the IBBS survey and presented these to a civil society-convened stakeholder group. Stakeholders vetted all estimates in light of other data points, including programmatic experience, ensuring inclusion only of plausible point estimates in median calculation. After vetting, stakeholders adopted three consensus point estimates with plausible ranges: Johannesburg 7697 (5000-10,895); Cape Town 6500 (4579-9000); eThekwini 9323 (4000-10,000). CONCLUSIONS: Using several population size estimates methods embedded in an IBBS survey and a participatory stakeholder consensus process, the South Africa Health Monitoring Survey produced female sex worker size estimates representing approximately 0.48%, 0.49%, and 0.77% of the adult female population in Johannesburg, Cape Town, and eThekwini, respectively. In data-sparse environments, stakeholder engagement and consensus is critical to vetting of multiple empirically based size estimates procedures to ensure adoption and utilization of data-informed size estimates for coordinated national and subnational benchmarking. It also has the potential to increase coherence in national and key population-specific HIV responses and to decrease the likelihood of duplicative and wasteful resource allocation. We recommend building cooperative and productive academic-civil society partnerships around estimates and other strategic information dissemination and sharing to facilitate the incorporation of additional data as it becomes available, as these additional data points may minimize the impact of the known and unknown biases inherent in any single, investigator-calculated method.

Prescriptions Written for Opioid Pain Medication in the Veterans Health Administration Between 2000 and 2016.

OBJECTIVES: The purpose of this study was to identify national opioid pain medication (OPM) prescribing trends within the Veterans Health Administration (VA), and assess the impact of educational campaigns introduced in 2010 and 2013. METHODS: We created a national cohort that documents more than 21 million patient records and 97 million outpatient OPM prescriptions covering a 17-year period. We examined OPM prescriptions in emergency departments, outpatient clinics, and inpatient settings. RESULTS: The cohort accounted for 2.5 billion outpatient clinic visits, 18.9 million emergency department visits, and 12.4 million hospital admissions. The number of OPM prescriptions peaked in 2011, when they were provided during 5% of all outpatient visits and 15% of all emergency department visits. The morphine milligram equivalents (MMEs) peaked in 2014 at almost 17 billion in outpatient clinics and at 137 million in emergency departments. In 2016, OPM prescriptions were down 37% in outpatient clinics and 23% in emergency departments, and MMEs were down 30% in both settings. Prescriptions for hydrocodone and tramadol increased markedly between 2011 and 2015. OPM doses in inpatient settings continued to rise until 2015. CONCLUSIONS: We used a large national cohort to study trends in OPM prescriptions within the VA. Educational efforts to reduce the number of OPM prescriptions coincided with these reductions, but were initially associated with an increase in OPM dosage, an increase in the use of tramadol and hydrocodone, and an increase in the use of OPMs in inpatient settings.

Opioid pain medication prescriptions obtained through emergency medical visits in the Veterans Health Administration.

OBJECTIVE: This study sought to characterize national patterns for opioid pain medication (OPM) prescriptions received during emergency medical encounters in the Veterans Health Administration (VA). DESIGN: The authors conducted a retrospective study of all emergency department (ED) visits by adults in the VA between January 2009 and June 2015. We examined demographics, comorbidities, utilization measures, diagnoses, and prescriptions. MAIN OUTCOME MEASURES: The percentage of ED visits that culminated in the receipt of a prescription for an OPM. RESULTS: There were 6,721,134 emergency medical visits by 1,708,545 individuals during the study period. An OPM was prescribed during 913,872 visits (13.6 percent), and 407,408 individuals (27.5 percent) received at least one OPM prescription. Prescriptions for OPMs peaked in 2011 at 14.5 percent, declining to 12.3 percent in 2015. The percentage of prescriptions limited to 12 pills increased from 25.0 to 32.4 percent. The heaviest users (top 1.5 percent, n = 7,247) received an average 602.5 total doses, and had at least 10 ED visits during the study period. The most frequently prescribed OPMs were acetaminophen/hydrocodone, followed by tramadol and acetaminophen/oxycodone. Receiving a prescription was associated with younger patients, musculoskeletal diagnoses, higher pain scores, a history of chronic pain, a history of mental illness, a history of substance abuse, prior heavy prescription OPM use, and lower participation in outpatient services. CONCLUSIONS: The writing of OPM prescriptions after an ED visit is on the decline in the VA. Compliance with prescribing guidelines is increasing, but is not yet at goal.

The Decline in Hydrocodone/Acetaminophen Prescriptions in Emergency Departments in the Veterans Health Administration Between 2009 to 2015.

INTRODUCTION: The purpose of the study was to measure national prescribing patterns for hydrocodone/acetaminophen among veterans seeking emergency medical care, and to see if patterns have changed since this medication became a Schedule II controlled substance. METHODS: We conducted a retrospective cohort study of emergency department (ED) visits within the Veterans Health Administration (VA) between January 2009 and June 2015. We looked at demographics, comorbidities, utilization measures, diagnoses, and prescriptions. RESULTS: During the study period, 1,709,545 individuals participated in 6,270,742 ED visits and received 471,221 prescriptions for hydrocodone/acetaminophen (7.5% of all visits). The most common diagnosis associated with a prescription was back pain. Prescriptions peaked at 80,776 in 2011 (8.7% of visits), and declined to 35,031 (5.6%) during the first half of 2015 (r=-0.99, p<0.001). The percentage of hydrocodone/acetaminophen prescriptions limited to 12 pills increased from 22% (13,949) in 2009 to 31% (11,026) in the first half of 2015. A prescription was more likely written for patients with a pain score≥7 (OR 3.199, CI [3.192-3.205]), a musculoskeletal (OR 1.622, CI [1.615-1.630]) or soft tissue (OR 1.656, CI [1.649-1.664]) diagnosis, and those below the first quartile for total ED visits (OR 1.282, CI [1.271-1.293]) and total outpatient ICD 9 codes (OR 1.843, CI [1.833-1.853]). CONCLUSION: Hydrocodone/acetaminophen is the most frequently prescribed ED medication in the VA. The rate of prescribing has decreased since 2011, with the rate of decline remaining unchanged after it was classified as a Schedule II controlled substance. The proportion of prescriptions falling within designated guidelines has increased but is not at goal.

Estimating the Prevalence and Predictors of Incorrect Condom Use Among Sexually Active Adults in Kenya: Results From a Nationally Representative Survey.

BACKGROUND: Condom use continues to be an important primary prevention tool to reduce the acquisition and transmission of HIV and other sexually transmitted infections. However, incorrect use of condoms can reduce their effectiveness. METHODS: Using data from a 2012 nationally representative cross-sectional household survey conducted in Kenya, we analyzed a subpopulation of sexually active adults and estimated the percent that used condoms incorrectly during sex, and the type of condom errors. We used multivariable logistic regression to determine variables to be independently associated with incorrect condom use. RESULTS: Among 13,720 adolescents and adults, 8014 were sexually active in the previous 3 months (60.3%; 95% confidence interval [CI], 59.0-61.7). Among those who used a condom with a sex partner, 20% (95% CI, 17.4-22.6) experienced at least one instance of incorrect condom use in the previous 3 months. Of incorrect condom users, condom breakage or leakage was the most common error (52%; 95% CI, 44.5-59.6). Factors found to be associated with incorrect condom use were multiple sexual partnerships in the past 12 months (2 partners: adjusted odds ratio [aOR], 1.5; 95% CI, 1.0-2.0; P = 0.03; ≥3: aOR, 2.3; 95% CI, 1.5-3.5; P < 0.01) and reporting symptoms of a sexually transmitted infection (aOR, 2.8; 95% CI, 1.8-4.3; P < 0.01). CONCLUSIONS: Incorrect condom use is frequent among sexually active Kenyans and this may translate into substantial HIV transmission. Further understanding of the dynamics of condom use and misuse, in the broader context of other prevention strategies, will aid program planners in the delivery of appropriate interventions aimed at limiting such errors.

Using Big Data to Evaluate the Association between Periodontal Disease and Rheumatoid Arthritis.

An association between periodontal disease and rheumatoid arthritis is believed to exist. Most investigations into a possible relationship have been case-control studies with relatively low sample sizes. The advent of very large clinical repositories has created new opportunities for data-driven research. We conducted a retrospective cohort study to measure the association between periodontal disease and rheumatoid arthritis in a population of 25 million patients. We demonstrated that subjects with periodontal disease were roughly 1.4 times more likely to have rheumatoid arthritis. These results compare favorably with those of previous studies on smaller cohorts. Additional work is needed to identify the mechanisms behind this association and to determine if aggressive treatment of periodontal disease can alter the course of rheumatoid arthritis.

Survey of handheld computing among medical students.

The purpose of this study was to identify trends in the utilization and acceptance of handheld computers (personal digital assistants) among medical students during preclinical and clinical training. We surveyed 366 medical students and collected information on computer expertise, current handheld computer use, predicted future use, and user acceptance. Handheld computers were primarily used for personal applications by students during their preclinical training and as drug references and clinical calculators during their clinical training. In the future, all participants predicted they would use handheld computers at significantly higher rates and on a broader range of medical applications. The adoption of handheld computing was independent of user satisfaction. Those with more clinical experience were less satisfied with handheld computers, suggesting that the expectations of the more experienced users were not met. The lack of institutional support was seen as a key limitation.

Handheld computer application for medical disaster management.

We developed a prototype system that can provide reliable communications in the event of a medical disaster. The system uses redundant wireless protocols on handheld computers to deploy medical personnel, and to facilitate communication between ancillary treatment sites and a command center.

Trends in handheld computing among medical students.

The purpose of this study was to identify trends in the utilization and acceptance of handheld computers (personal digital assistants) among medical students during preclinical and clinical training. These results can be used to identify differences between preclinical and clinical users, differences between current use and idealized use, and perceived limitations of these devices.