Description of the 2020 NEMSIS Public-Release Research Dataset.

BACKGROUND: The National Emergency Medical Services Information System (NEMSIS) is a federally funded program designed to standardize Emergency Medical Services (EMS) patient care reporting and facilitate state and national data repositories for the assessment and improvement of EMS systems of care. This manuscript characterizes the 2020 submissions to the National EMS Database, detailing the strengths and limitations associated with use of these data for public health surveillance, improving prehospital patient care, critical resource allocation, clinician safety, system quality assurance and research purposes. METHODOLOGY: Using the 2020 NEMSIS Public-Release Research Dataset (NEMSIS dataset), we evaluated the dataset completeness (i.e., presence of missing/null values), dataset content and assessed data generalizability. The analysis focused on 9-1-1 EMS activations resulting in the treatment and transport of a patient, except for out-of-hospital cardiac arrests for which all patients were included regardless of transport status. RESULTS: In 2020, 43,488,767 EMS activations were reported to the National EMS Database by 12,319 agencies serving 50 states and territories. Of the 19,533,036 9-1-1 EMS activations reportedly treating and transporting a patient, the majority were attended by "non-volunteer" clinicians (77%) working in a fire-based EMS agency (35%) certified to offer Advanced Life Support (ALS) Paramedic service (80%) and located in an urban area (82%). 9-1-1 call centers most often dispatched EMS for "sick person" (20%), while EMS clinicians most likely reported asthenia (7%) as the patient's primary symptom as well as the clinician's primary impression (6%), and documented "fall on same level, slip, or trip" as the most common cause of injury (37%). The NEMSIS dataset demonstrates some "missingness" and element inconsistencies, but methods may be employed to mitigate these data limitations. CONCLUSIONS: The National EMS Database is a free and publicly available resource for evaluating EMS system utilization, response, and prehospital patient care. Understanding the characteristics of the underlying dataset and known data limitations will help ensure proper analysis and reporting of research and quality metrics based on nationally standardized NEMSIS data.

Implementation of a Web-Based Tool for Shared Decision-making in Lung Cancer Screening: Mixed Methods Quality Improvement Evaluation.

BACKGROUND: Lung cancer risk and life expectancy vary substantially across patients eligible for low-dose computed tomography lung cancer screening (LCS), which has important consequences for optimizing LCS decisions for different patients. To account for this heterogeneity during decision-making, web-based decision support tools are needed to enable quick calculations and streamline the process of obtaining individualized information that more accurately informs patient-clinician LCS discussions. We created DecisionPrecision, a clinician-facing web-based decision support tool, to help tailor the LCS discussion to a patient's individualized lung cancer risk and estimated net benefit. OBJECTIVE: The objective of our study is to test two strategies for implementing DecisionPrecision in primary care at eight Veterans Affairs medical centers: a quality improvement (QI) training approach and academic detailing (AD). METHODS: Phase 1 comprised a multisite, cluster randomized trial comparing the effectiveness of standard implementation (adding a link to DecisionPrecision in the electronic health record vs standard implementation plus the Learn, Engage, Act, and Process [LEAP] QI training program). The primary outcome measure was the use of DecisionPrecision at each site before versus after LEAP QI training. The second phase of the study examined the potential effectiveness of AD as an implementation strategy for DecisionPrecision at all 8 medical centers. Outcomes were assessed by comparing absolute tool use before and after AD visits and conducting semistructured interviews with a subset of primary care physicians (PCPs) following the AD visits. RESULTS: Phase 1 findings showed that sites that participated in the LEAP QI training program used DecisionPrecision significantly more often than the standard implementation sites (tool used 190.3, SD 174.8 times on average over 6 months at LEAP sites vs 3.5 SD 3.7 at standard sites; P<.001). However, this finding was confounded by the lack of screening coordinators at standard implementation sites. In phase 2, there was no difference in the 6-month tool use between before and after AD (95% CI -5.06 to 6.40; P=.82). Follow-up interviews with PCPs indicated that the AD strategy increased provider awareness and appreciation for the benefits of the tool. However, other priorities and limited time prevented PCPs from using them during routine clinical visits. CONCLUSIONS: The phase 1 findings did not provide conclusive evidence of the benefit of a QI training approach for implementing a decision support tool for LCS among PCPs. In addition, phase 2 findings showed that our light-touch, single-visit AD strategy did not increase tool use. To enable tool use by PCPs, prediction-based tools must be fully automated and integrated into electronic health records, thereby helping providers personalize LCS discussions among their many competing demands. PCPs also need more time to engage in shared decision-making discussions with their patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT02765412; https://clinicaltrials.gov/ct2/show/NCT02765412.

Identifying individuals with opioid use disorder: Validity of International Classification of Diseases diagnostic codes for opioid use, dependence and abuse.

BACKGROUND: Policy evaluations and health system interventions often utilize International Classification of Diseases (ICD) codes of opioid use, dependence, and abuse to identify individuals with opioid use disorder (OUD) and assess receipt of evidence-based treatments. However, ICD codes may not map directly onto the Diagnostic and Statistical Manual of Mental Disorder (DSM-5) OUD criteria. This study investigates the positive predictive value of ICD codes in identifying patients with OUD. METHODS: We conducted a clinical chart review on a national sample of 520 Veterans assigned ICD-9 or ICD-10 codes for opioid use, dependence, or abuse from 2012 to 2017. We extracted evidence of DSM-5 OUD criteria and opioid misuse from clinical documentation in the month preceding and three months following initial ICD code listing, and categorized patients into: 1) high likelihood of OUD, 2) limited aberrant opioid use, 3) prescribed opioid use without evidence of aberrant use, and 4) insufficient information. Positive predictive value was calculated as the percentage of individuals with these ICD codes meeting high likelihood of OUD criteria upon chart review. RESULTS: Only 57.7 % of patients were categorized as high likelihood of OUD; 16.5 % were categorized as limited aberrant opioid use, 18.9 % prescribed opioid use without evidence of aberrant use, and 6.9 % insufficient information. CONCLUSIONS: Patients assigned ICD codes for opioid use, dependence, or abuse often lack documentation of meeting OUD criteria. Many receive long-term opioid therapy for chronic pain without evidence of misuse. Robust methods of identifying individuals with OUD are crucial to improving access to clinically appropriate treatment.

A Method to Quantify Mean Hypertension Treatment Daily Dose Intensity Using Health Care System Data.

Importance: Simple measures of hypertension treatment, such as achievement of blood pressure (BP) targets, ignore the intensity of treatment once the BP target is met. High-intensity treatment involves increased treatment burden and can be associated with potential adverse effects in older adults. A method was previously developed to identify older patients receiving intense hypertension treatment by low BP and number of BP medications using national Veterans Health Administration and Medicare Part D administrative pharmacy data to evaluate which BP medications a patient is likely taking on any given day. Objective: To further develop and validate a method to more precisely quantify dose intensity of hypertension treatment using only health system administrative pharmacy fill data. Design, Setting, and Participants: Observational, cross-sectional study of 319 randomly selected older veterans in the national Veterans Health Administration health care system who were taking multiple BP-lowering medications and had a total of 3625 ambulatory care visits from July 1, 2011, to June 30, 2013. Measure development and medical record review occurred January 1, 2017, through November 30, 2018, and data analysis was conducted from December 1, 2019, to August 31, 2020. Main Outcomes and Measures: For each BP-lowering medication, a moderate hypertension daily dose (HDD) was defined as half the maximum dose above which no further clinical benefit has been demonstrated by that medication in hypertension trials. Patients' total HDD was calculated using pharmacy data (pharmacy HDDs), accounting for substantial delays in refills (>30 days) when a patient's pill supply was stretched (eg, cutting existing pills in half). As an external comparison, the pharmacy HDDs were correlated with doses manually extracted from clinicians' visit notes (clinically noted HDDs). How well the pharmacy HDDs correlated with clinically noted HDDs was calculated (using C statistics). To facilitate interpretation, HDDs were described in association with the number of medications. Results: A total of 316 patients (99.1%) were male; the mean (SD) age was 75.6 (7.2) years. Pharmacy HDDs were highly correlated (r = 0.92) with clinically noted HDDs, with a mean (SD) of 2.7 (1.8) for pharmacy HDDs and 2.8 (1.8) for clinically noted HDDs. Pharmacy HDDs correlated with high-intensity, clinically noted HDDs ranging from a C statistic of 92.8% (95% CI, 92.0%-93.7%) for 2 or more clinically noted HDDs to 88.1% (95% CI, 85.5%-90.6%) for 6 or more clinically noted HDDs. Conclusions and Relevance: This study suggests that health system pharmacy data may be used to accurately quantify hypertension regimen dose intensity. Together with clinic-measured BP, this tool can be used in future health system-based research or quality improvement efforts to fine-tune, manage, and optimize hypertension treatment in older adults.

Validation of a Health System Measure to Capture Intensive Medication Treatment of Hypertension in the Veterans Health Administration.

Importance: Blood pressure (BP) targets are the main measure of high-quality hypertension care in health systems. However, BP alone does not reflect intensity of pharmacological treatment, which should be carefully managed in older patients. Objectives: To develop and validate an electronic health record (EHR) data-only algorithm using pharmacy and BP data to capture intensive hypertension care (IHC), defined as 3 or more BP medications and BP less than 120 mm Hg, and to identify conditions associated with greater IHC, either through greater algorithm false-positive IHC, or by contributing clinically to delivering more IHC. Design, Setting, and Participants: This cross-sectional study was conducted among 319 randomly selected patients aged 65 years or older receiving IHC from the Veterans Health Administration (VHA) from July 1, 2011, to June 30, 2013. Data were collected from a total of 3625 primary care visits. Data were analyzed from January 2017 to March 2020. Exposures: Calibration and measurement of the algorithm for IHC (algorithm IHC). Main Outcomes and Measures: For each primary care visit, the reference standard, clinical IHC, was determined by detailed review of free-text clinical notes. The correlation in BP medication count between the EHR-only algorithm vs the reference standard and the sensitivity and specificity of the algorithm IHC were calculated. In addition, presence vs absence of contributing conditions acting in combination with hypertension management were measured to examine incidence of IHC associated with contributing conditions, including an acute condition that lowered BP (eg, dehydration), another condition requiring a BP target lower than the standard 140 mm Hg (eg, diabetes), or the patient needing a BP-lowering medication for a nonhypertension condition (eg, ß-blocker for atrial fibrillation) resulting in low BP. Results: Among 319 patients with 3625 visits (mean [SD] age, 75.6 [7.2] years; 3592 [99.1%] men), 911 visits (25.1%) had clinical IHC by the reference standard. The algorithm for determining medication count was highly correlated with the reference standard (r = 0.84). Sensitivity of detecting clinical IHC was 92.2% (95% CI, 89.3%-95.1%), and specificity was 97.2% (95% CI, 96.1%-98.3%), suggesting that clinical IHC can be identified from routinely collected data. Only 75 visits (2.1%) were algorithm IHC false positives, 55 visits (1.5%) involved IHC with contributing conditions, and 125 visits (3.5%) involved either false-positive or IHC with contributing conditions. Among select contributing conditions, congestive heart failure (37 patients [5.2%]) was most associated with a prespecified combined false-positive or IHC with contributing conditions rate higher than 5%. Conclusions and Relevance: These findings suggest that health system data can be used reliably to estimate IHC.

The "State of Implementation" Progress Report (SIPREP): a pilot demonstration of a navigation system for implementation.

BACKGROUND: Implementation of new clinical programs across diverse facilities in national healthcare systems like the Veterans Health Administration (VHA) can be extraordinarily complex. Implementation is a dynamic process, influenced heavily by local organizational context and the individual staff at each medical center. It is not always clear in the midst of implementation what issues are most important to whom or how to address them. In recognition of these challenges, implementation researchers within VHA developed a new systemic approach to map the implementation work required at different stages and provide ongoing, detailed, and nuanced feedback about implementation progress. METHODS: This observational pilot demonstration project details how a novel approach to monitoring implementation progress was applied across two different national VHA initiatives. Stage-specific grids organized the implementation work into columns, rows, and cells, identifying specific implementation activities at the site level to be completed along with who was responsible for completing each implementation activity. As implementation advanced, item-level checkboxes were crossed off and cells changed colors, offering a visual representation of implementation progress within and across sites across the various stages of implementation. RESULTS: Applied across two different national initiatives, the SIPREP provided a novel navigation system to guide and inform ongoing implementation within and across facilities. The SIPREP addressed different needs of different audiences, both described and explained how to implement the program, made ample use of visualizations, and revealed both what was happening and not happening within and across sites. The final SIPREP product spanned distinct stages of implementation. CONCLUSIONS: The SIPREP made the work of implementation explicit at the facility level (i.e., who does what, and when) and provided a new common way for all stakeholders to monitor implementation progress and to help keep implementation moving forward. This approach could be adapted to a wide range of settings and interventions and is planned to be integrated into the national deployment of two additional VHA initiatives within the next 12 months.

Adverse events among high-risk participants in a home-based walking study: a descriptive study.

BACKGROUND: For high-risk individuals and their healthcare providers, finding the right balance between promoting physical activity and minimizing the risk of adverse events can be difficult. More information on the prevalence and influence of adverse events is needed to improve providers' ability to prescribe effective and safe exercise programs for their patients. METHODS: This study describes the type and severity of adverse events reported by participants with cardiovascular disease or at-risk for cardiovascular disease that occurred during an unsupervised, home-based walking study. This multi-site, randomized controlled trial tested the feasibility of a diet and lifestyle activity intervention over 1.5 years. At month 13, 274 eligible participants (male veterans) were recruited who were ambulatory, BMI > 28, and reporting one or more cardiovascular disease risk factors. All participants attended five, face-to-face dietitian-delivered counseling sessions during the six-month intervention. Participants were randomized to three study arms: 1) time-based walking goals, 2) simple pedometer-based walking goals, and 3) enhanced pedometer-based walking goals with Internet-mediated feedback. Two physicians verified adverse event symptom coding. RESULTS: Enrolled participants had an average of five medical comorbidities. During 1110 person months of observation, 87 of 274 participants reported 121 adverse events. One serious study-related adverse event (atrial fibrillation) was reported; the individual resumed study participation within three days. Non-serious, study related adverse events made up 12% of all symptoms - predominantly minor musculoskeletal events. Serious, non-study related adverse events represented 32% of all symptoms while non-serious, non-study related adverse events made up 56% of symptoms. Cardiovascular disease events represented over half of the non-study related adverse event symptoms followed by musculoskeletal complaints. Adverse events caused 50 temporary suspensions averaging 26 days in duration before physician medical clearance was obtained to resume walking. CONCLUSION: Men at high risk for adverse cardiovascular events can safely be advised to start a progressive walking program. Results suggest that minor to serious medical problems unrelated to exercise are a major barrier to walking adherence. Helping individuals with chronic illness return to physical activity quickly but safely after an adverse event is an important component of any physical activity intervention targeting this population.

A Comparative Effectiveness Trial of Three Walking Self-monitoring Strategies.

PURPOSE: Walking programs improve health outcomes in adults at risk for cardiovascular disease and self-monitoring strategies can improve adherence to such programs. The objective of this study was to determine if a six-month internet-based walking program using web-enhanced pedometers results in more weight loss than walking programs based on time or simple pedometer-step count goals in adults with or at risk for cardiovascular disease (CVD). METHODS: This was a multi-site, randomized controlled trial of 255 male Veterans who were ambulatory, insufficiently active, BMI ≥ 28, and who reported 1 ≥ CVD risk factors. Participants were randomized to one of three self-monitoring strategies to increase walking: (1) time-based walking goals; (2) simple pedometer-based walking goals; and (3) web-enhanced pedometer feedback goals with Internet-mediated feedback. All participants also attended five individual weight loss sessions with a dietitian. The main outcome measure was change in weight at six months (kg) and secondary outcomes were change in accelerometer-measured physical activity (min) and change in health-related quality of life at six months. RESULTS: The 255 participants had a mean age of 56.3 years (SD = 10.0), BMI=36.3 (SD = 5.3) with a mean of 5.2 (SD = 2.3) medical comorbidities. Dropouts were distributed evenly across the three groups and 72% of participants completed the program. At six months, participants in the web-enhanced pedometer arm lost significantly more weight (-1.9 kg, 95% CI=-2.7, -1.1) than those in the time-based group (-0.7 kg, 95% CI=-1.5, 0.0; p = 0.04) and simple pedometer group (-0.6 kg, 95% CI=-1.4, 0.2; p = 0.02). CONCLUSION: Internet-enhanced pedometers result in greater weight loss in Veterans than walking programs using time-based walking goals or simple pedometers.

Evaluation of a nurse practitioner disease management model for chronic heart failure: a multi-site implementation study.

While disease management appears to be effective in selected, small groups of CHF patients from randomized controlled trials, its effectiveness in a broader CHF patient population is not known. This prospective, quasi-experimental study compared patient outcomes under a nurse practitioner-led disease management model (intervention group) with outcomes under usual care (control group) in both primary and tertiary medical centers. The study included 969 veterans (458 intervention, 511 control) treated for CHF at six VA medical centers. Intervention patients had significantly fewer (p<0.05) CHF and all-cause admissions at one-year follow-up, and lower mortality at both one- and two-year follow-up. These data provide support for the potential effectiveness of the intervention, and suggest that the evidence from RCTs of disease management models for CHF can be translated into clinical practice, even without the benefits of a selected patient population and dedicated resources often found in RCTs.