scholarly journals Novel Methodology to Measure Preprocedure Antimicrobial Prophylaxis: Integrating Text Mining With Structured Data

2020 ◽  
Vol 41 (S1) ◽  
pp. s12-s13
Author(s):  
Hillary Mull ◽  
Kelly Stolzmann ◽  
Emily Kalver ◽  
Marlena Shin ◽  
Marin Schweizer ◽  
...  
Keyword(s):  
Antimicrobial Prophylaxis ◽  
High Sensitivity ◽  
Structured Data ◽  
Fiscal Year ◽  
Veterans Health ◽  
Health Administration ◽  
Implementation Barriers ◽  
Cardiac Device ◽  
Device Infection ◽  
Manual Review

Background: Antimicrobial prophylaxis is an evidence-proven strategy for reducing procedure-related infections; however, measuring this key quality metric typically requires manual review, due to the way antimicrobial prophylaxis is documented in the electronic medical record (EMR). Our objective was to combine structured and unstructured data from the Veterans’ Health Administration (VA) EMR to create an electronic tool for measuring preincisional antimicrobial prophylaxis. We assessed this methodology in cardiac device implantation procedures. Methods: With clinician input and review of clinical guidelines, we developed a list of antimicrobial names recommended for the prevention of cardiac device infection. Next, we iteratively combined positive flags for an antimicrobial order or drug fill from structured data fields in the EMR and hits on text string searches of antimicrobial names documented in electronic clinical notes to optimize an algorithm to flag preincisional antimicrobial use with high sensitivity and specificity. We trained the algorithm using existing fiscal year (FY) 2008-15 data from the VA Clinical Assessment Reporting and Tracking-Electrophysiology (CART-EP), which contains manually determined information about antimicrobial prophylaxis. We then validated the performance of the final version of the algorithm using a national cohort of VA patients who underwent cardiac device procedures in FY 2016 or 2017. Discordant cases underwent expert manual review to identify reasons for algorithm misclassification and to identify potential future implementation barriers. Results: The CART-EP dataset included 2,102 procedures at 38 VA facilities with manually identified antimicrobial prophylaxis in 2,056 cases (97.8%). The final algorithm combining structured EMR fields and text-note search results flagged 2,048 of the CART-EP cases (97.4%). Algorithm validation identified antimicrobial prophylaxis in 16,334 of 19,212 cardiac device procedures (87.9%). Misclassifications occurred due to EMR documentation issues. Conclusions: We developed a methodology with high accuracy to measure guideline-concordant use of antimicrobial prophylaxis before cardiac device procedures using data fields present in modern EMRs that does not rely on manual review. In addition to broad applicability in the VA and other healthcare systems with EMRs, this method could be adapted for other procedural areas in which antimicrobial prophylaxis is recommended but comprehensive measurement has been limited to resource-intense manual review.Funding: NoneDisclosures: None

scholarly journals Associations between stopping prescriptions for opioids, length of opioid treatment, and overdose or suicide deaths in US veterans: observational evaluation

BMJ ◽  
2020 ◽  
pp. m283 ◽  
Author(s):  
Elizabeth M Oliva ◽  
Thomas Bowe ◽  
Ajay Manhapra ◽  
Stefan Kertesz ◽  
Jennifer M Hah ◽  
...  
Keyword(s):  
Opioid Analgesic ◽  
Veterans Health Administration ◽  
Fiscal Year ◽  
Veterans Health ◽  
Health Administration ◽  
Opioid Treatment ◽  
Risk Of Death ◽  
Length Of Treatment ◽  
Increased Risk ◽  
Stopping Treatment

Abstract Objective To examine the associations between stopping treatment with opioids, length of treatment, and death from overdose or suicide in the Veterans Health Administration. Design Observational evaluation. Setting Veterans Health Administration. Participants 1 394 102 patients in the Veterans Health Administration with an outpatient prescription for an opioid analgesic from fiscal year 2013 to the end of fiscal year 2014 (1 October 2012 to 30 September 2014). Main outcome measures A multivariable Cox non-proportional hazards regression model examined death from overdose or suicide, with the interaction of time varying opioid cessation by length of treatment (≤30, 31-90, 91-400, and >400 days) as the main covariates. Stopping treatment with opioids was measured as the time when a patient was estimated to have no prescription for opioids, up to the end of the next fiscal year (2014) or the patient’s death. Results 2887 deaths from overdose or suicide were found. The incidence of stopping opioid treatment was 57.4% (n = 799 668) overall, and based on length of opioid treatment was 32.0% (≤30 days), 8.7% (31-90 days), 22.7% (91-400 days), and 36.6% (>400 days). The interaction between stopping treatment with opioids and length of treatment was significant (P<0.001); stopping treatment was associated with an increased risk of death from overdose or suicide regardless of the length of treatment, with the risk increasing the longer patients were treated. Hazard ratios for patients who stopped opioid treatment (with reference values for all other covariates) were 1.67 (≤30 days), 2.80 (31-90 days), 3.95 (91-400 days), and 6.77 (>400 days). Descriptive life table data suggested that death rates for overdose or suicide increased immediately after starting or stopping treatment with opioids, with the incidence decreasing over about three to 12 months. Conclusions Patients were at greater risk of death from overdose or suicide after stopping opioid treatment, with an increase in the risk the longer patients had been treated before stopping. Descriptive data suggested that starting treatment with opioids was also a risk period. Strategies to mitigate the risk in these periods are not currently a focus of guidelines for long term use of opioids. The associations observed cannot be assumed to be causal; the context in which opioid prescriptions were started and stopped might contribute to risk and was not investigated. Safer prescribing of opioids should take a broader view on patient safety and mitigate the risk from the patient’s perspective. Factors to address are those that place patients at risk for overdose or suicide after beginning and stopping opioid treatment, especially in the first three months.

Opioid use disorder and homelessness in the Veterans Health Administration: The challenge of multimorbidity

2018 ◽  
Vol 14 (3) ◽  
pp. 171-182 ◽  
Author(s):  
Theddeus Iheanacho, MD ◽  
Elina Stefanovics, PhD ◽  
Robert Rosenheck, MD
Keyword(s):  
Risk Factor ◽  
Service Use ◽  
Veterans Health Administration ◽  
Opioid Use Disorder ◽  
Fiscal Year ◽  
Veterans Health ◽  
Health Administration ◽  
Opioid Use ◽  
Agonist Therapy ◽  
Homeless Veterans

Objective: The aim of this study is to estimate the prevalence and sociodemographic and clinical correlates of opioid use disorder (OUD), a major cause of morbidity and mortality in the United States, among homeless veterans nationally in the Veterans Health Administration (VHA).Design: Administrative data on 256,404 veterans who were homeless and/or had OUD in fiscal year 2012 were analyzed to evaluate OUD as a risk factor for homelessness along with associated characteristics, comorbidities, and patterns of service use. Bivariate analyses and logistic regression were used to compare homeless veterans with OUD to veterans with OUD but no homelessness and homeless veterans with no OUD.Results: Altogether 17.9 percent of homeless VHA users were diagnosed with OUD and 34.6 percent of veterans with OUD were homeless. The risk ratio (RR) for homelessness among veterans with OUD was 28.7. Homeless veterans with OUD, compared to nonhomeless veterans with OUD showed extensive multimorbidity with greater risk for HIV (RR = 1.57), schizophrenia (RR = 1.62), alcohol use disorder (RR = 1.67), and others. Homeless veterans with OUD also showed more multimorbidity and used more services than homeless veterans without OUD. Homeless and nonhomeless OUD veterans used opiate agonist therapy at similar, but very low rates (13 and 15 percent).Conclusions: OUD is a major risk factor for homelessness. Homeless veterans with OUD have high levels of multimorbidity and greater service use than veterans with either condition alone. Tailored, facilitated access to opioid agonist therapy may improve outcomes for these vulnerable veterans.

scholarly journals Estimating the Cost of Surgical Care Purchased in the Community by the Veterans Health Administration

2021 ◽  
Vol 6 (2) ◽  
pp. 238146832110579
Author(s):  
Todd H. Wagner ◽  
Jeanie Lo ◽  
Erin Beilstein-Wedel ◽  
Megan E. Vanneman ◽  
Michael Shwartz ◽  
...  
Keyword(s):  
Average Cost ◽  
Surgical Care ◽  
Risk Scores ◽  
Fiscal Year ◽  
Veterans Health ◽  
Health Administration ◽  
Complex Patients ◽  
Risk Patients ◽  
Community Providers ◽  
The Cost

Background. Veterans’ access to Veterans Affairs (VA)-purchased community care expanded due to large increases in funding provided in the 2014 Veterans Choice Act. Objectives. To compare costs between VA-delivered care and VA payments for purchased care for two commonly performed surgeries: total knee arthroplasties (TKAs) and cataract surgeries. Research Design. Descriptive statistics and regressions examining costs in VA-delivered and VA-purchased care (fiscal year [FY] 2018 [October 2017 to September 2018]). Subjects. A total of 13,718 TKAs, of which 6,293 (46%) were performed in VA. A total of 91,659 cataract surgeries, of which 65,799 (72%) were performed in VA. Measures. Costs of VA-delivered care based on activity-based cost estimates; costs of VA-purchased care based on approved and paid claims. Results. Ninety-eight percent of VA-delivered TKAs occurred in inpatient hospitals, with an average cost of $28,969 (SD $10,778). The majority (86%) of VA-purchased TKAs were also performed at inpatient hospitals, with an average payment of $13,339 (SD $23,698). VA-delivered cataract surgeries were performed at hospitals as outpatient procedures, with an average cost of $4,301 (SD $2,835). VA-purchased cataract surgeries performed at hospitals averaged $1,585 (SD $629); those performed at ambulatory surgical centers cost an average of $1,346 (SD $463). We also found significantly higher Nosos risk scores for patients who used VA-delivered versus VA-purchased care. Conclusions. Costs of VA-delivered care were higher than payments for VA-purchased care, but this partly reflects legislative caps limiting VA payments to community providers to Medicare amounts. Higher patient risk scores in the VA could indicate that community providers are reluctant to accept high-risk patients because of Medicare reimbursements, or that VA providers prefer to keep the more complex patients in VA.

scholarly journals Legionella in the veterans healthcare system: report of an eight-year survey

2003 ◽  
Vol 131 (2) ◽  
pp. 835-839 ◽  
Author(s):  
A. A. KELLY ◽  
L. H. DANKO ◽  
S. M. KRALOVIC ◽  
L. A. SIMBARTL ◽  
G. A. ROSELLE
Keyword(s):  
Healthcare System ◽  
Positive Outcome ◽  
The United States ◽  
Veterans Affairs ◽  
Outpatient Clinics ◽  
Fiscal Year ◽  
Veterans Health ◽  
Department Of Veterans Affairs ◽  
Health Administration ◽  
Healthcare Associated

The Veterans Health Administration (VHA) of the Department of Veterans Affairs tracks legionella disease in the system of 172 medical centres and additional outpatient clinics using an annual census for reporting. In fiscal year 1999, 3·62 million persons were served by the VHA. From fiscal year 1989–1999, multiple intense interventions were carried out to decrease the number of cases and case rates for legionella disease. From fiscal year 1992–1999, the number of community-acquired and healthcare-associated cases decreased in the VHA by 77 and 95·5% respectively (P=0·005 and 0·01). Case rates also decreased significantly for community and healthcare-associated cases (P=0·02 and 0·001, respectively), with the VHA healthcare-associated case rates decreasing at a greater rate than VHA community-acquired case rates (P=0·02). Over the time of the review, the VHA case rates demonstrated a greater decrease compared to the case rates for the United States as a whole (P=0·02). Continued surveillance, centrally defined strategies, and local implementation can have a positive outcome for prevention of disease in a large, decentralized healthcare system.

The shift in therapies for the treatment of chronic lymphocytic leukemia (CLL) patients in the US Veterans Health Administration (VHA) from 2013-2018.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e19339-e19339
Author(s):  
Zohra Nooruddin ◽  
Hannah Le ◽  
Daniel McHugh ◽  
Kellie Ryan ◽  
Xavier Jones ◽  
...  
Keyword(s):  
B Cell Lymphoma ◽  
Lymphocytic Leukemia ◽  
Agent Orange ◽  
Novel Agents ◽  
Fiscal Year ◽  
Veterans Health ◽  
Health Administration ◽  
Secondary Complications ◽  
The Impact ◽  
Novel Agent

e19339 Background: The first novel agent for use in CLL was approved in 2014; however, the extent of novel agent uptake in the VHA is largely unknown. Objective: This study described the pharmacoepidemiology of three novel agents (ibrutinib, idelalisib, venetoclax), and traditional chemotherapies/chemoimmunotherapies (CT/CIT) in the VHA. Methods: This was a retrospective study of 26,879 adults with CLL in the VHA from 10/01/2013 to 5/31/2018. All were followed for at least 6 months. Data were extracted from the VHA electronic health record. Patients came from all 18 Veterans Integrated Service Networks, spanning all 50 states and US territories. Descriptive statistics were used to summarize baseline characteristics, CLL treatments, next therapies, and secondary complications. Results: A total of 3670 patients received at least one of 12 CLL therapies of interest. Patients had a median age of 69 years (47% were 65+ and 26% were 75+), a median age-adjusted Charlson comorbidity score of 6, and 6% had a history of exposure to Agent Orange. Ibrutinib accounted for 89% of the novel agent use. Ibrutinib use across all lines of therapy (LOTs) increased sevenfold over the study period (Table). Venetoclax (42%) and idelalisib (30%) were the most common therapies for the next LOT after ibrutinib. Across all LOTs, traditional CT/CIT use declined steadily over the study period. However, in fiscal year (FY) 2018, there were still 17% of patients receiving CT/CIT. Ibrutinib was the most common therapy for the next LOT in these patients (43–74%). Incidence of diffuse large B cell lymphoma post-index was 2–6 times higher in patients on CT/CIT than those on ibrutinib. Other secondary complications were similar between ibrutinib and CT/CIT. Conclusions: To our knowledge, this is the largest study looking at CLL treatment patterns among VHA patients in the real world. There has been a major shift in the treatment of CLL, with fast adoption of novel agents in the VHA from 2013 to 2018. The impact of this shift on healthcare resource use and cost burden in the VHA will need to be examined. [Table: see text]

scholarly journals Review of purchases of unapproved medications by the Veterans Health Administration

2019 ◽  
Vol 76 (23) ◽  
pp. 1934-1943 ◽  
Author(s):  
Ron L Carico ◽  
Thomas R Emmendorfer ◽  
Sherrie L Aspinall ◽  
Margaret T Mizah ◽  
Chester B Good
Keyword(s):  
Pharmaceutical Expenditure ◽  
Sodium Hyaluronate ◽  
Active Pharmaceutical Ingredient ◽  
Veterans Health Administration ◽  
The United States ◽  
Fiscal Year ◽  
Veterans Health ◽  
Health Administration ◽  
Safety And Efficacy ◽  
Usage Patterns

Abstract Purpose Many medications that were marketed prior to 1962 but lack Food and Drug Administration (FDA) approval are prescribed in the United States. Usage patterns of these “unapproved medications” are poorly elucidated, which is concerning due to potential lack of data on safety and efficacy. The purpose of this project was to characterize purchases of unapproved medications within the Veterans Health Administration (VHA) by type, frequency, and cost. Methods VHA purchasing databases were used to create a list of all products with National Drug Codes (NDCs) purchased nationwide in fiscal year 2016 (FY16). This list was compared to FDA databases to identify unapproved prescription medications. For each identified combination of active pharmaceutical ingredient (API) and route of administration (“API/route combination”), numbers of packages purchased and associated costs were added. Results VHA pharmacy purchasing records contained 3,299 unapproved products with NDCs in FY16. After excluding equipment, nutrition products, compounding ingredients, nonmedication products, and duplicate NDCs, there were 600 unique NDCs associated with 130 distinct API/route combinations. The most commonly acquired product was prescription sodium fluoride dental paste (350,775 packages). The greatest pharmaceutical expenditure was for sodium hyaluronate injection ($24.5 million). Unapproved products accounted for less than 1% of overall VHA pharmacy purchasing in FY16. Conclusion VHA purchased many unapproved prescription products in FY16 but is taking action to address use of such products in consideration of safety and efficacy data and available alternatives.

scholarly journals A modified collaborative model to improve surgical flow health care processes in Veterans Affairs Medical Centers

2017 ◽  
Vol 3 (2) ◽  
pp. 47 ◽  
Author(s):  
Balmatee Bidassie ◽  
William Gunnar ◽  
Leigh Starr ◽  
George Van Buskirk ◽  
Lisa J Warner ◽  
...  
Keyword(s):  
Process Improvement ◽  
Systems Engineering ◽  
Performance Outcomes ◽  
Veterans Affairs ◽  
Fiscal Year ◽  
Veterans Health ◽  
Health Administration ◽  
Improve Performance ◽  
Collaborative Model ◽  
First Case

The Veterans Health Administration (VHA) Office of Systems Redesign and Improvement, in collaboration with the VHA National Surgery Office and Veterans Affairs Center for Applied Systems Engineering (VA-CASE) - Veterans Engineering Resource Center (VERC), conducted a national process improvement initiative in Fiscal Year 2012 to promote more effective and efficient use of surgical unit resources. This improvement effort adopted a modified collaborative model with the incorporation of symposia and Rapid Process Improvement Workshops (RPIWs) to address concerns from collaborative teams for a more efficient surgical flow. Throughout the seven-month duration of the initiative, 20 teams participated and completed a total of 468 Plan-Do-Study-Act (PDSA) cycles to implement changes and improve performance levels in defined measures. At the conclusion, on average, teams were able to improve performance on the first case on-time start rate by 24%, mean turnover time by 14%, cancellation rate by 5%, and Operating Room (OR) utilization by 8%. The projected annual Cost Savings was estimated to be nearly $25 million. This modified improvement model overcame some of the challenges experienced in a traditional improvement collaborative model such as lack of clarity of clear roles and responsibilities of team members and clear and consistent aims. The operations in surgical flow were improved in multiple ways to achieve overall better performance. Future improvement initiatives have the potential to further enhance performance outcomes by focusing even more efforts on the preparation phase, increasing team participation and leadership buy-in, utilizing on-going reports that track team progress and focusing on sustain and spread.

scholarly journals Validity of Veterans Health Administration structured data to determine accurate smoking status

2019 ◽  
Vol 26 (3) ◽  
pp. 1507-1515 ◽  
Author(s):  
Sara E Golden ◽  
Elizabeth R Hooker ◽  
Sarah Shull ◽  
Matthew Howard ◽  
Kristina Crothers ◽  
...  
Keyword(s):  
Smoking Status ◽  
Kappa Statistic ◽  
Veterans Health Administration ◽  
Structured Data ◽  
Future Research ◽  
Kappa Statistics ◽  
Veterans Health ◽  
Health Administration ◽  
Text Data ◽  
Total Agreement

We compared smoking status from Veterans Health Administration (VHA) structured data with text in electronic health record (EHR) to assess validity. We manually abstracted the smoking status of 5,610 VHA patients. Only those with a smoking status found in both EHR text data and VHA structured data were included (n=5,289). We calculated agreement and kappa statistics to compare structured data vs. manually abstracted EHR text smoking status. We found a kappa statistic of 0.70 and total agreement of 81.1% between EHR text data and structured data for Current, Former, and Never smoking categories. Comparing EHR text data and structured data between Never and Ever smokers revealed a kappa statistic of 0.62 and total agreement of 89.1%. For comparison between Current and Never/Former smokers, the kappa statistic was 0.80 and total agreement was 90.2%. We found substantial and significant agreement between smoking status in EHR text data and structured data that may aid in future research.

scholarly journals Development of an Electronic Tool to Measure Daily Appropriateness of Inpatient Antibacterial Use

2020 ◽  
Vol 41 (S1) ◽  
pp. s2-s2
Author(s):  
Vanessa Stevens ◽  
Pamela Belperio ◽  
Melinda Neuhauser ◽  
Lauri Hicks ◽  
McKenna Nevers ◽  
...  
Keyword(s):  
Risk Factors ◽  
Chart Review ◽  
Signs And Symptoms ◽  
Veterans Health ◽  
Health Administration ◽  
Electronic Health Record Data ◽  
Electronic Tool ◽  
Electronic Health ◽  
Facility Level ◽  
Manual Review

Background: Assessing antimicrobial use (AU) appropriateness isa cornerstone of antimicrobial stewardship, largely accomplished through time-intensive manual chart review of specific agents or diagnoses. Efforts to evaluate appropriateness have focused on assessing the appropriateness of an entire treatment course. An electronic measure was developed to assess the appropriateness of each day of inpatient AU leveraging electronic health record data. Methods: We extracted contextual data, including risk factors for resistant organisms, allergies, constitutional signs and symptoms from diagnostic and procedural codes, and microbiological findings, from the electronic health records of patients in Veterans’ Health Administration inpatient wards reporting data to the National Healthcare Safety Network (NHSN) AU option from 2017–2018. Only the antibacterial categories shown in Figure 1 were included. Respiratory, urinary tract, skin and soft-tissue, and other infection categories were defined and applied to each hospital day. Algorithm rules were constructed to evaluate AU based on the clinical context (eg, in the ICU, during empiric therapy, drug–pathogen match, recommended drugs, and duration). Rules were drawn from available literature, were discussed with experts, and were then refined empirically. Generally, the rules allowed for use of first-line agents unless risk factors or contraindications were identified. AU was categorized as appropriate, inappropriate, or indeterminate for each day, then aggregated into an overall measure of facility-level AU appropriateness. A validation set of 20 charts were randomly selected for manual review. Results: Facility distribution of appropriateness, inappropriateness, and indeterminate AU by 4 of the adult, 2017 baseline NHSN Standardized Antimicrobial Administration Ratio (SAAR) categories are shown in Figure 1. The median facility-level inappropriateness across all SAAR categories was 37.2% (IQR, 29.4%–52.5%). The median facility-level indeterminate AU across all SAAR categories was 14.4% (IQR, 9.1%–21.2%). Chart review of 20 admissions showed agreement with algorithm appropriateness and inappropriateness in 95.4% of 240 antibacterial days.Conclusions: We developed a comprehensive, flexible electronic tool to evaluate AU appropriateness for combinations of setting, antibacterial agent, syndrome, or time frame of interest (eg, empiric, definitive, or excess duration). Application of our algorithm in 2 years of VA acute-care data suggest substantial interfacility variability; the highest rates of inappropriateness were for anti-MRSA therapy. Our preliminary chart review demonstrated agreement between electronic and manual review in >95% of antimicrobial days. This approach may be useful to identify potential stewardship targets, in the development of decision support systems, and in conjunction with other metrics to track AU over time.Funding: NoneDisclosures: None

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