Marjorie E. Carter

Psychometric assessment of the patient activation measure short form (PAM-13) in rural settings

PurposeThe patient activation measure short form (PAM-13) assesses patients’ self-reported health management skills, knowledge, confidence, and motivation. We used item response theory to evaluate the psychometric properties of the PAM-13 utilized in rural settings.MethodsA Rasch partial credit model analysis was conducted on the PAM-13 instrument using a sample of 812 rural patients recruited by providers and our research staff. Specially, we examined dimensionality, item fit, and quality of measures, category response curves, and item differential functioning. Convergent and divergent validities were also examined.FindingsThe PAM-13 instrument has excellent convergent and divergent validities. It is fairly unidimensional, and all items fit the Rasch model well. It has relatively high person and item reliability indices. Majority of the items were free of item differential functioning. There were, however, some issues with ceiling effects. Additionally, there was a lack of responses for category one across all items.ConclusionsPatient activation measure short form (PAM-13) performs well in some areas, but not all. In general, more items need to be added to cover the upper end of the trait. The four response categories of PAM-13 should be collapsed into three.

NON-INVASIVE SAMPLE COLLECTION FOR RESPIRATORY VIRUS TESTING BY MULTIPLEX PCR

Abstract Background Identifying respiratory pathogens within populations is difficult because invasive sample collection, such as with nasopharyngeal aspirate (NPA), is generally required. PCR technology could allow for non-invasive sampling methods. Objective Evaluate the utility of non-invasive sample collection using anterior nare swabs and facial tissues for respiratory virus detection by multiplex PCR. Study design Children aged 1 month–17 years evaluated in a pediatric emergency department for respiratory symptoms had a swab, facial tissue, and NPA sample collected. All samples were tested for respiratory viruses by multiplex PCR. Viral detection rates were calculated for each collection method. Sensitivity and specificity of swabs and facial tissues were calculated using NPA as the gold standard. Results 285 samples from 95 children were evaluated (92 swab-NPA pairs, 91 facial tissue-NPA pairs). 91% of NPA, 82% of swab, and 77% of tissue samples were positive for ≥1 virus. Respiratory syncytial virus (RSV) and human rhinovirus (HRV) were most common. Overall, swabs were positive for 74% of virus infections, and facial tissues were positive for 58%. Sensitivity ranged from 17 to 94% for swabs and 33 to 84% for tissues. Sensitivity was highest for RSV (94% swabs and 84% tissues). Specificity was ≥95% for all viruses except HRV for both collection methods. Conclusions Sensitivity of anterior nare swabs and facial tissues in the detection of respiratory viruses by multiplex PCR varied by virus type. Given its simplicity and specificity, non-invasive sampling for PCR testing may be useful for conducting epidemiologic or surveillance studies in settings where invasive testing is impractical or not feasible.

Identifying homelessness among veterans using VA administrative data: Opportunities to expand detection criteria

Researchers at the U.S. Department of Veterans Affairs (VA) have used administrative criteria to identify homelessness among U.S. Veterans. Our objective was to explore the use of these codes in VA health care facilities. We examined VA health records (2002-2012) of Veterans recently separated from the military and identified as homeless using VA conventional identification criteria (ICD-9-CM code V60.0, VA specific codes for homeless services), plus closely allied V60 codes indicating housing instability. Logistic regression analyses examined differences between Veterans who received these codes. Health care services and co-morbidities were analyzed in the 90 days post-identification of homelessness. VA conventional criteria identified 21,021 homeless Veterans from Operations Enduring Freedom, Iraqi Freedom, and New Dawn (rate 2.5%). Adding allied V60 codes increased that to 31,260 (rate 3.3%). While certain demographic differences were noted, Veterans identified as homeless using conventional or allied codes were similar with regards to utilization of homeless, mental health, and substance abuse services, as well as co-morbidities. Differences were noted in the pattern of usage of homelessness-related diagnostic codes in VA facilities nation-wide. Creating an official VA case definition for homelessness, which would include additional ICD-9-CM and other administrative codes for VA homeless services, would likely allow improved identification of homeless and at-risk Veterans. This also presents an opportunity for encouraging uniformity in applying these codes in VA facilities nationwide as well as in other large health care organizations.

Military Misconduct and Homelessness Among US Veterans Separated From Active Duty, 2001-2012.

Military Misconduct and Homelessness Among US Veterans Separated From Active Duty, 2001-2012 Misconduct-related separations from the military are associated with subsequent adverse civilian outcomes that are of substantial public health concern.1 We investigated the association between misconduct-related separations and homelessness among recently returned active-duty military service members.

Differential Risk for Homelessness Among US Male and Female Veterans With a Positive Screen for Military Sexual Trauma

IMPORTANCE Military sexual trauma (MST) is associated with adverse physical and mental health outcomes following military separation. Recent research suggests that MST may be a determinant in several factors associated with postdeployment homelessness. OBJECTIVE To evaluate MST as an independent risk factor for homelessness and to determine whether risk varies by sex. DESIGN, SETTING, AND PARTICIPANTS A retrospective cohort study of US veterans who used Veterans Health Administration (VHA) services between fiscal years 2004 and 2013 was conducted using administrative data from the Department of Defense and VHA. Included in the study were 601 892 US veterans deployed in Iraq or Afghanistan who separated from the military between fiscal years 2001 and 2011 and subsequently used VHA services. EXPOSURE Positive response to screen for MST administered in VHA facilities. MAIN OUTCOMES AND MEASURES Administrative evidence of homelessness within 30 days, 1 year, and 5 years following the first VHA encounter after last deployment. RESULTS The mean (SD) age of the 601 892 participants was 38.9 (9.4) years, 527 874 (87.7%) were male, 310 854 (51.6%) were white, and 382 361 (63.5%) were enlisted in the Army. Among veterans with a positive screen for MST, rates of homelessness were 1.6% within 30 days, 4.4% within 1 year, and 9.6% within 5 years, more than double the rates of veterans with a negative MST screen (0.7%, 1.8%, and 4.3%, respectively). A positive screen for MST was significantly and independently associated with postdeployment homelessness. In regression models adjusted for demographic and military service characteristics, odds of experiencing homelessness were higher among those who screened positive for MST compared with those who screened negative (30-day: adjusted odds ratio [AOR], 1.89; 95% CI, 1.58-2.24; 1-year: AOR, 2.27; 95% CI, 2.04-2.53; and 5-year: AOR, 2.63; 95% CI, 2.36-2.93). Military sexual trauma screen status remained independently associated with homelessness after adjusting for co-occurring mental health and substance abuse diagnoses in follow-up regression models (30-day: AOR, 1.62; 95% CI, 1.36-1.93; 1-year: AOR, 1.49; 95% CI, 1.33-1.66; and 5-year: AOR, 1.39; 95% CI, 1.24-1.55). In the fully adjusted models, the interaction between MST status and sex was significant in the 30-day and 1-year cohorts (30-day: AOR, 1.54; 95% CI, 1.18-2.02; and 1-year: AOR, 1.46; 95% CI, 1.23-1.74), denoting higher risk for homelessness among males with a positive screen for MST. CONCLUSIONS AND RELEVANCE A positive screen for MST was independently associated with postdeployment homelessness, with male veterans at greater risk than female veterans. These results underscore the importance of the MST screen as a clinically important marker of reintegration outcomes among veterans. These findings demonstrate significant long-term negative effects and inform our understanding of the public health implications of sexual abuse and harassment.

Validating a strategy for psychosocial phenotyping using a large corpus of clinical text

OBJECTIVE To develop algorithms to improve efficiency of patient phenotyping using natural language processing (NLP) on text data. Of a large number of note titles available in our database, we sought to determine those with highest yield and precision for psychosocial concepts. MATERIALS AND METHODS From a database of over 1 billion documents from US Department of Veterans Affairs medical facilities, a random sample of 1500 documents from each of 218 enterprise note titles were chosen. Psychosocial concepts were extracted using a UIMA-AS-based NLP pipeline (v3NLP), using a lexicon of relevant concepts with negation and template format annotators. Human reviewers evaluated a subset of documents for false positives and sensitivity. High-yield documents were identified by hit rate and precision. Reasons for false positivity were characterized. RESULTS A total of 58 707 psychosocial concepts were identified from 316 355 documents for an overall hit rate of 0.2 concepts per document (median 0.1, range 1.6-0). Of 6031 concepts reviewed from a high-yield set of note titles, the overall precision for all concept categories was 80%, with variability among note titles and concept categories. Reasons for false positivity included templating, negation, context, and alternate meaning of words. The sensitivity of the NLP system was noted to be 49% (95% CI 43% to 55%). CONCLUSIONS Phenotyping using NLP need not involve the entire document corpus. Our methods offer a generalizable strategy for scaling NLP pipelines to large free text corpora with complex linguistic annotations in attempts to identify patients of a certain phenotype.

Non-routine Discharge From Military Service: Mental Illness, Substance Use Disorders, and Suicidality

INTRODUCTION Mental illness and substance use disorders among newly returned military service members pose challenges to successful reintegration into civilian life and, in extreme cases, may lead to outcomes such as incarceration, homelessness, and suicide. One potential early indicator for these difficulties is non-routine discharge from military service. METHODS Using data from the Veterans Health Administration (VHA) for 443,360 active duty service Veterans who deployed to Afghanistan and Iraq and subsequently utilized VHA services between Fiscal Years 2004 and 2013, this study examined risk for receiving a VHA-documented diagnosis of mental illness, substance use disorders, and suicidality as a function of discharge type, controlling for demographic and military service covariates. Analyses were conducted in 2016. RESULTS In total, 126,314 Veterans (28.5%) had a non-routine military service discharge. Compared with routinely discharged Veterans, odds for nearly all diagnostic outcomes were significantly greater among Veterans discharged for disqualification or misconduct, including personality disorders (AOR=9.21 and 3.29, respectively); bipolar/psychotic disorders (AOR=3.98 and 3.40); alcohol/substance use disorders (AOR=1.55 and 4.42); and suicidal ideation and behaviors (AOR=2.81 and 2.77). Disability-discharged Veterans had significantly higher odds for diagnoses of anxiety disorders (AOR=1.97) and bipolar/psychotic disorders (AOR=3.93). CONCLUSIONS Non-routine service discharge strongly predicts VHA-diagnosed mental illness, substance use disorders, and suicidality, with particularly elevated risk among Veterans discharged for disqualification or misconduct. Results emphasize the importance of discharge type as an early marker of adverse post-discharge outcomes, and suggest a need for targeted prevention and intervention efforts to improve reintegration outcomes among this vulnerable subpopulation.

Correlates of Initiation of Treatment for Chronic Hepatitis C Infection in United States Veterans, 2004–2009

We describe the rates and predictors of initiation of treatment for chronic hepatitis C (HCV) infection in a large cohort of HCV positive Veterans seen in U.S. Department of Veterans Affairs (VA) facilities between January 1, 2004 and December 31, 2009. In addition, we identify the relationship between homelessness among these Veterans and treatment initiation. Univariate and multivariable Cox Proportional Hazards regression models with time-varying covariates were used to identify predictors of initiation of treatment with pegylated interferon alpha plus ribavirin. Of the 101,444 HCV treatment-naïve Veterans during the study period, rates of initiation of treatment among homeless and non-homeless Veterans with HCV were low and clinically similar (6.2% vs. 7.4%, p<0.0001). For all U.S. Veterans, being diagnosed with genotype 2 or 3, black or other/unknown race, having Medicare or other insurance increased the risk of treatment. Veterans with age ≥50 years, drug abuse, diabetes, and hemoglobin < 10 g/dL showed lower rates of treatment. Initiation of treatment for HCV in homeless Veterans is low; similar factors predicted initiation of treatment. Additionally, exposure to treatment with medications for diabetes predicted lower rates of treatment. As newer therapies become available for HCV, these results may inform further studies and guide strategies to increase treatment rates in all U.S. Veterans and those who experience homelessness.

Detecting earlier indicators of homelessness in the free text of medical records.

Early warning indicators to identify US Veterans at risk of homelessness are currently only inferred from administrative data. References to indicators of risk or instances of homelessness in the free text of medical notes written by Department of Veterans Affairs (VA) providers may precede formal identification of Veterans as being homeless. This represents a potentially untapped resource for early identification. Using natural language processing (NLP), we investigated the idea that concepts related to homelessness written in the free text of the medical record precede the identification of homelessness by administrative data. We found that homeless Veterans were much higher utilizers of VA resources producing approximately 12 times as many documents as non-homeless Veterans. NLP detected mentions of either direct or indirect evidence of homelessness in a significant portion of Veterans earlier than structured data.

v3NLP Framework: Tools to Build Applications for Extracting Concepts from Clinical Text.

Introduction: Substantial amounts of clinically significant information are contained only within the narrative of the clinical notes in electronic medical records. The v3NLP Framework is a set of “best-of-breed” functionalities developed to transform this information into structured data for use in quality improvement, research, population health surveillance, and decision support. Background: MetaMap, cTAKES and similar well-known natural language processing (NLP) tools do not have sufficient scalability out of the box. The v3NLP Framework evolved out of the necessity to scale-up these tools up and provide a framework to customize and tune techniques that fit a variety of tasks, including document classification, tuned concept extraction for specific conditions, patient classification, and information retrieval. Innovation: Beyond scalability, several v3NLP Framework-developed projects have been efficacy tested and benchmarked. While v3NLP Framework includes annotators, pipelines and applications, its functionalities enable developers to create novel annotators and to place annotators into pipelines and scaled applications. Discussion: The v3NLP Framework has been successfully utilized in many projects including general concept extraction, risk factors for homelessness among veterans, and identification of mentions of the presence of an indwelling urinary catheter. Projects as diverse as predicting colonization with methicillin-resistant Staphylococcus aureus and extracting references to military sexual trauma are being built using v3NLP Framework components. Conclusion: The v3NLP Framework is a set of functionalities and components that provide Java developers with the ability to create novel annotators and to place those annotators into pipelines and applications to extract concepts from clinical text. There are scale-up and scale-out functionalities to process large numbers of records.