Accuracy of pharmacy and coded-diagnosis information in identifying tuberculosis in patients with rheumatoid arthritis

Validity of ICD-10-CM diagnoses to identify hospitalizations for serious infections among patients treated with biologic therapies

PURPOSE

Identifying hospitalizations for serious infections among patients dispensed biologic therapies within healthcare databases is important for post-marketing surveillance of these drugs. We determined the positive predictive value (PPV) of an ICD-10-CM-based diagnostic coding algorithm to identify hospitalization for serious infection among patients dispensed biologic therapy within the FDA's Sentinel Distributed Database.

METHODS

We identified health plan members who met the following algorithm criteria: (1) hospital ICD-10-CM discharge diagnosis of serious infection between July 1, 2016 and August 31, 2018; (2) either outpatient/emergency department infection diagnosis or outpatient antimicrobial treatment within 7 days prior to hospitalization; (3) inflammatory bowel disease, psoriasis, or rheumatological diagnosis within 1 year prior to hospitalization, and (4) were dispensed outpatient biologic therapy within 90 days prior to admission. Medical records were reviewed by infectious disease clinicians to adjudicate hospitalizations for serious infection. The PPV (95% confidence interval [CI]) for confirmed events was determined after further weighting by the prevalence of the type of serious infection in the database.

RESULTS

Among 223 selected health plan members who met the algorithm, 209 (93.7% [95% CI, 90.1%-96.9%]) were confirmed to have a hospitalization for serious infection. After weighting by the prevalence of the type of serious infection, the PPV of the ICD-10-CM algorithm identifying a hospitalization for serious infection was 80.2% (95% CI, 75.3%-84.7%).

CONCLUSIONS

The ICD-10-CM-based algorithm for hospitalization for serious infection among patients dispensed biologic therapies within the Sentinel Distributed Database had 80% PPV for confirmed events and could be considered for use within pharmacoepidemiologic studies.

Exploring an alternative approach to Lyme disease surveillance in Maryland

In Maryland, Lyme disease (LD) is a reportable disease and all laboratories and healthcare providers are required to report to the local health department. Given the volume of LD reports and effort required for investigation, surveillance for LD is burdensome and subject to underreporting. We explored the utility of International Classification of Diseases, 9th Revision, Clinical Modification (administrative) codes for use with LD surveillance. We aimed to collect the administrative codes for a 10% sample of 2009 LD reports (n = 474) from 292 facilities stratified by case classification (confirmed, probable, suspected and not a case). Sixty-three per cent (n = 184) of facilities responded to the survey, and 341 different administrative codes were obtained for 91% (n = 430) of sampled reports. The administrative code for Lyme disease (088.81) was the most commonly reported code (133/430 patients) among sampled reports; while it was used for 62 of 151 (41%) confirmed cases, it was also used for 48 of 192 (25%) not a case reports (sensitivity 41% and specificity 73%). A combination of nine codes was developed with sensitivity of 74% and specificity of 37% when compared to not a case reports. We conclude that the administrative code for LD alone has low ability to identify LD cases in Maryland. Grouping certain codes improved sensitivity, but our results indicate that administrative codes alone are not a viable surveillance alternative for a disease with complex manifestations such as LD.

Antidepressant Regulatory Warnings, Prescription Patterns, Suicidality and Other Aggressive Behaviors in Major Depressive Disorder and Anxiety Disorders

In 2004 the Food and Drug Administration issued a warning on the risk of suicidality in children and adolescents receiving antidepressants. This was followed by reports of changes in antidepressant prescription patterns, suicidality and other aggressive behaviors, but debate is continuing regarding the nature and magnitude of these changes. We examined a large physician database for impact of the warning on antidepressant prescriptions, suicidality and other aggressive behaviors in major depressive disorder (MDD) and anxiety disorders in adult and pediatric patients. We analyzed electronic database covering over 100,000 patients, treated in Pre- (before 2003) and Post- (after 2004) warning periods. We compared strength of the association between the measures and the time period with two tests. Multivariate logistic regression analyses were performed to ascertain the unique effect of each parameter. Of 10,089 MDD (61.0 %) and anxiety disorders (39.0 %) patients, 65.2 % received antidepressant prescription and 16.1 % were pediatric patients. In post-warning period, there was a greater reduction in adult versus pediatric antidepressant prescription rates. Logistic modeling showed greater likelihood of antidepressant prescription in MDD as compared with anxiety disorders in post-warning period. Pediatric patients were more likely than adults to receive fluoxetine during the post-warning period. There was an overall reduction in suicidality and other aggressive behaviors in the post-warning period. Regulatory warnings may have had an impact on antidepressant benefit/risk assessment and consequent utilization, therapeutic effects, and adverse events. Our observations suggest that psychiatrists may heed regulatory warnings, but may also exert professional independence and discrimination in their application.

Using linked electronic data to validate algorithms for health outcomes in administrative databases

The validity of algorithms used to identify health outcomes in claims-based and administrative data is critical to the reliability of findings from observational studies. The traditional approach to algorithm validation, using medical charts, is expensive and time-consuming. An alternative method is to link the claims data to an external, electronic data source that contains information allowing confirmation of the event of interest. In this paper, we describe this external linkage validation method and delineate important considerations to assess the feasibility and appropriateness of validating health outcomes using this approach. This framework can help investigators decide whether to pursue an external linkage validation method for identifying health outcomes in administrative/claims data.

A population-based study of infection-related hospital mortality in patients with dermatomyositis/polymyositis

OBJECTIVE

Dermatomyositis (DM) and polymyositis (PM) are debilitating inflammatory myopathies associated with significant mortality. We evaluated the relative contribution of infection to hospital mortality in a large population-based study of individuals with PM/DM.

METHODS

Data derive from the 2007 to 2011 Healthcare Cost and Utilization Project National Inpatient Samples and include all hospital discharges that met a validated administrative definition of PM/DM. The primary outcome was hospital mortality. Variables for infections and comorbidities were generated from discharge diagnoses using validated administrative definitions. Logistic regression was used to investigate the relationship between infection and mortality in individuals with PM/DM, adjusting for sociodemographics, utilization variables, and comorbidities. Relative risks (RRs) were calculated to compare the overall prevalence of specific infections and associated mortality in PM/DM hospitalizations with those seen in the general hospitalized population.

RESULTS

A total of 15,407 hospitalizations with PM/DM met inclusion criteria for this study and inpatient mortality was 4.5% (700 deaths). In adjusted logistic regression analyses, infection (odds ratio [OR] 3.4, 95% confidence interval [95% CI] 2.9-4.0) was the strongest predictor of hospital mortality among individuals with PM/DM. Bacterial infection (OR 3.5, 95% CI 3.0-4.1), comprised primarily of pneumonia and bacteremia, and opportunistic fungal infections (OR 2.5, 95% CI 1.5-4.0) were independently associated with hospital mortality. The overall burden of infection in hospitalizations with PM/DM was significantly increased in comparison with the general hospitalized population (RR 1.5, 95% CI 1.4-1.6).

CONCLUSION

Among hospitalized individuals with PM/DM, infection is the leading cause of mortality. Strategies to mitigate infection risk in both the clinic and hospital settings should be evaluated to improve disease outcomes.

Infection risk in patients with rheumatoid arthritis treated with etanercept or adalimumab

OBJECTIVES

To compare the risk of infection for rheumatoid arthritis (RA) patients who took etanercept or adalimumab medication in a nationwide population.

METHODS

RA patients who took etanercept or adalimumab were identified in the Taiwan's National Health Insurance Research Database. The composite outcome of serious infections, including hospitalization for infection, reception of an antimicrobial injection, and tuberculosis were followed for 365 days. A Kaplan-Meier survival curve with a log-rank test and Cox proportional hazards regression were used to compare risks of infection between the two cohorts of tumor necrosis factor (TNF)-α antagonists users. Hazard ratios (HRs) were obtained and adjusted with propensity scores and clinical factors. Sensitivity analyses and subgroup analyses were also performed.

RESULTS

In total, 1660 incident etanercept users and 484 incident adalimumab users were eligible for the analysis. The unadjusted HR for infection of the etanercept users was significantly higher than that of the adalimumab users (HR: 1.93; 95% confidence interval (CI): 1.09-3.42; p=0.024). The HRs were 2.04 (95% CI: 1.14-3.65; p=0.016) and 2.02 (95% CI: 1.13-3.61; p=0.018) after adjusting for propensity scores and for propensity scores in addition to clinical factors, respectively. The subgroup analyses revealed that HRs for composite infection was significantly higher in patient subgroups of older age, female, as well as patients who did not have DM, COPD, and hospitalization history at the baseline.

CONCLUSION

In this head-to-head cohort study involving a nationwide population of patients with RA, etanercept users demonstrated a higher risk of infection than adalimumab users. Results of this study suggest the possible existence of an intra-class difference in infection risk among TNF-α antagonists.

Use of state administrative data sources to study adolescents and young adults with rare conditions

BACKGROUND

Effective care of young people with rare conditions requires ongoing coordinated medical treatment as well as educational and social support services. However, information on treatment is often lacking due to limited data. South Carolina has a repository of comprehensive health and human service data with which individuals may be tracked across the data systems of multiple state agencies and organizations.

OBJECTIVE

To develop a method for studying health care of young persons with rare conditions using this repository.

METHODS

We identified individuals aged 15 to 24 years diagnosed during 2000-2010 with Fragile X syndrome (FXS), spina bifida (SB), or muscular dystrophy (MD) using a series of algorithms. ICD-9-CM codes were used to initially identify the cohort from medical billing data. Demographics, medical care, employment, education, and socioeconomic status data were then extracted from linked administrative sources.

RESULTS

We identified 1,040 individuals with these rare conditions: 125 with FXS, 695 with SB, and 220 with MD. The vast majority of the cases (95%) were identified in the Medicaid database. Half of the cohort was male, with a higher percentage in the FXS and MD groups. Sixty-two percent of the cohort was enrolled in the last year of high school. Over half of the cohort received support services from the state's disability and special-needs agency; 16% received food assistance. Thirty-eight percent were employed at some point during the study period. Forty-nine individuals with SB and 56 with MD died during the study period.

CONCLUSIONS

We used a linked statewide data system to study rare conditions. Strengths include the diversity of information, rigorous identification strategies, and access to longitudinal data. Despite limitations inherent to administrative data, we found that linked state data systems are valuable resources for investigating important public health questions on rare conditions.

Understanding the burden of tuberculosis among American Indians/Alaska Natives in the U.S.: a validation study

OBJECTIVE

We validated cases of active tuberculosis (TB) recorded in the Indian Health Service (IHS) National Patient Information Reporting System (NPIRS) and evaluated the completeness of TB case reporting from IHS facilities to state health departments.

METHODS

We reviewed the medical records of American Indian/Alaska Native (AI/AN) patients at IHS health facilities who were classified as having active TB using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic codes from 2006 to 2009 for clinical and laboratory evidence of TB disease. Individuals were reclassified as having active TB disease; recent latent TB infection (LTBI); past positive tuberculin skin test (TST) only; or as having no evidence of TB, LTBI, or a past positive TST. We compared validated active TB cases with corresponding state records to determine if they were reported.

RESULTS

The study included 596 patients with active TB as per ICD-9-CM codes. Based on chart review, 111 (18.6%) had active TB; 156 (26.2%) had LTBI; 104 (17.4%) had a past positive TST; and 221 (37.1%) had no evidence of TB disease, LTBI, or a past positive TST. Of the 111 confirmed cases of active TB, 89 (80.2%) resided in participating states; 81 of 89 (91.2%) were verified as reported TB cases.

CONCLUSIONS

ICD-9-CM codes for active TB disease in the IHS NPIRS do not accurately reflect the burden of TB among AI/ANs. Most confirmed active TB cases in the IHS health system were reported to the state; the national TB surveillance system may accurately represent the burden of TB in the AI/AN population.

Active tuberculosis and venous thromboembolism: association according to international classification of diseases, ninth revision hospital discharge diagnosis codes

BACKGROUND

Infections are risk factors for venous thromboembolism (VTE), especially if severe and acute. The role of chronic infections such as active tuberculosis is ill defined, although several case reports and small series have suggested an association between tuberculosis and VTE.

METHODS

Using data from the Premier Perspective database (27 659 947 admissions), we performed a multivariate analysis to assess the specific VTE risk associated with tuberculosis. The analysis was adjusted on classic risk factors for VTE.

RESULTS

The prevalence of VTE among patients with active tuberculosis was 2.07% (95% confidence interval [CI], 1.62%-2.59%). In a multivariate analysis model, adults with active tuberculosis had a greater risk of VTE than those without (odds ratio, 1.55 [95% CI, 1.23-1.97], P < .001), close to the previously reported risk associated with neoplasia. No particular link was found between pulmonary tuberculosis and pulmonary embolism, or between extrapulmonary tuberculosis and deep vein thrombosis. This may suggest the preponderant role of a systemic hypercoagulable state over an intrathoracic venous compression mechanism. In-hospital mortality of patients with both active tuberculosis and VTE (11/72 [15%]) was higher than mortality of patients with only active tuberculosis (92/3413 [2.7%]) or only VTE (5062/199 480 [2.5%]) (P < .001). Pulmonary embolism was more frequent in black patients, suggesting that this population, which is also more likely to suffer from tuberculosis, should be followed carefully.

CONCLUSIONS

Tuberculosis must be considered as a pertinent risk factor for VTE and should be included in thromboembolism risk evaluation similar to any acute and severe infection.

Systematic review of validation studies of the use of administrative data to identify serious infections

OBJECTIVE

To conduct a systematic review of the literature on the validation of algorithms identifying infections in administrative data for future use in populations with rheumatic diseases.

METHODS

Medline and EMBase were searched using the themes "administrative data" and "infection" between 1950 and October 2012. Inclusion criteria consisted of validation studies of administrative data identifying infections in adult populations. Article quality was assessed using a validated tool.

RESULTS

A total of 5,941 articles were identified, 90 articles underwent detailed review, and 24 studies were included. The majority (17 of 24) examined bacterial infections and 9 examined opportunistic infections. Eighteen studies were from the US and all but 4 studies used International Classification of Diseases, Ninth Revision codes. Rheumatoid arthritis patients were studied in 6 of 24 articles. The studies on bacterial infections in general reported highly variable sensitivity and positive predictive value (PPV) for the diagnosis of infections using administrative data (sensitivity range 4.4-100%, PPV range 21.7-100%). Algorithms to identify opportunistic infections similarly had a highly variable sensitivity (range 20-100%) and PPV (range 1.3-100%). Thirteen studies compared the diagnostic accuracy of different algorithms, which revealed that strategies including a comprehensive algorithm using a greater number of diagnostic codes or codes in any position had the highest sensitivity for the diagnosis of infection. Algorithms that incorporated microbiologic or pharmacy data in combination with diagnostic codes had improved PPV for identification of tuberculosis.

CONCLUSION

Algorithms for identifying infections using administrative data should be selected based on the purpose of the study, with careful consideration as to whether a high sensitivity or PPV is required.