Sensitivity and predictive value positive measurements for public health surveillance systems

Environmental tobacco smoke exposure in a multi-city cohort of children with asthma: Analyzing true exposure and the validity of caregiver survey

Introduction

The avoidance of asthma triggers, like tobacco smoke, facilitates asthma management. Reliance upon caregiver report of their child's environmental tobacco smoke (ETS) exposure may result in information bias and impaired asthma management. This analysis aimed to characterize the chronicity of ETS exposure, assess the validity of caregiver report of ETS exposure, and investigate the relationship between ETS exposure and asthma attack.

Methods

A secondary data analysis was performed on data from a longitudinal study of 162 children aged 7-12 years with asthma living in federally subsidized housing in three US cities (Boston, Cincinnati, and New Orleans). Data were collected at three time points over 1 year.

Results

Over 90% of children were exposed to ETS (≥0.25 ng/ml of urine cotinine (UC)). Exposure was consistent over 1 year. Questionnaire data had a sensitivity of 28-34% using UC ≥0.25 ng/ml as the gold standard. High ETS exposure (UC ≥ 30 ng/ml) was significantly associated with asthma attack (aOR 2.97, 0.93-9.52, p = 0.07). Lower levels (UC 0.25-30 ng/ml) were not statistically significant (aOR 1.76, 0.71- 4.38, p = 0.22). No association was found using caregiver-reported ETS exposure.

Conclusion

Relying on questionnaire data to assess children's exposure to tobacco smoke may lead to substantial information bias. For children with asthma, incorrect characterization may substantially impact asthma morbidity.

Sensitivity of an international notification system for wildlife diseases: A case study using the OIE-WAHIS data on tularemia

The World Organization for Animal Health (OIE) has recently developed a Wildlife Health Framework to respond to the need of members to manage the risk from emerging diseases at the animal-human-ecosystem interface. One of its objectives is to improve surveillance systems, early detection and notification of wildlife diseases. Members share information on disease occurrence by reporting through the OIE World Animal Health Information System (OIE-WAHIS-formerly known as 'WAHIS'). To evaluate the capacity of a surveillance system to detect disease events, it is important to quantify the gap between all known events and those officially notified to the OIE. This study used capture-recapture analysis to estimate the sensitivity of the OIE-WAHIS system for a OIE-listed wildlife disease by comparing information from publicly available sources to identify undetected events. This article presents a case study of the occurrence of tularemia in lagomorphs among selected North American and European countries during the period 2014-2019. First, an analysis using three data sources (OIE-WAHIS, ProMED, WHO-EIOS [Epidemic Intelligence from Open Sources]) was conducted. Subsequent analysis then explored the model integrating information from a fourth source (scientific literature collected in PubMed). Two models were built to evaluate both the sensitivity of the OIE-WAHIS using media reports (ProMED and WHO-EIOS), which is likely to represent current closer to real-time events, and published scientific data, which is more useful for retrospective analysis. Using the three-source approach, the predicted number of tularemia events was 93 (95% CI: 75-114), with an OIE-WAHIS sensitivity of 90%. In the four-source approach, the number of predicted events increased to 120 (95% CI: 99-143), dropping the sensitivity of the OIE-WAHIS to 70%. The results indicate a good sensitivity of the OIE-WAHIS system using the three-source approach, but lower sensitivity when including information from the scientific literature. Further analysis should be undertaken to identify diseases and regions for which international reporting presents a low sensitivity. This will enable evaluation and prioritization of underreported OIE-listed wildlife diseases and identify areas of focus as part of the Wildlife Health Framework. This study also highlights the need for stronger collaborations between academia and National Veterinary Services to enhance surveillance systems for notifiable diseases.

Assessment of electronic disease early warning system for improved disease surveillance and outbreak response in Yemen

BACKGROUND

Diseases Surveillance is a continuous process of data collection, analysis interpretation and dissemination of information for swift public health action. Recent advances in health informatics have led to the implementation of electronic tools to facilitate such critical disease surveillance processes. This study aimed to assess the performance of the national electronic Disease Early Warning System in Yemen (eDEWS) using system attributes: data quality, timeliness, stability, simplicity, predictive value positive, sensitivity, acceptability, flexibility, and representativeness, based on the Centres for Disease Control & Prevention (US CDC) standard indicators.

METHODS

We performed a mixed methods study that occurred in two stages: first, the quantitative data was collected from weekly epidemiological bulletins from 2013 to 2017, all alerts of 2016, and annual eDEWS reports, and then the qualitative method using in-depth interviews was carried out in a convergent strategy. The CDC guideline used to describe the following system attributes: data quality (reporting, and completeness), timeliness, stability, simplicity, predictive value positive, sensitivity, acceptability, flexibility and representativeness.

RESULTS

The finding of this assessment showed that eDEWS is a resilient and reliable system, and despite the conflict in Yemen, the system is still functioning and expanding. The response timeliness remains a challenge, since only 21% of all eDEWS alerts were verified within the first 24 h of detection in 2016. However, identified gaps did not affect the system's ability to identify outbreaks in the current fragile situation. Findings show that eDEWS data is representative, since it covers the entire country. Although, eDEWS covers only 37% of all health facilities, this represents 83% of all functional health facilities in all 23 governorates and all 333 districts.

CONCLUSION

The quality and timeliness of responses are major challenges to eDEWS' functionality, the eDEWS remains the only system that provides regular data on communicable diseases in Yemen. In particular, public health response timeliness needs improvement.

Development and Evaluation of a Fully Automated Surveillance System for Influenza-Associated Hospitalization at a Multihospital Health System in Northeast Ohio

BACKGROUND

Performing high-quality surveillance for influenza-associated hospitalization (IAH) is challenging, time-consuming, and essential.

OBJECTIVES

Our objectives were to develop a fully automated surveillance system for laboratory-confirmed IAH at our multihospital health system, to evaluate the performance of the automated system during the 2018 to 2019 influenza season at eight hospitals by comparing its sensitivity and positive predictive value to that of manual surveillance, and to estimate the time and cost savings associated with reliance on the automated surveillance system.

METHODS

Infection preventionists (IPs) perform manual surveillance for IAH by reviewing laboratory records and making a determination about each result. For automated surveillance, we programmed a query against our Enterprise Data Vault (EDV) for cases of IAH. The EDV query was established as a dynamic data source to feed our data visualization software, automatically updating every 24 hours.To establish a gold standard of cases of IAH against which to evaluate the performance of manual and automated surveillance systems, we generated a master list of possible IAH by querying four independent information systems. We reviewed medical records and adjudicated whether each possible case represented a true case of IAH.

RESULTS

We found 844 true cases of IAH, 577 (68.4%) of which were detected by the manual system and 774 (91.7%) of which were detected by the automated system. The positive predictive values of the manual and automated systems were 89.3 and 88.3%, respectively.Relying on the automated surveillance system for IAH resulted in an average recoup of 82 minutes per day for each IP and an estimated system-wide payroll redirection of $32,880 over the four heaviest weeks of influenza activity.

CONCLUSION

Surveillance for IAH can be entirely automated at multihospital health systems, saving time, and money while improving case detection.

Epidemiology and National Surveillance System for Foot and Mouth Disease in Cattle in Thailand during 2008-2019

Foot and mouth disease (FMD) is a prominent transboundary disease that threatens livestock production and can disrupt the trade in animals and animal products at both regional and international levels. The aims of this study were: (1) to analyze the distribution of FMD in Thailand during the period of 2008 to 2019, (2) to outline a national surveillance approach, and (3) to identify the existing knowledge gap that is associated with this disease in relation to cattle production. We analyzed FMD outbreak data in order to determine the existing spatial and temporal trends and reviewed relevant publications and official documents that helped us outline a national surveillance program. There were 1209 FMD outbreaks in cattle farms during the study period. FMD outbreaks occurred every year throughout the study period in several regions. Notably, FMD serotype O and A were considered the predominant types. The FMD National Strategic Plan (2008–2015) and the national FMD control program (2016–2023) have been implemented in order to control this disease. The surveillance approach employed by livestock authorities included both active and passive surveillance techniques. The vaccination program was applied to herds of cattle 2–3 times per year. Additionally, numerous control measures have been implemented across the country. We have identified the need for a study on the assessment of an applicable surveillance program, the evaluation of an appropriate vaccination strategy and an assessment of the effectiveness of a measured control policy. In conclusion, this study provided much needed knowledge on the epidemiology of FMD outbreaks across Thailand from 2008 to 2019. Additionally, we identified the need for future studies to address the existing knowledge gaps. The findings from this study may also be useful for livestock authorities and stakeholders to establish an enhanced control strategy and to implement an effective surveillance system that would control and eradicate FMD throughout the country.

Construction and application of surveillance and response systems for parasitic diseases in China, led by NIPD-CTDR

Parasitic diseases have been widely epidemic in China with a long history. Great endeavours made in past 70 years led to significant decrease in morbidity and mortablity caused by several major parasitic diseases, while challenges existed to eliminate parasitic diseases. Surveillance-response system has play a crucial role in identifying public health problems, ascertaining the distribution and epidemic dynamics, discovering outbreaks and epidemic anomalies, evaluating the effects of on-site intervention activities and identifying risk factors. In this article, we reviewed the progress of the surveillance system for parasitic diseases, analysed the role of NIPD in the construction and application of surveillance-response system of parasitic diseases through elaborating the surveillance activities and typical surveillance-response events led by NIPD. Suggestion and comments for improve the surveillance-response system were put forward for further control or elimination of parasitic diseases.

Summary of Notifiable Infectious Diseases and Conditions - United States, 2015

The Summary of Notifiable Infectious Diseases and Conditions - United States, 2015 (hereafter referred to as the summary) contains the official statistics, in tabular and graphical form, for the reported occurrence of nationally notifiable infectious diseases and conditions in the United States for 2015. Unless otherwise noted, data are final totals for 2015 reported as of June 30, 2016. These statistics are collected and compiled from reports sent by U.S. state and territories, New York City, and District of Columbia health departments to the National Notifiable Diseases Surveillance System (NNDSS), which is operated by CDC in collaboration with the Council of State and Territorial Epidemiologists (CSTE). This summary is available at https://www.cdc.gov/MMWR/MMWR_nd/index.html. This site also includes summary publications from previous years.

Capture-recapture approaches and the surveillance of livestock diseases: A review

In disease surveillance, capture-recapture approaches have been used to estimate the frequency of endemic diseases monitored by imperfect surveillance systems. A standard output of these techniques is an estimate of the sensitivity of the surveillance. In addition, capture-recapture applications contribute to a better understanding of the disease detection processes and of the relationships between different surveillance data sources, and help identify variables associated with the under-detection of diseases. Although capture-recapture approaches have long been used in public health, their application to livestock disease surveillance is only recent. In this paper, we review the different capture-recapture approaches applied in livestock disease surveillance, and discuss their benefits and limitations in the light of the characteristics of the surveillance and control practices used in animal health.

Systematic review and meta-analysis of validation studies on a diabetes case definition from health administrative records

OBJECTIVES

Health administrative data are frequently used for diabetes surveillance. We aimed to determine the sensitivity and specificity of a commonly-used diabetes case definition (two physician claims or one hospital discharge abstract record within a two-year period) and their potential effect on prevalence estimation.

METHODS

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Medline (from 1950) and Embase (from 1980) databases for validation studies through August 2012 (keywords: "diabetes mellitus"; "administrative databases"; "validation studies"). Reviewers abstracted data with standardized forms and assessed quality using Quality Assessment of Diagnostic Accuracy Studies (QUADAS) criteria. A generalized linear model approach to random-effects bivariate regression meta-analysis was used to pool sensitivity and specificity estimates. We applied correction factors derived from pooled sensitivity and specificity estimates to prevalence estimates from national surveillance reports and projected prevalence estimates over 10 years (to 2018).

RESULTS

The search strategy identified 1423 abstracts among which 11 studies were deemed relevant and reviewed; 6 of these reported sensitivity and specificity allowing pooling in a meta-analysis. Compared to surveys or medical records, sensitivity was 82.3% (95%CI 75.8, 87.4) and specificity was 97.9% (95%CI 96.5, 98.8). The diabetes case definition underestimated prevalence when it was ≤10.6% and overestimated prevalence otherwise.

CONCLUSION

The diabetes case definition examined misses up to one fifth of diabetes cases and wrongly identifies diabetes in approximately 2% of the population. This may be sufficiently sensitive and specific for surveillance purposes, in particular monitoring prevalence trends. Applying correction factors to adjust prevalence estimates from this definition may be helpful to increase accuracy of estimates.

Factors associated with the safety of voluntary medical male circumcision in Nyanza province, Kenya

OBJECTIVE

To determine factors associated with the incidence of adverse events associated with voluntary medical male circumcision (VMMC) for the prevention of HIV infection in Nyanza province, Kenya.

METHODS

Males aged 12 years or older who underwent VMMC between November 2008 and March 2010 in 16 clinics in three districts were followed through passive surveillance to monitor the incidence of adverse events during and after surgery. A subset of clinic participants was randomly selected for active surveillance post-operatively and was monitored for adverse events through a home-based, in-depth interview and a genital exam 28 to 45 days after surgery. Performance indicators were assessed for 167 VMMC providers.

FINDINGS

The adverse event rate was 0.1% intra-operatively and 2.1% post-operatively among clinic system participants (n = 3705), and 7.5% post-operatively among participants under active surveillance (n = 1449). Agreement between systems was moderate (κ: 0.20; 95% confidence interval, CI: 0.09-0.32). Providers who performed more than 100 procedures achieved an adverse event rate of 0.7% and 4.3% in the clinic and active surveillance systems, respectively, and had decreased odds of performing a procedure resulting in an adverse event. With provider experience, the mean duration of the procedure also dropped from 24.0 to 15.5 minutes. Among providers who had performed at least 100 procedures, nurses and clinicians provided equivalent services.

CONCLUSION

To reduce the adverse event rate, one must ensure that providers achieve a desired level of experience before they perform unsupervised procedures. Adverse events observed by the provider as well as those perceived by the client should both be monitored.

A Bayesian zero-truncated approach for analysing capture-recapture count data from classical scrapie surveillance in France

Capture-recapture (CR) methods are used to study populations that are monitored with imperfect observation processes. They have recently been applied to the monitoring of animal diseases to evaluate the number of infected units that remain undetected by the surveillance system. This paper proposes three bayesian models to estimate the total number of scrapie-infected holdings in France from CR count data obtained from the French classical scrapie surveillance programme. We fitted two zero-truncated Poisson (ZTP) models (with and without holding size as a covariate) and a zero-truncated negative binomial (ZTNB) model to the 2006 national surveillance count dataset. We detected a large amount of heterogeneity in the count data, making the use of the simple ZTP model inappropriate. However, including holding size as a covariate did not bring any significant improvement over the simple ZTP model. The ZTNB model proved to be the best model, giving an estimation of 535 (CI(95%) 401-796) infected and detectable sheep holdings in 2006, although only 141 were effectively detected, resulting in a holding-level prevalence of 4.4‰ (CI(95%) 3.2-6.3) and a sensitivity of holding-level surveillance of 26% (CI(95%) 18-35). The main limitation of the present study was the small amount of data collected during the surveillance programme. It was therefore not possible to build complex models that would allow depicting more accurately the epidemiological and detection processes that generate the surveillance data. We discuss the perspectives of capture-recapture count models in the context of animal disease surveillance.

Can near real-time monitoring of emergency department diagnoses facilitate early response to sporadic meningococcal infection?--prospective and retrospective evaluations

Background

Meningococcal infection causes severe, rapidly progressing illness and reporting of cases is mandatory in New South Wales (NSW), Australia. The NSW Department of Health operates near real-time Emergency Department (ED) surveillance that includes capture and statistical analysis of clinical preliminary diagnoses. The system can provide alerts in response to specific diagnoses entered in the ED computer system. This study assessed whether once daily reporting of clinical diagnoses of meningococcal infection using the ED surveillance system provides an opportunity for timelier public health response for this disease.

Methods

The study involved a prospective and retrospective component. First, reporting of ED diagnoses of meningococcal infection from the ED surveillance system prospectively operated in parallel with conventional surveillance which requires direct telephone reporting of this scheduled medical condition to local public health authorities by hospitals and laboratories when a meningococcal infection diagnosis is made. Follow-up of the ED diagnoses determined whether meningococcal infection was confirmed, and the time difference between ED surveillance report and notification by conventional means. Second, cases of meningococcal infection reported by conventional surveillance during 2004 were retrospectively matched to ED visits to determine the sensitivity and positive predictive value (PPV) of ED surveillance.

Results

During the prospective evaluation, 31 patients were diagnosed with meningococcal infection in participating EDs. Of these, 12 had confirmed meningococcal disease, resulting in a PPV of 38.7%. All confirmed cases were notified earlier to public health authorities by conventional reporting.

Of 149 cases of notified meningococcal disease identified retrospectively, 130 were linked to an ED visit. The sensitivity and PPV of the ED diagnosis for meningococcal infection was 36.2% and 36.7%, respectively.

Conclusions

Based on prospective evaluation, it is reassuring that existing mechanisms for reporting meningococcal infection perform well and are timely. The retrospective evaluation found low sensitivity and PPV of ED diagnoses for meningococcal disease. Even if more rapid forwarding of ED meningococcal diagnoses to public health authorities were possible, the low sensitivity and PPV do not justify this. In this study, use of an ED surveillance system to augment conventional surveillance of this scheduled medical condition did not demonstrate a benefit.

Assessment of a syndromic surveillance system based on morbidity data: results from the Oscour network during a heat wave

BACKGROUND

Syndromic surveillance systems have been developed in recent years and are now increasingly used by stakeholders to quickly answer questions and make important decisions. It is therefore essential to evaluate the quality and utility of such systems. This study was designed to assess a syndromic surveillance system based on emergency departments' (ED) morbidity rates related to the health effects of heat waves. This study uses data collected during the 2006 heat wave in France.

METHODS

Data recorded from 15 EDs in the Ile-de-France (Paris and surrounding area) from June to August, 2006, were transmitted daily via the Internet to the French Institute for Public Health Surveillance. Items collected included diagnosis (ICD10), outcome, and age. Several aspects of the system have been evaluated (data quality, cost, flexibility, stability, and performance). Periods of heat wave are considered the most suitable time to evaluate the system.

RESULTS

Data quality did not vary significantly during the period. Age, gender and outcome were completed in a comprehensive manner. Diagnoses were missing or uninformative for 37.5% of patients. Stability was recorded as being 99.49% for the period overall. The average cost per day over the study period was estimated to be euro287. Diagnoses of hyperthermia, malaise, dehydration, hyponatremia were correlated with increased temperatures. Malaise was most sensitive in younger and elderly adults but also the less specific. However, overall syndrome groups were more sensitive with comparable specificity than individual diagnoses.

CONCLUSION

This system satisfactorily detected the health impact of hot days (observed values were higher than expected on more than 90% of days on which a heat alert was issued). Our findings should reassure stakeholders about the reliability of health impact assessments during or following such an event. These evaluations are essential to establish the validity of the results of syndromic surveillance systems.

Disease reporting and surveillance: where do companion animal diseases fit in?

Disease surveillance and reporting is a necessary and integral part of public health practice. Surveillance systems have been developed over many years for both human medicine and veterinary medicine. However, these systems are not usually interconnected. Today, with the benefits of advanced information technology, the development and integration of existing and new resources in companion-animal practice should be focused on "one medicine-one health" for the betterment and health of all species. This means more sharing of surveillance data, greater cooperation among organizations involved in surveillance, and further integration of human and animal surveillance activities.

[Public health surveillance and role of administrative data]

BACKGROUND

Public health surveillance constitutes an important activity since it helps in identifying health needs through data collection, and contributes to decision making and actions by analyzing and interpreting data and communicating key results.

METHODS

This paper presents a discussion on the concept of public health surveillance, its objectives and its historical evolution. It deals with the importance of surveillance systems while describing their components and challenges. In addition, the authors point out the importance of administrative data as a relevant source for the surveillance of public health problems, particularly chronic diseases and risk factors.

RESULTS

This theoretical discussion leads to the proposal of a conceptual model for surveillance systems, which integrates implementation and evaluation.

CONCLUSION

This article provides a summary of the concept of public health surveillance and underlines the general aspects to be considered by the managers of surveillance systems. It also discusses the use of administrative data for surveillance.

A conditional probability approach to surveillance system sensitivity assessment

OBJECTIVE

To determine the sexually transmitted diseases (STD) surveillance system sensitivity with a conditional probability approach at district level in Darregaz, a frontier town in the north of Iran.

STUDY DESIGN

A cross-sectional survey.

METHODS

We used a sample survey of sexually active inhabitants for proxy measurement of the medical service utilization pattern for STD, and interviews with all practitioners to determine their knowledge of STD diagnosis and attitude towards STD reporting as proxy measures of actual STD diagnosis and reporting, respectively. Point estimates of the STD surveillance system sensitivity for each of the health service sectors were derived from multiplying the three proxy measures of sensitivity determinants, i.e., utilization, diagnosis, and reporting, as conditional probabilities. Estimates of sensitivity for all health service sectors were summed to obtain the overall sensitivity.

RESULTS

The sensitivity of the surveillance system was 21.2% (95% confidence interval (CI) 15.5-25.3%) for detecting symptomatic STD. Of the sexually active inhabitants, 8.9% (95% CI 5.5-14.2%) did not use health services if they contracted STDs. The public health sector's contribution to overall sensitivity (59.6%) was greater than its proportion of service utilization for STD (45.3%).

CONCLUSIONS

The strengths of the conditional probability approach are feasibility of conducting necessary surveys, decomposing sensitivity into its determinants, and providing evidence for intervention at different points for planning purposes. This approach tends to overestimate the overall sensitivity.

[Data quality of dengue epidemiological surveillance in Belo Horizonte, Southeastern Brazil]

OBJECTIVE

To evaluate the quality of data from the Brazilian information system for mandatory reporting diseases, for the detection of cases notified as suspected dengue fever and hospitalized in the public and private hospitals associated to the Public Health System.

METHODS

The study was carried out in Belo Horizonte, Southeastern Brazil, during the years of 1996 to June 2002. The criterion of evaluation used were those recommended by the Guidelines for Evaluating Public Health Surveillance Systems. As a reference standard, medical charts recorded in the Unified System hospitalized discharge database system were revised and validated. A total of 266 (90%) of 294 medical charts were selected; 230 (86.5%) filled the suspect dengue fever criterion. To verify possible association between underreporting and selected variables, was used the odds ratio, with 95% of confidence interval in a logistic regression model. The sensitivity was defined as the proportion of hospitalized dengue cases registered in both systems. Predictive value positive was calculated as the proportion of confirmed cases and those recorded in the reporting system.

RESULTS

Underreporting of suspected dengue fever was of 37% cases during 1997 to 2002, it was five times higher during the first three years (OR=5.93; 95% CI: 2.50-14.04) and eight times higher for patients hospitalized in private hospitals than in the public ones (OR=8.42; 95% CI: 2.26-31.27). Underreport was also associated to cases with no haemorrhagic episodes (OR=2.81; 95% CI: 1.28-6.15) and without dengue-specific laboratory exams in medical charts (OR=4.07; 95% CI:1.00-16.52). Sensitivity was 63% and predictive value positive was 43%.

CONCLUSIONS

Cases recorded in the reporting system were those more severe and did not represent the total of cases hospitalized in Unified Health System, thus the case fatality rate may be overestimated. The results indicate the necessity of changes in the evaluated surveillance model and in the implementation of the qualification of the health professionals, mainly those working in the private hospitals associated to Unified Health System.

The added value of claims for cancer surveillance: results of varying case definitions

OBJECTIVE

As cancer diagnosis and treatment has moved to the outpatient healthcare setting, traditional cancer surveillance tools are less effective for complete and unbiased capture of incident cases. This study evaluates the potential for Medicare data to supplement cancer surveillance in a unique manner by using a standard that is independent of a central cancer registry.

DESIGN

State cancer registry records were matched with Medicare data. Case validation included inpatient record abstraction combined with a mail/telephone survey of treating physicians. The positive predictive value (PPV), sensitivity (capture rate), and potential additional cases were calculated for 6 Medicare claims-based case definitions.

RESULTS

The PPV varied according to cancer site and definition, ranging from 70%-97% (prostate) to 87%-98% (breast). Sensitivity varied inversely with PPV, ranging from 51%-94% (breast) to 10%-88% (lung). The most important factors that predicted being missed by the registry were having no admission to an ACOS-certified hospital and no surgical treatment.

CONCLUSION

Medicare data represent a valid resource for supplementing state cancer registries in surveillance efforts. This potential is especially applicable to cancers predominantly diagnosed and treated outside the hospital setting.

Reporting incidence from a surveillance system with an operational case definition of unknown predictive value positive

When reporting incidence rate estimates for relatively rare health conditions, associated case counts are often assumed to follow a Poisson distribution. Case counts obtained from large-scale electronic surveillance systems are often inflated by the presence of false positives, however, and adjusted case counts based on the results of a validation sample will have variances which are hyper-Poisson. This paper presents a simple method for constructing interval estimates for incidence rates based on case counts that are adjusted downward using an estimate of the predictive value positive of the surveillance case definition.

Trends in the sensitivity, positive predictive value, false-positive rate, and comparability ratio of hospital discharge diagnosis codes for acute myocardial infarction in four US communities, 1987-2000

Variations in the validity of hospital discharge diagnoses can complicate the assessment of trends in incidence of acute myocardial infarction (AMI). To clarify trends in the validity of discharge codes, the authors compared event classification based on published Atherosclerosis Risk in Communities (ARIC) Study criteria with the presence or absence of an International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) hospital discharge code for AMI (code 410). Between 1987 and 2000, 154,836 coronary heart disease events involving hospitalization in the four ARIC communities had ICD-9-CM codes screened for AMI. The sensitivity of ICD-9-CM code 410 for classifying AMI in men (sensitivity = 0.65, 95% confidence interval (CI): 0.63, 0.66) was statistically significantly greater than that found for women (sensitivity = 0.60, 95% CI: 0.58, 0.62) and was greater in Whites (sensitivity = 0.67, 95% CI: 0.65, 0.68) than in Blacks (sensitivity = 0.50, 95% CI: 0.47, 0.53). The ethnic difference was related to a greater frequency of hypertensive heart disease and congestive heart failure codes encompassing AMI among Blacks as compared with Whites. The authors found that although the validity of ICD-9-CM code 410 to identify AMI was generally stable from 1987 through 2000, differences between Blacks and Whites and across geographic locations support investment in validation efforts in ongoing surveillance studies.

Review of the performance of methods to identify diabetes cases among vital statistics, administrative, and survey data

PURPOSE

The ability to identify prevalent cases of diagnosed diabetes is crucial to monitoring preventative care practices and health outcomes among persons with diagnosed diabetes.

METHODS

We conducted a comprehensive literature review to assess and summarize the validity of various strategies for identifying individuals with diagnosed diabetes and to examine the factors influencing the validity of these strategies.

RESULTS

We found that studies using either administrative data or survey data were both adequately sensitive (i.e., identified the majority of cases of diagnosed diabetes) and highly specific (i.e., did not identify the individuals as having diabetes if they did not). In contrast, studies based on cause-of-death data from death certificates were not sensitive, failing to identify about 60% of decedents with diabetes and in most of these studies, researchers did not report specificity or positive predictive value.

CONCLUSIONS

Surveillance is critical for tracking trends in diabetes and targeting diabetes prevention efforts. Several approaches can provide valuable data, although each has limitations. By understanding the limitations of the data, investigators will be able to estimate diabetes prevalence and improve surveillance of diabetes in the population.