Interestingly, the findings in Fig. 4 are congruent with a previous study of Texas Blood donors, highlighting significant localities of concern .CD is more prevalent among individuals who have lived in endemic regions of Latin America and are considered to be at a higher risk for CD. However, it is estimated that only about 1% of the individuals living with CD in the U.S. are aware of their diagnosis . In our study, heart disease symptoms that are common for patients with CD are used as a proxy to estimate possible cases and indicate areas to increase screening efforts. Areas in Texas with younger Hispanic populations and increased persons presenting with heart disease that could be related to CD was the focus of this paper . It should be noted that this is not the only population at risk in Texas, however they are at a higher risk than other populations . Presenting data in a visual and spatial format can often be useful in illustrating and contextualizing environmental factors . Given that the CD vector is found throughout the State of Texas , local transmission is not well understood and the large Hispanic population of Texas, visualization of potential missed diagnoses is an important and significant exploratory analysis. In turn, through GIS analysis and data visualization, educational and outreach efforts can be further targeted throughout the state. The application of contextualizing maps and integrating with statistical methods to enhance public health activities has been described in chronic diseases . However, the value and use of GIS to inform public health education activities on CD has not been previously studied.
The CD cases reported to TxDSHS are not homogenously dispersed throughout the state but occur in clusters and primarily in urban areas, where presumably there is increased access to physician care and larger populations. The policy implication is that screening for CD should begin with the populations most likely at risk [48, 52]. The data from TxDSHS  show the possibility for locally acquired or imported infection. Pockets of locally acquired cases were reported specifically in Bexar, Hidalgo, Brooks, and Cameron counties. However, no other areas, (i.e., the panhandle; western Texas including the El Paso region; and the eastern parts) show locally acquired infections. Moreover, five newly diagnosed CD patients are described in a case report : All of the patients acquired CD locally and resided in rural Southeast Texas counties. This highlights the possibility of persons currently not knowing that they have CD because many cases remain undiagnosed, particularly since the disease can become latent. In addition to local transmission, Texas presents the opportunity to surveil and diagnose imported cases. It is imperative for HCP’s throughout the state to recognize CD and be able to screen and diagnose patients.
Some counties with a high burden of heart-related diagnosis are also areas with CD diagnosis. The congruence in the urban hubs (Bexar, Dallas, and Harris counties) reflects the overall population but may also reflect the availability and ability of physicians in those counties to recognize CD and appropriately screen, diagnose, and treat. Conversely the modeling provided new insight into geographic areas (i.e., Kenedy County that was not believed by the researchers to be an area if interest). More focused education and outreach could be targeted to healthcare providers who may have limited knowledge in screening and diagnosis of CD in geographic areas where we find that there could be a higher risk for CD along with noted elevations in heart disease among a higher population of Latinos. As of 2017, the estimated seroprevalence of CD in Mexico was 2.26%, much higher than previously thought . A study in Starr County, Texas which lies adjacent to the Mexican border found that eight of 1196 study participants (0.7%) screened positive with 2 of the cases 1196 (0.2%) confirmed by study criteria . With Texas and Mexico sharing such a large border region, it stands to reason that the seroprevalence in places such as Texas could be higher, however with limited surveillance and screening it is hard to know the true amount of CD in Texas or the U.S.
This research is one of a few examining CD through hospital records . This is the first to examine statewide hospital records in order to qualify the potential for missed CD diagnosis in Texas. However, this research focused on potentially-missed diagnosed cases of chronic Chagas, rather than including acute and indeterminate chronic forms of CD. Moreover, in examining chronic CD, the scope of this research was limited to CCC, rather than looking at other sequelae (i.e., gastrointestinal complications). Furthermore, establishing the criteria for missed diagnoses of CD was the greatest challenge, given the lack of research to inform specific risk factors that account for CCC. Thus, the risk of misclassification is a concern.
Inpatient records were exclusively used, rather than including outpatient records given that CD patients do not necessarily require a hospitalization to be diagnosed. CD patients may be unaware of their CD status since the disease is asymptomatic. Because the patients are asymptomatic, they may be undiagnosed and thus not receiving appropriate care. Finally, the IPUDF data set does not provide unique patients, rather enumerates the records. Ultimately, this highlights the under-estimation of tur missed diagnoses of CD in Texas.
ICD-9 and ICD-10 heart-related and CD diagnostic codes were not completely comparable given differences in their definitions. While ICD-10 denotes the disease progression (i.e., acute, or chronic), there is no code specifying the indeterminate form of CD. In ICD-9 there is a code (086.2) that alludes to the asymptomatic, indeterminate form (i.e., Chagas without mention or organ involvement). Similarly, among the heart-related diagnostics, there is a cardiomyopathy, excluding Chagas in ICD-9 code but not one for ICD-10. Between 2013 and August of 2015, a total of 21 records indicated Chagas without mention of organ involvement. Furthermore, ICD codes are intended for medical billing and are not confirmed CD diagnosis. The identified barriers  to screening and diagnosing acute and chronic CD are documented further highlight the challenges in fully estimating the true prevalence of CD across the state. Our study utilized the hospital inpatient data to focus and target educational efforts throughout Texas.
Future research can further explore the patterns of missed diagnoses within specific geographical targets. For example, examining and comparing urban and rural counties only in contrast to examining patterns throughout the state; or by examining differences in census tracts or zip codes). Furthermore, the case definitions for the missed CD diagnostic codes could be re-evaluated. For example, additional geospatial and statistical analyses can be performed on specific counties using only idiopathic cardiomyopathy diagnoses and comparing to other codes that accounted for the large number of potential CD heart-related diagnoses (e.g., other ischemic heart disease, ischemic cardiomyopathy, unspecified cardiomyopathy). Finally, additional research can map the county demographics and more specific risk factors for CCC (i.e., by narrowing the age group).
Secondly, the findings support the need for surveillance systems. An entomological surveillance system should include the study of natural infection in vectors. In turn, such systems could facilitate screening for individuals in communities with documented infestation. In the human population, a surveillance system would facilitate an increase in the accuracy, validity, and generalizability of a geospatial analysis. That is, maps that are created to illustrate the magnitude of CD cases in Texas would greatly benefit from epidemiological data that is specific to CD, rather than relying on administrative data such as the Texas PUDF. For example, recent findings have helped focus educational approaches, particularly using an Extension for Community Healthcare Outcomes (ECHO) model among community healthcare workers  in Texas.