The goal of health technology is to assist in more efficient data collection, increase connectivity, and foresee market changes. A push for a more healthy lifestyle across the United States has lead to an increasing need for innovative ideas that can lead to healthy behavior changes. Even with governmental efforts, life expectancy in the United States has decreased, inequities in healthcare persist in rural communities and healthcare costs are still at an all time high. Developing partnerships between healthcare communities and business technology firms has the possibility to strengthen the development of evidence-based research and HIPAA-compliant clinical resources that can contribute to an improved population health in the United States. Using these firms can also establish more reputable platforms, health analytics, and marketing expertise that could serve beneficial to the current healthcare issues.
Implementing technology into exercise devices has lead to success stories surrounding smart technology abound. Exercise using smart technology has been shown to increase physical activity compared to traditional healthcare models. Access to healthcare is also an issue due to the US healthcare industry structure. This can be improved through the use of online applications geared towards connecting clinicians with patients. Through businesses engagement, assistance in the development of technology services that increases access to low-cost care for patients in need is possible.
Innovative inventions in data collection would assist with patients having access to their own health information. This gives them the opportunity to make informed decisions about their own health. It also reduces redundant testing resulting in patients and clinicians saving time and money. Collaborating with businesses and technology firms on healthcare issues and projects could improve population health overall.
- Stey A, Kanzaria H, Brook R. How disruptive innovation by business and technology firms could improve population health [published online August 16, 2018]. JAMA.doi:10.1001/jama.2018.10782
Texas has one of the highest vaccination rates for childhood diseases overall, 97.4%, according to CDC. But the number of children not vaccinated because of their parents’ “personal beliefs”—as opposed to medical reasons—has risen since 2003, when such exemptions were introduced, to more than 44,000 so far in 2017 according to CDC. The 4:3:1:3:3:1:4 series is an overall measure that encompasses many vaccines that are recommended for children. Various demographic factors (sex, gender, race, availability of commercial health insurance) influence the decision to get vaccinated, were looked at.
The county-level data on the socioeconomic factors were obtained from US Census Bureau (American Factfinder). The health insurance data was obtained from Small Area Health Insurance Estimates (SAHIE). The vaccination rates were obtained from Texas Immunization registry through DSHS. The data was cleaned and geocoded to be analyzed in ArcGIS to produce maps as shown in Figure 1. Pearson’s correlation coefficient was used to analyze the relationship between vaccination rates and independent variable.
The non-vaccination rates are higher around the major cities of Dallas, Austin-San Antonio, Houston and some northwest Texas counties. Population density has a positive correlation with the non-vaccination rate. Other demographic factors have a positive correlation in certain counties as opposed to others.
Source: American FactFinder, Texas Immunisation Registry
The limitation on the immunization data is it being an optional registry so it would not be accurate to run statistics off this information to estimate an immunization rate. In future, it is productive to expand this concept to use regression analysis to try to find the odds of the relationship expressed in the maps and to find if there is a significant association.
Preventive oral health care is essential for one’s overall health. For children, it is important to address oral health needs earlier in life to prevent oral health issues from forming and progressing into adulthood. Below is a map of the percentage of children in Georgia with financial access to preventive dental care. This map comes from an article written by Cao, Gentili, Griffin, Griffin & Serban (2017) titled, “Disparities in Preventive Dental Care Among Children in Georgia.”
The authors of the article state that financial access is, “the percentage of children who either are eligible for public insurance or have the ability to afford dental care through commercial insurance or ability to pay out-of-pocket,” (Cao et al., 2017). Although there are plenty of children who are eligible to receive public funding for preventive dental care in GA, only 27.9% of the 4,123 dentists in GA who offer preventive dental services to children accept public insurance, (Cao et al., 2017).
What are your thoughts? What does financial access to preventive dental care mean to you? Is this an accurate representation of financial access? I invite you to read more of the article on the CDC’s website, here.
Source: Cao S, Gentili M, Griffin PM, Griffin SO, Serban N. Disparities in Preventive Dental Care Among Children in Georgia. Prev Chronic Dis 2017;14:170176. DOI: http://dx.doi.org/10.5888/pcd14.170176.
Check out this map that shows the number of National Health Service Corps (NHSC) sites in Tennessee as of 10/6/17 and the number of National Committee for Quality Assurance certified Patient Center Medical Home (PCMH) sites in Tennessee as of 1/23/18.
For more information on the Patient Centered Medical Home click here.
By Julia Watson
A National Health Service Corps (NHSC) Site is an approved health care facility that provides healthcare to populations residing in Health Professional Shortage Areas (HPSAs). Check out this density map which shows the total number of federal bureau of prison sites that are designated as national loan repayment locations. Eligible health care professionals that work at these sites receive a certain amount each year towards their school loans. From the map we see there are highly concentrated areas in the southeast and northeast regions of the country.
By Michael Paul
Today’s map shows the rate of self reported pesticide related illness by state for the year of 2014 per 100,000 person. From the map we can see some states had rates ranging as low as 0.00 to 0.27 indicated by the yellow shading. In contrast some states, such as Alaska, Florida, Alabama, Mississippi, Arkansas, New York, Kansas and Virginia had rates as high as 0.87 to 2.56 indicated by the dark blue shading. However, its important to note that because these are self-reported rates the date is subjected to under-reporting. In addition, because these exposures are self-reported both the type of pesticide and the degree of illness associated with the exposure may be mis-classified since the designation by the poison control center for both is based on the description provided by the caller.
According to the CDC farmworkers are among those when are subjected to pesticide exposure. For more information on migrant workers click here.
By Julia Watson
Check out this map that shows the number of homes built between 1950 and 1979 by county for year 2000. From the map we can see there were many new homes built in counties within the eastern states, such as New York, New Jersey, Road Island, Main indicated by the darker shading. There were also many new homes built in counties within some western states, such as California and Arizona. We can see states such as North and South Dakota, Nebraska, Montana and Kansas had fewer new homes built within the 29 year period indicated by the yellow/yellowish shading. This makes sense because when compared to the previous map of homes built prior to 1950 for the year of 2000 we see these states had a higher percentage of older homes.
By Julia Watson