Publications

OBJECTIVE

To examine adherence to guideline-concordant hypertension treatment practices at community health centers (CHCs) compared with private physicians' offices.

DATA SOURCES/STUDY SETTING

National Ambulatory Medical Care Survey from 2006 to 2010.

STUDY DESIGN

We examined four guideline-concordant treatment practices: initiation of a new medication for uncontrolled hypertension, use of fixed-dose combination drugs for patients on multiple antihypertensive medications, use of thiazide diuretics among patients with uncontrolled hypertension on ≥3 antihypertensive medications, and use of aldosterone antagonist for resistant hypertension, comparing use at CHC with private physicians' offices overall and by payer group.

DATA COLLECTION/EXTRACTION METHODS

We identified visits of nonpregnant adults with hypertension at CHCs and private physicians' offices.

PRINCIPAL FINDINGS

Medicaid patients at CHCs were as likely as privately insured individuals to receive a new medication for uncontrolled hypertension (AOR 1.0, 95 percent CI: 0.6-1.9), whereas Medicaid patients at private physicians' offices were less likely to receive a new medication (AOR 0.3, 95 percent CI: 0.1-0.6). Use of fixed-dose combination drugs was lower at CHCs (AOR 0.6, 95 percent CI: 0.4-0.9). Thiazide use for patients was similar in both settings (AOR 0.8, 95 percent CI: 0.4-1.7). Use of aldosterone antagonists was too rare (2.1 percent at CHCs and 1.5 percent at private clinics) to allow for statistically reliable comparisons.

CONCLUSIONS

Increasing physician use of fixed-dose combination drugs may be particularly helpful in improving hypertension control at CHCs where there are higher rates of uncontrolled hypertension.

BACKGROUND

It is difficult to synthesize the vast amount of textual data available from social media websites. Capturing real-world discussions via social media could provide insights into individuals' opinions and the decision-making process.

OBJECTIVE

We conducted a sequential mixed methods study to determine the utility of sparse machine learning techniques in summarizing Twitter dialogues. We chose a narrowly defined topic for this approach: cervical cancer discussions over a 6-month time period surrounding a change in Pap smear screening guidelines.

METHODS

We applied statistical methodologies, known as sparse machine learning algorithms, to summarize Twitter messages about cervical cancer before and after the 2012 change in Pap smear screening guidelines by the US Preventive Services Task Force (USPSTF). All messages containing the search terms "cervical cancer," "Pap smear," and "Pap test" were analyzed during: (1) January 1-March 13, 2012, and (2) March 14-June 30, 2012. Topic modeling was used to discern the most common topics from each time period, and determine the singular value criterion for each topic. The results were then qualitatively coded from top 10 relevant topics to determine the efficiency of clustering method in grouping distinct ideas, and how the discussion differed before vs. after the change in guidelines .

RESULTS

This machine learning method was effective in grouping the relevant discussion topics about cervical cancer during the respective time periods (~20% overall irrelevant content in both time periods). Qualitative analysis determined that a significant portion of the top discussion topics in the second time period directly reflected the USPSTF guideline change (eg, "New Screening Guidelines for Cervical Cancer"), and many topics in both time periods were addressing basic screening promotion and education (eg, "It is Cervical Cancer Awareness Month! Click the link to see where you can receive a free or low cost Pap test.")

CONCLUSIONS

It was demonstrated that machine learning tools can be useful in cervical cancer prevention and screening discussions on Twitter. This method allowed us to prove that there is publicly available significant information about cervical cancer screening on social media sites. Moreover, we observed a direct impact of the guideline change within the Twitter messages.

BACKGROUND

Canine intervertebral disc πherniation causes a naturally-occurring spinal cord injury (SCI) that bears critical similarities to human SCI with respect to both injury pathomechanisms and treatment. As such, it has tremendous potential to enhance our understanding of injury biology and the preclinical evaluation of novel therapies. Currently, there is limited understanding of the role of arachidonic acid metabolites in canine SCI.

RESULTS

The CSF concentrations of PLA2 and PGE2 were higher in SCI dogs compared to control dogs (p = 0.0370 and 0.0273, respectively), but CSF LCT4 concentration in SCI dogs was significantly lower than that in control dogs (p < 0.0001). Prostaglandin E2 concentration in the CSF was significantly and positively associated with increased severity of SCI at the time of sampling (p = 0.041) and recovery 42 days post-injury (p = 0.006), as measured by ordinal behavioral scores.

CONCLUSION

Arachidonic acid metabolism is altered in dogs with SCI, and these data suggest that these AA metabolites reflect injury severity and recovery, paralleling data from other model systems.