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Browsing by Author "Willis, Deanna R."
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Item Computer-tailored intervention increases colorectal cancer screening among low-income African Americans in primary care: Results of a randomized trial(Elsevier, 2021) Rawl, Susan M.; Christy, Shannon M.; Perkins, Susan M.; Tong, Yan; Krier, Connie; Wang, Hsiao-Lan; Huang, Amelia M.; Laury, Esther; Rhyant, Broderick; Lloyd, Frank; Willis, Deanna R.; Imperiale, Thomas F.; Myers, Laura J.; Springston, Jeffrey; Sugg Skinner, Celette; Champion, Victoria L.; School of NursingIntroduction: Although African Americans have the highest colorectal cancer (CRC) incidence and mortality rates of any racial group, their screening rates remain low. Study design/purpose: This randomized controlled trial compared efficacy of two clinic-based interventions for increasing CRC screening among African American primary care patients. Methods: African American patients from 11 clinics who were not current with CRC screening were randomized to receive a computer-tailored intervention (n = 335) or a non-tailored brochure (n = 358) designed to promote adherence to CRC screening. Interventions were delivered in clinic immediately prior to a provider visit. Univariate and multivariable logistic regression models analyzed predictors of screening test completion. Moderators and mediators were determined using multivariable linear and logistic regression analyses. Results: Significant effects of the computer-tailored intervention were observed for completion of a stool blood test (SBT) and completion of any CRC screening test (SBT or colonoscopy). The colonoscopy screening rate was higher among those receiving the computer-tailored intervention group compared to the nontailored brochure but the difference was not significant. Predictors of SBT completion were: receipt of the computer-tailored intervention; being seen at a Veterans Affairs Medical Center clinic; baseline stage of adoption; and reason for visit. Mediators of intervention effects were changes in perceived SBT barriers, changes in perceived colonoscopy benefits, changes in CRC knowledge, and patient-provider discussion. Moderators of intervention effects were age, employment, and family/friend recommendation of screening. Conclusion: This one-time computer-tailored intervention significantly improved CRC screening rates among low-income African American patients. This finding was largely driven by increasing SBT but the impact of the intervention on colonoscopy screening was strong. Implementation of a CRC screening quality improvement program in the VA site that included provision of stool blood test kits and follow-up likely contributed to the strong intervention effect observed at that site.Item Effect of Advanced Access Scheduling on Processes and Intermediate Outcomes of Diabetes Care and Utilization(2009-03) Subramanian, Usha; Ackermann, Ronald T.; Brizendine, Edward J.; Saha, Chandan; Rosenman, Marc B.; Willis, Deanna R.; Marrero, David G.BACKGROUND The impact of open access (OA) scheduling on chronic disease care and outcomes has not been studied. OBJECTIVE To assess the effect of OA implementation at 1 year on: (1) diabetes care processes (testing for A1c, LDL, and urine microalbumin), (2) intermediate outcomes of diabetes care (SBP, A1c, and LDL level), and (3) health-care utilization (ED visits, hospitalization, and outpatient visits). METHODS We used a retrospective cohort study design to compare process and outcomes for 4,060 continuously enrolled adult patients with diabetes from six OA clinics and six control clinics. Using a generalized linear model framework, data were modeled with linear regression for continuous, logistic regression for dichotomous, and Poisson regression for utilization outcomes. RESULTS Patients in the OA clinics were older, with a higher percentage being African American (51% vs 34%) and on insulin. In multivariate analyses, for A1c testing, the odds ratio for African-American patients in OA clinics was 0.47 (CI: 0.29-0.77), compared to non-African Americans [OR 0.27 (CI: 0.21-0.36)]. For urine microablumin, the odds ratio for non-African Americans in OA clinics was 0.37 (CI: 0.17-0.81). At 1 year, in adjusted analyses, patients in OA clinics had significantly higher SBP (mean 6.4 mmHg, 95% CI 5.4 – 7.5). There were no differences by clinic type in any of the three health-care utilization outcomes. CONCLUSION OA scheduling was associated with worse processes of care and SBP at 1 year. OA clinic scheduling should be examined more critically in larger systems of care, multiple health-care settings, and/or in a randomized controlled trial.Item Primary Care Appointment Systems: Causes and Implications of Timely Arrivals(TECSI, 2022) Alibeiki, Hedayat; Kumar, Chetan; Ballard, Jim; Willis, Deanna R.; Given, Scott; Taylor, Jennifer; Family Medicine, School of MedicineThe primary goal of this study was to identify potential factors that might contribute to patient punctuality issues, while also assessing the satisfaction of a proposed intervention. In addition, we aimed to learn more about the psychosocial and behavioral implications that patients face with regards to arriving on time for their primary care visits. A mixed-method research study was used to identify and quantify potential factors that might contribute to patient punctuality issues, while also assessing the satisfaction of a proposed intervention. In addition to possible factors that contribute to punctuality, we aimed to learn more about how patients are affected when they arrive late for appointments. Through qualitative assessment, we explored the psychosocial and behavioral implications that patients face with regards to arriving on time for their primary care appointments. A total of 524 individuals out of 1050 patients (50%) responded to the paper-based survey. Of the 524 adult respondents, we excluded 103 (19.7%) participants due to the missing data on either of their historical behavior patterns, future intentions for arrival, or their definition of appointment time. We analyzed the data for the remaining 421 eligible survey participants. In addition, seven of the eight patient interviews were transcribed and analyzed in order to identify themes using the patient’s own words to better understand the psychosocial and behavioral implications patients face on arriving to their appointment on time. Three primary themes emerge in the interviews related to the perception of arriving late to appointments at the FMC. The findings of this study indicate that regardless of patients’ interpretation of appointment time, they typically arrive 10-15 minutes before the appointment time. In addition, there is a significant connection between patients’ perceptions of historically arriving late to appointments and the intent to arrive very early to their future appointments. Combined with the qualitative results, this study suggests that most patients are motivated to be on time, in some cases seeing the idea of lateness as a contradiction of their own self-identity. The behavioral causes and implications of the findings are explained using the concept of Fear Appeals and the Protection Motivation Theory (PMT).Item Primary Care Appointment Systems: Causes and Implications of Timely Arrivals(Journal of Information Systems and Technology Management, 2021-07-12) Alibeiki, Hedayat; Kumar, Chetan; Ballard, Jim; Willis, Deanna R.; Medicine, School of MedicineABSTRACT The primary goal of this study was to identify potential factors that might contribute to patient punctuality issues, while also assessing the satisfaction of a proposed intervention. In addition, we aimed to learn more about the psychosocial and behavioral implications that patients face with regards to arriving on time for their primary care visits. A mixed-method research study was used to identify and quantify potential factors that might contribute to patient punctuality issues, while also assessing the satisfaction of a proposed intervention. In addition to possible factors that contribute to punctuality, we aimed to learn more about how patients are affected when they arrive late for appointments. Through qualitative assessment, we explored the psychosocial and behavioral implications that patients face with regards to arriving on time for their primary care appointments. A total of 524 individuals out of 1050 patients (50%) responded to the paper-based survey. Of the 524 adult respondents, we excluded 103 (19.7%) participants due to the missing data on either of their historical behavior patterns, future intentions for arrival, or their definition of appointment time. We analyzed the data for the remaining 421 eligible survey participants. In addition, seven of the eight patient interviews were transcribed and analyzed in order to identify themes using the patient’s own words to better understand the psychosocial and behavioral implications patients face on arriving to their appointment on time. Three primary themes emerge in the interviews related to the perception of arriving late to appointments at the FMC. The findings of this study indicate that regardless of patients’ interpretation of appointment time, they typically arrive 10-15 minutes before the appointment time. In addition, there is a significant connection between patients’ perceptions of historically arriving late to appointments and the intent to arrive very early to their future appointments. Combined with the qualitative results, this study suggests that most patients are motivated to be on time, in some cases seeing the idea of lateness as a contradiction of their own self-identity. The behavioral causes and implications of the findings are explained using the concept of Fear Appeals and the Protection Motivation Theory (PMT).Item Screening, referral, and participation in a weight management program implemented in five CHCs(Johns Hopkins University Press, 2010-05) Clark, Daniel; Chrysler, Lisa; Perkins, Anthony; Keith, Nicole R.; Willis, Deanna R.; Abernathy, Greg; Smith, Faye; Department of Medicine, IU School of MedicineCommunity health centers have the potential to lessen obesity. We conducted a retrospective evaluation of a quality improvement program that included electronic body mass index (BMI) screening with provider referral to an in-clinic lifestyle behavior change counselor with weekly nutrition and exercise classes. There were 26,661 adult patients seen across five community health centers operating the weight management program. There were 23,593 (88%) adult patients screened, and 12,487 (53%) of these patients were overweight or obese (BMI >or=25). Forty percent received a provider referral, 15.6% had program contact, and 2.1% had more than 10 program contacts. A mean weight loss of seven pounds was observed among those patients with more than 10 program contacts. No significant weight change was observed in patients with less contact. Achieving public health impact from guideline recommended approaches to CHC-based weight management will require considerable improvement in patient and provider participation.Item The pneumonia severity index: Assessment and comparison to popular machine learning classifiers(Elsevier, 2022) Wang , Dawei; Willis, Deanna R.; Yih, Yuehwern; Medicine, School of MedicineIntroduction: Pneumonia is the top communicable cause of death worldwide. Accurate prognostication of patient severity with Community Acquired Pneumonia (CAP) allows better patient care and hospital management. The Pneumonia Severity Index (PSI) was developed in 1997 as a tool to guide clinical practice by stratifying the severity of patients with CAP. While the PSI has been evaluated against other clinical stratification tools, it has not been evaluated against multiple classic machine learning classifiers in various metrics over large sample size. Methods: In this paper, we evaluated and compared the prediction performance of nine classic machine learning classifiers with PSI over 34,720 adult (age 18+) patient records collected from 749 hospitals from 2009 to 2018 in the United States on Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) and Average Precision (Precision-Recall AUC). Results: Machine learning classifiers, such as Random Forest, provided a statistically highly(p < 0.001) significant improvement (∼33% in PR AUC and ∼6% in ROC AUC) compared to PSI and required only 7 input values (compared to 20 parameters used in PSI). Discussion: Because of its ease of use, PSI remains a very strong clinical decision tool, but machine learning classifiers can provide better prediction accuracy performance. Comparing prediction performance across multiple metrics such as PR AUC, instead of ROC AUC alone can provide additional insight.