Browsing by Subject "Community health centers"
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Item Application for Public Health Accreditation Among US Local Health Departments in 2013 to 2019: Impact of Service and Activity Mix(American Public Health Association, 2021) Leider, Jonathon P.; Kronstadt, Jessica; Yeager, Valerie A.; Hall, Kellie; Saari, Chelsey K.; Alford, Aaron; Tremmel Freeman, Lori; Kuehnert, Paul; Health Policy and Management, School of Public HealthObjectives: To examine correlates of applying for accreditation among small local health departments (LHDs) in the United States through 2019. Methods: We used administrative data from the Public Health Accreditation Board (PHAB) and 2013, 2016, and 2019 Profile data from the National Association of County and City Health Officials to examine correlates of applying for PHAB accreditation. We fit a latent class analysis (LCA) to characterize LHDs by service mix and size. We made bivariate comparisons using the t test and Pearson χ2. Results: By the end of 2019, 126 small LHDs had applied for accreditation (8%). When we compared reasons for not pursuing accreditation, we observed a difference by size for perceptions that standards exceeded LHD capacity (47% for small vs 22% for midsized [P < .001] and 0% for large [P < .001]). Conclusions: Greater funding support, considering differing standards by LHD size, and recognition that service mix might affect practicality of accreditation are all relevant considerations in attempting to increase uptake of accreditation for small LHDs. Public Health Implications: Overall, small LHDs represented about 60% of all LHDs that had not yet applied to PHAB.Item Exploring the Influence of Sociodemographic Characteristics on the Utilization of Maternal Health Services: A Study on Community Health Centers Setting in Province of Jambi, Indonesia(MDPI, 2022-07-11) Herwansyah, Herwansyah; Czabanowska, Katarzyna; Kalaitzi, Stavroula; Schröder-Bäck, Peter; Health Policy and Management, Richard M. Fairbanks School of Public HealthThe Maternal Mortality Ratio in Indonesia has remained high, making it a national priority. The low utilization of maternal health services at community health centers is considered to be one of the reasons for poor maternal health status. This study aims to assess the influence of sociodemographic factors on utilization of maternal health services. The analysis was completed using binary and logistic regression to examine the association between sociodemographic variables and maternal health services utilization. A total of 436 women participated in the survey. In the multivariable analysis, age, education, ethnicity, parity status, distance to health centers and insurance ownership were associated with the utilization of maternal health services. Ethnicity (OR, 2.1; 95% confidence interval, 1.4-3.3) and distance to the CHC (OR, 0.5; 95% confidence interval, 0.3-0.8) were significantly associated with ANC visits. The association between parity and place of delivery was statistically significant (OR, 0.8; 95% confidence interval, 0.5-1.4). A positive association between basic health insurance ownership and PNC services was reported (OR, 0.3; 95% confidence interval, 0.1-0.6). Several sociodemographic factors were positively associated with the utilization of maternal health services at the CHCs. The required measures to improve the utilization of maternal health services at the CHCs level have to take into consideration the sociodemographic factors of reproductive age women.Item Hypothesis Generation Using Network Structures on Community Health Center Cancer-Screening Performance(Elsevier, 2015-10) Carney, Timothy Jay; Morgan, Geoffrey P.; Jones, Josette; McDaniel, Anna M.; Weaver, Michael; Weiner, Bryan; Haggstrom, David A.; BioHealth Informatics, School of Informatics and ComputingRESEARCH OBJECTIVES: Nationally sponsored cancer-care quality-improvement efforts have been deployed in community health centers to increase breast, cervical, and colorectal cancer-screening rates among vulnerable populations. Despite several immediate and short-term gains, screening rates remain below national benchmark objectives. Overall improvement has been both difficult to sustain over time in some organizational settings and/or challenging to diffuse to other settings as repeatable best practices. Reasons for this include facility-level changes, which typically occur in dynamic organizational environments that are complex, adaptive, and unpredictable. This study seeks to understand the factors that shape community health center facility-level cancer-screening performance over time. This study applies a computational-modeling approach, combining principles of health-services research, health informatics, network theory, and systems science. METHODS: To investigate the roles of knowledge acquisition, retention, and sharing within the setting of the community health center and to examine their effects on the relationship between clinical decision support capabilities and improvement in cancer-screening rate improvement, we employed Construct-TM to create simulated community health centers using previously collected point-in-time survey data. Construct-TM is a multi-agent model of network evolution. Because social, knowledge, and belief networks co-evolve, groups and organizations are treated as complex systems to capture the variability of human and organizational factors. In Construct-TM, individuals and groups interact by communicating, learning, and making decisions in a continuous cycle. Data from the survey was used to differentiate high-performing simulated community health centers from low-performing ones based on computer-based decision support usage and self-reported cancer-screening improvement. RESULTS: This virtual experiment revealed that patterns of overall network symmetry, agent cohesion, and connectedness varied by community health center performance level. Visual assessment of both the agent-to-agent knowledge sharing network and agent-to-resource knowledge use network diagrams demonstrated that community health centers labeled as high performers typically showed higher levels of collaboration and cohesiveness among agent classes, faster knowledge-absorption rates, and fewer agents that were unconnected to key knowledge resources. Conclusions and research implications: Using the point-in-time survey data outlining community health center cancer-screening practices, our computational model successfully distinguished between high and low performers. Results indicated that high-performance environments displayed distinctive network characteristics in patterns of interaction among agents, as well as in the access and utilization of key knowledge resources. Our study demonstrated how non-network-specific data obtained from a point-in-time survey can be employed to forecast community health center performance over time, thereby enhancing the sustainability of long-term strategic-improvement efforts. Our results revealed a strategic profile for community health center cancer-screening improvement via simulation over a projected 10-year period. The use of computational modeling allows additional inferential knowledge to be drawn from existing data when examining organizational performance in increasingly complex environments.Item Large-Scale Data Mining to Optimize Patient-Centered Scheduling at Health Centers(Springer, 2018-09-04) Kunjan, Kislaya; Wu, Huanmei; Toscos, Tammy R.; Doebbeling, Bradley N.; BioHealth Informatics, School of Informatics and ComputingPatient-centered appointment access is of critical importance at community health centers (CHCs) and its optimal implementation entails the use of advanced data analytics. This study seeks to optimize patient-centered appointment scheduling through data mining of Electronic Health Record/Practice Management (EHR/PM) systems. Data was collected from different EHR/PM systems in use at three CHCs across the state of Indiana and integrated into a multidimensional data warehouse. Data mining was performed using decision tree modeling, logistic regression, and visual analytics combined with n-gram modeling to derive critical influential factors that guide implementation of patient-centered open-access scheduling. The analysis showed that appointment adherence was significantly correlated with the time dimension of scheduling, with lead time for an appointment being the most significant predictor. Other variables in the time dimension such as time of the day and season were important predictors as were variables tied to patient demographic and clinical characteristics. Operationalizing the findings for selection of open-access hours led to a 16% drop in missed appointment rates at the interventional health center. The study uncovered the variability in factors affecting patient appointment adherence and associated open-access interventions in different health care settings. It also shed light on the reasons for same-day appointment through n-gram-based text mining. Optimizing open-access scheduling methods require ongoing monitoring and mining of large-scale appointment data to uncover significant appointment variables that impact schedule utilization. The study also highlights the need for greater "in-CHC" data analytic capabilities to re-design care delivery processes for improving access and efficiency.Item A Multidimensional Data Warehouse for Community Health Centers(2015-11-05) Kunjan, Kislaya; Toscos, Tammy; Turkcan, Ayten; Doebbeling, Brad N.; BioHealth Informatics, School of Informatics and ComputingCommunity health centers (CHCs) play a pivotal role in healthcare delivery to vulnerable populations, but have not yet benefited from a data warehouse that can support improvements in clinical and financial outcomes across the practice. We have developed a multidimensional clinic data warehouse (CDW) by working with 7 CHCs across the state of Indiana and integrating their operational, financial and electronic patient records to support ongoing delivery of care. We describe in detail the rationale for the project, the data architecture employed, the content of the data warehouse, along with a description of the challenges experienced and strategies used in the development of this repository that may help other researchers, managers and leaders in health informatics. The resulting multidimensional data warehouse is highly practical and is designed to provide a foundation for wide-ranging healthcare data analytics over time and across the community health research enterprise.Item Recommendations to Address Barriers to Patient Portal Use Among Persons With Diabetes Seeking Care at Community Health Centers: Interview Study With Patients and Health Care Providers(JMIR, 2024-09-16) Akyirem, Samuel; Wagner, Julie; Chen, Helen N.; Lipson, Joanna; Minchala, Maritza; Cortez, Karina; Whittemore, Robin; Epidemiology, School of Public HealthBackground: Community health centers (CHCs) are safety-net health care facilities in the United States that provide care for a substantial number of low-income, non-English speaking adults with type 2 diabetes (T2D). Whereas patient portals have been shown to be associated with significant improvements in diabetes self-management and outcomes, they remain underused in CHCs. In addition, little is known about the specific barriers to and facilitators of patient portal use in CHCs and strategies to address the barriers. Objective: The objectives of this qualitative study were to explore the barriers to and facilitators of the use of patient portals for managing diabetes in 2 CHCs from the perspective of adults with T2D and clinicians (community health workers, nurses, nurse practitioners, and physicians) and to make recommendations on strategies to enhance use. Methods: A qualitative description design was used. A total of 21 participants (n=13, 62% clinicians and n=8, 38% adults with T2D) were purposively and conveniently selected from 2 CHCs. Adults with T2D were included if they were an established patient of one of the partner CHCs, aged ≥18 years, diagnosed with T2D ≥6 months, and able to read English or Spanish. Clinicians at our partner CHCs who provided care or services for adults with T2D were eligible for this study. Semistructured interviews were conducted in either Spanish or English based on participant preference. Interviews were audio-recorded and transcribed. Spanish interviews were translated into English by a bilingual research assistant. Data were collected between October 5, 2022, and March 16, 2023. Data were analyzed using a rapid content analysis method. Standards of rigor were implemented. Results: Themes generated from interviews included perceived usefulness and challenges of the patient portal, strategies to improve patient portal use, and challenges in diabetes self-management. Participants were enthusiastic about the potential of the portal to improve access to health information and patient-clinician communication. However, challenges of health and technology literacy, maintaining engagement, and clinician burden were identified. Standardized implementation strategies were recommended to raise awareness of patient portal benefits, provide simplified training and technology support, change clinic workflow to triage messages, customize portal notification messages, minimize clinician burden, and enhance the ease with which blood glucose data can be uploaded into the portal. Conclusions: Adults with T2D and clinicians at CHCs continue to report pervasive challenges to patient portal use in CHCs. Providing training and technical support on patient portal use for patients with low health literacy at CHCs is a critical next step. Implementing standardized patient portal strategies to address the unique needs of patients receiving care at CHCs also has the potential to improve health equity and health outcomes associated with patient portal use.Item Twelve-Month Outcomes of the First 1000 Days Program on Infant Weight Status(American Academy of Pediatrics, 2021) Taveras, Elsie M.; Perkins, Meghan E.; Boudreau, Alexy Arauz; Blake-Lamb, Tiffany; Matathia, Sarah; Kotelchuck, Milton; Luo, Mandy; Price, Sarah N.; Roche, Brianna; Cheng, Erika R.; Pediatrics, School of MedicineObjectives: To examine the effects of the First 1000 Days intervention on the prevalence of infant overweight and maternal postpartum weight retention and care. Methods: Using a quasi-experimental design, we evaluated the effects of the First 1000 Days program among 995 term, low-income infants and their mothers receiving care in 2 intervention community health centers and 650 dyads in 2 comparison health centers. The program includes staff training, growth tracking, health and behavioral screening, patient navigation, text messaging, educational materials, and health coaching. Comparison centers implemented usual care. Infant outcomes were assessed at 6 and 12 months, including weight-for-length z score and overweight (weight for length ≥97.7th percentile). We also examined maternal weight retention and receipt of care 6 weeks' post partum. Results: The mean birth weight was 3.34 kg (SD 0.45); 57% of infants were Hispanic; 66% were publicly insured. At 6 months, infants had lower weight-for-length z scores (β: -.27; 95% confidence interval [CI]: -.39 to -.15) and lower odds of overweight (adjusted odds ratio [OR]: 0.46; 95% CI: 0.28 to 0.76) than infants in comparison sites; differences persisted at 12 months (z score β: -.18; 95% CI: -.30 to -.07; adjusted OR for overweight: 0.60; 95% CI: 0.39 to 0.92). Mothers in the intervention sites had modestly lower, but nonsignificant, weight retention at 6 weeks' post partum (β: -.51 kg; 95% CI: -1.15 to .13) and had higher odds (adjusted OR: 1.50; 95% CI: 1.16 to 1.94) of completing their postpartum visit compared with mothers in the comparison sites. Conclusions: An early-life systems-change intervention combined with coaching was associated with improved infant weight status and maternal postpartum care.Item Unmet information needs of clinical teams delivering care to complex patients and design strategies to address those needs(Oxford University Press, 2020-05-01) Cohen, Deborah J.; Wyte-Lake, Tamar; Dorr, David A.; Gold, Rachel; Holden, Richard J.; Koopman, Richelle J.; Colasurdo, Joshua; Warren, Nathaniel; Medicine, School of MedicineObjectives: To identify the unmet information needs of clinical teams delivering care to patients with complex medical, social, and economic needs; and to propose principles for redesigning electronic health records (EHR) to address these needs. Materials and methods: In this observational study, we interviewed and observed care teams in 9 community health centers in Oregon and Washington to understand their use of the EHR when caring for patients with complex medical and socioeconomic needs. Data were analyzed using a comparative approach to identify EHR users' information needs, which were then used to produce EHR design principles. Results: Analyses of > 300 hours of observations and 51 interviews identified 4 major categories of information needs related to: consistency of social determinants of health (SDH) documentation; SDH information prioritization and changes to this prioritization; initiation and follow-up of community resource referrals; and timely communication of SDH information. Within these categories were 10 unmet information needs to be addressed by EHR designers. We propose the following EHR design principles to address these needs: enhance the flexibility of EHR documentation workflows; expand the ability to exchange information within teams and between systems; balance innovation and standardization of health information technology systems; organize and simplify information displays; and prioritize and reduce information. Conclusion: Developing EHR tools that are simple, accessible, easy to use, and able to be updated by a range of professionals is critical. The identified information needs and design principles should inform developers and implementers working in community health centers and other settings where complex patients receive care.