A Health Information Technology Protocol to Enhance Colorectal Cancer Screening.

This study addresses barriers to electronic health records-based colorectal cancer screening and follow-up in primary care through the development and implementation of a health information technology protocol.

Evaluation of self-measured blood pressure monitoring in a southern rural West Virginia health system.

INTRODUCTION: At the time of the 2021 Behavioral Risk Factor Surveillance System survey, an estimated 32.3% of adults in the US and nearly half (43.4%, 776 000) of adults in West Virginia (WV) had hypertension. Further, the Interactive Atlas of Heart Disease and Stroke estimates an increase in the percentage of adults with hypertension in the US from 32.3% to 47.0%, with hypertension rates in WV rising as high as 58.7%, indicating a significant public health concern in the community. Hypertension increases the risk of several negative health outcomes, including heart disease and stroke, and leads to increased economic and chronic disease burden. Although certain unmodifiable factors (sex, age, race, ethnicity, and family history) increase the risk of developing hypertension, a healthy lifestyle - including a nutritious diet, maintaining a healthy weight, avoiding nicotine products, and participating in regular moderate physical activity - can decrease the risk of developing hypertension. Self-measured blood pressure (SMBP) monitoring, or home BP monitoring, when integrated with a provider's clinical management approach, is linked to improvements in BP management and control. This study represents a mid-point assessment of a remote SMBP monitoring program implemented by Cabin Creek Health Systems (CCHS), a federally qualified health center, and its impact on BP control. METHODS: CCHS implemented SMBP programming in March 2020 as one element of a developing comprehensive program aimed at reducing uncontrolled hypertension, and therefore chronic disease burden, in its service area and patient population. The project, funded by the Health Resources and Services Administration, continued to February 2023. This report represents a mid-point analysis and was based on the retrospective analysis of de-identified data collected for 234 patients to June 2022, who were assessed for changes in BP between the date of enrollment and the most recently available BP measurement. Patients were enrolled in the SMBP program if they exhibited current or previous indicators of uncontrolled hypertension (systolic ≥140 mmHg and/or diastolic ≥90 mmHg), at the discretion of their provider, and were equipped with an iBloodPressure cellular connected home BP monitoring system, manufactured by Smart Meter. Their BP readings were documented in the integration software TimeDoc Health and electronic health record athenahealth. RESULTS: At the time of enrollment, 201 (86.0%) patients had uncontrolled hypertension, with 116 (49.6%) patients having both uncontrolled systolic (≥140 mmHg) and diastolic (≥90 mmHg) values. At follow-up, the number of patients with uncontrolled hypertension decreased from 201 to 98 (41.9%), with only 36 (15.4%) patients having both uncontrolled systolic and diastolic values. Additionally, 26 (11.1%) patients were in hypertensive crisis at the time of enrollment, and no patients remained in crisis at the time of follow-up. The number of patients with BP values in the controlled range (systolic <140 mmHg and diastolic <90 mmHg) increased from 33 (14.1%) at enrollment to 136 (58.1%) at follow-up. Overall, there was a 44.0% increase in the number of patients with BP values in the controlled range at follow-up, and a concomitant 44.1% decrease in the number of patients in the uncontrolled range. These observations were consistent across multiple demographic indicators, including clinic location, three-digit zip code, and patient sex. CONCLUSION: Systematic implementation of remote BP monitoring, when integrated into clinician workflows, was associated with a substantial reduction in the number of patients with uncontrolled hypertension in this rural federally qualified health center. Further, CCHS was successful in implementing a remote SMBP monitoring program in a community challenged with transportation insecurity, and poor cellular and broadband access, of which lessons learned are applicable to other health systems interested in pursuing comparable efforts.

Using Health Information Technology to Create Pathways for Hepatitis C Treatment and Cure in West Virginia.

This case study describes use of health information technology for enhanced team-based care and care coordination between primary care providers and infectious disease specialists for curing and eventually eliminating hepatitis C in West Virginia. This program, the West Virginia Hepatitis Academic Mentoring Partnership, aims to improve outcomes of West Virginians with chronic hepatitis C infection by training and supporting primary care providers to screen, diagnose, evaluate, treat, cure, and follow patients in the community rather than referring them to distant specialists with long wait times. This initiative supports health equity by increasing access to quality care in severely under-resourced rural areas. Primary care providers engage with hepatitis C experts in a web-based training and mentoring process, combined with informatics training in use of a customized Research Electronic Data Capture (REDCAP) platform for secure data tracking and bidirectional communication. This use of an informatics platform available to all partners supports shared decision-making between primary care providers and specialists, fostering a primary care learning network for improved hepatitis C care in West Virginia.

Informatics-Supported Diabetes Prevention Programming in West Virginia.

Addressing diabetes, prediabetes, and related health conditions such as high blood pressure, high cholesterol, obesity, and physical inactivity are critical public health priorities for the United States, particularly West Virginia. Preventing chronic conditions through early identification of risk and intervention to reduce risk is essential. Primary care and community-based programs need a more connected informatics system by which they work in tandem to identify, refer, treat, and track target populations. This case study in quality improvement examines the effectiveness of national diabetes prevention programming in West Virginia via the West Virginia Health Connection initiative, which was designed to provide such an informatics structure. Cohort analysis reveals an average weight loss of 13.6 pounds-or 6.3 percent total body weight loss-per person. These changes represent decreased risk of diabetes incidence and increased healthcare savings. Lessons learned are applicable to other areas aiming to build and sustain a data-informed health analytics network.

Leveraging Electronic Health Records Data for Enhanced Colorectal Cancer Screening Efforts.

Introduction: Colorectal cancer is the third most common type of cancer in the United States for men and women combined. While the current threat of disease nationally is significant, the majority of colorectal cancer cases and deaths could be prevented through established screening tests and guidelines. Within the Appalachian region and West Virginia in particular, colorectal cancer is a significant public health problem. A more systematic, comprehensive approach to preventing and controlling cancer is essential. Methods: Through the West Virginia Program to Increase Colorectal Cancer Screening, primary care systems across the state received data-informed practice facilitation designed to increase screening rates. Results: Year-1 cohort health systems had an overall baseline screening rate of 28.4% during calendar year 2014. This rate increased and remained steady during the three follow-up measurement time periods, with a rate of 49.5% during calendar year 2018. This increase is notably greater than comparable health systems not part of the initiative. Implications: Lessons learned in increasing colorectal cancer screening rates are applicable to other priority health needs as well.

An Electronic Health Record Data-driven Model for Identifying Older Adults at Risk of Unintentional Falls.

Screening for risk of unintentional falls remains low in the primary care setting because of the time constraints of brief office visits. National studies suggest that physicians caring for older adults provide recommended fall risk screening only 30 to 37 percent of the time. Given prior success in developing methods for repurposing electronic health record data for the identification of fall risk, this study involves building a model in which electronic health record data could be applied for use in clinical decision support to bolster screening by proactively identifying patients for whom screening would be beneficial and targeting efforts specifically to those patients. The final model, consisting of priority and extended measures, demonstrates moderate discriminatory power, indicating that it could prove useful in a clinical setting for identifying patients at risk of falls. Focus group discussions reveal important contextual issues involving the use of fall-related data and provide direction for the development of health systems-level innovations for the use of electronic health record data for fall risk identification.

Implementation and Outcomes of a Community-Based Pulmonary Rehabilitation Program in Rural Appalachia.

PURPOSE: To report on the implementation and clinical outcomes of a community-based pulmonary rehabilitation program in rural Appalachia. METHODS: Three rural health centers and a large referral hospital worked together to establish pulmonary rehabilitation services based on AACVPR guidelines. Each site hired at least 1 respiratory therapist. To measure clinical outcomes, a retrospective medical record study compared pre- and post-program values for the modified Medical Research Council dyspnea level, 6-minute walk test (6MWT), negative inspiratory force (NIF), respiratory disease knowledge, St George Respiratory Questionnaire (SGRQ), BODE index (body mass index, airflow obstruction, dyspnea and exercise capacity), and smoking status. The percentages of persons completing the program and participating in maintenance exercise after the program were recorded. RESULTS: During the first 20 months of the program, 195 unduplicated persons with qualifying chronic lung diseases started the program. Of these, 111 (57%) completed the program. Mean improvements for all 6 measures were highly significant (P < .001) and compared favorably with published results from hospital-based programs: dyspnea level, -1.2; 6MWT, +259 ft; NIF, +11.3 cm H2O; knowledge test, +1.9; SGRQ, -6.2; BODE index, -1.1. Of the 23 smokers, 5 quit by the end of the program. CONCLUSIONS: Community-based pulmonary rehabilitation in rural health centers is feasible and achieves clinical outcomes similar to programs in large hospitals and academic centers. Furthermore, the addition of respiratory therapists to these primary care teams provides important collateral benefits for the evidence-based care of patients with chronic lung diseases.

Developing Methods of Repurposing Electronic Health Record Data for Identification of Older Adults at Risk of Unintentional Falls.

Nationally, nearly 40 percent of community-dwelling adults age 65 and older fall at least once a year, making unintentional falls the leading cause of both fatal and nonfatal injuries among this age group. Addressing this public health problem in primary care offers promise. However, challenges in incorporating fall risk screening into primary care result in a problem of missed opportunities for screening, counseling, intervention, and ultimately prevention. Given these barriers, this study examines the potential for the innovative use of routinely collected electronic health record data to provide enhanced clinical decision support in busy, often resource-thin primary care environments. Using de-identified data from a sample of West Virginia primary care centers, we find that it is both feasible and worthwhile to repurpose routinely collected data for the purpose of identification of older adults at risk of falls. Searching of both free-text and semistructured data was particularly valuable.

Using i2b2 to Bootstrap Rural Health Analytics and Learning Networks.

We demonstrate that the open-source i2b2 (Informatics for Integrating Biology and the Bedside) data model can be used to bootstrap rural health analytics and learning networks. These networks promote communication and research initiatives by providing the infrastructure necessary for sharing data and insights across a group of healthcare and research partners. Data integration remains a crucial challenge in connecting rural healthcare sites with a common data sharing and learning network due to the lack of interoperability and standards within electronic health records. The i2b2 data model acts as a point of convergence for disparate data from multiple healthcare sites. A consistent and natural data model for healthcare data is essential for overcoming integration issues, but challenges such as those caused by weak data standardization must still be addressed. We describe our experience in the context of building the West Virginia/Kentucky Health Analytics and Learning Network, a collaborative, multi-state effort connecting rural healthcare sites.

Registry-based diabetes risk detection schema for the systematic identification of patients at risk for diabetes in West Virginia primary care centers.

Approximately 466,000 West Virginians, or about 25 percent of the state population, have prediabetes and are at high risk for developing type 2 diabetes. Appropriate lifestyle intervention can prevent or delay the onset of type 2 diabetes if individuals at risk are identified and treated early. The West Virginia Diabetes Prevention and Control Program and the West Virginia University Office of Health Services Research are developing a systematic approach to diabetes prevention within primary care. This study aims to demonstrate the viability of patient registry software for the analysis of disparate electronic health record (EHR) data sets and standardized identification of at-risk patients for early detection and intervention. Preliminary analysis revealed that of 94,283 patients without a documented diagnosis of diabetes or prediabetes, 10,673 (11.3 percent) meet one or more of the risk criteria. This study indicates that EHR data can be repurposed into an actionable registry for prevention. This model supports meaningful use of EHRs, the Patient-Centered Medical Home program, and improved care through enhanced data management.

Identifying patients with hypertension: a case for auditing electronic health record data.

Problems in the structure, consistency, and completeness of electronic health record data are barriers to outcomes research, quality improvement, and practice redesign. This nonexperimental retrospective study examines the utility of importing de-identified electronic health record data into an external system to identify patients with and at risk for essential hypertension. We find a statistically significant increase in cases based on combined use of diagnostic and free-text coding (mean = 1,256.1, 95% CI 1,232.3-1,279.7) compared to diagnostic coding alone (mean = 1,174.5, 95% CI 1,150.5-1,198.3). While it is not surprising that significantly more patients are identified when broadening search criteria, the implications are critical for quality of care, the movement toward the National Committee for Quality Assurance's Patient-Centered Medical Home program, and meaningful use of electronic health records. Further, we find a statistically significant increase in potential cases based on the last two or more blood pressure readings greater than or equal to 140/90 mm Hg (mean = 1,353.9, 95% CI 1,329.9-1,377.9).

Serum gamma-glutamyl transferase level and diabetes mellitus among US adults.

Serum gamma-glutamyl transferase (GGT), a marker of oxidative stress, has been shown to be associated with diabetes mellitus in some population-based studies, but not all. Also, it is not clear if there is a continuous dose-response relationship in this association, or if this association is evident only beyond a particular threshold level of GGT. We examined the association between serum GGT and diabetes mellitus in a representative sample of US adults aged > or = 20 years, in a cross-sectional study involving 7,976 National Health and Nutrition Examination Survey 1999-2002 participants. Diabetes mellitus was defined as a fasting glucose > or = 126 mg/dl, nonfasting glucose > or = 200 mg/dl, or use of oral hypoglycemic medication or insulin (n = 805). Higher serum GGT levels were positively associated with diabetes mellitus, independent of, alcohol consumption, body mass index, hypertension and other confounders. Multivariable odds ratio (95% confidence interval) comparing quartile 4 of GGT (>33 U/L) to quartile 1 (<15 U/L) was 2.33 (1.59-3.41), P-trend < 0.0001. This association persisted in separate analysis among men and women. In nonparametric models, the positive association between serum GGT and diabetes appeared to be present across the full range of GGT, without any threshold effect. Higher serum GGT levels are positively associated with diabetes mellitus.

Electronic patient registries improve diabetes care and clinical outcomes in rural community health centers.

CONTEXT: Diabetes care is challenging in rural areas. Research has shown that the utilization of electronic patient registries improves care; however, improvements generally have been described in combination with other ongoing interventions. The level of basic registry utilization sufficient for positive change is unknown. PURPOSE: The goal of the current study was to examine differential effects of basic registry utilization on diabetes care processes and clinical outcomes according to level of registry use in a rural setting. METHODS: Patients with diabetes (N = 661) from 6 Federally Qualified Health Centers in rural West Virginia were entered into an electronic patient registry. Data from pre- and post-registry were compared among 3 treatment and control groups that had different levels of registry utilization: low, medium, or high (for example, variations in the use of registry-generated progress notes examined at the point-of-care and in the accuracy of registry-generated summary reports to track patients' care). Data included care processes (annual exams, screens to promote wellness, education, and self-management goal-setting) and clinical outcomes (HbA1c, LDL, HDL, cholesterol, triglycerides, blood pressure). FINDINGS: The registry assisted in significantly improving 12 of 13 care processes and 3 of 6 clinical outcomes (HbA1c, LDL, cholesterol) for patients exposed to at least medium levels of registry utilization, but not for the controls. For example, the percent of patients who had received an annual eye exam at follow-up was 11%, 34%, and 38% for the low, medium, and high utilization groups, respectively; only the latter groups improved. CONCLUSIONS: As an initial step to achieving control of diabetes, basic registry utilization may be sufficient to drive improvements in provider-patient care processes and in patient outcomes in rural clinics with few resources.

The C8 health project: design, methods, and participants.

BACKGROUND: The C8 Health Project was created, authorized, and funded as part of the settlement agreement reached in the case of Jack W. Leach, et al. v. E.I. du Pont de Nemours & Company (no. 01-C-608 W.Va., Wood County Circuit Court, filed 10 April 2002). The settlement stemmed from the perfluorooctanoic acid (PFOA, or C8) contamination of drinking water in six water districts in two states near the DuPont Washington Works facility near Parkersburg, West Virginia. OBJECTIVES: This study reports on the methods and results from the C8 Health Project, a population study created to gather data that would allow class members to know their own PFOA levels and permit subsequent epidemiologic investigations. METHODS: Final study participation was 69,030, enrolled over a 13-month period in 2005-2006. Extensive data were collected, including demographic data, medical diagnoses (both self-report and medical records review), clinical laboratory testing, and determination of serum concentrations of 10 perfluorocarbons (PFCs). Here we describe the processes used to collect, validate, and store these health data. We also describe survey participants and their serum PFC levels. RESULTS: The population geometric mean for serum PFOA was 32.91 ng/mL, 500% higher than previously reported for a representative American population. Serum concentrations for perfluorohexane sulfonate and perfluorononanoic acid were elevated 39% and 73% respectively, whereas perfluorooctanesulfonate was present at levels similar to those in the U.S. population. CONCLUSIONS: This largest known population study of community PFC exposure permits new evaluations of associations between PFOA, in particular, and a range of health parameters. These will contribute to understanding of the biology of PFC exposure. The C8 Health Project also represents an unprecedented effort to gather basic data on an exposed population; its achievements and limitations can inform future legal settlements for populations exposed to environmental contaminants.

Maternal diabetes and perinatal outcomes in West Virginia Medicaid enrollees.

Diabetes Mellitus (DM) is a serious problem in West Virginia. Diabetes during pregnancy has been associated with several negative outcomes. This study tested the hypotheses that women who had DM during pregnancy would have more negative perinatal outcomes than those who did not and women with pre-gestational DM would have more negative perinatal outcomes than women with gestational DM. The population included 14,583 mothers enrolled in WV Medicaid in 2001 and 2002. The population was divided according to the presence of DM in the mother, and then sub-divided into pregestational and gestational DM groups. Results showed significant associations between maternal diabetes and occurrence of macrosomia, pre-term delivery and less than optimal one-minute Apgar scores. The pre-gestational DM group had significantly more occurrences of macrosomia, pre-term birth, less than optimal Apgar scores, occurrence of complications of labor and/or delivery and occurrence of congenital anomalies than the gestational DM group.