Applying the Medications at Transitions and Clinical Handoffs Toolkit in a Rural Primary Care Clinic: Implications for Nursing, Patients, and Caregivers.

BACKGROUND: Adequate medication reconciliation is related to patients' safety. Rural populations are at increased risk of adverse drug events due to errors in medication reconciliation and often receiving medical care across multiple health care entities and across long distances with separate electronic medical records. METHODS: This study examined the implementation of Medications at Transitions and Clinical Handoffs Toolkit (MATCH) in a rural primary care clinic and assessed the acceptability and feasibility of implementation. INTERVENTION: MATCH was developed as a workflow process intervention to improve medication reconciliation. RESULTS: Findings from MATCH implementation indicate that the process improved medication reconciliation workflow. A shared definition of current medications across providers and patients was essential. CONCLUSIONS: Empowering patients and caregivers with tools and language to work with providers, particularly nurses, to conduct medication reconciliation during primary care clinic visits is key to improving patient medication reconciliation in rural settings.

Feasibility of a mHealth Approach to Nutrition Counseling in an Appalachian State.

West Virginia is a rural state with an aging population that may experience barriers to accessing nutritional and lifestyle counseling. This study examined feasibility of an online personalized nutrition tracking application, Good Measures (GM), with patients at seven health care clinics throughout the state. Fourteen healthcare providers and 64 patients 18 years or older with a Body Mass Index (BMI) greater than or equal to 30 and access to the Internet were recruited for this 12-week feasibility study. Patient participants logged meals and exercise into the GM application via smart phone, tablet, or computer and virtually engaged with a Registered Dietitian Nutritionist (RDN) in one-on-one sessions. The primary endpoint was to examine feasibility of the program by usage of the application and feedback questions regarding the benefits and challenges of the application. Participants were predominately white (92%) and female (76%). Minimal improvements in weight and systolic blood pressure were found. Participant attitude survey data declined from 4-weeks to 12-weeks of the intervention. Interestingly though, patients in a rural clinic had lesser declines in attitudes than peri-urban participants. Qualitative feedback data identified participants predominately had a positive overall feeling toward the approach. Participants expressed favorability of RDN access, the variety of foods, but did give suggestions for in-person meetings and more updating of the application. Implementing a technology approach to nutrition in rural areas of West Virginia using a mobile application with RDN access may be one strategy to address public health issues such as obesity.

MedManage: The development of a tool to assist medication reconciliation in a rural primary care clinic.

BACKGROUND: Medication reconciliation is a critical step in the health care process to prevent hospital readmission, adverse drug events, and fall prevention. The purpose of the study was to pilot test a medication reconciliation process, MedManage, informed by the Medications at Transitions and Clinical Handoffs (MATCH) toolkit with nursing staff in a rural primary care clinic. METHODS: The research team conducted 38 chart audits of high-risk patients, and preintervention and postintervention were conducted to assess changes in medications reported by patients. The intervention included a chart audit tool and medication reconciliation tool created by the interdisciplinary team, MedManage, were pilot tested in the clinic. CONCLUSIONS: The Use of MedManage resulted in improvements in patient reporting of over-the-counter (82% of patients reported previously unrecorded OTCs), PRN medications (3% unreported), and herbal supplements/vitamins (28% reported previously unrecorded vitamins). IMPLICATIONS FOR PRACTICE: MedManage may be an effective tool to assist clinical nursing staff to attain a more complete and accurate medication list from patients and should be assessed more broadly across rural primary care clinics.

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.

Inappropriate Use of Homeostasis Model Assessment Cutoff Values for Diagnosing Insulin Resistance in Pediatric Studies.

BACKGROUND: Assessing pediatric patients for insulin resistance is one way to identify those who are at a high risk of developing type 2 diabetes mellitus. The homoeostasis model assessment (HOMA) is a measure of insulin resistance based on fasting blood glucose and insulin levels. Although this measure is widely used in research, cutoff values for pediatric populations have not been established. OBJECTIVE: To assess the validity of HOMA cutoff values used in pediatric studies published in peer-reviewed journals. METHODS: Studies published from January 2010 to December 2015 were identified through MEDLINE. Initial screening of abstracts was done to select studies that were conducted in pediatric populations and used HOMA to assess insulin resistance. Subsequent full-text review narrowed the list to only those studies that used a specific HOMA score to diagnose insulin resistance. Each study was classified as using a predetermined fixed HOMA cutoff value or a cutoff that was a percentile specific to that population. For studies that used a predetermined cutoff value, the references cited to provide evidence in support of that cutoff were evaluated. RESULTS: In the 298 articles analyzed, 51 different HOMA cutoff values were used to classify patients as having insulin resistance. Two hundred fifty-five studies (85.6%) used a predetermined fixed cutoff value, but only 72 (28.2%) of those studies provided a reference that supported its use. One hundred ten studies (43%) that used a fixed cutoff either cited a study that did not mention HOMA or provided no reference at all. Tracing of citation history indicated that the most commonly used cutoff values were ultimately based on studies that did not validate their use for defining insulin resistance. CONCLUSION: Little evidence exists to support HOMA cutoff values commonly used to define insulin resistance in pediatric studies. These findings highlight the importance of validating study design elements when training medical students and novice investigators. Using available data to generate population ranges for HOMA would improve its clinical utility.

Use of the triglyceride to HDL cholesterol ratio for assessing insulin sensitivity in overweight and obese children in rural Appalachia.

BACKGROUND: Studies have suggested that triglyceride to HDL-cholesterol ratio (TRG/HDL) is a surrogate marker of insulin resistance (IR), but information regarding its use in pediatric patients is limited. This study investigated the ability of TRG/HDL ratio to assess IR in obese and overweight children. METHODS: The sample consisted of de-identified electronic medical records of patients aged 10-17 years (n=223). Logistic regression was performed using TRG/HDL ratio as a predictor of hyperinsulinemia or IR defined using homeostasis model assessment score. RESULTS: TRG/HDL ratio had limited ability to predict hyperinsulinemia (AUROC 0.71) or IR (AUROC 0.72). Although females had higher insulin levels, male patients were significantly more likely to have hypertriglyceridemia and impaired fasting glucose. CONCLUSIONS: TRG/HDL ratio was not adequate for predicting IR in this population. Gender differences in the development of obesity-related metabolic abnormalities may impact the choice of screening studies in pediatric patients.

Developing Interventions for Overweight and Obese Children using Electronic Health Records Data.

Childhood obesity and the resulting co-morbid conditions have become a massive burden for primary caregivers in West Virginia and across the United States. Building culturally sensitive clinical interventions to meet population health needs presents a multi-factorial challenge. Historically it has been is difficult to accurately assess the demographic characteristics of clinic populations. Fortunately, the use of electronic health records (EHR) has created a major shift in clinical documentation and ability to routinely collect essential demographic and clinical data. While data for Meaningful Use under the Centers for Medicare and Medicaid Services is increasingly used to evaluate clinical care and outcomes, use of EHR data outside of the Meaningful Use umbrella has not received sufficient attention. This study explores use of EHR data beyond Meaningful Use to obtain demographic characteristics of an obese and overweight pediatric population in a rural primary care center for the purpose of informing appropriate, locally relevant intervention strategies. We find that the breadth and depth of information recorded on each patient can collectively provide valuable information to describe and evaluate the clinic population, identify priority areas to address, and measure change over time. Application of EHR data to understand the demographic characteristics of this particular patient population highlights the ability to identify target patient populations, uncover critical patient-level and population-level outcomes, inform intervention development and implementation, and add value to efforts in quality improvement systems transformation. Use of EHR data outside of the Meaningful Use umbrella needs increased attention in primary care.