Bridging the Location Gap: Physician Perspectives of Physician-Pharmacist Collaboration in Patient Care (BRIDGE Phase II)

Background: To optimize patient outcomes, the patient-centred medical home model emphasizes comprehensive team-based care. Pharmacists are qualified to enhance appropriate medication use and help improve patient outcomes through provision of medication therapy management (MTM) services. To optimally provide MTM, pharmacists must effectively collaborate with physicians. This study explored factors that influence pharmacist-physician collaboration. Methods and Findings: A convenience sample of five physicians participated in semi-structured interviews and the resulting data were analyzed using qualitative methods. Transcripts of the interviews were independently coded for themes by two researchers. Five themes emerged: trustworthiness, role specification, relationship initiation, effects on practice, and professional awareness/expectations. Conclusions: Overall interviewees spoke positively about pharmacists; however, when discussing collaboration, they spoke almost exclusively about pharmacists within their clinic. Since most pharmacists practice outside of clinics, bridging the location gap is imperative for collaboration. In addition, physicians lacked an overall understanding of pharmacists’ training and clinical capacity. This may inhibit pharmacists from participating to their full professional capability within integrated healthcare teams. One approach to resolve this lack of physician understanding of pharmacists’ role and value may be to co-educate health professional students. Further research is needed to explore ways to improve interprofessional collaborative care

Trends in Opioid Use in Pediatric Patients in US Emergency Departments From 2006 to 2015

Importance The use of opioids to treat pain in pediatric patients has been viewed as necessary; however, this practice has raised concerns regarding opioid abuse and the effects of opioid use. To effectively adjust policy regarding opioids in the pediatric population, prescribing patterns must be better understood. Objective To evaluate opioid prescribing patterns in US pediatric patients and factors associated with opioid prescribing. Design, Setting, and Participants This cross-sectional study used publicly available data from the National Hospital Ambulatory Medical Care Survey from January 1, 2006, to December 31, 2015. Analysis included the use of bivariate and multivariate models to evaluate factors associated with opioid prescribing. Practitioners from emergency departments throughout the United States were surveyed, and data were collected using a representative sample of visits to hospital emergency departments. The study analyzed all emergency department visits included in the National Hospital Ambulatory Medical Care Survey for patients younger than 18 years. All statistical analysis was completed in June of 2018 and updated upon receiving reviewer feedback in October of 2018. Exposures Information regarding participants’ medications was collected at time of visit. Participants who reported taking 1 or more opioids were identified. Main Outcomes and Measures Evaluation of opioid prescribing patterns across demographic factors and pain diagnoses. Results A total of 69 152 visits with patients younger than 18 years (32 727 female) were included, which were extrapolated by the National Hospital Ambulatory Medical Care Survey to represent 293 528 632 visits nationwide, with opioid use representing 21 276 831 (7.25%) of the extrapolated visits. Factors including geographic region, race, age, and payment method were associated with statistically significant differences in opioid prescribing. The Northeast reported an opioid prescribing rate of 4.69% (95% CI, 3.69%-5.70%) vs 8.84% (95% CI, 6.82%-10.86%) in the West (P = .004). White individuals were prescribed an opioid at 8.11% (95% CI, 7.23%-8.99%) of visits vs 5.31% (95% CI, 4.31%-6.32%) for nonwhite individuals (P \u3c .001). Those aged 13 to 17 years were significantly more likely to receive opioid prescriptions (16.20%; 95% CI, 14.29%-18.12%) than those aged 3 to 12 years (6.59%; 95% CI, 5.75%-7.43%) or 0 to 2 years (1.70%; 95% CI, 1.42%-1.98%). Patients using Medicaid for payment were less likely to receive an opioid than those using private insurance (5.47%; 95% CI, 4.79%-6.15% vs 9.73%; 95% CI, 8.56%-10.90%). There was no significant difference in opioid prescription across sexes. Opioid prescribing rates decreased when comparing 2006 to 2010 with 2011 to 2015 (8.23% [95% CI, 6.75%-9.70%] vs 6.30% [95% CI, 5.44%-7.17%]; P \u3c .001); however, opioid prescribing rates remained unchanged in specific pain diagnoses, including pelvic and back pain. Conclusions and Relevance This research demonstrated an overall reduction in opioid use among pediatric patients from 2011 to 2015 compared with the previous 5 years; however, there appear to be variations in factors associated with opioid prescribing. The association of location, race, payment method, and pain diagnoses with rates of prescribing of opioids suggests areas of potential quality improvement and further research

Conservative treatment and outcome of upper cervical spine fractures in young children: A STROBE-compliant case series.

Cervical spine (C-spine) fractures in young children are very rare, and little information on treatment modalities and functional, radiographic, and patient-reported outcome exists. In this 2-center, retrospective case series, we assessed subjective and functional mid-term outcomes in children aged ≤5 years whose C-spine fractures were treated nonoperatively.Between 2000 and 2018, 6 children (median age at injury: 23.5 months; range: 16-31 months) with C1 or C2 injuries were treated with Minerva cast/brace or soft collar brace at 1 of the 2 study centers. Two patients suffered C1 fractures, and 4 patients had lysis of the odontoid synchondrosis. Overall, 3 children had sustained polytrauma. One child died due to the consequences of massive head injury.For the primary outcome parameter, we recorded subjective symptoms such as pain and functional restrictions due to the sequelae of C-spine injuries at follow-up.Based on medical records, we also assessed the causes of injury, diagnostic procedures, treatments and complications, and time to fracture consolidation.Median follow-up of the 5 surviving children was 51 months (range: 36-160 months). At the latest follow-up, 4 of 5 children did not complain of any pain. One child who sustained an open head injury in combination with a subluxation of the odontoid and undisplaced fracture of the massa lateralis reported occasional headache. All patients experienced complete fracture healing and normal range of motion of the cervical spine.Median duration of cast/brace treatment was 8.5 weeks. Fracture healing was confirmed by computed tomography in all patients.All C-spine injuries were managed with either Minerva cast/Halo brace or soft collar brace without complications.In our retrospective case series, nonoperative treatment of atlas fractures and dislocations or subluxations of the odontoid in young children using Minerva casts or prefabricated Halo braces resulted in good subjective and functional outcomes at mid-term. We observed no complications of conservative treatment of C1 and C2 injuries in young children

Relationship between self-efficacy and patient knowledge on adherence to oral contraceptives using the Morisky Medication Adherence Scale (MMAS-8)

BackgroundPreconception care, including family planning, is a vital component of healthcare for women of reproductive age. An average female spends the majority of her reproductive life trying to prevent a pregnancy. In order to prevent unintended pregnancy, women often rely on the use of hormonal contraceptives. In the United States, the majority of hormonal contraceptive users are prescribed oral contraceptive pills (OCPs). Reduced adherence to OCPs decreases their ability to prevent pregnancy. The study aimed to measure OCP adherence among female college students, and explore the relationship between OCP adherence, knowledge, and self-efficacy. MethodsThis cross-sectional study recruited a random sample of female college students to participate in an online survey. OCP adherence was based on the 8-item Morisky Medication Adherence Scale (MMAS-8). Secondary reporting of medication adherence included participant reports of the number of missed OCP doses in the previous month and typical month of use. ResultsOf the 5000 invited, 1559 (31.3%) completed the survey. Of those responding, 670 (41.3%) reported use of OCPs. A total of 293 (44.3%) OCP users met criteria for low adherence, 241 (36.4%) met criteria for medium adherence, and 128 (19.3%) met criteria for high adherence. Those with high adherence had higher self-efficacy (P \u3c 0.001) and perceived knowledge (p \u3c 0.001). After controlling for other factors, self-efficacy (b = .37) and perceived knowledge (b = .09) remained associated with OCP adherence. ConclusionLess than 20% of respondents met the criteria for high adherence to OCPs. Self-efficacy and knowledge were associated with higher OCP adherence. Targeted interventions from healthcare providers, health educators, and other adherence related media to increase the knowledge and self-efficacy of patients using OCPs may improve adherence rates. Additional research is needed to evaluate the impact of innovative interventions focused on social and behavioral patient factors, like knowledge and self-efficacy, on adherence to OCPs

Development of the Adherence Predictive Index (API) for Medication Taking

The objective for this study was to explore if characteristics of personality type using the Preferred Communication Style Questionnaire, in concert with the demographic characteristics of age, education, and race/ethnicity, are associated with, and help predict, individuals’ medication adherence behavior. Data were collected via an on-line survey, sent to a sample of adults residing in the United States, between April 28 and June 22, 2015. Out of 26,173 responses to the survey, 16,736 reported taking one or more medications and were eligible for inclusion in this study. The development of the Adherence Predictive Index (API) used mean Morisky Medication Adherence Scale (MMAS-8) scores for each of eight personality types as a starting point. API scores were calculated by adding or subtracting specific values to each group’s mean MMAS-8 score based on personality type, age, education and race/ethnicity characteristics which were demonstrated to have significant effects on adherence. The weighting system was informed by linear regression, logistic regression, personality type literature, researcher experience, and previous qualitative and quantitative research. The resultant score was converted to an API score that ranged from 1 to 5 so that it would be feasible for health care providers to understand and use. The findings showed that an Adherence Predictive Index (API) could be developed based upon a relatively small number of questions that focus on personality type and generational, educational, and cultural experiences. It was developed in order to be a component of a comprehensive program that has the goals of (1) identifying and describing specific behavioral strategies individuals are most likely to successfully employ, (2) motivating patients by using their preferred communication style, and (3) predicting each patient’s propensity to adhere. Future research is needed to evaluate the index’s validity, sensitivity, and effectiveness in actual practice compared with other risk indices

Development of the Adherence Predictive Index (API) for Medication Taking

The objective for this study was to explore if characteristics of personality type using the Preferred Communication Style Questionnaire, in concert with the demographic characteristics of age, education, and race/ethnicity, are associated with, and help predict, individuals’ medication adherence behavior. Data were collected via an on-line survey, sent to a sample of adults residing in the United States, between April 28 and June 22, 2015. Out of 26,173 responses to the survey, 16,736 reported taking one or more medications and were eligible for inclusion in this study. The development of the Adherence Predictive Index (API) used mean Morisky Medication Adherence Scale (MMAS-8) scores for each of eight personality types as a starting point. API scores were calculated by adding or subtracting specific values to each group’s mean MMAS-8 score based on personality type, age, education and race/ethnicity characteristics which were demonstrated to have significant effects on adherence. The weighting system was informed by linear regression, logistic regression, personality type literature, researcher experience, and previous qualitative and quantitative research. The resultant score was converted to an API score that ranged from 1 to 5 so that it would be feasible for health care providers to understand and use. The findings showed that an Adherence Predictive Index (API) could be developed based upon a relatively small number of questions that focus on personality type and generational, educational, and cultural experiences. It was developed in order to be a component of a comprehensive program that has the goals of (1) identifying and describing specific behavioral strategies individuals are most likely to successfully employ, (2) motivating patients by using their preferred communication style, and (3) predicting each patient’s propensity to adhere. Future research is needed to evaluate the index’s validity, sensitivity, and effectiveness in actual practice compared with other risk indices.   Type: Original Researc

Evaluating Factors Impacting Medication Adherence Among Rural, Urban, and Suburban Populations

Purpose: To evaluate differences in prescription medication adherence rates, as well as influencing factors, in rural and urban adults. Methods: This is a retrospective analysis of the 2015 National Consumer Survey on the Medication Experience and Pharmacists’ Role. A total of 26,173 participants completed the survey and provided usable data. Participants using between 1 and 30 prescription medications and living more than 0 miles and up to 200 miles from their nearest pharmacy were selected for the study, resulting in a total of 15,933 participants. Data from the 2010 US Census and Rural Health Research Center were used to determine the population density of each participant’s ZIP code. Participant adherence to reported chronic medications was measured based on the 8-item Morisky Medication Adherence Scale (MMAS-8). Findings: Overall adherence rates did not differ significantly between rural and urban adults with average adherence based on MMAS-8 scores of 5.58 and 5.64, respectively (P = .253). Age, income, education, male sex, and white race/ethnicity were associated with higher adherence rates. While the overall adherence rates between urban and rural adults were not significantly different, the factors that influenced adherence varied between age-specific population density groupings. Conclusion: These analyses suggest that there is no significant difference in adherence between rural and urban populations; however, the factors contributing to medication adherence may vary based on age and population density. Future adherence intervention methods should be designed with consideration for these individualized factors

Evaluating Opioid Dispensing Rates among Pediatrics and Young Adults based on CURES Data Reporting in California from 2015–2019

Background Receipt of opioid prescriptions in pediatric and young adult patients may be a risk factor for future opioid misuse. Data from prescription drug monitoring programs provide insight on outpatient opioid use. In our study, we analyzed the opioid dispensing rates for pediatrics and young adults in California. Methods A secondary analysis was performed from 2015–2019 using Controlled Utilization Review and Evaluation System data. This database provides dispensing data of controlled substances in California. Patients younger than 25 years who were prescribed opiates were analyzed by county. We further divided them into two groups (children: ≤14 years; adolescents and young adult: 15–24 years). Descriptive statistics and heat maps were used to illustrate the trends in opioid usage among different age groups. Results The overall percentages for the number of opioids being dispensed to patients aged \u3c25 years have decreased over the past four years. In 2015, 6 out of 58 counties in California were considered “high-rate” with \u3e2.9% of opioids dispensed to patients younger than 25 years old; in 2019, this number reduced to zero. Patients 25 and older received a higher proportion of opioids compared to younger populations; in 2019, 35.91% of opioids were dispensed to patients 45–64, and 8.92% to patients younger than 25. Conclusion Pediatric opioid prescriptions have declined over the recent years. However, a high degree of variability of prescription rates between demographic counties was noted. More studies are warranted in order to understand this discrepancy in opioid prescribing among pediatric and young adult patients

Racial and Ethnic Disparities in Opioid Use for Adolescents at US Emergency Departments

Background Racial/ethnic disparities in the use of opioids to treat pain disorders have been previously reported in the emergency department (ED). Further research is needed to better evaluate the impact race/ethnicity may have on the use of opioids in adolescents for the management of pain disorders in the ED. Methods This was a cross-sectional study using data from the National Hospital Ambulatory Medical Care Survey from 2006 to 2016. Multivariate models were used to evaluate the role of race/ethnicity in the receipt of opioid agonists while in the ED. All ED visits with patients aged 11–21 years old were analyzed. Races/ethnicities were stratified as non-Hispanic Whites, non-Hispanic Blacks, and Hispanics. In addition to race, statistical analysis included the following covariates: pain score, pain diagnosis, age, region, sex, and payment method. Results There was a weighted total of 189,256,419 ED visits. Those visits involved 109,826,315 (58%) non-Hispanic Whites, 46,314,977 (24%) non-Hispanic Blacks, and 33,115,127 (18%) Hispanics, with 21.6% (95% CI, 21.1%-22.1), 15.2% (95% CI, 14.6–15.9%), and 17.4% (95% CI, 16.5–18.2%) of those visits reporting use of opioids, respectively. Regardless of age, sex, and region, non-Hispanic Whites received opioids at a higher rate than non-Hispanic Blacks and Hispanics. Based on diagnosis, non-Hispanic Whites received opioids at a higher rate in multiple pain diagnoses. Additionally, non-Hispanic Blacks and Hispanics were less likely to receive an opioid when reporting moderate pain (aOR = 0.738, 95% CI 0.601–0.906, aOR = 0.739, 95% CI 0.578–0.945, respectively) and severe pain (aOR = 0.580, 95% CI 0.500–0.672, aOR = 0.807, 95% CI 0.685–0.951, respectively) compared to non-Hispanic Whites. Conclusions Differences in the receipt of opioid agonists in EDs among the races/ethnicities exist, with more non-Hispanic Whites receiving opioids than their minority counterparts. Non-Hispanic Black women may be an especially marginalized population. Further investigation into sex-based and regional differences are needed

Development of the Adherence Predictive Index (API) for Medication Taking

The objective for this study was to explore if characteristics of personality type using the Preferred Communication Style Questionnaire, in concert with the demographic characteristics of age, education, and race/ethnicity, are associated with, and help predict, individuals’ medication adherence behavior. Data were collected via an on-line survey, sent to a sample of adults residing in the United States, between April 28 and June 22, 2015. Out of 26,173 responses to the survey, 16,736 reported taking one or more medications and were eligible for inclusion in this study. The development of the Adherence Predictive Index (API) used mean Morisky Medication Adherence Scale (MMAS-8) scores for each of eight personality types as a starting point. API scores were calculated by adding or subtracting specific values to each group’s mean MMAS-8 score based on personality type, age, education and race/ethnicity characteristics which were demonstrated to have significant effects on adherence. The weighting system was informed by linear regression, logistic regression, personality type literature, researcher experience, and previous qualitative and quantitative research. The resultant score was converted to an API score that ranged from 1 to 5 so that it would be feasible for health care providers to understand and use. The findings showed that an Adherence Predictive Index (API) could be developed based upon a relatively small number of questions that focus on personality type and generational, educational, and cultural experiences. It was developed in order to be a component of a comprehensive program that has the goals of (1) identifying and describing specific behavioral strategies individuals are most likely to successfully employ, (2) motivating patients by using their preferred communication style, and (3) predicting each patient’s propensity to adhere. Future research is needed to evaluate the index’s validity, sensitivity, and effectiveness in actual practice compared with other risk indices.   Type: Original Researc