Impact of Outpatient Pharmacist Dispensing in an Opioid Use Disorder Clinic.

BACKGROUND: Medications for opioid use disorder (MOUD) are effective in reducing opioid deaths, but access can be an issue. Relocating an outpatient pharmacist for weekly buprenorphine dispensing in an outpatient clinic may facilitate coverage for buprenorphine and mitigate access and counseling barriers. OBJECTIVES: To evaluate if staffing an outpatient resident pharmacist to dispense in the buprenorphine clinic had a positive impact on 1) mean cost-per-prescription charged to charity care and 2) basic elements of patient satisfaction with the on-site pharmacist. METHODS: Patient demographics, buprenorphine formulation, insurance type, and uncovered costs were abstracted from dispensing records in the 16 weeks before the pharmacist clinic presence and 16 weeks with the pharmacist present. The difference in insurance types across the two periods was tested using a Chi-square test and the mean uncovered prescription costs charged to charity care for the two periods was compared using an independent samples t-test. A brief survey was administered while the pharmacist was on site to evaluate satisfaction which was analyzed with frequencies of "yes" responses and free-text comments. RESULTS: A total of 38 patients received buprenorphine during both the pre- and post-periods. Once the pharmacist was on-site, more patients used Medicaid or private insurance, decreasing the mean uncovered cost per prescription from $55.00 (sd 68.7) to $36.97 (sd 60.1) p=.002. Patients reported high levels of satisfaction with most reporting they were more likely to ask questions, pick up their prescriptions, and take their medicine with the pharmacist in clinic. CONCLUSIONS: The pharmacist successfully transitioned a portion of prescriptions previously covered by charity care to Medicaid or private insurance. This shift led to a decrease in charity care costs by $2,950.20 and a reduction in the average uncovered cost per prescription. The pharmacist's presence in the clinic appeared to reduce barriers especially related to inconvenience.

Hepatitis C screening in a community pharmacy setting: Patient perspective.

BACKGROUND: Hepatitis C virus (HCV) is an infection of the liver, which contributes to over 15,000 deaths in the United States annually. When treated, HCV has a 90% or greater cure rate, however testing for HCV remains low. OBJECTIVES: To assess patient perspectives on HCV screenings in the community pharmacy setting including awareness of screening, willingness to be screened, barriers to screening, and willingness to pay for HCV screening. METHODS: This study used a cross-sectional survey design. The surveys were distributed by staff at an independent community pharmacy participating in an HCV screening initiative through the state department of public health. Eligible patients were born between 1945 and 1965. Descriptive statistics were calculated for survey variables. Open-ended responses were analyzed for additional context. RESULTS: Fifty-seven surveys were returned and analyzed. The majority of the respondents were White (94%), female (56%), and had some college education (26%). Only 7% were aware that a finger-stick point-of-care test was available and 67% were unaware of the Centers for Disease Control and Prevention (CDC) recommendation for testing. The most frequently reported barrier or hesitation to screening was the patient not thinking they were at risk (29%) followed by uncertainty about cost (14%). Over half of respondents (63%) were either somewhat interested or very interested in testing in a community pharmacy, however, the majority (71%) were not willing to pay or only willing to pay less than $20. CONCLUSIONS: Survey respondents were largely unaware of the recommendations and availability of finger-stick HCV screenings at community pharmacies but many were willing to be tested if low-cost. Providing patient education on the importance of HCV screenings and CDC recommendations may bolster interest in screening.

Machine learning approaches to predict the 1-year-after-initial-AMI survival of elderly patients.

BACKGROUND: While multiple randomized controlled trials (RCTs) are available, their results may not be generalizable to older, unhealthier or less-adherent patients. Observational data can be used to predict outcomes and evaluate treatments; however, exactly which strategy should be used to analyze the outcomes of treatment using observational data is currently unclear. This study aimed to determine the most accurate machine learning technique to predict 1-year-after-initial-acute-myocardial-infarction (AMI) survival of elderly patients and to identify the association of angiotensin-converting- enzyme inhibitors and angiotensin-receptor blockers (ACEi/ARBs) with survival. METHODS: We built a cohort of 124,031 Medicare beneficiaries who experienced an AMI in 2007 or 2008. For analytical purposes, all variables were categorized into nine different groups: ACEi/ARB use, demographics, cardiac events, comorbidities, complications, procedures, medications, insurance, and healthcare utilization. Our outcome of interest was 1-year-post-AMI survival. To solve this classification task, we used lasso logistic regression (LLR) and random forest (RF), and compared their performance depending on category selection, sampling methods, and hyper-parameter selection. Nested 10-fold cross-validation was implemented to obtain an unbiased estimate of performance evaluation. We used the area under the receiver operating curve (AUC) as our primary measure for evaluating the performance of predictive algorithms. RESULTS: LLR consistently showed best AUC results throughout the experiments, closely followed by RF. The best prediction was yielded with LLR based on the combination of demographics, comorbidities, procedures, and utilization. The coefficients from the final LLR model showed that AMI patients with many comorbidities, older ages, or living in a low-income area have a higher risk of mortality 1-year after an AMI. In addition, treating the AMI patients with ACEi/ARBs increases the 1-year-after-initial-AMI survival rate of the patients. CONCLUSIONS: Given the many features we examined, ACEi/ARBs were associated with increased 1-year survival among elderly patients after an AMI. We found LLR to be the best-performing model over RF to predict 1-year survival after an AMI. LLR greatly improved the generalization of the model by feature selection, which implicitly indicates the association between AMI-related variables and survival can be defined by a relatively simple model with a small number of features. Some comorbidities were associated with a greater risk of mortality, such as heart failure and chronic kidney disease, but others were associated with survival such as hypertension, hyperlipidemia, and diabetes. In addition, patients who live in urban areas and areas with large numbers of immigrants have a higher probability of survival. Machine learning methods are helpful to determine outcomes when RCT results are not available.

Warmer Weather and the Risk of Urinary Tract Infections in Women.

PURPOSE: The incidence of urinary tract infections is seasonal, peaking in summer months. One possible mechanism for the observed seasonality of urinary tract infections is warmer weather. MATERIALS AND METHODS: We identified all urinary tract infection cases located in approximately 400 metropolitan statistical areas in the contiguous United States between 2001 and 2015 using the Truven Health MarketScan® databases. A total of 167,078,882 person-years were included in this data set and a total of 15,876,030 urinary tract infection events were identified by ICD-9 code 599.0. Weather data for each metropolitan statistical area and date were obtained from the National Centers for Environmental Information. We computed the mean temperature during the period 0 to 7 days prior to the urinary tract infection diagnosis. We used a quasi-Poisson generalized linear model. The primary outcome was the number of urinary tract infections each day in a metropolitan statistical area in each age group. Covariates considered included age group, day of week, year and the temperature during the previous 7 days. RESULTS: Warmer weather increases the risk of urinary tract infections among women treated in outpatient settings in a dose-response fashion. On days when the prior week's average temperature was between 25 and 30C, the incidence of urinary tract infections was increased by 20% to 30% relative to when the prior week's temperature was 5 to 7.5C. CONCLUSIONS: The incidence of urinary tract infections increases with the prior week's temperature. Our results indicate that warmer weather is a risk factor for urinary tract infections. Furthermore, as temperatures rise, the morbidity attributable to urinary tract infections may increase.

Distance from Home to Research Center: A Barrier to In-Person Visits but Not Treatment Adherence in a Stroke Trial.

BACKGROUND AND PURPOSE: Clinical trials often seek to enroll patients from both urban and rural areas to safeguard the generalizability of results. However, maintaining contact with patients who live away from a recruitment site, including rural areas, can be challenging. In this research we examine the effect of distance between patient and study centers on treatment adherence and retention. METHODS: Secondary analysis of 2,466 participants in the Insulin Resistance Intervention after Stroke trial who were enrolled from research sites in the United States. Driving distance between the zipcodes of patient's reported place of residence and the study center was calculated. Outcome measures were loss to follow-up, completion of annual in-person visits, adherence to preventive therapy, and adherence to study drug in the first 3 years of participation. Logistic regression models were used to adjust for confounders. RESULTS: Distance from residence to research center was not associated with loss to follow-up, adherence to study drug, or adherence to preventive therapy (p > 0.05 for each). However, patients who lived farther from the research center (>120 miles), compared to patients who lived closer (<60 miles), were less likely to complete the second annual in-person visit (62 vs. 81%; adjusted OR 0.48; 95% CI 0.31-0.75) and third visit (53 vs. 75%; adjusted OR 0.44; 95% CI 0.29-0.67). CONCLUSIONS: Distance between patient and study center was an independent predictor of missed in-person visits but not with adherence to study treatment or preventive care.

Team-Based Care with Pharmacists to Improve Blood Pressure: a Review of Recent Literature.

PURPOSE OF REVIEW: We review studies published since 2014 that examined team-based care strategies and involved pharmacists to improve blood pressure (BP). We then discuss opportunities and challenges to sustainment of team-based care models in primary care clinics. RECENT FINDINGS: Multiple studies presented in this review have demonstrated that team-based care including pharmacists can improve BP management. Studies highlighted the cost-effectiveness of a team-based pharmacy intervention for BP control in primary care clinics. Little information was found on factors influencing sustainability of team-based care interventions to improve BP control. Future work is needed to determine the best populations to target with team-based BP programs and how to implement team-based approaches utilizing pharmacists in diverse clinical settings. Future studies need to not only identify unmet clinical needs but also address reimbursement issues and stakeholder engagement that may impact sustainment of team-based care interventions.

The Seasonal Variability of Surgical Site Infections in Knee and Hip Arthroplasty.

BACKGROUND: Surgical site infections (SSIs) after total knee (TKA) and total hip (THA) arthroplasty are devastating to patients and costly to healthcare systems. The purpose of this study is to investigate the seasonality of TKA and THA SSIs at a national level. METHODS: All data were extracted from the National Readmission Database for 2013 and 2014. Patients were included if they had undergone TKA or THA. We modeled the odds of having a primary diagnosis of SSI as a function of discharge date by month, payer status, hospital size, and various patient co-morbidities. SSI status was defined as patients who were readmitted to the hospital with a primary diagnosis of SSI within 30 days of their arthroplasty procedure. RESULTS: There were 760,283 procedures (TKA 424,104, THA 336,179) in our sample. Our models indicate that SSI risk was highest for patients discharged from their surgery in June and lowest for December discharges. For TKA, the odds of a 30-day readmission for SSI were 30.5% higher at the peak compared to the nadir time (95% confidence interval [CI] 20-42). For THA, the seasonal increase in SSI was 19% (95% CI 9-30). Compared to Medicare, patients with Medicaid as the primary payer had a 49% higher odds of 30-day SSI after TKA (95% CI 32-68). CONCLUSION: SSIs following TKA and THA are seasonal peaking in summer months. Payer status was also a significant risk factor for SSIs. Future studies should investigate potential factors that could relate to the associations demonstrated in this study.

Warmer Weather as a Risk Factor for Cellulitis: A Population-based Investigation.

Background: The incidence of cellulitis is highly seasonal and this seasonality may be explained by changes in the weather, specifically, temperature. Methods: Using data from the Nationwide Inpatient Sample (years 1998 to 2011), we identified the geographic location for 773719 admissions with the primary diagnosis (ICD-9-CM code) of cellulitis and abscess of finger and toe (681.XX) and other cellulitis and abscess (682.XX). Next, we used data from the National Climatic Data Center to estimate the monthly average temperature for each of these different locations. We modeled the odds of an admission having a primary diagnosis of cellulitis as a function of demographics, payer, location, patient severity, admission month, year, and the average temperature in the month of admission. Results: We found that the odds of an admission with a primary diagnosis of cellulitis increase with higher temperatures in a dose-response fashion. For example, relative to a cold February with average temperatures under 40° F, an admission in a hot July with an average temperature exceeding 90°F has 66.63% higher odds of being diagnosed with cellulitis (95% confidence interval [CI]: [61.2, 72.3]). After controlling for temperature, the estimated amplitude of seasonality of cellulitis decreased by approximately 71%. Conclusion: At a population level, admissions to the hospital for cellulitis risk are strongly associated with warmer weather.

Weather-Dependent Risk for Legionnaires' Disease, United States.

Using the Nationwide Inpatient Sample and US weather data, we estimated the probability of community-acquired pneumonia (CAP) being diagnosed as Legionnaires' disease (LD). LD risk increases when weather is warm and humid. With warm weather, we found a dose-response relationship between relative humidity and the odds for LD. When the mean temperature was 60°-80°F with high humidity (>80.0%), the odds for CAP being diagnosed with LD were 3.1 times higher than with lower levels of humidity (<50.0%). Thus, in some regions (e.g., the Southwest), LD is rarely the cause of hospitalizations. In other regions and seasons (e.g., the mid-Atlantic in summer), LD is much more common. Thus, suspicion for LD should increase when weather is warm and humid. However, when weather is cold, dry, or extremely hot, empirically treating all CAP patients for LD might contribute to excessive antimicrobial drug use at a population level.

Increased statin prescribing does not lower pneumonia risk.

BACKGROUND: Investigators have attributed protective effects of statins against pneumonia and other infections. However, these reports are based on observational data where treatments are not assigned randomly. We aimed to determine if the protective effects of statins against pneumonia are due to nonrandom treatment assignment. METHODS: We built a cohort consisting of 124 695 Medicare beneficiaries diagnosed with an acute myocardial infarction (AMI) for which we had complete claims data. We considered patients who survived at least 30 days post-AMI (full sample), or who survived for 1 year post-AMI (survivors). First, we used ordinary least squares (OLS) and logit models to determine if receiving a statin was protective against pneumonia. Second, to control for nonrandom treatment assignment, we performed an instrumental variables analysis using geographic treatment rates as an instrument. All models included patient demographics, medications, diagnoses, length of hospital stay, and out-of-pocket drug costs as covariates. Our outcome measure was a pneumonia diagnosis during the 1 year following AMI. RESULTS: A total of 76 994 patients (61.9%) filled a statin prescription, and 19 078 (15.3%) were diagnosed with pneumonia. Using OLS, the statin coefficient was -0.016 (P < .001), indicating that statins are associated with a reduction in pneumonia. Using instrumental variables, we find that statin prescriptions are not associated with a reduction in pneumonia. For the full sample, statin coefficients ranged from -0.001 to -0.01 (P > .6). CONCLUSIONS: For patients with AMI, the protective effect of statins against pneumonia is most likely the result of nonrandom treatment assignment (ie, a healthy-user bias).

Optimal screening strategies for healthcare associated infections in a multi-institutional setting.

Health institutions may choose to screen newly admitted patients for the presence of disease in order to reduce disease prevalence within the institution. Screening is costly, and institutions must judiciously choose which patients they wish to screen based on the dynamics of disease transmission. Since potentially infected patients move between different health institutions, the screening and treatment decisions of one institution will affect the optimal decisions of others; an institution might choose to "free-ride" off the screening and treatment decisions of neighboring institutions. We develop a theoretical model of the strategic decision problem facing a health care institution choosing to screen newly admitted patients. The model incorporates an SIS compartmental model of disease transmission into a game theoretic model of strategic decision-making. Using this setup, we are able to analyze how optimal screening is influenced by disease parameters, such as the efficacy of treatment, the disease recovery rate and the movement of patients. We find that the optimal screening level is lower for diseases that have more effective treatments. Our model also allows us to analyze how the optimal screening level varies with the number of decision makers involved in the screening process. We show that when institutions are more autonomous in selecting whom to screen, they will choose to screen at a lower rate than when screening decisions are more centralized. Results also suggest that centralized screening decisions have a greater impact on disease prevalence when the availability or efficacy of treatment is low. Our model provides insight into the factors one should consider when choosing whether to set a mandated screening policy. We find that screening mandates set at a centralized level (i.e. state or national) will have a greater impact on the control of infectious disease.

Factors related to receipt of well-child visits in insured children.

Our objective was to identify factors related to receipt of the recommended number of well-child visits in insured children. We hypothesized parent insurance status would be related to receipt of well-child visits, with those with uninsured parents more likely to have fewer visits than recommended. Data for the study came from the 2007 Medical Expenditure Panel Survey-Household Component. The sample included children <18 years of age with full-year insurance coverage and parents who were insured or uninsured the entire year. The outcome variable indicated whether children had received fewer than the recommended number of well-child visits in physician offices or outpatient departments. Parent, family, and child characteristics were measured. Forty-eight percent of the 4,650 children included in the study had fewer well-child visits than recommended. Children whose parents did not visit a physician during the year and children whose parents had not completed high school were more likely to miss recommended visits. Parent insurance status did not affect well-child visits. We identified child, family, and parent factors influencing well-child visits in insured children, including the parent's own use of physician visits. Contrary to our hypothesis, well-child visits were not influenced by parent insurance status. Determining which insured children are at greater risk of missing recommended well-child visits aids policymakers in identifying those who may benefit from interventions to improve use of preventive care.

Association between household opioid prescriptions and risk for overdose among family members not prescribed opioids.

BACKGROUND: Prescription opioids have contributed to the rise in opioid-related overdoses and deaths. The presence of opioids within households may increase the risk of overdose among family members who were not prescribed an opioid themselves. Larger quantities of opioids may further increase risk. OBJECTIVES: To determine the risk of opioid overdose among individuals who were not prescribed an opioid but were exposed to opioids prescribed to other family members in the household, and evaluate the risk in relation to the total morphine milligram equivalents (MMEs) present in the household. METHODS: We conducted a cohort study using a large database of commercial insurance claims from 2001 to 2021. For inclusion in the cohort, we identified individuals not prescribed an opioid in the prior 90 days from households with two or more family members, and determined the total MMEs prescribed to other family members. Individuals were stratified into monthly enrollment strata defined by household opioid exposure and other confounders. A generalized linear model was used to estimate incidence rate ratios (IRRs) for overdose. RESULTS: Overall, the incidence of overdose among enrollees in households where a family member was prescribed an opioid was 1.73 (95% confidence interval [CI]: 1.67-1.78) times greater than households without opioid prescriptions. The risk of overdose increased continuously with the level of potential MMEs in the household from an IRR of 1.23 (95% CI: 1.16-1.32) for 1-100 MMEs to 4.67 (95% CI: 4.18-5.22) for >12,000 MMEs. The risk of overdose associated with household opioid exposure was greatest for ages 1-2 years (IRR: 3.46 [95% CI: 2.98-4.01]) and 3-5 years (IRR: 3.31 [95% CI: 2.75-3.99]). CONCLUSIONS: The presence of opioids in a household significantly increases the risk of overdose among other family members who were not prescribed an opioid. Higher levels of MMEs, either in terms of opioid strength or quantity, were associated with increased levels of risk. Risk estimates may reflect accidental poisonings among younger family members.

Using a Fitbit-based Walking Game to Improve Physical Activity Among U.S. Veterans.

INTRODUCTION: Physical inactivity, hereafter inactivity, is a serious health problem among U.S. veterans, hereafter veterans. Inactive adults are at risk for adverse cardiac events and premature mortality. Specifically, among veterans, inactivity has been associated with a 23% increase in mortality. In order to increase physical activity among veterans, we developed Veterans Affairs (VA) MapTrek, a mobile-phone-based web app that allows users to take a virtual walk in interesting locations around the world while tracking their progress against that of others like themselves on an interactive map. Steps are counted by a commercially available Fitbit triaxial accelerometer, and users see their progress along a predefined scenic path overlaid on Google Maps. The objective of this study was to determine the effectiveness of VA MapTrek to increase physical activity in a population of veterans at risk for obesity-related morbidity. MATERIALS AND METHODS: We recruited overweight and obese veterans obtaining care at the Iowa City Veterans Affairs Health Center. Half of the veterans were assigned to participate in VA MapTrek. Each week, participants were assigned virtual walking races (Monday through Saturday), which followed a predetermined route that is displayed on Google Maps. The participant's position on the map is automatically updated each time their Fitbit syncs to their phone. In addition, challenges were issued periodically. Veterans in the control group were only given a Fitbit. We regressed daily step counts on the days of the week, the days since the start of the intervention period, whether the user was in the VA MapTrek or Control group, and an interaction between the study group and the days since the start of the intervention period. We included subject-specific random intercepts and subject-specific random slopes. This model was estimated using Bayesian Hamiltonian Monte Carlo using Stan's No-U-Turns sampler. We set vague, uniform priors on all the parameters. RESULTS: We enrolled 276 participants, but only 251 (102 in the control group and 149 in the VA MapTrek group) contributed data during the intervention period. Our analysis suggests an 86.8% likelihood that the VA MapTrek intervention led to a minimum increase of 1,000 daily steps over the 8-week period, compared to the control group. Throughout the 8-week intervention, we project that VA MapTrek participants would have taken an extra 96,627 steps, equivalent to 77.8 additional kilometers (km) (48.3 additional miles), assuming an average of 1,242 steps per km (2,000 steps per mile). CONCLUSIONS: Our study underscores the potential of VA MapTrek as an intervention for promoting walking among veterans who face elevated risks of obesity and cardiac issues. Rural veterans are a high-risk population, and new interventions like VA MapTrek are needed to improve veterans' health.

Using Thermal Imaging to Track Cellulitis.

Background: Cellulitis is a common soft tissue infection and a major cause of morbidity. The diagnosis is based almost exclusively on clinical history and physical exam. To improve the diagnosis of cellulitis, we used a thermal camera to track how skin temperature of the affected area changed during a hospital stay for patients with cellulitis. Methods: We recruited 120 patients admitted with a diagnosis of cellulitis. Daily thermal images of the affected limb were taken. Temperature intensity and area were analyzed from the images. Highest daily body temperature and antibiotics administered were also collected.We estimated a longitudinal linear mixed-effects model with a random intercept for the affected body area. All observations on a given day were included, and we used an integer time indicator indexed to the initial day (ie, t = 1 for the first day the patient was observed, etc.). We then analyzed the effect of this time trend on both severity (ie, normalized temperature) and scale (ie, area of skin with elevated temperature). Results: We analyzed thermal images from the 41 patients with a confirmed case of cellulitis who had at least 3 days of photos. For each day that the patient was observed, the severity decreased by 1.63 (95% CI, -13.45 to 10.32) units on average, and the scale decreased by 0.63 (95% CI, -1.08 to -0.17) points on average. Also, patients' body temperatures decreased by 0.28°F each day (95% CI, -0.40 to -0.17). Conclusions: Thermal imaging could be used to help diagnose cellulitis and track clinical progress.

Predicting use of a gait-stabilizing device using a Wii Balance Board.

Gait-stabilizing devices (GSDs) are effective at preventing falls, but people are often reluctant to use them until after experiencing a fall. Inexpensive, convenient, and effective methods for predicting which patients need GSDs could help improve adoption. The purpose of this study was to determine if a Wii Balance Board (WBB) can be used to determine whether or not patients use a GSD. We prospectively recruited participants ages 70-100, some who used GSDs and some who did not. Participants first answered questions from the Modified Vulnerable Elders Survey, and then completed a grip-strength test using a handgrip dynamometer. Finally, they were asked to complete a series of four 30-second balance tests on a WBB in random order: (1) eyes open, feet apart; (2) eyes open, feet together; (3) eyes closed, feet apart; and (4) eyes closed, feet together. The four-test series was repeated a second time in the same random order. The resulting data, represented as 25 features extracted from the questionnaires and the grip test, and data from the eight balance tests, were used to predict a subject's GSD use using generalized functional linear models based on the Bernoulli distribution. 268 participants were consented; 62 were missing data elements and were removed from analysis; 109 were not GSD users and 97 were GSD users. The use of velocity and acceleration information from the WBB improved upon predictions based solely on grip strength, demographic, and survey variables. The WBB is a convenient, inexpensive, and easy-to-use device that can be used to recommend whether or not patients should be using a GSD.

Team-based home blood pressure monitoring for blood pressure equity a protocol for a stepped wedge cluster randomized trial.

BACKGROUND: Home Blood Pressure Monitoring (HBPM) that includes a team with a clinical pharmacist is an evidence-based intervention that improves blood pressure (BP). Yet, strategies for promoting its adoption in primary care are lacking. We developed potentially feasible and sustainable implementation strategies to improve hypertension control and BP equity. METHODS: We assessed barriers and facilitators to HBPM and iteratively adapted implementation strategies through key informative interviews and guidance from a multistakeholder stakeholder team involving investigators, clinicians, and practice administration. RESULTS: Strategies include: 1) pro-active outreach to patients; 2) provision of BP devices; 3) deployment of automated bidirectional texting to support patients through education messages for patients to transmit their readings to the clinical team; 3) a hypertension visit note template; 4) monthly audit and feedback reports on progress to the team; and 5) training to the patients and teams. We will use a stepped wedge randomized trial to assess RE-AIM outcomes. These are defined as follows Reach: the proportion of eligible patients who agree to participate in the BP texting; Effectiveness: the proportion of eligible patients with their last BP reading <140/90 (six months); Adoption: the proportion of patients invited to the BP texting; Implementation: patients who text their BP reading ≥10 of days per month; and Maintenance: sustained BP control post-intervention (twelve months). We will also examine RE-AIM metrics stratified by race and ethnicity. CONCLUSIONS: Findings will inform the impact of strategies for the adoption of team-based HPBM and the impact of the intervention on hypertension control and equity. REGISTRATION DETAILS: www. CLINICALTRIALS: gov Identifier: NCT05488795.

Association of Appendicitis Incidence With Warmer Weather Independent of Season.

Importance: Acute appendicitis is a common cause of abdominal pain and the most common reason for emergency surgery in several countries. Increased cases during summer months have been reported. Objective: To investigate the incidence of acute appendicitis by considering local temperature patterns in geographic regions with different climate over several years. Design, Setting, and Participants: This cohort study used insurance claims data from the MarketScan Commercial Claims and Encounters Database and the Medicare Supplemental and Coordination of Benefits Database from January 1, 2001, to December 31, 2017. The cohort included individuals at risk for appendicitis who were enrolled in US insurance plans that contribute data to the MarketScan databases. Cases of appendicitis in the inpatient, outpatient, and emergency department settings were identified using International Classification of Diseases, Ninth Revision, Clinical Modification or International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes. Local weather data were obtained for individuals living in a metropolitan statistical area (MSA) from the Integrated Surface Database. Associations were characterized using a fixed-effects generalized linear model based on a negative binomial distribution. The model was adjusted for age, sex, and day of week and included fixed effects for year and MSA. The generalized linear model was fit with a piecewise linear model by searching each 0.56 °C in temperature for change points. To further isolate the role of temperature, observed temperature was replaced with the expected temperature and the deviation of the observed temperature from the expected temperature for a given city on a given day of year. Data were analyzed from October 1, 2021, to July 31, 2022. Main Outcomes and Measures: The primary outcome was the daily number of appendicitis cases in a given city stratified by age and sex, with mean temperature in the MSA over the previous 7 days as the independent variable. Results: A total of 450 723 744 person-years at risk and 689 917 patients with appendicitis (mean [SD] age, 35 [18] years; 347 473 male [50.4%] individuals) were included. Every 5.56 °C increase in temperature was associated with a 1.3% increase in the incidence of appendicitis (incidence rate ratio [IRR], 1.01; 95% CI, 1.01-1.02) when temperatures were 10.56 °C or lower and a 2.9% increase in incidence (IRR, 1.03; 95% CI, 1.03-1.03) for temperatures higher than 10.56 °C. In terms of temperature deviations, a higher-than-expected temperature increase greater than 5.56 °C was associated with a 3.3% (95% CI, 1.0%-5.7%) increase in the incidence of appendicitis compared with days with near-0 deviations. Conclusions and Relevance: Results of this cohort study observed seasonality in the incidence of appendicitis and found an association between increased incidence and warmer weather. These results could help elucidate the mechanism of appendicitis.

Proceedings From a National Heart, Lung, and Blood Institute and the Centers for Disease Control and Prevention Workshop to Control Hypertension.

Hypertension treatment and control prevent more cardiovascular events than management of other modifiable risk factors. Although the age-adjusted proportion of US adults with controlled blood pressure (BP) defined as <140/90 mm Hg, improved from 31.8% in 1999-2000 to 48.5% in 2007-2008, it remained stable through 2013-2014 and declined to 43.7% in 2017-2018. To address the rapid decline in hypertension control, the National Heart, Lung, and Blood Institute and the Division for Heart Disease and Stroke Prevention of the Centers for Disease Control and Prevention convened a virtual workshop with multidisciplinary national experts. Also, the group sought to identify opportunities to reverse the adverse trend and further improve hypertension control. The workshop immediately preceded the Surgeon General's Call to Action to Control Hypertension, which recognized a stagnation in progress with hypertension control. The presentations and discussions included potential reasons for the decline and challenges in hypertension control, possible "big ideas," and multisector approaches that could reverse the current trend while addressing knowledge gaps and research priorities. The broad set of "big ideas" was comprised of various activities that may improve hypertension control, including: interventions to engage patients, promotion of self-measured BP monitoring with clinical support, supporting team-based care, implementing telehealth, enhancing community-clinical linkages, advancing precision population health, developing tailored public health messaging, simplifying hypertension treatment, using process and outcomes quality metrics to foster accountability and efficiency, improving access to high-quality health care, addressing social determinants of health, supporting cardiovascular public health and research, and lowering financial barriers to hypertension control.