Introduction The lingering burden of the COVID-19 pandemic on primary care clinicians and practices poses a public health emergency for the United States. This study uses clinician-reported data to examine changes in primary care demand and capacity.Methods From March 2020 to March 2022, 36 electronic surveys were fielded among primary care clinicians responding to survey invitations as posted on listservs and identified through social media and crowd sourcing. Quantitative and qualitative analyses were performed on both closed- and open-ended survey questions.Results An average of 937 respondents per survey represented family medicine, pediatrics, internal medicine, geriatrics, and other specialties. Responses reported increases in patient health burden, including worsening chronic care management and increasing volume and complexity. A higher frequency of dental- and eyesight-related issues was noted by respondents, as was a substantial increase in mental or emotional health needs. Respondents also noted increased demand, "record high" wait times, and struggles to keep up with patient needs and the higher volume of patient questions. Frequent qualitative statements highlighted the mismatch of patient needs with practice capacity. Staffing shortages and the inability to fill open clinical positions impaired clinicians' ability to meet patient needs and a substantial proportion of respondents indicated an intention to leave the profession or knew someone who had.Conclusion These data signal an urgent need to take action to support the ability of primary care to meet ongoing patient and population health care needs.

OBJECTIVE:Contrast-sparing strategies have been developed for percutaneous coronary intervention (PCI) patients at increased risk of contrast-induced acute kidney injury (CI-AKI), and numerous CI-AKI risk prediction models have been created. However, the potential clinical and economic consequences of using predicted CI-AKI risk thresholds for assigning patients to contrast-sparing regimens have not been evaluated. We estimated the clinical and economic consequences of alternative CI-AKI risk thresholds for assigning Medicare PCI patients to contrast-sparing strategies.METHODS:Medicare data were used to identify inpatient PCI from January 2017 to June 2021. A prediction model was developed to assign each patient a predicted probability of CI-AKI. Multivariable modeling was used to assign each patient two marginal predicted values for each of several clinical and economic outcomes based on (1) their underlying clinical and procedural characteristics plus their true CI-AKI status in the data and (2) their characteristics plus their counterfactual CI-AKI status. Specifically, CI-AKI patients above the predicted risk threshold for contrast-sparing were reassigned their no CI-AKI (counterfactual) outcomes. Expected event rates, resource use, and costs were estimated before and after those CI-AKI patients were reassigned their counterfactual outcomes. This entailed bootstrapped sampling of the full cohort.RESULTS:Of the 542,813 patients in the study cohort, 5,802 (1.1%) had CI-AKI. The area under the receiver operating characteristic curve for the prediction model was 0.81. At a predicted risk threshold for CI-AKI of >2%, approximately 18.0% of PCI patients were assigned to contrast-sparing strategies, resulting in (/100,000 PCI patients) 121 fewer deaths, 58 fewer myocardial infarction readmissions, 4,303 fewer PCI hospital days, $11.3 million PCI cost savings, and $25.8 million total one-year cost savings, versus no contrast-sparing strategies.LIMITATIONS:Claims data may not fully capture disease burden and are subject to inherent limitations such as coding inaccuracies. Further, the dataset used reflects only individuals with fee-for-service Medicare, and the results may not be generalizable to Medicare Advantage or other patient populations.CONCLUSIONS:Assignment to contrast-sparing regimens at a predicted risk threshold close to the underlying incidence of CI-AKI is projected to result in significant clinical and economic benefits.

OBJECTIVES:To study the predictive validity of the CMS Practice Assessment Tool (PAT) among 632 primary care practices.STUDY DESIGN:Retrospective observational study.METHODS:The study included primary care physician practices recruited by the Great Lakes Practice Transformation Network (GLPTN), 1 of 29 CMS-awarded networks, and used data from 2015 to 2019. At enrollment, trained quality improvement advisers scored each of the PAT's 27 milestones by its degree of implementation based on interviews with staff, review of documents, direct observation of practice activity, and professional judgment. The GLPTN also tracked each practice's status regarding alternative payment model (APM) enrollment. Exploratory factor analysis (EFA) was used to identify summary scores; mixed-effects logistic regression was used to assess the relationship between derived scores with APM participation.RESULTS:EFA revealed that the PAT's 27 milestones could be summed into 1 overall score and 5 secondary scores. By the end of the 4-year project, 38% of practices were enrolled in an APM. A baseline overall score and 3 secondary scores were associated with increased odds of joining an APM (overall score: odds ratio [OR], 1.06; 95% CI, 0.99-1.12; P = .061; data-driven care quality score: OR, 1.11; 95% CI, 1.00-1.22; P = .040; efficient care delivery score: OR, 1.08; 95% CI, 1.03-1.13; P = .003; collaborative engagement score: OR, 0.88; 95% CI, 0.80-0.96; P = .005).CONCLUSIONS:These results demonstrate that the PAT has adequate predictive validity for APM participation.

Background Acute kidney injury (AKI), including contrast-induced AKI (CI-AKI), is an important complication of per cutaneous coronary intervention (PCI), resulting in short-and long-term adverse clinical outcomes. While prior research has reported an increased cost burden to hospitals from CI-AKI, the incremental cost to payers remains unknown. Understanding this incremental cost may inform decisions and even policy in the future. The objective of this study was to estimate the short-and long-term cost to Medicare of AKI overall, and specifically CI-AKI, in PCI.Methods Patients undergoing inpatient PCI between January 2017 and June 2020 were selected from Medicare 100% fee-for-service data. Baseline clinical characteristics, PCI lesion/procedural characteristics, and AKI/CI-AKI during the PCI admission, were identified from diagnosis and procedure codes. Poisson regression, generalized linear modelling, and longitudinal mixed effects modelling, in full and propensity-matched cohorts, were used to compare PCI admission length of stay (LOS) and cost (Medicare paid amount inflated to 2022 US$), as well as total costs during 1-year following PCI, between AKI and non-AKI patients.Results The study cohort included 509,039 patients, of whom 104,033 (20.4%) were diagnosed with AKI and 9,691 (1.9%) with CI-AKI. In the full cohort, AKI was associated with + 4.12 (95% confidence interval = 4.10, 4.15) days index PCI admission LOS, + $11,313 ($11,093, $11,534) index admission costs, and + $14,800 ($14,359, $15,241) total 1-year costs. CI-AKI was associated with + 3.03 (2.97, 3.08) days LOS, +$6,566 ($6,148, $6,984) index admission costs, and + $13,381 ($12,118, $14,644) cumulative 1-year costs (all results are adjusted for baseline characteristics). Results from the propensity-matched analyses were similar.Conclusions AKI, and specifically CI-AKI, during PCI is associated with significantly longer PCI admission LOS, PCI admission costs, and long-terms costs. (Am Heart J 2023;262:20-28.)

This study aimed to develop and temporally validate an electronic medical record (EMR)-based insomnia prediction model. In this nested case-control study, we analyzed EMR data from 2011–2018 obtained from a statewide health information exchange. The study sample included 19,843 insomnia cases and 19,843 controls matched by age, sex, and race. Models using different ML techniques were trained to predict insomnia using demographics, diagnosis, and medication order data from two surveillance periods: −1 to −365 days and −180 to −365 days before the first documentation of insomnia. Separate models were also trained with patient data from three time periods (2011–2013, 2011–2015, and 2011–2017). After selecting the best model, predictive performance was evaluated on holdout patients as well as patients from subsequent years to assess the temporal validity of the models. An extreme gradient boosting (XGBoost) model outperformed all other classifiers. XGboost models trained on 2011–2017 data from −1 to −365 and −180 to −365 days before index had AUCs of 0.80 (SD 0.005) and 0.70 (SD 0.006), respectively, on the holdout set. On patients with data from subsequent years, a drop of at most 4% in AUC is observed for all models, even when there is a five-year difference between the collection period of the training and the temporal validation data. The proposed EMR-based prediction models can be used to identify insomnia up to six months before clinical detection. These models may provide an inexpensive, scalable, and longitudinally viable method to screen for individuals at high risk of insomnia.

The ability to assess the value of various health-care activities, processes, and outcomes is critical for decision making and essential to maintain the fidelity of value-based payment mechanisms. However, value is subjective and differs by perspective, context, and situation. Furthermore, the complex nature of health-care delivery and payment complicates efforts to determine the value of individual components or interventions. While a variety of methods exist to quantify and compare value, none have been able to fully capture value for all stakeholders. As an alternative, a general framework that guides how one should define, measure, and interpret value would provide some needed consistency for those looking to assess value while allowing for enough flexibility to address different perspectives, situations, and evaluation goals.

Objective: To leverage electronic health record (EHR) data to explore the relationship between weight gain and antipsychotic adherence among patients with schizophrenia and bipolar disorder (BD). Methods: EHR data were used to identify individuals with at least 60 days of continuous antipsychotic use between 2005 and 2019. Patients were diagnosed with schizophrenia, schizoaffective disorder, BD, or neither diagnosis (psychiatric controls). We examined the association of weight gain in the first 90 days with the proportion of days covered (PDC) with an antipsychotic and with the frequency of medication switching or stopping. Results: We identified 590 adults with schizophrenia or schizoaffective disorder, 819 adults with BD, and 642 psychiatric controls. In the first 90 days, the percentages of patients with a PDC ≥ 0.80 were 76.8% (schizophrenia), 77.1% (BD), and 70.7% (controls). Logistic regression models revealed that weight gain of ≥ 7% trended toward being significantly associated with greater adherence in the first 90 days (odds ratio = 1.29, P = .077) and was significantly associated with an increased likelihood of a medication switch in the first 180 days (odds ratio = 1.60, P = .003). Discussion: Patients whose weight increased by 7% or more in the first 90 days were more adherent but were also more likely to switch medications during the first 180 days.

BACKGROUND:Intensive care unit (ICU) utilization has increased among patients with Alzheimer disease and related dementia (ADRD), although outcomes are poor.OBJECTIVES:To compare ICU discharge location and subsequent mortality between patients with and patients without ADRD enrolled in Medicare Advantage.METHODS:This observational study used Optum's Clinformatics Data Mart Database from years 2016 to 2019 and included adults aged >67 years with continuous Medicare Advantage coverage and a first ICU admission in 2018. Alzheimer disease and related dementia and comorbid conditions were identified from claims. Outcomes included discharge location (home vs other facilities) and mortality (within the same calendar month of discharge and within 12 months after discharge).RESULTS:A total of 145 342 adults met inclusion criteria; 10.5% had ADRD and were likely to be older, female, and have more comorbid conditions. Only 37.6% of patients with ADRD were discharged home versus 68.6% of patients who did not have ADRD (odds ratio [OR], 0.40; 95% CI, 0.38-0.41). Both death in the same month as discharge (19.9% vs 10.3%; OR, 1.54; 95% CI, 1.47-1.62) and death in the 12 months after discharge (50.8% vs 26.2%; OR, 1.95; 95% CI, 1.88-2.02) were twice as common among patients with ADRD.CONCLUSIONS:Patients with ADRD have lower home discharge rates and greater mortality after an ICU stay than patients without ADRD.

Background Non-adherence to psychotropic medications is common in schizophrenia and bipolar disorders (BDs) leading to adverse outcomes. We examined patterns of antipsychotic use in schizophrenia and BD and their impact on subsequent acute care utilization. Methods We used electronic health record (EHR) data of 577 individuals with schizophrenia, 795 with BD, and 618 using antipsychotics without a diagnosis of either illness at two large health systems. We structured three antipsychotics exposure variables: the proportion of days covered (PDC) to measure adherence; medication switch as a new antipsychotic prescription that was different than the initial antipsychotic; and medication stoppage as the lack of an antipsychotic order or fill data in the EHR after the date when the previous supply would have been depleted. Outcome measures included the frequency of inpatient and emergency department (ED) visits up to 12 months after treatment initiation. Results Approximately half of the study population were adherent to their antipsychotic medication (a PDC ≥ 0.80): 53.6% of those with schizophrenia, 52.4% of those with BD, and 50.3% of those without either diagnosis. Among schizophrenia patients, 22.5% switched medications and 15.1% stopped therapy. Switching and stopping occurred in 15.8% and 15.1% of BD patients and 7.4% and 20.1% of those without either diagnosis, respectively. Across the three cohorts, non-adherence, switching, and stopping therapy were all associated with increased acute care utilization, even after adjusting for baseline demographics, health insurance, past acute care utilization, and comorbidity. Conclusion Non-continuous antipsychotic use is common and associated with high acute care utilization.

PURPOSE During the COVID-19 pandemic, telemedicine emerged as an important tool in primary care. Technology and policy-related challenges, however, revealed barriers to adoption and implementation. This report describes the findings from weekly and monthly surveys of primary care clinicians regarding telemedicine during the first 2 years of the pandemic.METHODS From March 2020 to March 2022, we conducted electronic surveys using convenience samples obtained through social networking and crowdsourcing. Unique tokens were used to confidentially track respondents over time. A multidisciplinary team conducted quantitative and qualitative analyses to identify key concepts and trends.RESULTS A total of 36 surveys resulted in an average of 937 respondents per survey, representing clinicians from all 50 states and multiple specialties. Initial responses indicated general difficulties in implementing telemedicine due to poor infrastructure and reimbursement mechanisms. Over time, attitudes toward telemedicine improved and respondents considered video and telephone-based care important tools for their practice, though not a replacement for in-person care.CONCLUSIONS The implementation of telemedicine during COVID-19 identified barriers and opportunities for technology adoption and highlighted steps that could support primary care clinics' ability to learn, adapt, and implement technology.

Institute for Advancing Health Value, Western Governors University, Salt Lake City, UT, Solid Research Group, LLC, St. Paul, MN, Jefferson College of Population Health, Thomas Jefferson University, Philadelphia, PA, Optum, Minnetonka, MN

As industry consolidation leads to a growing number of large new healthcare delivery networks, patients and their clinicians are losing the important human-centric and relationship-based nature of medical care. The leadership of Hackensack Meridian Health (HMH), a New Jersey-based network of hospitals, research center, and medical school, made an organizational commitment to reverse such loss and restore the social nature of medicine. To attain that goal, HMH engaged both clinicians and administrators to confirm the demand for change, foster a collaborative culture design, and address the unique nature of the individual components in the HMH network. Efforts to transform the HMH care delivery model illustrate the effectiveness of Agile science and its problem-solving methods.

Background:Although the management of chronic kidney disease (CKD) has changed considerably in US adults, it is uncertain whether the burden, risk factors, and temporal trends of CKD are similar regarding prior military service.Methods:This observational study used National Health and Nutrition Examination Survey data to quantify the association between CKD and military service in a generalizable sample of US adults between 1999 and 2018.Results:The respective frequencies (standard error [SE]) of CKD and military service were 15.2% (0.3) and 11.5% (0.3). The proportion (SE) with CKD was significantly higher among those with prior MS vs the overall population (22.7% [0.7] vs 15.2% [0.3]; P < .001). Within the military service population, the proportion (SE) with CKD differed by era: 1999 to 2002, 18.9% (1.1); 2003 to 2006, 24.9% (1.5); 2007 to 2010, 22.3% (1.5); 2011 to 2014, 24.3% (1.7); and 2015 to 2018, 24.0% (1.8) (P = .02). Following adjustment for age, sex, and race and ethnicity, prior military service was associated (P < .05) with a higher likelihood of CKD (adjusted odds ratio, 1.17; 95% CI 1.06-1.28). Adjusted associations of CKD differed in groups with and without military service for the 40 to 64 years age group, ≥ 65 years age group, female sex, and family poverty (P < .05 vs variable-specific reference category).Conclusions:Military service is associated with a higher likelihood of CKD in US adults. Risk factors for CKD differed among many subgroups both with and without military service history. Future research is needed to better determine whether military service constitutes a unique risk factor for CKD.

PURPOSE:Care continuity is foundational to the clinician/patient relationship; however, little has been done to operationalize continuity of care (CoC) as a clinical quality measure. The American Board of Family Medicine developed the Primary Care CoC clinical quality measure as part of the Measures That Matter to Primary Care initiative.METHODS:Using 12-month Optum Clinformatics Data Mart claims data, we calculated the Bice-Boxerman Continuity of Care Index for each patient, which we rolled up to create an aggregate, physician-level CoC score. The physician quality score is the percent of patients with a Bice-Boxerman Index ≥0.7 (70%). We tested validity in 2 ways. First, we explored the validity of using 0.7 as a threshold for patient CoC within the Optum claims database to validate its use for reflecting patient-level continuity. Second, we explored the validity of the physician CoC measure by examining its association with patient outcomes. We assessed reliability using signal-to-noise methodology.RESULTS:Mean performance on the measure was 27.6%; performance ranged from 0% to 100% (n = 555,213 primary care physicians). Higher levels of CoC were associated with lower levels of care utilization. The measure indicated acceptable levels of validity and reliability.CONCLUSIONS:Continuity is associated with desirable health and cost outcomes as well as patient preference. The CoC clinical quality measure meets validity and reliability requirements for implementation in primary care payment and accountability. Care continuity is important and complementary to access to care, and prioritizing this measure could help shift physician and health system behavior to support continuity.

Population Health ManagementVol. 25, No. 3 CommentariesFree AccessMajor Economic Losses Associated with Inadequate Control of High Blood Pressure: Time for a Major ChangeDonald E. Casey, Andrew Kopolow, and Craig SolidDonald E. CaseyAddress correspondence to: Donald E. Casey, Jr, MD, MPH, MBA, Department of Medicine, Rush University, 1717 W. Congress Pkwy. 10th Floor, Chicago, IL 60612, USA E-mail Address: don.casey@ipo4health.comhttps://orcid.org/0000-0002-3820-598XJefferson College of Population Health, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.Department of Medicine, Rush Medical College, Rush University, Chicago, Illinois, USA.Institute for Healthcare Informatics, University of Minnesota, Minneapolis, Minnesota, USA.*Coauthor.Search for more papers by this author, Andrew KopolowJefferson College of Population Health, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.Population Health Division, United Healthcare Clinical Services, Minnetonka, MN, USA.Search for more papers by this author, and Craig SolidSolid Research Group, LLC, St. Paul, Minnesota, USA.Search for more papers by this authorPublished Online:7 Jun 2022https://doi.org/10.1089/pop.2022.0002AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Recent analyses of data from the National Health and Nutrition Examination Survey (NHANES) estimate that 115 million adults (46%) in the United States have hypertension (also referred to as High Blood Pressure or "HBP") as defined by systolic blood pressure BP ≥130 mm Hg or diastolic BP ≥80 mm Hg.1 Atherosclerotic cardiovascular disease (ASCVD) and stroke, when combined, remain the leading causes of death in the United States with more than 1 million deaths annually, translating to a rate of 2754 deaths per day.2 In addition, individuals with HBP face, on average, nearly $2000 more in annual health care expenditures than those who do not have HBP.3In this issue of Population Health Management, researchers and health economists from the Centers for Disease Control and Prevention (CDC) summarize a literature review of peer-reviewed articles published 2000–2019 to determine the types and extent of hypertension-associated work-related productivity loss among adults in the United States.4 Of the initial 411 relevant references screened, 27 articles met the selection criteria and were included in this review, which focused on hypertension-related productivity losses in the United States, paid work or unpaid home activities, and monetary or nonmonetary outcomes.All monetary outcomes were standardized to 2019 US dollars using the Employment Cost Index for total compensation for civilian workers. Nearly half (12) of the 27 articles meeting inclusion criteria presented monetary outcomes of productivity loss. Work characteristics were considered in 9 studies and several studies focused on specific companies and industries, such as financial/insurance services, manufacturing, oil, and health care. There was heterogeneity in statistical methods and sources of dollar values assigned in each of these 12 studies.The authors also note that there are different forms of productivity loss that can include short-term absences from work, reduced function while at work, the inability to work due to disability and premature mortality, and impairments to activities of daily living. In addition, multiple data sources were used to examine these categories of productivity loss, such as short-term disability claims or company personnel records of absenteeism, as well as data from several different commonly used standardized questionnaires.Absenteeism (14 articles) and presenteeism (8 articles) were most frequently assessed. Annual absenteeism attributable to hypertension was estimated as more than $11 billion nationally controlling for sociodemographic characteristics. Annual excess per capita costs related to workers with hypertension were estimated at $63 for short-term disability, $72–$330 for absenteeism, $53–$156 for presenteeism, and may be as high as $2362 for absenteeism and presenteeism when studied in combination, controlling for participant characteristics.Using Medical Expenditures Panel Survey (MEPS) data, the authors estimate that hypertension-associated productivity loss from absenteeism could be lowered by 15%–36% depending on the extent of controlling for sociodemographic characteristics, work characteristics, health risk factors (such as obesity, smoking, and physical inactivity), and common comorbidities related to HBP (such as diabetes, hyperlipidemia, cardiovascular disease, and stroke).Also using MEPS, hypertension-associated productivity loss from absenteeism was lowered by 51% after controlling for hypertension comorbidities (specifically, heart disease, stroke, diabetes, and mood disorders) and health conditions unrelated to hypertension (eg, cancer and arthritis) from estimates that controlled for sociodemographic characteristics, body mass index, and smoking. None of the studies evaluated in this article were noted to address the "silent killer" in terms of treatment versus nontreatment, or work-related causative and associative factors contributing to the development and worsening of high blood pressure.For the first time, we have a comprehensive summary of a structured evaluation of published peer-reviewed research on the monetary and nonmonetary impacts of productivity loss due to HBP for individual workers and their employers. For the first time, we are able to leverage a body of peer-reviewed research to better understand broader implications for effective control of HBP for larger populations (communities, regions, states, nationally, etc.). And through this literature review, 2 critical insights have emerged: (1) hypertension has a significant impact on workplace productivity on multiple levels and (2) economic estimates of these impacts vary widely in size and scope.In other words, hypertension research has proven problematic for more generalized impact estimation. Pulling this disparate body of research together is the necessary first step to begin doing just that. We applaud the authors for the breadth of the information provided and feel the sheer variability of the reviewed studies merits a concrete conceptualization to fully grasp their collective implications. In this vein, and purely for demonstrative purposes, imagine a hypothetical company we will call HTN, Inc. Using rates and dollar amounts pulled from the CDC's review and other previously published research on hypertension and related outcomes (available upon request), we can make a "back of the envelope" estimate of the cost of productivity loss due to HBP for this population.As the health care industry is well represented (cited in 4 of the 12 articles where specific industries are identified, more so than any other industry), we will make HTN a modest-sized health system in the nondescript suburban community of Anytown, USA. HTN's employee demographics are representative of the larger eligible US labor force (ie, adults 18 and older). Of HTN's 1000 employees, nearly half (470) have a diagnosis of hypertension. For more than a full third (390), it is uncontrolled hypertension. And the next 12 months will be precarious, both for this subgroup and HTN itself. From the employee perspective, 2 will have strokes, 3 will suffer acute myocardial infarction, 3 will require treatment for chronic kidney disease, and a dozen more will have chronic heart failure.Over the next year, HTN, Inc.'s workforce with hypertension will miss an additional 1034 days of work more than their nonhypertension counterparts. Those with uncontrolled hypertension will accrue roughly $600,000 in medical expenses and cost HTN an additional $400,000 in work disability, absenteeism, presenteeism, and general work-productivity loss.Is $1,000,000 per year in additional costs for a single business and its employees enough to grab your attention? If not, let us explore some additional implications. Estimates indicate an additional 20% of the population have undiagnosed hypertension due to lack of awareness, thereby further magnifying the costs for HTN, Inc. and its employees. Again, we acknowledge these estimates to be back of the envelope. They are nonetheless relatively conservative and reflective of the general adult population within the United States. Were we to slightly shift HTN, Inc.'s demographics toward an older population with more of its 1000-person work force >65 years of age or skewed toward certain comorbidities represented in the research, loss impacts could be far greater.With these new findings in mind, what are future opportunities and challenges for population health professionals and the US population health industry? In essence, the staggering overall annual economic and noneconomic losses from almost 50% of the overall US population with HBP (when including all age ranges for adults) are currently in the hundreds of billions of dollars. Since 80% of those with hypertension are currently considered "uncontrolled,"1 the opportunities are many for employers to partner with health care delivery systems, health insurers, and digital health industries to effectively implement more effective evidence-based recommendations from the 2017 American College of Cardiology (ACC)/American Heart Association (AHA) HBP Guidelines.5For example, the authors note that none of the economic evaluations used in their review explicitly assessed or documented the use of recommendations outlined in these guidelines, which include specific standards for obtaining accurate BP measurement, evaluating 10-year ASCVD Risk and appropriately classifying patients with HBP. Incorrect and hence inaccurate measurement of blood pressure has also now become a major challenge in terms of correct identification and treatment of people with high blood pressure, an issue that could be addressed and reinforced within the workplace through standardized self-monitoring programs such as the national AHA/American Medical Association Target BP program.6It has also become clear that effective and consistent ongoing assessment of social determinants of health through team-based care and shared decision making is important to help guide treatment options with nonpharmacological interventions, lifestyle modifications, and (when appropriate) medications provide excellent opportunities for improved BP control.2Extensive empiric evidence evaluations of so-called "workplace wellness" programs designed to improve blood pressure control in employees with hypertension have not demonstrated to be of any consistent positive impact, although recent data from China has shown promise that may have some relevance.7,8 Unfortunately, national initiatives (such as the Health and Human Services [HHS]-sponsored "Million Hearts" model) have also (so far) only made small marginal improvements on blood pressure control at the national level.9Hence, employers and their workers must work more closely with cardiovascular researchers, health economists, and public health officials to standardize measurement and monitoring of hypertension-associated productivity and nonproductivity costs, especially when implementing cost-effective national guideline-driven interventions designed to achieve better BP control. For example, employers could very easily provide and promote use of certified semiautomated oscillometric self-monitoring BP devices for home BP monitoring and patient/family digital educational resources on how to correctly measure BP in accordance with standard protocols espoused by Target BP,7 perhaps in partnership/collaboration with their health insurers and/or local health systems.Good quality scientific evidence now confirms that multilevel multicomponent strategies, including patient coaching and self-monitoring with home BP monitoring, provider training to address social determinants of health and lifestyle modification, clinical decision support within electronic health records, and multidisciplinary team-based care, when combined, are most effective for improving BP control in patients with hypertension.10 Hence, it is no longer necessary to argue about "The What," but instead, focus on successful implementation of "The How" and "By Who."This responsibility now lies simultaneously at the feet of not only employers, but health systems, insurers, and the digital health companies that provide so-called "solution" services to them. A group of nationally renowned health care and hypertension experts have recently published "The Blueprint for Change" model, which is a comprehensive evidence-based guideline-driven system of care for people with HBP, calling on managerial, clinical, and operational leaders of these organizations to actively collaborate at the local, regional, and national levels to create and support a coordinated system of guideline-based care delivery for adults with HBP.2The model is based on high-quality evidence-based guidelines and serves as the basis for (1) engaging and activating health system, payer, and employer leadership for organizational and financial support at every level; (2) continuously using transparent evidence-based standardized performance measurement and quality improvements to assess progress; and (3) insisting on effective shared accountability at all levels (including governance) of the US health system for ensuring access, infrastructure, and coverage (including proper and adequate payment).Without this type of active collaboration, current unrealistic and unfortunate expectations that employers, providers, payers, and digital health companies will be able to achieve population levels of effective patient-centered BP control in the current siloed environment will continue to lead to failure of the population health industry for millions of Americans.DisclaimerThe views expressed in this article include those of the aforementioned coauthors and should not be interpreted as policy of the American Heart Association, the American College of Cardiology, the National Hypertension Control Roundtable, or United Healthcare.Author Disclosure StatementDr. Casey: ACC/AHA 2017 Guideline for High Blood Pressure in Adults; Member, Advisory Board, National Hypertension Control Initiative (NHCI). Mr. Kopolow and Mr. Solid have no competing financial interests.Funding InformationNone of the authors have received any financial support for the research, authorship or publication of this article.References1. Facts About Hypertension | cdc.gov. https://www.cdc.gov/bloodpressure/facts.htm#:~:text=Nearly%20half%20of%20adults%20in%20the%20United%20States,with%20hypertension%20have%20their%20condition%20under%20control.%203 Accessed February 2, 2022. Google Scholar2. Casey DE, Daniel DM, Bhatt J, et al. Controlling high blood pressure: an evidence-based blueprint for change. Am J Med Qual 2022;37:22–31. Crossref, Medline, Google Scholar3. Kirkland EB, Heincelman M, Bishu KG, et al. Trends in healthcare expenditures among US adults with hypertension: national estimates, 2003–2014. J Am Heart Assoc 2018;7:e008731. Crossref, Medline, Google Scholar4. MacLeod KE, Ye Z, Donald B, Wang G. A literature review of productivity loss associated with hypertension in the United States. 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Among individuals living with schizophrenia or bipolar disorder, several reasons for non-adherence to antipsychotic medication have been cited, including attitudes about medication and side-effects. It has been shown that medication non-adherence is associated with increased utilization of healthcare resources. We used electronic health records (EHR) data to identify individuals with at least one 60-day period of suspected continuous use of antipsychotics between 2005 and 2019. Adult patients were identified with bipolar and schizophrenia spectrum disorders, or psychiatric controls (neither a schizophrenia nor bipolar diagnosis). We examined the association of acute care utilization (all cause ED visits and inpatient admissions) with medication adherence and medication switching during the first 180 days of treatment. Adherence was defined as proportion of days counts (PDC) greater than 0.8. The antipsychotic medication exposure variable was a combination of adherence and switching to account for an interaction between the two measures. After adjusting for prior utilization and medical comorbidity, patients who were non-adherent without switching medications were more likely to have an inpatient admission (OR=1.58, 95% CI=[1.20, 2.08]) than patients who were adherent to their first antipsychotic medication. Patient who switched antipsychotic medications were more likely to have an inpatient admission than patients adherent to initial antipsychotic medication (switched and adherent (OR=2.77, 95% CI=[1.82, 4.21]); switched and non-adherent (OR=2.24, 95% CI=[1.48, 3.39])). Finally, patients who completely stopped antipsychotic medication were more likely (OR=1.77, 95% CI=[1.29, 2.41]) to have an inpatient admission during the first 180 days of treatment compared to patients who were adherent to their first antipsychotic medication. We obtained similar results when examining the effect of non-adherence and medication switches on any ED visit and the number of ED visits. Non-adherence and medication switches were both associated with increased acute care utilization during the first 180 days of treatment.

Background: A common critique of adventure education research methodology is the overreliance on pre-/post-study designs to measure change. Purpose: This paper compares and contrasts two methods of data analysis on the same adventure education data set to show how these distinct approaches provide starkly different results and interpretation. Methodology/Approach: Using secondary data analysis, we employ a longitudinal data set of the social skill development of urban middle school students who participated in an adventure education program over the course of three academic years. First, change was assessed using a pre-/post-design by a traditional analysis of variance (ANOVA). Next, change was assessed with a six-wave, longitudinal design using multilevel modeling. Findings/Conclusions: Results show that the multilevel modeling approach revealed nonlinear change in the social skill development of middle school students, resulting in more accurate, nuanced estimation of change in social skill development than the ANOVA approach. Implications: The use of longitudinal data and multilevel modeling can be a useful methodological approach and statistical tool for adventure education researchers to not only address the criticisms of quantitative research in adventure education, but more importantly, provide a more thorough understanding of the impact of adventure education on human development.