Clinical and economic outcomes of assigning percutaneous coronary intervention patients to contrast-sparing strategies based on the predicted risk of contrast-induced acute kidney injury.

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.

Is primary care ready for a potential new public health emergency in the wake of the COVID-19 pandemic, now subsided?

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.

Using Agile Science for Rapid Innovation and Implementation of a New Care Model.

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.

How Value is Determined in Health Care.

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.

Telemedicine in Primary Care: Lessons Learned About Implementing Health Care Innovations During the COVID-19 Pandemic.

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.

Lymphedema self-care: economic cost savings and opportunities to improve adherence.

BACKGROUND: Breast cancer-related lymphedema (BCRL) imposes a significant economic burden on patients, providers, and society. There is no curative therapy for BCRL, but management through self-care can reduce symptoms and lower the risk of adverse events. MAIN BODY: The economic burden of BCRL stems from related adverse events, reductions in productivity and employment, and the burden placed on non-medical caregivers. Self-care regimens often include manual lymphatic drainage, compression garments, and meticulous skin care, and may incorporate pneumatic compression devices. These regimens can be effective in managing BCRL, but patients cite inconvenience and interference with daily activities as potential barriers to self-care adherence. As a result, adherence is generally poor and often worsens with time. Because self-care is on-going, poor adherence reduces the effectiveness of regimens and leads to costly treatment of BCRL complications. CONCLUSION: Novel self-care solutions that are more convenient and that interfere less with daily activities could increase self-care adherence and ultimately reduce complication-related costs of BCRL.

Mortality and Discharge Location of Intensive Care Patients With Alzheimer Disease and Related Dementia.

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.

Development and Temporal Validation of an Electronic Medical Record-Based Insomnia Prediction Model Using Data from a Statewide Health Information Exchange.

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.

Cost to Medicare of acute kidney injury in percutaneous coronary intervention.

BACKGROUND: Acute kidney injury (AKI), including contrast-induced AKI (CI-AKI), is an important complication of percutaneous 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.

Association of Antipsychotic-Related Weight Gain With Treatment Adherence and Switching Using Electronic Medical Records Data.

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.

CMS Practice Assessment Tool validity for alternative payment models.

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.

The impact of antipsychotic adherence on acute care utilization.

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.

Chronic Kidney Disease and Military Service in US Adults, 1999-2018.

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.

Measuring the Value Functions of Primary Care: Physician-Level Continuity of Care Quality Measure.

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.

Passive Digital Signature for Early Identification of Alzheimer's Disease and Related Dementia.

OBJECTIVES: Developing scalable strategies for the early identification of Alzheimer's disease and related dementia (ADRD) is important. We aimed to develop a passive digital signature for early identification of ADRD using electronic medical record (EMR) data. DESIGN: A case-control study. SETTING: The Indiana Network for Patient Care (INPC), a regional health information exchange in Indiana. PARTICIPANTS: Patients identified with ADRD and matched controls. MEASUREMENTS: We used data from the INPC that includes structured and unstructured (visit notes, progress notes, medication notes) EMR data. Cases and controls were matched on age, race, and sex. The derivation sample consisted of 10 504 cases and 39 510 controls; the validation sample included 4500 cases and 16 952 controls. We constructed models to identify early 1- to 10-year, 3- to 10-year, and 5- to 10-year ADRD signatures. The analyses included 14 diagnostic risk variables and 10 drug classes in addition to new variables produced from unstructured data (eg, disorientation, confusion, wandering, apraxia, etc). The area under the receiver operating characteristics (AUROC) curve was used to determine the best models. RESULTS: The AUROC curves for the validation samples for the 1- to 10-year, 3- to 10-year, and 5- to 10-year models that used only structured data were .689, .649, and .633, respectively. For the same samples and years, models that used both structured and unstructured data produced AUROC curves of .798, .748, and .704, respectively. Using a cutoff to maximize sensitivity and specificity, the 1- to 10-year, 3- to 10-year, and 5- to 10-year models had sensitivity that ranged from 51% to 62% and specificity that ranged from 80% to 89%. CONCLUSION: EMR-based data provide a targeted and scalable process for early identification of risk of ADRD as an alternative to traditional population screening. J Am Geriatr Soc 68:511-518, 2020.

Mobile Phone Ownership, Health Apps, and Tablet Use in US Adults With a Self-Reported History of Hypertension: Cross-Sectional Study.

BACKGROUND: Mobile phone and tablet ownership have increased in the United States over the last decade, contributing to the growing use of mobile health (mHealth) interventions to help patients manage chronic health conditions like diabetes. However, few studies have characterized mobile device ownership and the presence of health-related apps on mobile devices in people with a self-reported history of hypertension. OBJECTIVE: This study aimed to describe the prevalence of smartphone, tablet, and basic mobile phone ownership and the presence of health apps by sociodemographic factors and self-reported hypertension status (ie, history) in a nationally representative sample of US adults, and to describe whether mobile devices are associated with health goal achievement, medical decision making, and patient-provider communication. METHODS: Data from 3285 respondents from the 2017 Health Information National Trends Survey were analyzed. Participants were asked if they owned a smartphone, tablet, or basic mobile phone and if they had health apps on a smartphone or tablet. Participants were also asked if their smartphones or tablets helped them achieve a health-related goal like losing weight, make a decision about how to treat an illness, or talk with their health care providers. Chi-square analyses were conducted to test for differences in mobile device ownership, health app presence, and app helpfulness by patient characteristics. RESULTS: Approximately 1460 (37.6% weighted prevalence) participants reported a history of hypertension. Tablet and smartphone ownership were lower in participants with a history of hypertension than in those without a history of hypertension (55% vs 66%, P=.001, and 86% vs 68%, P<.001, respectively). Participants with a history of hypertension were more likely to own a basic mobile phone only as compared to those without a history of hypertension (16% vs 9%, P<.001). Among those with a history of hypertension exclusively, basic mobile phone, smartphone, and tablet ownership were associated with age and education, but not race or sex. Older adults were more likely to report having a basic mobile phone only, whereas those with higher education were more likely to report owning a tablet or smartphone. Compared to those without a history of hypertension, participants with a history of hypertension were less likely to have health-related apps on their smartphones or tablets (45% vs 30%, P<.001) and report that mobile devices helped them achieve a health-related goal (72% vs 63%, P=.01). CONCLUSIONS: Despite the increasing use of smartphones, tablets, and health-related apps, these tools are used less among people with a self-reported history of hypertension. To reach the widest cross-section of patients, a mix of novel mHealth interventions and traditional health communication strategies (eg, print, web based, and in person) are needed to support the diverse needs of people with a history of hypertension.