Measuring Primary Care Spending in the US by State.

This case series identifies states' estimates of primary care spending and recommends steps policymakers can take toward standardizing these estimates.

Participatory logic modeling in a multi-site initiative to advance implementation science.

BACKGROUND: Logic models map the short-term and long-term outcomes that are expected to occur with a program, and thus are an essential tool for evaluation. Funding agencies, especially in the United States (US), have encouraged the use of logic models among their grantees. They also use logic models to clarify expectations for their own funding initiatives. It is increasingly recognized that logic models should be developed through a participatory approach which allows input from those who carry out the program being evaluated. While there are many positive examples of participatory logic modeling, funders have generally not engaged grantees in developing the logic model associated with their own initiatives. This article describes an instance where a US funder of a multi-site initiative fully engaged the funded organizations in developing the initiative logic model. The focus of the case study is Implementation Science Centers in Cancer Control (ISC3), a multi-year initiative funded by the National Cancer Institute. METHODS: The reflective case study was collectively constructed by representatives of the seven centers funded under ISC3. Members of the Cross-Center Evaluation (CCE) Work Group jointly articulated the process through which the logic model was developed and refined. Individual Work Group members contributed descriptions of how their respective centers reviewed and used the logic model. Cross-cutting themes and lessons emerged through CCE Work Group meetings and the writing process. RESULTS: The initial logic model for ISC3 changed in significant ways as a result of the input of the funded groups. Authentic participation in the development of the logic model led to strong buy-in among the centers, as evidenced by their utilization. The centers shifted both their evaluation design and their programmatic strategy to better accommodate the expectations reflected in the initiative logic model. CONCLUSIONS: The ISC3 case study demonstrates how participatory logic modeling can be mutually beneficial to funders, grantees and evaluators of multi-site initiatives. Funded groups have important insights about what is feasible and what will be required to achieve the initiative's stated objectives. They can also help identify the contextual factors that either inhibit or facilitate success, which can then be incorporated into both the logic model and the evaluation design. In addition, when grantees co-develop the logic model, they have a better understanding and appreciation of the funder's expectations and thus are better positioned to meet those expectations.

Diabetes and Hypertension Prevention and Control in Community Health Centers: Impact of the Affordable Care Act.

Access to care significantly improved following the implementation of the Patient Protection and Affordable Care Act. Since its implementation, the number of uninsured Americans has significantly decreased. Medicaid expansion played an important role in community health centers, who serve historically marginalized populations, leading to increased clinic revenue, and improved access to care. As the continuous Medicaid enrollment provision established during the pandemic ended, and states have to make decisions about their program eligibility, exploring the impact of Medicaid expansion on the detection, and management of hypertension and diabetes could inform these decisions. We summarized the effect of Medicaid expansion on community health centers and their patients specific to hypertension and diabetes from existing literature. These studies suggest the beneficial impact of the Affordable Care Act and acquiring insurance on diabetes and hypertension disease detection, treatment, and control for patients receiving care in community health centers. Overall, these studies suggest the clear importance of health insurance coverage, and notably insurance stability, on diabetes and hypertension control.

Health Literacy and Systemic Racism-Using Clear Communication to Reduce Health Care Inequities.

This Viewpoint describes why people need health information that is easy to understand to make informed decisions about health care and why this is necessary to avoid systemic racism.

The Impact of the Affordable Care Act Medicaid Expansion on Acute Diabetes Complications Among Community Health Center Patients.

OBJECTIVE: This study evaluates whether patients residing in expansion states have a greater increase in outpatient diagnoses of acute diabetes complications than those living in non-expansion states following the implementation of the Affordable Care Act (ACA). METHODS: This retrospective cohort study uses electronic health records (EHR) from 10,665 non-pregnant patients, aged 19 to 64 years old who were diagnosed with diabetes in 2012 or 2013 from 347 community health centers (CHCs) across 16 states (11 expansion and 5 non-expansion states). Patients included had ≥1 outpatient ambulatory visit in each of these periods: pre-ACA: 2012 to 2013, post-ACA: 2014 to 2016, and post-ACA: 2017 to 2019. Acute diabetes-related complications were identified using International Classification Diseases (ICD-9-CM and ICD-10-CM) codes classification and could occur on or after diagnosis of diabetes. We performed difference-in-differences (DID) analysis using a generalized estimating equation to compare the change in rates of acute diabetes complications by year and by Medicaid expansion status. RESULTS: There was a greater increase after year 2015 in visits related to abnormal blood glucose among patient living in Medicaid expansion states than in non-expansion states (2017 DID = 0.041, 95% CI = 0.027-0.056). Although both visits due to any acute diabetes complications and infection-related diabetes complications were higher among patients living in Medicaid expansion states, there was no difference in the trend overtime between expansion and non-expansion states. CONCLUSION: We found a significantly greater rate of visits for abnormal blood glucose in patients receiving care in expansion states relative to patients in CHCs in non-expansion states starting in 2015. Additional resources for these clinics, such as the ability to provide blood glucose monitoring devices or mailed/delivered medications, could substantially benefit patients with diabetes.

Precision Ecologic Medicine: Tailoring Care to Mitigate Impacts of Climate Change.

As recent extreme weather events demonstrate, climate change presents unprecedented and increasing health risks, disproportionately so for disadvantaged communities in the U.S. already experiencing health disparities. As patients in these frontline communities live through extreme weather events, socioeconomic and health stressors are compounded; thus, their healthcare teams will need tools to provide precision ecologic medicine approaches to their care. Many primary care teams are taking actionable steps to bring community-level socioeconomic data ("community vital signs") into electronic medical records, to facilitate tailoring care based on a given patient's circumstances. This work can be extended to include environmental risk data, thus equipping healthcare teams with an awareness of clinical and community vital signs and making them better positioned to mitigate climate impacts on health. For example, if healthcare teams can easily identify patients who have multiple chronic conditions and live in an urban heat island, they can proactively arrange to "prescribe" an air conditioner, heat pump, and/or air purifier. Or, when a severe storm/heat event/poor air quality event is predicted, they can take preemptive steps to get help to patients at high medical and socioeconomic risk, rather than waiting for them to arrive in the emergency department. Advances in health information technologies now make it technically feasible to integrate a wealth of publicly-available community-level data into EMRs. Efforts to bring this contextual data into clinical settings must be accelerated to equip healthcare teams to provide precision ecologic medicine interventions to their patients.

An observational study of health insured visits for children following Medicaid eligibility expansion for adults among a linked cohort of parents and children.

Despite its focus on adults, the Affordable Care Act (ACA) Medicaid expansion led to increased health insurance enrollment for children in the United States. Previous studies looked at parent and child insurance changes separately, or used a single survey response item to understand changes in health insurance for parents and children. It is, however, important to understand the connection between parent and child insurance changes together (not individually) using data sources that account for insurance over time. Therefore, to understand the association of parental health insurance on their children's coverage, leveraging a cohort of linked families seen in community health centers (CHCs), we used electronic health records to link a cohort of parents and children with ≥1 visit to a CHC in a Medicaid expansion state pre- (1/1/2012-12/31/2013) and ≥1 visit post-ACA (1/1/2014-12/31/2018) and determined primary payer type for all visits. This observational, cohort study assessed the rate of insured visits for children pre- to post-ACA across four parental insurance groups (always insured, gained Medicaid, discontinuously insured, never insured) using Poisson mixed effects models. We included 335 CHCs across 7 United States. Insurance rates were highest (~95 insured visits/100 visits) for children of parents who were always insured; rates were lowest for children of parents who were never insured (~83 insured visits/100 visits). Children with a parent who gained Medicaid had 4.4% more insured visits post- compared to pre-ACA (adjusted relative rates  = 1.044, 95% confidence interval: 1.014, 1.074). When comparing changes from pre- to post-ACA between parent insurance groups, children's insured visit rates were significantly higher for children of parents who gained Medicaid (reference) compared to children of parents who were always insured (adjusted ratio of rate ratio: 0.963, confidence interval: 0.935-0.992). Despite differences in Medicaid eligibility for children and adults, health insurance patterns were similar for linked families seen in CHCs. Findings suggest consideration should be paid to parent health insurance options when trying to increase children's coverage.

Diabetes And The Fragmented State Of US Health Care And Policy.

Progress in the prevention and treatment of type 2 diabetes-the dominant form of diabetes-appears to have stalled in the US over the past decade, and diabetes-related morbidity has increased nationally. The most geographically and socioeconomically disadvantaged segments of the population have been especially hard hit, and interventions that reduce the risk for diabetes have not reached these populations. In this overview article we lay out how fragmentation in health policy and governance, payers and reimbursement design, and service delivery in the US has contributed to low accountability and coordination, and thus stagnation and persistent inequities. We also review the evidence regarding past, ongoing, and new reforms that may help address fragmentation, lower diabetes burdens, and narrow disparities.

Affordable Care Act Medicaid expansion and access to primary-care based smoking cessation assistance among cancer survivors: an observational cohort study.

BACKGROUND: Smoking among cancer survivors can increase the risk of cancer reoccurrence, reduce treatment effectiveness and decrease quality of life. Cancer survivors without health insurance have higher rates of smoking and decreased probability of quitting smoking than cancer survivors with health insurance. This study examines the associations of the Affordable Care Act (ACA) Medicaid insurance expansion with smoking cessation assistance and quitting smoking among cancer survivors seen in community health centers (CHCs). METHODS: Using electronic health record data from 337 primary care community health centers in 12 states that expanded Medicaid eligibility and 273 CHCs in 8 states that did not expand, we identified adult cancer survivors with a smoking status indicating current smoking within 6 months prior to ACA expansion in 2014 and ≥ 1 visit with smoking status assessed within 24-months post-expansion. Using an observational cohort propensity score weighted approach and logistic generalized estimating equation regression, we compared odds of quitting smoking, having a cessation medication ordered, and having ≥6 visits within the post-expansion period among cancer survivors in Medicaid expansion versus non-expansion states. RESULTS: Cancer survivors in expansion states had higher odds of having a smoking cessation medication order (adjusted odds ratio [aOR] = 2.54, 95%CI = 1.61-4.03) and higher odds of having ≥6 office visits than those in non-expansion states (aOR = 1.82, 95%CI = 1.22-2.73). Odds of quitting smoking did not differ significantly between patients in Medicaid expansion versus non-expansion states. CONCLUSIONS: The increased odds of having a smoking cessation medication order among cancer survivors seen in Medicaid expansion states compared with those seen in non-expansion states provides evidence of the importance of health insurance coverage in accessing evidence-based tobacco treatment within CHCs. Continued research is needed to understand why, despite increased odds of having a cessation medication prescribed, odds of quitting smoking were not significantly higher among cancer survivors in Medicaid expansion states compared to non-expansion states.

Patient-level factors associated with receipt of preventive care in the safety net.

Prevention is critical to optimizing health, yet most people do not receive all recommended preventive services. As the complexity of preventive recommendations increases, there is a need for new measurements to capture the degree to which a person is up to date, and identify individual-level barriers and facilitators to receiving needed preventive care. We used electronic health record data from a national network of community health centers (CHCs) in the United States (US) during 2014-2017 to measure patient-level up-to-date status with preventive ratios (measuring up-to-date person-time denoted as a percent) for 12 preventive services and an aggregate preventive index. We use negative binomial regression to identify factors associated with up-to-date preventive care. We assessed 267,767 patients across 165 primary care clinics. Mean preventive ratios ranged from 8.7% for Hepatitis C screening to 83.3% for blood pressure screening. The mean aggregate preventive index was 43%. Lack of health insurance, smoking, and homelessness were associated with lower preventive ratios for most cancer and cardiovascular screenings (p < 0.05). Having more ambulatory visits, better continuity of care, and enrollment in the patient portal were positively associated with the aggregate preventive index (p < 0.05) and higher preventive ratios for all services (p < 0.05) except chlamydia and HIV screening. Overall, receipt of preventive services was low. CHC patients experience many barriers to receiving needed preventive care, but certain healthcare behaviors - regular visits, usual provider continuity, and patient portal enrollment - were consistently associated with more up-to-date preventive care. These associations should inform future efforts to improve preventive care delivery.

Effectiveness of an insurance enrollment support tool on insurance rates and cancer prevention in community health centers: a quasi-experimental study.

BACKGROUND: Following the ACA, millions of people gained Medicaid insurance. Most electronic health record (EHR) tools to date provide clinical-decision support and tracking of clinical biomarkers, we developed an EHR tool to support community health center (CHC) staff in assisting patients with health insurance enrollment documents and tracking insurance application steps. The objective of this study was to test the effectiveness of the health insurance support tool in (1) assisting uninsured patients gaining insurance coverage, (2) ensuring insurance continuity for patients with Medicaid insurance (preventing coverage gaps between visits); and (3) improving receipt of cancer preventive care. METHODS: In this quasi-experimental study, twenty-three clinics received the intervention (EHR-based insurance support tool) and were matched to 23 comparison clinics. CHCs were recruited from the OCHIN network. EHR data were linked to Medicaid enrollment data. The primary outcomes were rates of uninsured and Medicaid visits. The secondary outcomes were receipt of recommended breast, cervical, and colorectal cancer screenings. A comparative interrupted time-series using Poisson generalized estimated equation (GEE) modeling was performed to evaluate the effectiveness of the EHR-based tool on the primary and secondary outcomes. RESULTS: Immediately following implementation of the enrollment tool, the uninsured visit rate decreased by 21.0% (Adjusted Rate Ratio [RR] = 0.790, 95% CI = 0.621-1.005, p = .055) while Medicaid-insured visits increased by 4.5% (ARR = 1.045, 95% CI = 1.013-1.079) in the intervention group relative to comparison group. Cervical cancer preventive ratio increased 5.0% (ARR = 1.050, 95% CI = 1.009-1.093) immediately following implementation of the enrollment tool in the intervention group relative to comparison group. Among patients with a tool use, 81% were enrolled in Medicaid 12 months after tool use. For the 19% who were never enrolled in Medicaid following tool use, most were uninsured (44%) at the time of tool use. CONCLUSIONS: A health insurance support tool embedded within the EHR can effectively support clinic staff in assisting patients in maintaining their Medicaid coverage. Such tools may also have an indirect impact on evidence-based practice interventions, such as cancer screening. TRIAL REGISTRATION: This study was retrospectively registered on February 4th, 2015 with Clinicaltrials.gov (#NCT02355262). The registry record can be found at https://www.clinicaltrials.gov/ct2/show/NCT02355262 .

Shared Language for Shared Work in Population Health.

People working on behalf of population health, community health, or public health often experience confusion or ambiguity in the meaning of these and other common terms-the similarities and differences and how they bear on the tasks and division of labor for care delivery and public health. Shared language must be clear enough to help, not hinder people working together as they ultimately come to mutual understanding of roles, responsibilities, and actions in their joint work. Based on an iterative lexicon development process, the authors developed and propose a definitional framework as an aid to navigating among related population and community health terms. These terms are defined, similarities and differences clarified, and then organized into 3 categories that reflect goals, realities, and ways to get the job done. Goals include (a) health as well-being for persons, (b) population health as that goal expressed in measurable terms for groups, and (c) community health as population health for particular communities of interest, geography, or other defining characteristic-groups with shared identity and particular systemic influences on health. Realities are social determinants as influences, health disparities as effects, and health equity as both a goal and a design principle. Ways to get the job done include health care delivery systems for enrollees and public health in population-based civic activities-with a broad zone of collaboration where streams of effort converge in partnership with served communities. This map of terms can enable people to move forward together in a broad zone of collaboration for health with less confusion, ambiguity, and conflict.

Rates of Undiagnosed Hypertension and Diagnosed Hypertension Without Anti-hypertensive Medication Following the Affordable Care Act.

BACKGROUND: The Affordable Care Act (ACA) Medicaid expansion improved access to health insurance and health care services. This study assessed whether the rate of patients with undiagnosed hypertension and the rate of patients with hypertension without anti-hypertensive medication decreased post-ACA in community health center (CHC). METHODS: We analyzed electronic health record data from 2012 to 2017 for 126,699 CHC patients aged 19-64 years with ≥1 visit pre-ACA and ≥1 post-ACA in 14 Medicaid expansion states. We estimated the prevalence of patients with undiagnosed hypertension (high blood pressure reading without a diagnosis for ≥1 day) and the prevalence of patients with hypertension without anti-hypertensive medication by year and health insurance type (continuously uninsured, continuously insured, gained insurance, and discontinuously insured). We compared the time to diagnosis or to anti-hypertensive medication pre- vs. post-ACA. RESULTS: Overall, 37.3% of patients had undiagnosed hypertension and 27.0% of patients with diagnosed hypertension were without a prescribed anti-hypertensive medication for ≥1 day during the study period. The rate of undiagnosed hypertension decreased from 2012 through 2017. Those who gained insurance had the lowest rates of undiagnosed hypertension (2012: 14.8%; 2017: 6.1%). Patients with hypertension were also more likely to receive anti-hypertension medication during this period, especially uninsured patients who experienced the largest decline (from 47.0% to 8.1%). Post-ACA, among patients with undiagnosed hypertension, time to diagnosis was shorter for those who gained insurance than other insurance types. CONCLUSIONS: Those who gained health insurance were appropriately diagnosed with hypertension faster and more frequently post-ACA than those with other insurance types. CLINICAL TRIALS REGISTRATION: Trial Number NCT03545763.

Launching a Statewide COVID-19 Primary Care Hotline and Telemedicine Service.

To respond to the COVID-19 pandemic and recover from its aftermath, primary care teams will face waves of overwhelming demand for information and the need to significantly transform care delivery. INNOVATION: Oregon Health & Science University's primary care team envisioned and implemented the COVID-19 Connected Care Center, a statewide telephone "hotline" service. RESULTS: The hotline has taken more than 5825 calls from patients in 33 of Oregon's 36 counties in less than 3 months. In preliminary survey data, 86% of patients said their questions were answered during the call, 90% would recommend this service, and 70% reported a reduction in stress levels about coronavirus. In qualitative interviews, patients reported their questions answered, short wait times, nurses spent time as needed, and appropriate follow-up was arranged. CONCLUSION: Academic health centers may have the capacity to leverage their extensive resources to rapidly launch a multiphased pandemic response that meets peoples' need for information and access to primary care, while minimizing risk of infection and emergency department use and rapidly supporting primary care teams to make the necessary operational changes to do the same in their communities. Such efforts require external funding in a fee-for-service payment model.

Prevalence of Pre-existing Conditions Among Community Health Center Patients With COVID-19: Implications for the Patient Protection and Affordable Care Act.

BACKGROUND: Short- and long-term effects of COVID-19 will likely be designated pre-existing conditions. We describe the prevalence of pre-existing conditions among community health center patients overall and those with COVID-19 by race/ethnicity. MATERIALS AND METHODS: This cross-sectional study used electronic health record data from OCHIN, a network of 396 community health centers across 14 states. RESULTS: Among all patients with COVID-19, 33% did not have a pre-existing condition before the pandemic. Up to half of COVID-19-positive non-Hispanic Asians (51%), Hispanic (36%), and non-Hispanic black (28%) patients did not have a pre-existing condition before the pandemic. CONCLUSIONS: The future of the Patient Protection and Affordable Care Act is uncertain, and the long-term health effects of COVID-19 are largely unknown; therefore, ensuring people with pre-existing conditions can acquire health insurance is essential to achieving health equity.

New hypertension and diabetes diagnoses following the Affordable Care Act Medicaid expansion.

OBJECTIVE: To assess the Affordable Care Act (ACA) Medicaid expansion's impact on new hypertension and diabetes diagnoses in community health centres (CHCs). DESIGN: Rates of new hypertension and diabetes diagnoses were computed using generalised estimating equation Poisson models and we tested the difference-in-difference (DID) pre-ACA versus post-ACA in states that expanded Medicaid compared with those that did not. SETTING: We used electronic health record data (pre-ACA: 1 January 2012-31 December 2013-post-ACA: 1 January 2014-31 December 2016) from the Accelerating Data Value Across a National Community Health Center Network clinical data network. We included clinics with ≥50 patients contributing to person-time-at risk in each study year. PARTICIPANTS: Patients aged 19-64 with ≥1 ambulatory visit in the study period were included. We then excluded patients who were pregnant during the study period (N=127 530). For the hypertension outcome, we excluded individuals with a diagnosis of hypertension prior to the start of the study period, those who had a hypertension diagnosis on their first visit to a clinic or their first visit after 3 years without a visit, and those who had a diagnosis more than 3 years after their last visit (pre-ACA non-expansion N=130 973; expansion N=193 198; post-ACA non-expansion N=186 341; expansion N=251 015). For the diabetes analysis, we excluded patients with a diabetes diagnosis prior to study start, on their first visit or first visit after inactive patient status, and diagnosis while not an active patient (pre-ACA non-expansion N=145 435; expansion N=198 558; post-ACA non-expansion N=215 039; expansion N=264 644). RESULTS: In non-expansion states, adjusted hypertension diagnosis rates saw a relative decrease of 6%, while in expansion states, the adjusted rates saw a relative increase of 7% (DID 1.14, 95% CI 1.11 to 1.18). For diabetes diagnosis, adjusted rates in non-expansion states experienced a significant relative increase of 28% and in expansion states the relative increase was 25%; yet these differences were not significant pre-ACA to post-ACA comparing expansion and non-expansion states (DID 0.98, 95% CI 0.91 to 1.05). CONCLUSION: There was a differential impact of Medicaid expansion for hypertension and diabetes diagnoses. Moderate increases were found in diabetes diagnosis rates among all patients served by CHCs post-ACA (both in expansion and non-expansion states). These increases suggest that ACA-related opportunities to gain health insurance (such as marketplaces and the Medicaid expansion) may have facilitated access to diagnostic tests for this population. The study found a small change in hypertension diagnosis rates from pre-ACA to post-ACA (a decrease in non-expansion and an increase in expansion states). Despite the significant difference between expansion and non-expansion states, the small change from pre-ACA to post-ACA suggests that the diagnosis of hypertension is likely documented for patients, regardless of health insurance availability. Future studies are needed to understand the impact of the ACA on hypertension and diabetes treatment and control.

A Practice-Based Research Network (PBRN) Roadmap for Evaluating COVID-19 in Community Health Centers: A Report From the OCHIN PBRN.

BACKGROUND: Primary care practice-based research networks (PBRNs) are critical laboratories for generating evidence from real-world settings, including studying natural experiments. Primary care's response to the novel coronavirus-19 (COVID-19) pandemic is arguably the most impactful natural experiment in our lifetime. EVALUATING THE IMPACT OF COVID-19: We briefly describe the OCHIN PBRN of community health centers (CHCs), its partnership with implementation scientists, and how we are leveraging this infrastructure and expertise to create a rapid research response evaluating how CHCs across the country responded to the COVID-19 pandemic. COVID-19 RESEARCH ROADMAP: Our research agenda focuses on asking: How has care delivery in CHCs changed due to COVID-19? What impact has COVID-19 had on the delivery of preventive services in CHCs? Which PBRN services (e.g., data surveillance, training, evidence synthesis) are most impactful to real-world practices? What decision-making strategies were used in the PBRN and its practices to make real-time changes in response to the pandemic? What critical factors in successfully and sustainably transforming primary care are illuminated by pandemic-driven changes? DISCUSSION AND CONCLUSIONS: PBRNs enable real-world evaluation of practice change and natural experiments, and thus are ideal laboratories for implementation science research. We present a real-time example of how a PBRN Implementation Laboratory activated a response to study a historic natural experiment, to help other PBRNs charting a course through this pandemic.

Uptake of Preventive Services Among Patients With and Without Multimorbidity.

INTRODUCTION: Patients with multiple chronic conditions (multimorbidity) are seen commonly in primary care practices and often have suboptimal uptake of preventive care owing to competing treatment demands. The complexity of multimorbidity patterns and their impact on receiving preventive services is not fully understood. This study identifies multimorbidity combinations associated with low receipt of preventive services. METHODS: This was a retrospective cohort study of U.S. community health center patients aged ≥19 years. Electronic health record data from 209 community health centers for the January 1, 2014-December 31, 2017 study period were analyzed in 2018-2019. Multimorbidity patterns included physical only, mental health only, and physical and mental health multimorbidity patterns, with no multimorbidity as a reference category. Electronic health record-based preventive ratios (number of months services were up-to-date/total months the patient was eligible for services) were calculated for the 14 preventive services. Negative binomial regression models assessed the relationship between multimorbidity physical and/or mental health patterns and the preventive ratio for each service. RESULTS: There was a variation in receipt of preventive care between multimorbidity groups: individuals with mental health only multimorbidity were less likely to be up-to-date with cardiometabolic and cancer screenings than the no multimorbidity group or groups with physical health conditions, and the physical only multimorbidity group had low rates of depression screening. CONCLUSIONS: This study provided critical insights into receipt of preventive service among adults with multimorbidity using a more precise method for measuring up-to-date preventive care delivery. Findings would be useful to identify target populations for future intervention programs to improve preventive care.