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The Health Information Technology for Economic and Clinical Health Act is intended to enhance reimbursement of health care providers for meaningful use of electronic health records systems. This presents both opportunities and challenges for public health departments. To earn incentive payments, clinical providers must exchange specified types of data with the public health system, such as immunization and syndromic surveillance data and notifiable disease reporting. However, a crisis looms because public health's information technology systems largely lack the capabilities to accept the types of data proposed for exchange. Cloud computing may be a solution for public health information systems. Through shared computing resources, public health departments could reap the benefits of electronic reporting within federal funding constraints. [ABSTRACT FROM AUTHOR]

The United States faces tremendous challenges with its healthcare system. By any standard, it is expensive and performs poorly in most measures of health and thus, is in great need of reform. But how do we reform things without making the situation worse? Some of the more fundamental problems arise from the combination of a fee-for-service payment system for physicians with insurance-based financing care. This combination results in conflicts among the interests of patients, physicians and payers. This paper examines this issue from a decision analytic perspective, starting with a definition of the patient-centered view, and an assessment of the practicality of controlling costs by making healthcare more patient-centric. It then illustrates how fee-for-service models corrupt decision-making and other solutions designed to reign in the abuses of the fee-for-service model and also negatively impacts the quality of decision making for individual patients. Whatever the strategies for health reform, the degree of patient-centeredness of care is a benchmark that allows policy makers to understand how far they have had to deviate from optimal to achieve the desired ends of cost control. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia is a common severe syndrome with a highly variable pattern of symptoms. The medications used to treat this disorder are expensive and may cause severe adverse effects. Little is known about how the public perceives health outcomes in schizophrenia or the potential adverse effects of antipsychotic medication. This complicates the use of standard cost-effectiveness analysis to set priorities for health resource allocation.Objective: In this study, we measured utility weights for a set of health states derived from Positive and Negative Symptom Scale (PANSS) scores, and a set of health states that included the presence of common adverse effects of medication, thus creating utility mapping function for clinical data.Methods: We presented a convenience sample of members of a large commercial Internet survey panel with digital video materials portraying eight different patterns of schizophrenia with varying levels of positive, negative and cognitive symptoms, and five common adverse effects of antipsychotic medications. We then elicited their standard gamble (SG) and visual analog scale (VAS) ratings using iMPACT3 computer program, with an automated error repair feature, deliberately over-sampling minority ethnic groups in the panel. We censored subjects with uncorrected errors in ratings and estimated utilities for each state by re-weighting responses to match United States population demographics.Subjects: 620 well-educated, ethnically diverse volunteers (54% Caucasian), who spanned a broad range of age groups and geographical regions of the US participated in this study.Results: Because of evidence of bias in ratings, 175 (29%) subjects with internal inconsistencies in ratings were censored from estimates of mean population utilities. In the remaining 441 subjects, SG utilities, re-weighted to match US population demographic profiles, ranged from 0.88 for mild schizophrenia to 0.47 extremely severe schizophrenia. Variability in the types of symptoms exhibited (positive, negative or cognitive) was less important to participants than the overall severity of each state. Modest reductions in symptoms (for example, from severe to moderate or moderate to mild) were associated with relatively large changes in utility (0.12-0.19). Adverse effects decreased utilities for states by amounts ranging from 0.09 (pseudo-parkinsonism) to 0.05 (obesity).Conclusions: The public views schizophrenia is a very disabling syndrome and treatments that reduce symptoms produce important gains in utility, even if they do not induce a complete remission. Adverse effects significantly reduce utilities for states; therefore, cost-effectiveness analyses for this disorder should take adverse effects of treatment into consideration. [ABSTRACT FROM AUTHOR]

Background: Electronic health records (EHRs) commonly contain patient addresses that provide valuable data for geocoding and spatial analysis, enabling more comprehensive descriptions of individual patients for clinical purposes. Despite the widespread use of EHRs in clinical decision support and interventions, no systematic review has examined the extent to which spatial analysis is used to characterize patient phenotypes., Objective: This study reviews advanced spatial analyses that used individual-level health data from EHRs within the United States to characterize patient phenotypes., Methods: We systematically evaluated English-language, peer-reviewed studies from the PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases from inception to August 20, 2023, without imposing constraints on study design or specific health domains., Results: A substantial proportion of studies (>85%) were limited to geocoding or basic mapping without implementing advanced spatial statistical analysis, leaving only 49 studies that met the eligibility criteria. These studies used diverse spatial methods, with a predominant focus on clustering techniques, while spatiotemporal analysis (frequentist and Bayesian) and modeling were less common. A noteworthy surge (n=42, 86%) in publications was observed after 2017. The publications investigated a variety of adult and pediatric clinical areas, including infectious disease, endocrinology, and cardiology, using phenotypes defined over a range of data domains such as demographics, diagnoses, and visits. The primary health outcomes investigated were asthma, hypertension, and diabetes. Notably, patient phenotypes involving genomics, imaging, and notes were limited., Conclusions: This review underscores the growing interest in spatial analysis of EHR-derived data and highlights knowledge gaps in clinical health, phenotype domains, and spatial methodologies. We suggest that future research should focus on addressing these gaps and harnessing spatial analysis to enhance individual patient contexts and clinical decision support., (©Abolfazl Mollalo, Bashir Hamidi, Leslie A Lenert, Alexander V Alekseyenko. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 15.10.2024.)

Background: Although tobacco use is associated with elevated morbidity and mortality, its use remains widespread among adults within the United States. Nicotine Replacement Therapy (NRT) products are effective aids that improve rates of tobacco cessation. Many smokers interact with the medical system, such as during hospitalization, without their tobacco use addressed. Hospitalization is a teachable moment for patients to make health-related changes, including tobacco cessation., Methods: Retrospective cohort study of adult patients in a university-based patient-centered medical home from 2012 to 2021 evaluating the proportion of adults who smoke who received at least one prescription for NRT. Logistic regression models were used to analyze the association of being hospitalized and receipt of a NRT prescription., Results: Of the 4,072 current smokers identified, 1,182 (29%) received at least one prescription for NRT during the study period. Hospitalization was associated with increased odds of receiving a NRT prescription (OR 1.68). Of 1,844 current smokers with a hospitalization during the study period, 1,078 (58%) never received a prescription for NRT at any point. Only 87 (5%) of the smokers received a prescription for NRT during hospitalization or at the time of hospital discharge., Conclusions: Despite hospitalization being associated with NRT prescribing, most patients who use tobacco and are hospitalized are not prescribed NRT. Hospitalization is an underutilized opportunity for both hospitalists and primary care physicians to intervene on smoking cessation through education and prescription of tobacco cessation aids., Competing Interests: Conflict of Interest Statement Benjamin Toll testifies on behalf of plaintiffs who have filed litigation against the tobacco industry. All other authors report no conflicts of interest., (Copyright © 2023. Published by Elsevier Inc.)

Cancer is the second leading cause of death in the United States, and breast cancer is the fourth leading cause of cancer-related death, with 42,275 women dying of breast cancer in the United States in 2020. Screening is a key strategy for reducing mortality from breast cancer and is recommended by various national guidelines. This study applies machine learning classification methods to the task of predicting which patients will fail to complete a mammogram screening after having one ordered, as well as understanding the underlying features that influence predictions. The results show that a small group of patients can be identified that are very unlikely to complete mammogram screening, enabling care managers to focus resources., Significance: The motivation behind this study is to create an automated system that can identify a small group of individuals that are at elevated risk for not following through completing a mammogram screening. This will enable interventions to boost screening to be focused on patients least likely to complete screening., (© 2023 The Authors; Published by the American Association for Cancer Research.)

The COVID-19 pandemic exposed multiple weaknesses in the nation's public health system. Therefore, the American College of Medical Informatics selected "Rebuilding the Nation's Public Health Informatics Infrastructure" as the theme for its annual symposium. Experts in biomedical informatics and public health discussed strategies to strengthen the US public health information infrastructure through policy, education, research, and development. This article summarizes policy recommendations for the biomedical informatics community postpandemic. First, the nation must perceive the health data infrastructure to be a matter of national security. The nation must further invest significantly more in its health data infrastructure. Investments should include the education and training of the public health workforce as informaticians in this domain are currently limited. Finally, investments should strengthen and expand health data utilities that increasingly play a critical role in exchanging information across public health and healthcare organizations., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Public health needs up-to-date information for surveillance and response. As healthcare application programming interfaces become widely available, a novel data gathering mechanism could provide public health with critical information in a timely fashion to respond to a fast-moving epidemic. In this article, we extrapolate from our experiences using a Fast Healthcare Interoperability Resource-based architecture for infectious disease surveillance for sexually transmitted diseases to its application to gather case information for an outbreak. One of the challenges with a fast-moving outbreak is to accurately assess its demand on healthcare resources, since information specific to comorbidities is often not available. These comorbidities are often associated with poor prognosis and higher resource utilization. If the comorbidity data and other clinical information were readily available to public health workers, they could better address community disruption and manage healthcare resources. The use of FHIR resources available through application programming and filtered through tools such as described herein will give public health the flexibility needed to investigate rapidly emerging disease while protecting patient privacy., (Published by Oxford University Press on behalf of the American Medical Informatics Association 2020. This work is written by US Government employees and is in the public domain in the US.)

The novel coronavirus disease 2019 infection poses serious challenges to the healthcare system that are being addressed through the creation of new unique and advanced systems of care with disjointed care processes (eg, telehealth screening, drive-through specimen collection, remote testing, telehealth management). However, our current regulations on the flows of information for clinical care and research are antiquated and often conflict at the state and federal levels. We discuss proposed changes to privacy regulations such as the Health Insurance Portability and Accountability Act designed to let health information seamlessly and frictionlessly flow among the health entities that need to collaborate on treatment of patients and, also, allow it to flow to researchers trying to understand how to limit its impacts., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

The Office of the National Coordinator will be defining the architecture of the Nationwide Health Information Network (NWHIN) together with the proposed HealtheWay public/private partnership as a development and funding strategy. There are a number of open questions--for example, what is the best way to realize the benefits of health information exchange? How valuable are regional health information organizations in comparison with a more direct approach? What is the role of the carriers in delivering this service? The NWHIN is to exist for the public good, and thus shares many traits of the common law notion of 'common carriage' or 'public calling,' the modern term for which is network neutrality. Recent policy debates in Congress and resulting potential regulation have implications for key stakeholders within healthcare that use or provide services, and for those who exchange information. To date, there has been little policy debate or discussion about the implications of a neutral NWHIN. This paper frames the discussion for future policy debate in healthcare by providing a brief education and summary of the modern version of common carriage, of the key stakeholder positions in healthcare, and of the potential implications of the network neutrality debate within healthcare.

The AMIA biomedical informatics (BMI) core competencies have been designed to support and guide graduate education in BMI, the core scientific discipline underlying the breadth of the field's research, practice, and education. The core definition of BMI adopted by AMIA specifies that BMI is 'the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health.' Application areas range from bioinformatics to clinical and public health informatics and span the spectrum from the molecular to population levels of health and biomedicine. The shared core informatics competencies of BMI draw on the practical experience of many specific informatics sub-disciplines. The AMIA BMI analysis highlights the central shared set of competencies that should guide curriculum design and that graduate students should be expected to master.

In the midst of a US $30 billion USD investment in the Nationwide Health Information Network (NwHIN) and electronic health records systems, a significant change in the architecture of the NwHIN is taking place. Prior to 2010, the focus of information exchange in the NwHIN was the Regional Health Information Organization (RHIO). Since 2010, the Office of the National Coordinator (ONC) has been sponsoring policies that promote an internet-like architecture that encourages point to-point information exchange and private health information exchange networks. The net effect of these activities is to undercut the limited business model for RHIOs, decreasing the likelihood of their success, while making the NwHIN dependent on nascent technologies for community level functions such as record locator services. These changes may impact the health of patients and communities. Independent, scientifically focused debate is needed on the wisdom of ONC's proposed changes in its strategy for the NwHIN.

The United States faces tremendous challenges with its healthcare system. By any standard, it is expensive and performs poorly in most measures of health and thus, is in great need of reform. But how do we reform things without making the situation worse? Some of the more fundamental problems arise from the combination of a fee-for-service payment system for physicians with insurance-based financing care. This combination results in conflicts among the interests of patients, physicians and payers. This paper examines this issue from a decision analytic perspective, starting with a definition of the patient-centered view, and an assessment of the practicality of controlling costs by making healthcare more patient-centric. It then illustrates how fee-for-service models corrupt decision-making and other solutions designed to reign in the abuses of the fee-for-service model and also negatively impacts the quality of decision making for individual patients. Whatever the strategies for health reform, the degree of patient-centeredness of care is a benchmark that allows policy makers to understand how far they have had to deviate from optimal to achieve the desired ends of cost control.

Health care providers are legally obliged to report cases of specified diseases to public health authorities, but existing manual, provider-initiated reporting systems generally result in incomplete, error-prone, and tardy information flow. Automated laboratory-based reports are more likely accurate and timely, but lack clinical information and treatment details. Here, we describe the Electronic Support for Public Health (ESP) application, a robust, automated, secure, portable public health detection and messaging system for cases of notifiable diseases. The ESP application applies disease specific logic to any complete source of electronic medical data in a fully automated process, and supports an optional case management workflow system for case notification control. All relevant clinical, laboratory and demographic details are securely transferred to the local health authority as an HL7 message. The ESP application has operated continuously in production mode since January 2007, applying rigorously validated case identification logic to ambulatory EMR data from more than 600,000 patients. Source code for this highly interoperable application is freely available under an approved open-source license at http://esphealth.org.

Objective: The objective of this study was to demonstrate a multivariate health state approach to analyzing complex disease data that allows projection of long-term outcomes using clustering, Markov modeling, and preference weights., Subjects: We studied patients hospitalized 30 to 364 days with refractory schizophrenia at 15 Veterans Affairs medical centers., Study Design: We conducted a randomized clinical trial comparing clozapine, an atypical antipsychotic, and haloperidol, a conventional antipsychotic., Methods: Health status instruments measuring disease-related symptoms and drug side effects were administered in face-to-face interviews at baseline, 6 weeks, and quarterly follow-up intervals for 1 year. Cost data were derived from Veterans Affairs records supplemented by interviews. K-means clustering was used to identify a small number of health states for each instrument. Markov modeling was used to estimate long-term outcomes., Results: Multivariate models with 7 and 6 states, respectively, were required to describe patterns of psychiatric symptoms and side effects (movement disorders). Clozapine increased the proportion of clients in states characterized by mild psychiatric symptoms and decreased the proportion with severe positive symptoms but showed no long-term benefit for negative symptoms. Clozapine dramatically increased the proportion of patients with no movement side effects and decreased incidences of mild akathisia. Effects on extrapyramidal symptoms and tardive dyskinesia were far less pronounced and slower to develop. Markov modeling confirms the consistency of these findings., Conclusions: Analyzing complex disease data using multivariate health state models allows a richer understanding of trial effects and projection of long-term outcomes. Although clozapine generates substantially fewer side effects than haloperidol, its impact on psychiatric aspects of schizophrenia is less robust and primarily involves positive symptoms.

Background: There is a wide range of therapeutic options for migraine headaches, yet little is known about how patients value different treatment alternatives nor how to tailor treatments to patients' preferences., Objective: Assess patients' preferences for outcomes of treatment of migraine headache based on their marginal willingness to pay (WTP) for treatment attributes., Materials and Methods: In an Internet-based study, we used computer software to measure participants' WTP for a hypothetical ideal drug (one that was 100% effective, worked quickly, and had no adverse effects) and for other hypothetical drugs, each with one "less than ideal" attribute of performance., Subjects: Two hundred fifty-seven self-identified migraineurs recruited via an Internet Web site., Results: A high proportion of participants in the study had symptoms consistent with migraine etiology of headache (99%). Median "out-of-pocket" monthly WTP cost for an ideal migraine therapy was 130 dollars. WTP was associated with participants' own migraine experience: severity of pain, frequency of headaches, and the types of medications used in the past. WTP was reduced when pharmaceuticals offered less benefit, ranging from a mean of 74% of ideal for treatments that failed to relieve nausea, to 43% of ideal in treatments associated with a 50% chance of a rebound headache., Conclusions: There is wide variability in patients' strength of preference for different attributes of migraine therapy. Choice of therapy for migraine headache should be individualized based on patients' preferences. WTP measures appear to be a valid and feasible metric for quantifying treatment preferences for migraine therapies.