Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center.

OBJECTIVE: Broad adoption of digital pathology (DP) is still lacking, and examples for DP connecting diagnostic, research, and educational use cases are missing. We blueprint a holistic DP solution at a large academic medical center ubiquitously integrated into clinical workflows; researchapplications including molecular, genetic, and tissue databases; and educational processes. MATERIALS AND METHODS: We built a vendor-agnostic, integrated viewer for reviewing, annotating, sharing, and quality assurance of digital slides in a clinical or research context. It is the first homegrown viewer cleared by New York State provisional approval in 2020 for primary diagnosis and remote sign-out during the COVID-19 (coronavirus disease 2019) pandemic. We further introduce an interconnected Honest Broker for BioInformatics Technology (HoBBIT) to systematically compile and share large-scale DP research datasets including anonymized images, redacted pathology reports, and clinical data of patients with consent. RESULTS: The solution has been operationally used over 3 years by 926 pathologists and researchers evaluating 288 903 digital slides. A total of 51% of these were reviewed within 1 month after scanning. Seamless integration of the viewer into 4 hospital systems clearly increases the adoption of DP. HoBBIT directly impacts the translation of knowledge in pathology into effective new health measures, including artificial intelligence-driven detection models for prostate cancer, basal cell carcinoma, and breast cancer metastases, developed and validated on thousands of cases. CONCLUSIONS: We highlight major challenges and lessons learned when going digital to provide orientation for other pathologists. Building interconnected solutions will not only increase adoption of DP, but also facilitate next-generation computational pathology at scale for enhanced cancer research.

Using Health Information Technology to Engage African American Women on Nutrition and Supplement Use During the Preconception Period.

Importance: Healthy nutrition and appropriate supplementation during preconception have important implications for the health of the mother and newborn. The best way to deliver preconception care to address health risks related to nutrition is unknown. Methods: We conducted a secondary analysis of data from a randomized controlled trial designed to study the impact of conversational agent technology in 13 domains of preconception care among 528 non-pregnant African American and Black women. This analysis is restricted to those 480 women who reported at least one of the ten risks related to nutrition and dietary supplement use. Interventions: An online conversational agent, called "Gabby", assesses health risks and delivers 12 months of tailored dialogue for over 100 preconception health risks, including ten nutrition and supplement risks, using behavioral change techniques like shared decision making and motivational interviewing. The control group received a letter listing their preconception risks and encouraging them to talk to a health care provider. Results: After 6 months, women using Gabby (a) reported progressing forward on the stage of change scale for, on average, 52.9% (SD, 35.1%) of nutrition and supplement risks compared to 42.9% (SD, 35.4) in the control group (IRR 1.22, 95% CI 1.03-1.45, P = 0.019); and (b) reported achieving the action and maintenance stage of change for, on average, 52.8% (SD 37.1) of the nutrition and supplement risks compared to 42.8% (SD, 37.9) in the control group (IRR 1.26, 96% CI 1.08-1.48, P = 0.004). For subjects beginning the study at the contemplation stage of change, intervention subjects reported progressing forward on the stage of change scale for 75.0% (SD, 36.3%) of their health risks compared to 52.1% (SD, 47.1%) in the control group (P = 0.006). Conclusion: The scalability of Gabby has the potential to improve women's nutritional health as an adjunct to clinical care or at the population health level. Further studies are needed to determine if improving nutrition and supplement risks can impact clinical outcomes including optimization of weight. Clinical Trial Registration: ClinicalTrials.gov, identifier NCT01827215.

The Value of Diagnostic Information in Personalised Healthcare: A Comprehensive Concept to Facilitate Bringing This Technology into Healthcare Systems.

Health systems around the world seek to address patients' unmet health needs for a range of acute and chronic diseases. Simultaneously, governments strive to keep healthcare spending sustainable, while providing equal access to high-quality care. This has fuelled debate around what constitutes a valuable healthcare intervention in a health system and the corollary consideration of what governments are willing to pay for a certain health intervention. Until recently, the value of information in general, and the value of diagnostic information (VODI) specifically, was not part of the discussion.However, investment in diagnostic information can be a key development as information may guide more effective and efficient healthcare and help maintain an affordable health system. This paper therefore explores ways to best define, evaluate, and reward the value created from diagnostics in healthcare and how to include these value considerations in decision-making processes for diagnostics. The authors ultimately call for a holistic VODI framework that accounts for the full range of potential benefits of diagnostic testing, beyond the traditional clinical and health economic domains, and that is essential to recognise, measure, and fully leverage the benefits of diagnostics for patients, health systems, and society.

Does adding clinical data to administrative data improve agreement among hospital quality measures?

BACKGROUND: Hospital performance measures based on patient mortality and readmission have indicated modest rates of agreement. We examined if combining clinical data on laboratory tests and vital signs with administrative data leads to improved agreement with each other, and with other measures of hospital performance in the nation's largest integrated health care system. METHODS: We used patient-level administrative and clinical data, and hospital-level data on quality indicators, for 2007-2010 from the Veterans Health Administration (VA). For patients admitted for acute myocardial infarction (AMI), heart failure (HF) and pneumonia we examined changes in hospital performance on 30-d mortality and 30-d readmission rates as a result of adding clinical data to administrative data. We evaluated whether this enhancement yielded improved measures of hospital quality, based on concordance with other hospital quality indicators. RESULTS: For 30-d mortality, data enhancement improved model performance, and significantly changed hospital performance profiles; for 30-d readmission, the impact was modest. Concordance between enhanced measures of both outcomes, and with other hospital quality measures - including Joint Commission process measures, VA Surgical Quality Improvement Program (VASQIP) mortality and morbidity, and case volume - remained poor. CONCLUSIONS: Adding laboratory tests and vital signs to measure hospital performance on mortality and readmission did not improve the poor rates of agreement across hospital quality indicators in the VA. INTERPRETATION: Efforts to improve risk adjustment models should continue; however, evidence of validation should precede their use as reliable measures of quality.

Does use of computer technology for perinatal data collection influence data quality?

Population health data, collected worldwide in an effort to monitor mortality and morbidity of mothers and babies, namely, perinatal data, are mandated at a federal level within Australia. The data are used to monitor patterns in midwifery, obstetric and neonatal practice, health outcomes, used for research purposes, funding allocation and education. Accuracy in perinatal data is most often reported via quantitative validation studies of perinatal data collections both internationally and in Australia. These studies report varying levels of accuracy and suggest researchers need to be more aware of the quality of data they use. This article presents findings regarding issues of concern identified by midwives relating to their perceptions of how technology affects the accuracy of perinatal data records. Perinatal data records are perceived to be more complete when completed electronically. However, issues regarding system functionality, the inconsistent use of terminology, lack of data standards and the absence of clear, written records contribute to midwives' perceptions of the negative influence of technology on the quality of perinatal data.

The Technological Growth in eHealth Services.

The infusion of information communication technology (ICT) into health services is emerging as an active area of research. It has several advantages but perhaps the most important one is providing medical benefits to one and all irrespective of geographic boundaries in a cost effective manner, providing global expertise and holistic services, in a time bound manner. This paper provides a systematic review of technological growth in eHealth services. The present study reviews and analyzes the role of four important technologies, namely, satellite, internet, mobile, and cloud for providing health services.

Workforce preparation: the Biohealth computing model for Master and PhD students.

The article addresses the strategic role of workforce preparation in the process of adoption of Systems Medicine as a driver of biomedical research in the new health paradigm. It reports on relevant initiatives, like CASyM, fostering Systems Medicine at EU level. The chapter focuses on the BioHealth Computing Program as a reference for multidisciplinary training of future systems-oriented researchers describing the productive interactions with the Synergy-COPD project.

The integration aspiration.

Integration is a common goal when health systems acquire medical practices, but may take various forms and continue to evolve beyond the classic model. Characteristics of the classic model of integration include strong and committed physician leadership, an emphasis on care coordination, easy access to primary care, integrated IT and business intelligence, and a willingness to accept financial risk. Leaders of integrated delivery systems continue to strive for greater levels of coordination and leveraging of collected talents and resources.

Computerisation of perinatal data entry: is the data accurate?

Perinatal data (PD) is collected for mothers and babies Australia wide as mandated at a federal level. The data is used to monitor patterns in midwifery, obstetric and neonatal practice and health outcomes and is also used for research purposes, funding allocation and the education of midwives and medical officers. Accuracy in PD is most often reported via quantitative validation studies of PD collections both internationally and within Australia. These studies report varying levels of accuracy in PD collection and suggest researchers need to be more aware of the quality of data they use. This paper presents findings from doctoral research that regarding issues of concern identified by midwives relating to their perceptions of the accuracy of computer PD records. Research, such as that presented in this paper, may improve the robustness of the PD collection and allow for more accurate planning of health services.

Perinatal data collection: current practice in the Australian nursing and midwifery healthcare context.

The collection of perinatal data within Queensland, Australia, has traditionally been achieved via a paper form completed by midwives after each birth. Recently, with an increase in the use of e-health systems in healthcare, perinatal data collection has migrated to an online system. It is suggested that this move from paper to an ehealth platform has resulted in improvement to error rates, completion levels, timeliness of data transfer from healthcare institutions to the perinatal data collection and subsequent publication of data items. Worldwide, perinatal data are collected utilising a variety of methods, but essentially data are used for similar purposes: to monitor outcome patterns within obstetrics and midwifery. This paper discusses current practice in relation to perinatal data collection worldwide and within Australia, with a specific focus on Queensland, highlights relevant issues for midwives, and points to the need for further research into the efficient use of an e-health platform for perinatal data collection.

Integrating health and social care informatics to enable holistic health care.

Personalization of healthcare has a number of claimants, including pHealth. However, to the citizen real personalization is the delivery of integrated support services to maintain their health and well-being, particularly in times of chronic illness and frailty. The integration of health and social care support has been identified a key but challenging step in this. The pHealth community faces the choice either of reinforcing the isolation of silos of care and thus fragmentation of service, or of seeking to become a unifying agent though thoughtful and considered development of sharing of monitoring from pHealth devices.

Are healthcare leaders ready for the real revolution?

The current revolution, that could pass us by if we are not prepared to join it, is a consumer-directed, technologically driven revolution in the way we receive, process, and use information. Today, the knowledge we need--as business owners, healthcare consumers, and informed citizens--is literally in the palm of our hands. The future has arrived and we cannot be late to the dance. Citizen science, integration, and data-driven care will shape our future. Healthcare leaders must be comfortable with complexity and eager to embrace fast-paced, revolutionary changes. We must be prepared to lead in integrated health care environments that harness technology and value data.

New systems of care for substance use disorders: treatment, finance, and technology under health care reform.

This article outlined ways in which persons with addiction are currently underserved by our current health care system. However, with the coming broad scale reforms to our health care system, the access to and availability of high-quality care for substance use disorders will increase. Addiction treatments will continue to be offered through traditional substance abuse care systems, but these will be more integrated with primary care, and less separated as treatment facilities leverage opportunities to blend services, financing mechanisms, and health information systems under federally driven incentive programs. To further these reforms, vigilance will be needed by consumers, clinicians, and policy makers to assure that the unmet treatment needs of individuals with addiction are addressed. Embedded in this article are essential recommendations to facilitate the improvement of care for substance use disorders under health care reform. Ultimately, as addiction care acquires more of the "look and feel" of mainstream medicine, it is important to be mindful of preexisting trends in health care delivery overall that are reflected in recent health reform legislation. Within the world of addiction care, clinicians must move beyond their self-imposed "stigmatization" and sequestration of specialty addiction treatment. The problem for addiction care, as it becomes more "mainstream," is to not comfortably feel that general slogans like "Treatment Works," as promoted by Substance Abuse and Mental Health Services Administration's Center for Substance Abuse Treatment during its annual Recovery Month celebrations, will meet the expectations of stakeholders outside the specialty addiction treatment community. Rather, the problem is to show exactly how addiction treatment works, and to what extent it works-there have to be metrics showing changes in symptom level or functional outcome, changes in health care utilization, improvements in workplace attendance and productivity, or other measures. At minimum, clinicians will be required to demonstrate that their new systems of care and future clinical activity are in conformance with overall standards of "best practice" in health care.