Fulfilling the Promise of Artificial Intelligence in the Health Sector: Let's Get Real.

OBJECTIVES: This study aimed to showcase the potential and key concerns and risks of artificial intelligence (AI) in the health sector, illustrating its application with current examples, and to provide policy guidance for the development, assessment, and adoption of AI technologies to advance policy objectives. METHODS: Nonsystematic scan and analysis of peer-reviewed and gray literature on AI in the health sector, focusing on key insights for policy and governance. RESULTS: The application of AI in the health sector is currently in the early stages. Most applications have not been scaled beyond the research setting. The use in real-world clinical settings is especially nascent, with more evidence in public health, biomedical research, and "back office" administration. Deploying AI in the health sector carries risks and hazards that must be managed proactively by policy makers. For AI to produce positive health and policy outcomes, 5 key areas for policy are proposed, including health data governance, operationalizing AI principles, flexible regulation, skills among health workers and patients, and strategic public investment. CONCLUSIONS: AI is not a panacea, but a tool to address specific problems. Its successful development and adoption require data governance that ensures high-quality data are available and secure; relevant actors can access technical infrastructure and resources; regulatory frameworks promote trustworthy AI products; and health workers and patients have the information and skills to use AI products and services safely, effectively, and efficiently. All of this requires considerable investment and international collaboration.

Unexpected Inequality: Disparate-Impact From Artificial Intelligence in Healthcare Decisions.

Systemic discrimination in healthcare plagues marginalized groups. Physicians incorrectly view people of color as having high pain tolerance, leading to undertreatment. Women with disabilities are often undiagnosed because their symptoms are dismissed. Low-income patients have less access to appropriate treatment. These patterns, and others, reflect long-standing disparities that have become engrained in U.S. health systems. As the healthcare industry adopts artificial intelligence and algorithminformed (AI) tools, it is vital that regulators address healthcare discrimination. AI tools are increasingly used to make both clinical and administrative decisions by hospitals, physicians, and insurers--yet there is no framework that specifically places nondiscrimination obligations on AI users. The Food and Drug Administration has limited authority to regulate AI and has not sought to incorporate anti-discrimination principles in its guidance. Section 1557 of the Affordable Care Act has not been used to enforce nondiscrimination in healthcare AI and is under-utilized by the Office of Civil Rights. State level protections by medical licensing boards or malpractice liability are similarly untested and have not yet extended nondiscrimination obligations to AI. This Article discusses the role of each legal obligation on healthcare AI and the ways in which each system can improve to address discrimination. It highlights the ways in which industries can self-regulate to set nondiscrimination standards and concludes by recommending standards and creating a super-regulator to address disparate impact by AI. As the world moves towards automation, it is imperative that ongoing concerns about systemic discrimination are removed to prevent further marginalization in healthcare.

A Market Shaping Approach for the Biopharmaceutical Industry: Governing Innovation Towards the Public Interest.

Enhancing research and development and ensuring equitable pricing and access to cutting-edge treatments are both vital to a biopharmaceutical innovation system that works in the public interest. However, despite delivering numerous therapeutic advances, the existing system suffers from major problems: a lack of directionality to meet key needs, inefficient collaboration, high prices that fail to reflect the public contribution, and an overly-financialized business model.

Perspectives on statistical strategies for the regulatory biomarker qualification process.

Qualification of a biomarker for use in a medical product development program requires a statistical strategy that aligns available evidence with the proposed context of use (COU), identifies any data gaps to be filled and plans any additional research required to support the qualification. Accumulating, interpreting and analyzing available data is outlined, step-by-step, illustrated by a qualified enrichment biomarker example and a safety biomarker in the process of qualification. The detailed steps aid requestors seeking qualification of biomarkers, allowing them to organize the available evidence and identify potential gaps. This provides a statistical perspective for assessing evidence that parallels clinical considerations and is intended to guide the overall evaluation of evidentiary criteria to support a specific biomarker COU.

Addressing Care Continuity and Quality Challenges in the Management of Hypertension: Case Study of the Private Health Care Sector in Kenya.

BACKGROUND: Hypertension is a major risk factor of cardiovascular disease and a leading cause of morbidity and mortality globally. In Kenya, the rise of hypertension strains an already stretched health care system that has traditionally focused on the management of infectious diseases. Health care provision in this country remains fragmented, and little is known about the role of health information technology in care coordination. Furthermore, there is a dearth of literature on the experiences, challenges, and solutions for improving the management of hypertension and other noncommunicable diseases in the Kenyan private health care sector. OBJECTIVE: The aim of this study is to assess stakeholders' perspectives on the challenges associated with the management of hypertension in the Kenyan private health care sector and to derive recommendations for the design and functionality of a digital health solution for addressing the care continuity and quality challenges in the management of hypertension. METHODS: We conducted a qualitative case study. We collected data using in-depth interviews with 18 care providers and 8 business leads, and direct observations at 18 private health care institutions in Nairobi, Kenya. We analyzed the data thematically to identify the key challenges and recommendations for technology-enabled solutions to support the management of hypertension in the Kenyan private health sector. We subsequently used the generated insights to derive and describe the design and range of functions of a digital health wallet platform for enabling care quality and continuity. RESULTS: The management of hypertension in the Kenyan private health care sector is characterized by challenges such as high cost of care, limited health care literacy, lack of self-management support, ineffective referral systems, inadequate care provider training, and inadequate regulation. Care providers lack the tools needed to understand their patients' care histories and effectively coordinate efforts to deliver high-quality hypertension care. The proposed digital health platform was designed to support hypertension care coordination and continuity through clinical workflow orchestration, decision support, and patient-mediated data sharing with privacy preservation, auditability, and trust enabled by blockchain technology. CONCLUSIONS: The Kenyan private health care sector faces key challenges that require significant policy, organizational, and infrastructural changes to ensure care quality and continuity in the management of hypertension. Digital health data interoperability solutions are needed to improve hypertension care coordination in the sector. Additional studies should investigate how patients can control the sharing of their data while ensuring that care providers have a holistic view of the patient during any encounter.

A model respiratory personal protective programme for the New Zealand healthcare industry.

In the absence of advice from the workplace regulator, a model respiratory protection programme for healthcare workers is presented based in healthcare and wider industry experience. Hospital and other healthcare institutions can use this as a basis for their programmes in preparation for the next infective disease outbreak.

Clinical target achievement is associated with better quality of life among dialysis patients: results from a continuous quality improvement program in a Portuguese healthcare network.

BACKGROUND: Patients with kidney failure have multifaced clinical needs. Continuous quality improvement (CQI) programs initiated by large healthcare provider networks bear the promise of improving guideline adherence and improving patient-centered outcome, including health-related quality of life (HRQOL). We aimed at evaluating the association between key performance indicators (KPI) adopted for our CQI and HRQOL in a large network of dialysis providers. METHODS: We conducted a survey study in 39 centers belonging to the Portuguese Fresenius Medical Care (FME) network, in September 2017. For each participant, we retrospectively extracted clinical information during the 6-month period preceding survey administration. We used this information to calculate KPI as defined by the FME-CQI policy. Those KPI were selected in the FME-CQI policy as modifiable intermediate endpoints for which previous evidence suggested a causal relationship with patients' morbidity and mortality. HRQOL was assessed by the Kidney Disease Quality of Life Short Form 36 (KDQOL-36) questionnaire. RESULTS: Among 4691 eligible patients who were invited to participate in the survey, 2263 (48.2%) answered the self-administered survey. Based on KPI standards, patients had 1.5 (± 1.2) off-target clinical parameters on average. KDQOL-36 score were generally higher than those observed in European reference population. We found a significant linear association between KPI parameters and HRQOL. This pattern was robust to adjustment for satisfaction scores. CONCLUSIONS: Our data demonstrated a graded, monotonic, dose-response relationship between the number of off-target KPIs and HRQOL. Such relationship was not mediated by patients' satisfaction and may be attributed to amelioration of disease-specific symptoms and functional capacity.

[From "culprits" to "victims:" the expansion and professionalization of the healthcare system in the province of Mendoza in the late nineteenth and early twentieth century]. / De "culpables" a "víctimas": expansión y profesionalización del sistema de salud en la provincia Mendoza a fines del siglo XIX y principios del XX.

From the late 19th century to the beginning of the 20th, the province of Mendoza presented problematic sanitary conditions due to rapid demographic and urban growth, the scarcity of public services, and the poor state of the old colonial city (destroyed by the 1861 earthquake), which facilitated the spread of various infectious diseases. The objective of this article is to inquire into the ways in which the healthcare system in the province of Mendoza both expanded and became increasingly professionalized from the late 19th to early 20th century. We explore how these factors, along with the predominant social representations of disease that permeated the discourses of governing elites, influenced public policy aimed at combating the diseases of the time. To that end, we consulted a wide range of written documents and photographic material that allowed us to analyze changes in discourse as well as public policy.

Entre fines del siglo XIX y comienzos del XX, la provincia de Mendoza presentaba un estado sanitario marcado por el crecimiento demográfico y urbanístico, la escasez de los servicios públicos y la destrucción de la antigua ciudad colonial como consecuencia del terremoto de 1861, lo que propiciaba un ambiente favorable para el desarrollo de diversas enfermedades infectocontagiosas. El objetivo de este artículo es indagar cómo se fue profesionalizando y expandiendo el sistema de salud en la provincia de Mendoza a fines del siglo XIX e inicios del XX, y cómo esos factores, junto con las representaciones sobre la enfermedad que predominaban en el discurso de la elite gobernante, incidieron en las políticas públicas para combatir las dolencias de la época. Para ello se consultaron diversos documentos escritos y fotográficos que permitieron analizar las modificaciones del discurso y las políticas públicas implementadas.

Relationship between leadership support and operational excellence in health care sector: A study of Indian health care managers.

BACKGROUND AND OBJECTIVE: Leadership communicates purpose and innovative ways to thrive for performance. Leadership support influences and impacts operational excellence in the health sector as a patient-centered operation, with effective management, excellence framework, challenges and constraints, teamwork and value stream mapping. It is hypothesized that: (1) perceived leadership support will positively correlate with perceived operational excellence (Patient-centered Operations, Effective Resource Management, Excellence framework, Eliminating Challenges or Constraints, Team Work, Value Stream Mapping) and (2) the correlation would be highest with Patient-centered Operations. The aim of this study was to examine the relationship between leadership support and operational excellence in the health care sector among a selected group of healthcare managers. MATERIALS AND METHOD: A correlation study between leadership support and operational excellence was designed for a group of health care managers (n=80) from eight hospitals in Kerala, South India. The selection of executives was from NABH accredited hospitals from districts with a minimum of four NABH accredited hospital. A survey was sent to a selected study sample. The respondents were cooperative and provided responses on perceived leadership support for operational excellence. RESULTS: Factors of leadership support correlated to operational excellence. CONCLUSION: In the health care sector, leadership support for patient-centered operations helps achieve operational excellence.

The use of real-world effectiveness measurements in clinical settings at Helsinki University Hospital: a systematic literature review.

Aim: Patient reported outcomes collected alongside clinical trials do not reflect real-world effectiveness (RWE). This review assessed the use of RWE measurements in routine clinical treatment and the instruments applied to collect that data. Materials & methods: The RWE articles published from HUS (Helsinki University Hospital) were extracted from several databases. Results: Out of 170 eligible articles, generic health-related quality of life instruments were used in 87 (51.2%) and disease-specific health-related quality of life instruments in 58 (34.1%) articles as a primary measurement. Most of the articles pertained to surgery, gynecology and pediatric surgery. Conclusion: The number of articles assessing RWE is very limited compared with all the articles published from HUS. Thus, we still have limited information about the effectiveness of the treatment in real life.

Quantifying the handprint-Footprint balance into a single score: The example of pharmaceuticals.

Life Cycle Assessment typically focuses on the footprint of products and services, expressed on three Areas of Protection (AoP): Human Health, Ecosystems and Resources. While the handprint is often expressed qualitatively, quantified handprints have recently been compared directly to the footprint concerning one AoP: Human Health. We propose to take this one step further by simultaneously comparing the quantified handprint and footprint on all AoPs through normalization and weighting of the results towards a single score. We discuss two example cases of a pharmaceutical treatment: mebendazole to treat soil-transmitted helminthiases and paliperidone palmitate to treat schizophrenia. Each time, treatment is compared to 'no treatment'. The footprint of health care is compared to the handprint of improved patient health. The handprint and footprint were normalized separately. To include sensitivity in the normalization step we applied four sets of external normalization factors for both handprint (Global Burden of Disease) and footprint (ReCiPe and PROSUITE). At the weighting step we applied 26 sets of panel weighting factors from three sources. We propose the Relative Sustainability Benefit Rate (RSBR) as a new metric to quantify the relative difference in combined handprint and footprint single score between two alternatives. When only considering the footprint, the first case study is associated with an increased single score burden of treatment compared to 'no treatment', while in the second case study treatment reduces the single score burden by 41.1% compared to 'no treatment'. Also including the handprint provided new insights for the first case study, now showing a decrease of 56.4% in single score burden for treatment compared to 'no treatment'. For the second case study the reduction of single score burden was confirmed as the handprint burden was also decreased because of treatment by 9.9%, reinforcing the findings.

Quantifying the competitiveness of the electronic health record market and its implications for interoperability.

OBJECTIVE: The objective of this study was to quantify both the competitiveness of the EHR vendor market in the United States of America (US) and the degree of fragmentation of individual Medicare beneficiaries' medical records across the differing EHR vendors found in the US healthcare system. METHODS AND MATERIALS: We determined the Part A and Part B Medicare-expenditure weighted market shares of EHR vendors and estimated the rate of attestation of meaningful use (MU) for EHRs among Medicare Part A & B providers from 2011 to 2016. Based on these data we calculated the annual Herfindahl-Hirschman Index to quantify the competitiveness of the EHR market as well as the number of vendors individual Medicare beneficiaries' medical records were stored in for the period 2014-2016. RESULTS: We find that as of 2016 the EHR vendor environment was competitive but trending towards becoming highly concentrated soon. We also found that patient medical records were highly fragmented as only 4.5 % of expenditure-weighted individual Medicare beneficiaries had their MU medical records associated with a single vendor, while 19.8 % of expenditure-weighted beneficiaries had their MU medical records stored in 8 or more vendors. DISCUSSION: These results indicate that there are tradeoffs between EHR market competition, and the challenges associated with achieving interoperability across numerous competing vendors. CONCLUSION: Uncertainty of interoperability among different EHR vendors may make transmission of medical records among different providers challenging, mitigating the benefit of vendor competition. This highlights the critical importance of current interoperability efforts moving forward.

Hidden big data analytics issues in the healthcare industry.

The goal of the study was to identify big data analysis issues that can impact empirical research in the healthcare industry. To accomplish that the author analyzed big data related keywords from a literature review of peer reviewed journal articles published since 2011. Topics, methods and techniques were summarized along with strengths and weaknesses. A panel of subject matter experts was interviewed to validate the intermediate results and synthesize the key problems that would likely impact researchers conducting quantitative big data analysis in healthcare studies. The systems thinking action research method was applied to identify and describe the hidden issues. The findings were similar to the extant literature but three hidden fatal issues were detected. Methodical and statistical control solutions were proposed to overcome the three fatal healthcare big data analysis issues.