A Shared Information Technology-Business-Health Model: Lessons for Healthcare Leaders on Integrating Technology from Investment

Donald M. Hilty, MD, MBA

Professor, Department of Psychiatry and Behavioral Sciences, UC Davis, 10535 Hospital Way, Mather, CA 95655, USA; E-mail: donh032612@gmail.com

INTRODUCTION

Technology is sweeping through our society in unparalleled fashion, affecting our day-to-day life, education, social relationships, health care and business.¹ In this era of patient-centered care, telepsychiatry (i.e., video or synchronous) facilitates access to care, leverages a wide range of treatments at a distance and provides quality care with outcomes as good as in-person care.^2,3 It also provides versatility to health systems by enabling more patient points-of-entry, matching patient needs with provider skills and helping providers work at the top of their licenses.³ Many clinicians are still shifting from doctor-, treatment- and/or clinic-centered care, to person-centered health promotion and patient-centered care–much less adapting to new technologies (e.g., text, apps, wearable sensors, social media). Integrative use of mobile health (e.g., emergency transport linkage to the emergency department cardiologist) and in-time clinical decision support is a goal, yet not a standard practice in many institutions.

The adjustment to technology is informed by the consumer movement, traditional medical practice and the evolution of institutional approaches to incorporate it. In business, technology is a key part of the consumer decision journey, in which people consider life choices, evaluate options, make purchases, develop loyalty and advocate others do the same.⁴ In health care, clinicians and people make decisions based on perceived needs, resources and experiences.⁵ While people may conduct their life with technology in-time, health decisions are usually best weighed over time, based on patient-physician discussion and informed by data. More broadly, traditional medical practice and the evolution of science have stood the test of time, similar to the evolution of a country’s development with checks and balances (e.g., U.S. between the executive office, legislature and judiciary system). Academic health centers (AHCs) promote science and stability, but may make decisions about technology incrementally compared to private health care systems.

Globally, health care systems and governmental agencies are emphasizing quality, evidence-based care and are trying to set individual patient, aggregate and population outcomes that can be evaluated by mental health data/indicators.⁶ This requires services that are acceptable to patients, have metrics that can be measured and approaches that are scalable—all of which depend on technology. System management (e.g., health information systems (IS), information technology (IT), telehealth), facilities and clinics (e.g., labs, home health) and delivery structures (e.g., integrated networks) can play a key role in health care. IT falls into three general categories: clinical information systems, administrative information and clinical decision support (CDS) systems, which are supported by advances in artificial intelligence (AI) and machine learning (ML).⁷ Incremental often means “adding to” existing options (e.g., scheduling systems, the electronic health record (EHR), telehealth video). For example, technology is added to improve documentation of care or as part of a new clinical service, yet the practical impact on clinicians may be overlooked (e.g., time cost, burnout).⁸ Unintended consequences often occur in system implementation as trade-offs are made between goals and users’ work practices.⁹

The field of business has some similarities with health care related to implementation of technology. Both business and medicine have innovators, early adopters, early majority, late majority and laggards.¹⁰ However, large businesses and those in competitive industries have had to adopt quickly—to avoid going extinct (e.g., Nintendo).¹¹ Indeed, progressive business practice depends on technology heavily (e.g., banking, marketing, sales). Successful businesses shifted IT from an “add-on” or appendage to a core, integrated foundation with research and development, marketing, production and financing functions—they came to a shared IT-business understanding to use IT as an organizing framework.¹² Core components of this model have transformed the work of investment banking and other companies like Cirque de Soliel, L’Oreal and Nintendo.^11,13,14,15

This paper is designed for leaders of health care, training/education, and other organizations as a tool to “step back” and see business enterprises and now academic health care systems are integrating IT for service delivery and workflow. It draws from a literature across psychiatry/behavioral science, technology, business and health care (i.e., clinical care, education and administration). It may help the reader learn in three ways, to: 1) understand the foundational principles and processes of business and health care in order to contextualize the role of technology; 2) apply a case example to health care of how IT was used to engage customers in banking, financing and investing (i.e., straight through processing to streamline transactions, reduce errors and manual cognitive processes); and 3) understand the challenges for Health Care systems to implement a shared IT-business-health model rather than incremental none-integrative approaches for clinical care, education and administration.

METHODS

Approach

This scoping review used a literature search of Medline, PsycNET, PsycINFO, Embase, Cochrane, SpringerLink, Scopus, ABI/Inform, Business Source Complete, and Web of Science, using subject headings and keywords along with a manual search of reference lists of articles published by November 2020. The stages in this process have been described as: 1) using a well-defined research question with purpose; 2) identifying relevant studies based on the question and purpose, employing a suitable team; 3) selecting studies based on an iterative process for searching the literature, refining the search strategy, and reviewing articles for study inclusion; 4) charting the data by having at least two reviewers extract information; 5) analyzing reporting, and considering the meaning of the findings; and 6) using preliminary findings to obtain consultation from stakeholders.^16,17

The Research Question

The question that guided the review was, “What approaches are successful for health care organizations to integrate technology into clinical and administrative workflow, based on inroads from business?”

The goal was to use identify models of integrating technology into health care practices in addition to traditional clinical informatics approaches, so that clinical, technical, workflow, and administrative factors could be better planned, implemented, evaluated and improved. While clinical informatics is a rapidly expanding area may be central to this process, additional paradigms were sought to facilitate patient-centered care as defined by quality, affordable, and timely health care. For example, effectiveness and implementation science approaches assess acceptability, adoption, feasibility, cost, and sustainability.

Identifying Relevant Studies: The Search Strategy

Search terms were organized in four concept areas akin to a scoping review¹⁶ with modifications¹⁷:

• Business: adaptive, administrative, asset, break-even, brand, channel, communication, competitive, consolidate, content, corporate, costs, deliver, development, distribution, diversification, equipment, equity, expense, finance, fiscal, fixed, industry, inventory, investment, labor, leadership, liability, loss, management, margin, market(ing), opportunity, organization, outsourcing, plant, product(ion), profit, research, return, service, strategy, sunk, transaction, value.
• Service delivery: access, asynchronous, clinical, clinician, continuity, curriculum, decision, distance, documentation, education, e-mail, framework, learner, learning, measure, monitor, outcome, patient, pedagogy, remote, sensor, share, skill, social media, support, team, text, training, video, virtual, wearable.
• System change: academic, adapt, addition, adopt, alternative, analysis, approaches, assessment, benchmark, center, complementary, configure, data, design, develop, engineer, evaluation, health, implementation, improvement, installation, integration (integrity), long-term, maintain, manage, method, model, modification, operating, optimization, procedure, process, program, quality, phase, process, regulation, resolution, replacement, revision, scalable, science, short-term, simulation, standard, technique, transmission, workflow, utility.
• Technology: app, architecture, bridge, cell, computer, connection, database, development, device, digital, eConsult, e-consult, electronic, hardware, health, infrastructure, information, Internet, medical, mobile, monitoring, network, on-line, protocol, record, registry, software, store-and-forward, structure, system, web-based..

Study Selection

Articles were reviewed by title/abstract, full text review and review of references. The goal was to explore how medicine/psychiatry has integrated technology compared to business, and apply business approaches to health care and training; service delivery rather than production models of business were sought.

Articles were included if they discussed integration of technology into health care and compared literature from medicine/health, psychiatry/behavioral health, business, technology, leadership and health care administration. Articles were excluded if they were restricted to one concept area, did not have data, did not have business or scientific methodology, or if were not in English.

Charting the Data

A data-charting form was not developed and used to extract data from each study, but notes were organized consistent with a narrative review or descriptive analytical methods by each reviewer to extract contextual or process-oriented information from each study. The reviewers then compared and consolidated information regarding content. A qualitative content analysis approach would have been used if there was more content, to make sense of the wealth of extracted data. A descriptive analytical method was used to summarize the process and content information of discussions with experts, in an effort to chart and summarize complex concepts in a meaningful way.

Analysis, Reporting and Considering the Meaning of the Findings

This phase often organizes meaningful results in a table, study by study, with data outlined and consolidated by the authors and expert consensus step, but a thematic analysis was not possible.

A field study approach with unstructured interviews was used to investigate how a Company explores the use of STP. This method allows respondents to express in their own ways and pace without bias.¹⁸ To be precise, unstructured interview resembles a conversation more than an interview–thought the questions come from the interviewer–for an open-ended exploration of the issues rather than making assumptions. Sometimes independent and dependent variables already exist within the social structure of a Company under study, and inferences can then be drawn about behaviors, social attitudes, values and beliefs.¹⁹

Consultation for Expert Opinion

Expert option was solicited to review preliminary findings, and suggest additional steps to improve the review. The goal was to gain input and perspective from a diverse group of health professionals from business, medicine, behavioral health, health services and technology. Participants were also sought from clinical, administrative (e.g., chairs, deans, leaders of national organizations), health care (e.g., health system director, executive, chief of staff) and technology (e.g., artificial intelligence, developers, engineers, informatics, information systems) sectors.

RESULTS

Literature

The flow chart shows that from a total of 2,710 potential references, two authors (DH, JL) found 2,678 eligible for title and abstract review and found 327 papers eligible for full text review as directly relevant to the concept areas in combination. The authors found 58 papers directly relevant to the concepts and 11 from references searched for a total of 69.

A Historical Perspective: Similarities/Differences Between

Business and Medicine/Psychiatry, in General, and Related to Technology

A business is usually defined as any organization that provides products, services or both to individual consumers or to other organizations.²⁰ The premise is a need for goods and services that satisfy the need, and there is an aim to make a profit and share that with stakeholders who have invested. Leaders steer the functions of businesses, which include research and development, marketing, production, accounting and financing. Businesses operate within in an overall economic system (i.e., market with supply and demand) with risk and uncertainty.

Science and medicine has changed significantly over time,^20,21 with the late 19^th-20^th century bringing a scientific foundation and organized medicine. The focus of medicine as a business started in the 1920s, and later, health care systems, reform of training and other tenets of modern care (e.g., specialization, public health, insurance and governmental funding) appeared. The late 20^th-early 21^st century has seen corporatization, information revolution, globalization and the era of health care reform. Academic medicine comprises medical schools, teaching hospitals and large multispecialty physician practices and its key roles are: treating complex conditions; advancing medical discoveries for better diagnostics, preventive strategies, and treatments; educating the next generation of physicians; and providing irreplaceable community services.²² Medical research is conducted by sustainable, predictable funding growth for the National Institutes of Health. Specialized clinical care at teaching hospitals includes Medicare finances graduate medical education (GME) for direct costs for physician training and indirect medical education (IME).

The U.S. has a unique system of health care delivery, as most developed countries have national health insurance and governmental oversight.²⁰ It is fragmented with people seeking health care through different means and a constantly changing pattern of financing, insurance, delivery and payment mechanisms with private and public components. The complexity of health care includes education/research, suppliers, insurers, providers, payers and the government. The policy cycle is complex itself, with issue, design, public support, legislative decisions and policy implementation steps. The newest movements in addition to patient-centered care are value-based care and accountable care organizations driven by the Centers for Medicare and Medicaid Service.^23,24  Value-based purchasing (VBP) adjustments on reimbursement have been tied to clinical care quality (2013), patient experience (2014), safety (2015), efficiency (2016) and mortality (2017).

Technology, clinical care and competencies: There are continuum of technology-based options used by patients, families, caregivers and professionals. This continuum includes: Internet-based information; self-help/support groups; materials for patient and clinician education; social media; self- and clinician-assisted self-assessment; asynchronous text, e-mail and video options; mobile health with apps; and synchronous video (i.e., telepsychiatry) (Table 1).^25,26 Technology helps users with goals, and systems may help reduce liabilities of technologies for consumers and patients by standardizing approaches. The spectrum reflects a shift to patient-centered care – and person-centered care²⁷—empowering the whole person behind the patient.^28,29 These movements put business and medicine on a common ground—helping the person/customer/patient with quality service/care. This shift parallels past trends in banking, as people have used automated teller machines (ATMs) instead of banks/tellers, though health care is more complex than that.

An e-platform may be needed for infrastructure and to efficiently and effectively stage various telecare options. Common technological approaches in medicine include: 1) EHRs, though for users, may interfere with patient engagement and menu-based user interfaces have been cumbersome and unforgiving, but are evolving into more intuitive graphical interfaces^30,31; 2) dictation with voice recognition, which still has challenges of integration with legacy, billing and practice management systems—this text system could be replaced by video recordings)³²; 3) e-consultation (i.e., e-consult or eConsult) to support a primary care provider (PCP) for decision-making^33,34; 4) text-based, chat and social media communication, pose integration challenges and keyboard characters/ emoticons may be used differently across cultures³²; and 5) mobile phones, apps and wearable sensors, which are not always evidence-based or integrated into health care systems, but could provide comprehensive self-management approaches and advanced features that leverage the broader functionalities of mobile phones (e.g., sensors, ecological momentary assessments).^35,38 By obtaining patient input and preventing/troubleshooting problems, users build trust (i.e., reduce concerns of privacy).²⁶

Many BH professions have put out best practices, guidelines, and position statements for clinicians to adjust to video and asynchronous technologies. Contributions come from: psychiatry/medicine, psychology, social work, counseling, couple/marriage/family, the American Telemedicine Association, the American Psychiatric Association and the Coalition for Technology in Behavioral Science.³⁹ Most guidelines focused on video and sparingly mentioned e-mail, e-consultation, social media or texting,^40,41,42 until competencies were published for social media,^39,43 mobile health,^44,45 and asynchronous care. The overarching goal of competencies is to ensure quality of care for patients, improve clinician skills and promote training.

Business versus medicine/psychiatry leadership: Continuous, committed and active leadership is crucial for strategic planning, management and implementation of change.⁴⁶ Technology may mean different things to different people, professions and businesses, but it is almost always associated with innovation.^47,48 A comprehensive definition of innovation relates to the impact on an organization, based on the magnitude of the advance and the dimension of novelty experienced⁴⁷

• Incremental: expresses minor changes to current services/product and processes;
• Radical: not frequent in organizations, but requires a major breakthrough or discovery; and
• Transformative: an exceptional shift in processes and beliefs.

John Kotter, Professor of Leadership at Harvard Business School, has contributed two key approaches to leadership for business and health care.⁴⁹ First, he proposed that leadership is a process that focuses on making organizational changes – the stimuli behind an organization’s adoption of — and adaptation to — improved processes. Management is primarily assigning and tracking tangible outcomes, however, leaders manage and managers lead to some degree. Second, he highlighted eight essential factors for transformation efforts.⁵⁰ Transformation takes time, so performance improvements must be planned, actively created and achieved, and short-term wins keep participants interested and experiencing some sense of urgency.

In spite of the plethora of possibilities for improved patient care through the use of technology, human factors present the greatest impediment to the implementation of new systems. Success depends upon a blend of both technical and strong organizational skills to plan and manage these changes. Leaders need to strategically plan, understand how innovations diffuse through groups,¹⁰ assess the groups’ readiness for change,⁵¹ monitor the organizational culture, recognize/plan for resistance to change and communicate effectively. Failure of implementation is usually due to insufficient attention to how change is experienced by the people who do most of the changing.^10,52

Effective change leaders:

• Embrace change when needed and take initiative;
• Develop a vision for change and communicate its urgency;
• Communicate with managers and employees, individually and through mass media, with feedback options;
• Stay actively involved; and
• Direct and review change management planning and implementation.

Several approaches, such as those of Deming and Walton^53,54 and of Nadler et al,⁵⁵ describe detailed tactics for working through problems and change in large organizations. Deming, in particular, stressed the importance of including staff at all organizational levels including the lowest tier front-line workers and, notably, customers in “quality circles” as he engineered numerous quality improvements at Toyota. Similarly, behavioral health care institutions need an approach for change management and a technology e-platform to plan, prioritize, and allocate resources for technology (e.g., telepsychiatric video) related to academic goals, education and community partnerships.⁵⁶ This may include competencies related to patient care, education, faculty development, leadership, finance and partnerships – and it is better to take a broader e-health approach rather than focusing on one technology like telepsychiatry.²⁶

Assessing and enhancing readiness for change: Successful change requires both individuals at all levels and their organizational policies and procedures to change or shift. Complicated processes may seem wonderful to leadership, but can be perceived as burdensome, overly complicated, ineffective, and even counterproductive by those in middle management and those providing services. Unless each level perceives the intended changes to be in their own interests, they may not prioritize or cooperate with implementation, and if objections are not adequately voiced and addressed, those affected may refuse to participate or, in subtler fashion, may engage in passive-aggressive behavior, such as delay, which sabotages the implementation plan.

Assessing how ready to change a group of individuals and organizations may be is complex. Readiness is associated with people’s perceptions of financial support, a well-defined mission, leadership structure, cohesive teamwork, the technical skills needed to adopt an innovation, and the extent to which they see their own needs for safety, security, and autonomy protected. From studies using survey instruments, focus groups, clinical interviews, site visits, and community profiles, it is key to 1) assess, 2) contextualize, and 3) enhance readiness.⁵⁷ A checklist of factors may help organizations measure readiness for change and develop attitudes and beliefs that provide the context (Table 2). The personal attributes of “change agents,” are important, such as perceived credibility, trustworthiness, sincerity, and expertise. Internal change agents who are mid-range authority figures may assess readiness better than leaders at the top.

Implementing innovations often meets resistance to change. Many senior managers forget a critical principle of change management: organizations do not change; people do (Marshall, 1996).⁵⁸ It is inevitable, particularly if individuals experience a loss of control. An outside organizational consultant who facilitates workers’ grief processes may help.⁵⁹ Such consultants may provide a safe, non-punitive environment—a transitional space—in which employees may safely explore the implications of the imposed changes. The consultants may explore how anxieties and uncertainty, the introduction of additional complications in the form of new procedures, red tape, regulations, and other factors appear to take precedence over problem-solving, provision of services, and addressing worker concerns.

Predictors of success: leadership and management orientation: Studies have been examining relationships between the managerial-controlled critical success factors, which predict good performance across business, education and health care (largely non-profit) service sectors of the U.S. economy. In 2001, services-producing industries accounted for 81% of the nation’s employment.⁶⁰ Between 1960 and 2002, employment went from: 0.6 to 2.5 million (M) in education; 0.66 to 9.3 M in business; and 1.5 to 11M in health care⁶¹ then 16.4 M in 2010.²⁰ Market orientation (MKT), learning orientation (LRN), entrepreneurial management style (ENT) and organizational flexibility (ORG) are predictors of organizational success (Table 3).

Market orientation had the highest correlation with performance in all three sectors.⁶² Generally, the next-highest correlations were with LRN and ENT style rather than ORG. However, in business services, ORG had a higher correlation with performance than either ENT or LRN. There were a number of managerial implications, which not surprisingly, varied by sector. Different industries and markets have different critical success factors and drivers. It is important that executives reflect on these factors, their industry and the market. Health care has done well vis-à-vis both business services and education on MKT, LRN and ENT. This probably reflects challenges faced with managed care/capitation, hyper-competition with mergers/acquisitions and discussions on who is the decision-maker (i.e., now the patient more than ever). Surviving health care organizations have been forced to become marketers and more entrepreneurial with innovation and excellent care.

An Example of Straight Through Processing: How the Banking, Financing and Investing Institutions Have Engaged Customers

Company background/history: Businesses respond to challenges of generating income, meeting consumer expectations and competing with others in a variety of ways. The Company offers life insurance products, such as term, whole, universal and variable universal life insurances, fixed and variable annuities, disability income insurance products, retirement plans and business solutions (e.g., fringe benefits and retirement plans). In addition, it also offers investments which include mutual funds, variable annuities, direct participation programs, full-service stock and bond trading products, group retirement plans, college savings plans, health savings accounts and cash management accounts. The company has strategically grown as a leader within the insurance industry for providing quality, low cost products and achieving superior financial growth. Its shares of stock are 100% owned by the Company’s Mutual Holding, Inc., whose voting members are life insurance policyholders and annuity contract owners. In 2018, it accomplished its 29^th consecutive year of growth of individual life insurance sales, a record unmatched in the industry, with a 20% increase from 2015 and $XX billion (B) of assets under management.

Challenges for the company and other banking, financing and investing institutions include generating income, meeting consumer expectations and competing with others. Manual data may have some pearls, but they are hard to access quickly and require reconciliation. This delays decisions, costs time to reconcile and leads to dissatisfaction.⁶³ In the trade life cycle — from initiation to settlement — trades by phone or via a trading desk had to be keyed into PDF trade tickets, entered into the investment accounting system in order to process the trade and security information for reporting purposes and general ledger notation. The trade is then faxed to the custodian for settlement purposes and all communication with brokers is done via phone and email. Companies had tended to leave out IT, in general, or to barely include it in order to capture parts of the data flow^64,65:

Two issues have encouraged the Company to change. First, insurers — like all other businesses — have to determine how to utilize technology strategically to best manage current and new challenges related to core processes and growth of market share.⁶⁶ Insurers have had more downgrades per Fitch Ratings, Standard & Poor’s and A.M. Best than other businesses, suggesting that the “back office” had to be modernized.⁶⁷ Second, global financial services had skyrocketed from 13 M ($382 B) in 1980 to 221M ($11.1 trillion (T) in 2000.⁶³ The Security and Exchange Commission (SEC) facilitated STP use for cross-border trading by setting standards T+1 (trade day + 1 day instead of T+3). This required millions of transactions — and the participants — to interface and use a system that did not crash.^63,68

The company considered a solution for analysis, time/resources and planning.

Straight through processing (STP) is defined as end-to-end automation of security trading from order to settlement. Information that has been electronically entered by one party may to be transferred from another party instead of manually re-entering the same pieces of information repeatedly over the entire sequence of events (Figure 1). This reduces the time it takes to process a transaction and increases the likelihood that a contract or an agreement is settled on time and without error. This works using automatic linkages across geography with a paperless sequence of events. STP helps all parties, including asset managers, brokers, dealers, custodians, banks and other financial services players.

Figure 1. Steps of Trading Processes and Participating Parties Under the Sraight Through Processing Umbrella

There are levels of STP: 1) intra-STP, within an organization and its branches; 2) extra-STP, between firms with direct access into other companies’ internal processes across an industry; and 3) global-STP, across worldwide or global boundaries. Challenges are/have been: 1) data capture; 2) internal workflow; 3) external workflow; 4) real time processing; 5) front, middle and back end office connectivity; 6) adoption of industry standards and protocols; 7) multilateral interfaces with third parties; 8) just-in-time enrichment; and 9) global implementation.

Field study notes: Questions asked of Company leaders and application to psychiatry/behavioral health and health care (progression from current state to IT integration).

1. How would you describe the current IT/systems structure within the back office and the front office areas within your Company?

It has the functional capacity for status quo operations, but with significant opportunity for improvement. We are attempting to move away from a situation where we are playing catch-up to one more adaptable to future changes. These things take time and resources. There are an incredible number of obstacles all companies face to accomplish this. Too many of our manual and IT processes are exceptions instead of the rule. This not only creates inefficiencies, but it reduces adaptability and increases risk, especially in the areas of potential sharing of knowledge by personnel.

Application to psychiatry: mental health clinical care. In an outpatient department, there are many gaps between the back office and front office (i.e., patient side). Clinical care involves insurance (i.e., benefits), scheduling, billing, collections and communication (e.g., records to primary care) – rarely are all parties on the same page (e.g., insurer and clinic administration may only know benefits and patients and clinicians have to double check). For clinical care workflow, information systems and domains include the EHR, picture archiving and communication systems (PACS), laboratory information systems and CDS systems. Some health care systems have CDS to provide clinicians, patients and others with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care.^7,69 Similar to STP for investments, CDS improves patient outcomes, reduces unnecessary mistakes and expenses and increases efficiency.⁷⁰

2. Would you say that most of your IT projects currently within the back-office and front office within the investment department are short-term (i.e., 6-months) or long-term? What has caused this?

We have been focused on shorter-term solutions more recently given the lack of appetite for longer-term projects, which tend to be on the pricier side in both terms of dollars and people. We have been trying to show a clear cost/benefit solution to the projects we are pursuing. Most critically we are getting creative with how to solve problems. For example, I might not be able to sell a project on implementing a new data warehouse. But I might be able to sell someone building the database structure for me. We attempt to budget for the actual IT, marketing/messaging and training short-term costs –if we do that well, we believe we get lower direct and indirect costs later. Then, over 1-6-months, We borrow help from existing or others’ staff to load data into the data warehouse in an automated fashion via extract, transform and load (ETL) or scheduled jobs, and I can build the reporting systems myself. These pieces make it easier to get enhanced, dedicated resources for the whole process via permanent funding.

Application to psychiatry: Mental health research and clinical care. With research there is a need to link participant expectations with procedures and completion of a study. The time, resources and infrastructure is organized with a grant, though short-term rather than long-term; some are pilots to collect data for more substantial grants for long-term projects. Clinical services and insurance are usually focused short-term (e.g., 2-4-months for therapy) or mid-term if not intensive (e.g., medication visits); few have extensive long-term insurance for clinical care. The best that can be hoped for is cost-offset, with IS and IT investments for a health care system adding to workflow, information used by multiple parties in-time across departments, and rarely, in a community.

3. How are insurance companies managing the complex challenges of integrating back-office processes with front-office solutions (i.e., what is your Company’s approach)?

Companies have to create accountability for results and this means that people have to be empowered with the correct tools and resources (i.e., more than dollars and staff). The correct ethos of an organization is the biggest benefit, which for us is about customer service, accurate data, precise operations, teamwork and more transparency; we move away from silos of responsibility and disconnects between staff and customers. Business processes are becoming more complicated all the time, across multiple departments, computer software and companies. We often rely on project managers who are only concerned about their “project silo” rather than integrating multiple projects, departments, and systems together in a cohesive process (i.e., true accountability). IT additions over the years have not helped; we needed systems that enhanced data flow, integration, access and communication. Now, there are project prioritization meetings across groups (IT, marketing and production) — in-person and virtual — and we have a committed effort to break knowledge silos/barriers. Coronavirus disease 2019 (COVID-19) has boosted our virtual culture quite a bit.

Application to psychiatry: Administration: We have too few staff and many managers to keep up with university/hospital, accreditation and regular administrative tasks. We do not have time, resources and infrastructure to get organized and we have to focus on the short-term rather than the long-term — there is never enough time? Assertive health care systems forge through these challenges with incremental IT — often because “patients deserve the best.” However, expenditures are limited by budgets and systems usually do not face extinction and there are not millions or billions of dollars to make it worth their while. Some systems will invest, though, as IT can link clinical, administrative, quality improvement and external accreditation processes, making it is easier to queue participants for completing tasks, monitoring outcomes and documenting standards are met.

Summary

The company decided to prioritize the following:

• Reach higher volume activity (various instruments other than the routine fixed income and futures),
• Acquire more drill-down data and complex analytics demanded by strategic business units (SBUs),
• More quickly obtain financial information for financial control, and
• Require portfolio managers to be trained for more in-depth risk analysis and portfolio analytics.

While STP initially was seen as the way to get a trade “locked in,”⁷¹ perspective shifted from settling the trade to multilateral payment and netting⁶⁴ – a significant reshaping of the Company’s entire process from before and after STP (Figures 2 and 3). Overall, STP has reduced trade life time cycle — with the potential to reduce systemic and operational risk — while increasing speed and reducing cost. STP provides a competitive advantage for a company with a good business understanding-IT relationship.

Challenges and Reasons for Health Care (e.g., Medicine/

Psychiatry) to Implement a Shared IT-Business Understanding

AHCs are the standard in the health care system for tertiary and quartinery care, training/education/professional development and research. AHCs also have important partnerships with other organizations, provide jobs for the economy and serve communities in many other ways. They have survived through vigorous cost-cutting efforts, but AHCs must change dramatically to meet the changing needs of patients and society.⁷² First, there is the need for better balance between specialization, ambulatory/primary care and cost-effective services. Second, they face aging of the population, a dramatic rise of chronic disease, an influx of patients from different cultures, decreasing financing streams and marketplace dynamics. Third, they have to contend with technology implantation and change.

Institutional movement toward telemedicine and telepsychiatry – whose modern era probably started around 20-years-ago – has been slow with some exceptions (e.g., research, private companies, Veterans Affairs).⁴⁰ Telepsychiatry video aligns with conventional care compared to other technologies used by patients, clinicians and others. Along with the EHR, it had been a specific indicator for institutional e-readiness (or not) until the COVID-19 era; the degree of telepsychiatric integration into workflow – if measured and measurable – will be an indicator of systems’ progress (or not) in the near future. AHCs have implemented EHRs, some decision support and a few other technologies (e.g., robotics, mobile health). Institutions with e-service lines (Veterans Affairs), training guidelines (e.g., Department of Defense) and technology-specific competencies (e.g., video, mobile health) indicate progress and readiness for technological integration; most IT and IS interventions are more hospital centered and in medicine (e.g., intensive care) rather than behavioral health.

Figure 2. Processing Transactions Before STP In PAM (An Investment Accounting System) for Securities System
Environment Manual Process

Figure 3. Processing Security Transactions after STP with Bloomberg AIM to PAM (An Investment Accounting System) Operational Workflow for Fixed Securities

The shared IT-business understanding: A Shared IT-Business Understanding is defined as shared domain knowledge and common understanding between the IT and research and development, marketing, production and financing functions.¹² Specifically, a shared IT-Business Understanding is: 1) the knowledge that IT managers possess about a specific process; 2) the knowledge the line managers possess about potential opportunities to apply IT to improve the process; and 3) the common understanding between IT and line managers regarding how IT can be used to improve process performance. Problems have been associated with adding on IT for one function, short-term rather than long-term planning, manual processes and problems evaluating entire workflow systems.^73,74

Empirical studies show successful implementation of IT requires integration with other core business functions and it leads to improved organizational performance.¹² IT helps leaders negotiate change and position for the next growth cycle, in terms of distribution, management, scale and capital issues.⁷⁵ This reflects the IT-business strategic alignment can support, organize and drive business processes. IT integration in this sense, then, is an indicator of the maturity of an organization. Investments in IT via STP have surged and the payoffs are significant – if done with a specific goal in mind and with purpose.^76,78

The Ross competencies/stages: Perhaps the best step toward a shared IT-business understanding is to create a strategic IT architecture with outcomes tiered in four levels.⁷⁹ In fact, the terms architecture and infrastructure are sometimes used interchangeably, with architecture seen as the plan for the next infrastructure. More often, IT architecture refers to a firm’s list of technology standards. But viewing IT architecture only as technology standards does not connect it to business requirements. An enterprise IT architecture concept, though, does place technology standards in the context of business requirements.

To develop a synergy between business strategy and IT architecture, firms must develop organizational competencies in IT architecture.⁷⁹ An IT architecture competency is the ability of a firm to create a mutually reinforcing pattern of evolving, tightly aligned business strategy and IT capabilities. The logical sequence for developing an enterprise IT architecture is based on defining: 1) the firm’s strategic objectives; 2) key IT capabilities for enabling those objectives; and 3) the policies and technical choices for developing the IT capabilities. This specifically includes a company’s need (e.g., doing a needs assessment) and assessing how IT is used (i.e., levels extend from silo to standardized to rationalized data to modular architecture)⁷⁹ (Table 4). Steps include defining a set of critical IT capabilities with lasting value, tradeoffs due to policies and technical choices and incremental progress.

In the case example, the Company realized that they needed to look more closely at developing a shared IT-business understanding, and that specifically, that they were missing the opportunity to capture more/better data and moving too slowly through manual processes. They also realized that this type of IT intervention was not just a “good idea” or innovation, but that they may be falling behind competitors – at a competitive disadvantage.

Will AHCs, health care systems adopt a shared IT-business understanding model?

Key steps suggested for institutions to integrate video apply to other technologies: 1) assess readiness; 2) create/hardwire the culture; 3) write policies and procedures; 4) establish the curriculum and competencies; 5) train learners and faculty; and 6) evaluate/manage change.⁵⁶ Institutional level competencies – aside from technology competencies for clinicians – involve steps for video and asynchronous competencies organized into focus areas: Patient-Centered Care; Evaluation and Outcomes; Roles/Needs of Participants (e.g., Trainees, Faculty, Teams, Professions); Teams, Professions and Systems Within Institutions; and the Academic Health Center Institutional Structure, Process and Administration (Table 5).

There are usually competing priorities in companies akin to AHCs’ clinical care, education, research and other missions. In addition, AHCs contend with policy, accreditation, reimbursement and other administrative tasks. Regulatory standards often determine how quickly policy decisions are reached and consequently result in huge differences in current state of the technology development and adoption around the globe. The significant disadvantage that an AHC or a department has, is that its existence does not depend on a shared IT-business understanding unless an AHC’s does, since millions or billions of dollars are not immediately at stake to remain viable. Traditional AHCs are not competitive with clinical models of other more modern health care systems (e.g., Kaiser, Veterans Affairs), so new AHC models by the Mayo and Cleveland Clinics are moving forward.

If an AHC decides to transform its strategic planning with technology, then institutional competencies would include a better e-platform for integrated clinical and administrative workflow, as well as a vision for short- and long-term planning. A change management plan with process management²⁶ could help to plan, prioritize and allocate resources. Buy-in across all levels is essential,^50,51 as stakeholders have to believe that technology significantly contributes to improving the mission. Then, training, supervision and evaluation is needed for managing, adjusting competencies/skills and quality/performance improvement. The deployment, innovation and integration – not the cost or elegance – enables companies to standardize and reduce costs and risks. eHealth integration and interoperability solutions use an enterprise architecture.⁸⁰ When implementation climate is strong, consistency of technology use is high. However, quality of technology use was high only when implementation climate was strong and values compatibility is high.⁸¹

DISCUSSION

Technology is rapidly shifting what we do and how we do it in day-to-day life, education, social relationships, health care and business. Our view of technology, like our view of medicine, will change over time based on social, political and scientific roots. Much of this is evident in the evolution of telephone, the stethoscope and now telehealth and telepsychiatry; human factors have always played a role.⁸² Similarly, how medicine has been conceptualized has changed over many eras from descriptions a social science, a germ theory of disease, and a battleground to a management enterprise, as well as a way to meet rights/needs (i.e., the social justice model) and an evidence-based practice (i.e., public or population health).⁸³ Business may serve as a role model for medicine/psychiatry to use technology to streamline health care across individual, community and societal domains. Models like the Learning-Adapting-Leveling (LAL) shoot for translation of technology from market to implementation into health care systems moving towards personalized health care.⁸⁴

Technology via mobile health could reshape health care service delivery if is integrated into services, used wisely and limitations are addressed.⁸⁵ A review of cognition and mobile health has raised concerns about attention, memory, and delay of gratification – and undercut colloquial assumptions that we can cognitively multi-task.^86,87 Current research on mobile health does not often employ true experimental methods with random assignment, longitudinal evaluation, momentary in-time integration of data, diverse populations and objective measures.^86,88 A further shift is research and evaluation based on effectiveness, implementation science and models of assessment of technology.^89,90,91,92 User-friendly approaches and frameworks for evaluating multi-stakeholder perspectives predict success (e.g., co-construction between designers and users).^93,94 One example would be applying the Effective Technology Use Model to implementation of e-consult management software.⁹⁵ Another option is to upgrade the Integrated Technology Implementation Model (TIM) for integrating technology into health care practice by adding a conceptual guide for nursing leadership, vendors, and engineers based on focus group methodology (i.e., Integrated TIM (ITIM)).⁹⁶

A shift in research paradigms is also suggested at a system level.⁹⁷ The Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) have been used widely in studies of health information technology implementation. TAM is determined by attitude toward using the technology, which in turn is determined by two perceptions of usefulness and ease of use. Various external factors affect both perceptions. UTAUT’s four constructs that affect usage intention are performance expectancy, effort expectancy, social influence and facilitating conditions. Age, gender, experience, and voluntariness of use mediate the impact of these expectancies on intention⁹⁸ and poor perceptions about the technology’s usefulness and lack of trust employers’ use of tracking data were associated with weaker intentions.⁹⁹ In addition, these tend to focus on individual adopters’ beliefs, perceptions and intention rather than tackling complexity with a broad enough perspective for all levels of an institution – or preferably across populations.

Multi-dimensional approaches can better capture the complexity of issues surrounding implementation and use of HIT. Models for good governance of health care technology management in the public sector globally, based on evidence-informed policy development and implementation are also suggested.¹⁰⁰ Furthermore, health technology reassessment is suggested via structured, evidence-based assessment of the clinical, social, ethical and economic effects to inform optimal use and quality of technology in comparison with its alternatives by health care providers, managers and policy-makers.¹⁰¹ Suggested phases are: 1) selection (identification and prioritization), 2) decision (evidence synthesis, policy development); and 3) policy implementation, evaluation. Some countries have an advantage in establishing consortia to create an alliance of universities, university hospitals, research institutions and IT companies, which establish Data Integration Centers (DICs) at each partner hospital and to implement use cases which demonstrate the usefulness of the approach.¹⁰²

AHC and psychiatric leaders have slowly explored/added telepsychiatric services – but few have an approach to technology, in general, due to competing clinical, educational and research demands. On one hand, radical and/or transformative change is not easy for AHCs, but on the other hand, incremental approaches are resulting in health care and psychiatry/behavioral health being passed by other components of our culture. The model of a shared IT-business-medicine¹⁰³ or IT-business-health understanding¹⁰⁴ – as part of strategic planning – could improve performance via efficiency, quality of data/information processing/integration and managerial teamwork. For it to work, though, clinicians, managers and administrators need to shift their philosophy—from seeing what happens—to proactively designing the services in advance to achieve outcomes. Needs and impact assessment for participants across all levels of the organization, continuous quality/performance and short- and long-term planning are required. For example, it is important to assess attitudes and behavior of health care workers before, during, and after implementation of real-time location system technology.⁹⁹

There are limitations to this work and many future directions are suggested. The first limitation is that this is not a formal systematic review, as this explored the literature to find key concepts, which will serve as the foundation for more specific future research. Second, other models of assessing, implementing and integrating technology exist. The shared IT-business understanding, though, is conceptually simple. If it is coupled with institutional competencies for technology and an architectural process with competency stages, institutions may self-assess and explore the next step. Third, STP is only one of many potential examples of system integration, but it is representative of business culture. Fourth, a more formal process of expert consensus could be helpful for this type of review. Finally, more research is needed on the assessment of companies’ models, objectives, methods and outcomes. The pilot application of this model and similar frameworks to medicine/psychiatry would also be helpful. Within such research, quantitative and qualitative methods would be imperative. Effectiveness rather than efficacy evaluation would also be suggested.

CONCLUSION

The field of business has some similarities with health care related to implementation of technology. Continuous, committed and active leadership is crucial for strategic planning, management and implementation of change. Leadership skill and orientation toward market, learning, entrepreneurial management style (ENT) and organizational flexibility are predictors of organizational success When IT is integrated into health care service delivery workflow rather than appended, it facilitates the translation of strategic planning into organizational change. Successful implementation requires a needs and impact assessment for patients, staff, clinicians and leaders across all levels of the organization. Incremental and strategically innovative approaches need to be evaluated and quality improved. Benefits to the mission, limited disruptions of core operational workflow and reasonable costs reduce the likelihood of failure.

ETHICAL CONSIDERATIONS

IRB approval was not necessary due to this being a review of

literature.

FUNDING SOURCES

No funding sources were required for this literature review.

ACKNOWLEDGEMENTS

VA Northern California Health care System.University of Cincinnati Lindner College of Business. University of California, Davis School of Medicine and Department of Psychiatry & Behavioral Sciences.

DISCLOSURE

On behalf of all authors, the corresponding author states that there are no financial or personal conflicts of interest. The authors participate in national organizations, but do not have leadership positions, nor would that participation impact competencies, as far as can be ascertained. The authors alone are responsible for the content and writing of the paper.

CONFLICTS OF INTEREST

The authors declare that they have no conflicts of interest

1. Pew Research Center, 2019. Mobile Fact Sheet. Web site. https://www.pewresearch.org/internet/fact-sheet/mobile/. Accessed December 18, 2020.

2. Hilty DM, Ferrer D, Callahan EJ, Johnston B, Yellowlees PM. The effectiveness of telemental health: A 2013 review. Telemed J E Health. 2013; 19: 444-454. doi: 10.1089/tmj.2013.0075

3. Hilty DM, Rabinowitz TR, McCarron RM, Katzelnick DJ, Chang T, Bauer A, et al. An update on telepsychiatry and how it can leverage collaborative, stepped, and integrated services to primary care. Psychosomatics. 2018; 59(3): 227-250. doi: 10.1016/j.psym.2017.12.005

4. Edelman DC. Branding in the digital age: You’re spending your money in all the wrong places. Harvard Business Review, 2010; 63-69.

5. Hilty DM. Advancing science, clinical care and education: Shall we update Engel’s biopsychosocial model to a bio-psycho-socio-cultural model? Psychol Cogn Sci. 2016; 1(1): e1-e6. doi: 10.17140/PCSOJ-1-e001

6. Ahuja S, Hanlon C, Chisholm D, Semrau M, Gurung D, Abdulmalik J, et al. Experience of implementing new mental health indicators within information systems in six low- and middle-income countries. BJPsych Open. 2019; 5(5): e71. doi: 10.1192/bjo.2019.29

7. Luxton DD. Artificial Intelligence in Behavioral Health Care. Boston, MA: Elsevier; 2016.

8. Shanafelt TD, Dyrbye LN, Sinsky C, Hasan O, Satele D, Sloan J, et al. Relationship between clerical burden and characteristics of the electronic environment with physician burnout and professional satisfaction. Mayo Clinic Proceedings. 2016; 91(7): 836-848. doi: 10.1016/j.mayocp.2016.05.007

9. Kuziemsky CE. A model of tradeoffs for understanding health information technology implementation. Studies in Health Technology and Informatics. 2015; 215: 116-128. doi: 10.3233/978-1-61499-560-9-116

10. Rogers EM. Diffusion of innovations. 4^th ed. New York, USA: Free Press; 1995.

11. Emerald Group Publishing Group. Survival through innovation: Microsoft and Nintendo strive to offer the latest “must haves.” Strategic Direction; Bradford. 2007; 24(1): 21-24. doi: 10.1108/02580540810839313

12. Ray G, Muhanna WA, Barney JB. Competing with IT: The role of shared IT-business understanding. Communications of the ACM. 2007; 50: 87-91. doi: 10.1145/1323688.1323700

13. Handrigan J. Nintendo’s disruptive strategy: Implications for the Video Game Industry. Memorial University of Newfoundland – Marine Institute. Case Study #2. 2013. Web site. http://www.johnpaulhandrigan.net/wp-content/uploads/2013/04/Nintendos-Disruptive-Strategy-Implications-for-the-Video-Game-Industry.pdf. Accessed December 18, 2020.

14. Rivard S, Pinsonneault A, Croteau AM. Information technology at Cirque du Soleil: Looking back, moving forward. International Journal of Case Studies in Management. 2012; 10(4): 1-13.

15. Dubois D, Bens K. Ombre, Tie-Dye, Splat Hair: Trends or Fads? “Pull” and “Push” Social Media Strategies at L’Oréal Paris. 2014. Web site. https://cases.insead.edu/loreal-google/documents/6060-Ombre_LOreal-CS-EN-0-06-2014-w.pdf. Accessed December 18, 2020.

16. Arksey H, O’Malley L. Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology. 2005; 8: 19-32. doi: 10.1080/1364557032000119616

17. Levac D, Colquhoun H, O’Brien KK. Scoping studies: Advancing the methodology. Implementation Science. 2010; 5: 69. doi: 10.1186/1748-5908-5-69

18. Corbin J, Morse JM. The unstructured interactive interview: Issues of reciprocity and risks when dealing with sensitive topics. Qualitative Inquiry. 2003; 9: 335-354. doi: 10.1177/1077800403009003001

19. Gray DE. Doing Research in the Real World. 2^nd ed. Thousand Oaks, California, USA: Sage Publications; 2009.

20. Shi L, Singh DA. Delivering Health Care in America: A Systems Approach. 6^th ed. Burlington, MA, USA: Jones and Bartlett Learning. 2015; 17(40): 195-245.

21. Dye CF. Leadership in Health Care: Essential Values and Skills. 2^nd ed. Chicago, IL, USA: Health Administration Press; 2010.

22. American Association of Medical Colleges. Academic medicine’s three missions of research, education, and patient care are critical to ensuring preparedness. 2015. Web site. https://www.aamc.org/download/446672/data/academicmedicinesthreemissionsofresearcheducationandpatientcare.pdf. Accessed December 18, 2020.

23. Centers for Medicare and Medicaid Services. Value-Based Programs. 2020. Web site. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/Value-Based-Programs. Accessed December 18, 2020.

24. Affordable Care Act (ACA). 2018. Web site. https://www.healthcare.gov/glossary/affordable-care-act/. Accessed December 18, 2020.

25. Hilty DM, Chan S, Torous J, Mahautmr J, Mucic DM. New frontiers in health care and technology: Internet- and web-based mental options emerge to complement in-person and telepsychiatric care options. Journal of Health and Medical Informatics. 2015; 6(4): 1-14. doi: 10.4172/2157-7420.1000200

26. Hilty DM, Torous J, Parish M, Chan S, Xiong G, Scher L, et al. A literature review comparing clinicians’ approaches and skills to in-person, synchronous and asynchronous care: Moving toward asynchronous competencies to ensure quality care. Telemedicine Journal and E-Health. 2020; doi: 10.1089/tmj.2020.0054

27. deBronkart D. From patient centred to people powered: Autonomy on the rise. Br Med J. 2015; 350: 148. doi: 10.1136/bmj.h148

28. Miles A, Mezzich J. The care of the patient and the soul of the clinic: Person- centered medicine as an emergent model of modern clinical practice. Int J Pers Centered Med. 2011; 1(2): 207-222. doi: 10.5750/ijpcm.v1i2.61

29. Ekman I, Swedberg K, Taft C, Lindseth A, Norberg A, Brink E, et al. Person- centered care—ready for prime time. Eur J Cardiovasc Nurs. 2011; 10(4): 248-251. doi: 10.1016/j.ejcnurse.2011.06.008

30. Aydin CE, Forsythe DE. Implementing computers in ambulatory care: Implications of physician practice patterns for system design. Proc AMIA Annu Fall Symp. 1997; 677-681.

31. Terry K. Electronic medical records make sense—at last. Medical Economics. 1999; 76: 134-153.

32. Hilty DM, Randhawa K, Maheu MM, McKean AS, Pantera R, Rizzo A. A review of telepresence, virtual reality and augmented reality applied to clinical care. J Technol Behav Sci. 2020; 5: 178-205. doi: 10.1007/s41347-020-00126-x

33. Liddy C, Drosinis P, Keely E. Electronic consultation systems: worldwide prevalence and their impact on patient care – a systematic review. Fam Pract. 2016; 33(3): 274-285. doi: 10.1093/fampra/cmw024

34. Archibald D, Stratton J, Liddy C, Grant RE, Green D, Keely EJ. Evaluation of an electronic consultation service in psychiatry for primary care providers. BMC Psychiatry. 2018; 18(1): 119. doi: 10.1186/s12888-018-1701-3

35. Berrouiguet S, Baca-García E, Brandt S, Walter M, Courtet P. Fundamentals for future mobile-health (mhealth): A systematic review of mobile phone and web-based text messaging in mental health. J Med Int Res. 2016; 18(6): e135. doi: 10.2196/jmir.5066

36. Pisani AR, Wyman PA, Gurditta K, Schmeelk-Cone K, Anderson CL, Judd E. Mobile phone intervention to reduce youth suicide in rural communities: Field test. JMIR Ment Health. 2018; 5(2): e10425. doi: 10.2196/10425

37. L’Hommedieu M, L’Hommedieu J, Begay C, Schenone A, Dimitropoulou L, Margolin G, et al. Lessons learned: recommendations for implementing a longitudinal study using wearable and environmental sensors in a health care organization. JMIR mHealth and uHealth. 2019; 7(12): e13305. doi: 10.2196/13305

38. Hilty DM, Armstrong CM, Luxton DD, Gentry M, Krupinski E. A framework of sensor, wearable and remote patient monitoring competencies for clinical care and training: Scoping review. JMIR Mhealth Uhealth. 2020; 8(2): e12229. doi: 10.2196/12229

39. Hilty DM, Zalpuri I, Stubbe D, Snowdy CE, Shoemaker EZ, Joshi SV, et al. Social media/networking as part of e-behavioral health and psychiatric education: Competencies, teaching methods, and implications. J Technol Behav Sci. 2018; 3(4): 268-293. doi: 10.1007/s41347-018-0061-7

40. Hilty DM, Crawford A, Teshima J, Chan S, Sunderji N, Yellowlees PM, et al. A framework for telepsychiatric training and e-health: Competency-based education, evaluation and implications. Int Rev Psychiatry. 2015; 27(6): 569-592. doi: 10.3109/09540261.2015.1091292

41. Hilty DM, Maheu MM, Drude KP, Hertlein KM. The need to implement and evaluate telehealth competency frameworks to ensure quality care across behavioral health professions. Acad Psychiatry. 2018; 42(6): 818-824. doi: 10.1007/s40596-018-0992-5

42. Maheu M, Drude K, Hertlein K, Lipschutz R, Wall K, Hilty DM. An interdisciplinary framework for telebehavioral health competencies. J Technol Behav Sci. 2019; 3(2): 108-140. doi: 10.1007/s41347-019-00113

43. Zalpuri I, Liu H, Stubbe D, Wrzosek M, Sadhu J, Hilty D. A competency-based framework for social media for trainees, faculty and others. Academic Psychiatry. 2018; 42(6): 808-817. doi: 10.1007/s40596-018-0983-6

44. Hilty DM, Chan S, Torous J, Luo J, Boland R. A telehealth framework for mobile health, smartphones and apps: Competencies, training and faculty development. J Technol Behav Sci. 2019; 4(2): 106-123. doi: 10.1007/s41347-019-00091-0

45. Hilty DM, Chan S, Torous J, Luo J, Boland RJ. A framework for competencies for the use of mobile technologies in psychiatry and medicine. JMIR Mhealth Uhealth. 2020; 8(2): e12229. doi: 10.2196/12229

46. Carr DK, Hard KJ, Trahant WJ. Managing the Change Process: A Field Book for Change Agents, Consultants, Team Leaders, and Reengineering Managers. New York, NY, USA: McGraw Hill. 1996; 115-140.

47. Mulgan G, Albury D. Innovation in the Public Sector, Strategy Unit, Cabinet Office, October 2003. Web site. http://www.sba.oakland.edu/faculty/mathieson/mis524/resources/readings/innovation/innovation_in_the_public_sector.pdf. Accessed December 18, 2020.

48. Borins S. The Challenge of Innovating in Government. The Pricewaterhouse Coopers Endowment for The Business of Government. 2001. Web site. http://www.businessofgovernment.org/report/challenge-innovating-government. Accessed December 18, 2020.

49. Kotter JP. A Force for Change: How Leadership Differs from Management. New York, USA: The Free Press; 1990.

50. Kotter JP. Leading change. Why transformation efforts fail. Harvard Business Review. 1996; 59-67.

51. Miller WR, Rollnick S. Motivational Interviewing: Preparing People for Change. 2^nd ed. New York, USA: Guilford; 2002.

52. Backer TE. Managing the human side of change in VA’s transformation. Hosp Health Serv Adm. 1997; 42: 431-459.

53. Deming WE. Out of the Crisis. Cambridge, England: MIT Press; 1982.

54. Walton M. The Deming Management Method. New York, USA: Perigee Trade; 1988.

55. Nadler G, Hibino S, Farrell J. Creative Solution Finding: The Triumph of Breakthrough Thinking Over Conventional Problem Solving. Rocklin, CA, USA: Prima Publications; 1999.

56. Hilty DM, Unutzer J, Ko D-K, Luo J, Worley LM, Yager J. Approaches for departments, schools and health systems to better implement technologies used for clinical care and education. Acad Psychiatry. 2019; 43: 611-616. doi: 10.1007/s40596-019-01074-2

57. Armenakis AA, Harris SG, Mossholder KW. Creating readiness for organizational change. Human Relations. 1993; 46: 681-703. doi: 10.1177/001872679304600601

58. Marshall J, Conner DR. Another reason why companies resist change. strategy and business. 1996. Web site. http://www.strategy-business.com/press/article/8614?pg=0. Accessed December 18, 2020.

59. Diamond MA. Organizational change as human process, not technique. NIDA research monograph. 1995; 155: 119-131.

60. U. S. Department of Labor, Bureau of Labor Statistics. Coronavirus Resources. Web site. https://www.dol.gov. Accessed August 20, 2020.

61. Hagenbaugh B. Nation’s wealth disparity widens. USA Today. 2002. Web site. http://usatoday.printthis.clickability.com/pt/cpt?action=cpt&expire=&urlID=5183409&fb=Y&partnerID=1661. Accessed December 18, 2020.

62. Hilton B, Balloun J, Weinstein C. Success factors for organizational performance: Comparing business services, health care, and education. SAM Advanced Management Journal. 2005; 70(4): 16-28.

63. Hee J, Chen Y, Huang W. Straight through processing technology in global financial market: Readiness assessment and implementation. Journal of Global Information Management. 2003; 11(2): 56-66.

64. Grody AD. Observations on the new US financial regulation challenges to the financial sector: data standardization, straight-through-processing and operational risks. Journal of Operational Risk. 2010; 5(3): 23-27.

65. Sinn B. Straight-through processing helps bolster insurer data quality, client intelligence. 2009. Web site. https://www.propertycasualty360.com/2009/09/20/straight-through-processing-helps-bolster-insurer-data-quality-client-intelligence/?slreturn=20210028203035. Accessed December 18, 2020.

66. Saccocia C. Placing your technology bets. Insur Tech. 2003; 28(13): 37-41.

67. Franklin R. Modernizing the back office of the securities industry. Computer World. 2000; 34: 11-36.

68. Mearian L. Trades at top speed. Computer World. 2003; 37(9): 21-24.

69. Osheroff JA, Teichc JM, Middletone B, Steen EB, Wright A, Detmer DE. A roadmap for national action on clinical decision support. J Am Med Inform Assoc. 2007; 14(2): 141-145. doi: 10.1197/jamia.M2334

70. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: A systematic review of trials to identify features critical to success. BMJ (Clinical Research Edition). 2005; 330(7494): 765. doi: 10.1136/bmj.38398.500764.8F

71. Natarajan M, Arshad K, Girish N, Sethu G. (). Straight through processing (STP): Prospects and challenges. Journal of Decision Making. 2004; 29(1): 93-100. doi: 10.1177/0256090920040108

72. The National Academy of Sciences, Engineering, and Medicine. Health and Medicine Division. 2020. Web site. https://www.nationalacademies.org/hmd/health-and-medicine-division. Accessed December 18, 2020.

73. Bower JL, Christensen CM. Disruptive Technologies: Catching the Wave. 1995. Web site. https://hbr.org/1995/01/disruptive-technologies-catching-the-wave. Accessed December 18, 2020.

74. Christensen CM, Grossman JH, Hwang J. The Innovators Prescription – A Disruptive Solution for Health Care. New York, NY, USA: McGraw Hill; 2009.

75. Annunziata VP. Straight-through Processing. Energy Markets. 2001. Web site. https://search-proquest-com.proxy.libraries.uc.edu/docview/228764026?accountid=2909. Accessed December 18, 2020.

76. Dedrick J, Gurbaxani V, Kramer KL. Information technology and economic performance: A critical review of the empirical evidence. ACM Computing Surveys. 2003; 35: 1-28. doi: 10.1145/641865.641866

77. Kohlh R, Devarag S. Measuring information technology payoff: A meta-analysis of structural variables in firm-level empirical research. Information Systems Research. 2003; 14: 127-145. doi: 10.1287/isre.14.2.127.16019

78. Rai A, Parnayakuni R, Patnayakuni N. Technology investments and business performance. Communication of the ACM. 1997; 40: 89-97. doi: 10.1145/256175.256191

79. Ross JW. Creating a strategic IT architecture competency: Learning in stages. MIT Sloan School of Management Working Paper, 4314-03, Center for Information Systems Research Working Paper, No. 335. 2003. Web site. http://dspace.mit.edu/handle/1721.1/3526. Accessed December 18, 2020.

80. Adenuga OA, Kekwaletswe RM, Coleman A. eHealth integration and interoperability issues: Towards a solution through enterprise architecture. Health Inf Sci Syst. 2015; 3: 1. doi: 10.1186/s13755-015-0009-7

81. Holahan PJ, Lesselroth BJ, Adams K, Wang K, Church V. Beyond technology acceptance to effective technology use: A parsimonious and actionable model. Journal of the American Medical Informatics Association. 2015; 22(3): 718-729. doi: 10.1093/jamia/ocu043

82. Mermelstein H, Krupinski E, DeGuzman E, Rabinowitz T, Hilty DM. The application of technology to health: The evolution of telephone to telemedicine and telepsychiatry: A historical review and look at human factors. J Technol Behav Sci. 2017; 1(2): 5-20. doi: 10.1007/s41347-017-0010-x

83. Sturmberg JP, O’Halloran D, Colagiuri R, Fernandez A, Lukersmith S, Torkfar G, et al. Health care frames – from Virchow to Obama and beyond: The changing frames in health care and their implications for patient care. J Eval Clin Pract. 2014; 20(6): 1036-1044. doi: 10.1111/jep.12266

84. Lal JA, Morré SA, Brand A. The overarching framework of translation and integration into health care: A case for the LAL model. Per Med. 2014; 11(1): 41-62. doi: 10.2217/pme.13.97.13.97

85. Hilty DM, Chan S. Human behavior with mobile health: Smartphone/devices, apps and cognition. Psychol Cogn Sci Open J. 2018; 4(2): 36-47. doi: 10.17140/PCSOJ-4-141

86. Wilmer HH, Sherman LE, Chein JM. Smartphones and cognition: A review of research exploring the links between mobile technology habits and cognitive functioning. Frontiers in Psychology. 2017; 8: 605. doi: 10.3389/fpsyg.2017.00605

87. Egan T. The Eight-Second Attention Span. New York, NY, USA: The New York Times.2016

88. Vukovic V, Favaretti C, Ricciardi W, de Waure C. Health technology assessment evidence on e-health/m-health technologies: Evaluating the transparency and thoroughness. Int J Technol Assess Health Care. 2018; 34(1), 87-96. doi: 10.1017/S026646231700451262317004512

89. Proctor E, Silmere H, Raghavan R, Raghavan R, Hovmand P, Aarons G, et al. Outcomes for implementation research: Conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2010; 38(2): 65-76. doi: 10.1007/s10488-010-0319-7

90. Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: Combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012; 50(3): 217-226. doi: 10.1097/MLR.0b013e3182408812

91. Gargon E, Gorst SL, Williamson PR. Choosing important health outcomes for comparative effectiveness research: 5th annual update to a systematic review of core outcome sets for research. PLoS One. 2019; 14(12): e0225980. doi: 10.1371/journal.pone.0225980

92. Kidholm K, Jensen LK, Kjølhede T, Nielsen E, Horup MB. Validity of the model for assessment of telemedicine: A delphi study. Journal of Telemedicine and Telecare. 2018; 24(2): 118-125. doi: 10.1177/1357633X16686553

93. Cranfield S, Hendy J, Reeves B, Hutchings A, Collin S, Fulop N. Investigating health care IT innovations: A “conceptual blending” approach. Journal of Health Organizational Management. 2015; 29(7): 1131-1148. doi: 10.1108/JHOM-08-2015-0121

94. Walker DM, Hefner JL, Sieck CJ, Huerta TR, McAlearney AS. Framework for evaluating and implementing inpatient portals: A multi-stakeholder perspective. Journal of Medical Systems. 2018; 42(9): 158. doi: 10.1007/s10916-018-1009-3

95. Lesselroth B, Adams K, Mastarone G, Tallett S, Ragland S, Laing A, et al. Applying the effective technology use model to implementation of electronic consult management software. Stud Health Technol Inform. 2019; 257: 261-265.

96. Schoville R, Titler MG. Integrated technology implementation model: Examination and enhancements. Computers, Informatics, Nursing. 2020; 38(11): 579-589. doi: 10.1097/CIN.0000000000000632

97. Shachak A, Kuziemsky C, Petersen C. Beyond TAM and UTAUT: Future directions for HIT implementation research. Journal of Biomedical Informatics. 2019; 100; 103315. doi: 10.1016/j.jbi.2019.103315

98 . Rahimi B, Nadri H, Lotfnezhad Afshar H, Timpka T. A systematic review of the technology acceptance model in health informatics. Applied Clinical Informatics. 2018; 9(3): 604-634. doi: 10.1055/s-0038-1668091

99. Griffin JM, Hellmich TR, Pasupathy KS, Funni SA, Pagel SM, Srinivasan SS, et al. Attitudes and behavior of health care workers before, during, and after implementation of real-time location system technology. Mayo Clin Proc Innov Qual Outcomes. 2020; 4(1): 90-98. doi: 10.1016/j.mayocpiqo.2019.10.007

100. Houngbo PT, Coleman HL, Zweekhorst M, De Cock Buning T, Medenou D, Bunders JF. A model for good governance of health care technology management in the public sector: Learning from evidence-informed policy development and implementation in benin. PLoS One. 2017; 12(1): e0168842. doi: 10.1371/journal.pone.0168842

101. Soril LJ, MacKean G, Noseworthy TW, Leggett LE, Clement FM. Achieving optimal technology use: A proposed model for health technology reassessment. SAGE Open Med. 2017; 5: 2050312117704861. doi: 10.1177/2050312117704861

102. Winter A, Stäubert S, Ammon D, Aiche S, Beyan O, Bischoff V, et al. Smart Medical Information Technology for Health care (SMITH) *- Data Integration based on Interoperability Standards. Methods Inf Med. 2018; 57(S 01): e92-e105. doi: 10.3414/ME18-02-0004

103. Hilty DM, Uno J, Chan S, Torous J, Boland RJ. Role of technology in faculty development in psychiatry. Psychiatric Clinics of North America. 2019; 42: 493-512. doi: 10.1016/j.psc.2019.05.013

104. Hilty DM, Armstrong CM, Luxton DD, Gentry M, Krupinski E. Sensor, wearable and remote patient monitoring competencies for clinical care and training: Scoping review. J Tech Behav Sci. 2021; 1-26. doi: 10.1007/s41347-020-00190-3