Peer Review Articles on Sdlc and the Dynamic System Development Method in Nursing

Nurs Outlook. Writer manuscript; available in PMC 2020 Jul ane.

Published in concluding edited form as:

PMCID: PMC6679802

NIHMSID: NIHMS1523923

Models of Collaboration and Dissemination for Nursing Informatics Innovations in the 21^st Century

Jing Wang, PhD, MPH, RN, FAAN, Professor,^one Sheila K. Gephart, PhD, RN, Associate Professor,² Jennifer Mallow, PhD, FNP-BC, Associate Professor,³ and Suzanne Bakken, PhD, RN, FAAN, FACMI, Alumni Professor ^iv

Jing Wang

^1.The University of Texas Health Science Eye at San Antonio, School of Nursing, San Antonio, TX, USA

Sheila M. Gephart

^2.University of Arizona College of Nursing, Tucson, AZ, U.s.a.

Jennifer Mallow

^iii.West Virginia University, Morgantown, WV, USA

Suzanne Bakken

^4.Nursing and Professor of Biomedical Informatics, Columbia University, New York, NY, Usa

Abstract

Nursing informatics innovations are constantly adapting to a rapidly changing healthcare environment. Four example studies of informatics projects led by nurse scientists were described and analyzed through the lens of the Informatics Inquiry Organizing Model (IROM) which was modified to include policy and interoperability contexts. The comparing analysis examined dynamic relationships between processes and constructs in nursing informatics interventions and too highlighted the scientific, intellectual property, technical, and policy challenges encountered amidst the four case studies. The assay provided implications for future intervention development and implementation in consideration of multiple contexts.

Keywords: Health equity, connected wellness, intellectual property, nursing informatics, mobile health, informatics, remote monitoring, clinical conclusion support system, data scientific discipline, policy

Introduction

The American Nurses Clan (ANA) defined nursing informatics as a "specialty that integrates nursing science, estimator science, and information science to manage and communicate data, information, noesis, and wisdom in nursing practise. Nursing informatics supports consumers, patients, and providers in their decision‐making in all roles and settings. This support is accomplished through the utilise of information structures, data processes, and data technology." (ANA, 2008) While this definition remains relevant today, the policy drivers for nursing informatics specialists have evolved to meet the demands of the 21^st century. Appropriately, inquiry in nursing information science is constantly adapting. In this paper, we starting time review fundamental policy drivers in the 21^st century with an accent on nursing informatics research. Then, nosotros depict and analyze four information science research projects led by nurse scientists using the lens of the Informatics Inquiry Organizing Model (IROM) every bit a strategy to compare and contrast technical and scientific approaches. We selected the IROM from among the many informatics frameworks because of its explicit handling of context, which we modified by including policy considerations. Based upon this analysis, we describe key lessons for nurse scientists conducting informatics research in the current policy context.

Key Policy Drivers

Health Information technology for Economic and Clinical Health Act

The enactment of the Health Information Technology for Economic and Clinical Health (HITECH) Act in 2009 spurred health institutions and practices throughout the nation to implement health information technology (HIT) (The U.South. Department of Health & Human Services, 2009). For case, over 4800 hospitals have received payment incentives for participation in the Medicare and Medicaid Electronic Health Record (EHR) Incentive Program (Centers for Medicare and Medicaid Services, 2016). These developments in the Hitting mural accept been supported by regulations to guide the use and deployment of technology with the aim of achieving real, measurable benefits for wellness institutions, professionals, and patients.

Meaningful Use, Federal Hit Strategic Plan 2015 – 2020 and ONC'southward A Shared Nationwide Interoperability Roadmap (2015)

Meaningful Apply Regulations, a program led by the Centers for Medicare and Medicaid Services (CMS) and the Office of the National Coordinator (ONC) for HIT were adult to prepare requirements and deadlines for the implementation and employ of certified EHRs (Centers for Medicare and Medicaid Services, 2018). The latest endeavour, stage 3 of Meaningful Use, seeks to attain the interoperability of health data by ensuring that certified EHRs are continued to exist able to support the electronic commutation of wellness information. Stage 3 requires that this integration be able to demonstrate improvements in the quality of care for patients while maintaining adequate privacy and security. The evolution of local and national health data exchange (HIE) is ane initiative promoted to accomplish these goals.

More recently, the Federal HIT Strategic Plan (2015–2020) from the ONC outlines how the federal authorities aims to use Striking to leverage lower costs while achieving higher quality care and greater engagement from the population (ONC, 2015). The ONC'due south shared nationwide interoperability roadmap further highlights the importance of integrating patient-generated health data into care commitment and research (ONC, 2018). Nurses, regarded as the most honest and ethical profession past the public, are in an ideal position to apply Hitting tools and patient-generated health data to engage patients in their own intendance and promote continued health and care.

21^st Century Cures Act

In 2016, the 21^st Century Cures Human action was signed into police to accelerate innovations in inquiry and medical products to help patients in demand of faster access and efficiency (The 114th United States Congress, 2016). In 2017, ONC engaged with stakeholders in back up of the 21^st Century Cures Act Trusted Exchange Framework and Common Understanding that prioritized the cohesiveness and interoperability of HIT. However, in the clinical implementation of HIT, a developer or researcher can encounter significant barriers related to intellectual property and governance. In cases where an innovation is shown to exist constructive in one EHR arrangement, considerable reprogramming and retrofitting may be required for information technology to role in another. One possible solution to this upshot is the adoption of Hitting standards, including common data models. Yet, the implementation of such projects is subject to internal administrative determination-making and technology customization, which may be out of the command of nurse informaticians.

Modified IROM

To plan, blueprint, and implement Hit effectively, the social and organizational context of intendance must be considered. Although several frameworks exist in informatics to guide system development, few accept account of context. Effken (2003) The IROM is a comprehensive conceptual model adult at a high level of abstraction to guide many types of nursing computer science research (Effken, 2003; Figure 1). The IROM incorporates the elements of the Systems Development Life Cycle (SDLC) within the broader framework of the Systems Research Organizing Model (Effken, 2003). The IROM'southward concepts of client, context, outcomes, and activeness focus (adapted to nursing informatics innovation in the IROM) reflects the reciprocal nature of the concepts (Brewer, Verran, & Stichler, 2008). The SDLC, which is widely used in HIT projection management, guides the pattern, implementation, and evaluation procedure, creating many opportunities to develop and validate enquiry hypotheses. The SDLC is a unidirectional cycle that directs the planning, analysis, design, implementation, and maintenance of a nursing informatics innovation within the IROM. The IROM incorporates evaluation as an iterative pace, implying that evaluation is continuous and diffused at many stages in the innovation procedure. Outcomes evaluated with the IROM tin can include the data flow, noesis, quality of decisions, and the effect of actions taken to improve quality, safety, satisfaction, and toll (Effken, 2003). Evaluation can exist carried out using logic models, plan evaluation methods, or formal research studies. Effigy 1 operationalizes the concepts of the IROM for the projects conducted individually past the authors, and adding policy under "Context".

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Modified Computer science Research Organizing Model (Modified from Effken, 2003)

Study Purpose

In calorie-free of the policy context and the need to develop, exam and deploy informatics for nursing our study purpose was to: 1) analyze four informatics inquiry projects from the lens of the IROM, and 2) describe lessons learned and decision making to inform design choices for future information science projects. Issues effectually interoperability, intellectual belongings, decisions to build a new system or conform an existing arrangement, and the potential impact of decisions on patient outcomes are presented.

Methods

The constructs of the IROM were used as a lens to complete a cross-case assay of 4 different research projects. Employ of the IROM was selected to highlight how each case written report addressed different stages of the SDLC and to identify lessons learned. These projects addressed unique populations and were conducted beyond varied healthcare settings (e.g., urban, rural, intensive care, primary care, and outpatient patient teaching). Variations in the approaches to technology design, intellectual property management, and project implementation are presented. While Institutional Review Board (IRB) approval was obtained by each author for their respective projects, this cross-instance analysis did not involve human subjects. Hence, IRB blessing was non necessary for this project.

Over 10 months, contiguous and electronic meetings were conducted to collaboratively place and analyze the application of the IROM elements across the cases using a multiple case study arroyo (Eisenhardt, 2007; Stake, 2013). This cross-case arroyo mirrored one taken when applying customs-based participatory research principles to appoint underserved populations in informatics research (Unertl et al., 2016).

The four cases varied in terms of study procedures, populations, metrics captured, and analytic approaches. Hence, merging their results was non possible. Still, applying a cross-case qualitative comparison was used to identify a set of key ideas that others may find helpful as they create, implement, and disseminate technologies. For that reason, the collection and analysis of data for the cross-instance comparison followed a descriptive qualitative approach. In initial meetings, the writer team described their private projects and the components thereof using the IROM concepts (Table 1). Their stage of development according to the SDLC was identified (Table ii), and then development decisions were described (Tabular array three). Together, the tables served as information drove structures to facilitate the cantankerous-case qualitative analysis. The authors reviewed and discussed report details and examined patterns across the cases to identify central lessons learned. Grouping discussions held via briefing calls allowed deeper explorations of decisions and approaches and identified patterns beyond cases in add-on to individual differences.

Tabular array 1.

Components of the Information science Inquiry Organizing Model by Instance

Project	Context	Customer	Informatics Intervention	Evaluation/Outcomes
Connect Diabetes (Jing Wang, Chu, Li, Hayes, & Siminerio, 2018; J. Wang, Coleman, Kanter, Ummer, & Siminerio, 2018; Wang J, 2015)	Cultural (organizational culture): Newspaper-based food diaries that can be tracked by educators to gear up behavioral goals Economic: Patients are increasingly using apps and wearable devices for tracking diet and concrete action and adopt various brands Social: Increase patient-educator communication; patient-centered medical dwelling Concrete (implementation): Diabetes educational activity programs in master care and other ambulatory settings urban and rural Houston, TX, and Pittsburgh, PA Policy: None of the major hospitals or clinics were willing to connect mobile data to EHR as of 2013 when the project started. Diabetes educators typically use 2 systems: EHR for general patient records and Chronicle system for diabetes education specific documentation. Interoperability of these 2 systems	Users of the arrangement: diabetes educators Intervention target: Blazon ii diabetes patients Information: Diet and concrete activity behaviors	Patients: Behavioral self-monitoring using mobile app and habiliment fitness tracker Diabetes educators: Tailored diabetes selfmanagement education using mobile selfmonitoring data Content: Calendar view in two tabs on patient cocky-monitoring of diet and activity data Structure: This connected interface is housed in an existing platform used past diabetes educators for documentation. Menstruation of information: From patients to educators Applied science characteristics: Web-based electronic organization for diabetes pedagogy documentation Proprietary or non: Interoperability Patients: commercial apps or fettle trackers that are uniform with the Validic system. Diabetes educators: freely available for ADA-recognized education programs in one case activated.	Usability: of continued interface, Organisation usability scale think aloud, cognitive walkthrough of continued interface prior to the design of wireframe, subsequently the wireframe, and iterative evaluation, real-earth usability evaluation in a 2-week pilot and 3-month feasibility trial. Feasibility: Capacity to use this tool to facilitate diabetes education sessions to be more personalized Acceptability: Patients and diabetes educators' views on the acceptability of this continued interface Patient/clinical outcomes: Efficacy Patient A1 c change and weight loss Effectiveness Future studies in evaluating this tool.
ml SMART(J. A. Mallow et al., 2015; J. A. Mallow, Theeke, L. A., Walls, R., Theeke, E., & Mallow, B. G., 2016a, 2016b)	Cultural: Patients experience multiple chronic conditions and health disparity. Providers need to provide frequent, intensive intervention that decreases brunt for patients. Physical: Gratuitous primary care clinic in rural Appalachia Economical: Depression-income patients who yet have access to net and mobile devices. Social: Increase patient and provider advice and patient centered intendance. Policy: Policies for federal payers were improving and Medicare pays for services that provide live, interactive videoconferencing at the fourth dimension of development. Regionally, no system was willing to connect mobile data to EHR due to potential legal considerations. Locally, Near of the intendance provided at the dispensary is by nurse practitioners. Interoperability: Providers have to use log into multiple systems to provide comprehensive care to patients.	Users of the system: Rural patients and healthcare providers. Intervention target: Patients with multiple chronic conditions and wellness disparities Information: Blood glucose, blood pressure, pulse, and weight from mHealth monitors; mistake logs from application; page hits and time in application for patients and providers	Patients: Access patient facing application that enables main care from a altitude. track diagnoses, medications, lab results, receive reminders for self-management, perform self-monitoring for multiple chronic conditions, obtain feedback in real time, appoint in education, and attend eVisits (video conferencing) Providers: Access provider facing awarding to deliver education, prescribe selfmanagement via mHealth devices, monitor patient self-monitoring results, provide feedback and intervention, perform assessment and intervention via video conferencing. Content: Rails diagnoses, medications, laboratory results, receive reminders for selfmanagement, perform cocky-monitoring, obtain feedback in real time, engage in education, and attend video visits Structure: Web based platform to brandish results of self-management results using mHealth devices Menstruation of information: two mode between patients and healthcare providers. Technology characteristics: Web-based organization for primary intendance delivery and access. Proprietary or Not: Proprietary	Feasibility: Power to receive and transmit health data wirelessly in rural areas. Power to complete main care visits without travel. Acceptability: Evaluated cost, quality, prophylactic, interface usability, and patient satisfaction Patient/clinical outcomes: Adherence to treatment/Delivery of guideline-recommended intendance via technology Efficacy: Self-management ability, quality of life, low, blood glucose, blood force per unit area, and torso weight. Effectiveness: Future studies.
NEC-Zero Clinical Determination Support (Gephart et al., 2017; Gephart, Wyles, & Canvasser, 2018)	Cultural: Directed at clinicians and not specifically addressing cultural factors for patients. Fit to clinician workflow and designed to align with their clinical decision-making approaches. Economic: Goal to reduce barriers to use of the technology across systems but did non want information technology to become the holding of a single EHR. Information technology is costly to recreate CDS beyond systems. Social: Distributed decisionmaking in the NICU so that clinicians can place decisions made by others. Physical: Neonatal intensive care unit Policy: 21st Century Cures Act, MACRA and HITECH prioritize interoperable clinical decision support to support loftier quality care and lower cost. Local CDs and clinician governance groups involved with designing the CDS. Local policies that support or limit access to FHIR apps have affected their readiness to implement.	Users: Neonatal clinicians making decisions Intervention target: Very low birth weight neonates within the showtime 2 months of life Data: Clinician part, neonate risk, feeding, lab, medications, and care factors from the EHR. Information is accessed via API request using FHIR.	Patients: Premature infants weighing < 1500 grams at birth. Clinicians: Neonatologists, neonatal nurse practitioners, nurses, pharmacists, physician assistants Content: Text-based and dashboard displays of guidance and clinical information to support clinical decisions that align with the NEC-Zero show-based intervention. NEC-Nada includes early, sectional access to man milk; utilise of a standardized feeding protocol; avoiding prolonged early on antibiotics and any antacids; and a structured hazard assessment with early warning score for NEC. Construction: in-line with EHR using a CDS claw to link from within the EHR to the dashboard which displays exterior of the EHR. The CDS architecture is separate from the data that is generated within the EHR. Flow of data: EHR-generated information used to populate the dashboard. Rules trigger guidance within the dashboard based on data that is fed in from the EHR. Engineering science characteristics: Service-oriented architecture that lays over the EHR within a hospital'south firewall with CDS engine separated from EHR. Proprietary or not: Connecting platform (designed to work across platforms-e.chiliad. Cerner, GE Centricity, Sorian) is proprietary with components (i.e. dashboard) bachelor open source.	Feasibility: FHIR ceremoniousness and need for extensions to suit the neonatal intensive intendance information elements. Case examples of NICUs using the knowledge in NEC-Cipher to reduce NEC. Acceptability: Adherence score deemed acceptable by clinicians, data used to populate display identified via clinician focus groups. Clinician satisfaction and usability cess planned. Efficacy: Testing is in progress to evaluate result on patient and CDS outcomes. Effectiveness: Future studies
EnTICE³ (Arcia, 2018; Unertl et al., 2016)	Cultural: Latino research subjects Physical: community-based information drove restricted to 5 ZIP codes in Washington Heights and Inwood communities in NYC Economic: Mainly Medicaid/Medicare recipients Social: Depression levels of pedagogy and wellness literacy Policy: RESTful Web service architecture supports interoperability	User: Researcher Target population: Latino research participants in WICER project Information: Participantgenerated via contiguous survey (sociodemographics, PROMIS measures, health behaviors), claret pressure, BMI	Tailored infographics Content: Visual display of individual or aggregate with comparison to benchmark, community, or national standards on blood pressure, physical activeness, PROMIS concrete and mental wellness, etc. Structure: Standalone module using the RESTful Web service architecture Flow of data: Participant data to EnTICE3, output equally tailored infographic infographics Technology platform: Web Proprietary or not: Not-proprietary (open up source in GitHub)	Software: EnTICE³ Feasibility: Demonstrated capacity to create tailored visualizations at scale Visualization output component of EnTICE³ Usability: Stage 1: Participatory pattern - designs perceived to be understandable, acceptable, and actionable Stage 2: Tailored designs created with EnTICEⁱⁱⁱ rated as useful and important by >100 participants in a town hall setting who received their individual information Phase iii: Comprehensive laboratory study (in progress)

Tabular array two.

Development Decisions

Project	Conclusion	Rationale
Project	Conclusion	Scientific Rationale	Intellectual Property Considerations	Technical Chapters	Policy Considerations
Connect Diabetes	Build a connected interface linking mobile self-monitoring information into Chronicle Diabetes, a nationally available electronic diabetes pedagogy system used by diabetes didactics programs and focus on usability of the connected interface, without real integration into EHRs	Diabetes educators demand integration of mobile self-monitoring data into Chronicle Diabetes system to facilitate goal setting and follow-up for diabetes selfmanagement education and back up. Patients and diabetes educators volition benefit from this with less fourth dimension spent on doing dietary recalls, and more than time on individualized educational activity and support. Focusing on usability of the connected interface is critically of import earlier implementing continued systems nationwide.	Chronicle Diabetes system is owned by a company and the Academy of Pittsburgh. The ADA has gratis license to utilise it to benefit the diabetes educator community. A number of commercially bachelor mobile tools can engage patients in diet and physical activity cocky-monitoring, with open APIs to link to other systems. Connecting Chronicle Diabetes with a single mobile app or fitness tracker company does non allow patients to cull their preferred brands. The decision was made to use a 3^rd political party intermediary platform to enable patient choices of different mobile and article of clothing tools, all the same standardized its connection with EHRs.	Chronicle Diabetes is a nationally used arrangement specifically designed for and by diabetes educators on documenting diabetes selfmanagement education, a perfect location to receive patient self-monitoring data. The 3^rd party intermediary platform is a HIPPA-compliant system experienced in connecting different mobile and habiliment tools, and standardizing language to connect with EHRs.	Local/System: No local hospital system was willing to connect mobile information into their EHRs. National: The ADA is giving the Relate Diabetes system to all of its recognized diabetes instruction programs to use for complimentary as an EHR system for tracking diabetes teaching practice.
ml SMART	Apply engineering to overcome the known wellness disparity of distance to dispensary for depression-income individuals in a rural land living with multiple chronic conditions.	No existing applied science tool or intervention was able to treat/monitor multiple chronic conditions for individuals with social determinants of health disparity such every bit depression socioeconomic condition, education, poor concrete environment, employm ent challenges, lack of social support networks, and access to wellness care low literacy.	Components of the mI SMART intervention are published and freely usable by interested individuals. However, the intellectual property related implementation of the mI SMART intervention into workflow of individual systems and customization prior to implementation remains proprietary. This decision was made by the squad to insure brunt of using the applied science intervention for patients and providers is minimized. Customization takes time and monetary resources.	The mI SMART intervention is a web-based application that sits outside of individual EHRs. This allows assuasive for hereafter expansion without the need for a specific app operating systems. All the same, this requires patients and providers to log into a separate system exterior the EHR.	Local/System: The local free clinic uses a free EHR. Integration into this EHR would limit the scalability of the intervention to clinics using this specific EHR. While, Application Programing Interfaces are available to developers, the local big medical center was non willing to permit the integration of the intervention into the nationally used EHR system.
NEC-Zero	Build a SMART on FHIR app using standards and open source licensing for CDS to help clinicians brand evidence-based decisions about preventing neonatal complications.	To test effectiveness in the future, the CDS must be efficiently scaled to apply to 20+ NICUs at one time. Recreating information technology in each system would prohibit the feasibility of conducting a pragmatic trial in the future.	Needed to have the freedom to exam it beyond NICUs without recreating the CDS. Did non desire one vendor to "own" or "limit" our power to share it or scale it.	Every neonatal intensive care unit of measurement clinician could benefit from the knowledge base for NEC-Nada and it was an ethical determination to make information technology open source.	Local: Hospital needs to allow and use the FHIR server. National: The 21st Century Cures human action made information technology mandatory for EHR vendors to allow open APIs that enable linking into the EHR via SMART on FHIR (Mandl & Kohane, 2017).
EnTICEⁱⁱⁱ	Build a visualization module suitable for interfacing with applications	Returning research results through tailored information visualizations has the potential to amend understanding of healthcare data, promote appointment, and motivate selfmanagement activities.	Open-source approach	No existing tool met project requirements for a module that could have input information from a multifariousness of sources (e.g., survey) and output tailored data visualizations to a variety of applications (e.g., paper, customs portal, EHR)	Local: Institutional policy prevented release of infographic data to research cohort via community portal due to a recent HIPAA violation fine.

Table 3.

Current and Future Informatics Innovation Decisions Targeting Individual, Grouping, or Population Levels

Project	Private	Grouping	Population
Connect Diabetes	Continued arrangement allowed diabetes educators to look at individual patient cocky-monitoring of diet and concrete activity data in a agenda format, daily, weekly average, and monthly options	Current: Diabetes educators can select a subgroup of individuals based on their A1c, for example, and send a letter or email to those with A1c>7. Future: Diabetes educators will be able to transport an email to those who practise not monitor their diet for >seven days or before the visit.	Current: System evaluates and selects a specific parameter (eastward.g., percentage of people with A1c >7) Future: % under dietary target, or % nether certain self-monitored claret glucose levels
ml SMART	A web-based organization to allow the bi-directional flow of information between individuals and the healthcare system through the post-obit modalities: 1) Spider web app personalized reminders for cocky-management (medications, finger sticks, etc.), ii) mHealth sensors send self-monitoring results to the health system 3) Web app provides automated personalized cocky-management feedback 4) Web app provides disquisitional values to provider in real time five) secure messaging or phone phone call feedback from providers for critical values half dozen) Web app/EHR communication to provide active medication listing, diagnosis list, lab results 7) video conferencing for healthcare visits and personalized didactics 8) Web app provides recorded educational videos.	Providers can await at results on cocky-monitoring data from individuals or subgroups of patients.	Futurity: Use predictive analysis to identify trends in data to ameliorate overall population health in West Virginia, Medicare and Medicaid and employees of wellness organisation
NEC-Cypher	Direct CDS at the individual level (clinician taking care of one infant) that includes progress toward NEC-Zero adherence, alerts for non-adherence and NEC early alarm score integration. Displays clinical variables relevant to NEC in a dashboard.	Planned: Group-level adherence to the NEC prevention practices and quality result visualizations. Shows the overall NICU functioning to meet quality drivers and how they marshal with meeting procedure targets.	Electric current: Able to assimilate data for a group of NICUs to provide population level quality measurement for participating NICUs. Hereafter: Apply machine learning to learn from population-level data to heighten early on recognition dashboard.
EnTICE³	Creates tailored visualizations based on individual measures	Individual measures are compared to aggregate measures (due east.g., PROMIS anxiety) or criteria (e.one thousand., CDC fruit and vegetable recommendations) at WICER cohort/community/ZIP lawmaking level depending upon specific measure.	Private measures are aggregated at WICER population level.

Results

Analysis of 4 Instance Studies Using the Modified IROM

An overview of the four cases is presented in Supplemental File ane. Table ane summarizes our analysis of the iv example studies using the iv IROM constructs (customer, context, outcomes, and nursing informatics intervention).

Context

In the original IROM, context is defined equally a complex, multifaceted concept that exists within the cultural, economic, social, and physical environment of the intervention. As information science interventions are heavily influenced by current fundamental policies within the context, nosotros expanded the original definition of context to include policy at both the local and/or national level. This decision was made in light of the enormous touch on local policies take on the ability to implement interventions at the system level. Such policies include the willingness of local systems or clinical partners to implement nursing informatics innovations that are across their technical capacity.

Cultural context.

The cultural context includes the traditional cultural factors in the study settings and specific populations that shaped the iv informatics projects. The cultural context in the iv studies included the burden related to managing multiple chronic conditions, difficulty tracking behavioral goals with paper diaries for diabetes educators, shared conclusion making in the neonatal intensive care unit (NICU), and reporting research results to Latinos with varied levels of health literacy and limited English proficiency.

Economical context.

The economic context includes the fiscal affordability of target users (i.e., patients, providers, or researchers). Funding resources for developing the information science tools played an important role in the economic context every bit well. Connect Diabetes and ml SMART both targeted patients (low-income and others) who endemic mobile devices and providers who were part of a limited pool that had access to the organisation. NEC-Aught considered economical factors that could reduce financial barriers to accessing the informatics organisation. EnTICE³ was used by researchers to create tailored infographics with the initial target population of the visualizations existence primarily Medicare/Medicaid recipients; there were no technology requirements for the recipients. To date, EnTICE³ apply has been funded by grants. Both NEC-Zero and EnTICE^three were primarily funded past federal resources. All of the authors considered economical context with the goal of scaling the intervention in the future.

Social context.

Connect Diabetes and ml SMART aimed to increase patient-provider advice to facilitate patient-centered intendance. The social context of both studies facilitated the connection of patient information from mobile devices to providers. NEC-Cipher aimed for distributed decision making in the NICU, which supports the evolution of its decision back up tool. EnTICEⁱⁱⁱ aimed to meliorate the advice of research results from the researcher to the research participant.

Physical context.

The physical context of the settings included NICUs, specialized diabetes educational activity clinics, and the community. One mutual concrete context was that the application of informatics tools all aimed to support an underserved or vulnerable population.

Policy context.

Policy context both facilitated and limited the scope of the projects. Both Connect Diabetes and ml SMART encountered barriers posed by institutional policies. Neither local system was willing to connect data from mobile devices directly to the EHR. Both healthcare systems cited legal, security, or cost considerations around the fourth dimension of implementation (2013–2015). NEC-Zero was able to capitalize its momentum on the 21st Century Cures and HITECH Acts, prioritizing interoperable CDS and involving CDS experts and clinician groups in designing its tool.

Client

The ANA position argument on nursing information science explicitly states that target user groups of the innovation should back up consumers, patients, and other providers in their decision‐making in all roles and settings. Our iv example studies reflected this wide range of targeted users indicated in the ANA definition. The target population of the four case studies included patients or community residents from various settings; notwithstanding, the targeted users of these proposed systems were clinicians in 2 of the studies, with EnTICE³ focusing on researchers and mlSMART targeting both patients and clinicians.

Informatics Intervention

The original IROM outlines content, construction, menstruum of information, and technology characteristics. We farther outlined the content component to specifically include informatics intervention content for each type of targeted user if in that location were multiple targeted user groups and to characterize the engineering science as proprietary or non-proprietary.

Content.

Connect Diabetes and mlSMART both focused on connecting patient self-monitoring values, nutrition, and physical action to clinicians. While Connect Diabetes focused on diabetes patients, ml SMART focused on individuals with multiple chronic conditions, including diabetes, obesity, hypertension, and depression, who resided in rural areas. Both mlSMART and NEC-Nix gave clinicians easy access to clinical practice guidelines. NEC-Zero's tool focused on CDS in text and dashboard guidance. Patients in the ml SMART trial also receive educational videos prescribed past their clinicians. EnTICE³' input content was participant-generated enquiry data (e.k., BP, BMI, physical activity, fruit and vegetable consumption, Patient-Reported Outcomes Measurement Information System [PROMIS] low score), which were processed and output as tailored infographics.

Structure.

Both the Connect Diabetes and ml SMART projects used a proprietary spider web-based platform. NEC-Zero'south structure is in line with EHR with components simply designed to integrate from outside of the EHR, and EnTICE³'s structure is a standalone module using the Representational State Transfer (RESTful) web service architecture.

Flow of information.

The diabetes educators in the Connect Diabetes written report are receiving information from patients, however, patients are not receiving feedback from the connected arrangement. The tool was adult to support face-to-face or telephone communication betwixt patients and diabetes educators. The ml SMART platform enabled two-style advice through its web-based organization. Participant data are input to EnTICE^three, which processes the data to produce output as tailored infographics.

Technology characteristics.

Three of the four studies used spider web-based platforms, while NEC-Zero, with a focus on implementation and broadcasting, used a service-oriented architecture that overlays the EHR, and separates the data source (EHR) from the CDS engine and dashboard.

Proprietary or non-proprietary:

While EnTICE³ and NEC-Zero were designed every bit open up-source platforms, the information science tools adult in the other two studies are more often than not proprietary. NEC-Zero code is available at Bitbucket.

Outcomes and Evaluation Plan

All four case studies had a component of feasibility/usability/acceptability evaluation to ensure that the developed informatics innovations were perceived to exist usable, adequate, and useful by the respective users and clients. Evaluations for usability, feasibility, acceptability, efficacy and effectiveness are described in Table 1.

Decision Points/Rationale for Different Decisions

While all 4 case studies practical scientific rationale to develop informatics innovations to accost a significant gap in science, dissimilar decisions were made owing to considerations related to intellectual property, technical capacity, and policy constraints (Table ii).

In summary, when in that location is no existing tool or system framework that meets the desired design system, new computer science tools are designed from scratch (mlSMART and EnTICE³). When in that location was an existing tool to meet certain needs, simply there was a lack of part in the existing tool to back up the desired specification, the decision was to expand the existing tool (Connect Diabetes) or develop an engine that will run with the existing tool (NEC-Nix). The ml SMART team developed a web-based system outside the EHR to have the flexibility of two-fashion advice between patients and providers. Connect Diabetes used a third-party intermediary platform to enable the patient to cull from diverse mobile and clothing tools, yet standardized its connection with EHR systems. NEC-Zero focused on implementation and dissemination research, so it is one step ahead in that the SMART on the FHIR app was adult to enable like shooting fish in a barrel integration with any EHR. The other three studies planned to integrate with EHRs in their next steps. Connect Diabetes and EnTICEⁱⁱⁱ focused on usability testing of the adult systems in their studies as the initial focus, while noting the potential to output to the EHR. EnTICE^three was designed to integrate with a variety of applications other than EHRs, including community portals.

In addition to the national and local policy context that impacted decisions, funding support for the evolution of some of these information science tools was primarily from the federal authorities, and this impacted the terminal decision to make the tools open source. ml SMART was developed as a proprietary platform because function of the implementation of the mI SMART arrangement involves the assessment of the workflow of private systems and customization prior to implementation. NEC-Nix's in-line structure can operate within the infirmary's firewall, but the investigators tried to make the component of the CDS engine available in an interoperable way via SMART on FHIR. EnTICE³ is open-source, and Connect Diabetes was limited to a pool of national users with its understanding betwixt the original developer and the American Diabetes Association.

Comparison of Example Studies Working at Individual, Group, and Population Levels

In the original IROM as depicted in Figure 1, three 2-directional arrows connecting the four key constructs indicated that nursing informatics interventions can work at individual, group, and population levels. Data can be collected at the private level and aggregated later on at the group or population level to measure out outcomes or exist part of the informatics intervention to provide CDS. Tabular array 3 highlights the current informatics innovations in the four case studies targeting each of the three levels as well as hereafter and planned information science innovations that can exist built upon existing efforts. All four case studies targeted private level data in the initial trial. An expansion of this word is bachelor in supplementary file 1.

Give-and-take

Our comparative analysis provided insights into the awarding of a comprehensive framework to guide nursing information science research and system development past mapping 4 health informatics instance studies to the modified IROM, which was expanded by calculation policy context. The significance of the IROM lies in its incorporation of the SROM and the SDLC; the former takes into account the care, customer, computer science intervention, and outcomes, and the iterative, unidirectional SDLC allows for the planning, analysis, design, implementation, and maintenance of the health informatics innovation (Effken, 2003). The successful application of the IROM and cross-instance qualitative comparison analysis in this study resulted in the identification of tangible benefits, such equally an examination of dynamic relationships between processes and constructs in nursing informatics interventions and the standardization of the cosmos, implementation, and dissemination of future Striking based on IROM concepts. Our analysis also highlighted scientific rationales and challenges encountered among the 4 instance studies based on the SDLC. These findings facilitated development decisions and examined the trajectory of such decisions co-ordinate to individual, group, and population level needs. The broad applicability of the model enables the consideration of such factors every bit nursing computer science researchers found their own projects in tandem with IROM principles.

Nurses, researchers, and informaticists must prioritize the cultural, economical, social, physical, and policy contexts of nursing informatics technologies for the successful implementation of such projects. Aligning with studies by Effken (2003) and (Brennan & Bakken, 2015), our cantankerous-case qualitative analysis confirmed the contextual footing of health computer science innovations equally an important relationship and a critical component of the IROM that must be taken into consideration during planning, design, and implementation stages. A modified IROM was suggested with the inclusion of policy equally an additional contextual basis, given that informatics interventions are influenced, and often express, past institutional, local, and federal policies on interoperability and meaningful utilize. Taking context into account while evaluating intervention outcomes transforms clinical inquiry into systems-oriented enquiry (Brennan & Bakken, 2015). Our report plant that the inclusion of evaluation in the IROM assures continuous improvement and enables the management of information science innovations toward definite outcomes, such equally desired efficacy and effectiveness. Furthermore, sustained date with target users is maintained by focusing on usability, feasibility, and acceptability as central IROM components. Our findings too support the active identification of the target users, content, construction, menses of data, and applied science characteristics of the nursing informatics intervention. Brewer et al. (2008) noted that the discovery and interrelationships between all these constructs may non apply in private inquiry studies; nonetheless, testing such links signifies mature enquiry processes with supporting data from multiple studies. Appropriately, we found that addressing nigh of these factors allows for uniformity, emphasizes structure, and enables the discovery of new features and limitations that demand to be established among nursing informatics inquiry and interventions.

We also analyzed the application of the iv computer science interventions on individual, grouping, and population level equally it relates to the design of information science interventions in these four projects too as future chapters that tin exist built upon existing infrastructure to expand into the population level. Three of the studies focused on current efforts at an individual level with plans to expand into population health, while ane report started with the population level in mind and provided informatics solutions to accost all levels. Equally nurses play an increasingly important part (Mason, 2016) in primary care and population health, nursing informatics tools should consider group and population level application from the commencement.

Decisions about the time to come evolution and improvement of the interventions were fabricated based on scientific merit, intellectual property, technical capacity considerations, and policy limitations. Scientific rationales addressed current limitations in health education, intendance coordination, and delivery that the interventions proposed to accost. A distinguishing perspective in our cross-case analysis was edifice technical capacity past locating inefficiencies and expanding the functionality of existing tools and system frameworks alongside the development of new systems based on care needs. Secondary awarding integration, specially with EHRs, was of substantial business concern for care coordination. While being enlightened of its potential for integration with EHR our comparative analysis too noted that focusing on EHR integration tended to stall innovative intervention development, especially in the initial planning and design stages. Our research accordingly promotes the need for nursing research to exist informed past multiple data sources that get beyond the confines of the EHR (Brennan & Bakken, 2015; Westra et al., 2017). Policy constraints were centered on enhancing accessibility through open source systems and the scalability of interventions. The structuring of these features helped guide decisions about current private, group, and population level outcomes and will inform time to come innovation development. The National Consortium for Data Scientific discipline (Ahalt, 2014) advocates a data-driven economy that uses digital information to accelerate discovery and improve critical decision-making processes. We thus conceptualized data-driven decisions that focused on augmenting the flow of data betwixt patients and providers, show-based CDS and adherence, efficient information visualization based on provider needs, and statistical means for trend analysis and prediction. In particular, enabling the data flow between patients and providers to address the needs of incorporating patient-generated wellness data into clinical workflow and giving patients access to longitudinal health records requires advancing research agendas on common information fields and standards. Particular attention should exist paid to enhancing usability (Wang J, 2015) and reducing inefficiencies or interruptions to clinical work period and clinician burnout (Shanafelt et al., 2016) related to the use of connected systems to bring more patient-generated health data into clinical intendance.

Our findings also back up the notion that thoughtful considerations in intellectual property strategy in combination with bookish industry collaboration tin can move an information science programme forward. Developing innovation programs and solutions in academic settings and seeking industry collaboration to commercialize or brand the created intellectual property open source are central. The utilise of Minor Business organisation Innovation Research Small Business concern Technology Transfer grants (US Small Business Administration, 2018) every bit a funding mechanism may offer opportunities for such a collaboration and will play a key role in moving projects forward. In addition, these collaborations with small businesses could offering a unique perspective relevant to consumers.

While our study offers perspectives that may be useful to nurse informaticians and others developing and designing technology solutions, our arroyo had a few limitations. The 4 case studies were not selected to correspond the whole spectrum of nursing informatics studies. The authors coalesced around this topic because of our common interests in nursing informatics innovations with a focus on different aspects of interoperability and our insights when working together in a leadership training plan. Thus, these four case studies are not meant to be representative. The IROM was applied to the studies after they were conducted and that assay is portrayed here as an organizing framework to explore similarities and differences across the studies.

Conclusion

Past comparing four computer science innovations that were conducted by unlike nurse scientists and addressed different clinical challenges, this paper demonstrates the utility of applying the IROM across nursing informatics and describes primal development decisions that were driven by policy contexts. As computer science grows and the specialty of nursing informatics expands its attain, nursing scientific discipline volition grapple with more meaningful ways to harness, learn from, study, and apply big data to clinical questions. This paper offers a framework for designing and evaluating such innovations. In the future, nursing informatics volition require less focus on developing for specific brands and devices (due east.g., EHR vendors, stand-alone systems) and will emphasize the need to enable patient engagement and patient autonomy in connected health and care. This will demand to be done in means that maximize interoperability, reduce interruptions in clinical workflow, handle the complication of integrating multiple devices, and address investments in fourth dimension and iterative development to ensure usability and leverage diverse data streams.

Highlights

Within a policy context of national initiatives focused on information science, precision health, and broad technology integration, nursing informatics innovations need to be adaptive.
The design, adaptation, and implementation of informatics innovations tin can exist informed through the lens of the Modified Informatics Research Organizing Model with policy context added.
Informatics evolution decisions were influenced by a combination of scientific, intellectual holding, technical, and policy factors, as well equally commercialization potential and stakeholder needs.
Issues around interoperability, intellectual property, decisions to build a new arrangement or suit an existing organization, and the potential impact of decisions on patient outcomes tin impact design choices for future informatics projects.
Designing to scale to the group and population level in the futurity facilitates broader engineering science integration and long-term dissemination and implementation.

Supplementary Material

1 ii

Acknowledgements

REMOVED FOR BLINDING

Funding:

The Robert Forest Johnson Foundation Nurse Faculty Scholars Plan provided funding support for Wang (71245), Gephart (72114), and Mallow (72119). Bakken served every bit national mentor for Wang and Mallow in the programme. Dr. Gephart is also supported past the Agency for Healthcare Research and Quality (K08HS022908), and an express outreach award from the University of California, Los Angeles, Louise G. Darling Biomedical Library, headquarters for the National Network of Libraries of Medicine, Pacific Southwest Region (NNLM PSR). Dr. Mallow is also supported by National Plant of General Medical NIH/NIGMS Award Number U54GM104942. Dr. Bakken is too supported past the National Plant of Nursing Research (T32NR007969). Wang's study is also supported by Jawbone, Inc. and the John P. McGovern Distinguished Professorship at the Academy of Texas Health Science Middle at Houston Cizik Schoolhouse of Nursing and the Hugh Roy Cullen Professorship at the University of Texas Health Scientific discipline Middle at San Antonio. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality, Robert Forest Johnson Foundation, or NNLM. The views expressed hither do not necessarily reflect those of any of the funding organizations.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. Every bit a service to our customers nosotros are providing this early version of the manuscript. The manuscript volition undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable class. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Supplemental File 1. Clarification of Cases used in Cross-Case Analysis

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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679802/