Heather Zumpano Walden University

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• Outline impact of the Patient Care and Affordable Care

Act on Telemedicine (TM)

• Identify barriers to telemedicine (TM) implementation

• Discuss impact on stakeholders

• Overview of TM evolution and origins in radiology

• Details of three studies designed to overcome barriers

• Synthesis and future outlook for TM

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• Enacted new provisions for advancing health

technology

• H. R. 3590-652 declared the Department of

Health and Human services accountable to:

1) Conduct improved research

2) Establish laws and policies

3) Implement TM services

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Poor Research Methodologies 1

Absence of Laws and Policies 2

3 Interstate Patient Care via TM

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Economics principles tell us a monetary value needs to be established on the TM visit in order to make

sound business decisions regarding its highest and best use (Zumpano, 2014).

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• Lack of detailed design methods

• Failure to state the economic approach

• Failure to consider all direct and indirect costs related to TM (Mistry, 2012).

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Establish a comprehensive plan for: Readiness Decision making Assessment…

…of TM services.

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• 20-year lag in medical advancement

• Exorbitant costs for health care

• Long waiting room lines

• Rural patients travel long distances to

see a doctor

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Pacemakers

Glucose monitors

MedicAlert® necklaces

2000’s

IOM Report (2001)

Crossing the

Quality Chasm…

1990’s 2010’s

Online doctor visits

Virtual

Intensive care

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• Transition from analog to digital image capture in late 1990’s and early 2000’s

• Digitally obtained images printed on laser film in early 2000’s

• Picture archiving, communication, and storage (PACS) systems arrived soon after digital imaging

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• Paradigm shift across the industry from

film/light box systems to digital

images/computer monitor systems in

late 2000’s

• Image sharing capabilities among

physicians, surgeons, caregivers,

and patients is now mainstream

method of radiology practice

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Three (3) separate models were identified, which captured

the spectrum of factors impacted by TM

• Maturity model (MM)

• Decision modeling (DM)

• Model for Assessment of Telemedicine (MAST)

All of these studies considered the direct and indirect costs

associated with TM, which was highly recommended in the

literature (Mistry, 2012; Wootton, 2012).

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• Matrix designed for use by the end users

• Maturity models (MMs) allow for measurement, and management of an organization’s maturity levels and readiness to adopt TM

• Enables comprehensive and synergistic workflow planning

• Develop uniformity from one user to the next and from one implementation phase to the next

• Ensures the chosen solution will possess the necessary capabilities for current needs as well as upgrades in the future

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• eHealth readiness instrument

• Layered TM implementation model

• PACS maturity model

• TM process map

• National Health Service (NHS) maturity model

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Definition: The level of knowledge and experience end users, health care

organizations, and the entire industry possess for successful implementation of TM.

Table 1- Low and high level names for eHealth readiness assessment tools

(van Dyk et al., 2012)

Low Level High Level

Core readiness Development and assimilation

Technological readiness Accessibility, dependability, financials, etc.

Learning readiness Adequate resources to support technology training

Societal readiness Inter- and intra- organizational relationships, roles, and responsibilities

Policy readiness Regulatory and executive matters (i. e. licensure, insurance, payments, etc.)

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• Strength: Created an enhanced perspective of the

end users’ levels of knowledge and comfort with

the technology

• Weakness: Do not consider evidence-based

practices, or integrate processes for achieving

them

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Layered TM implementation model: The theory behind this framework is a large project must be broken down into smaller tasks and learned one by one. The order in which Broens et al. (2007) prioritized the implementation is:

1) technology

2) favorable reception

3) finance and administration

4) laws and regulations

National Health Service (NHS) maturity model (NIMM): An IT infrastructure maturity model which can be generalized to any application

• Developed by the NHS Technology Office, several NHS IT Organizations and Atos Healthcare

• van Dyk et al. (2012) used the NIMM as a benchmark for their MM 17 Zumpano, 2014

PACS maturity model (PMM): A maturity model was also used in

the development of PACS infrastructure. Demonstrated

sustainability in teleradiology inspired the researchers to adapt

methodologies from the PMM (van Dyk et al., 2012).

TM process map: The researchers developed a 10-step process

map to illustrate the order of operations, including collecting

data; making a diagnosis; and analyzing patient outcomes. Each

step is critical to the overall success of TM practices (van Dyk et

al., 2012).

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The three dimensions were:

eReadiness categories, maturity

levels, and TM process steps (van

Dyk et al., 2012). In the MM,

eReadiness categories were the

dependent variables and TM

process steps were the

independent variables. Maturity

levels, ranging from one to five,

were measured on the z-axis.

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Problem statement: From an economic standpoint, it has

remained challenging to generalize the practice of TM from the

lab to the real world (Bergmo, 2012; Mistry, 2012; Wootton,

2012). This is because there are so many specialties of medicine

investigating TM; and each one has their own unique attributes.

Definition: Decision modeling is a computer-based technique

that uses a database of existing secondary literature to

simulate an infinite array of scenarios (Bergmo, 2012).

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• Aids in learning the relationships among different variables

• In combines with secondary literature, researchers are able to

increase validity with multiple regressions of existing studies

• Offers a systematic approach to investigating hypotheses in TM

implementation

• Simulations can be constructed to make predictions about items

of interest to health leaders

• Indiscriminate about the sources of data used during analysis

• Useful in service development and expansion to rural areas

• Able to duplicate outcomes from one arena to another

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• The European Commission (EC) strongly advocated for the use

of telemedicine in their health delivery system.

• Their goal was to develop and test an evidence-based model of

a TM system architecture designed to measure and manage TM

health outcomes (Kidholm et al., 2012).

• The EC hired Kidholm et al. (2012) to conduct two workshops

comprised of end users and stakeholders. They were charged

with using their findings from the workshops to develop an

implementation model.

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Results of workshop one: Although the groups agreed to the core model

objectives, they developed three main suggestions.

• Separate assessments at the local, regional, and national levels

• Identified additional considerations not captured by the core

model

• The degree of generalizability of results from research to general

practice

Results of workshop two:

• Lack of an objective statement

• Include outcome measures to illustrate patient benefits

• Consolidated the EC core model from nine domains to three

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As assigned, the researchers used these findings to develop the Model for Assessment of Telemedicine (MAST). The model was comprised of three steps: 1) preceding considerations, 2) multidisciplinary assessment, and 3) assessment of transferability.

Preceding Considerations

Mission statement

Description of reasonable

substitutions

Separate assessments for each domain of authority

(i.e. local, state, federal, etc.)

Assessment of the maturity level of

the TM solution

Multidisciplinary Assessment

Statement of medical issue and

TM application combination in

use

Safety precautions

Measure for addition of value

Survey patients for satisfaction

levels

Conduct economic analyses

Monitor organizational

financial performance

Societal, ethical, and legal

effects

Table 3- Step 2: Multidisciplinary assessment

Table 2- Step 1: Preceding considerations assessment

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Transferability Assessment

Between countries

Different sized organizations

Universal to any medical specialty

In summary, the MAST involved stakeholders at the discovery phase of the research process, to improve upon the core model created by the EC. Hebda and Czar (2009) emphasized the importance of involving everyone from the executives to the end users in the TM project, to increase the organization’s chances of realizing an appealing solution. The model will also be more likely to gain buy-in across the industry (Hebda & Czar, 2009).

Table 4- Step 3: Transferability assessment

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• PPACA (2010) mandated HIT solutions be implemented to improve costs and quality of health services.

• The models examined here were more scientific, rigorous, and objective (Wootton, 2012).

• Future research to study cost-effectiveness of TM versus traditional health delivery (Wootton, 2012).

• Future research should investigate plausibility of QALYs in the standardization of TM costs (Bergmo, 2012).

• Further regressions of the MM, DM, and MAST are needed to test their ability to inform TM project guidelines.

• Understanding the relationships among the factors which influence the success of TM will enable decision makers to measure and manage data.

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