7 steps for developing an effective eHealth strategy

Very few health organizations or geographic regions have a proper strategy for the implementation of eHealth, despite evidence that technology's role in healthcare continues to grow, according to research published this week in the Journal of Internet Medical Research. To that end, a pair of researchers from South Africa and Canada outlined seven steps necessary to the development of an effective eHealth strategy.

"Entities will often emulate or adapt practice from elsewhere," the study's authors said. "While emulation or adaptation is common, these approaches are inappropriate: 'emulation' because solutions and approaches must be context-specific, and 'adaptation' because, although a compromise, it remains suboptimal."

The seven steps, according to the researchers, include:

  1. Gathering evidence to assess your specific situation: As mentioned earlier, approaches to eHealth must be context-specific. According to the study's authors, digging through previous yet relevant reports can help to ensure accuracy, while simultaneously revealing information gaps that need to be addressed. "This evidence gathering and situation assessment step establishes a solid foundation and baseline that is defensible to critics and also provides a preliminary list of areas where an eHealth application may offer a solution," they added.
  2. Conducting a holistic review: Factors beyond health--such as poverty, current economic policy, governance culture and geopolitics--can play a crucial role in how such a plan might succeed, according to the authors. "The goal is to examine the broader socioeconomic, political and environmental context in relation to their impact on health need and to identify available assets, strengths and capacity that might be brought to be on the identified issues," they said.
  3. Differential diagnosis: Even though two patients might present with similar signs and symptoms, that doesn't mean their care should be the same. "Health issues and settings may be similar, but when examined carefully, the real health needs" often times are different, the authors said.
  4. Preliminary prioritization: Triage, in a nutshell, according to the authors. Disease morbidity and mortality often frame how priorities are determined, they said. "The overall goal of this step is to determine priority health needs and their associated characteristics for further review."
  5. Identifying solutions: Expansive thought must be employed during this step, according to the authors. "These solutions need not involve technological intervention and might function at one or more of the practice, process or policy levels," they said.
  6. Considering eHealth solutions: At this stage, seeking the advice of local or external eHealth experts is wise, according to the authors. In addition, as in the prior step, expansive thinking is required. "It is recommended that attention still be focused on the top 20 percent," the researchers said. "E-health solutions may well be feasible for the remaining 80 percent, but if they are not highly prioritized, then funding such initiatives may not be the wisest investment."
  7. Secondary prioritization: During this step, if multiple care options are available, those implementing eHealth should rank the options to determine the best and most cost-effective approach to care delivery. "This is a crucial stage in the eHealth strategy development process, as it sets direction for allocation of resources and commits to a certain path of [information and communications technology] infrastructure development and policy need," the researchers said.

While big data has been a hot topic of the healthcare industry over the past few months, its role--and deployment strategy--in healthcare still remains very much up in the air. At a discussion held at the Health Privacy Summit in Washington, D.C., in June, several panel speakers viewed it as an enigma, with some touting its infinite positive possibilities, but others pointing out its related privacy issues.

A report published by the Institute for Health Technology Transformation in March, however, called evidence-supported decisions key to big data success. "The potential for benefits is predicated on the assumption that the organization/providers are committed to evidence-supported decisions using analytic tools with available information," the report's authors said. "If that commitment has not been made, analytic tools provide little value. … Key to achieving [these goals] is knowing specifically what metrics are necessary to measure progress."

To learn more:
- read the JMIR article

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