Clinical decision support / Knowledge-powered tools

Why clinical technology must be knowledge-powered

February 8, 2016

With medical research advancing more rapidly than ever, there needs to be an increased effort to bring that knowledge where it’s needed most, at the point of care. The future of health care requires digital tools that have integrated evidenced-based content, can be quickly and easily implemented into workflows, and yield valuable data that would further research and quality improvement efforts.

Addressing the Evidence-Practice Gap

With billions of dollars invested annually in clinical and biomedical research, a greater push is required to translate that wealth of generated knowledge and disseminate it where it counts most—at the point of care. Studies identify a 17-year gap from the bench to the bedside1. This evidence-practice gap could prove detrimental for patients. According to one American study, patients are only receiving up to 55% of care recommended by latest research2. Furthermore, approximately 20% to 30% of patients are receiving care that is not even required, and could potentially be harmful3. These disparities expose health systems to unnecessary expenditures and strain already limited financial resources and personnel.

Develop digital solutions with integrated clinical content

With the continual rise in adoption and usage of Electronic Medical Records (EMRs), digital health has certainly been at the top of health care administrators’ minds. Studies show that 77% of Canadian family physicians now use EMRs for their practice4, and 63% of nurses enter and retrieve notes electronically5. However, digital health must begin evaluating and improving itself. Simply entering the digital sphere isn’t enough. In order to keep up with the increasing demands of the sector, digital tools need to work smarter. Maximizing the utility of digital tools by building them with evidence-based clinical content integrated into their infrastructure is the next step towards optimizing patient outcomes.

Many institutions have now begun implementing digital order sets into their clinical workflow. Building order sets with leading clinical content, and organizing them in a structured, modular way provides decision support for clinicians and other health care professionals. By standardizing and digitizing the ordering process, clinicians are able to spend more time caring for patients, and can be assured that they are delivering care based on the latest clinical evidence.

Leveraging data for quality improvement

With evidence-based data being utilized to build clinical tools, it’s imperative that those same tools contain additional functionalities that can be further leveraged to benefit health systems and clinicians. Monitoring and tracking detailed analytics such as clinician ordering behaviours, usage frequency, and patient health outcomes helps to inform administrators about which initiatives and tools are actually useful to their institution, as well as where adjustments and improvements can be made. This data output will be especially beneficial as most health care systems move towards an Activity-Based Funding (ABF) model that is determined by patient-outcomes data.

Deploying more elaborate, sophisticated solutions which have built-in evidence-based research input and output components will support future medical and health care research efforts. Novel research developments and knowledge is needed by clinicians as it happens, not 17 years later. Digital clinical tools must be the conduit through which those transactions are made—swiftly, economically, and efficiently.

Notes

  1. Balas, EA, Boren, SA. Yearbook of Medical Informatics: Managing Clinical Knowledge for Health Care Improvement. Stuttgart, Germany: Schattauer Verlagsgesellschaft mbH; 2000. pp 65-70.
  2. Asch SM, Adams J, Keesey J, Hicks J, DeCristofaro A, Kerr EA: The quality of health care deliver to adults in the United States. N Engl J Med 2003, 348:2635-2645.
  3. Schuster MA, McGlynn EA, Brook RH: How good is the quality of health care in the United States? 1998. Milbank Q 2005, 83:843-895.
  4. Canada Health Infoway. National Physician Survey (2014, December 3). Retrieved from https://www.infoway-inforoute.ca/en/component/edocman/resources/reports/clinical-adoption/2163-2014-national-physicians-survey
  5. Canada Health Infoway. National Survey of Canadian Nurses: Use of Digital Health Technologies in Practice (2014, June 25). Retrieved from https://www.infoway-inforoute.ca/en/component/edocman/resources/reports/clinical-adoption/1913-national-survey-of-canadian-nurses-use-of-digital-health-technologies-in-practice
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