Process: System Implementation and support
Health care practices based on evidence are currently readily available for a number of health care issues like heart failures, asthma, and diabetes. Unfortunately, these practices do not always get implemented in healthcare delivery, and related practices bounded by the same (Houser & Oman, 2011). Formerly, the main focus of any research dealing with healthcare was to enhance analysis of data in order to identify safety concerns of the patient and to show likelihood of arriving at advanced quality and patient safety.
There is much less attention given to practice implementation. It is important to note that by putting emphasis on the practices studied in research would improve the rate of healthcare. Implementation of EBP safety practices is a difficult task that needs to be strategized in order to manage related complications of care systems, senior leadership, and health care cultural changes to safety practices environment based on evidence (Melnyk & Fineout-Overholt, 2010).
EBP refers to meticulous and sensible employment of present day best evidence in combination with health expertise and patients morals to lead medical care decisions. There are a number of models of EBP in business operation in various medical care environments. Common components of these models include practice topic selection, evidence assessment and synthesis, discharge, assessment of the effect on the patient care and the performance of the medical care provider, and contemplation of platform/context of practice implementation.
Implementation of EBP is a process comprising of many actors and systems, and so it is done in stages. Steps taken in implementation of this system can be viewed from in various perspectives including perspective of those who generate knowledge or carry out research, users of the evidence-based information, and the border spanners to connect those who generate knowledge with those who consume knowledge.
Creation and refinement of knowledge - Refers to carrying out research (prospected outcomes in promptness to use in medical care delivery systems) followed by wrapping pertinent research results into refined products that are promptly consumable; like particular practice suggestions – thereby heightening the probability that the research outcomes may be put into practice.
It is important that the process of knowledge refinement be updated and led by the users of the end product in order for the research outcomes get its way to implementation by healthcare providers in their medical care delivery systems (Malloch & Porter-O'Grady, 2010). Aspects to be included in knowledge refinement process include end users perspective (for example transferability to real-business world of medical care environment, feasibility, amount of evidence required by medical care entities and clinic personnel), as well as consideration of traditional ways of generating knowledge (for example evidence generalizability).
Diffusion and dissemination - This involve collaboration with specialized judgment leaders and medical care entities to distribute knowledge that can structure the basis of action (like basic components for release teaching for patients suffering from heart failures) to prospect users. Dissemination associations connect researchers with mediators that could act as brokers of knowledge and linkages to the medical practitioners and medical care delivery entities. Here intermediaries/mediators can be specialized organizations like National Patient Safety Foundation (NPSF) or teams that deal with knowledge on multiple disciplines like the ones that are effectively disseminate cancer prevention programs based on research. In case of any new knowledge, the dissemination mediators provides authoritative seal and assist in identifying influential entities that can create demand for evidence-based applications in practice (Malloch & Porter-O'Grady, 2010).
End user acceptance, Implementation and institutionalization - This is the last phase of knowledge transfer. It concentrates on getting teams, organizations, and individuals to accept and use the evidence-based outcomes together with innovations in a consistent manner. Implementation and sustaining EBPs in medical care environments involves complicated association among the EBP topic (like minimization of medication uncertainties), the characteristics of the organizational social system (like structures of operation and values, external medical care setting), and the individual clinic personnel (Malloch & Porter-O'Grady, 2010).
Strategies employed in the implementation of the EBP include usage of change champion who can handle prospective issues barring implementation, piloting (changing in parts) and getting assistance from multidisciplinary implementation entities to aid in incorporating the new system into the processes of the organization. The changing practice needs significant amount of effort at both the organizational and personal level to employ information based on evidence and other products in specific setting.
After the improvements in health care system have been revealed in the pilot study and communicate across the entire organization, key executives in the organization may then accept to fully implement and maintain the change in practice.
Opportunities
A study by RAND Health reveals that US Healthcare Information system possibly will save higher than USD81 billion yearly, trim down undesirable medical care events together with improving the quality of care if implemented.
In nutshell, implementation of HIS in clinical setting would help reduce cost (both time and money), informed decision-making, quality healthcare and reduce occurrences of acute sufferings.
Challenges
One of the most critical issues in implementation of HIS is usability. Introduction of HIS into healthcare setting needs considerable amount of redesigning the workflow. Training, time and/or finances are also required for healthcare providers and other staff to get knowledge regarding use of the system.
Leadership is another challenge. There is need for strong leadership in support of HIS in order to successfully implement the system. Local champions understand the benefits and so they are committed to improving quality of care through use of HIS.
Change in the manner in which medical records are taken and kept may lead to change in the organizational composition of the organization and if overlooked may lead to failure.
HIS normally don’t get its way to implementation since they are acquired and deployed into computing systems. Training and tech-support is required so as to equip the health professionals with knowledge on how to use the system.
References
Houser, J., & Oman, K. S. (2011). Evidence-based practice: an implementation guide for healthcare organizations. US: Jones & Bartlett Publishers.
Malloch, K., & Porter-O'Grady, T. (2010). Introduction to Evidence-Based Practice in Nursing and Healthcare. USA: Jones & Bartlett Learning.
Melnyk, B. M., & Fineout-Overholt, E. (2010). Evidence-Based Practice in Nursing & Healthcare: A Guide to Best Practice. New York: Lippincott Williams & Wilkins
People: How Patient Portal will help Patient
Patient Portal project need reasonable planning for it to be successful. Planning needs courage and innovativeness in order to bring together major stakeholders.
Patients portal provide a one-to-one communication between healthcare providers and the patients. Patients are granted access by the providers (using trusted s and passwords) to vital information via the web connection. When the patients log into the system, the can check appointments, check lab outcomes, check scheduled appointments, examine their statements, post request for prescription refill, and complete forms for new intake (Jones & Johns, 2009).
The state of data being transmitted remotely explains the significance of patient portals whereby there are new modes of information exchange with providers, and interventions from non-clinical, remote advocates. These advocates could communicate solely through online channels, corresponding via a portal or PHR. They could communicate with patients on regular intervals. While not replacing medical providers, this support and guidance could help patients stay on track and manage minor questions before they multiply, possibly cutting down the number of office visits. These advocates or clinic personnel could also react to more critical data emerging from patients, and less major medical encounters could also be a possible outcome. For example, a diabetes patient struggling with a spate of low blood sugars episode could receive a message from a remote care provider prior to a severe hypoglycemic episode via the patient portal.
Opportunities
The patients have a chance to fill out forms at home. For patients who don’t have internet connection at their home, they have to visit cyber cafes around which are still to their advantage in terms of cost and tome. The vendors dealing with development of EMR have also built in to the system capability of language translation thus suitable to all patients across the world.
To the Chief Information Officers, empowering of the patients goes along with improvement in care quality, and patients build trust in you. Patients have to be connected so as they can access their health information in real-time. When patients go to be tested in labs, their lab outcomes are sent to them via secure messaging service. For them to access this information, they need to log into their accounts in the patients portal via internet connected computers.
Patient portals have the ability to heighten patients’ concern in their personal care. This can be very helpful especially for people having unceasing conditions like diabetes. Through the same portal, the clinic personnel can easily contact their patients through messaging. The patients get this information at much lower cost, and get information regarding their state of health (Jones & Johns, 2009).
The portal also help to solve the ambiguity that always rises when monitoring the patient health as the medical practitioners are being updated by the patient themselves of any unusual or emergency conditions. For instance in situations where an outpatient is involved, the portal can simulate the virtual inpatient environment due to the feedback functionality implemented in the portal (Skolnik, 2010).
The practice of involving quality Patient Portal enables the patients to upload and store their health electronic records in a central database. The safety of the patient is enhanced since disease management simplified by accompanying reminders, alerts, and condition-specific messages in the system. There is also online education offered to the patients. These health education programs assist the patients to properly understand their health conditions and uphold a desirable lifestyle (Wager, Lee, & Glaser, 2009).
Patient-keyed data can be also mined for trends monitoring. PHR or patient portals could also assist patients monitor own goals that may not help healthcare providers, but still encourage patients to be healthier, such as calorie counts and exercise schedules. The more engaged and well-informed, most likely the healthier the patient will be.
Challenges
The greatest hindrance faced by the health care systems with patient portals is inclined to cultural issues rather than technical problem. The issue of transparency of health records is something not usual for clinic personnel and so it needs to be introduced in bits. Doctors seem to be very reluctant to answer voluminous questions from the patients (Wager, Lee, & Glaser, 2009).
The functionality for “single portal access” in a pool of partners has implication that one patient login to the portal permits accessibility of multiple clinicians, departmental units and other services in entire centers. One patient account need to be linked to one practice but the rising demand for PHRs or portals to be employed in special care and secondary departmental units need not be overlooked.
Another challenge is that not all population is computer literate, and if they are, a few of them have internet at their homes. This acts as a potential barrier to the success of the PHR or patient portals.
References
Jones, J. B., & Johns, T. (2009). Evaluation of an electronic patient portal for chronically ill patients in a rural integrated delivery system. Vietnam: ProQuest.
Skolnik, N. S. (2010). Electronic Medical Records: A Practical Guide for Primary Care. Australia: Springer.
Wager, K. A., Lee, F. W., & Glaser, J. P. (2009). Health Care Information Systems: A Practical Approach for Health Care Management. New York City: John Wiley and Sons
Technology: artificial intelligence in healthcare
Content
As defined earlier in this paper, AI studies to imitate the intelligence of a human being into computing technology. A study by Combi, Shahar and Abu-Hanna (2009) placed the probable of AI technology in healthcare as follows:
Offers a lab for examination, arrangement, depiction and classification of health knowledge.
Brings into existence of new artifacts to support making of decisions in medicine, training and study.
Incorporate activities in health science, computer science, cognitive science and other science disciplines
Gives a discipline rich of content for future specialization in medical science.
The main goal for the intelligent systems that already in operation is to heighten the standards of medical care and offer advanced medical facilities, to cut down cost and to minimize time of administering healthcare services.
Medical Diagnostic Systems based on experience is an interactive system that is accessible over the internet (Combi, Shahar, & Abu-Hanna, 2009). Cases based on reasoning (CBR) have been used to exploit the particular acquaintance of formerly experienced and difficult issues. The users (patients) could use the system to do their own diagnosis instead of making recurrent visits to clinical doctors and medical practitioners so as to expand their awareness in domain samples.
Data mining is the process of sorting through a collection of data for the purpose of identifying patterns and using the patterns to establish relationships. With competition going tighter, organizations are becoming more sensitive to how they handle the patterns they get from the behavior of their clients. These patterns can be used for the benefit of the organization. Many of the decision making process today are based on pattern that is got from the data. Data mining will usually involve the use of complicated tools to get patterns which were hitherto unknown to the organization (Wagner, Lee, & Glaser, 2009).
In medicine, data mining is becoming increasingly popular and essential. The subsistence of fraud and abuse of medical insurance has caused the health care insurers to attempt cut down their losses by using data mining techniques to track the offenders. Another factor causing healthcare institutions to use data mining techniques is vast amount of data resulting from transactions that are complex and voluminous to undergo processing and analysis. Decision making can be facilitated by the same technique by discovering patterns and trends in large amounts in vast volumes of complex data.
There is yet another branch of AI called Fuzzy logic that is dealing with vagueness in facts that imitates human reasoning in deficient/fuzzy data. Fuzzy relational deduction has been employed in health diagnosis and was used with system based on knowledge called Clinaid. This IS handles diagnostic action, treatment suggestions and patient’s administration (Warner, 1997).
Neural Networks isa powerful AI technique that is capable of learning an array of raw facts together with constructs weight matrices to stand for learning models. Neural Networks has been employed in the medical field such as Myocardial Infection, coronary artery, pneumonia and brain ailments.
Opportunities
Early researches in the paradigm of intelligent systems like CASNET, PIP, MYCIN and Internist-I have proved to have potential ability of outperforming the manual practices in the diagnosis process (Shortliffe, 1998).
MYCIN was built to diagnose antimicrobial contaminations and suggest drugs for treating the same. In it are facilities for explanation, facilities for knowledge acquisition, facilities for teaching and facilities for system-building.
CASNET (Causal Association NETworks) is an overall facility for constructing expert information system for diagnosis and disease treatment. Its major work was diagnosis and suggestion of glaucoma treatment.
Present Illness Program (PIP) was built to simulate the manners manifested by an expert nephrologist in noting the past of the patient’s current illness and the prevailing renal disease.
Internist-I focused on the analysis of heuristic means for imposing degree-of-difference diagnostic chore organizations on making of decisions in clinical setup which was internal medicine diagnosis.
The recent application of AI technology in doing complex operations has led to its adoption in the field of surgery. IA has led to development of semi-automatic robots that do perform surgical tasks with heightened efficiency. The only most challenging aspect in robotics is the mimicking of human brainpower and motions of the body. It is important to note that the largest obstacle towards embracing of healthcare robotic surgical systems is elevated capital cost for equipment.
Challenges
A study by Shortlife (2000), revealed three main challenges that hindered effective employment of IA in healthcare delivery systems. These are:
i. The dominating issue in medicine is diagnosis
ii. Clinic personnel are likely to use systems based on knowledge if and only if they perform at an expert level.
iii. Most clinicians tend to use non-interactive (standalone) tools to support decision making.
References
Combi, C., Shahar, Y., & Abu-Hanna, A. (2009). Artificial Intelligence in Medicine. Artificial Intelligence in Medicine: 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Verona, Italy, July 18-22, 2009. Australia: Springer.
Shortliffe, E. H., Fagan, L. M. and Yu, V. L. (2000). The Infectious Diseases Physician and the Internet. In Mandell, G.L., Bennett, J.E. and Dolin, R. (Eds.), Mandell, Douglas, and Bennett's Principles and Practice of Infectious Diseases, Churchill Livingstone, Inc., Pennsylvania, pp. 3258-3263.
Wagner, K. A., Lee, F. W., & Glaser, J. P. (2009). Health Care Information Systems: A Practical Approach for Health Care Management (Second Edition ed.). New York: John Wiley & Sons
Warner, D. (1997). Malaysian Medical Matrix: Telemedicine in the age of the Multimedia Super Coridor. http://www.pulsar.org/febweb/papers/m3web.htm.
