https://clinfowiki.org/wiki/api.php?action=feedcontributions&user=Hammoudb&feedformat=atomClinfowiki - User contributions [en]2024-03-28T23:33:00ZUser contributionsMediaWiki 1.22.4https://clinfowiki.org/wiki/index.php/Reasons_provided_by_prescribers_when_overriding_drug-drug_interaction_alertsReasons provided by prescribers when overriding drug-drug interaction alerts2009-11-23T18:33:05Z<p>Hammoudb: </p>
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<div>'''Any J grizzle, pharmD, maysaaH. Mahmood, MS; Yu Ko, MS; John E. Murphy, PharmD. Reasons provided by prescribers when overriding drug-drug interaction alerts; The American Journal of managed care. Vol 13, NO.10.''' <br />
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Preventable adverse drug events comprise a large percentage of reported medical errors. An adverse drug event is defined as “an injury resulting from a medical intervention related to a Drug-drug interaction (DDIs). The risk of DDIs to patient safety is substantial, and the economic burden on the healthcare system that occurs when interaction leads to patient morbidity is significant. <br />
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The prescription medication process could be divided into three phases: the prescription, dispensing and administering and finally monitoring the patient. Communication between the individuals carrying those steps in the prescription process is very important for patient safety. <br />
Studies have shown that physicians and other prescribers fail to recognize between 37% and 47% of clinically meaningful DDIs. A solution for reducing the incidence of DDIs at the prescribing phase is the use of computerized physician order entry (CPOE) system that allows prescribers to enter orders electronically. These systems can provide an immediate alert to a prescriber who is trying to order a medication that interacts with another medication the patient is already receiving. However, it has been shown that physicians frequently override such alerts, with some CPOE systems requiring physicians to enter a reason for this decision. <br />
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This study was conducted to evaluate the DDIs override reasons provided by prescribers using a CPOE system at 6 Veterans affairs medical centers (VAMCs). The objective of the study was to determine the frequency at which physicians override DDI alerts, and to categorize the override reasons and to determine whether the reasons were useful to the pharmacists dispensing the medications. <br />
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Method: <br />
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Data related to prescriber’s reasons for overriding DDI alerts used in the VAMC system were obtained from ambulatory pharmacy dispensing records at 6 VAMC sites. The override reasons were collected over a period of one year from July 1, 2003 to June 30, 2004. The VA classifies 2 levels of severity for DDIs, critical and significant interactions. When a DDI alert message appears, the prescriber could either cancel the order, or override the alert and complete the prescription. It was mandatory for the prescribers to give reasons for critical interaction alerts only. The reasons were entered as free text. Once the provider verifies that an order is desired, the order with override reasons if applicable are sent to the pharmacy to be reviewed and approved. <br />
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The reasons collected were organized into 14 major categories developed by the authors. Each reason was then evaluated and rated as being clinically useful or not to the pharmacist for his/her assessment before dispensing the medication. <br />
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Results: <br />
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A total of 15,848 unique DDI overrides occurred during the first year of study. The DDI override reasons were reviewed, assessed and categorized. It was found that 72% of the DDIs were critical interactions. An override reason was not provided for 53% of these critical DDIs. When override reasons were documented, approximately 43% of those critical DDIs were rated as useful and 50% for significant DDIs were rated as useful. <br />
For significant DDIs, 4% included an override reason, with 50% of those being rated as useful. The 3 most common categories were identified for each of the study sites. There was consistency in that 4 of 6 sites had the same 3 categories (“no reason provided”, “patient has been taking combination”, and “patient being monitored”) in the same order. The other 2 sites shared the same top 3 categories (“no reason provided”, “prescriber aware of interaction” and “patient being monitored”).<br />
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Discussion:<br />
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The reasons for overrides by prescribers at VAMCs in this study were difficult to assess because reasons were not provided 84% of the time. The reason for this might be that the prescribers felt that providing response is an increased burden that could be safely ignored. In addition, prescribers may not view the alert system as a means of communication with the pharmacist but rather as a tool to help in their decision making. Although the response was mandatory for critical DDI overrides in the VAMC system, 53% of these fields were left blank. A possible explanation for a blank field is that the system interprets the space bar or the enter key as a response and essentially allows no response from the prescriber. <br />
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It is clear from this study that additional attention is needed to provide solutions that will improve the prescriber’s ability to communicate with the pharmacist and to ensure optimal patient outcomes with every medication prescribed. <br />
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Comments:<br />
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Using free text fields to enter reasons for overrides in the CPOE system might be the reason behind the lack of communication between the prescriber and the pharmacist. Incorporating preformatted responses and drop-down menus to express clinician’s rationales may enhance communication. More studies are needed to examine the response of the pharmacists to specific override reasons and the clinical outcomes associated with the potential DDI reaching patients. <br />
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Submitted by (Bassima Hammoud)<br />
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[[Category:BMI512-FALL-09]]</div>Hammoudbhttps://clinfowiki.org/wiki/index.php/CDSCDS2008-02-29T17:53:28Z<p>Hammoudb: /* Examples available on the web */</p>
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<div>==Clinical Decision Support -- CDS==<br />
<br />
===Overview===<br />
<br />
Clinical Decision Support (CDS) refers broadly to providing clinicians or patients with clinical knowledge and patient-related information, intelligently filtered or presented at appropriate times, to enhance patient care. Clinical knowledge of interest could range from simple facts and relationships to best practices for managing patients with specific disease states, new medical knowledge from clinical research and other types of information.<br />
<br />
For an overview of the process that healthcare organizations can use to begin, or improve, a clinical decision support (CDS) initiative interested parties can follow the guidelines described in <br />
[http://www.himss.org/ASP/topics_cds_workbook.asp?faid=108&tid=14 Improving Outcomes with Clinical Decision Suppport: An Implementer's Guide] to measurably improve key healthcare outcomes such as the quality, safety, and cost-effectiveness of care delivery.<br />
<br />
*[[National Roadmap for Clinical Decision Support]]<br />
*[[History of decision support]]<br />
*[[General system features associated with improvements in clinical practice]]<br />
*[http://wellness.wikispaces.com/Tactic+-+Support+Decisions+with+Diagnostic+Aids Support Decisions with Diagnostic Aids]<br />
*[[Clinical Decision Support Liability]]<br />
<br />
===[[Modes of Interaction]]===<br />
*[[Interpretation]]<br />
*[[Consultation]]<br />
*[[Monitoring]]<br />
*[[Critiquing]]<br />
*[[Teaching]]<br />
<br />
===[[Order Sets]]===<br />
*[[Personal Order Sets]]<br />
*[[Functional Specifications]]<br />
*[[Criteria for creating new order sets]]<br />
*[[A Process for Creating and Maintaining Order Sets]]<br />
<br />
===[[Information Resources]]===<br />
*[[Alerts and Reminders]]<br />
*[[Alert Fatigue]]?<br />
*[[Alert placement in clinical workflow]]<br />
*[[Initial Selection of What to Alert on...]]<br />
<br />
===Artificial intelligence===<br />
<br />
Artificial intelligence is a system that was developed by a team of system engineers and clinicians. The system would take some of the workload from medical teams by assisting the physicians with tasks like diagnosis & Therapy recommendations. An AI system could be running within electronic medical record system, and alert a clinician when it detects a contraindication to a planned treatment. It could also alert the clinician when it detected patterns in clinical data that suggested significant changes in a patient’s condition.<br />
The definition of artificial intelligence has changed over the years, since 1956 till now. It is mostly found in data rich areas like intensive care settings<br />
There are many different types of clinical task to which Artificial intelligence can be applied.<br />
1. Monitoring patients vital signs and then evaluating and administering the right amounts of different drugs needed<br />
2. Planning an adequate nutritional support for maintaining the metabolic needs of newborn infants. Control of the level of pressure support ventilation.<br />
3. Reading of the electrocardiogram (ECG).<br />
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There are numerous reasons why more expert systems are not in routine use. Some require the existence of an electronic medical record system to supply their data and most institutions do not yet have all their working data available electronically. Much of the difficulty has been the poor way in which they have fitted into clinical practice, which required additional effort from already busy individuals.<br />
<br />
Examples of AI that are still in practice <br />
samrtcare/pc ventilator manager, 2004.<br />
VIE-PNN Neo-natal parentral nutrition 1993. <br />
Examples of decommissioned AI are:<br />
N‘eoGaneshVentilator manager, 1992.<br />
ACORN Coronary care admission ,1987.<br />
By Bassima Hammoud<br />
[[category:BMI-512-W-08]]<br />
<br />
===Business Intelligence and Data Warehousing===<br />
*[[Business Intelligence & Data Warehousing for Healthcare]]<br />
*[[Clinical Data Warehousing]]<br />
<br />
===Medication-Based Safety Rules===<br />
*[[Potentially Inappropriate Medication (PIM) Use in Older Adults:65 years and older (Based on 2000 updated Beers Criteria)]]<br />
**[[List of some PIM use independent of patient conditions and diagnosis (drugs with ADE severity rating of HIGH only)]]<br />
**[[List of some PIM use for patient with specific conditions (drugs with ADE severity rating of HIGH only)]]<br />
*[[Medications to be avoided in the elderly]]<br />
*[[Medications requiring dosage adjustments in renal insufficiency]]<br />
*[[Common Corollary orders]]<br />
*[[Drug-Laboratory Interactions]]<br />
*[[Drug-Drug interaction]]<br />
*[[Drug-Allergy Interactions]]<br />
*[[Detection of Adverse Mediation-Related Events]]<br />
*[[Drug-Food Interactions]]<br />
*[[Drug-Tobacco Interactions]]<br />
*[[Medications requiring dosage adjustments in hepatic disease]]<br />
*[[Medications to be avoided during pregnancy]]<br />
*[[Medications to be avoided while breastfeeding]]<br />
*[[Vaccination contraindications]]<br />
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===Non-Medication-Based Safety Rules===<br />
* [[Diagnosis-Order Rules]]<br />
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===Validation and Verification of Clinical Decision Support===<br />
*[[On Validation and Verification Of Decision Support Protocol Subsystems During Implementation-Optimization: Encapsulating P(X)]]<br />
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===Sample Decision Support Content===<br />
* [[Diabetes CDS Content]]<br />
* [[Drug-Drug Interaction Rules]]</div>Hammoudbhttps://clinfowiki.org/wiki/index.php/Integrating_physician_sign-out_with_the_electronic_medical_recordIntegrating physician sign-out with the electronic medical record2008-02-18T17:34:35Z<p>Hammoudb: </p>
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<div>integrating physician sign-out with the electronic medical record.25. Sarkar U, Carter JT, Omachi TA, Vidyarthi AR, Cucina R, Bokser S, van Eaton E, Blum M. J Hosp Med. 2007 Sep;2(5):336-42<br />
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SynopSISis a tool that is used mainly to compile and organize information from the electronic medical record to support hospital discharge, daily provider decisions and overnight or cross coverage decisions. It reflects the provider’s- patient care and daily work-flow needs. <br />
<br />
2006 National patient safety goals, the joint commission on accreditation of health care organization JCAHO requires that each hospital implement a standardized structured approach to transfers of care.<br />
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Transfers of care have shown to be a source of medical error. Ad hoc systems have been created by providers separate from the chart, designed to track a patient’s progress over time and to facilitate transfers of care. These sign-out systems range in complexity from simple handwritten index cards to adapted spreadsheets, PDA systems. Those ad-hoc systems are not standardized, resulting in content and accuracy that vary among providers. These systems may fail to identify critical elements of a patient condition, promoting ineffective communication and placing the patient at increased risk of adverse events. <br />
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SynopSIS is integrated with hospital’s EMR, it provides an at a glance screen of the patient’s current condition. A problem list is entered by the primary hospital physician. The Anticipated problem/To do list supports the sign-out function from which providers can coordinate care related activities and make contingency plans for anticipated events. This screen is editable by physicians. Data may be removed as their importance lessens or as the patient’s condition changes. Deleted data are saved in the medical record and are viewable by audit. <br />
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A study was conducted in a tertiary university based teaching hospital with 2 campuses at the university of California, San Francisco, Medical Center (UCSFMC), to evaluate synopSIS impact on communication between care teams, quality of sign-out, patient continuity of care and rounding efficiency. <br />
<br />
The study showed that quality of care will improve with synopSIS , providers can assume care of an unfamiliar patient, increase time with patients during rounds and allow more education time for trainees.<br />
Bassima Hammoud<br />
[[category:BMI-512-W-08]]</div>Hammoudbhttps://clinfowiki.org/wiki/index.php/Integrating_physician_sign-out_with_the_electronic_medical_recordIntegrating physician sign-out with the electronic medical record2008-02-18T17:29:29Z<p>Hammoudb: </p>
<hr />
<div><br />
integrating physician sign-out with the electronic medical record.25. Sarkar U, Carter JT, Omachi TA, Vidyarthi AR, Cucina R, Bokser S, van Eaton E, Blum M. J Hosp Med. 2007 Sep;2(5):336-42<br />
<br />
<br />
SynopSISis a tool that is used mainly to compile and organize information from the electronic medical record to support hospital discharge, daily provider decisions and overnight or cross coverage decisions. It reflects the provider’s- patient care and daily work-flow needs. <br />
<br />
2006 National patient safety goals, the joint commission on accreditation of health care organization JCAHO requires that each hospital implement a standardized structured approach to transfers of care.<br />
<br />
Transfers of care have shown to be a source of medical error. Ad hoc systems have been created by providers separate from the chart, designed to track a patient’s progress over time and to facilitate transfers of care. These sign-out systems range in complexity from simple handwritten index cards to adapted spreadsheets, PDA systems. Those ad-hoc systems are not standardized, resulting in content and accuracy that vary among providers. These systems may fail to identify critical elements of a patient condition, promoting ineffective communication and placing the patient at increased risk of adverse events. <br />
<br />
SynopSIS is integrated with hospital’s EMR, it provides an at a glance screen of the patient’s current condition. A problem list is entered by the primary hospital physician. The Anticipated problem/To do list supports the sign-out function from which providers can coordinate care related activities and make contingency plans for anticipated events. This screen is editable by physicians. Data may be removed as their importance lessens or as the patient’s condition changes. Deleted data are saved in the medical record and are viewable by audit. <br />
<br />
A study was conducted in a tertiary university based teaching hospital with 2 campuses at the university of California, San Francisco, Medical Center (UCSFMC), to evaluate synopSIS impact on communication between care teams, quality of sign-out, patient continuity of care and rounding efficiency. <br />
<br />
The study showed that quality of care will improve with synopSIS , providers can assume care of an unfamiliar patient, increase time with patients during rounds and allow more education time for trainees.</div>Hammoudbhttps://clinfowiki.org/wiki/index.php/Medical_laboratory_informaticsMedical laboratory informatics2008-02-02T16:32:12Z<p>Hammoudb: </p>
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<div> <br />
This article is a useful tool to introduce Medical laboratory informatics for new users of LIS or HIS. It starts by providing general information about computing and the different components of the computer. Then the article gives basic information about networking and how it works. The authors briefly mention the importance of the World Wide Web to pathologists as a training and educational tool. An introduction for databases, as the preferred method of storage for a large application like the LIS, is then given.<br />
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Then the authors introduce the main topic of the article which is Lab information system. LIS functions include workflow management, specimen tracking, data entry and reporting, interfacing with other systems, and providing billing information. It could be used for quality assurance. <br />
Then the authors talk about each function in details.<br />
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1.Interface: Most laboratories report results electronically through an interface to an EMR or HIS. A data exchange with other information systems and devices can improve the efficiency and eliminate potential error.<br />
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2.Workflow: LIS supports the workflow in all steps pre-analytic, analytic and post-analytic. Certain areas in the laboratory have specialized LIS needs, Microbiology and histopathology as well as Blood bank. There is a choice within the lab between integrated or separate systems for anatomic pathology, blood bank and clinical pathology.<br />
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3.Rules: LIS can easily perform calculation and execute algorithms or rules. This reduces errors and staff needs. One advantage of LIS in blood bank is the computer assisted cross-match to confirm the compatibility between patient and donor without doing the serologic crossmatch.<br />
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4.Auto-verification: It needs to be performed using middleware, or the LIS. It ensures consistency of applying decision rules across all shifts at all times and it decreases the turnaround time. <br />
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5.Standards: It defines how to encode identifiable data and how to package and communicate this information. Examples of different standards include HL7, XML, and ASTM.<br />
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6.Digital imaging: Image-enhanced reports are a growing trend among pathologists. Telepathology has demonstrated improved accuracy and reproducibility.<br />
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7.Coding: LOINC is one example of a numeric code system aimed at standardizing laboratory and clinical codes. It works within HL7 messages to standardize test names and codes. <br />
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Specialty laboratories, such as molecular diagnostics, cytogenetic, flow cytometry and tissue typing, do not conform to current LIS models. They represent a new challenge for information management in pathology informatics.<br />
By Bassima Hammoud<br />
[[category:BMI-512-W-08]]</div>Hammoudb