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author:("piper, Eric A")
1.  Detecting pregnancy use of non-hormonal category X medications in electronic medical records 
To determine whether a rule-based algorithm applied to an outpatient electronic medical record (EMR) can identify patients who are pregnant and prescribed medications proved to cause birth defects.
A descriptive study using the University of Pennsylvania Health System outpatient EMR to simulate a prospective algorithm to identify exposures during pregnancy to category X medications, soon enough to intervene and potentially prevent the exposure. A subsequent post-hoc algorithm was also tested, working backwards from pregnancy endpoints, to search for possible exposures that should have been detected.
Category X medications prescribed to pregnant patients.
The alert simulation identified 2201 pregnancies with 16 969 pregnancy months (excluding abortions and ectopic pregnancies). Of these, 30 appeared to have an order for a non-hormone category X medication during pregnancy. However, none of the 30 ‘exposed pregnancies’ were confirmed as true exposures in medical records review. The post-hoc algorithm identified 5841 pregnancies with 64 exposed pregnancies in 52 569 risk months, only one of which was a confirmed case.
Category X medications may indeed be used in pregnancy, although rarely. However, most patients identified by the algorithm as exposed in pregnancy were not truly exposed. Therefore, implementing an electronic warning without evaluation would have inconvenienced prescribers, possibly hurting some patients (leading to non-use of needed drugs), with no benefit. These data demonstrate that computerized physician order entry interventions should be selected and evaluated carefully even before their use, using alert simulations such as that performed here, rather than just taken off the shelf and accepted as credible without formal evaluation.
PMCID: PMC3241158  PMID: 22071529
Category X medications; computerized physician order entry (CPOE); electronic medical records (EMR); electronic warning; improving healthcare workflow and process efficiency; informatics; measuring/improving outcomes in specific conditions and patient subgroups; measuring/improving patient safety and reducing medical errors; medications during pregnancy; monitoring the health of populations; pharmacoepidemiology; statistical computing; violence
2.  Effectiveness of an information technology intervention to improve prophylactic antibacterial use in the postoperative period 
A 2005 report from the Centers for Medicare and Medicaid Services and the Centers for Disease Control Surgical Infection Prevention program indicated that only 41% of prophylactic antibacterials were correctly stopped within 24 h of the end of surgery. Electronic order sets have shown promise as a means of integrating guideline information with electronic order entry systems and facilitating safer, more effective care.
The aim was to study the effectiveness of a computer-based antibacterial order set on increasing the proportion of patients who have antibacterial wound prophylaxis discontinued in the appropriate time frame.
The authors conducted a quasi-experimental interrupted time-series analysis over an 8-month study period with the implementation of a computer-based order system designed to prevent excessive duration of surgical prophylaxis antibacterials.
The primary outcome was the proportion of surgeries with antibacterials discontinued in the appropriate time frame. Additionally, we evaluated the percent of surgeries after implementation of the electronic intervention with chart documentation of infection among surgeries where the prescriber indicated the reason for antibacterial therapy was treatment.
The computer-based order intervention significantly improved the proportion of surgeries with timely discontinuation of antibacterials from 38.8% to 55.7% (p<0.001) in the intervention hospital, while the control hospital remained at 56–57% (p=0.006 for the difference between treated and control hospitals). In surgeries after intervention implementation where a prescriber indicated the reason for antibacterial therapy was treatment, the prevalence of chart documented infection was only 14%.
A computer-based electronic order set intervention increased timely discontinuation of postoperative antibacterials.
PMCID: PMC3116254  PMID: 21262922
3.  Randomized clinical trial of a customized electronic alert requiring an affirmative response compared to a control group receiving a commercial passive CPOE alert: NSAID–warfarin co-prescribing as a test case 
Studies that have looked at the effectiveness of computerized decision support systems to prevent drug–drug interactions have reported modest results because of low response by the providers to the automated alerts.
To evaluate, within an inpatient computerized physician order entry (CPOE) system, the incremental effectiveness of an alert that required a response from the provider, intended as a stronger intervention to prevent concurrent orders of warfarin and non-steroidal anti-inflammatory drugs (NSAIDs).
Randomized clinical trial of 1963 clinicians assigned to either an intervention group receiving a customized electronic alert requiring affirmative response or a control group receiving a commercially available passive alert as part of the CPOE. The study duration was 2 August 2006 to 15 December 2007.
Alert adherence was compared between study groups.
The proportion of desired ordering responses (ie, not reordering the alert-triggering drug after firing) was lower in the intervention group (114/464 (25%) customized alerts issued) than in the control group (154/560 (28%) passive alerts firing). The adjusted OR of inappropriate ordering was 1.22 (95% CI 0.69 to 2.16).
A customized CPOE alert that required a provider response had no effect in reducing concomitant prescribing of NSAIDs and warfarin beyond that of the commercially available passive alert received by the control group. New CPOE alerts cannot be assumed to be effective in improving prescribing, and need evaluation.
PMCID: PMC2995662  PMID: 20595308
Computerized physician order entry (CPOE); drug alert; drug-drug interaction; warfarin; nonsteroidal anti-inflammatory drugs; clinical trial; electronic ordering system; effectiveness; drug prescribing
4.  Recommendations for Clinical Decision Support Deployment: Synthesis of a Roundtable of Medical Directors of Information Systems 
Background: Ample evidence exists that clinical decision support (CDS) can improve clinician performance. Nevertheless, additional evidence demonstrates that clinicians still do not perform adequately in many instances. This suggests an ongoing need for implementation of CDS, in turn prompting development of a roadmap for national action regarding CDS.
Objective: Develop practical advice to aid CDS implementation in order to improve clinician performance. Method: Structured group interview during a roundtable discussion by medical directors of information systems (N = 30), with subsequent review by participants and synthesis.
Results: Participant consensus was that CDS should be comprehensive and should involve techniques such as order sets and facilitated documentation as well as alerts; should be subject to ongoing feedback; and should flow from and be governed by an organization’s clinical goals.
Conclusion: A structured roundtable discussion of clinicians experienced in health information technology can yield practical, consensus advice for implementation of CDS.
PMCID: PMC2655795  PMID: 18693858
5.  Clinical Decision Support in Electronic Prescribing: Recommendations and an Action Plan 
Clinical decision support (CDS) in electronic prescribing (eRx) systems can improve the safety, quality, efficiency, and cost-effectiveness of care. However, at present, these potential benefits have not been fully realized. In this consensus white paper, we set forth recommendations and action plans in three critical domains: (1) advances in system capabilities, including basic and advanced sets of CDS interventions and knowledge, supporting database elements, operational features to improve usability and measure performance, and management and governance structures; (2) uniform standards, vocabularies, and centralized knowledge structures and services that could reduce rework by vendors and care providers, improve dissemination of well-constructed CDS interventions, promote generally applicable research in CDS methods, and accelerate the movement of new medical knowledge from research to practice; and (3) appropriate financial and legal incentives to promote adoption.
PMCID: PMC1174880  PMID: 15802474
6.  Obstacles to answering doctors' questions about patient care with evidence: qualitative study 
BMJ : British Medical Journal  2002;324(7339):710.
To describe the obstacles encountered when attempting to answer doctors' questions with evidence.
Qualitative study.
General practices in Iowa.
9 academic generalist doctors, 14 family doctors, and 2 medical librarians.
Main outcome measure
A taxonomy of obstacles encountered while searching for evidence based answers to doctors' questions.
59 obstacles were encountered and organised according to the five steps in asking and answering questions: recognise a gap in knowledge, formulate a question, search for relevant information, formulate an answer, and use the answer to direct patient care. Six obstacles were considered particularly salient by the investigators and practising doctors: the excessive time required to find information; difficulty modifying the original question, which was often vague and open to interpretation; difficulty selecting an optimal strategy to search for information; failure of a seemingly appropriate resource to cover the topic; uncertainty about how to know when all the relevant evidence has been found so that the search can stop; and inadequate synthesis of multiple bits of evidence into a clinically useful statement.
Many obstacles are encountered when asking and answering questions about how to care for patients. Addressing these obstacles could lead to better patient care by improving clinically oriented information resources.
What is already known on this topicDoctors are encouraged to search for evidence based answers to their questions about patient care but most go unansweredStudies have not defined the obstacles to answering questions in a systematic mannerA comprehensive description of such obstacles has not been presentedWhat this study addsFifty nine obstacles were found while attempting to answer clinical questions with evidence; six were particularly salientThe obstacles were comprehensively described and organised
PMCID: PMC99056  PMID: 11909789
7.  A taxonomy of generic clinical questions: classification study 
BMJ : British Medical Journal  2000;321(7258):429-432.
To develop a taxonomy of doctors' questions about patient care that could be used to help answer such questions.
Use of 295 questions asked by Oregon primary care doctors to modify previously developed taxonomy of 1101 clinical questions asked by Iowa family doctors.
Primary care practices in Iowa and Oregon.
Random samples of 103 Iowa family doctors and 49 Oregon primary care doctors.
Main outcome measures
Consensus among seven investigators on a meaningful taxonomy of generic questions; interrater reliability among 11 individuals who used the taxonomy to classify a random sample of 100 questions: 50 from Iowa and 50 from Oregon.
The revised taxonomy, which comprised 64 generic question types, was used to classify 1396 clinical questions. The three commonest generic types were “What is the drug of choice for condition x?” (150 questions, 11%); “What is the cause of symptom x?” (115 questions, 8%); and “What test is indicated in situation x?” (112 questions, 8%). The mean interrater reliability among 11 coders was moderate (κ=0.53, agreement 55%).
Clinical questions in primary care can be categorised into a limited number of generic types. A moderate degree of interrater reliability was achieved with the taxonomy developed in this study. The taxonomy may enhance our understanding of doctors' information needs and improve our ability to meet those needs.
PMCID: PMC27459  PMID: 10938054

Results 1-7 (7)