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Biomedical subjects

Dean F Sittig

Publications and source records attributed to Dean F Sittig.

At least 19 recordsLinked to original sources
PubMed2006

Types of unintended consequences related to computerized provider order entry.

OBJECTIVE: To identify types of clinical unintended adverse consequences resulting from computerized provider order entry (CPOE) implementation. DESIGN: An expert panel provided initial examples of adverse unintended consequences of CPOE. The authors, using qualitative methods, gathered and analyzed additional examples from five successful CPOE sites. METHODS: Using a card sort method, the authors developed a categorization scheme for the 79 unintended consequences initially identified and then iteratively modified the scheme to categorize 245 additional adverse consequences resulting from fieldwork. Because the focus centered on consequences requiring prevention or remedial action, the authors did not further analyze reported unintended beneficial (positive) consequences. RESULTS: Unintended adverse consequences (UACs) fell into nine major categories (in order of decreasing frequency): 1) more/new work for clinicians; 2) unfavorable workflow issues; 3) never ending system demands; 4) problems related to paper persistence; 5) untoward changes in communication patterns and practices; 6) negative emotions; 7) generation of new kinds of errors; 8) unexpected changes in the power structure; and 9) overdependence on the technology. Clinical decision support features introduced many of these unintended consequences. CONCLUSION: Identifying and understanding the types and in some instances the causes of unintended adverse consequences associated with CPOE will enable system developers and implementers to better manage implementation and maintenance of future CPOE projects.

Communication↗
PubMed2006

Categorizing the unintended sociotechnical consequences of computerized provider order entry.

OBJECTIVE: To describe the kinds of unintended consequences related to the implementation of computerized provider order entry (CPOE) in the outpatient setting. DESIGN: Ethnographic and interview data were collected by an interdisciplinary team over a 7 month period at four clinics. MEASUREMENTS: Instances of unintended consequences were categorized using an expanded Diffusion of Innovations theory framework. RESULTS: The framework was clarified and expanded. There are both desirable and undesirable unintended consequences, and they can be either direct or indirect, but there are also many consequences that are not clearly either desirable or undesirable or may even be both, depending on one's perspective. The undesirable consequences include error and security concerns and issues related to alerts, workflow, ergonomics, interpersonal relations, and reimplementations. CONCLUSION: Consequences of implementing and reimplementing clinical systems are complex. The expanded Diffusion of Innovations theory framework is a useful tool for analyzing such consequences.

Ambulatory Care↗
PubMed2006

The impact of prescribing safety alerts for elderly persons in an electronic medical record: an interrupted time series evaluation.

BACKGROUND: Considerable effort and attention have focused on medication safety in elderly persons; one approach that has been understudied in the outpatient environment is the use of computerized provider order entry with clinical decision support. The objective of this study was to examine the effects of computerized provider order entry with clinical decision support in reducing the use of potentially contraindicated agents in elderly persons. METHODS: With data from a 39-month period of a natural experiment, we evaluated changes in medication dispensing using interrupted time series analysis to estimate changes, controlling for prealert prescribing trends. The setting was a large health maintenance organization in the Pacific Northwest. All adult enrollees of the health plan participated. The intervention was computerized alerts cautioning against using certain medications in elderly persons. The main outcome measure was dispensing per 10,000 members per month. RESULTS: Following the implementation of the drug-specific alerts, a large and persistent reduction (5.1 prescriptions per 10,000, P=.004), a 22% relative decrease from the month before alert implementation, in the exposure of elderly patients to nonpreferred medications was observed. We found no evidence of a decrease in use of nonpreferred agents for nonelderly patients. The reduction seen in use of nonpreferred agents for elderly persons was driven primarily by decreases in dispensing for tertiary tricyclic agents. CONCLUSIONS: We found that alerts in an outpatient electronic medical record aimed at decreasing prescribing of medication use in elderly persons may be an effective method of reducing prescribing of contraindicated medications. The effect of the alerts on patient outcomes is less certain and deserves further investigation.

Adult↗
PubMed2006

Reducing warfarin medication interactions: an interrupted time series evaluation.

BACKGROUND: Computerized decision support reduces medication errors in inpatients, but limited evidence supports its effectiveness in reducing the coprescribing of interacting medications, especially in the outpatient setting. The usefulness of academic detailing to enhance the effectiveness of medication interaction alerts also is uncertain. METHODS: This study used an interrupted time series design. In a health maintenance organization with an electronic medical record, we evaluated the effectiveness of electronic medical record alerts and group academic detailing to reduce the coprescribing of warfarin and interacting medications. Participants were 239 primary care providers at 15 primary care clinics and 9910 patients taking warfarin. All 15 clinics received electronic medical record alerts for the coprescription of warfarin and 5 interacting medications: acetaminophen, nonsteroidal anti-inflammatory medications, fluconazole, metronidazole, and sulfamethoxazole. Seven clinics were randomly assigned to receive group academic detailing. The primary outcome, the interacting prescription rate (ie, the number of coprescriptions of warfarin-interacting medications per 10 000 warfarin users per month), was analyzed with segmented regression models, controlling for preintervention trends. RESULTS: At baseline, nearly a third of patients had an interacting prescription. Coinciding with the alerts, there was an immediate and continued reduction in the warfarin-interacting medication prescription rate (from 3294.0 to 2804.2), resulting in a 14.9% relative reduction (95% confidence interval, -19.5 to -10.2) at 12 months. Group academic detailing did not enhance alert effectiveness. CONCLUSIONS: This study, using a strong and quasi-experimental design in ambulatory care, found that medication interaction alerts modestly reduced the frequency of coprescribing of interacting medications. Additional efforts will be required to further reduce rates of inappropriate prescribing of warfarin with interacting drugs.

Acetaminophen↗
PubMed2006

A survey of factors affecting clinician acceptance of clinical decision support.

BACKGROUND: Real-time clinical decision support (CDS) integrated into clinicians' workflow has the potential to profoundly affect the cost, quality, and safety of health care delivery. Recent reports have identified a surprisingly low acceptance rate for different types of CDS. We hypothesized that factors affecting CDS system acceptance could be categorized as relating to differences in patients, physicians, CDS-type, or environmental characteristics. METHODS: We conducted a survey of all adult primary care physicians (PCPs, n = 225) within our group model Health Maintenance Organization (HMO) to identify factors that affect their acceptance of CDS. We defined clinical decision support broadly as "clinical information" that is either provided to you or accessible by you, from the clinical workstation (e.g., enhanced flow sheet displays, health maintenance reminders, alternative medication suggestions, order sets, alerts, and access to any internet-based information resources). RESULTS: 110 surveys were returned (49%). There were no differences in the age, gender, or years of service between those who returned the survey and the entire adult PCP population. Overall, clinicians stated that the CDS provided "helps them take better care of their patients" (3.6 on scale of 1:Never-5:Always), "is worth the time it takes" (3.5), and "reminds them of something they've forgotten" (3.2). There was no difference in the perceived acceptance rate of alerts based on their type (i.e., cost, safety, health maintenance). When asked about specific patient characteristics that would make the clinicians "more", "equally" or "less" likely to accept alerts: 41% stated that they were more (8% stated "less") likely to accept alerts on elderly patients (> 65 yrs); 38% were more (14% stated less) likely to accept alerts on patients with more than 5 current medications; and 38% were more (20% stated less) likely to accept alerts on patients with more than 5 chronic clinical conditions. Interestingly, 80% said they were less likely to accept alerts when they were behind schedule and 84% of clinicians admitted to being at least 20 minutes behind schedule "some", "most", or "all of the time". CONCLUSION: Even though a majority of our clinical decision support suggestions are not explicitly followed, clinicians feel they are of benefit and would be even more beneficial if they had more time available to address them.

Adult↗
PubMed2006

Potential impact of advanced clinical information technology on cancer care in 2015.

New clinical information technologies now sporadically available will soon be in routine clinical use, bringing many changes to all phases of the cancer care continuum. For example, new technologies such as: (1) The next generation Internet; (2) Real-time clinical decision support systems; (3) Off-line, population-based systems; (4) Large, integrated, individual patient-level phenotypic and genotypic databases with intelligent data mining capabilities; (5) Wireless, invasive and non-invasive physiologic monitoring devices; (6) Natural Language Processing (NLP) systems; and (7) Mathematical models of complex biological systems all have the potential to impact significantly the provision of cancer care throughout its continuum. While new information management and communication techniques and technologies will reduce many of the inefficiencies and inaccuracies of our present systems, there will be an equal, and potentially far more dangerous, set of unintended consequences. Informatics investigators, cancer specialists, and health system administrators must focus on the study of what is working and what is not, as well as, on development and testing of the new clinical information management and communication technologies, if we are to be ready for the future.

Cancer Care Facilities↗
PubMed2005

A draft framework for measuring progress towards the development of a National Health Information Infrastructure.

BACKGROUND: American public policy makers recently established the goal of providing the majority of Americans with electronic health records by 2014. This will require a National Health Information Infrastructure (NHII) that is far more complete than the one that is currently in its formative stage of development. We describe a conceptual framework to help measure progress toward that goal. DISCUSSION: The NHII comprises a set of clusters, such as Regional Health Information Organizations (RHIOs), which, in turn, are composed of smaller clusters and nodes such as private physician practices, individual hospitals, and large academic medical centers. We assess progress in terms of the availability and use of information and communications technology and the resulting effectiveness of these implementations. These three attributes can be studied in a phased approach because the system must be available before it can be used, and it must be used to have an effect. As the NHII expands, it can become a tool for evaluating itself. SUMMARY: The NHII has the potential to transform health care in America--improving health care quality, reducing health care costs, preventing medical errors, improving administrative efficiencies, reducing paperwork, and increasing access to affordable health care. While the President has set an ambitious goal of assuring that most Americans have electronic health records within the next 10 years, a significant question remains "How will we know if we are making progress toward that goal?" Using the definitions for "nodes" and "clusters" developed in this article along with the resulting measurement framework, we believe that we can begin a discussion that will enable us to define and then begin making the kinds of measurements necessary to answer this important question.

Health Policy↗
PubMed2005

Emotional aspects of computer-based provider order entry: a qualitative study.

OBJECTIVES: Computer-based provider order entry (CPOE) systems are implemented to increase both efficiency and accuracy in health care, but these systems often cause a myriad of emotions to arise. This qualitative research investigates the emotions surrounding CPOE implementation and use. METHODS: We performed a secondary analysis of several previously collected qualitative data sets from interviews and observations of over 50 individuals. Three researchers worked in parallel to identify themes that expressed emotional responses to CPOE. We then reviewed and classified these quotes using a validated hierarchical taxonomy of semantically homogeneous terms associated with specific emotions. RESULTS: The implementation and use of CPOE systems provoked examples of positive, negative, and neutral emotions. Negative emotional responses were the most prevalent, by far, in all the observations. CONCLUSION: Designing and implementing CPOE systems is difficult. These systems and the implementation process itself often inspire intense emotions. If designers and implementers fail to recognize that various CPOE features and implementation strategies can increase clinicians' negative emotions, then the systems may fail to become a routine part of the clinical care delivery process. We might alleviate some of these problems by designing positive feedback mechanisms for both the systems and the organizations.

Attitude of Health Personnel↗
PubMed2005

MediClass: A system for detecting and classifying encounter-based clinical events in any electronic medical record.

MediClass is a knowledge-based system that processes both free-text and coded data to automatically detect clinical events in electronic medical records (EMRs). This technology aims to optimize both clinical practice and process control by automatically coding EMR contents regardless of data input method (e.g., dictation, structured templates, typed narrative). We report on the design goals, implemented functionality, generalizability, and current status of the system. MediClass could aid both clinical operations and health services research through enhancing care quality assessment, disease surveillance, and adverse event detection.

Artificial Intelligence↗
PubMed2005

Clinical decision support in electronic prescribing: recommendations and an action plan: report of the joint clinical decision support workgroup.

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.

Decision Support Systems, Clinical↗
PubMed2005

Natural language processing in the electronic medical record: assessing clinician adherence to tobacco treatment guidelines.

BACKGROUND: Comprehensively assessing care quality with electronic medical records (EMRs) is not currently possible because much data reside in clinicians' free-text notes. METHODS: We evaluated the accuracy of MediClass, an automated, rule-based classifier of the EMR that incorporates natural language processing, in assessing whether clinicians: (1) asked if the patient smoked; (2) advised them to stop; (3) assessed their readiness to quit; (4) assisted them in quitting by providing information or medications; and (5) arranged for appropriate follow-up care (i.e., the 5A's of smoking-cessation care). DESIGN: We analyzed 125 medical records of known smokers at each of four HMOs in 2003 and 2004. One trained abstractor at each HMO manually coded all 500 records according to whether or not each of the 5A's of smoking cessation care was addressed during routine outpatient visits. MEASUREMENTS: For each patient's record, we compared the presence or absence of each of the 5A's as assessed by each human coder and by MediClass. We measured the chance-corrected agreement between the human raters and MediClass using the kappa statistic. RESULTS: For "ask" and "assist," agreement among human coders was indistinguishable from agreement between humans and MediClass (p>0.05). For "assess" and "advise," the human coders agreed more with each other than they did with MediClass (p<0.01); however, MediClass performance was sufficient to assess quality in these areas. The frequency of "arrange" was too low to be analyzed. CONCLUSIONS: MediClass performance appears adequate to replace human coders of the 5A's of smoking-cessation care, allowing for automated assessment of clinician adherence to one of the most important, evidence-based guidelines in preventive health care.

Counseling↗
PubMed2005

Adding insight: a qualitative cross-site study of physician order entry.

The research questions, strategies, and results of a 7-year qualitative study of computerized physician order entry implementation (CPOE) at successful sites are reviewed over time. The iterative nature of qualitative inquiry stimulates a consecutive stream of research foci, which, with each iteration, add further insight into the overarching research question. A multidisciplinary team of researchers studied CPOE implementation in four organizations using a multi-method approach to address the question "what are the success factors for implementing CPOE?" Four major themes emerged after studying three sites; ten themes resulted from blending the first results with those from a fourth site; and twelve principles were generated when results of a qualitative analysis of consensus conference transcripts were combined with the field data. The study has produced detailed descriptions of factors related to CPOE success and insight into the implementation process.

Attitude to Computers↗
PubMed2005

Ambulatory computerized physician order entry implementation.

As part of broader effort to identify success factors for implementing computerized physician order entry(CPOE), factors specific to the ambulatory setting were investigated in the field at Kaiser Permanente Northwest. A multidisciplinary team of five qualitative researchers spent seven months at four clinics conducting observations, interviews, and focus groups. The team analyzed the data using a combination of template and grounded theory approaches. The result is a description of fourteen themes, clustered into technology, organizational,personal, and environmental categories. While similar to inpatient study results in many respects,this outpatient CPO investigation generated subtly different themes.

Ambulatory Care Information Systems↗
PubMed2004

How to design computerized alerts to safe prescribing practices.

BACKGROUND: Medication errors and preventable adverse drug events are common, and about half of medication errors occur during medication ordering. This study was designed to develop and evaluate medication safety alerts and processes for educating prescribers about the alerts. METHODS: At Kaiser Permanente Northwest, a group-model health maintenance organization where prescribers have used computerized order entry since 1996, qualitative interviews were conducted with 20 primary care prescribers. RESULTS: Prescribers considered alerts helpful for providing prescribing and preventive health information. More than half the interviewees stated that it would be unwise to let clinicians control or avoid safety alerts. Common frustrations were (1) being delayed by the alert, (2) having difficulty interpreting the alert, and (3) receiving the same alert repeatedly. Most prescribers preferred small-group educational sessions tied to existing meetings and having local physicians conduct education sessions. DISCUSSION: The findings were used to design a strategy for introducing and promoting the interventions, modifying the alert text and tools, and focusing the education on how clinicians could use the alerts effectively.

Attitude of Health Personnel↗
PubMed2004

Adding insight: a qualitative cross-site study of physician order entry.

The research questions, strategies, and results of a six-year qualitative study of computerized physician order entry implementation (CPOE) at successful sites are reviewed over time. The iterative nature of qualitative inquiry stimulates a consecutive stream of research foci which, with each iteration, add further insight into the overarching research question. A multidisciplinary team of researchers studied CPOE implementation in four organizations using a multi-method approach to address the question "what are the success factors for implementing CPOE?" Four major themes emerged after studying three sites; ten themes resulted from blending the first results with those from a fourth site; and twelve principles were generated when results of a qualitative analysis of consensus conference transcripts were combined with the field data. The study has produced detailed descriptions of factors related to CPOE success and insight into the implementation process.

Data Collection↗
PubMed2004

Potential impact of advanced clinical information technology on healthcare in 2015.

Clinical information technologies now sporadically available will soon be in routine clinical use, bringing many changes to healthcare. For example, 1) The next generation Internet; 2) Real-time clinical decision support systems; 3) Off-line, population-based systems; 4) Large, integrated, individual patient-level phenotypic and genotypic databases with intelligent data mining capabilities; 5) Wireless, invasive and non-invasive physiologic monitoring devices; 6) Natural Language Processing (NLP) systems; and 7) Mathematical models of complex biological systems have the potential to impact significantly the future healthcare delivery system. While new information management and communication techniques and technologies will reduce many of the inefficiencies and inaccuracies of our present systems, there will be an equal, and potentially far more dangerous, set of unintended consequences. Informatics investigators and health system administrators must focus on the study of what is working and what is not, as well as, on development and testing of the new clinical information management and communication technologies, if we are to be ready for the future.

Databases as Topic↗