Adam Wright
Publications
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3.97Impact points
Development and evaluation of a crowdsourcing methodology for knowledge base construction: identifying relationships between clinical problems and medications.
Journal of the American Medical Informatics Association : JAMIA. 05/2012;
ObjectiveWe describe a novel, crowdsourcing method for generating a knowledge base of problem-medication pairs that takes advantage of manually asserted links between medications and problems.MethodsThrough iterative review, we developed metrics to estimate the appropriateness of manually entered pr... [more] ObjectiveWe describe a novel, crowdsourcing method for generating a knowledge base of problem-medication pairs that takes advantage of manually asserted links between medications and problems.MethodsThrough iterative review, we developed metrics to estimate the appropriateness of manually entered problem-medication links for inclusion in a knowledge base that can be used to infer previously unasserted links between problems and medications.ResultsClinicians manually linked 231 223 medications (55.30% of prescribed medications) to problems within the electronic health record, generating 41 203 distinct problem-medication pairs, although not all were accurate. We developed methods to evaluate the accuracy of the pairs, and after limiting the pairs to those meeting an estimated 95% appropriateness threshold, 11 166 pairs remained. The pairs in the knowledge base accounted for 183 127 total links asserted (76.47% of all links). Retrospective application of the knowledge base linked 68 316 medications not previously linked by a clinician to an indicated problem (36.53% of unlinked medications). Expert review of the combined knowledge base, including inferred and manually linked problem-medication pairs, found a sensitivity of 65.8% and a specificity of 97.9%.ConclusionCrowdsourcing is an effective, inexpensive method for generating a knowledge base of problem-medication pairs that is automatically mapped to local terminologies, up-to-date, and reflective of local prescribing practices and trends.
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2.65Impact points
Use of an Electronic Problem List by Primary Care Providers and Specialists.
Journal of general internal medicine. 03/2012;
BACKGROUND: Accurate patient problem lists are valuable tools for improving the quality of care, enabling clinical decision support, and facilitating research and quality measurement. However, problem lists are frequently inaccurate and out-of-date and use varies widely across providers. OBJECTIVE: ... [more] BACKGROUND: Accurate patient problem lists are valuable tools for improving the quality of care, enabling clinical decision support, and facilitating research and quality measurement. However, problem lists are frequently inaccurate and out-of-date and use varies widely across providers. OBJECTIVE: Our goal was to assess provider use of an electronic problem list and identify differences in usage between medical specialties. DESIGN: Chart review of a random sample of 100,000 patients who had received care in the past two years at a Boston-based academic medical center. PARTICIPANTS: Counts were collected of all notes and problems added for each patient from 1/1/2002 to 4/30/2010. For each entry, the recording provider and the clinic in which the entry was recorded was collected. We used the Healthcare Provider Taxonomy Code Set to categorize each clinic by specialty. MAIN MEASURES: We analyzed the problem list use across specialties, controlling for note volume as a proxy for visits. KEY RESULTS: A total of 2,264,051 notes and 158,105 problems were recorded in the electronic medical record for this population during the study period. Primary care providers added 82.3% of all problems, despite writing only 40.4% of all notes. Of all patients, 49.1% had an assigned primary care provider (PCP) affiliated with the hospital; patients with a PCP had an average of 4.7 documented problems compared to 1.5 problems for patients without a PCP. CONCLUSIONS: Primary care providers were responsible for the majority of problem documentation; surgical and medical specialists and subspecialists recorded a disproportionately small number of problems on the problem list.
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Clinical Summarization Capabilities of Commercially-available and Internally-developed Electronic Health Records.
Applied clinical informatics. 02/2012; 3(1):80-93.
OBJECTIVE: Clinical summarization, the process by which relevant patient information is electronically summarized and presented at the point of care, is of increasing importance given the increasing volume of clinical data in electronic health record systems (EHRs). There is a paucity of research on... [more] OBJECTIVE: Clinical summarization, the process by which relevant patient information is electronically summarized and presented at the point of care, is of increasing importance given the increasing volume of clinical data in electronic health record systems (EHRs). There is a paucity of research on electronic clinical summarization, including the capabilities of currently available EHR systems. METHODS: We compared different aspects of general clinical summary screens used in twelve different EHR systems using a previously described conceptual model: AORTIS (Aggregation, Organization, Reduction, Interpretation and Synthesis). RESULTS: We found a wide variation in the EHRs' summarization capabilities: all systems were capable of simple aggregation and organization of limited clinical content, but only one demonstrated an ability to synthesize information from the data. CONCLUSION: Improvement of the clinical summary screen functionality for currently available EHRs is necessary. Further research should identify strategies and methods for creating easy to use, well-designed clinical summary screens that aggregate, organize and reduce all pertinent patient information as well as provide clinical interpretations and synthesis as required.
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1.90Impact points
Recommended practices for computerized clinical decision support and knowledge management in community settings: a qualitative study.
BMC medical informatics and decision making. 02/2012; 12(1):6.
ABSTRACT: BACKGROUND: The purpose of this study was to identify recommended practices for computerized clinical decision support (CDS) development and implementation and for knowledge management (KM) processes in ambulatory clinics and community hospitals using commercial or locally developed system... [more] ABSTRACT: BACKGROUND: The purpose of this study was to identify recommended practices for computerized clinical decision support (CDS) development and implementation and for knowledge management (KM) processes in ambulatory clinics and community hospitals using commercial or locally developed systems in the U.S. METHODS: Guided by the Multiple Perspectives Framework, the authors conducted ethnographic field studies at two community hospitals and five ambulatory clinic organizations across the U.S. Using a Rapid Assessment Process, a multidisciplinary research team: gathered preliminary assessment data; conducted on-site interviews, observations, and field surveys; analyzed data using both template and grounded methods; and developed universal themes. A panel of experts produced recommended practices. RESULTS: The team identified ten themes related to CDS and KM. These include: 1) workflow; 2) knowledge management; 3) data as a foundation for CDS; 4) user computer interaction; 5) measurement and metrics; 6) governance; 7) translation for collaboration; 8) the meaning of CDS; 9) roles of special, essential people; and 10) communication, training, and support. Experts developed recommendations about each theme. The original Multiple Perspectives framework was modified to make explicit a new theoretical construct, that of Translational Interaction. CONCLUSIONS: These ten themes represent areas that need attention if a clinic or community hospital plans to implement and successfully utilize CDS. In addition, they have implications for workforce education, research, and national-level policy development. The Translational Interaction construct could guide future applied informatics research endeavors.
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2.10Impact points
Preventability of adverse drug events involving multiple drugs using publicly available clinical decision support tools.
American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists. 02/2012; 69(3):221-7.
The results of a retrospective evaluation of the frequency and preventability of adverse drug events (ADEs) involving multiple drugs among hospital inpatients are reported. Data collected in a previous cohort study of 180 actual ADEs and 552 potential ADEs (PADEs) at six community hospitals in Massa... [more] The results of a retrospective evaluation of the frequency and preventability of adverse drug events (ADEs) involving multiple drugs among hospital inpatients are reported. Data collected in a previous cohort study of 180 actual ADEs and 552 potential ADEs (PADEs) at six community hospitals in Massachusetts were analyzed to determine the frequency and types of multiple-drug ADEs and the extent to which the ADEs might have been prevented using publicly available clinical decision-support (CDS) knowledge bases. None of the hospitals had a computerized prescriber-order-entry system at the time of data collection (January 2005-August 2006). A total of 17 ADEs (rate, 1.4 per 100 admissions) and 146 PADEs (rate, 12.2 per 100 admissions) involving multiple drugs were identified. The documented events were related to drug duplication (n = 126), drug-drug interaction (n = 21), additive effects (n = 14), and therapeutic duplication (n = 7) or a combination of those factors. The majority of actual ADEs were due to drug-drug interactions, most commonly involving opioids, benzodiazepines, or cardiac medications; about 75% of the PADEs involved excessive drug doses resulting from order duplication or the prescribing of combination drugs with overlapping ingredients, usually products containing acetaminophen and an opioid. It was determined that 5 (29.4%) of the ADEs and 131 (89.7%) of the PADEs could have been detected through the use of the evaluated CDS tools. A substantial number of actual ADEs and PADEs in the community hospital setting may be preventable through the use of publicly available CDS knowledge bases.
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3.97Impact points
Improving completeness of electronic problem lists through clinical decision support: a randomized, controlled trial.
Journal of the American Medical Informatics Association : JAMIA. 01/2012;
BackgroundAccurate clinical problem lists are critical for patient care, clinical decision support, population reporting, quality improvement, and research. However, problem lists are often incomplete or out of date.ObjectiveTo determine whether a clinical alerting system, which uses inference rules... [more] BackgroundAccurate clinical problem lists are critical for patient care, clinical decision support, population reporting, quality improvement, and research. However, problem lists are often incomplete or out of date.ObjectiveTo determine whether a clinical alerting system, which uses inference rules to notify providers of undocumented problems, improves problem list documentation.Study Design and MethodsInference rules for 17 conditions were constructed and an electronic health record-based intervention was evaluated to improve problem documentation. A cluster randomized trial was conducted of 11 participating clinics affiliated with a large academic medical center, totaling 28 primary care clinical areas, with 14 receiving the intervention and 14 as controls. The intervention was a clinical alert directed to the provider that suggested adding a problem to the electronic problem list based on inference rules. The primary outcome measure was acceptance of the alert. The number of study problems added in each arm as a pre-specified secondary outcome was also assessed. Data were collected during 6-month pre-intervention (11/2009-5/2010) and intervention (5/2010-11/2010) periods.Results17 043 alerts were presented, of which 41.1% were accepted. In the intervention arm, providers documented significantly more study problems (adjusted OR=3.4, p<0.001), with an absolute difference of 6277 additional problems. In the intervention group, 70.4% of all study problems were added via the problem list alerts. Significant increases in problem notation were observed for 13 of 17 conditions.ConclusionProblem inference alerts significantly increase notation of important patient problems in primary care, which in turn has the potential to facilitate quality improvement.Trial RegistrationClinicalTrials.gov: NCT01105923.
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3.97Impact points
Are physicians' perceptions of healthcare quality and practice satisfaction affected by errors associated with electronic health record use?
Journal of the American Medical Informatics Association : JAMIA. 12/2011;
BackgroundElectronic health record (EHR) adoption is a national priority in the USA, and well-designed EHRs have the potential to improve quality and safety. However, physicians are reluctant to implement EHRs due to financial constraints, usability concerns, and apprehension about unintended conseq... [more] BackgroundElectronic health record (EHR) adoption is a national priority in the USA, and well-designed EHRs have the potential to improve quality and safety. However, physicians are reluctant to implement EHRs due to financial constraints, usability concerns, and apprehension about unintended consequences, including the introduction of medical errors related to EHR use. The goal of this study was to characterize and describe physicians' attitudes towards three consequences of EHR implementation: (1) the potential for EHRs to introduce new errors; (2) improvements in healthcare quality; and (3) changes in overall physician satisfaction.MethodsUsing data from a 2007 statewide survey of Massachusetts physicians, we conducted multivariate regression analysis to examine relationships between practice characteristics, perceptions of EHR-related errors, perceptions of healthcare quality, and overall physician satisfaction.Results30% of physicians agreed that EHRs create new opportunities for error, but only 2% believed their EHR has created more errors than it prevented. With respect to perceptions of quality, there was no significant association between perceptions of EHR-associated errors and perceptions of EHR-associated changes in healthcare quality. Finally, physicians who believed that EHRs created new opportunities for error were less likely be satisfied with their practice situation (adjusted OR 0.49, p=0.001).ConclusionsAlmost one third of physicians perceived that EHRs create new opportunities for error. This perception was associated with lower levels of physician satisfaction.
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3.97Impact points
A multi-layered framework for disseminating knowledge for computer-based decision support.
Journal of the American Medical Informatics Association : JAMIA. 11/2011; 18 Suppl 1:i132-9.
There are several challenges in encoding guideline knowledge in a form that is portable to different clinical sites, including the heterogeneity of clinical decision support (CDS) tools, of patient data representations, and of workflows. We have developed a multi-layered knowledge representation fra... [more] There are several challenges in encoding guideline knowledge in a form that is portable to different clinical sites, including the heterogeneity of clinical decision support (CDS) tools, of patient data representations, and of workflows. We have developed a multi-layered knowledge representation framework for structuring guideline recommendations for implementation in a variety of CDS contexts. In this framework, guideline recommendations are increasingly structured through four layers, successively transforming a narrative text recommendation into input for a CDS system. We have used this framework to implement rules for a CDS service based on three guidelines. We also conducted a preliminary evaluation, where we asked CDS experts at four institutions to rate the implementability of six recommendations from the three guidelines. The experience in using the framework and the preliminary evaluation indicate that this approach has promise in creating structured knowledge, to implement in CDS systems, that is usable across organizations.
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4.47Impact points
Risk of thiazide-induced hyponatremia in patients with hypertension.
The American journal of medicine. 11/2011; 124(11):1064-72.
Although hyponatremia is a well-recognized complication of treatment with thiazide diuretics, the risk of thiazide-induced hyponatremia remains uncertain in routine care. We conducted a retrospective cohort study using a multicenter clinical research registry to identify 2613 adult outpatients that ... [more] Although hyponatremia is a well-recognized complication of treatment with thiazide diuretics, the risk of thiazide-induced hyponatremia remains uncertain in routine care. We conducted a retrospective cohort study using a multicenter clinical research registry to identify 2613 adult outpatients that were newly treated for hypertension between January 1, 2000 and December 31, 2005 at 2 teaching hospitals in Boston, Massachusetts, and followed them for up to 10 years. Two hundred twenty patients exposed to ongoing thiazide therapy were compared with 2393 patients who were not exposed. In the exposed group, 66 (30%) developed hyponatremia (sodium ≤130 mmol/L). The adjusted incidence rate of hyponatremia was 140 cases per 1000 person-years for patients treated with thiazides, compared with 87 cases per 1000 person-years in those without thiazides. Patients exposed to thiazides were more likely to develop hyponatremia (adjusted incidence rate ratio, 1.61; 95% confidence interval [CI], 1.15-2.25). There was no significant difference in the risk of hospitalizations associated with hyponatremia (adjusted rate ratio, 1.04; 95% CI, 0.46-2.32) or mortality (adjusted rate ratio, 0.41; 95% CI, 0.12-1.42). The number needed to harm (to result in one excess case of incident hyponatremia in 5 years) was 15.02 (95% CI, 7.88-160.30). Approximately 3 in 10 patients exposed to thiazides who continue to take them develop hyponatremia.
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2.65Impact points
Randomized controlled trial of health maintenance reminders provided directly to patients through an electronic PHR.
Journal of general internal medicine. 09/2011; 27(1):85-92.
Provider and patient reminders can be effective in increasing rates of preventive screenings and vaccinations. However, the effect of patient-directed electronic reminders is understudied. To determine whether providing reminders directly to patients via an electronic Personal Health Record (PHR) im... [more] Provider and patient reminders can be effective in increasing rates of preventive screenings and vaccinations. However, the effect of patient-directed electronic reminders is understudied. To determine whether providing reminders directly to patients via an electronic Personal Health Record (PHR) improved adherence to care recommendations. We conducted a cluster randomized trial without blinding from 2005 to 2007 at 11 primary care practices in the Partners HealthCare system. A total of 21,533 patients with access to a PHR were invited to the study, and 3,979 (18.5%) consented to enroll. Patients in the intervention arm received health maintenance (HM) reminders via a secure PHR "eJournal," which allowed them to review and update HM and family history information. Patients in the active control arm received access to an eJournal that allowed them to input and review information related to medications, allergies and diabetes management. The primary outcome measure was adherence to guideline-based care recommendations. Intention-to-treat analysis showed that patients in the intervention arm were significantly more likely to receive mammography (48.6% vs 29.5%, p = 0.006) and influenza vaccinations (22.0% vs 14.0%, p = 0.018). No significant improvement was observed in rates of other screenings. Although Pap smear completion rates were higher in the intervention arm (41.0% vs 10.4%, p < 0.001), this finding was no longer significant after excluding women's health clinics. Additional on-treatment analysis showed significant increases in mammography (p = 0.019) and influenza vaccination (p = 0.015) for intervention arm patients who opened an eJournal compared to control arm patients, but no differences for any measure among patients who did not open an eJournal. Providing patients with HM reminders via a PHR may be effective in improving some elements of preventive care.
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3.97Impact points
A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record.
Journal of the American Medical Informatics Association : JAMIA. 05/2011; 18(6):859-67.
Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often ... [more] Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100,000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100,000 records to assess its accuracy. Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100,000 randomly selected patients showed high sensitivity (range: 62.8-100.0%) and positive predictive value (range: 79.8-99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts.
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3.97Impact points
Clinical decision support in small community practice settings: a case study.
Journal of the American Medical Informatics Association : JAMIA. 04/2011; 18(6):879-82.
Using an eight-dimensional model for studying socio-technical systems, a multidisciplinary team of investigators identified barriers and facilitators to clinical decision support (CDS) implementation in a community setting, the Mid-Valley Independent Physicians Association in the Salem, Oregon area.... [more] Using an eight-dimensional model for studying socio-technical systems, a multidisciplinary team of investigators identified barriers and facilitators to clinical decision support (CDS) implementation in a community setting, the Mid-Valley Independent Physicians Association in the Salem, Oregon area. The team used the Rapid Assessment Process, which included nine formal interviews with CDS stakeholders, and observation of 27 clinicians. The research team, which has studied 21 healthcare sites of various sizes over the past 12 years, believes this site is an excellent example of an organization which is using a commercially available electronic-health-record system with CDS well. The eight-dimensional model proved useful as an organizing structure for the evaluation.
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3.97Impact points
Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems.
Journal of the American Medical Informatics Association : JAMIA. 03/2011; 18(3):232-42.
Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems. To d... [more] Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems. To develop and validate a taxonomy of front-end CDS tools and to assess support for these tools in major commercial and internally developed EHRs. We used a modified Delphi approach with a panel of 11 decision support experts to develop a taxonomy of 53 front-end CDS tools. Based on this taxonomy, a survey on CDS tools was sent to a purposive sample of commercial EHR vendors (n=9) and leading healthcare institutions with internally developed state-of-the-art EHRs (n=4). Responses were received from all healthcare institutions and 7 of 9 EHR vendors (response rate: 85%). All 53 types of CDS tools identified in the taxonomy were found in at least one surveyed EHR system, but only 8 functions were present in all EHRs. Medication dosing support and order facilitators were the most commonly available classes of decision support, while expert systems (eg, diagnostic decision support, ventilator management suggestions) were the least common. We developed and validated a comprehensive taxonomy of front-end CDS tools. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of clinical decision support content.
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2.43Impact points
Summarization of clinical information: a conceptual model.
Journal of biomedical informatics. 03/2011; 44(4):688-99.
To provide high-quality and safe care, clinicians must be able to optimally collect, distill, and interpret patient information. Despite advances in text summarization, only limited research exists on clinical summarization, the complex and heterogeneous process of gathering, organizing and presenti... [more] To provide high-quality and safe care, clinicians must be able to optimally collect, distill, and interpret patient information. Despite advances in text summarization, only limited research exists on clinical summarization, the complex and heterogeneous process of gathering, organizing and presenting patient data in various forms. To develop a conceptual model for describing and understanding clinical summarization in both computer-independent and computer-supported clinical tasks. Based on extensive literature review and clinical input, we developed a conceptual model of clinical summarization to lay the foundation for future research on clinician workflow and automated summarization using electronic health records (EHRs). Our model identifies five distinct stages of clinical summarization: (1) Aggregation, (2) Organization, (3) Reduction and/or Transformation, (4) Interpretation and (5) Synthesis (AORTIS). The AORTIS model describes the creation of complex, task-specific clinical summaries and provides a framework for clinical workflow analysis and directed research on test results review, clinical documentation and medical decision-making. We describe a hypothetical case study to illustrate the application of this model in the primary care setting. Both practicing physicians and clinical informaticians need a structured method of developing, studying and evaluating clinical summaries in support of a wide range of clinical tasks. Our proposed model of clinical summarization provides a potential pathway to advance knowledge in this area and highlights directions for further research.
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1.90Impact points
Comparison of clinical knowledge management capabilities of commercially-available and leading internally-developed electronic health records.
BMC medical informatics and decision making. 02/2011; 11:13.
We have carried out an extensive qualitative research program focused on the barriers and facilitators to successful adoption and use of various features of advanced, state-of-the-art electronic health records (EHRs) within large, academic, teaching facilities with long-standing EHR research and dev... [more] We have carried out an extensive qualitative research program focused on the barriers and facilitators to successful adoption and use of various features of advanced, state-of-the-art electronic health records (EHRs) within large, academic, teaching facilities with long-standing EHR research and development programs. We have recently begun investigating smaller, community hospitals and out-patient clinics that rely on commercially-available EHRs. We sought to assess whether the current generation of commercially-available EHRs are capable of providing the clinical knowledge management features, functions, tools, and techniques required to deliver and maintain the clinical decision support (CDS) interventions required to support the recently defined "meaningful use" criteria. We developed and fielded a 17-question survey to representatives from nine commercially available EHR vendors and four leading internally developed EHRs. The first part of the survey asked basic questions about the vendor's EHR. The second part asked specifically about the CDS-related system tools and capabilities that each vendor provides. The final section asked about clinical content. All of the vendors and institutions have multiple modules capable of providing clinical decision support interventions to clinicians. The majority of the systems were capable of performing almost all of the key knowledge management functions we identified. If these well-designed commercially-available systems are coupled with the other key socio-technical concepts required for safe and effective EHR implementation and use, and organizations have access to implementable clinical knowledge, we expect that the transformation of the healthcare enterprise that so many have predicted, is achievable using commercially-available, state-of-the-art EHRs.
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Leveraging electronic health records to support chronic disease management: the need for temporal data views.
Informatics in primary care. 01/2011; 19(2):65-74.
The ageing population worldwide is increasingly acquiring multiple chronic diseases. The complex management of chronic diseases could be improved with electronic health records (EHRs) tailored to chronic disease care, but most EHRs in use today do not adequately support longitudinal data management.... [more] The ageing population worldwide is increasingly acquiring multiple chronic diseases. The complex management of chronic diseases could be improved with electronic health records (EHRs) tailored to chronic disease care, but most EHRs in use today do not adequately support longitudinal data management. A key aspect of chronic disease management is that it takes place over long periods, but the way that most EHRs display longitudinal data makes it difficult to trend changes over time and slows providers as they review each patient's unique course. We present five clinical scenarios illustrating longitudinal data needs in complex chronic disease management. These scenarios may function as example cases for software development. OUTPUTS: For each scenario, we describe and illustrate improvements in temporal data views. Two potential solutions are visualisation for numerical data and disease-oriented text summaries for non-numerical data. We believe that development and widespread implementation of improved temporal data views in EHRs will improve the efficiency and quality of chronic disease management in primary care.
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1.90Impact points
Clinician attitudes toward and use of electronic problem lists: a thematic analysis.
BMC medical informatics and decision making. 01/2011; 11:36.
The clinical problem list is an important tool for clinical decision making, quality measurement and clinical decision support; however, problem lists are often incomplete and provider attitudes towards the problem list are poorly understood. An ethnographic study of healthcare providers conducted f... [more] The clinical problem list is an important tool for clinical decision making, quality measurement and clinical decision support; however, problem lists are often incomplete and provider attitudes towards the problem list are poorly understood. An ethnographic study of healthcare providers conducted from April 2009 to January 2010 was carried out among academic and community outpatient medical practices in the Greater Boston area across a wide range of medical and surgical specialties. Attitudes towards the problem list were then analyzed using grounded theory methods. Attitudes were variable, and dimensions of variations fit into nine themes: workflow, ownership and responsibility, relevance, uses, content, presentation, accuracy, alternatives, support/education and one cross-cutting theme of culture. Significant variation was observed in clinician attitudes towards and use of the electronic patient problem list. Clearer guidance and best practices for problem list utilization are needed.
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3.97Impact points
Governance for clinical decision support: case studies and recommended practices from leading institutions.
Journal of the American Medical Informatics Association : JAMIA. 01/2011; 18(2):187-94.
Clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety; however, effective implementation of CDS requires effective clinical and technical governance structures. The authors sought to determine the range and variety of these governance structu... [more] Clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety; however, effective implementation of CDS requires effective clinical and technical governance structures. The authors sought to determine the range and variety of these governance structures and identify a set of recommended practices through observational study. Three site visits were conducted at institutions across the USA to learn about CDS capabilities and processes from clinical, technical, and organizational perspectives. Based on the results of these visits, written questionnaires were sent to the three institutions visited and two additional sites. Together, these five organizations encompass a variety of academic and community hospitals as well as small and large ambulatory practices. These organizations use both commercially available and internally developed clinical information systems. Characteristics of clinical information systems and CDS systems used at each site as well as governance structures and content management approaches were identified through extensive field interviews and follow-up surveys. Six recommended practices were identified in the area of governance, and four were identified in the area of content management. Key similarities and differences between the organizations studied were also highlighted. Each of the five sites studied contributed to the recommended practices presented in this paper for CDS governance. Since these strategies appear to be useful at a diverse range of institutions, they should be considered by any future implementers of decision support.
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Comparative analysis of the VA/Kaiser and NLM CORE problem subsets: an empirical study based on problem frequency.
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 01/2011; 2011:1532-40.
The problem list is a critical component of the electronic medical record, with implications for clinical care, provider communication, clinical decision support, quality measurement and research. However, many of its benefits depend on the use of coded terminologies. Two standard terminologies (ICD... [more] The problem list is a critical component of the electronic medical record, with implications for clinical care, provider communication, clinical decision support, quality measurement and research. However, many of its benefits depend on the use of coded terminologies. Two standard terminologies (ICD-9 and SNOMED-CT) are available for problem documentation, and two SNOMED-CT subsets (VA/KP and CORE) are available for SNOMED-CT users. We set out to examine these subsets, characterize their overlap and measure their coverage. We applied the subsets to a random sample of 100,000 records from Brigham and Women's Hospital to determine the proportion of problems covered. Though CORE is smaller (5,814 terms vs. 17,761 terms for VA/KP), 94.8% of coded problem entries from BWH were in the CORE subset, while only 84.0% of entries had matches in VA/KP (p<0.001). Though both subsets had reasonable coverage, CORE was superior in our sample, and had fewer clinically significant gaps.
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A prototype knowledge base and SMART app to facilitate organization of patient medications by clinical problems.
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 01/2011; 2011:888-94.
Increasing use of electronic health records requires comprehensive patient-centered views of clinical data. We describe a prototype knowledge base and SMART app that facilitates organization of patient medications by clinical problems, comprising a preliminary step in building such patient-centered ... [more] Increasing use of electronic health records requires comprehensive patient-centered views of clinical data. We describe a prototype knowledge base and SMART app that facilitates organization of patient medications by clinical problems, comprising a preliminary step in building such patient-centered views. The knowledge base includes 7,164,444 distinct problem-medication links, generated from RxNorm, SNOMED CT, and NDF-RT within the UMLS Metathesaurus. In an evaluation of the knowledge base applied to 5000 de-identified patient records, 22.4% of medications linked to an entry in the patient's active problem list, compared to 32.6% of medications manually linked by providers; 46.5% of total links were unique to the knowledge base, not added by providers. Expert review of a random patient subset estimated a sensitivity of 37.1% and specificity of 98.9%. The SMART API successfully utilized the knowledge base to generate problem-medication links for test patients. Future work is necessary to improve knowledge base sensitivity and efficiency.
Following (32)
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Carmit Mcmullen
Kaiser Permanente Center for Health Research -
Dean F Sittig
The University of Texas Health Science Center at Houston -
Philip B Mitchell
University of New South Wales -
Francis J Mcmahon
National Institutes of Health -
Erin Smith
University of California at San Diego
