197 research outputs found
The frequency of missed test results and associated treatment delays in a highly computerized health system
<p>Abstract</p> <p>Background:</p> <p>Diagnostic errors associated with the failure to follow up on abnormal diagnostic studies ("missed results") are a potential cause of treatment delay and a threat to patient safety. Few data exist concerning the frequency of missed results and associated treatment delays within the Veterans Health Administration (VA).</p> <p>Objective:</p> <p>The primary objective of the current study was to assess the frequency of missed results and resulting treatment delays encountered by primary care providers in VA clinics.</p> <p>Methods:</p> <p>An anonymous on-line survey of primary care providers was conducted as part of the health systems ongoing quality improvement programs. We collected information from providers concerning their clinical effort (e.g., number of clinic sessions, number of patient visits per session), number of patients with missed abnormal test results, and the number and types of treatment delays providers encountered during the two week period prior to administration of our survey.</p> <p>Results:</p> <p>The survey was completed by 106 out of 198 providers (54 percent response rate). Respondents saw and average of 86 patients per 2 week period. Providers encountered 64 patients with missed results during the two week period leading up to the study and 52 patients with treatment delays. The most common missed results included imaging studies (29 percent), clinical laboratory (22 percent), anatomic pathology (9 percent), and other (40 percent). The most common diagnostic delays were cancer (34 percent), endocrine problems (26 percent), cardiac problems (16 percent), and others (24 percent).</p> <p>Conclusion:</p> <p>Missed results leading to clinically important treatment delays are an important and likely underappreciated source of diagnostic error.</p
Understanding the management of electronic test result notifications in the outpatient setting
<p>Abstract</p> <p>Background</p> <p>Notifying clinicians about abnormal test results through electronic health record (EHR) -based "alert" notifications may not always lead to timely follow-up of patients. We sought to understand barriers, facilitators, and potential interventions for safe and effective management of abnormal test result delivery via electronic alerts.</p> <p>Methods</p> <p>We conducted a qualitative study consisting of six 6-8 member focus groups (N = 44) at two large, geographically dispersed Veterans Affairs facilities. Participants included full-time primary care providers, and personnel representing diagnostic services (radiology, laboratory) and information technology. We asked participants to discuss barriers, facilitators, and suggestions for improving timely management and follow-up of abnormal test result notifications and encouraged them to consider technological issues, as well as broader, human-factor-related aspects of EHR use such as organizational, personnel, and workflow.</p> <p>Results</p> <p>Providers reported receiving a large number of alerts containing information unrelated to abnormal test results, many of which were believed to be unnecessary. Some providers also reported lacking proficiency in use of certain EHR features that would enable them to manage alerts more efficiently. Suggestions for improvement included improving display and tracking processes for critical alerts in the EHR, redesigning clinical workflow, and streamlining policies and procedures related to test result notification.</p> <p>Conclusion</p> <p>Providers perceive several challenges for fail-safe electronic communication and tracking of abnormal test results. A multi-dimensional approach that addresses technology as well as the many non-technological factors we elicited is essential to design interventions to reduce missed test results in EHRs.</p
Improving healthcare delivery with new interactive visualization methods
Over the last years, the implementation and evolution of computer resources in hospital institutions has been improving both the financial and temporal efficiency of clinical processes, as well as the security in the transmission and maintenance of their data, also ensuring the reduction of clinical risk. Diagnosis, treatment and prevention of human illness are some of the most information-intensive of all intellectual tasks. Health providers often do not have or cannot find the information they need to respond quickly and appropriately to patient’s medical problems. Failure to review and follow up on patient’s test results in a timely manner, for example, represents a patient’s safety and malpractice concern. Therefore, it was sought to identify problems in a medical exams results management system and possible ways to improve this system in order to reduce both clinical risks and hospital costs. In this sense, a new medical exams visualization platform (AIDA-MCDT) was developed, specifically in the Hospital Center of Porto (CHP), with several new functionalities in order to make this process faster, intuitive and efficient, always guaranteeing the confidentiality and protection of patients’ personal data and significantly improving the usability of the system, leading to a better health care delivery.FCT - Fundação para a Ciência e a Tecnologia (UID/CEC/00319/2019
Patient- and system-related barriers for the earlier diagnosis of colorectal cancer
<p>Abstract</p> <p>Background</p> <p>A cohort of colorectal cancer (CRC) patients represents an opportunity to study missed opportunities for earlier diagnosis. Primary objective: To study the epidemiology of diagnostic delays and failures to offer/complete CRC screening. Secondary objective: To identify system- and patient-related factors that may contribute to diagnostic delays or failures to offer/complete CRC screening.</p> <p>Methods</p> <p>Setting: Rural Veterans Administration (VA) Healthcare system. Participants: CRC cases diagnosed within the VA between 1/1/2000 and 3/1/2007. Data sources: progress notes, orders, and pathology, laboratory, and imaging results obtained between 1/1/1995 and 12/31/2007. Completed CRC screening was defined as a fecal occult blood test or flexible sigmoidoscopy (both within five years), or colonoscopy (within 10 years); delayed diagnosis was defined as a gap of more than six months between an abnormal test result and evidence of clinician response. A summary abstract of the antecedent clinical care for each patient was created by a certified gastroenterologist (GI), who jointly reviewed and coded the abstracts with a general internist (TW).</p> <p>Results</p> <p>The study population consisted of 150 CRC cases that met the inclusion criteria. The mean age was 69.04 (range 35-91); 99 (66%) were diagnosed due to symptoms; 61 cases (46%) had delays associated with system factors; of them, 57 (38% of the total) had delayed responses to abnormal findings. Fifteen of the cases (10%) had prompt symptom evaluations but received no CRC screening; no patient factors were identified as potentially contributing to the failure to screen/offer to screen. In total, 97 (65%) of the cases had missed opportunities for early diagnosis and 57 (38%) had patient factors that likely contributed to the diagnostic delay or apparent failure to screen/offer to screen.</p> <p>Conclusion</p> <p>Missed opportunities for earlier CRC diagnosis were frequent. Additional studies of clinical data management, focusing on following up abnormal findings, and offering/completing CRC screening, are needed.</p
Assessing the accuracy of an inter-institutional automated patient-specific health problem list
<p>Abstract</p> <p>Background</p> <p>Health problem lists are a key component of electronic health records and are instrumental in the development of decision-support systems that encourage best practices and optimal patient safety. Most health problem lists require initial clinical information to be entered manually and few integrate information across care providers and institutions. This study assesses the accuracy of a novel approach to create an inter-institutional automated health problem list in a computerized medical record (MOXXI) that integrates three sources of information for an individual patient: diagnostic codes from medical services claims from all treating physicians, therapeutic indications from electronic prescriptions, and single-indication drugs.</p> <p>Methods</p> <p>Data for this study were obtained from 121 general practitioners and all medical services provided for 22,248 of their patients. At the opening of a patient's file, all health problems detected through medical service utilization or single-indication drug use were flagged to the physician in the MOXXI system. Each new arising health problem were presented as 'potential' and physicians were prompted to specify if the health problem was valid (Y) or not (N) or if they preferred to reassess its validity at a later time.</p> <p>Results</p> <p>A total of 263,527 health problems, representing 891 unique problems, were identified for the group of 22,248 patients. Medical services claims contributed to the majority of problems identified (77%), followed by therapeutic indications from electronic prescriptions (14%), and single-indication drugs (9%). Physicians actively chose to assess 41.7% (n = 106,950) of health problems. Overall, 73% of the problems assessed were considered valid; 42% originated from medical service diagnostic codes, 11% from single indication drugs, and 47% from prescription indications. Twelve percent of problems identified through other treating physicians were considered valid compared to 28% identified through study physician claims.</p> <p>Conclusion</p> <p>Automation of an inter-institutional problem list added over half of all validated problems to the health problem list of which 12% were generated by conditions treated by other physicians. Automating the integration of existing information sources provides timely access to accurate and relevant health problem information. It may also accelerate the uptake and use of electronic medical record systems.</p
Why is it difficult to implement e-health initiatives? A qualitative study
<b>Background</b> The use of information and communication technologies in healthcare is seen as essential for high quality and cost-effective healthcare. However, implementation of e-health initiatives has often been problematic, with many failing to demonstrate predicted benefits. This study aimed to explore and understand the experiences of implementers - the senior managers and other staff charged with implementing e-health initiatives and their assessment of factors which promote or inhibit the successful implementation, embedding, and integration of e-health initiatives.<p></p>
<b>Methods</b> We used a case study methodology, using semi-structured interviews with implementers for data collection. Case studies were selected to provide a range of healthcare contexts (primary, secondary, community care), e-health initiatives, and degrees of normalization. The initiatives studied were Picture Archiving and Communication System (PACS) in secondary care, a Community Nurse Information System (CNIS) in community care, and Choose and Book (C&B) across the primary-secondary care interface. Implementers were selected to provide a range of seniority, including chief executive officers, middle managers, and staff with 'on the ground' experience. Interview data were analyzed using a framework derived from Normalization Process Theory (NPT).<p></p>
<b>Results</b> Twenty-three interviews were completed across the three case studies. There were wide differences in experiences of implementation and embedding across these case studies; these differences were well explained by collective action components of NPT. New technology was most likely to 'normalize' where implementers perceived that it had a positive impact on interactions between professionals and patients and between different professional groups, and fit well with the organisational goals and skill sets of existing staff. However, where implementers perceived problems in one or more of these areas, they also perceived a lower level of normalization.<p></p>
<b>Conclusions</b> Implementers had rich understandings of barriers and facilitators to successful implementation of e-health initiatives, and their views should continue to be sought in future research. NPT can be used to explain observed variations in implementation processes, and may be useful in drawing planners' attention to potential problems with a view to addressing them during implementation planning
Medication administration errors for older people in long-term residential care
Background
Older people in long-term residential care are at increased risk of medication errors. The purpose of this study was to evaluate a computerised barcode medication management system designed to improve drug administrations in residential and nursing homes, including comparison of error rates and staff awareness in both settings.
Methods
All medication administrations were recorded prospectively for 345 older residents in thirteen care homes during a 3-month period using the computerised system. Staff were surveyed to identify their awareness of administration errors prior to system introduction. Overall, 188,249 attempts to administer medication were analysed to determine the prevalence of potential medication administration errors (MAEs). Error classifications included attempts to administer medication at the wrong time, to the wrong person or discontinued medication. Analysis compared data at residential and nursing home level and care and nursing staff groups.
Results
Typically each resident was exposed to 206 medication administration episodes every month and received nine different drugs. Administration episodes were more numerous (p < 0.01) in nursing homes (226.7 per resident) than in residential homes (198.7). Prior to technology introduction, only 12% of staff administering drugs reported they were aware of administration errors being averted in their care home. Following technology introduction, 2,289 potential MAEs were recorded over three months. The most common MAE was attempting to give medication at the wrong time. On average each resident was exposed to 6.6 potential errors. In total, 90% of residents were exposed to at least one MAE with over half (52%) exposed to serious errors such as attempts to give medication to the wrong resident. MAEs rates were significantly lower (p < 0.01) in residential homes than nursing homes. The level of non-compliance with system alerts was low in both settings (0.075% of administrations) demonstrating virtually complete error avoidance.
Conclusion
Potentially inappropriate administration of medication is a serious problem in long-term residential care. A computerised barcode system can accurately and automatically detect inappropriate attempts to administer drugs to residents. This tool can reliably be used by care staff as well as nurses to improve quality of care and patient safety
Hospital characteristics associated with highly automated and usable clinical information systems in Texas, United States
<p>Abstract</p> <p>Background</p> <p>A hospital's clinical information system may require a specific environment in which to flourish. This environment is not yet well defined. We examined whether specific hospital characteristics are associated with highly automated and usable clinical information systems.</p> <p>Methods</p> <p>This was a cross-sectional survey of 125 urban hospitals in Texas, United States using the Clinical Information Technology Assessment Tool (CITAT), which measures a hospital's level of automation based on physician interactions with the information system. Physician responses were used to calculate a series of CITAT scores: automation and usability scores, four automation sub-domain scores, and an overall clinical information technology (CIT) score. A multivariable regression analysis was used to examine the relation between hospital characteristics and CITAT scores.</p> <p>Results</p> <p>We received a sufficient number of physician responses at 69 hospitals (55% response rate). Teaching hospitals, hospitals with higher IT operating expenses (>75,000 annually) and hospitals with larger IT staff (≥ 10 full-time staff) had higher automation scores than hospitals that did not meet these criteria (p < 0.05 in all cases). These findings held after adjustment for bed size, total margin, and ownership (p < 0.05 in all cases). There were few significant associations between the hospital characteristics tested in this study and usability scores.</p> <p>Conclusion</p> <p>Academic affiliation and larger IT operating, capital, and staff budgets are associated with more highly automated clinical information systems.</p
Glucose testing and insufficient follow-up of abnormal results: a cohort study
BACKGROUND: More than 6 million Americans have undiagnosed diabetes. Several national organizations endorse screening for diabetes by physicians, but actual practice is poorly understood. Our objectives were to measure the rate, the predictors and the results of glucose testing in primary care, including rates of follow-up for abnormal values. METHODS: We conducted a retrospective cohort study of 301 randomly selected patients with no known diabetes who received care at a large academic general internal medicine practice in New York City. Using medical records, we collected patients' baseline characteristics in 1999 and followed patients through the end of 2002 for all glucose tests ordered. We used multivariate logistic regression to measure associations between diabetes risk factors and the odds of glucose testing. RESULTS: Three-fourths of patients (78%) had at least 1 glucose test ordered. Patient age (≥45 vs. <45 years), non-white ethnicity, family history of diabetes and having more primary care visits were each independently associated with having at least 1 glucose test ordered (p < 0.05), whereas hypertension and hyperlipidemia were not. Fewer than half of abnormal glucose values were followed up by the patients' physicians. CONCLUSION: Although screening for diabetes appears to be common and informed by diabetes risk factors, abnormal values are frequently not followed up. Interventions are needed to trigger identification and further evaluation of abnormal glucose tests
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