Hypersensitivity cases associated with drug-eluting coronary stents: a review of available cases from the Research on Adverse Drug Events and Reports (RADAR) project

OBJECTIVES

We undertook the review of all available cases of hypersensitivity reactions after placement of a drug-eluting stent (DES) and classified potential causes.

BACKGROUND

Six months after the approval of the first DES, the Food and Drug Administration (FDA) reported 50 hypersensitivity reactions after stent placement but later concluded these were due to concomitantly prescribed medications such as clopidogrel. Nevertheless, the FDA continued to receive reports of hypersensitivity.

METHODS

Reports available from April 2003 through December 2004 for hypersensitivity-like reactions associated with the sirolimus-eluting stent (CYPHER, Cordis Corp., Miami Lakes, Florida) and paclitaxel-eluting stent (TAXUS, Boston Scientific Corp., Natick, Massachusetts) were reviewed. Sources of reports included the FDA's adverse-device-event database, the published literature, and investigators from the Research on Adverse Drug/Device events And Reports (RADAR) project. Causality was assessed using standardized World Health Organization criteria.

RESULTS

Of 5,783 reports identified for the DES in the FDA database, 262 unique events included hypersensitivity symptoms. Of these reports, 2 were certainly and 39 unlikely caused by clopidogrel and 1 was certainly, 9 probably, and 13 unlikely caused by the DES. From all sources, we identified 17 distinct cases that were probably or certainly caused by the stent, of which 9 had symptoms that lasted longer than four weeks. Four autopsies confirmed intrastent eosinophilic inflammation, thrombosis, and lack of intimal healing.

CONCLUSIONS

The FDA reports and autopsy findings suggest that DES may be a cause of systemic and intrastent hypersensitivity reactions that, in some cases, have been associated with late thrombosis and death.

Clarifying adverse drug events: a clinician's guide to terminology, documentation, and reporting

Adverse drug events cause substantial morbidity and mortality, yet they remain underappreciated and misunderstood. The terminology to describe errors and patient harm associated with medications causes much confusion. This article uses the case study of a patient with multiple adverse drug events to clarify key terms, such as adverse event, adverse drug reaction, adverse drug event, medication error, and side effect. The case discussion illustrates clinical approaches to analyzing the causal connection between a suspect drug and an adverse event. Examples and rationale for meaningful documentation of adverse drug events are provided, along with an outline of the types of events that should be reported to regulatory agencies.

High rates of adverse drug events in a highly computerized hospital

BACKGROUND

Numerous studies have shown that specific computerized interventions may reduce medication errors, but few have examined adverse drug events (ADEs) across all stages of the computerized medication process. We describe the frequency and type of inpatient ADEs that occurred following the adoption of multiple computerized medication ordering and administration systems, including computerized physician order entry (CPOE).

METHODS

Using explicit standardized criteria, pharmacists classified inpatient ADEs from prospective daily reviews of electronic medical records from a random sample of all admissions during a 20-week period at a Veterans Administration hospital. We analyzed ADEs that necessitated a changed treatment plan.

RESULTS

Among 937 hospital admissions, 483 clinically significant inpatient ADEs were identified, accounting for 52 ADEs per 100 admissions and an incidence density of 70 ADEs per 1000 patient-days. One quarter of the hospitalizations had at least 1 ADE. Of all ADEs, 9% resulted in serious harm, 22% in additional monitoring and interventions, 32% in interventions alone, and 11% in monitoring alone; 27% should have resulted in additional interventions or monitoring. Medication errors contributed to 27% of these ADEs. Errors associated with ADEs occurred in the following stages: 61% ordering, 25% monitoring, 13% administration, 1% dispensing, and 0% transcription. The medical record reflected recognition of 76% of the ADEs.

CONCLUSIONS

High rates of ADEs may continue to occur after implementation of CPOE and related computerized medication systems that lack decision support for drug selection, dosing, and monitoring.

Risk factors for adverse drug events: a 10-year analysis

BACKGROUND

Many adverse drug events (ADEs) are the result of known pharmacologic properties, and some result from medication errors. However, some are the result of patient-specific risk factors.

OBJECTIVE

To identify inpatient risk factors for ADEs.

METHODS

Conditional logistic regression was used to analyze all pharmacist-verified ADEs by therapeutic class of drugs and severity during a 10-year study period. All inpatients > or = 18 years of age from a 520-bed tertiary teaching hospital were included. Each case patient was matched with up to 16 control patients. Odds ratios for patient factors associated with ADEs were calculated from different therapeutic classes of drugs.

RESULTS

Odds ratios for numerous risk factors were identified for 4376 ADEs and were found to vary depending on therapeutic classification. The risk factors for the different classifications were grouped by (1) patient characteristics--female (OR 1.5-1.7), age (0.7-0.9), weight (1.2-1.4), creatinine clearance (0.8-4.7), and number of comorbidities (1.1-12.6); (2) drug administration--dosage (1.2-3.7), administration route (1.4-149.9), and number of concomitant drugs (1.2-2.4); and (3) patient type--service (1.2-4.9), nursing division (1.5-3.8), and diagnosis-related group (1.5-5.7).

CONCLUSIONS

Some risk factors are consistent for all ADEs and across multiple therapeutic classes of drugs, while others are class specific. High-risk agents should be closely monitored based on patient characteristics (gender, age, weight, creatinine clearance, number of comorbidities) and drug administration (dosage, administration route, number of concomitant drugs).

The Research on Adverse Drug Events and Reports (RADAR) project

CONTEXT

In 1998, a multidisciplinary team of investigators initiated RADAR (Research on Adverse Drug events And Reports), a clinically based postmarketing surveillance program that systematically investigates and disseminates information describing serious and previously unrecognized adverse drug and device reactions (ADRs).

OBJECTIVE

To describe the structure, operations, and preliminary findings from the RADAR project and related dissemination efforts by pharmaceutical suppliers and the US Food and Drug Administration (FDA).

DESIGN

After identifying a serious and unexpected clinical event suitable for further investigation, RADAR collaborators postulated clinical hypotheses and derived case series and incidence estimates from physician queries, published and unpublished clinical trials, published case reports, FDA databases, and manufacturer sales figures.

RESULTS

RADAR investigators identified 16 types of serious ADRs among 1699 patients, of whom 169 (10%) died as a result of the reaction. Initial cases were identified by 7 RADAR investigators, 4 collaborating physicians, 2 attorneys, and by reviewing 3 published reports. Additional sources included queries of occupational health programs and medical directors of interventional cardiology laboratories (3 types of ADRs), published manuscripts and clinical trials (11 types of ADRs), review of medical records at a RADAR site (2 types of ADRs), unpublished clinical trial reports (3 types of ADRs), and reports from attorneys, family members, or patients (4 types of ADRs). Incidence estimates, ranging from 0.4% to 33%, were derived from 5 clinical trial reports, 2 physician queries, and 2 observational databases. Laboratory support for hypotheses included identification of 3 neutralizing antibodies and 3 histopathological findings. ADR reports were disseminated as 8 revised package inserts, 7 "dear doctor" letters, and 9 peer-reviewed articles.

CONCLUSION

A new, clinically based, hypothesis-driven approach to postmarketing surveillance may supplement existing regulatory surveillance systems and improve patient safety.

Prescribing discrepancies likely to cause adverse drug events after patient transfer

BACKGROUND

Medication-prescribing discrepancies are used as a quality measure for patients transferred between sites of care. The objective of this study was to quantify the rate of adverse drug events (ADEs) caused by prescribing discrepancies and the discrimination of an index of high-risk transition drug prescribing.

METHODS

We examined medical records of patients transferred between seven nursing homes and three hospitals between 1999 and 2005 in New York and Connecticut for transfer-associated prescribing discrepancies. ADEs caused by discrepancies were determined by two clinician raters. We calculated the fraction of medication discrepancies that caused ADEs in each of 22 drug classes by calculating positive predictive values (PPVs). We calculated the discrimination of a count of high-risk drug discrepancies, selected from published lists of high-risk medications and using observed PPVs.

RESULTS

208 patients were hospitalised 304 times. Overall, 65 of 1350 prescribing discrepancies caused ADEs, for a PPV of 0.048 (95% CI 0.037 to 0.061). PPVs by drug class ranged from 0 to 0.28. Drug classes with the highest PPVs were opioid analgesics, metronidazole, and non-opioid analgesics. Patients with 0, 1-2 and >/=3 high-risk discrepancies had a 13%, 23% and 47% chance of experiencing a discrepancy-related ADE, respectively.

CONCLUSIONS

Discrepancies in certain drug classes more often caused ADEs than other types of discrepancies in hospitalised nursing-home patients. Information about ADEs caused by medication discrepancies can be used to enhance measurement of care quality, identify high-risk patients and inform the development of decision-support tools at the time of patient transfer.

Medication reconciliation: barriers and facilitators from the perspectives of resident physicians and pharmacists

BACKGROUND

Medication reconciliation can prevent medication errors and harm when patients transition between hospital and other care settings. Though a Joint Commission hospital Patient Safety Goal since 2006, organizations continue to have difficulty implementing the process.

OBJECTIVE

To determine factors that influence performance of medication reconciliation in a hospital setting with a computerized medication reconciliation tool.

DESIGN

Cognitive task analysis (CTA) and focus group interviews.

SETTING

Urban, academic, tertiary-care Veterans Affairs medical center.

PARTICIPANTS

Internal medicine house staff physicians (n = 23) and inpatient staff pharmacists (n = 12).

MEASUREMENTS

CTA participants verbalized their thoughts while they completed medication reconciliation with the computerized tool. Focus group participants described medication reconciliation's purpose and effectiveness, how they completed the task, and its barriers and facilitators. Interviews were recorded and analyzed using social science methods for analyzing qualitative data.

RESULTS

Participants agreed that a central goal of medication reconciliation is to prevent prescribing errors, but disagreed about whether it achieves this goal. Computerization facilitated the task, but participants said that computers and patients can be unreliable sources of information. Participants varied in how they sequenced components of the task. When time was limited, physicians considered other responsibilities higher priority. Both physicians and pharmacists expressed low self-efficacy, ie, low perceived capability to achieve the objectives of the process.

CONCLUSION

Key barriers to medication reconciliation are unreliable sources of medication information and tasks that compete for providers' time and attention that they consider higher priority. Addressing these barriers while increasing providers' self-efficacy might improve medication reconciliation and its outcomes.

Accelerated approval of cancer drugs: improved access to therapeutic breakthroughs or early release of unsafe and ineffective drugs?

PURPOSE

Accelerated approval (AA) was initiated by the US Food and Drug Administration (FDA) to shorten development times of drugs for serious medical illnesses. Sponsors must confirm efficacy in postapproval trials. Confronted with several drugs that received AA on the basis of phase II trials and for which confirmatory trials were incomplete, FDA officials have encouraged sponsors to design AA applications on the basis of interim analyses of phase III trials.

METHODS

We reviewed data on orphan drug status, development time, safety, and status of confirmatory trials of AAs and regular FDA approvals of new molecular entities (NMEs) for oncology indications since 1995.

RESULTS

Median development times for AA NMEs (n = 19 drugs) and regular-approval oncology NMEs (n = 32 drugs) were 7.3 and 7.2 years, respectively. Phase III trials supported efficacy for 75% of regular-approval versus 26% of AA NMEs and for 73% of non-orphan versus 45% of orphan drug approvals. AA accounted for 78% of approvals for oncology NMEs between 2001 and 2003 but accounted for 32% in more recent years. Among AA NMEs, confirmatory trials were nine-fold less likely to be completed for orphan drug versus non-orphan drug indications. Postapproval, black box warnings were added to labels for four oncology NMEs (17%) that had received AA and for two oncology NMEs (9%) that had received regular approval.

CONCLUSION

AA oncology NMEs are safe and effective, although development times are not accelerated. A return to endorsing phase II trial designs for AA for oncology NMEs, particularly for orphan drug indications, may facilitate timely FDA approval of novel cancer drugs.

pSCANNER: patient-centered Scalable National Network for Effectiveness Research

This article describes the patient-centered Scalable National Network for Effectiveness Research (pSCANNER), which is part of the recently formed PCORnet, a national network composed of learning healthcare systems and patient-powered research networks funded by the Patient Centered Outcomes Research Institute (PCORI). It is designed to be a stakeholder-governed federated network that uses a distributed architecture to integrate data from three existing networks covering over 21 million patients in all 50 states: (1) VA Informatics and Computing Infrastructure (VINCI), with data from Veteran Health Administration's 151 inpatient and 909 ambulatory care and community-based outpatient clinics; (2) the University of California Research exchange (UC-ReX) network, with data from UC Davis, Irvine, Los Angeles, San Francisco, and San Diego; and (3) SCANNER, a consortium of UCSD, Tennessee VA, and three federally qualified health systems in the Los Angeles area supplemented with claims and health information exchange data, led by the University of Southern California. Initial use cases will focus on three conditions: (1) congestive heart failure; (2) Kawasaki disease; (3) obesity. Stakeholders, such as patients, clinicians, and health service researchers, will be engaged to prioritize research questions to be answered through the network. We will use a privacy-preserving distributed computation model with synchronous and asynchronous modes. The distributed system will be based on a common data model that allows the construction and evaluation of distributed multivariate models for a variety of statistical analyses.

Histologic features of human orbicularis oculi treated with botulinum A toxin

To evaluate muscle histologic features in humans following therapeutic botulinum toxin injections, we studied orbicularis oculi from 11 patients with blepharospasm; nine had previously received botulinum toxin injections and two had not. All muscles had comparable variability in muscle fiber diameter, with no necrosis, inflammation, denervation, or consistent alterations in muscle fiber internal architecture. Botulinum toxin produces no persistent histologic changes in human muscle fibers.

Dissemination of information on potentially fatal adverse drug reactions for cancer drugs from 2000 to 2002: first results from the research on adverse drug events and reports project

PURPOSE

To describe the clinical findings, occurrence rates, causality evidence, and dissemination media for serious cancer drug-associated adverse drug reactions (ADRs) reported in the postmarketing setting.

METHODS

ADRs were termed serious if they resulted in death or severe organ failure. ADR information for oncology drugs from package insert (PI) revisions, so-called Dear Doctor letters, and journal articles was evaluated to identify serious ADRs reported from 2000 to 2002. Timing and content of information disseminated was assessed.

RESULTS

Twenty-five serious ADRs associated with 22 oncology drugs were identified after approval. Approximately half of these serious ADRs are associated with drugs approved before 1995. ADRs were described in articles in medical journals (17 ADRs), PI revisions (18 ADRs), and Dear Doctor letters (12 ADRs). PI revisions occurred less than 1 year after peer-reviewed publication for four ADRs. These revisions often differed for similar ADRs that occurred with drugs of the same class. Five of the seven ADRs lacking PI changes occurred with off-label use, for which PI change is not recommended by US Food and Drug Administration (FDA) policy. No cancer drug was withdrawn from the market during the observation period.

CONCLUSION

Our findings demonstrate that serious ADRs may be discovered as long as 36 years after a drug receives FDA approval. This suggests a need for continued vigilance and efficient strategies for dissemination of information about ADRs associated with cancer drugs.

Evaluation of serious adverse drug reactions: a proactive pharmacovigilance program (RADAR) vs safety activities conducted by the Food and Drug Administration and pharmaceutical manufacturers

BACKGROUND

The Food and Drug Administration (FDA) and pharmaceutical manufacturers conduct most postmarketing pharmaceutical safety investigations. These efforts are frequently based on data mining of databases. In 1998, investigators initiated the Research on Adverse Drug events And Reports (RADAR) project to investigate reports of serious adverse drug reactions (ADRs) and prospectively obtain information on these cases. We compare safety efforts for evaluating serious ADRs conducted by the FDA and pharmaceutical manufacturers vs the RADAR project.

METHODS

We evaluated the completeness of serious ADR descriptions in the FDA and RADAR databases and the comprehensiveness of notifications disseminated by pharmaceutical manufacturers and the RADAR investigators. A serious ADR was defined as an event that led to death or required intensive therapies to reverse.

RESULTS

The RADAR investigators evaluated 16 serious ADRs. Compared with descriptions of these ADRs in FDA databases (2296 reports), reports in RADAR databases (472 reports) had a 2-fold higher rate of including information on history and physical examination (92% vs 45%; P<.001) and a 9-fold higher rate of including basic science findings (34% vs 4%; P = .08). Safety notifications were disseminated earlier by pharmaceutical suppliers (2 vs 4 years after approval, respectively), although notifications were less likely to include information on incidence (46% vs 93%; P = .02), outcomes (8% vs 100%; P<.001), treatment or prophylaxis (25% vs 93%; P<.001), or references (8% vs 80%; P<.001).

CONCLUSION

Proactive safety efforts conducted by the RADAR investigators are more comprehensive than those conducted by the FDA and pharmaceutical manufacturers, but dissemination of related safety notifications is less timely.

Pharmacists versus nonpharmacists in adverse drug event detection: A meta-analysis and systematic review

PURPOSE

A systematic review and metaanalysis were conducted to determine if studies that included pharmacists as chart reviewers detected higher rates of adverse drug events (ADEs) than studies that included other health care professionals or hospital personnel as chart reviewers.

METHODS

A systematic review and metaanalysis of studies using chart review as the method of detection of ADEs were conducted. Pooled estimates of the ADE rates were calculated using the inverse variance weight method. Meta-analysis was performed using a random effects model. Using the Mann-Whitney U test, weighted rates of studies in which pharmacists versus other clinicians were the chart reviewers were compared.

RESULTS

Thirteen studies satisfied the inclusion criteria. Using random effects metaanalysis, the mean of the weighted incidence rate detected by pharmacists was 0.33 ADE per admission (95% confidence interval [CI], 0.17-0.50); the mean was 0.16 ADE per admission (95% CI, 0.11-0.22) with detection by nonpharmacists. Significant heterogeneity was present between studies in both groups. A significant difference (p=0.003) existed between the ADE rate reported by pharmacists (median=0.23; interquartile range [IQR], 0.18-0.44) and that of nonpharmacists (median=0.12; IQR, 0.02-0.49). Although there is overwhelming evidence of statistical heterogeneity, the numbers pertaining to the ADE rates detected by the two groups were large enough to indicate significant differences. Despite the heterogeneity, there is strong evidence that pharmacist-led interventions based on chart review report a higher ADE rate among inpatients.

CONCLUSION

A review of the literature revealed that pharmacists make a salient contribution as manual chart reviewers in inpatient ADE interventions.

Overestimation of the effects of adherence on outcomes: a case study in healthy user bias and hypertension

BACKGROUND

The healthy user bias is usually overlooked as an explanation in studies in which a strong association is found between poor patient medication adherence and worse disease outcomes. Such studies are increasing in frequency across disease states and influence clinical practice. Adherence to antihypertensive medications was studied to illustrate confounding in such studies.

METHODS

Using data from veterans with hypertension starting antihypertensive treatment, causal models were developed that predicted the risks of hospitalisation, myocardial infarction (MI) and death associated with poor adherence (<80%) while adjusting for patient demographics, baseline disease severity and disease comorbidity. In a second set of otherwise identical models, adjustment was made for time-varying blood pressure (BP), thus controlling for adherence effects that were mediated through the main pharmacological effects of the drugs. It was hypothesised that the second set of models would reveal a positive association between poor adherence and adverse disease outcomes that is largely explained by unmeasured confounders, including health-related behaviours.

RESULTS

The models that did not adjust for time-varying BP levels showed that patients with poor adherence had statistically significantly increased risks of 3.7% for hospitalisation, 28.1% for MI and 23.3% for death. These estimates exceed the benefits of these drugs demonstrated by clinical trials. When controlling for time-varying BP, the increased risks were similar (3.4% for hospitalisation, 27.7% for MI and 23.4% for death). The findings were consistent across a range of adherence thresholds (50-90%) and when allowing disease status variables to vary.

CONCLUSIONS

The associations between poor adherence and outcomes are largely independent of the pharmacological effects of the drugs on BP control as well as commonly measured patient covariates. This finding suggests that even carefully designed observational adherence studies using rich clinical data are impossibly confounded and probably overestimate the true magnitude of the effect. Clinical practice guidelines based on reported adherence effects should be reconsidered.

Effect of health information exchange on recognition of medication discrepancies is interrupted when data charges are introduced: results of a cluster-randomized controlled trial

OBJECTIVES

To determine the effect of health information exchange (HIE) on medication prescribing for hospital inpatients in a cluster-randomized controlled trial, and to examine the prescribing effect of availability of information from a large pharmacy insurance plan in a natural experiment.

METHODS

Patients admitted to an urban hospital received structured medication reconciliation by an intervention pharmacist with (intervention) or without (control) access to a regional HIE. The HIE contained prescribing information from the largest hospitals and pharmacy insurance plan in the region for the first 10 months of the study, but only from the hospitals for the last 21 months, when data charges were imposed by the insurance plan. The primary endpoint was discrepancies between preadmission and inpatient medication regimens, and secondary endpoints included adverse drug events (ADEs) and proportions of rectified discrepancies.

RESULTS

Overall, 186 and 195 patients were assigned to intervention and control, respectively. Patients were 60 years old on average and took a mean of 7 medications before admission. There was no difference between intervention and control in number of risk-weighted discrepancies (6.4 vs 5.8, P = .452), discrepancy-associated ADEs (0.102 vs 0.092 per admission, P = .964), or rectification of discrepancies (0.026 vs 0.036 per opportunity, P = .539). However, patients who received medication reconciliation with pharmacy insurance data available had more risk-weighted medication discrepancies identified than those who received usual care (8.0 vs 5.9, P = .038).

DISCUSSION AND CONCLUSION

HIE may improve outcomes of medication reconciliation. Charging for access to medication information interrupts this effect. Efforts are needed to understand and increase prescribers' rectification of medication discrepancies.

A Simulation-Based Evaluation of Methods to Estimate the Impact of an Adverse Event on Hospital Length of Stay

INTRODUCTION

We used agent-based simulation to examine the problem of time-varying confounding when estimating the effect of an adverse event on hospital length of stay. Conventional analytic methods were compared with inverse probability weighting (IPW).

METHODS

A cohort of hospitalized patients, at risk for experiencing an adverse event, was simulated. Synthetic individuals were assigned a severity of illness score on admission. The score varied during hospitalization according to an autoregressive equation. A linear relationship between severity of illness and the logarithm of the discharge rate was assumed. Depending on the model conditions, adverse event status was influenced by prior severity of illness and, in turn, influenced subsequent severity. Conditions were varied to represent different levels of confounding and categories of effect. The simulation output was analyzed by Cox proportional hazards regression and by a weighted regression analysis, using the method of IPW. The magnitude of bias was calculated for each method of analysis.

RESULTS

Estimates of the population causal hazard ratio based on IPW were consistently unbiased across a range of conditions. In contrast, hazard ratio estimates generated by Cox proportional hazards regression demonstrated substantial bias when severity of illness was both a time-varying confounder and intermediate variable. The direction and magnitude of bias depended on how severity of illness was incorporated into the Cox regression model.

CONCLUSIONS

In this simulation study, IPW exhibited less bias than conventional regression methods when used to analyze the impact of adverse event status on hospital length of stay.

Developing Indicators of Inpatient Adverse Drug Events Through Nonlinear Analysis Using Administrative Data

BACKGROUND

Because of uniform availability, hospital administrative data are appealing for surveillance of adverse drug events (ADEs). Expert-generated surveillance rules that rely on the presence of International Classification of Diseases, 9th Revision Clinical Modification (ICD-9-CM) codes have limited accuracy. Rules based on nonlinear associations among all types of available administrative data may be more accurate.

OBJECTIVES

By applying hierarchically optimal classification tree analysis (HOCTA) to administrative data, derive and validate surveillance rules for bleeding/anticoagulation problems and delirium/psychosis.

RESEARCH DESIGN

Retrospective cohort design.

SUBJECTS

A random sample of 3987 admissions drawn from all 41 Utah acute-care hospitals in 2001 and 2003.

MEASURES

Professional nurse reviewers identified ADEs using implicit chart review. Pharmacists assigned Medical Dictionary for Regulatory Activities codes to ADE descriptions for identification of clinical groups of events. Hospitals provided patient demographic, admission, and ICD9-CM data.

RESULTS

Incidence proportions were 0.8% for drug-induced bleeding/anticoagulation problems and 1.0% for drug-induced delirium/psychosis. The model for bleeding had very good discrimination and sensitivity at 0.87 and 86% and fair positive predictive value (PPV) at 12%. The model for delirium had excellent sensitivity at 94%, good discrimination at 0.83, but low PPV at 3%. Poisoning and adverse event codes designed for the targeted ADEs had low sensitivities and, when forced in, degraded model accuracy.

CONCLUSIONS

Hierarchically optimal classification tree analysis is a promising method for rapidly developing clinically meaningful surveillance rules for administrative data. The resultant model for drug-induced bleeding and anticoagulation problems may be useful for retrospective ADE screening and rate estimation.

Future history: medical informatics in geriatrics

With deference to Isaac Asimov's The Foundation, which is the inspiration for this series, we briefly describe the "present history" of medical informatics (the application of information technology in medicine) in geriatrics, and then project a "future history" of this same endeavor. The older patient often has multiple acute and chronic problems that require management by a variety of medical professionals in a variety of settings. Proper care necessitates efficient gathering, integration, and management of information by each professional in each setting. As medical informatics evolves, we project that barriers to information exchange (both between providers and between providers and patients) will continue to decrease while the quality and relevance of exchanged information will continue to increase. The nexus of care will be the electronic medical record (EMR), which will shed its current paper chart metaphor and adopt an industrial process metaphor based on tasks and tolerances or goals. The multidisciplinary management of geriatric patients will strike a new balance: doctors, nurses, allied health professionals, family, and patients will all participate in the management of the patient's care. The EMR will coordinate data from a variety of novel sources, including wearable sensors monitoring physiologic parameters, falls, diet, ambulation, and medication compliance. The highly organized data in the EMR will allow explicit decision support for computer-facilitated, evidence-based care; will empower midlevel providers and patients with an increased role in the care plan; and will promote the realignment of care from hospitals/clinics to the patient's home.

Crossing the Quality Chasm: The Role of Information Technology Departments

Integrating information technology (IT) into medical settings is considered essential to transforming hospitals into 21st-century health care institutions. Yet the role of IT departments in maximizing the effectiveness of information systems is not well understood. This article reports a 3-round Delphi panel of Veterans Administration personnel experienced with provider order entry electronic systems. In round 1, 35 administrative, clinical, and IT personnel answered 10 open-ended questions about IT strategies and structures that best support successful transformation. In round 2, panelists rated item importance and ranked proposed strategies. In round 3, panelists received aggregate feedback and rerated the items. Four domains emerged from round 1: IT organization, IT performance monitoring, user-support activities, and core IT responsibilities (eg, computer security, training). In rounds 2 and 3, IT performance monitoring was rated the most important, closely followed by clinical support. Strategies associated with each domain are identified and discussed.

Factors associated with screening or treatment initiation among male United States veterans at risk for osteoporosis fracture

Male osteoporosis continues to be under-recognized and undertreated in men. An understanding of which factors cue clinicians about osteoporosis risk in men, and which do not, is needed to identify areas for improvement. This study sought to measure the association of a provider's recognition of osteoporosis with patient information constructs that are available at the time of each encounter. Using clinical and administrative data from the Veterans Health Administration system, we used a stepwise procedure to construct prognostic models for a combined outcome of osteoporosis diagnosis, treatment, or a bone mineral density (BMD) test order using time-varying covariates and Cox regression. We ran separate models for patients with at least one primary care visit and patients with only secondary care visits in the pre-index period. Some of the strongest predictors of clinical osteoporosis identification were history of gonadotropin-releasing hormone (GnRH) agonist exposure, fragility fractures, and diagnosis of rheumatoid arthritis. Other characteristics associated with a higher likelihood of having osteoporosis risk recognized were underweight or normal body mass index, cancer, fall history, and thyroid disease. Medication exposures associated with osteoporosis risk recognition included opioids, glucocorticoids, and antidepressants. Several known clinical risk factors for fracture were not correlated with osteoporosis risk including smoking and alcohol abuse. Results suggest that clinicians are relying on some, but not all, clinical risk factors when assessing osteoporosis risk.

Development of trigger tools for surveillance of adverse events in ambulatory surgery

BACKGROUND

The trigger tool methodology uses clinical algorithms applied electronically to 'flag' medical records where adverse events (AEs) have most likely occurred. The authors sought to create surgical triggers to detect AEs in the ambulatory care setting.

METHODS

Four consecutive steps were used to develop ambulatory surgery triggers. First, the authors conducted a comprehensive literature review for surgical triggers. Second, a series of multidisciplinary focus groups (physicians, nurses, pharmacists and information technology specialists) provided user input on trigger selection. Third, a clinical advisory panel designed an initial set of 10 triggers. Finally, a three-phase Delphi process (surgical and trigger tool experts) evaluated and rated the suggested triggers.

RESULTS

The authors designed an initial set of 10 surgical triggers including five global triggers (flagging medical records for the suspicion of any AE) and five AE-specific triggers (flagging medical records for the suspicion of specific AEs). Based on the Delphi rating of the trigger's utility for system-level interventions, the final triggers were: (1) emergency room visit(s) within 21 days from surgery; (2) unscheduled readmission within 30 days from surgery; (3) unscheduled procedure (interventional radiological, urological, dental, cardiac or gastroenterological) or reoperation within 30 days from surgery; (4) unplanned initial hospital length of stay more than 24 h; and (5) lower-extremity Doppler ultrasound order entry and ICD code for deep vein thrombosis or pulmonary embolus within 30 days from surgery.

CONCLUSION

The authors therefore propose a systematic methodology to develop trigger tools that takes into consideration previously published work, end-user preferences and expert opinion.

Electronic health records and adverse drug events after patient transfer

BACKGROUND

Our objective was to examine the frequencies of medication error and adverse drug events (ADEs) at the time of patient transfer in a system with an electronic health record (EHR) as compared with a system without an EHR. It was hypothesised that the frequencies of these events would be lower in the EHR system because of better information exchange across sites of care.

METHODS

469 patients transferred between seven nursing homes and three hospitals in New York and Connecticut between 1999 and 2005 were followed retrospectively. Two groups of patients were compared: US Veterans Affairs (VA) patients, with an EHR, and non-VA patients, without an EHR, on the following measures: (1) medication prescribing discrepancies at nursing home/hospital transfer, (2) high-risk medication discrepancies and (3) ADEs caused by medication discrepancies according to structured medical record review by pairs of physician and pharmacist raters.

RESULTS

The overall incidence of ADE caused by medication discrepancies was 0.20 per hospitalisation episode. After controlling for demographic and clinical covariates, there were no significant differences between VA and non-VA groups in medication discrepancies (mean difference 0.02; 95% CI -0.81 to 0.85), high-risk medication discrepancies (-0.18; 95%CI -0.22 to 0.58) or occurrence of an ADE caused by a medication discrepancy (OR 0.96; 95% CI 0.18 to 5.01).

CONCLUSIONS

There was no difference, with and without an EHR, in the occurrence of medication discrepancies or ADEs caused by medication discrepancies at the time of transfer between sites of care. Reducing such problems may require specialised computer tools to facilitate medication review.

Patient-centered care and the electronic health record: exploring functionality and gaps

OBJECTIVE

Healthcare systems have adopted electronic health records (EHRs) to support clinical care. Providing patient-centered care (PCC) is a goal of many healthcare systems. In this study, we sought to explore how existing EHR systems support PCC; defined as understanding the patient as a whole person, building relational connections between the clinician and patient, and supporting patients in health self-management.

MATERIALS AND METHODS

We assessed availability of EHR functions consistent with providing PCC including patient goals and preferences, integrated care plans, and contextual and patient-generated data. We surveyed and then interviewed technical representatives and expert clinical users of 6 leading EHR systems. Questions focused on the availability of specific data and functions related to PCC (for technical representatives) and the clinical usefulness of PCC functions (for clinicians) in their EHR.

RESULTS

Technical representatives (n = 6) reported that patient communication preferences, personalized indications for medications, and end of life preferences were functions implemented across 6 systems. Clinician users (n = 10) reported moderate usefulness of PCC functions (medians of 2-4 on a 5-pointy -35t scale), suggesting the potential for improvement across systems. Interviews revealed that clinicians do not have a shared conception of PCC. In many cases, data needed to deliver PCC was available in the EHR only in unstructured form. Data systems and functionality to support PCC are under development in these EHRs.

DISCUSSION AND CONCLUSION

There are current gaps in PCC functionality in EHRs and opportunities to support the practice of PCC through EHR redesign.

Effect on VA Patient Satisfaction of Provider's Use of an Integrated Viewer of Multiple Electronic Health Records

PURPOSE

To examine associations between patient perceptions that their provider was knowledgeable of their medical history and clinicians' early adoption of an application that presents providers with an integrated longitudinal view of a patient's electronic health records (EHR) from multiple healthcare systems.

METHOD

This retrospective analysis utilizes provider audit logs from the Veterans Health Administration Joint Legacy Viewer (JLV) and patient responses to the Survey of Patient Healthcare Experiences Patient-Centered Medical Home (SHEP/PCMH) patient satisfaction survey (FY2016) to assess the relationship between the primary care provider being an early adopter of JLV and patient perception of the provider's knowledge of their medical history. Multivariate logistic regression models were used to control for patient age, race, sex education, health status, duration of patient-provider relationship, and provider characteristics.

RESULTS

The study used responses from 203,903 patients to the SHEP-PCMH survey in FY2016 who received outpatient primary care services from 11,421 unique providers. Most (91%) clinicians had no JLV utilization in the 6 months prior to the studied patient visit. Controlling for patient demographics, length of the patient-provider relationship, and provider and facility characteristics, being an early adopter of the JLV system was associated with a 14% (adj OR 1.14, p < 0.000) increased odds that patients felt their provider was knowledgeable about their medical history. When evaluating the interaction between duration of patient-provider relationship and being an early adopter of JLV, a greater effect was seen with patient-provider relationships that were greater than 3 years (adj OR 1.23, p < 0.000), compared to those less than 3 years.

CONCLUSIONS

Increasing the interoperability of medical information systems has the potential to improve both patient care and patient experience of care. This study demonstrates that early adopters of an integrated view of electronic health records from multiple delivery systems are more likely to have their patients report that their clinician was knowledgeable of their medical history. With provider payments often linked to patient satisfaction performance metrics, investments in interoperability may be worthwhile.