Is It Time for the Customizable Infobutton?

Infobuttons are intended to provide links to context-sensitive information in online resources to support clinical decision making. In this issue, we discuss challenges that impact the maximal effective use of Infobuttons. We also suggest methods to facilitate the role of Infobuttons as a tool to support optimal use of medications.The medication use process can be negatively impacted by inappropriate patient selection for drug therapy, nonscientific ordering behaviors, incorrect preparation procedures, inaccurate administration, and poor follow-up procedures. The process is further complicated when patients demand therapeutic interventions and providers believe that medication use is appropriate, even when there is no scientific evidence to support these treatment decisions. Access to information can aid clinical decision making and avoid the problems affecting the medication use process.HL7 International Context-Aware Information Retrieval standard (the HL7 “Infobutton” standard) has been widely adopted since 2007. Infobuttons are decision support tools that provide links within electronic medical record (EMR) systems to online information. Many practitioners are discovering that the Infobutton is defaulting to a static, tertiary reference monograph that is intended to guide decisions for all who participate in the medication use process. But decision support information is seldom a one-size-fits-all proposition. We believe that the Infobutton should be customizable for an individual health system’s use.Every guideline that is distributed to health systems gets vetted by a clinical review committee prior to being placed online for general use. We worked on a project where such a guideline was distributed to 128 hospitals and nearly every hospital found something to tweak in the guideline. We believe that Infobuttons could appropriately publish checklisted, evidence-based decision support to prompt both experienced and naïve users throughout the medication use process. Infobutton use could also lead to more updates, as feedback is gained from the use of specific medications and problems emerge in actual practice.The Agency for Healthcare Research and Quality considers a checklist to be “an algorithmic listing of actions to be performed in a clinical setting” with the intended goal being “to ensure that no step will be forgotten. Although a seemingly simple intervention, checklists have a sound theoretical basis in principles of human factors engineering and have played a major role in some of the most significant successes achieved in the patient safety movement.”¹ Patient safety movements continue to promote the benefit of checklist-based approaches. Although mistakes can happen, slips are very preventable with the appropriate use of this tool.Clinicians are pressed for time due to the emergent conditions of their patients and their total patient loads. Under this pressure, they must make decisions about the safe use of drug interventions for which they may have little or no prior experience. This situation is not exclusive to physicians; it occurs across the medication use process. Therefore, the ideal Infobutton should allow systematic access and concurrently allow users to drill down to the precise nugget of information that is needed. We recommend navigation options that include links to these nuggets but also provide the ability to expand and collapse sections of extensive monographs to aid the rapid access to the desired decision support.When calculations about medications are required, it would be ideal to have patient demographics and lab values accessible and integrated to the Infobutton so that values can be verified and calculations can be made from prepopulated data. When integration is not available, data entry should be supported through checkboxes, radio buttons, pull-down lists, and controlled keyboard/touchscreen inputs. Instructions that require preparation procedures for drug products should utilize video demonstrations or illustrated steps that demonstrate how to achieve optimal results. Infobuttons should be designed to prevent errors by requiring users to start with a checklist that has been cleared automatically from any previous user. Additionally, print capabilities and download capabilities should make the Infobutton materials available for in-service education when desired.The use of checklists and other decision-support tools is not without controversy. Many clinicians see them as time robbers and yet another distraction to their thought processes. This viewpoint may indicate the need for a shift in organizational culture to put safety first, employing procedures, policies, and tools to enable a unified focus. A shift to a culture of safety often advances the use of decision-support tools. It may be necessary to hold providers accountable when they fail to use these tools when working with either new medications or medications that have known safety implications and have created problems in the medication use process. The ability for an individual health system to customize decision-support tools may help providers feel that they have ownership of the approach and may undercut their criticism that guidelines promote cookie-cutter medicine. Each Infobutton would be available on every screen in the EHR any time a medication consideration is being addressed. Thus, no provider would have to pull out a smart phone or go to another program outside of the EHR to access information.We found out through an advisory board that many drug products are associated with expert users in health systems. A further customization of an Infobutton would be to add a list of these experts and their contact information that would be available for clinicians when they experience difficulty with the use of these products or procedures. Most pharmaceutical companies also provide additional support in the form of 24-hour medical information hotlines and product-specific Web sites. We believe that the best customizable Infobutton would have a controlled editing environment that would allow US Food and Drug Administration–approved content to be displayed initially and would have the capacity for additional helpful information to be added through editing of the distributed information button content. The restoration of the original text back to the distributed document would also be a desirable feature for this content.We are excited that the opportunity for the receipt of just-in-time information continues to be enhanced. Although we know that errors and mistakes will occur, time-proven methods such as checklists can make the medication use process increasingly safe. We encourage your comments and questions to either Bill at ude.nrubua@gbeklef or Brent at ude.nrubua@nerbxof. We would enjoy continuing this conversation.     

How Population Health Management and Big Data Can Rock Your World

Hospitals and health systems like yours have been aggressively pursuing a range of information systems over the last several decades. Cited goals are often efficiency, lower costs, better decisions, and better patient outcomes. But how do these systems purportedly lead to population-level improvements in care? In this column, we address the connections that are anticipated as well as challenges to be expected along the way.Let’s start with some definitions. Population health management, according to a leading outcomes management provider, is the “aggregation of patient data across multiple health information technology resources, the analysis of that data into a single, actionable patient record, and the actions through which care providers can improve both clinical and financial outcomes.”¹ While we like this definition because systems are used in a way that patient care is provided to individual patients, we think that the intelligence gained from each patient encounter can concurrently be applied throughout the continuum of care for any population being served. Big data is a buzzword in health care, even though other industries have been using the analysis of huge quantities of digitized data for many years. In health care, the rapid adoption of the electronic health record (EHR) provides an opportunity to finally having a real chance for improving health outcomes and controlling costs.The definition of big data varies, but we will define it as the “ability to access and analyze information that holds the key to more efficient, higherquality health care while significantly shortening the time between research and translation into practice.”² Big data is made possible because health care is now moving toward being a real digital enterprise to leverage the collective power of information. In our examination of health system technology devices that have been deployed for the last 10 years, we discovered that some had the ability to be networked but many were not. The EHR can now be the data hub for providers while supporting care provision by consolidating and analyzing these digital warehouses of real-time data to discover trends and make predictions.In a previous column, we described these processes as enterprise performance management. At a strategic level, a health system would generate critical success factors and key performance indicators that would lead to outcomes improvement. At an operational level, data would be gathered as a byproduct of rendering patient care to determine how well these indicators of success were being met. The system would generate e-mails to managers to give them feedback on any success factors assigned to them. Exception reports could include deficiencies, meeting of goals, and exceeding expectations. When best practices were identified within the enterprise, the methods being utilized to exceed expectations could then be used to address the problems experienced in units where expectations were not being met.In our experience, niche industries are being generated by the inability of EHR vendors to address both the developmental needs to improve their core product for its primary purpose of patient care and to add all of the population health and data analysis capabilities required. Add to this the fact that the individuals who are needed at the health system level to work with data analysis are the same people that Google and Microsoft are recruiting as quickly as possible. Thus, entrepreneurs look at the needs of health care and bring the skills and expertise necessary to the task. The expectation is that the EHR vendors who are going to cooperate by providing the needed data will eventually wrap the capabilities of these consultants into the everyday functions found in their systems.The complexity inherent in population health management is quite high. The data sources and their divergent information standards bring about the first challenge. Again, starting with a specific EHR, integration or interfaces must be established with any ambulatory electronic medical record being utilized by employed or affiliated providers. Each of these medical records could utilize one of 10 standards to include HL7, CCR, CCD, and so on that will need to be translated and normalized to be of any use for analysis. Next, we have separate computerized prescriber order entry systems, labs, imaging, health information exchanges, payers, and claims data. Each of these data sources must be integrated and normalized before they provide any real utility.Now we need to talk about clinical decision support systems. As a provider, you are probably already aware of the problem we call flag fatigue where alerts and warnings interrupt your provision of care for your patients. The challenge for an enterprise decision support system will be to ensure that the right provider is involved in the appropriate intervention at the appropriate point in the care process in the appropriate facility for the appropriate patient at the appropriate time. Get your mind around this complexity. Now think about multidisciplinary care team coordination and communication. How are we going to know who did what, when, and how?Alerts that are needed in population health management can also start when care gaps are identified. They can start when a patient steps on a digital scale that transmits a 10-lb weight gain due to heart failure–related edema. The alert may take place because patient outreach is indicated and an assignment for this task must be made. Action may be needed due to a patient’s entry in a notes section of a patient portal. Alerts may occur because quality reporting is either missing or the values entered have triggered the need for a response.Right now, we’re spending most of our time putting these data in and straddling the current reimbursement system that is so heavily based on fee-forservice care provision while preparing for anticipated, future ways of providing care. To understand how life will be different as these changes take place, look at those health systems that have already gone through significant population health management transitions and who use big data routinely to improve their operations.We have been attending presentations by health systems that have started with the care provision of their own employees as a way to get some small population experience in the area and then moved on to larger populations they were able to attract. Just Google “population health management” and explore testimonials on how care provision has changed among these frontrunners. Some will definitely rock your world or at least give you a few “ah-ha” moments. We would enjoy hearing your comments and questions on this topic. You can reach Bill at felkebg@auburn.edu or Brent at foxbren@auburn.edu.     

IT Maximization for Population Health Management

Those of you who have been in the health-system setting for several decades have seen many changes. Some of the changes originate within the care setting, whereas many others are brought on by external circumstances. Even those who have been in health systems for only 5 years can recall a recent change in the organization that greatly impacted pharmacy. More change is coming. In this installment, we explore critical technology-related changes of which you should be aware.Health systems are increasingly finding themselves involved in something they describe as “straddling.” They are straddling current reimbursement drivers and practices while concurrently getting ready for population health strategies to replace what has been the norm for decades. We have been saying for years that we cannot imagine a scenario where we will use less technology in any foreseeable future. When it comes to operating a health system focused on managing populations, we cannot imagine anything more important than the effective use of the following top 5 technologies.     

Exercise Stress Testing in Patients with Chest Pain and Normal Coronary Arteriography: With Review of the Literature

Eighty of 654 patients studied because of chest pain were found to have normal coronary arteriography. Fifty of these completed submaximal treadmill exercise studies. The purpose of this study was to determine whether treadmill electrocardiography could obviate the need for coronary arteriography in the evalution of patients with undiagnosed chest pain. Of patients studied, 22% had typical angina pectoris, while 78% had atypical chest pain. The resting electrocardiogram was normal in 58% of patients, while 42% showed repolarization abnormalities. Submaximal treadmill testing was normal in 64%, incomplete in 12%, and demonstrated classic ischemic S-T depression in 24%. Our findings of 24% positive studies in patients with normal vessels and 12% incomplete tests suggest that stress electrocardiography may be of limited value in predicting the morphologic state of the coronary arteries in patients with undiagnosed chest pain.     

腺病毒介导的心肌蛋白激酶Cε基因转移导致心功能损害

目的本文旨在研究腺病毒介导的成年小鼠心肌直接PKCε基因转移对左室收缩功能的影响。方法使用标准方法建立表达PKCt基因的重组腺病毒载体。直接注射重组腺病毒到FVB／N和ICR小鼠心肌，对照鼠给予相同剂量空载腺病毒。Western免疫印迹测定PKCε蛋白质表达水平。用非开胸经颈总动脉插管的显微外科技术评价小鼠左室收缩功能。结果与对照鼠相比基因转移鼠心肌转基因PKCε蛋白质表达水平增加近4倍，基线左室最大收缩压、最大收缩速率（dP／dt）、-dP／dt明显降低，左室舒张末压、舒张压明显升高（P〈0．01），异丙肾上腺素激发后左室dP／dt剂量依赖的升高明显减弱（P〈0．01），PKCε基因转移鼠心脏／体重比也较对照鼠明显增加（P〈0．01）。结论腺病毒介导的、心肌直接的PKCε基因转移诱发了左室收缩功能的损害，导致了心肌肥厚和心衰。     

Testing the relation between dispositional optimism and conditioned pain modulation: does ethnicity matter?

Greater dispositional optimism has been related to less severe pain; however, whether optimism is associated with endogenous pain modulation has not yet been examined. The beneficial effects of dispositional optimism often vary according to cultural dynamics. Thus, assessing optimism–pain relationships across different ethnic groups is warranted. This study sought to examine the association between optimism and conditioned pain modulation (CPM), and test whether this association differs according to ethnicity. Optimism and CPM were assessed in a sample of healthy, ethnically diverse young adults. CPM was determined by comparing pressure pain thresholds obtained before and during exposure to a cold pressor task. All participants completed a validated measure of dispositional optimism. Greater reported optimism was significantly associated with enhanced CPM, and the strength of this association did not vary according to individuals’ ethnic background. These findings suggest that an optimistic disposition may potentiate endogenous pain inhibition.     

Processing of vestibular inputs by the medullary lateral tegmental field of conscious cats: implications for generation of motion sickness

The dorsolateral reticular formation of the caudal medulla, the lateral tegmental field (LTF), participates in generating vomiting. LTF neurons exhibited complex responses to vestibular stimulation in decerebrate cats, indicating that they received converging inputs from a variety of labyrinthine receptors. Such a convergence pattern of vestibular inputs is appropriate for a brain region that participates in generating motion sickness. Since responses of brainstem neurons to vestibular stimulation can differ between decerebrate and conscious animals, the current study examined the effects of whole-body rotations in vertical planes on the activity of LTF neurons in conscious felines. Wobble stimuli, fixed-amplitude tilts, the direction of which moves around the animal at a constant speed, were used to determine the response vector orientation, and also to ascertain whether neurons had spatial–temporal convergence (STC) behavior (which is due to the convergence of vestibular inputs with different spatial and temporal properties). The proportion of LTF neurons with STC behavior in conscious animals (25 %) was similar to that in decerebrate cats. Far fewer neurons in other regions of the feline brainstem had STC behavior, confirming findings that many LTF neurons receive converging inputs from a variety of labyrinthine receptors. However, responses to vertical plane vestibular stimulation were considerably different in decerebrate and conscious felines for LTF neurons lacking STC behavior. In decerebrate cats, most LTF neurons had graviceptive responses to rotations, similar to those of otolith organ afferents. However, in conscious animals, the response properties were similar to those of semicircular canal afferents. These differences show that higher centers of the brain that are removed during decerebration regulate the labyrinthine inputs relayed to the LTF, either by gating connections in the brainstem or by conveying vestibular inputs directly to the region.     

Hip and knee muscle torque and its relationship with dynamic balance in chronic ankle instability,copers and controls

ObjectivesWe compared hip and knee isometric muscle torque between individuals with chronic ankle instability (CAI), those who have sustained one ankle sprain with no ongoing problems (copers) and healthy controls. Our secondary objective was to compare balance between groups and investigate the relationship between muscle torque and balance.DesignCross-sectional study.Methods22 CAI, 20 copers and 22 uninjured participants were tested. Isometric torque (normalised to body mass (Nm/kg)) was measured using a rigidly-fixated hand-held dynamometer. Balance was assessed with the Y-balance test.ResultsKnee and hip flexor and extensor, and hip adductor and abductor muscle torque was less in individuals with CAI compared to controls (standardised mean difference (SMD) >1.2). Hip and knee flexor and extensor muscle torque was less in CAI participants than copers (SMD: 0.69–1.1). Hip external and internal rotator torque did not differ between groups. There was no difference in hip or knee muscle torque between controls and copers (SMD: 0.01–0. 54). Balance was impaired in CAI participants compared to copers and controls in all directions. There was a strong positive correlation between posterolateral Y-balance test performance and torque of the hip adductors (r = 0.53), flexors (r = 0.52) and extensors (r = 0.50).ConclusionsIndividuals with CAI have weak knee and hip muscles compared to copers and controls. Hip strength was shown to be related to posterolateral balance performance. Future studies may investigate the effect of hip and knee strengthening exercise on ongoing ankle problems, such as episodic giving way in individuals with CAI.