Name: Steven

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Bio: Steven H. Shaha, Ph.D., DBA, is a Professor at the Center for Policy & Public Administration, and the Principal Outcomes Consultant for Allscripts. Dr. Shaha received his first doctorate in Research Methods and Applied Statistics from UCLA and has taught and lectured at universities including Harvard, University of Utah, UCLA, Princeton, Cambridge and others. An internationally recognized thought leader, lecturer, consultant and outcomes researcher, Dr. Shaha has provided advisory and consulting work to healthcare organizations including the National Institutes for Health (NIH), and to over 50 non-healthcare corporations including RAND Corp, AT&T, Coca-Cola, Disney, IBM, Johnson & Johnson, Kodak, and Time Warner. Dr. Shaha has presented over 200 professional papers, has over 100 peer-reviewed publications in print, over 35 technical notes and two books. He served on the 15-member team that authored and piloted the Malcolm Baldrige National Quality Award for Health Care, and he contributed to the Baldrige for Education.

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    Reducing pressure ulcers and falls with collaboration and a programmable EHR

    April 26th, 2016

    Some time ago (i.e., 2008), the Centers for Medicare & Medicaid Services (CMS) implemented policies aimed at eliminating reimbursements for several “never events.” CMS estimated that avoidable adverse events and errors cost $300 million annually – not to mention unnecessary patient suffering – and so needed to end. High among the focal never events were falls, including falls with injuries, and decubitus or pressure ulcers (PUs), especially those of higher severity, risk and cost, Stage III or Stage IV.

    Yet no computer can turn a patient to avoid a pressure ulcer, nor catch a patient to avoid a fall. So how can a programmable electronic health record (EHR) make a difference?

    Conquest of pressure ulcers and falls is not simple, but can an EHR help?

    PUs are the second most common of the never events, estimated to occur for as many as 34 of every 1,000 patients, and cost $10,845 per case. So it is mission critical that healthcare organizations do all they can to avoid acquisition of PUs, and reduce the rate of patient harm and financial damage.

    Many factors come into play by which the EHR can help beyond antiquated paper-based risk assessment, including encouraging key assessments through the EHR, alerting when needed assessments are missing, then advising clinicians of patients at risk as identified by the EHR. Also the EHR can remind bedside clinicians to turn patients at risk on a frequent cadence.

    Falls are not any easier to avoid than PUs. The more severe falls are those in which a patient suffers an injury. CMS has long ago determined to provide no reimbursement for falls. And falls, particularly those with injury, are extremely costly – recent estimates of the cost of a fall with injury are as much as $14,000 per event. What’s more, a fall with injuries can result in extended length of stay by as much as an additional six days which has led to estimates as high as $35,000 per fall with injury.

    The EHR-enabled solution

    With a locally programmable EHR, clinicians can finally join with IT professionals in the long sought after collaborative partnership. Clinicians select the crucial indicators for never events, along with the EHR-accomplished computations needed, to enable notifications that will lead to favorable actions. The IT professionals then program the EHR to automatically and continuously assess each and every patient for risks, all through embedded medical logic modules (MLMs) within the EHR.

    When clinicians and IT professionals collaborate, we see great examples of reductions in PUs at Allscripts client sites with a programmable EHR:

    • 70% reduced at an Alabama hospital
    • 69% down at a Florida hospital – and four consecutive quarters of zero acquired PUs
    • 74% fewer at a Connecticut hospital
    • 79% less at a United Kingdom hospital, and zero Stage IV cases for 14 months now

    Examples of reductions in falls with injury post-implementation of the programmable EHR at the same four Allscripts implementations include:

    • 57% reduced at a Connecticut hospital
    • 70% lower rate at an Alabama hospital
    • 84% fewer at a Florida hospital
    • 46% less at a United Kingdom hospital

    The collaborative partnership of clinicians with their local IT professionals works, even within the United Kingdom’s completely different healthcare model and role mixture. And the culture of these organizations changes from clinician compliance to shared collaborative solutions. All enabled by the nature and capabilities of the locally programmable and adaptable EHR.

    What more could any organization want?

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    Fewer alerts reduce the amount of “think time” for clinicians

    March 10th, 2016

    Drug-drug interaction (DDI) alerts are supposed to help clinicians reduce risk of prescribing medications that may result in adverse drug events. The adverse events reflect medications that, when prescribed together, can cause bad events and outcomes for patients. But it is well proven that “alert fatigue” does harm, and in this case, negatively impacts any favorable intents or efficacy of avoiding DDIs.

    Alert fatigue, including for DDIs, happens because of the onerous number of alerts considered low-value by clinicians and information overload, causing prescribers to override or ignore alerts as often as 98% of the time. Another reason for limited impact of DDI-related alerts is that, for some specialties, the prescribing of the drug combinations tagged as DDI risks are commonplace and already proven to be good, efficacious medication approaches – cardiology among the most frequent.

    The medical staff at Holy Spirit Hospital (Pennsylvania, U.S.A.) studied this issue, and focused on reducing DDI-related alert fatigue while simultaneously making the fewer alerts even more effective. The aim was to increase responsiveness to fewer DDI alerts, and better affect clinical decisions. Specifically the team focused on DDI alerts that clinicians frequently overrode as mere interruptions, or that they did not read for long enough to reflect any effect on their decisions.

    Thus, with the focus on less alert fatigue, but higher consideration and processing, three benefits were quantified:

    1) Numbers of alerts fired

    A team of pharmacists and physicians identified DDI alerts by specialty that physicians/prescribers overrode about 97% of the time. They then determined they could reduce certain DDI alerts for specific specialties without compromising patient safety or outcomes. As a result, the total number of alerts decreased by 11.0% organization-wide, reducing alert fatigue. The reduced total alerts also led to improved time spent considering and responding to the fewer remaining alerts.

    2) Alert burden as measured by “think time”

    A major metric next became the amount of time clinicians invested in responding to DDI alerts. Calculated as the minutes between alert appearance and closure of the alert window, “think time” had two interpretations:  first, the time for clinicians to process and consider the alert. Second, the time to address the issue without time wasted in further considerations or avoidance.

    Results showed fewer alerts yet significantly improved think times. The cumulative change in time was computed organization-wide to equal 26.8 hours per year of reduced waste in prescriber time. While arguably a small number, that is the cumulative effect of alert processing beyond the pre-change condition, ensuring better decision-making and heightened efficacy.

    Specifically, think time increased for clinicians within specialties that usually prescribed the drugs labeled as DDI combinations – because they knew best treatment involved the combination of the medications ordered, and that outweighed any risk. Additionally the think time decreased and order changes increased for clinicians in specialties that did not typically prescribe the drugs involved concurrently.

    3) Decision changes in prescribers

    Increased think time for users who are more familiar with these drug combinations is interpreted that prescribers are weighing the fewer alerts more carefully, actively and attentively than before.

    Organizations can overcome alert fatigue and favorably increase alert efficacy when local clinicians and their IT professionals collaborate to fine-tune alert-assisted clinical decision support (CDS) within electronic health records (EMRs or EHRs).

    Focused reduction in numbers of alerts, along with targeting maximized efficacy, optimizes relevance and thus improves alert consideration, enhances decision making and saves time. This research confirmed that local, collaborative in-house adaptation of the EHR lead to better resolution of important challenges and achievement of priorities: the keys for helping clinicians help patients.


    Editor’s note: This research is currently in peer review for publication in an industry journal.

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    How a U.K. hospital reduced cardiac arrest rates by one-third

    December 21st, 2015

    Locally programmable, adaptable Electronic Patient Records (EPRs)* are the most justifiable approach for a host of reasons. It’s the only approach that empowers true collaboration between clinicians and IT professionals. Also, the only approach that can reflect current and newly evolving challenges and concerns clinically or otherwise.

    As a result, these EPRs lead to real and sustained improvements in clinical outcomes, such as reducing sepsis and length of stay.  As one clinician said, “If the EPR is not programmable here, then we can’t work together for improvements, and it’s just another black box dictating generic medicine to unthinking, compliant professionals.”

    One of the ultimate tests of versatility is to see if an EPR works in “our” unique healthcare environment rather than as a “black box” solution from elsewhere. For example, can an EPR that meets complex U.S. compliance requirements – such as Meaningful Use – also exceed expectations of a hospital in the United Kingdom … or any non-US community?

    Concern: Rising complexity of cardiac conditions

    A cardiology specialty hospital in the United Kingdom analyzed eight years of data about the number of cardiac arrests occurring among its non-ICU inpatient population. The first three years showed a pretty stable number, rising slowly.

    Then the next two years showed the number creeping upward at an alarming rate, reflecting the global trend in health care. No surprise that, as healthcare organizations strive to deliver care in the most cost-effective models and settings, patients are more often tracked toward non-hospital locations. So hospitals today only admit the sickest patients, and the complexity of patient populations keeps increasing year after year.

    Statistical analyses predicted a rising frequency for arrests, a trend projected to triple within another two years from the study date. However, instead of just accepting this trend, blaming clinicians, or adding more clinical staff, this hospital determined to reduce arrests through improved clinical care using its EPR.

    Solution: Using EPRs and Medical Early Warning System (MEWS) to reduce incidence of cardiac arrest

    By clinician design, the EPR was adapted to help clinicians intervene earlier and avoid cardiac arrests when avoidable.  Through Allscripts Sunrise™ they continuously compute and monitor patient risk levels. First, the clinicians in the organization identified the evidence-based characteristics that indicate increased risk, including as heart rate, respiration rate, temperature, blood pressure and relevant lab results. Next, the IT professionals programmed the EPR to continuously compute risk for every patient and advise caregivers correspondingly through the early warning system – commonly labelled as MEWs.

    As a result, this hospital successfully reduced arrest rates by 33% in only two years, regaining the levels experienced 4-5 years before. The estimated savings (cash release) is estimated at $144 million for reduced arrest-related interventions and care. As an additional benefit, mortality rates house-wide decreased to 16.7%, reaching rates lower than five years pre-EPR, even though the patient population reflected a more severe case mix.

    The hospital has seen the MEWS benefit other clinical areas, with reduced fall rates down 14.1% and falls with injury down 45.7%, and pressure ulcers down more than 50% with zero stage 4.

    Of course, a computer or EPR cannot intervene clinically to reduce unfortunate events. But when the computer provides a locally credible MEWs, designed and requested by the clinicians, early warning of impending undesirable outcomes, clinicians are able to intervene more quickly and appropriately on the patient’s behalf.

    Customization is more than just changed spelling with “customisation”

    This is a great example of how powerful a programmable, adaptable EPR is in the hands of clinicians and IT professionals as a team. And it is as effective in the United Kingdom as it is in the United States, even without identical healthcare models.  When an EPR is this flexible and customizable it can accommodate all kinds of local realities and real differences.

    Assuming all healthcare locations and organizations are interchangeable is delusional. Differences reflect organization size, specialty mix and approaches, operational layouts and patient population, to name a few uniquenesses.

    With relevant adaptability healthcare organizations can target and improve clinical results with substantive financial benefits and ROI. Bottom line, when it comes to our loved ones we expect better than mere black box medicine, and ours are safer when a programmable, adaptable EPR is available to clinicians.

    *Editor’s Note: Electronic Patient Record (EPR) is another term for Electronic Medical Record (EMR) or Electronic Health Record (EHR).

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    What does your EHR really cost?

    October 22nd, 2015

    Time and time again, we hear horror stories of electronic health record (EHR) systems that far exceed budgetary expectations of their healthcare organizations. Failure to estimate all of the expenses accurately has steep long-term effects on operating costs, as indicated in Steven R. Eastlaugh’s recent hfm® article*.

    It’s important to look at total cost of ownership – TCO – which goes well beyond the initial software, hardware and annual maintenance costs. For that reason, every well-managed healthcare organization purchases EHRs based on comparative TCO and then tracks the elements of TCO thereafter. Most often, executives do not fully account for long-term EHR expenses, such as ongoing cost of licenses, upgrade fees and staff dedicated to support.

    These cost factors vary widely by EHR vendor and solution. Using hospital data from HIMSS Analytics, the nonprofit research arm of the Healthcare Information and Management Systems Society (HIMSS), Eastlaugh compared TCOs for the three leading EHR vendors, adjusting for organization size, and referring to them as A, B and C.

    In Eastlaugh’s research, he includes two key factors in TCO that are often neglected, and since commonly ignored, become the unforeseen sources of catastrophic cost overruns:

    • FTE Support Costs – Hospitals using Vendor C employ twice as many staff dedicated to EHR support as those using Vendor A. Eastlaugh calculates that a 500-bed hospital that selects Vendor C instead of Vendor A can expect an additional 16 FTEs, which could amount to $16 million in incremental costs and TCO over a 10-year period.
    • Upgrade fees – Major upgrade costs for Vendor A averaged between 20%-22% of the original contract price, whereas it averaged 33%-35% for Vendor B and 40%-49% for Vendor C, constituting another major TCO overrun, when unanticipated.

    Eastlaugh draws further conclusions from the HIMSS Analytics data, reflecting the average annual revenue of hospitals using each system:

    The bottom line is this: If the average hospital using Vendor C’s system were instead to use Vendor A’s system, the difference in FTE support costs and upgrade fees would deliver an approximately 27.7 percent increase in hospital operating margins – from 2 percent to 2.6 percent. As a result, the average 350-bed hospital in the HIMSS Analytics sample could save $2.3 million a year, or $23 million over 10 years in ongoing EHR system costs in these two areas alone.

    It does not take much to decipher the most likely vendors to match those in Eastlaugh’s study. When best healthcare executives follow Eastlaugh’s unbiased, TCO-driven recommendations, their EHR decisions will lead toward better organizational performance, financially and clinically. TCO provides important considerations in making best EHR decisions.

    Financial pressures remain the sobering reality for healthcare organizations, even more so during the transition toward value-based-care models. It is more important than ever to carefully consider the total cost of ownership when making EHR decisions.

    * Source: “The total cost of EHR ownership” by Steven R. Eastlaugh, ScD. hfm®, a publication of the Healthcare Financial Management Association ( February 2013.

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    Fewer alerts, higher response rates, safer patients

    September 1st, 2015

    Applications of electronic health record (EHR) technology and capabilities often do NOT consider the needs of pediatric settings. As healthcare clinicians know, pediatric patients are not just small adults. Children have unique and different needs and interventions than their adult counterparts, so that many adult-ready HIT solutions do not necessarily fit comfortably with pediatric patients or caregivers.

    One of our clients, a pediatric specialty hospital, had been successfully using the EHR with full computerized physician order entry (CPOE) for three years. As part of its ongoing emphasis on continuous improvements, the organization programmed and adapted the EHR to better manage dosing-related computations. Concurrently, the organization was focused on reducing alerts due to alert fatigue issues clinicians were experiencing.

    Would clinicians value computer-generated recommendations for dosing?

    The guiding imperative was simple:  Clinicians value and therefore act on owned, computer-generated recommendations for dosing. On the other hand, if pediatric caregivers don’t have a programmable EHR, they are forced to rely either on old-school pocket notes and computations to determine best dosing OR on black-box-like, EHR-imposed, inflexible requirements from elsewhere without any local or innovation reflective capabilities.

    This facility had the benefit of a programmable EHR, Allscripts SunriseTM. These clinicians had their EHR locally programmed to calculate doses for each child invisibly in the background, each reflecting clinical documentation, such as age, weight, and other drugs onboard. Dosing recommendations for prioritized drugs were programmed into the EHR for genuine clinical decision support for prescribers in real-time. The dosing recommendations appear within informed, intelligent order sets for prescribers. Then clinicians use the EHR’s real-time, ad-hoc analytics and reporting capabilities to monitor efficacy and guide continuous improvement thereafter.

    Again, the imperative was for the EHR to generate dosing recommendations for improving clinician decisions and their impact on pediatric patients. To do so, the organization engaged local clinicians in defining best practices to improve responsiveness to alerts and adherence to recommendations.

    Analyses revealed statistically significant and favorable results for the locally-defined computer-generated dosing recommendations for three metrics:

    31% fewer alerts for questionable doses

    The alert rate was 31.2% lower (p<0.001) for pediatric orders through the computer-computed order sets versus alerts with CPOE alone. Prescribers with computer-assisted dosing had fewer errors. The alert rate was already under 10% due to previous CPOE- and EHR-based alert-reduction improvements, so this reduction, while statistically significant, was not as immense as it might have been in usual circumstances.

    Prescribers twice as likely to respond to alerts

    While alerts were less frequent, prescribers were 122.8% (p<0.001) more likely to respond to alerts received than before – that’s more than double the likelihood of responding versus prior to the implementation. Prescribers were more attentive to alerts, perceiving the alerts valuable and relevant, even when they reflected computationally-based recommendations. This response rate verified that former black-box-like alerts were viewed as nuisance alerts, and sources of “alert fatigue”, and thus had lower responsiveness.

    59% fewer medication-related incidents

    Finally and most importantly, the percentage of orders that led to medication-related errors or incidents fell to 59.2% fewer (p<0.001) than before the newer alert-based approach.

    With guidance and decision-making assistance through the EHR, prescribers received fewer alerts, were more likely to respond to and act on those alerts, and provided their patients with significantly fewer errors and incidents. Bottom line, when the EHR) computes the dosing, with local definitions and engagement, the results are more precise and lead to significantly and substantially fewer errors.

    Only four of every 10 errors that would have previously occurred now reached a patient. The organization improved quality of care through the power of the programmable EHR. And that programming reflected locally specified parameters, not those dictated by any distant HIT vendor or former model not reflecting openness to innovation and improvement.

    It remains curious and mysterious to me how so many leaders in health care are willing to hold fast to blind adherence by clinicians to inflexible EHR-vendor-determined standards of care as a measure of quality or excellence. Programmable and adaptable EHRs, ready for innovation and progress in care models and delivery, seem a more desirable ideal.

    For Sunrise clients interested in learning about more of our clients’ best outcomes, visit our Client Outcomes Collaboration Program on ClientConnect.

    Editor’s Note: Learn more about how Sunrise helped Phoenix Children’s Hospital with dose range checking in a recent blog post: Kid-sized doses in an adult-sized world

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    7 keys to success with clinical decision support

    July 8th, 2015

    I realize and admit I have biases. One bias is that I believe the principle reason for the healthcare IT industry is to optimize patient-clinician interactions to heal and keep people healthy. Another bias is that without solid financials and organizational performance, everyone ultimately loses. My third bias: I believe clinicians whom we trust with our very lives, and IT experts, are trained professionals and should be trusted to optimize electronic health records (EHRs) as a local team.

    EHRs should provide solid clinical decision support (CDS) to help clinicians optimize patient decisions and interactions, and help organizations exceed performance goals. CDS puts clinicians at the forefront for deciding, coding, monitoring and updating.  Here are the seven most powerful CDS-focused EHR characteristics for assisting clinicians with their decisions and documentation:

    1. Programmability

    Programmability ensures that hospitals can remain in sync with evolving needs and capabilities relevant to their specific populations and structures. Health care is innovation-rich and dependent, and it is always evolving and improving. While vendors may provide excellent starting points for CDS “within today’s science and delivery models,” programmability enables adaptation and innovation and progress without vendors dictating what can or should be done.

    Programmability should be locally achievable so no one is held hostage by EHR vendors. The clinician-IT partnership is the key to automating and standardizing progress, with leadership and governance as key components.

    2. Data Accessibility

    Best improvements are achieved by seeing data-driven proof of need for change, and of support for better approaches. Ad hoc and routine data searches are crucial to both, yet most EHRs are primarily “unanalyzable data repositories” with intentionally severe limited data access. EHRs should never be designed for data acquisitions and storage, and code capture conversion capabilities alone.

    Clinicians need access to data to study outcomes retrospectively, make best decisions reflecting “better,” and monitor the impacts thereafter. Clinicians and analysts can use data to identify successful approaches and then program those approaches for more routine usage. Data access will ensure that best clinical decisions are found, monitored to ensure routineness, and documented for ensured best care for all patients and practitioners.

    3. Population and Patient-type Adaptability

    While most healthcare communities and organizations are arguably “generalizable,” every organization remains unique in layout and staffing, and the healthcare challenges of each community and population varying between somewhat to very unique:  ethnics, genetics, socio-economics and healthcare models. Clinicians and healthcare organizations should be able to adapt EHRs and CDS to the uniqueness of each organization location and population set.

    4. Specialty Adaptable

    When those we care about need health care we realize the importance of specialists. Yet some EHR vendors resist or restrict adaptability to specialty-related needs, preferring instead to provide the fewest possible capabilities to meet the greatest numbers of patient types and diseases. Ideally, organizations should enable specialty-supporting CDS through their EHRs so clinicians can adapt to patient needs.

    5. Innovation Ready

    Best practices will change – it is a guarantee – and progress is the hallmark of health care.  As innovations become available, the EHRs and CDS should be capable of adapting to newer approaches with better outcomes. Some practitioners may resist change, and some organizations as well. Regardless, progress-related capabilities ought to enable ideal CDS, and adapt to outcomes-enhancing innovations, all without any vendors dictating what can or should not be done for better care and results.

    6. Open and Integratable

    Progressive healthcare organizations should not be held hostage by dictates from any EHR vendors that all applications must come from them alone as the single source. Such arrogance raises more questions than answers, at least for the logic that not one vendor “does it all.”

    Open platforms mean freedom to choose. An Open EHR empowers organizations to both fill gaps in capability as innovation requires, or as specialties need. Clinicians and IT professionals are more motivated, intelligent and capable in an Open environment, while closed environments communicate that “only the EHR vendor can be trusted.”

    7. Value to Clinicians

    Everyone’s needs are best met when clinicians make best decisions and document them well. For this reason, I believe that EHR selection should prioritize the needs and value to clinicians, and thus meet everyone’s needs. Yet too many leaders and IT professionals choose what will help organizational performance as the first priority, and then demand clinicians show compliance and adaptability as the primarily metrics of success.

    My biases frame why I remain convinced that organizations can find all of these attributes in Allscripts SunriseTM, with CDS at its very core.

    What else would you add to the list of what makes CDS successful at your organization?

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    How to avoid “alert fatigue”

    June 11th, 2015

    Some of us remember the old days and the art of tuning a radio. We finely adjusted the dials as we approached channels to get a clear signal, filtering out all the static and noise. The classic case of optimizing the signal-to-noise ratio.

    The art of optimizing our signal-to-noise ratio is alive and well when it comes to electronic health record (EHR) alerts. It’s important that alerts are relevant and meaningful to clinicians, or we run the risk of too much information becoming just noise. That’s the near-perfect definition of what we’ve come to refer to as “alert fatigue” among clinicians, which can be hazardous for everyone involved.

    Meaningful alerts help improve clinical results

    Here’s an example of how an organization not only optimized the signal-to-noise ratio, but conquered alert fatigue and improved clinical results. And all by addressing alerts for the need to complete the risk assessments for Deep Vein Thrombosis (DVT) and Venous Thrombolytic Embolism (VTE), which, for the purposes of simplicity in this blog post, I’ll refer to as blood clots.

    Restated simply: The circulatory system works best when we move a lot, as is known by all clinicians.  But when patients are bedridden, blood can pool and form clots, especially in the lower extremities – legs. If a clot dislodges and reaches the heart, lung or brain, the results can be catastrophic.

    Because patient safety is a top priority in hospitals, and DVTs and VTEs were considered avoidable through good care, the U.S. Federal Government no longer reimburses for care related to these preventable blood clots.  Smart organizations are using EHRs to remind clinicians to conduct timely DVT/VTE risk assessments.

    One of our clients, a teaching hospital, started its prevention measures by alerting clinicians to complete all the recommended evidence-based risk assessments, once per shift, per patient. The result was over 25,000 alerts a month due to missing assessments which the organization hoped alerts would  improve through compliance.

    For the first four months, the numerous alerts accomplished very little in improved compliance mainly because the clinicians predictably treated them as just noise. Busy clinicians clicked past them and compliance with risk assessments did not improve.

    Strategies for addressing “alert fatigue”

    There are different strategies for resolving the need for a host of risk assessments without inattention, and EHR capabilities are a key strategy. Some EHR systems are unfortunately much too rigid, however, and offer few options for tailoring alerts, or for altering the EHR to do the needed risk assessments automatedly. Some EHRs will even freeze up until clinicians comply with alerts, preventing them from doing anything else in the EHR.

    However, this organization beautifully illustrates a higher-order strategy to resolve “alert fatigue.” After four months of struggling with low compliance rates, it customized its approach to DVT and VTE risk assessments. It redesigned data and clinical workflows including collection of key risk-related data elements of information upon admission, which made it easier to complete the risk assessment as an automated benefit of a programmable EHR computer system.

    As a result, alerts were reduced by 97.4%, cutting out all of the noise, which improved adoption and compliance:


    More relevant alerts for blood clot assessments helped one organization increase compliance by 145% and reduce rate of VTEs by 62.6%


    Why it matters

    As a direct result of this customized information-related workflow, the organization not only eliminated alert fatigue … it reduced DVT and VTE blood clot rates by 62.6%. Put another way, an estimated 167 people annually did not experience VTEs who statistically would have because of this organization’s work to improve care leveraging the locally programmable, adjustable and adaptable EHR.

    Sometimes we get distracted with meeting healthcare requirements, and we forget the reason behind them. We hit a certain percentage target and move forward with a smile and congratulations. But we should stop and recognize that there’s deeper meaning on a human level, and that the programmable EHR can make better, safer care more commonplace with less alert fatigue and better data and documentation.

    That’s a list of reasons why I’m a passionate advocate for Allscripts Sunrise™. Clinicians and their IT professional partners can team up to program the EHR solution to filter out the noise and provide optimal signal.  Organizations can tune in to the most relevant information for their clinicians, their role in the community and their patient populations. They can use the EHR as a powerful tool to help them improve the efficiency and efficacy of care. And that means better health for your loved ones, you and me.



    Coordinated obstetric care reduces complications, infant mortality rates

    May 27th, 2015

    Sharing crucial information across care settings throughout a care-community is increasingly mission-critical, especially in the unpredictable world of obstetrics and deliveries.

    Hospital Labor and Delivery (L&D) departments endure dramatic volume fluctuations and many opportunities for complications, all generally unanticipated even though expected. Meanwhile, clinics and obstetricians routinely see and assess prenatal patients, capturing data from delivery dates to risks, then again the same women postpartum, now with their infants.

    However, clinicians in these two interdependent settings generally share NO data, causing re-assessments or re-documentations on both ends, and compromising capabilities to perceive and meet risk-related needs.

    After investing in Allscripts SunriseTM as its interoperable electronic health record system (EHR), one organization demonstrated the value of care coordination for mothers and infants. Clinicians and information technology (IT) professionals teamed up to fine-tune applications to their local needs and to create ideal implementations, with coding accuracy as a crucial business priority.   The goal was to share data from obstetrician prenatal clinics (OBs) with L&D, and then back again post-delivery, so that best care is always provided based on complete understanding of what has gone before.

    Now, L&D continuously receives all prenatal information and updates electronically regarding the mother and fetus from OB clinics, including mother and/or  baby risks, foreseen complications, anticipated delivery dates, etc.  One OB observed:

    “Standardization of the OB content has greatly increased the efficiency in how we view patient data. We don’t have to spend extra time asking the same questions for each visit. This is especially important when our patients arrive to Labor & Delivery and things are happening quickly.”

    L&D now staffs for anticipated volumes and clinical requirements with 93.9% “ideal staffing” rates – ideal being not over- or under-staffed, and unsurprised preparedness for complications. Postpartum, the OB clinics now receive all L&D and hospital-based postpartum data for mother and infant(s), including risk-related information and assessments.

    The organization achieved significant improvements within six months, including:

    Labor & Delivery Department

    • 3.8% reduced infant mortalities
    • 5.9% reduced infant complications
    • 43.3% reduced maternal unanticipated complications or risks
    • 14.1% reduced L&D repeat risk assessments
    • 3.9% reduced staffing-related costs

    Obstetric Clinic

    • 38.4% reduced patient wait times for office visits
    • 31.2% reduced patient wait time during office visits
    • 40.3% increased OB-with-patient time during visits – unanticipated and unperceived by OBs
    • 34.7% reduced unanticipated postpartum complications
    • 8.9% increased postpartum compliance to follow-up clinic visits

    Clearly mothers and infants are better off with this technology-enabled coordinated care. And the organizations and caregivers benefit as well: it reduced costs per mother by 12.8% across the hospital and clinic, and reduced hassles for clinicians while improving their knowledge for patients.  It also reduced postpartum diagnostic tests and costs by 8.4%.

    This success reflects the ability to transfer clinically pertinent information between hospitals, clinics, emergency departments, and others. Clients have had similar proven successes with other diseases, such as diabetes, sepsis, pulmonary diseases (e.g., COPD), pediatric asthma and more. So the ability to communicate throughout a community and care continuum ensures everyone gets best outcomes.

    Editor’s Note: Steve recently shared this example by invitation to the United Nations, as part of the Infopoverty World Conference, a platform focused on to fighting the effects of poverty and national and regional misfortunes through innovative uses of Information and Communication Technologies (ICT). You can watch his presentation (from 35:22 – 49:29) here.

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    EHRs help bedside caregivers provide better care with higher satisfaction

    May 13th, 2015

    Bedside caregivers provide most direct care for patients, from monitoring and continuity – no one seems to argue with that assertion. Still most electronic health records (EHRs) focus primarily on the combination of organizational performance and doctor-related costs of care, clinical decision efficacy, error reduction and documentation. What bedside caregivers do and need is often an afterthought.

    The healthcare industry needs the powerful impact of EHRs that help bedside clinicians more.  EHRs need to enhance bedside caregivers with intelligence-driven capabilities. Five healthcare organizations rigorously undertook six studies of how Allscripts SunriseTM affects bedside caregivers with nurses as the focal point – primarily both as the mainstays of the bedside presence, as well as proxy perspectives for the team of bedside non-physician caregivers.

    What was found, and published in peer-review*, adds enormous substance to the favorability of best-EHR impacts on bedside caregivers.  The findings substantiate the positive impact of EHRs for nursing and bedside caregivers when the EHR is specifically structured and customized to better meet their needs.

    1. Computer-based provider order entry (CPOE) capability reduces medication errors

    CPOE is among the most touted EHR capabilities, enabling orders for medications, labs and images with precise, transcription-free, immediate order communication and tracking. Optimal CPOE also ensures immediate, automated communication with bedside caregivers for execution.

    So in best EHRs, CPOE is not just about paperlessly sending orders – CPOE is also about relevant and timely communication with Nurses and bedside caregivers.  CPOE is also about ensuring highest safety and quality for caregivers, especially when supplemented by such technological advances as bar-code medication administration.

    One organization found that nursing-related medication errors fell 71.7%, falls decreased 83.6%, and acquired pressure ulcers grades 3 and 4 decreased 69.2%.  Exceptionally good nurses became even better.

    2. Fewer errors improve satisfaction ratings

    Another organization verified reduced errors and quantified favorable patient responsiveness. It also tracked satisfaction changes pre-versus-post-implementation for one year. It found significant improvements from 11.8%-38.5% for ratings on items related to safety, clinical management, documentation and communication.

    3. Efficient EHR workflows can give clinicians more time with patients

    It has long been asserted – and appropriately so – that bedside caregivers can be more vigilant and clinically effective with increased patient-proximity time. Caregivers can be more clinically expert with more time for observation, awareness and action, versus time spent on other non-care-related chores and tasks.

    Two studies (600+ shifts) confirmed 44-minute decrease in documentation time away from patients, and a 21-minute decrease in overall documentation time.  The summary confirmed that the EHR-enabled improvements resulted in nearly 50%-50% mix for nurses in patient-direct versus time away, which was a statistically significant improvement from the nearly 40%-60% patient-direct-indirect work mix before EHR implementation.

    Interestingly, these results stand in direct contrast to a HIMSS Analytics industrywide survey of nurses who use a variety of EHRs that are not customized to their needs. This contrast underscores the importance of using EHRs that are locally programmable to meet the needs of bedside caregivers and their patients.

    4. Faster response to signs of deterioration

    Two additional studies verified significantly reduced length of stay attributed to faster response to symptoms of deterioration and timeliness of intervention. Significantly reduced readmissions were also documented and attributed to improved care continuity during stay, followed by improved discharge preparedness and instructions.

    Allscripts Sunrise has the characteristics critical to success for improving nursing and bedside efficacy. The ability to adapt to locally and organizationally important criteria is necessary for achieving success.

    * Source: Mythbusters. Authier, Denise; Bradshaw, Pamela; Hickman, Louise; Shaha, Steve // Health Management Technology;Oct2012, Vol. 33 Issue 10, p10

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    Don’t settle for traditional outcomes

    April 2nd, 2015

    Over the past 30 years, we’ve seen upsurges in requirements for organizations to measure quality and continuous improvement. While these methods for sustaining continuous improvement are maturing, unfortunately many organizations remain satisfied with traditional outcomes. They settle and stop moving forward.

    Some lean on the proven traditional approaches to continuous improvement because they have to.  Their EHRs will not allow ad hoc accessibility to data, or development of locally interesting yet unique priorities and interests.

    Continuous improvement should be just that – continuous and focused on locally crucial improvement needs. When it is, everybody wins – organization, clinicians and patients. When it is neither continuous nor capable of local improvement, everyone loses (even though it may feel like winning). Leadership often encourages and celebrates better outcomes, when they should be aiming even higher.

    The quality of your outcomes depends on what type of EHR you have

    To continuously improve, it’s important to have an electronic health record (EHR) that adapts to your specific needs. Continuous improvement should not be about the organization and clinicians adapting to the EHR, but about the EHR being continuously adaptable to local needs.

    Following a meta-analysis approach, I studied the comparative impact of four continuous improvement approaches.  I gathered data from independent studies of 16 hospitals representing three different types of EHRs, on the condition we would not name the organization or data source.

    The four approaches to continuous improvement included:

    1) Traditional (no EHR) – include methods such as Lean and 6-Sigma.

    2) Compliance-based EHR – Requires users to adopt and comply with vendor-specified standards and not allowing locally-developed improvement to be programmed into the EHR.

    3) Clinical-based EHR – Enables some local adaptation, though limited options for users to program EHR for local needs.

    4) Locally programmable EHR – Enables organizations and key users to fully adapt the EHR, whether to meet local processes, role definitions, governmental or community imperatives, or even unique patient population needs.

    The first group of four hospitals represented the non-EHR approach, reflecting the traditional study-implement-monitor-restudy-repeat approaches.  The 32-month results were encouraging:

    But contrast these results with outcomes from a group of organizations using EHRs, and the degree of improvement is quickly less inspiring.  Even though the EHR in this case represents a compliance-focused, non-programmable framework, the improvements are more impressive:


    Note that impact was continuously better until the hospitals reached a new vendor-specified standard. Then improvement ceases.

    Next I analyzed 32-month data from four hospitals using a different EHR, this one being more clinical-based and offering some limited programmability:


    We see a longer train of improvement for greater end results.  Even limited programmability made better progress possible.

    What these hospitals are missing

    Unfortunately, in each of the previous examples the local leadership was oblivious to the second-rate outcomes they were achieving.  Next I looked at what happens when hospitals work with a fully adaptable, locally programmable EHR – I won’t name the other vendors, but these next graphs all represent Allscripts SunriseTM clients:

    Every hospital on the locally programmable EHR achieved continuously better outcomes most quickly.

    Each line represents a hospital that is able to adapt the EHR themselves to whatever else works best for the organization and community.  The orange and blue lines show more rapid improvements because they represent hospitals that used analytics, too.

    Essentially an EHR is to an organization what personal technology is to any person – the more I can make it fit my needs, the more fruitfully I will use it and benefit from it.

    With trust and the right EHR, better outcomes are possible

    Whether this exact same pattern applies to all organizations, or to all clinically-related or financially-related outcomes has yet to be studied.

    Things look good in the first charts, where adoption and compliance are the only measures of success. But look how much better an organization can do when they trust their clinicians and IT people to adapt the application to meet local patient and clinician needs.

    I realize the easiest thing to do is use compliance-based options and demands.  Forced adaptation to what the EHR delivers as best care is easy to implement and easy to enforce from the top down.  But organizations that are truly committed to continuous improvements need to take the leap of faith, and use an EHR that enables far better outcomes.

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