Healthcare | BAO | NetherlandsUniversitair Ziekenhuis Antwerpen (UZA) - (University Hospital of Antwerp)How can we improve the care and prognosis for patients diagnosed with rare diseases?For this University Hospital, a rare-disease diagnosis platform allows for an earlier, quicker and more accurate diagnosis by integratingboth medical expertise and data mining toolsThe Opportunity What Makes it SmarterOne of the biggest challenges in treating rare The University’s rare disease diagnosis platform allows for an earlier,diseases (those that affect fewer than five quicker and more accurate diagnosis by integratingpeople in 10,000) is the provision of an both medical expertise and data mining tools. Rules areearly diagnosis. Because of the generated much faster and more accurately through a predictive model basedrarity of their disease, patients may not be on known patient data. In comparison with a pure rule based system, adiagnosed early enough for the most combination with data mining tools provides both higher sensitivity and moreeffective treatments. UZA wanted to be able specificity. The solution can serve as an intelligent and dynamicto diagnose and treat these rare diseases knowledgebase on rare diseases. The improvement in the quick diagnosis and treatment of rare diseases can mean the difference in the lives of patients.earlier and more effectively. To do so, itneeded to be able to access and useinformation from many sources. Real Business Results • Rules are generated more quickly and accurately using a predictive model based on known patient data • The solution can serve as an intelligent and dynamic knowledgebase on rare diseases, improving the quick diagnosis and treatment of rare diseases • Compared with a pure rule based system, a combination of rules and data mining tools provides both higher sensitivity and more specificity ―The improvement in the quick diagnosis and treatment of rare diseases can mean the difference in the lives of patients.‖ – Geert Smits
Healthcare | Business Analytics & Optimization | Southern EuropeCiudad Real HospitalWhat if you could know in advance which patients would benefit most from initial interventions?A Spanish hospital is using predictive analytics to make significant improvements in the treatment of severe eating disorders.The Opportunity What Makes It SmarterThe hospital wanted to identify positive The ability to effectively handle and analyze data is essential to diagnosing illnesses earlier and speeding patients to recovery. Ciudad Real Hospital implemented a powerfuland negative prognosis factors in predictive analytics solution that enabled its practitioners to establish reliablelong-term monitoring of patients forecasting, control and early diagnosis variables for patients withbeing treated for serious eating severe eating disorders. The solution provides more accurate initialdisorders, such as anorexia and bulimia.Because such disorders affect almost 3% of patient evaluations, and has helped the clinical staff identify specific subgroupsSpains population, the goal was an urgent one. within the total patient population for whom initial interventions should lead to moreBut due to the high number of variables that successful treatment outcomes. The solution is also pointing the way towards new linespotentially factor into prognosis, the hospital had of research. For example, in supporting studies on the link between patient motivationbeen unable to execute the complex statistical and treatment effectiveness, the solution has discovered a direct link between patientsanalysis required to identify those that were expectations (e.g., feelings of despair) and poorer outcomes, even when other variablesmost important. A more powerful solution was previously identified as being able to predict treatment responses were controlled.needed. Real Business Results • Enabled 100% improvement in data handling for more accurate initial patient evaluations helping to develop more successful treatment outcomes • Uncovered specific links between patients’ expectations and treatment results • Helped identify new lines of research to be explored • An estimated 5-10% improvement of efficiency and effectiveness treatments of several chronic diseases ―In our opinion we were provided with enough support and it met our needs to incorporate this solution into the work we were beginning.‖ – Dr. Luis Beato Fernández, Ciudad Real Hospital
Healthcare | Information and Analytics | EuropeHospital Santa BárbaraWhat if you could find patients at high risk for serious disease by looking at analytic data?A hospital in Spain uses statistics and data analysis to identify key risk factors, improve diagnosis and treatment, use resources moreefficiently and effectively, and give patients a better quality of life.The Opportunity What Makes it SmarterLike many large research hospitals, Hospital Sometimes leg pain is just that. Sometimes it’s deep-vein thrombosis (DVT), aSanta Bárbara in Spain has amassed a large blood-clotting condition that may not be discovered until clots reach the lungs—often with fatal results. But researchers at Hospital Santa Bárbara have been able to useamount of research data and a wealth of statistics software to extract research data as well as patient records, and analyzeinformation on past and present patients. that data to more effectively target which patients are at risk for chronic, hard-to-However, the hospital was often at a loss detect diseases. By using statistical analysis, researchers came up with a morein terms of how to use that data to effective diagnostic model for DVT, pinpointed that 44 percent of colon cancer patients were between 75 and 79 years of age, and determined that chronicimprove processes and outcomes. obstructive pulmonary disease patients with a BODE rate of greater than 7 had anResearchers and hospital staff wanted to be 80 percent mortality rate within 48 months after diagnosis. With insight from in-depthable to extract critical data from various analysis, this hospital and others like it can more effectively screensources and analyze it to better diagnose patients for these serious conditions and others, advise preventive measures before disease takes hold, and even create new devices and treatments based onailments, refine treatments and innovate with both new research and past experience.new devices and procedures. Real Business Results • Established a new, reliable diagnostic model for DVT, expected to enable earlier diagnosis and treatment in high-risk patients • Helped researchers determine that age is the biggest risk factor in colon cancer patients, enabling staff to more effectively target tests to more high- risk patients • Reduced the cost of colon cancer diagnosis by 99 percent with targeted testing • Enabled researchers to isolate obesity as a key risk factor for chronic obstructive pulmonary disease, helping doctors get patients on the track to good health early ―Based on diagnostic models for chronic illnesses, we can provide clear evidence of risk factors and prescribe more effective treatment for individuals, resulting in better health outcomes.‖
Healthcare | Information and Analytics | AustraliaMetro Spinal ClinicWhat if your patient could show you what pain looks like?Metro Spinal Clinic, a pain management clinic in Australia implements an online patient data collection system that enables patients todescribe their pain symptoms more graphically and allows faster, more accurate diagnosis and treatment with statistical analysis.The Opportunity What Makes it SmarterMedical offices have gotten by with What causes chronic pain? Sometimes it’s obvious, but sometimes getting to the root of painpaper-based patient information systems for takes a little more digging and a lot of hindsight and research. One chronic pain managementyears. Done well, they can be quite efficient, clinic in Australia is diagnosing and treating pain with a new solution based on online databut a manual system will never match the collection and statistical analysis. Instead of filling out two-dimensional paper questionnaires, patients complete an online survey where they can describe their pain on a graphicalspeed and accuracy of an online data representation of the human body. This and other information gives physicians a more visualcollection process. One chronic pain clinic in look at patient pain. When combined with historical case data and peer discussions of painAustralia recognized that its paper-based management, staff can more accurately diagnose pain, refer treatment andpatient data process was taking too long, raise red flags when something isn’t right. Current patients benefit from fast treatment, andboth to input data and to find that data when future patients can benefit from the ever-growing database of information and analysis. The newdoctors needed it—and when patients are in system alleviates pain for the clinic as well, saving thousands of dollars in administrative costspain, even a few minutes is too long. The and reducing staff labor.clinic wanted a more efficient system, butalso wanted more analytical power to Real Business Resultstake that patient data and analyze it formore insight into diagnosis and • Reduced total administrative costs at the clinic by 75 percenttreatment. • Cut the cost per survey from USD10.65 to USD1.14, a 90 percent decrease • Increased post-treatment questionnaire follow-up rates to 85 to 100 percent • Enabled physicians to diagnose and treat pain more quickly and accurately with real-time access to data and visual representations of patient pain Measuring our own patient outcomes gives our future patients more realistic expectations of the treatments, and by benchmarking ourselves, we can continually improve upon patient treatment options and care.
Healthcare | Information & Analytics | JapanA Large Japanese HospitalWhat if predictive analytics could treat liver disease?A Japanese hospital uses regression and decision-tree analyses of patient records to predict the effectiveness of specific treatments foreach individual patient.The Opportunity The Solution What Makes it SmarterDetermining why one treatment The solution captures detailed patient By analyzing more than 400 factors perworks for one patient’s liver records and aggregates them into a central patient and by cross-functionallydisease and not another’s is greatly database, which provides a wealth of data in aggregating that data, doctors are able to which to run decision-tree and regression identify the specific treatments that will yieldenhanced by building predictive analyses. Through the creation of predictive the best result for each for patient.models based on more than 400 models, based on the records of patientsfactors, such as age, sex, race, blood who have had liver disease, doctors aretype, blood sugar content, body build, able to determine which treatmentmedical history and lifestyle. The models options would be the most effectiveenable the hospital to more accurately for each individual patient.assess the percentage of curerates for specific treatments. Real Business Results • Improved accuracy of virus removal by approximately 43 percent • Enables patients to avoid unnecessary, expensive and painful treatments if they are deemed inappropriate by the model Insight Smarter healthcare is using predictive analysis to help fight infectious disease and improve individual patient care.
Healthcare | Information and Analytics | Northeast EuropeA cardiac medical research organizationWhat if the doctor’s job were already halfway done by the time a heart attack patient checks into the hospital?A cardiac medical research firm in the Netherlands helps paramedics diagnose and treat heart attack patients on the way to thehospital when it applies advanced statistical analysis and predictive analytics to research data.The Opportunity What Makes it SmarterIn medical research, behind every discovery is The critical window for treating a heart attack is within one to two hours after the initiala mountain of data. And much of this data is attack occurs. After that, patients require more invasive treatment and longer recovery, andcomplex; any number of variables can be a the heart may sustain more damage in the long run. That often means administeringfactor in medical treatment. No case is the treatment before a doctor even enters the picture. How does a paramedic recognize a heart attack and know treatment options? Using advanced statistical analysis and predictivesame, and every case must be considered. analytics software, one medical research company created an algorithm that tellsOne Dutch research organization doing work paramedics the probability that a patient is having a heart attack based onon prehospital treatment for heart attacks had symptoms, patient history and other factors. The program will then suggestthousands of doctor, hospital and patient the most appropriate prehospital treatment and also direct the ambulance to thesurveys to consider as well as treatment nearest hospital with full cardiac care facilities. The solution saves precious time and moneyoutcomes and ambulance records. To make and helps ensure that hearts keep beating strong for years to come.sense of this data and help create aprotocol for prehospital treatment, the Real Business Resultsfirm needed a way to perform advancedanalytics on complex human data, including • Expects to improve patient survival rates and recovery times by treating heartpredictive analytics and in-depth regression attacks sooner after onsetanalysis. • Stands to improve treatment accuracy with a proven methodology and algorithm for heart attack diagnosis and prehospital treatment • Expects to save hospital operating costs and patient expenditures by reducing the average length of stay We now have a world-class analytics platform that matches our world-class reputation as a research organization. We will continue to use SPSS to support our research and hope to make further breakthroughs that enhance patient care and improve outcomes across the whole spectrum of cardiology.
Healthcare | Business Analytics and Optimization | ItalyA leading Italian cancer research instituteWhat if a cancer research center could create individualized cancer treatments that would reduce the number ofunnecessary treatments while improving therapeutic outcomes?This Italian medical institute pioneers the use of advanced analytics to analyze insights from clinical data, combined with patientinformation, to create personalized treatment plans for its patients, helping it treat cancer and other diseases more effectively.The Opportunity What Makes it SmarterThe fact that one-size-fits all cancer treatment may Until now, ―personalized‖ treatments in cancer and other disease treatment have generallyresult in more than half of all patients receiving been based on clinical trial results, a doctor’s subjective memory of past cases, and evenunnecessary treatment helps bring the goal of intuition. Finally, true evidence-based, personalized medicine is being implemented atfinding the right treatment plan for each the institute, where an in-depth analysis of a patient’s personal makeup and diseasepatient into sharper focus. This leading Italian profile, combined with insight gained from the analysis of past cases and clinicalcancer treatment and research center wanted to guidelines, enables doctors to provide an optimal treatment plan for each patient. Theimprove patient care by tailoring treatment solution proactively shows the physician statistics on similar clinical cases, possibleapproaches to specific individuals. The institute alternative treatments and predicted outcomes for each, allowing the doctor to makeneeded the ability to analyze past treatments and a truly informed decision. One insight from the solution showed that, statistically,cases, and combine that information with the physicians tend to give more aggressive medical therapy to women who are sick aspatient’s personal statistics and disease profile, to opposed to men with the same problem. Knowing this, physicians can guard against suchcreate a fact-based treatment plan for over-treatment, ensuring that patients receive only the medicine and procedures they need.each patient. In addition, being able to analyze Real Business Resultsoverall outcome data would help the institute • Avoids unnecessary treatment (estimated to be up to 60% of all treatment) andprovide more cost-effective, efficient care delays in treatment deliveryfor its patients. • Creates tailored and personalized treatments, increasing the chances of successful outcomes • Improves hospital performance, both clinical and operational, by providing a ―big picture‖ view of treatment delivery, helping streamline processes and lower costs By providing physicians with vital input on what worked best for patients with similar clinical characteristics, the institute can help improve treatment effectiveness and the final patient outcome.
Government, Healthcare | Smarter Analytics | Central EuropeA government healthcare organization in Central EuropeWhat could you do if you had up-to-date healthcare cost statistics for an entire country at your fingertips?A government healthcare organization uses sophisticated statistical analysis to calculate fair prices for healthcare services under adiagnosis-related group (DRG) system while helping hospitals root out inefficiencies.The Opportunity What Makes it SmarterAs the organization responsible for Around the world, countries are working to standardize healthcare fees using diagnosis-relatedcalculating and recommending healthcare groups (DRGs). Though DRG codes help to create fair payment systems, they arefees in a Central European country, this complicated and dynamic, built on extremely complex calculations. This governmentgovernment organization must maintain organization has reined in the complexity by applying sophisticated statistical analysisunparalleled knowledge of clinical to vast amounts of data collected from every hospital in the country. The organizationtreatment paths and trends in the tested multiple data models to find an algorithm that effectively mirrors the country’shealthcare sector. The organization healthcare system. The continuing influx of data creates a feedback loop that refines thecollects and analyzes enormous amounts accuracy of the algorithm over time. With these powerful analysis capabilities, theof hospital data. Manual data collection organization can calculate relative weights to account for variations in hospital costs, monitorand spreadsheet calculations, however, macro patterns in treatment paths and identify true cost outliers that might signal a need formade it difficult to navigate the complex change in DRG codes. Hospitals also benefit from the insights, using the data to benchmarkalgorithm required to understand costs their costs and spot inefficiencies. For example, if a hospital sees that its costs for treatingand define fees. To increase accuracy heart disease patients far exceed the norm, it can take steps to find and fix inefficiencies.and speed, the organization neededpowerful statistical analysis Real Business Resultscapabilities. • Reduced the time to perform complex calculations of relative weights from 3 days to 5 minutes—a more than 99 percent improvement • Increased the frequency of analysis by 1,100 percent with one-sixth of the manual labor requirement • Shifted focus from data collection and processing to in-depth statistical analysis, yielding a clearer view of the healthcare system and more accurate DRG codes Achieving this level of accuracy and foresight in modeling and understanding healthcare costs is unthinkable when you’re limited to the calculations of a spreadsheet. The dynamic statistical analysis we have now enables us to do so much more when calculating DRG fees and relative weights.
Healthcare | Business Analytics | Western EuropeSESCAMWhat if a tool for scientific research also could help you bettermanage efficiencies and improve services?SESCAM is using a powerful analytics and optimization solution to more effectively manage and better focus itsclinical research while at the same time significantly enhancing the quality of the care it delivers to more than 2million people.The Opportunity What Makes It SmarterSESCAM has a large number of clinical research Detecting inefficiencies quickly across a large healthcare network is key to better resourcecenters with projects focusing on improving management and service delivery – but doing so effectively entails managing, and analyzing,diagnosis and treatment. The organization needed enormous quantities of data. Implementing a sophisticated analysis and asset management solution hasappropriate statistical and analytical tools to support vastly improved this health services ability to manage operations across a vast web of 6,000 doctors, 31these projects that could, at the same time, pharmacists, 80 dentists, and 7,000 nurses. In the health sector, the solution is helping the organizationcontribute to the more effective management of easily manage all this information, identifying potential problems and inefficiencies across hospitalall of its hospitals and health centers by processes and facilitating their resolution to improve quality of care. In the research field, the new solutiondetecting inefficiencies and enhancing the level is helping investigators in developing innovative devices to assist patients in their daily lives and toof service provided to clients. improve the cure rate of illnesses. For example, clinical researchers in the hospitals nutritional illness unit hope to improve the cure rate of individuals suffering from anorexia and bulimia, illnesses affecting an estimated 3% of the population. The solution’s predictive analytics tool has been of fundamental importance in enabling researchers to implement a long-term monitoring program of these individuals in which possible variables relating to these diseases are recorded and analyzed, with the goal of improving prognoses and treatment. Real Business Results • Improved the efficiency of managing the organizations vast network of healthcare facilities • Enhanced the quality of care by identifying and eliminating inefficiencies in hospital processes • Provided researchers a powerful statistical tool for the development of more ergonomic wheelchairs for paraplegics • Aided researchers in studying sensory capacity losses related to aging ―We are now in a better position to optimize patient care across our large network – one that conducts more than 13 million medical appointments and 200,000 surgical procedures per year, as well as managing 1.2 million hospital stays annually."
Healthcare | Business Analytics | AustraliaWesley Research InstituteWhat if you could use analytics to dramatically improve patient care and quality of life?Wesley Research Institute is deploying a powerful analytics tool that enables doctors to make better-informed decisions that resultin improved patient outcomes. What Makes It SmarterThe OpportunityHaving access to enormous volumes of patient Effective hospitals manage, integrate and analyze clinical and research data to tackledata, this medical research institute wanted to find complex problems and improve patient care. This institute implemented a statistics-baseda better way to leverage all this basic analytics solution that successfully collects huge amounts of data – including patientinformation to enhance patient outcomes. A demographics and data on discrete procedures, surgical complications, risk factors and post-core element of the institute’s research program is operative tracking – and then quickly analyzes it to establish clinical benchmarks, identifythe collection and analysis of large amounts of risk factors and improve treatment results. The solution uses powerful statistical analysesdata from multiple sources and in various formats. to evaluate the range of factors influencing successful medical treatments. This enables theThe data need to be carefully and accurately institute’s doctors to proactively modify protocols to improve quality of care: for example,managed and interconnected in order to create an doctors who are about to perform high-risk surgeries can view statistics on the risk ofaccurate picture of patient outcomes. Without mortality, based on patient demographics, and make better, more well-informed decisions oncomprehensive data collection and more behalf of their patients.sophisticated data analysis, the institute wasstruggling to gain deeper insights across patient Real Business Resultsgroups. • Improved patient care across the hospital – for example, by identifying trauma (bruising, bleeding and hematomas) caused by catheter use, which the hospital immediately addressed • Improved clinician productivity by providing doctors with access to accurate data across patient groups • Decreased time spent in the production and delivery of reports to clinicians • Provided clinical staff with a valuable resource for ad hoc queries ―By quickly and accurately analyzing large volumes of data, we are helping to enhance quality of care and improve patient outcomes. The solution is making an enormous contribution, not only to us but also to the larger healthcare community.‖