3. Some Definitions. Information is not a necessary adjunct to care, it is care , and effective patient management requires effective management of patients’ clinical data. Donald M. Berwick President and CEO, Institute for Healthcare Improvement There is no health without management, and there is no management without information. WHO-Gonzalo Vecina Neto, head of the Brazilian National Health Regulatory Agency Information is necessary to provide and manage health care at all levels , from individual patients to health care systems to national Ministries of Health (MOH). W.Tierney. Dir. Regenstrief Institute. So what is eHealth? The World Health Organization (WHO) definition: “ e-Health is the combined use of electronic communication and information technology in the health sector.”
31. After Hours Resource Utilisation - 1998/99 (PRH0s-UK.) 87% Unnecessary out-of-hours tests 80% Diagnostic uncertainty 79% Medico-legal protection 66% Avoid leaving work for colleagues 71% Prevent criticism from staff (especially Consultants) 76% Lessen anxiety and reduce stress levels 71% Agreed attempts should be made to reduce unnecessary testing McConnell AA , Bowie P . Health Bull (Edinb). 2002 Jan;60(1):40-3. Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity.
32. THE VARIATION PHENOMENON “ The variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to another.” D. Blumenthal. Editorial NEJM 331:1994;1017-8
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35. IHC TURP QUE Study-Grams excised vs. Time variation
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39. Better Health Worse Health Less state spending Less state spending Individual US States
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41. Variation 2008 The wide variation in medical prices within U.S. markets that creates an opportunity for transparency to reduce spending. This variation exists even for relatively common procedures. New Hampshire-2008 Average payment for arthroscopic knee surgery - $2,406 with a standard deviation of $1,203 in hospital settings and $2,120 with a standard deviation of $1,358 in nonhospital settings. Tu HA, Lauer JR. Impact of health care price transparency on price variation: the New Hampshire experience. Issue brief no. 128. Washington, DC: Center for Studying Health System Change, 2009. Massachusetts- Median hospital cost in 2006 and 2007 for magnetic resonance imaging (MRI) of the lumbar spine, performed without contrast material, ranged from $450 to $1,675.2 Massachusetts Division of Healthcare Finance and Policy. Measuring healthcare quality and cost in Massachusetts. ( http://www.mass.gov/Eeohhs2/docs/dhcfp/r/pubs/09/measuring_hc_quality_cost_mass_nov-09.pdf .)
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43. USING PHYSICIAN INPATIENT ORDER WRITING ON MICROCOMPUTER WORKSTATIONS. REDUCTION IN HEALTH CARE RESOURCE UTILISATION Physician inpatient order writing on microcomputer workstations-effects on resource utilisation. WM Tierney and others. JAMA 1993;269:379-383
44. USING PHYSICIAN INPATIENT ORDER WRITING ON MICROCOMPUTER WORKSTATIONS. REDUCTION IN HEALTH CARE RESOURCE UTILISATION Physician inpatient order writing on microcomputer workstations-effects on resource utilisation. WM Tierney and others. JAMA 1993;269:379-383 $3 million per year savings- (USA $65b)
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47. Nurse Physician Pharmacist Physician Pharmacy Nurse/Clerk Physician Pharmacist Patient Physician Dietician ADE Rate Route Nurse Dose Dilution Time Wrong drug Spelling Scheduling Transcribing Dosage Route Order missed Psychic Compliance Neural Age Gender Electrolyte Hepatic Race Weight Renal Past Allergic Reaction Absorption Drug/Drug Unforeseen Drug/Food Drug/Lab Expected Hemal Brand name vs.. Generic Drug Administration Errors Ordering Errors Patient Physiologic Factors Pharmacological Factors Cause and effect of potential causes of ADEs. (From L.Grandia. IHC,Utah-with permission)
48. Nurse Physician Pharmacist Physician Pharmacy Nurse/Clerk Physician Pharmacist Patient Physician Dietician ADE Rate Route Nurse Dose Dilution Time Wrong drug Spelling Scheduling Transcribing Dosage Route Order missed Psychic Compliance Neural Age Gender Electrolyte Hepatic Race Weight Renal Past Allergic Reaction Absorption Drug/Drug Unforeseen Drug/Food Drug/Lab Expected Hemal Brand name vs.. Generic Drug Administration Errors Ordering Errors Patient Physiologic Factors Pharmacological Factors Cause and effect of potential causes of ADEs. (From L.Grandia. IHC,Utah-with permission) 60% Administration errors Occur between written orders and nurse administration
49. Computerized surveillance of adverse drug events in hospital patients Classen DC, Pestotnik SL, Evans RS, Burke JP. JAMA 1991;266:2847-2851.
50. ADVERSE EVENTS -IDENTIFICATION AND PREVENTION Potential identifiability and preventability of adverse events using information systems. D Bates et.al J Am Med Informatics Assoc. 1994;1:404-411 “ Most hospitals rely on spontaneous voluntary reporting to identify adverse events, but this method overlooks more than 90% of adverse events detected by other methods............... Retrospective chart review improves the rate of adverse event detection but is expensive and does not facilitate prevention .”
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53. Intermountain Health Care, Salt Lake City, Utah, USA Overall antibiotic use: d ecreased 22.8% Mortality rates: decreased from 3.65% to 2.65% Antibiotic-associated ADE: decreased 30% Antibiotic resistance: remained STABLE Appropriately timed preoperative a/biotics: 40% to 99.1% Antibiotic costs per treated patient: decreased $122.66 to $51.90 Acquisition costs for antibiotics: fell 24.8% to 12.9% ($987,547) to ($612,500) Our case-mix index which measures patient acuity levels INCREASED during this period, meaning we were treating sicker and sicker patients while better utilizing the delivery of antibiotics. Pestotnik, S. L. Classen, D. C. Evans, R. S. Burke, J. P. Implementing antibiotic practice guidelines through computer-assisted decision support: clinical and financial outcomes.Ann Intern Med 1996 May 15
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55. Not all HIT are beneficial. There were also some instances in which relationships in the opposite direction were found; for example, electronic documentation was associated with a 35% increase in the risk of complications in patients with heart failure, though this may have been present because it was easier to find these events since better documentation was present. 1. Bates DW. ARCH INTERN MED/VOL 169 (NO. 2), JAN 26, 2009 Editorial 2. Amarasingham R, Plantinga L, Diener-West M, Gaskin DJ, Powe NR. Clinical information technologies and inpatient outcomes: a multiple hospital study. Arch Intern Med . 2009;169(2):108-114.
56. Questions. 1. Are the technologies—computer order entry, decision support, and clinical documentation—sufficiently mature that hospitals should be adopting them now? Bates: the answer is a clear yes for large hospitals. For smaller hospitals, which use a different set of vendors, the answer is less clear, but studies are currently under way that should provide additional information regarding this. 2. For clinical documentation, the benefits are still only beginning to be determined and are likely to be spread across a wide range of areas, but this will likely prove to be beneficial as well. Bates DW. REPRINTED) ARCH INTERN MED/VOL 169 (NO. 2), JAN 26, 2009 WWW.ARCHINTERNMED.COM Amarasingham R, Plantinga L, Diener-West M, Gaskin DJ, Powe NR. Clinical information technologies and inpatient outcomes: a multiple hospital study. Arch Intern Med . 2009;169(2):108-114.
57. Do the negative consequences of implementing HIT in hospitals overwhelm or wash out the positive ones? Current evidence is that they do not overall. EVALUATION is critical with technology after implementation and making multiple changes to it—points that are all too often ignored. Bates DW. ARCH INTERN MED/VOL 169 (NO. 2), JAN 26, 2009
69. WHO/Evelyn Hockstein At every monthly check-up patients are given their charts and hand-carry them to the nurse, clinical officer and other providers they are seeing that day. Updates to the chart are made at each station. WHO/Evelyn Hockstein Clinical officers like Lillian Boit provide most patient care and maintain charts. "The electronic record-keeping system allows us to provide care to more people and take better care of patients", she says. http://www.who.int/features/africaworking/en/index.html
70. WHO/Evelyn Hockstein Outreach workers download completed forms into Mosoriot clinic's data management system daily. Automated alerts flag any alarming new symptoms to the attention of the responsible clinical officer, or when a patient has missed an appointment so that outreach workers can find out what is wrong. An innovative home-care programme using hand-held computers is also being piloted in the region. Monica Korir, who is living with HIV and is trained as an outreach worker, interviews Paul Ekorok, 52, at his home in Captarit village and records his answers.
72. Besides antiretroviral drugs (which are provided by USAID), care by AMPATH cost only $175/patient/year in 2007 and is now less than $100/patient/year in 2009. P. Park, et al., Case Report: The Academic Model for the Prevention and Treatment of HIV/AIDS . Harvard Business School, Boston, 2008. In addition to the monthly, quarterly, and annual reports required by funding and agencies and the MOH, the AMRS also provides data to a robust multidisciplinary research program: Researchers from more than a dozen North American universities and Moi University currently have more than 30 ongoing studies in East Africa, supported by >$26 million in grants from U.S. federal granting agencies and various foundations.
81. OpenMRS sites – Spring 2010 http://openmrs.org/wiki/Summary_of_OpenMRS_Implementation_Sites
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83. Implementation Time Frames and support. It took us about 6 weeks … to configure our ER and Surgery modules in OpenMRS. … Thanks again to Andy at MVP and James at HAS among others for considerable guidance and support … There are only a couple of us working on this project at MSF with limited resources, and without the help of the implementers group we would have been stopped in our tracks. On June 1 we went live with the production database in Port au Prince. … the system is run by local staff with limited technical training . … Overall we have been impressed with the stability of OpenMRS on Linux; server reboots are sometimes necessary once or twice a day because of Tomcat memory errors. With three months of data in the system now and stability and output tried and true … Thanks. John John Brooks. Médecins Sans Frontières (MSF)/Doctors Without Borders
87. Features This is an incomplete list of OpenMRS features “out of the box”. Our many add-on modules make it easy to infinitely expand and extend the system. Central concept dictionary: Definitions of all data (both questions and answers) are defined in a centralized dictionary, allowing for robust, coded data Currently, the AMRS (Kenya) contains 50 million observations from 2 million visits to 23 AMPATH clinics by >100,000 HIV-infected patients. (Oct 2010) Google Workshop-OpenMRS® - Is a community-developed, open-source, enterprise electronic medical record system platform and the most widely used EMR in the developing world.
88. Features of OpenMRS Security: User authentication Privilege-based access: User roles and permission system Patient repository: Creation and maintenance of all patient data, Multiple identifiers per patient: A single patient may have multiple medical record numbers Data entry: With the FormEntry module, clients with InfoPath (included in Microsoft Office 2003 and later) can design and enter data using flexible, electronic forms. With the HTML FormEntry module, forms can be created with customized HTML and run directly within the web application. Data export: Data can be exported into a spreadsheet format for use in other tools (Excel, Access, etc.) Standards support: HL7 engine for data import Modular architecture: An OpenMRS Module can extend and add any type of functionality to the existing API and web app.
89. Patient workflows: An embedded patient workflow service allows patient to be put into programs (studies, treatment programs, etc.) and tracked through various states. Cohort management: The cohort builder allows you to create groups of patients for data exports, reporting, etc. Relationships: Relationships between any two people (patients, relatives, caretakers, etc.) Patient merging: Merging duplicate patients Localization / internationalization: Multiple language support and the possibility to extend to other languages with full UTF-8 support. Support for complex data: Radiology images, sound files, etc. can be stored as “complex” observations Reporting tools : Flexible reporting tools Person attributes: The attributes of a person can be extended to meet local needs
90. Not all smooth sailing! A number of unintended adverse consequences that have followed CPOE implementation. Unfavourable workflow issues, Continuous demands for system change, Untoward changes in communications patterns and practices Generation of new kinds of medical errors, Negative emotional responses to the system by clinicians. Physician resistance can derail costly, complex CPOE projects . Campbell EM, Sittig, DF, Ash JS, et al. Types of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2006 Sept-Oct;13(5):547-556.
91. One of the answers to these questions are to be found in the CULTURE OF MEDICINE Deeply rooted customs and training High standards of autonomous individual performance A commitment to progress through research-lead to advances in biomedical science and cures to millions. However ……. These advances have created challenges to safety not faced by other hazardous industries. Five Years After To Err Is Human. What Have We Learned? JAMA. 2005;293:2384-2390
92. “ It must be remembered that there is nothing more difficult to plan, more doubtful of success, nor more dangerous to manage than the creation of a new system. For the initiator has the enmity of all who would profit by the preservation of an old institution and merely lukewarm defenders in those who would gain by the new ones,” Machiavelli., Niccolo 1532.
These are defined goals required for any EMR system and are taken from the review if effective EMR developments that have occurred during the last 25-30 years,in Volume 54 of the IJMI in 1999.
Compliments previous slide.
In a 1999 review of the major EMR systems in the world that are the models for future EMRs, these were the data/information and performance values for the Regenstrief system in Indian. They emphasize that technology is not the problem for EMRs and information retrieval must function at these levels of recall time.
The next two slides document the results of the studies (I & II) into negligence by the Harvard group and reflect outcomes of the clinical decision making process. Clinical decision making is not the sole element here but can be seen as a major factor.
Slide taken from the keynote address by Larry Grandia (IHC, Utah) demonstrating the relationship of health care costs to the remainder of the economy. In Western economies the effect of health costs on the economy are virtually the same and are not dependent upon the health funding mechanisms whether public, private or both.
Another manifestation of the information overload problem is variation in health care. Brent James from IHC in Utah (based on the HELP computer-based record) defines random variation and inappropriate variation and the reasons why this occurs and possible solutions.
The variation found in average hospital costs for UNCOMPLICATED TURP. All patients had the same co-morbidities.
Same TURP group with LOS variation.
Same group demonstrating the variation in surgeons relating the time taken to remove a specific mass of prostate tissue. The study demonstrated that there was variation within the individual surgeons activities. All surgeons considered they were performing the same prior to the study.
Brent James summary of the the reasons for practice variation. All these factors involve complex decision making in an information rich environment.
This study in 1973 looked a the variation in health care across 20 health care locations in Vermont where it was considered care was of similar standards. The authors found a wide variation in the use of clinical resources for items that cost less than $20 each-refer to study by Johns and Blum. We see here the continuing link between decisions-resource utilization-costs.
Core decision support tools for all E.H.Rs regardless of the complexity of the decision support required.
Tierney’s study into the use of of a longitudinal CBPR to reduce resource utilization. (Refer to the Johns and Blum study on costs, resource utilization, and clinical decision making)
Tierney’s study into the use of of a longitudinal CBPR to reduce resource utilization. (Refer to the Johns and Blum study on costs, resource utilization, and clinical decision making)
Title change to match next slide.
This is a flow diagram of all the elements that are potentially involved in the production of and Adverse Drug Event. It demonstrates all the points where decision making can fail.
This is a study of 38,000+ patients over an 18 month period comparing ADE detection between the paper record and the EMR which is able to integrate most of the data and information contributing to ADE. Column 1-traditional paper record. Column 2-nurse enhanced reporting from the paper record. Column 3- Computer surveillance-columns 2 & 3 (610) are life-threatening events. Column 1.-traditional record 9 ADE Column 2. – Nurse scrtutinization of the record 21 ADE Column 3 – EMR integration of ALL elements contributing to the ADE. 731 ADE of which 703 were considered life-threatening!
Conclusions drawn from a similar study to the previous slide by Bates from Brigham's & Women's Hospital in Boston. It is self-explanatory and confirms the inadequacy of the paper chart and its ability to support clinical decision making and is costly.
Slides 114-122 display the results of the above study. It is important to look at this study from many aspects. The size of the study (not possible with a paper-based record-time, costs, data accuracy), the alteration of process, the measurements of outcome, the definition of patient cohorts. This is the only institution that has shown the stabilization of antibiotic resistance – a major problem with antibiotic usage. The study also demonstrates that the rewards from CBPR systems are the result of an INCREMENTAL process with verification of benefits and or failures along the way.
At the time, there was a lot of work to be done.
OpenMRS was created in response to HIV/AIDS. Indiana University School of Medicine had been collaborating with Moi University Faculty of Health Sciences (Eldoret, Kenya) for over a decade when their focus, by necessity, turned toward the HIV pandemic.
But patients like Musa, who you’ve already met, showed that HIV was a treatable disease. The problem wasn’t how to treat HIV, but how to scale that up to 100,000 and millions of patients. That kind of scale could only be obtained through effective information management.
So, OpenMRS is an EMR, a data model (some folks have chosen to simply use our data model and build their own system), an API, an HIV system, a TB system, a Primary Care system, a strong developer community, and a vibrant implementer community. We’re all in this together.
And we’ve already seen evidence of the flexibility of a platform approach. Folks in Maryland have wired a different primary care system atop the OpenMRS API, so docs work within another system, but all data are stored within an instance of OpenMRS. Shaun Grannis developed a disease surveillance system using OpenMRS. In Skid Row of Los Angeles, OpenMRS is being used to manage data for homeless patients with TB. And Paul’s pediatric decision support system has been rebuilt and now runs within OpenMRS.