Medical Informatics in the Management of Diabetes Essay Example

Medical Informatics in the Management of Diabetes Essay Example Medical Informatics in the Management of Diabetes Paper Medical Informatics in the Management of Diabetes Paper Studies showed that the cost for quality health care increases but it is becoming inefficient when it comes to delivering service. One of the reasons for this is the cost of recordkeeping, a major component in health care. The Health Information Technology (HIT) was introduced for accurate processing of reports and to keep track of the programs and needs of the health care consumers. It will tackle problems posed by cost, access and quality. It refers to computer hardware and software that stores, retrieves and shares health care information for use by health care providers and consumers in decision making. HIT has many benefits in store for the health care system. Health care consumers will be assured that they can get the best medical goods and services from health care systems. They can cut costs while at the same time receiving the best health care there is. Diseases will also be prevented in their early stages. Storing patient medical records electronically allows for improved accuracy and privacy of records. It is easier to track individual records when needed and the health care providers can input or change data easier and faster. Besides being cost effective, storing records electronically helps doctors in making quicker and better informed decisions. The patients will also be assured that their medical records and in good hands. But this form of keeping records may be inefficient at times. A provider might input data on the wrong record. Electronic medical records are not protected, and this leads to a more serious problem. The biggest problem that seems to arise from this is on privacy. With a click of the mouse, it is easier to look into someone’s personal health information and it can be passed around without the patient knowing it. This would make many patients vulnerable especially when their records are used for purposes other than medical. REFERENCE Sennet, Cary and Daniel Wolfson. (2006). Taming Health Care Inefficiency. Diabetes is a serious medical condition characterized by the inability of the body to regulate glucose levels in the blood. In Type 1, which is usually childhood onset, the pancreas does not produce insulin, a hormone that is necessary for cells to absorb glucose and utilize it for metabolism. In the more common and usually adult onset Type 2, the body produces insulin but at insufficient levels or cells in the body have a reduced sensitivity to the hormone, hence unable to absorb insulin (American Diabetes Association, 2008). The high glucose levels or hyperglycemia in diabetics is the primary cause for life threatening complications which include heart disease, kidney failure, nerve damage, damage to blood vessels, necrosis in the extremities resulting in amputation, stroke, ketoacidosis leading to diabetic coma and prolonged emptying of gastric contents (American Diabetes Association, 2008). Diabetes also significantly increases the risks to developing glaucoma, cataracts and if unmanaged, eventually leads to blindness. The treatment for diabetes is a complex process which involves resolving the high blood glucose levels, preventing minor complications from becoming full blown, managing symptoms and major complications as well as instituting appropriate lifestyle changes. Medications and insulin shots, regular retinopathy and urine ketone tests, continuous blood glucose monitoring, diet and exercise and proper foot care are some of the treatment methods (Schaffer, 2008). Because there is currently no cure for the disease and treatment is both rigorous and long term, diabetics need to learn self-monitoring skills for ketones and blood glucose levels, self-administration of insulin and medications, how to buy and store diabetes supplies as well as weight and nutrition management in order to avert emergency conditions (Schaffer, 2008). When serious complications arise, these are usually treated through intensive medications, surgery and kidney transplants in the event of irreversible kidney damage. Current Equipment Used by Diabetics There are classes of equipment that are currently being used by diabetics and their caregivers in treating the disease. Bio signals, biomedical devices, insulin pumps, continuous glucose monitoring devices, insulin pens and pumps, retinopathy screening machines, blood glucose monitors, lancets and lancing devices are such equipment where most can be used in the home setting and limit the need for daily visits to the health care facility while providing effective treatment. Insulin pumps, such as the MiniMed Paradigm ® 722, are devices consisting of a computer, a pump with insulin supply and a catheter inserted into the abdominal fat of a diabetic (Hurd, 2007). They are meant to replace individual insulin shots and allow greater control over insulin dosage to fit one’s activity, food intake and glucose levels. Dosage information is entered into the computer which pumps the exact amount through the catheter. Insulin pens, like the HumaPen ® LUXURAâ„ ¢ HD, are used to self-administer insulin and have pre-filled cartridges of up to 300 units, a needle at one end, a plunger at the other and look like pen markers (Douglass, 2008). Indicators in the pen provide information as to the range of doses that can be administered, amount of insulin left, the date/time/dosages of insulin taken recently or how to fix wrong dosage instructions. The MiniMed Paradigm ® REAL-Time Continuous Glucose Monitoring System is a small device composed of glucose sensors, a transmitter, an alarm and a small computer that are continually attached to the abdomen (Minimed. com, 2008). The sensors transmit a blood glucose measurement per minute that transmitted and displayed on the computer screen as well as mean measurements per 5 minutes, glucose level trends and their direction. Abnormal glucose levels trigger the alarm. Blood glucose monitors may either come as blood glucose meters such as PocketChem EZ or chemical test strips which are visually compared to a color chart to obtain a reading. Glucose meters require a test strip and a lancet. A drop of blood is smeared on the strip to be fed into the meter which supplies a measurement (Douglass, 2008). PocketChem EZ can store more than 200 downloadable test results with time and dates indicated. A lancet is a metal with a needle like end used to prick the finger or alternative sites in the body to obtain minute amounts of blood for testing and are held in lancing devices to facilitate usage. An example is the Vitalcare Lancet Device which looks like a pen and uses Vitalcare lancets or other standard lancets (Douglass, 2008). The sterile lancet is placed in a holder inside the pen and slight pressure directed at the trigger will release it. A digital retinal camera such as the Canon CF-1 is used for retinopathy or diabetic eye disorder screening. After eye drops are applied to enlarge the patient’s pupils, high resolution diagnostic images of the posterior portion of the eyes are obtained for analysis (Canon. com, 2008). The CF-1 comes with a Retinal Imaging Control Software and conforms to the Digital Imaging and Communication in Medicine interface allowing images to be integrated into other image management systems as well as allows the device to connect to various network configurations (Canon. com, 2008). Biosignals are any measurable electrical and non-electrical signals in the human body while biomedical devices entail the use of living organisms and their processes in the treatment of disease (Singh, 2006). An application with regards to diabetes is the technique of attaching a pouch which contains transplanted insulin-producing cells into large veins where they can proliferate and yield much needed insulin (Kanaujia, 2007). Modern Technologies Used in the Treatment of Diabetes With the wealth of data that a diabetic has to contend with in dealing with his/her condition, organizational tools are necessary in order to generate accurate, useful and timely information for a more efficient and effective self-management of the disease in coordination with her health care team. For instance, the diabetic has to acquire information regarding the anticipated effects of foods she plans to eat or activities she wants to engage in on her glucose levels. The diabetic then has to calculate the dosage of insulin that she should receive and when. She may have other medications that have their own dosage instructions. She also has regular schedules for urine tests and retinal screening. She has to keep tabs of her supply of insulin, lancets and test strips. She has to regularly monitor her glucose levels, vitals signs and her weight. She has to adhere to physician recommended foot care and other treatments. Advances in the field of medical informatics has allowed for the integrated use of information, communication and medical technologies in managing patient data and has enhanced many other facets of health care. However, medical informatics does not only benefit the health care team but also individual patients such as diabetics. The diffusion of technology allowed systems and devices to be adapted and manufactured for patient use. A set of managerial tools that collectively work to enable a much simpler but more precise diabetes self-management is the Diabetes Pilotâ„ ¢. It is a software designed and tested by diabetics to replace the conventional method of manually writing down data onto paper and has three versions – the Diabetes Pilot Desktop, the Diabetes Pilot for Palm Handhelds and the Diabetes Pilot for Pocket PC (diabetespilot. com, 2007). The Diabetes Pilotâ„ ¢ enables patients to log various data such as their glucose level readings, compliance with their insulin and other drug regimens, meals taken per day, fitness workouts accomplished, blood pressure measurements, results of routine tests as well as other pertinent information into reports (diabetespilot. com, 2007). The Medication Totals report, Exercise Totals report and the Blood Pressure List report are examples of listings of different data categories. The software also provides a database containing information on the nutritive values of thousands of foods and through the Meal Listing and Daily Food Summary reports, aids the diabetic in determining the amount of carbohydrates, calories, fats, proteins, fiber, sodium, cholesterol, vitamins and other minerals they obtained from individual meals or from all meals taken during the day (diabetespilot. com, 2007). This provides for an effective way of establishing and maintaining a diet suitable for the diabetic. Like the MiniMed Paradigm ® REAL-Time Continuous Glucose Monitoring System, the Diabetes Pilotâ„ ¢ also features tabular or graphical representations of blood glucose level pattern in order for the diabetic to easily perceive the direction of such patterns and adjust her insulin dosages or medications accordingly. Mean measurements by hour, by day or by month can also be calculated as well as the highest and lowest readings taken. Options regarding what system the diabetic wishes to use to categorize data are also available and aimed at establishing significant trends in self care over a period of time. Because the Diabetes Pilotâ„ ¢ is not meant to replace physician care entirely with self-care, all records made by the diabetic can be communicated to her health care team for evaluation and further recommendations using a variety of methods. A similar product but only applicable to Palm PDA is the Universal Tracking System (UTS) Diabetes Palm PDA software. Among its features, data can be transformed into MS Excel format and has an E-mail Report application so that the patient can send the file to her physician (Universal Tracking System, 2007). Automatic calculation of insulin dosage based on glucose measurement is also accomplished. Aside from allowing data entry, the UTS can turn out a summary of the reports and interactive graphical representation of data which will enhance patient and physician decision making with regards to dosage adjustments. Color coding also effectively indicates if the glucose level is normal, high or low and in mg/dL or mmol/L units (Universal Tracking System, 2007). A similar database of food but also includes medications and insulin types is further provided. Medical Informatics’ Areas of Interest in the Treatment of Diabetes The largely fragmented health care system allows for many weaknesses with regards to caring for diabetic patients in that efforts are largely centered on acute conditions and serious complications rather than on chronic disease management. This poses significant challenges even for those in the area of medical informatics. In response, successful efforts have been made to develop a diabetes registry population management application aimed at integrating the chronic disease registry (an informatics system) into the clinical workflow (Zai et. al. , 2008). In terms of decision support, efforts have also been made in developing a model system for classifying knowledge in the area of insulin regimen specifications and dose adjustment in consideration of such factors as diabetes type, patient age, current treatment, glucose profile, physical activity, food intake and desirable blood glucose control Gogou et. al. , 2001). When a physician makes a decision, he relies on practice, intuition and knowledge. However, a knowledge classification system will enhance and standardize decision-making. With available organizational tool devices for diabetic patients, the need to integrate patient derived data into her medical records in the hospital’s EMR system is imminent. One such project is the Informatics for Diabetes Education and Telemedicine (IDEATel). Patients are equipped with a specialized computer called the Home Telemedicine Unit (HTU) with the following: 1. a video camera and microphone for videoconferencing with physicians, 2. a home glucose monitoring device which directly uploads readings, 3. accessibility of the patients’ self-derived medical data, and 4. patient access to educational websites (Starren, et. al. , 2006). With regards to diagnosing diabetic retinopathy via digital retinal cameras, the accuracy of human visual analysis can be increased with the aid of computers. The presence of fluids in the macular region of the eye is a major indicator of retinopathy and its detection is a significant diagnostic activity wherein computers may extend assistance (Walter, Klein, Massin and Erginay, 2002). An algorithm for exudate detection is currently in use which employs the characteristic high grey level variation and contours of exudates with the optic disc as point of reference (Walter, Klein, Massin and Erginay, 2002). Finally, biosignaling is also an important concern of medical informatics. In a recently developed application known as the Emer-Loc, emergency medical situations for diabetic patients may be speedily responded to from the use of location-based biosignaling (Maglogiannis and Hadjiefthymiades, 2007). The system employs sensors affixed to the patients body, a micro-computing unit which processes sensor readings and a central monitoring unit to coordinate data flow (Maglogiannis and Hadjiefthymiades, 2007). Global positioning system (GPS) is used to locate the patient if her signals correspond to an emergency condition. List of References American Diabetes Association (2008). Type 1 and Type 2 Diabetes. Retrieved 27 October 2008 from diabetes. org/type-1-diabetes/treatment-conditions. jsp. BD diabetes. com (2008). Insulin Pens. Retrieved 27 October 2008 from bddiabetes. com/US/main. aspx? cat=1id=254. Childrenwithdiabetes. com (2005). Auto-Lancet Adjustable. Retrieved 27 October 2008 from childrenwithdiabetes. com/d_06_2a7. htm. Diabetespilot. com (2008). Diabetes Pilot: Information Management for People with Diabetes. Retrieved 27 October 2008 from diabetespilot. com/index. php? ref=5gclid=CPiG5b2TwpYCFQeO1Qodm iMAzg. Douglass, K. (2008). New Products. Diabetes Forecast 2008 Resource Guide. Retrieved 27 October 2008 from diabetes. org/uedocuments/df-rg-new-products- 0108. pdf. Gogou, G. , Maglaveras, N. , Ambrosiadou, B. V. , Goulis, D. and Pappas, C. (2001). â€Å"A Neural Approach in Diabetes Management by Insulin Administration†. Journal of Medical Systems 2(25): 119-131. Retrieved 27 October 2008 from http://portal. acm. org/citation. cfm? id=609076. Hurd, R. (2007). Insulin Pump. Retrieved 27 October 2008 from nlm. nih. gov/ /ency/imagepages/18035. htm. Kanaujia, M. (2007). New Device to Treat Diabetes and Fulminant Liver Failure. Retrieved 27 October 2008 from medgear. org/page/4/. Maglogiannis, I. and Hadjiefthymiades, S. (2007). EmerLoc: Location-Based Services for Emergency Medical Incidents. International Journal of Medical Informatics 76(10): 747-759. Retrieved 27 October 2008 from find-health-articles. com/rec_pub_16949860-emerloc-location-based-services-emergency-medical-incidents. htm. Minimed. com (2008). MiniMed Paradigm Real-Time System. Retrieved 27 October 2008 from minimed. com/products/insulinpumps/components/minilink. html. Schaffer, A. (2008). New York Times Health Guide: Diabetes. Retrieved 27 October 2008 from http://health. nytimes. com/health/guides/disease/diabetes/overview. html. Singh, V. (2006). Introduction to Biosignals. Retrieved 27 October 2008 from ee. unimelb. edu. au/ISSNIP/multimedia/events/workshop22_09_06_final. p df. Starren, J. , Hilliman, C. , Weinstock, R. S. , Shea, S. and IDEATel Consortium (2006). â€Å"Theater Style Demonstration: The Informatics for Diabetes Education and Telemedicine (IDEATel) Project†. American Medical Informatics Association Annual Symposium Proceedings 2006. Retrieved 27 October 2008 from pubmedcentral. nih. gov/articlerender. fcgi? artid=1839417. Universal Tracking System (2007). UTS Diabetes Palm PDA Software. Retrieved 27 October 2008 from utracksys. com/plugins/diabetes/? ref=gaw_soft. Walter, T. , Klein, J. , Massin, P. and Erginay, A. (2002). â€Å"A Contribution of Image Processing to the Diagnosis of Diabetic Retinopathy†. IEEE Transactions on Medical Imaging 10(21): 1236- 1243. Retrieved 27 October 2008 from http://cat. inist. fr/? aModele=afficheNcpsidt=14504609. Zai, A. H. , Grant, R. W. , Estey, G. , Lester, W. T. , Andrews, C. T. , Yee, R. et. al. (2008). â€Å"Lessons From Implementing a Combined Workflow-Informatics System for Diabetes Management†. JAMIA 15: 524-533. Retrieved 27 October 2008 from jamia. org/cgi/content/short/15/4/524.