Technophobia, prescription checking and the future of diabetes management.

Is the medical prescription the root cause of the long-term complications of diabetes mellitus? This article presents the argument for introducing prescription checking into diabetes disease management. It discusses an evidence-based need for frequent revisions of the medical prescription as the key to preventing treatment-related complications in diabetes while achieving the now mandated standards in patient care. To do this it will be prudent for diabetes healthcare providers to enrich their clinical services with new information technology-based tools. These are easily acquired by participating in professional workshops focused on advanced diabetes management. In this light, the case presented here challenges leading practitioners to become early participants in the evolution of information technology that will ultimately enhance the management of all patients with diabetes.

Averting iatrogenic hypoglycemia through glucose prediction in clinical practice: progress towards a new procedure in diabetes.

BACKGROUND: Hypoglycemia is a risk factor common to all insulin therapy. The hypothesis is that efforts to reduce or prevent this adverse side effect may fail because providers generally lack the resources to predict not only future blood glucose levels but also future risks of hypoglycemia. This lack has been remedied. A controlled study was undertaken to test the hypothesis. METHODS: Twenty-two insulin dependent subjects suffering more than one (1) episode/week of hypoglycemia with similar insulin regimens, similar diabetes education and similar self-management training participated in this study. For all subjects, a remote monitoring resource (registry and database) was used to capture daily SMBG and afford a return path for provider interventions and decision support. Identical telemedical methods were used which differed only for the provider either by the presence (prediction group) or by the absence (control group) of an on-screen, visual display of predicted glycemia and predicted risks of hypoglycemia. The study lasted 2 months. RESULTS: Over an average of 41 days from baseline to follow up and while using the glycemic prediction resource, providers intervened more effectively in the prediction group reducing rates of hypoglycemia nine-fold (P<0.0001) and insulin therapy by just -9 U/day (P<0.01). Mean pre-meal glycemia was not compromised. Over 61 days from baseline to final follow up but without glycemic predictions in the control group, providers' interventions were less effective and resulted in no net changes in rates of hypoglycemia, daily insulin therapy, or mean pre-meal glycemia. CONCLUSIONS: Given knowledge of future glycemia and future risks of hypoglycemia, providers in clinical practice can now avert iatrogenic hypoglycemia in less than 2 months. A shared diabetes data center furnishing remote data capture and decision support is fundamental to the implementation of this as a new clinical procedure in diabetes.

Home blood glucose prediction: validation, safety, and efficacy testing in clinical diabetes.

BACKGROUND: Patients with diabetes do daily self-monitoring of blood glucose (SMBG). For such patients, we devised an engine that predicts not only the expected blood glucose level at the next meal but also the pending risks of hypoglycemia. The purpose of this study was to validate the predictions and provide evidence of the safety and efficacy of using predicted data in dosing decision support for routine patient care. RESEARCH DESIGN AND METHODS: The prediction engine is a computer program that accesses a central database into which daily records of self-monitored blood glucose data are captured by direct access either across the WWW or by an interactive voice response service on-line 24/7. Validation was done by comparison of predicted values to the subsequently observed data using a Clarke Error Grid. Safety focused on body weight and the frequency of hypoglycemia. Efficacy was judged according to glycated hemoglobin and daily insulin dosages. The experimental design contrasted patients in the tight control (TC) group who had been recently converted to intensified (basal-bolus) therapy with patients in the poor control (PC) group on conventional therapy and who were referred to begin intensified therapy. Both groups accessed the remote database to report their daily SMBG. Predicted glucose values were used in dosing decision support for the PC but not the TC group. RESULTS: Over the 6-month study period a total of 30,129 blood glucose levels were reported by the 54 study patients, and some 24,953 blood glucose predictions were made. Of these, 83% were in the clinically acceptable zones of the Clarke Error Grid. When these data were used for dosing decision support in the PC group, glycated hemoglobin levels fell significantly from 9.7 +/- 1.7% to 7.9 +/- 1.2%, and hypoglycemia dropped fourfold. Total daily insulin doses declined 22%, while body weight remained constant. In the parallel TC group (n = 24), glycated hemoglobin also fell, but only slightly from 7.6 +/- 0.9% to 7.2 +/- 1.1%, while daily insulin doses, rates of hypoglycemia and body weight remained constant. CONCLUSIONS: A novel engine is capable of generating meaningful predictions of blood glucose levels. Use of these validated predictions in decision support for managing medication doses proved safe and efficacious.

Home blood glucose prediction: clinical feasibility and validation in islet cell transplantation candidates.

AIMS/HYPOTHESIS: Diabetic subjects do home monitoring to substantiate their success (or failure) in meeting blood glucose targets set by their providers. To succeed, patients require decision support, which, until now, has not included knowledge of future blood glucose levels or of hypoglycaemia. To remedy this, we devised a glucose prediction engine. This study validates its predictions. METHODS: The prediction engine is a computer program that accesses a central database in which daily records of self-monitored blood glucose data and life-style parameters are stored. New data are captured by an interactive voice response server on-line 24 h a day, 7 days a week. Study subjects included 24 patients with debilitating hypoglycaemia (unawareness), which qualified them for islet cell transplantation. Comparison of each prediction with the actually observed data was done using a Clarke Error Grid (CEG). Patients and providers were blinded as to the predictions. RESULTS: Prior to transplantation, a total of 31,878 blood glucose levels were reported by the study subjects. Some 31,353 blood glucose predictions were made by the engine on a total of 8,733 days-used. Of these, 79.4% were in the clinically acceptable Zones of the CEG. Of 728 observed episodes of hypoglycaemia, 384 were predicted. After transplantation, a total of 45,529 glucose measurements were reported on a total of 12,906 days-used. Some 42,316 glucose predictions were made, of which 97.5% were in the acceptable CEG Zones A and B. Successful transplantation eliminated hypoglycaemia, improved glycaemic control, lowered HbA(1)c and freed 10 of 24 patients from daily insulin therapy. CONCLUSIONS/INTERPRETATION: It is clinically feasible to generate valid predictions of future blood glucose levels. Prediction accuracy is related to glycaemic stability. Risk of hypoglycaemia can be predicted. Such knowledge may be useful in self-management.

Clinical studies with home glucose clamping.

OBJECTIVE: Self-blood glucose control is crucial to improving long term outcomes in diabetes. To facilitate this task, we offered patients access to a remote computer continuously online for data collection, dosing decision support, and medical monitoring. Imbedded algorithms for home glucose clamping were custom programmed for each patient. The objectives of the present work were to determine what proportion of patients chose to use such support and whether users benefited from the effort compared to non-users. RESEARCH DESIGN AND METHODS: A single central computer system was used. Algorithms for home glucose clamping were custom programmed for each patient by their physician who set glucose targets, clamping factors and safety constraints. The systems were voice-interactive and required the remote patient to handle only a touch-tone telephone. Patients were free to access the system each day to report self-measured blood glucose levels or hypoglycemia symptoms together with carbohydrate counting, planned exercise, stress, illness or other life-style events. Clinical experience was in patients followed for 12 months in samples derived from three health-care environments. RESULTS: Some 388 patients were offered access to the system. Sixty percent of patients (N=231) actively used the system. Among the 3 study centers, over 104,000 blood glucose measurements were received during the start-up year. Each call was processed instantly and automatically. Patients benefited from the 24 hours access. Those receiving algorithmic assistance for home glucose clamping adjusted daily therapy more effectively: prevalence of hyper-glycemia and hypo-glycemia fell ~ 2-fold (p<0.05) and glycated hemoglobin levels declined 1.3% (p<0.001). CONCLUSIONS: Physicians and patients benefited. Patients with diabetes may be receptive to computer assistance. Many can accomplish glucose clamping at home and meet targets set by their physicians for self-blood glucose control while reducing the incidence of diabetic crises. The centralized system adds no costs for the patients and empowers physicians to provide safer and superior diabetes care.

The impact of initiatives in education, self-management training, and computer-assisted self-care on outcomes in diabetes disease management.

The purpose of this work is to elucidate the advantages and disadvantages arising from three distinct diabetes disease management initiatives in a managed care setting. The initiatives included (1) education alone, (2) education with self-management training, and (3) education with computer-assisted self-care. Outcomes of interest were changes in glycated hemoglobin (HbA1c), body weight, and costs of care in each cohort of care recipients. A total of 978 health plan members with diabetes within a mixed model HMO were included in the initiatives for improving blood glucose control. HbA1c was measured at baseline and at 3 and 12 months, body weight at baseline and 12 months, and costs of care over 1 year. Costs were derived from suppliers and the health plan. The design is a longitudinal observation study. With the edu-cation-alone initiative, costs, HbA1c, and body weight were unchanged. When education is supplemented with ongoing self-management training, HbA1c fell 1.1% (p < 0.01), body weight rose by 11 kg (p < 0.01), and costs for care increased by $18 per member per month. When education is supplemented with ongoing computer-assisted self-care, HbA1c also dropped by 1.1% (p < 0.01), body weight was unchanged (p > 0.4), and costs for care were $1.31 per member per month. All initiatives improved glycated hemoglobin. Other outcomes must therefore be considered. Among the initiatives, this study elucidated significant differences in body weight and costs. Therefore, in choosing a diabetes disease management program, it would appear that costs should be the primary consideration and methodologies that control body weight should be a priority.

Information technology and home glucose clamping.

Persons with diabetes are responsible for the day-to-day control of their glycemia. To assist patients in discharging this responsibility and help them achieve and sustain improvements in self-blood glucose control, we developed information technology capable of executing algorithms for "clamping glucose" at home. Algorithms for laboratory glucose clamping were translated and adapted for use by patients. The procedures were supported by a central computer and registry. Interaction with the algorithms from home required the patient to handle only a touch-tone telephone, which accessed voice response hardware in the central computer. Patients reported self-measured blood glucose levels or hypoglycemia symptoms together with dietary changes, planned exercise, stress, illness or other lifestyle events. In response, they received self-management instructions and dosing decision support. Metabolic end points were measured. System beta testing in active patients was for 1 year. Patients (n = 142) used the algorithms for their daily self-management, accumulating 1,651 patient-months of follow-up. Almost 100,000 telephone calls were received. Patients benefited. Prevalence of diabetes related crises (hyperglycemia > 400 mg/dL, hypoglycemia < 50 mg/dL or symptoms without measurement) fell approximately twofold (p < 0.05) and glycated hemoglobin levels fell 1.3% (p < 0.001), while body weight was stable. Providers benefited from the timely receipt of standardized reports to monitor the progress of their patients. Earlier intervention was possible. Information technology facilitated home glucose clamping whereby patients with diabetes received timely assistance, advice and decision support for crucial self-control of blood glucose levels. This empowered patients to achieve independence and improve diabetes self-management.

An electronic case manager for diabetes control.

OBJECTIVE: To evaluate the usage and safety of an electronic case manager (ECM) system designed to facilitate the task of glycemic control. Sustained improvement in blood glucose control is the proven treatment outcome that will reduce or eliminate the long-term complications of diabetes. RESEARCH DESIGN AND METHODS: A customized microcomputer system served as the ECM. Located at the clinic, this voice-interactive system required the remote patient to need only a touch-tone telephone. Patients accessed the system to report daily self-measured glucose levels or hypoglycemic symptoms together with associated lifestyle events. System beta-testing was in an open-case series (n = 184) in an academic diabetes center with the goal of evaluating the ECM in terms of utilization, frequency of crises, and fiscal matters. RESULTS: Of the patients, 58% (n = 107) actively used the ECM for their daily diabetes care, accumulating 788 patient-months of follow-up. Over 45,000 telephone calls were received by the ECM during the start-up year. Each call was processed instantly and automatically. Patients benefited from having 24-h access to the ECM. Prevalence of diabetes-related crises (hyperglycemia > 400 mg/dl [22 mmol/l] or hypoglycemia < 50 mg/dl [2.8 mmol/l]) decreased approximately threefold (P < 0.05), with a concomitant statistically significant decrease in HbA1c of 0.8% at 6 months (n = 45, P = 0.024) and 0.9% at 12 months (n = 30, P = 0.044). The ECM provided 24-h on-line assistance in adjusting daily insulin and/or tablet therapy, automatic generation of standardized medical reports, electronic medical-legal documentation, as well as a marked reduction in the time spent on the phone with patients. Clinic visits in managing complex diabetes were reduced approximately twofold (P < 0.0001), and the effort spent by case managers was estimated. CONCLUSIONS: Patients with diabetes who accessed the ECM system received timely, cost-effective, and reliable medical intervention. This reduced the incidence of diabetic crises and the need for frequent clinic visits. The ECM empowers case managers to provide safer and superior diabetes care.

Comparison of parametrized models for computer-based estimation of diabetic patient glucose response.

Two mathematical models for the description of diabetic patient glucose behaviour are proposed. Unlike high order differential-equation based compartmental models, these models employ only the data typically available to a diabetic patient: the history of measured blood glucose concentrations and of insulin injections. The model structures are compared with a native benchmark (zero-order hold) model in a computer simulation. It is demonstrated that, given four daily blood glucose measurements and two daily insulin injections, a parametrized model of patient blood glucose response to insulin can provide relevant data in the estimation of a patient's future blood glucose response in terms of past blood glucose measurements and insulin injections. Parametrized model root means squared errors of glycaemic predictions for 18 simulated patients ranged from 7-22 mg dl-1, as compared with 19-42 mg dl-1 for the benchmark model.

Diabetes intervention in the information age.

Sustained improvement in blood glucose control is the only treatment outcome which will reduce or eliminate the long term complications of diabetes mellitus. We have designed and evaluated an electronic information system which facilitates this task. The system is voice-interactive, physician directed and affords, to remote patients, 24 h access via touch-tone telephone. Accordingly, patients access the system each day to report self-measured blood glucose levels or hypoglycaemic symptoms together with dietary changes, planned exercise, stress, illness or other lifestyle events. In turn they receive immediate advice with respect to medication dosing changes, and other pertinent feedback. Preliminary system beta-testing for safety and efficacy was performed for one year in an open study of 204 patients derived from two independent, health-care environments. Among the two testing centres, over 60,000 telephone cells were received by the computer systems during the start-up year. Safety and efficacy expectations were met. In addition, prevalence of diabetes related crises (hyperglycaemia or hypoglycaemia) fell approximately 3-fold. Glycated haemoglobin fell significantly (1.0-1.3%) in patients actively using the system. In control groups of patients not actively using the system, there were no improvements in metabolic control while body weights were stable in all groups. The new system was safe and effective in our hands and empowered our health professionals to provide improved diabetes care.

Glucose turnover after a mixed meal in dogs: glucoregulation without change in arterial glycemia.

Because the dog can respond to a mixed-meal challenge with little or no change in plasma glucose concentration, we used kinetic techniques to quantify the magnitude and duration of changes in glucoregulation. Glucose turnover was measured using [3-3H]glucose and [U-14C]glucose over two 19-h periods in healthy dogs, first during a fast (n = 6) and then throughout the postprandial state (n = 6) after a single mixed meal. Mean arterial glycemia remained constant in the fasted state (7.5 +/- 0.2 mM) and in the fed state (7.6 +/- 0.3 mM). Glucose appearance (Ra), however, increased slowly after the meal from 38 +/- 2 mg/min to a maximum of 79 +/- 8 mg/min after 6 h and stayed elevated until 12 h (P < 0.001). In parallel, glucose disappearance (Rd) rose from 35 +/- 3 to 83 +/- 7 mg/min, closely matching the corresponding Ra. Glucose recycling rose from 25 +/- 8% at baseline to a maximum of 53 +/- 15% (P < 0.05) at 14 h in fed dogs, whereas levels for fasted dogs stayed between 19 +/- 7% at 0 h and 27 +/- 12% at 6 h. Insulin levels rose significantly 30 min after the meal from 67 +/- 7 pM to a peak of 208 +/- 54 pM at 6 h but remained elevated for 12 h. We conclude that 1) the dog was able to maintain postprandial glucoregulation by very precise matching of Ra and Rd such as to maintain glycemia constant.(ABSTRACT TRUNCATED AT 250 WORDS)

Adjusting insulins.

The teaching of effective insulin adjustment is a formal process that benefits from being carried out in a standardized way. The unique methods outlined in this report have been taught to people with diabetes for over 8 years. Iterative in nature, the methods are safe and work to achieve specified blood glucose or HbA1c targets. They are designed to accommodate each individual's habits, recognizing that acceptance depends on adapting the medication to the life-style rather than vice versa. New technology was used to mediate insulin adjustments at home. Insulin adjustment of itself, however, is but one of five interdependent factors involved in successful self-management. These include (1) choosing sites of insulin injection; (2) choosing species of origin of insulins to be used; (3) reviewing life-style habits, including diet and exercise; (4) implementing dosage titration; and (5) follow-up. Lack of formalized insulin adjustment methods may be a major reason why many diabetes control programs fail to demonstrate significantly better metabolic control in their patients.

The effect of a time delay on the characteristics of the canine glucoregulatory system.

In order to elucidate the effect of a relative time delay on glucose regulation, we performed experiments with differently timed infusions of insulin and glucose in a canine model. When portal insulin infusion (0.03 U/kg over 5 minutes) preceded portal glucose infusion (0.05 g/kg over 5 minutes) by 1 minute, glycemia increased to a maximum value of 104 +/- 4 mg/dL at 6 minutes, whereas insulinemia peaked at 3 minutes at a level of 130 +/- 4 microU/mL (baseline, 21 +/- 7 microU/mL). C-peptide levels increased from 200 +/- 50 to 270 +/- 30 pmol/L. Glycemia then decreased to a minimum level of 61 +/- 4 mg/dL, significantly lower (P less than .02) than the corresponding values in control experiments when insulin was infused alone. With a reversed timing sequence of infusions with glucose infusion preceding insulin infusion by 1 minute, glycemia increased similarly, but decreased to a minimum level of only 84 +/- 4 mg/dL, which was significantly higher (P less than .01) than in the above experiment. Insulinemia peaked similarly at 126 +/- 7 microU/mL, and C-peptide increased from 210 +/- 50 to 280 +/- 50 pmol/L. These experiments demonstrated an unexpected effect: adding glucose to an insulin infusion almost doubled the biological activity of the exogenous insulin as measured by its hypoglycemic action. They also indicated that small perturbations of glycemia and insulinemia in the portal circulation have a profound effect on metabolism, and that even short relative time delays in elevating either insulinemia or glycemia can cause significantly different metabolic outcomes.(ABSTRACT TRUNCATED AT 250 WORDS)

Controlled study in diabetic children comparing insulin-dosage adjustment by manual and computer algorithms.

A controlled trial of a new microprocessor device for insulin-dosage adjustment was undertaken in two matched groups of a priori well-controlled diabetic children. A prospective study design with three equal 8-wk periods was used. In the first period, both groups used manual methods for insulin-dosage adjustment after manual criteria. In the second period, one group of children adjusted insulin dosage by computer algorithms, whereas the other continued to use manual methods. In the third period, both groups again adjusted insulin by traditional methods. Mean premeal glycemia and glycosylated hemoglobin levels did not change in either group throughout the study. During the second period, episodes of hypoglycemia were more frequent in children without the computer than in those who used the device. In keeping with the latter outcome, the group that used the microprocessor device was given less insulin in the second period than the first (0.88 +/- 0.02 vs. 0.94 +/- 0.02 U.kg-1.day-1, P less than 0.0001) and in comparison to the control group of patients who concurrently were given an increased insulin dose in the second period compared with the first. This study showed that insulin treatment through specific computer-mediated dosage-adjusting algorithms was safe and minimized hypoglycemia by effectively accommodating seasonally changing insulin requirements. We recommend the device to help diabetic children and their families in the care of insulin-dependent diabetes.

Blood or urine glucose-based insulin therapy and control of glycemia. Computer-simulation study.

Adjustment algorithms for conventional insulin therapy must be tested for safety and efficacy before clinical implementation. We did this by computer simulation. Accordingly, a computer simulator of human intermediary metabolism created 10 randomly chosen diabetic subjects for study. All were well defined with respect to compliance (i.e., medication and diet) and life-style (i.e., physical and emotional stress). Insulin-adjustment algorithms that were tested calculated daily insulin dosages for these computer-simulated patients based on either blood or urine glucose concentrations self-measured 4 times/day before breakfast, lunch, dinner, and bedtime snack. The twofold purpose of the simulation study was to determine the ability of the adjustment algorithms to improve initially poor metabolic control and to compare the outcomes when either blood or urine glucose measurements were the basis on which glycemic control was implemented. A significant improvement in metabolic control could be achieved with either blood or urine glucose measurements as input to the algorithms. Detailed comparisons between blood and urine glucose-based treatments showed no significant advantage of blood glucose-based algorithms at breakfast (122 +/- 21 vs. 131 +/- 16 mg/dl) and dinner (117 +/- 27 vs. 130 +/- 23 mg/dl), whereas mean glycemia at lunch (122 +/- 24 vs. 164 +/- 21 mg/dl) and bedtime (117 +/- 25 vs. 150 +/- 21 mg/dl) after 120 days of simulation did differ significantly (P less than 0.01). Hypoglycemia was not provoked by either treatment. Total daily insulin doses evolved by blood glucose-based algorithms were significantly (P less than 0.05) higher than the doses used by urine glucose-based algorithms (53 vs. 47 U).(ABSTRACT TRUNCATED AT 250 WORDS)

Six generations of the insulin dosage computer: a new clinical device for diabetes self-management through specialized centres.

Modern technology and dedicated micro-processors in particular, are revolutionizing the treatment of diabetes. Through specialized centres and a select group of new medical experts, conventional diabetes management is gradually being replaced by a system of technology assisted self-care. The present paper outlines the characteristics of six consecutive generations of a new device called an insulin dosage computer. It facilitates self-care by calculating insulin dosages each day at each meal based on glucose measurements made by the patients themselves. The device was initially developed in 1982 and is now extended to over 1200 patients each of whom has acquired expert skills for self-management and thereby achieved improved metabolic control with freedom both from hypoglycemia and from the psychological dependencies usually accompanying this disorder.

Continuous flow peritoneal dialysis in pigs, using a silicone rubber double lumen catheter.

Continuous flow (CFPD) and intermittent (IPD) peritoneal dialysis were compared in pigs, using a double lumen silicone rubber peritoneal dialysis catheter. For CFPD, after instillation of 30 ml/kg into the peritoneal cavity, dialysate was continually infused and drained at approximately 25 ml/kg/h. A dwell volume of 30 ml/kg was also used for IPD. Similar length cycles of each technique were compared in Experiment 1. In Experiment 2 total solute clearance and ultrafiltration achieved over two consecutive IPD cycles were compared with CFPD of a similar duration. The catheter functioned well with few complications. In Experiment 1, CFPD produced greater ultrafiltration and significantly improved the clearance of urea, potassium and phosphate compared to IPD. No significant difference between the techniques was observed in Experiment 2. Our data suggest that for CFPD to retain its advantage over IPD intermittent complete drainage of the peritoneal cavity may be necessary.

In vivo bicarbonate deficiency and insulin dissolution.

Exogenous insulin exists primarily as the monomer in human plasma. However, in U100 regular insulin formulations, the concentrations of zinc and peptide are such that the insulin hexamer predominates. The biologic result is further disassociation to the monomer after subcutaneous or i.v. administration. Because of this, human plasma from seven normal controls dissolved 20-30 microm hexagonal insulin crystals in 3-8 min. This ability was inhibited by acid titration to a stable pH of 6.30, at which point bicarbonate depletion could be suggested. Repletion of bicarbonate remarkably restored the solvent effect, while back-titration to the initial pH without repleting bicarbonate had only a moderate result. To establish whether the in vivo reduction of bicarbonate in pathologic states had similar results, plasma from five Type I diabetics in severe acidosis (pH 7.06 +/- 0.04, HCO3 -7.3 +/- 0.6 mmol/l) was similarly studied after stabilization under 5% CO2 (pH, 6.97-7.17). In all cases, the dissolution of insulin crystals was inhibited (dissolution times greater than 25 min). When bicarbonate was replenished (HCO3- 24.1-26.7 mmol/l) and pH accordingly renormalized (pH 7.39-7.43), the dissolution of insulin crystals was completely restored. Because of these observations, we conclude that both plasma bicarbonate and pH markedly affect the dissolution of insulin and that reduced bicarbonate/pH in diabetic ketoacidosis may limit the availability of the biologically active monomer. These influences may play a role in the initial insensitivity to insulin frequently seen in severe insulin deficiency and ketoacidosis.