The need for radical and rapid improvement in diabetes care was clearly articulated by Williams in 1967 (1), but progress toward that laudable goal has been painfully slow. Only recently have population-based reports from primary care settings documented significant progress toward the goal of better diabetes care (2,3,4,5). In these and other studies (6), multiple interventions that address office systems, provider behavior, and patient behavior were usually needed to improve diabetes care (7,8). Successful interventions often used common strategies to improve care. These strategies included 1) accurately identifying patients with diabetes (9); 2) monitoring one or more important clinical parameters, such as glycosylated hemoglobin (HbA1c) or cholesterol levels; 3) prioritizing patients based on their clinical status and readiness to change (10); and 4) intensifying care through active outreach or visit planning.

Although identification of diabetic patients can be accomplished in most settings, stratification of patients by risk presents greater challenges. Risk information can be used to prioritize patients and to match interventions to level of risk, which may substantially increase the effectiveness of interventions (11). In this issue, Selby et al. (12) present an automated method to systematically identify patients at high risk. Selby et al. show that the predictive value of their multivariate risk measurement strategy is somewhat superior to simpler risk measurement strategies. They propose a multivariate risk measure that includes previous complications, high HbA1c levels, and elevated serum creatinine levels. The authors thereby contribute a useful and inexpensive tool to identify, monitor, and prioritize risk of diabetic complications on a population basis.

However, there are a number of factors that limit the usefulness of the proposed multivariate risk measure. First, many patients will not have up-to-date HbA1c or serum creatinine tests. Second, the authors do not separate risk of macrovascular and microvascular complications. Lifetime cumulative prevalence of end-stage microvascular complications is 4–15% depending on risk factors (13), yet 75% of adults with type 2 diabetes die from macrovascular causes (14,15). Macrovascular complications are also the leading driver of excess costs associated with diabetes in adults (16), and the number of patients that need to be treated to prevent one major cardiovascular event is much smaller than the number needed to treat to prevent one end-stage microvascular complication (17). Third, the sophisticated risk measure proposed by Selby et al. may be difficult to apply in smaller practice settings. Some smaller practices have successfully used much simpler systems to assess risk and tailor interventions (e.g., patients with a high HbA1c level) (2,3).

It seems clinically sensible to focus attention on high-risk patients because they lay claim to a disproportionate fraction of our time and energy and because they are the patients who may benefit most from intensified therapy (18). Furthermore, patients with high risk of major complications generally have more favorable short-term return on investment than lower-risk patients (19). Therefore, payers may be willing to devote more resources to the care of high-risk patients, because fewer such patients need to be treated with an effective intervention to prevent each complication.

On the other hand, what about younger, average-risk patients who may have more years ahead of them to develop and endure serious diabetes-related complications? Prioritization of risk is no benefit if average-risk patients are neglected. Most major cardiovascular events come from the large fraction of average-risk patients than from the smaller fraction of high-risk patients (20). Only by aggressively addressing the needs of average-risk diabetic patients will health plans and medical groups be able to slow down the pipeline that inexorably transforms our average-risk patients into high-risk patients who require higher resource use but achieve poorer outcomes. Effective interventions for average-risk patients present special challenges and offer important opportunities (21,22).

We are fortunate that many effective strategies to improve population-based diabetes care are now available, and several large primary care clinics have achieved median HbA1c levels near or below 7% on a population basis (2,3,5). Broad dissemination of the methods used to achieve these results in primary care practices is now needed. A more balanced clinical approach to the care of adults with type 2 diabetes—with much greater emphasis on multifactorial risk reduction, including blood pressure control, lipid control, use of aspirin, smoking cessation, and gylcemic control—is also needed.

We suffer the curse of living in interesting times. Thirty-four years after Williams’ prescient report (1), the proven efficacy of metformin (23), aspirin (24), angiotensin-converting enzyme inhibitors (25), and statins (26) offer our patients unprecedented hope for better clinical outcomes. Integrated, multifaceted primary care interventions that target organization of care, patient behavior, and provider behavior have been dramatically successful (2,3,4,5, 18). Yet <20% of diabetic patients in the richest country on earth have achieved simultaneous control of glucose, lipids, and blood pressure, while 75% of adults with diabetes continue to die prematurely of macrovascular disease. The clinical and population health tools we need to get the job done are now available, but our practices are not well organized, and too few of us have adopted the systematic strategy of “identify, monitor, prioritize, and intensify.” Will we take advantage of this powerful improvement strategy? Or will we wait for another generation of our patients to die premature deaths often caused by preventable macrovascular complications? The choice is ours today. Let us work together to organize, integrate, and coordinate all of our care—primary and subspecialty, doctor and nurse, inpatient and outpatient—without violating the confidentiality or privacy rights of our patients. We can do it, if we choose to.

1.
Williams TF, Martin DA, Watkins JD, Ellis EV: The clinical picture of diabetic control, studied in four settings.
Am J Public Health
57
:
41
–51,
1967
2.
Sperl-Hillen J, O’Connor PJ, Carlson RR, Lawson TB, Halstenson C, Crowson T, Wuorenma J: Improving diabetes care in a large health care system: an enhanced primary care approach.
It Comm J Qual Improv
26
:
615
–622,
2000
3.
Nyman MA, Murphy ME, Schryver PG, Naessens JM, Smith SA: Improving performance in diabetes care: a multicomponent intervention.
Eff Clin Pract
3
:
205
–212,
2000
4.
Sidorov J, Gabbay R, Harris R, Shull RD, Girolami S, Tomcavage J, Starkey R, Hughes R: Disease management for diabetes mellitus: impact on hemoglobin A1c.
Am J Manag Care
6
:
1217
–1226,
2000
5.
Sutherland JE, Hoehms JD, O’Donnell B, Wiblin RT: Diabetes management quality improvement in a family practice residency program.
J Am Board Fam Pract
14
:
243
–251,
2001
6.
Renders CM, Valk GD, Griffin SJ, Wagner EH, Eijk JTM, van Assendelft WJJ: Interventions to improve the management of diabetes mellitus in primary care, outpatient, and community settings. 2001 vol. Issue 1 ed. Cochrane Collaboration Library, 2001
7.
Wagner EH, Austin BT, Korff MV: Improving outcomes in chronic illness.
Managed Care Q
4
:
12
–25,
1996
8.
Griffin S, Kinmonth A: Diabetes care: the effectiveness of systems for routine surveillance for people with diabetes. Cochrane Database System Review, University of Cambridge, Institute of Public Health, 2000
9.
O’Connor P, Rush W, Pronk N, Cherney L: Identifying diabetes mellitus or heart disease among health maintenance organization members: sensitivity, specificity, predictive value and cost of survey and database methods.
Am J Manag Care
4
:
335
–342,
1998
10.
Boyle RG, O’Connor PJ, Pronk NP, Tan A: Stages of change for physical activity, diet, and smoking among HMO members with chronic conditions.
Am J Health Promot
12
:
170
–175,
1998
11.
Johnson P, Veazie P, O’Connor P, Pothaff SJ, Kochevar L, Verma D, Dutta P: Understanding variations in chronic disease outcomes.
Health Care Manag Sci
In press
12.
Selby J, Karter A, Ackerson L, Ferrara A, Liu J: Developing a prediction rule from automated clinical data bases to identify high-risk patients in a large population with diabetes.
Diabetes Care
24
:
1547
–1555,
2001
13.
Engelgau MM, Narayan KM, Herman WH: Screening for type 2 diabetes.
Diabetes Care
23
:
1563
–1580,
2000
14.
Haffner SM, Lehto S, Ronnemaa T, Pyorala K, Laakso M: Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarcdial infarction.
N Engl J Med
339
:
229
–234,
1998
15.
Modena MG, Barbieri A: Diabetes mellitus and cardiovascular complications: pathophysiological peculiarities and therapeutic implication.
Cardiologia
44
:
865
–877,
1999
16.
Gilmer TP, O’Connor PJ, Manning WG, Rush WA: The cost to health plans of poor glycemic control.
Diabetes Care
20
:
1847
–1853,
1997
17.
Barton S:
Clinical Evidence
. London, BMJ Publishing Group, 2000
18.
Aubert RE, Herman WH, Waters J, Moore W, Sutton D, Peterson BL, Bailey CM, Koplan JP: Nurse case management to improve glycemic control in diabetic patients in a health maintenance organization: a randomized, controlled trial.
Ann Intern Med
129
:
605
–612,
1998
19.
Pronk N, Goodman M, O’Connor P, Martinson B: Relationship between modifiable health risks and short-term health care charges.
JAMA
282
:
2235
–2239,
1999
20.
Wu LA, Kottke TE: Number needed to treat: caveat emptor.
J Clin Epidemiol
54
:
111
–116,
2001
21.
Glasgow RE, Hiss RG, Anderson RM, Friedman NM, Hayward RA, Marrero DG, Taylor CB, Vinicor F: Report of the health care delivery work group: behavioral research related to the establishment of a chronic disease model for diabetes care.
Diabetes Care
24
:
124
–130,
2001
22.
Martinson BC, O’Connor PJ, Pronk NP: Physical inactivity and short-term all-cause mortality in adults with chronic disease.
Arch Intern Med
161
:
1173
–1180,
2001
23.
UKPDS: Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). UK Prospective Diabetes Study (UKPDS) Group.
Lancet
352
:
852
–865,
1998
24.
ETDRS: Aspirin effects on mortality and morbidity in patients with diabetes mellitus: Early Treatment Diabetic Retinopathy Study report 14. ETDRS Investigators.
JAMA
268
:
1292
–1300,
1992
25.
Yusuf S, Sleight P, Pogue J, Bosch J, Davies R, Dagenais G: Effects of an angiotensin-converting-enzyme inhibitor, ramipril, on cardiovascular events in high-risk patients: the Heart Outcomes Prevention Evaluation Study Investigators.
N Engl J Med
342
:
145
–143,
2000
26.
Pyorala K, Pederson TR, Kjekshus J, Faegeman O, Olsson AG, Thorgeirsson G: Cholesterol lowering with simvastatin improves prognosis of diabetic patients with coronary heart disease: a subgroup analysis of the Scandinavian Simvastatin Survival Study (4S).
Diabetes Care
20
:
614
–620,
1997

Address correspondence and reprint requests to Dr. Patrick O’Connor, Senior Clinical Investigator, HealthPartners Research Foundation, 8100 34th Ave. South, Minneapolis, MN 554400-1524. E-mail: patrick.j.oconnor@healthpartners.com.