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Original Investigation | Health Care Reform

Encounter Frequency and Serum Glucose Level, Blood Pressure, and Cholesterol Level Control in Patients With Diabetes Mellitus FREE

Fritha Morrison, MPH; Maria Shubina, ScD; Alexander Turchin, MD, MS
[+] Author Affiliations

Author Affiliations: Division of Endocrinology, Brigham and Women's Hospital (Ms Morrison and Drs Shubina and Turchin); and Harvard Medical School, and Clinical Informatics Research and Development, Partners HealthCare System (Dr Turchin), Boston, Massachusetts.


Arch Intern Med. 2011;171(17):1542-1550. doi:10.1001/archinternmed.2011.400.
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Published online

Background More frequent patient-provider encounters may lead to faster control of hemoglobin A1c level, blood pressure (BP), and low-density lipoprotein (LDL) cholesterol (LDL-C) level (hereafter referred to as hemoglobin A1c, BP, and LDL-C) and improve outcomes, but no guidelines exist for how frequently patients with diabetes mellitus (DM) should be seen.

Methods This retrospective cohort study analyzed 26 496 patients with diabetes and elevated hemoglobin A1c, BP, and/or LDL-C treated by primary care physicians at 2 teaching hospitals between January 1, 2000, and January 1, 2009. The relationship between provider encounter (defined as a note in the medical record) frequency and time to hemoglobin A1c, BP, and LDL-C control was assessed.

Results Comparing patients who had encounters with their physicians between 1 to 2 weeks vs 3 to 6 months, median time to hemoglobin A1c less than 7.0% was 4.4 vs 24.9 months (not receiving insulin) and 10.1 vs 52.8 months (receiving insulin); median time to BP lower than 130/85 mm Hg was 1.3 vs 13.9 months; and median time to LDL-C less than 100 mg/dL was 5.1 vs 32.8 months, respectively (P < .001 for all). In multivariable analysis, doubling the time between physician encounters led to an increase in median time to hemoglobin A1c (not receiving [35%] and receiving [17%] insulin), BP (87%), and LDL-C (27%) targets (P < .001 for all). Time to control decreased progressively as encounter frequency increased up to once every 2 weeks for most targets, consistent with the pharmacodynamics of the respective medication classes.

Conclusions Primary care provider encounters every 2 weeks are associated with fastest achievement of hemoglobin A1c, BP, and LDL-C targets for patients with diabetes mellitus.

Figures in this Article

Diabetes mellitus (DM) is increasingly common in the United States and worldwide.1,2 Elevated serum glucose, blood pressure (BP), and low-density lipoprotein cholesterol (LDL-C) (hereafter referred to as hemoglobin A1c, BP, and LDL-C) values are associated with increased risk of microvascular and macrovascular complications, and their reduction decreases the risk.38 Nevertheless, most patients with DM do not have their hemoglobin A1c, BP, and LDL-C under control.9,10

A variety of studies1113 have shown that patients who visit their physicians more frequently have better outcomes. Current guidelines for treatment of DM do not include recommendations for how frequently patients should be observed.14 Recommended intervals for medication adjustments and testing range from every 2 to 3 days (for insulin) to every 3 months (for measuring hemoglobin A1c)1416; however, benefits of more frequent provider encounters may not be limited to treatment intensification and testing.

We, therefore, performed a retrospective study of more than 26 000 patients with DM and hyperglycemia, hypertension, and/or hyperlipidemia who received care in a primary care setting to test the hypothesis that higher encounter frequency is associated with better DM control.

DESIGN

We conducted a retrospective cohort study to determine the optimal frequency of patient-provider encounters for patients with DM. We evaluated the relationship between mean encounter frequency and time to hemoglobin A1c, BP, and LDL-C control. We also conducted a secondary analysis to examine the relationship between encounter frequency and the rate of decrease in hemoglobin A1c, BP, and LDL-C values.

STUDY COHORT

Patients with DM seen by primary care physicians affiliated with Brigham and Women's Hospital (BWH) and Massachusetts General Hospital (MGH) (both in Boston) for at least 2 years between January 1, 2000, and January 1, 2009, were studied. Patients were included in the analysis if they were 18 years and older, had a documented diagnosis of DM or a hemoglobin A1c of at least 7.0%, and at least 1 instance of hemoglobin A1c, BP, or LDL-C higher than the treatment target. Patients with missing zip codes were excluded to enable adjustment for median income by zip code.

To capture both face-to-face and remote interactions between patients and providers, we defined any note in the electronic medical record (EMR) as an encounter. We used treatment goals recommended at the beginning of the study: hemoglobin A1c less than 7.0%,17 BP lower than 130/85 mm Hg,17,18 and LDL-C less than 100 mg/dL (to convert to millimoles per liter, multiply by 0.0259).17 This study was approved by the Partners HealthCare System institutional review board, and the requirement for written informed consent was waived.

STUDY MEASUREMENTS

A single uncontrolled period served as the unit of analysis. We conducted 4 analyses: 1 for each of the 3 treatment targets (hemoglobin A1c, BP, and LDL-C) and a combined analysis that integrated all 3 targets. For analyses of individual treatment targets, an uncontrolled period started on the day when the relevant measurement (hemoglobin A1c, BP, or LDL-C for the hyperglycemic, hypertensive, and hyperlipidemic periods, respectively) was noted to be above the treatment target for the first time. The period ended on the first subsequent date when the measurement was below the target. Each patient could contribute multiple periods if measures fluctuated above and below target levels during the 9-year study. A combined uncontrolled period started on the first date when any of the 3 measures was above the treatment target and ended on the first subsequent date when all the measures were below their targets. The last known value was carried forward if all the measurements were not available on the same date.

The lowest measurement on a given date was used in the analysis. Lowest BP was defined as the BP measurement with the lowest mean arterial pressure. Transient elevations were defined as periods that contained only a single elevated measurement that subsequently normalized without any treatment intensification, and were excluded from the analysis. Uncontrolled periods without at least 1 annual encounter with a BWH or MGH primary care physician were excluded from the analysis to eliminate patients not actively treated in these practices. Periods without any medication information available in the EMR were excluded to enable inclusion of insulin treatment as a confounder variable in the analysis. Periods that contained more than 1 encounter with an endocrinologist were excluded to focus the analysis on the primary care setting. Finally, hyperglycemic and hyperlipidemic periods in which the rate of change of hemoglobin A1c and LDL-C, respectively, was greater than 3 SDs from the mean were excluded to eliminate likely measurement errors from the analysis.

Time to normalization for hemoglobin A1c, BP, and LDL-C during their respective uncontrolled periods was the length of the uncontrolled period. The mean encounter interval was determined by dividing the period length by the number of encounters with primary care physicians during that period. In these analyses, we categorized encounter intervals as 1 week or less, greater than 1 week to 2 weeks or less, greater than 2 weeks to 3 weeks or less, greater than 3 weeks to 1 month or less, greater than 1 month to 2 months or less, greater than 2 months to 3 months or less, and greater than 3 months. Treatment intensification was defined as initiation of a new medication or an increase in the dose of an existing medication.19 The treatment intensification rate was defined as the number of unique dates per month on which at least 1 medication in the relevant class was intensified. Medication change was conservatively classified as intensification as previously described20 because there is no reliable method to estimate relative medication potency for individual patients. Drug cessations were not captured in this analysis. Mean rate of change for hemoglobin A1c, systolic BP (SBP), diastolic BP (DBP), and LDL-C was calculated by subtracting the final value from the initial value and dividing by the period length. The patient's primary care physician was defined as the physician in a primary care practice who had the most encounters with the patient during the uncontrolled period.

Demographic information, BP measurements, and medication and laboratory data were obtained from the EMR at Partners HealthCare, an integrated health care delivery network in eastern Massachusetts that includes BWH and MGH. The Partners HealthCare EMR contains all medication prescription and laboratory records starting in at least 2000, and earlier for many patients. Blood pressure was obtained from a combination of structured vital sign records in the EMR and computational processing of narrative electronic provider notes as previously described.21 Medication intensification was abstracted from a combination of structured medication records and computational analysis of electronic provider notes as previously validated.22

STATISTICAL ANALYSIS

Summary statistics were conducted by using frequencies and proportions for categorical data and using means (SDs), medians, and ranges for continuous variables. The log-rank test was used to compare times to hemoglobin A1c, BP, and LDL-C normalization between different encounter intervals.

Marginal Cox proportional hazards regression models for clustered data23 were constructed to estimate the association between time to normalization and encounter interval while accounting for repeated events in individual patients and adjusting for demographic confounders (age, sex, race/ethnicity, primary language, health insurance, and median income by zip code), patient Charlson Comorbidity Index, treatment intensification, hemoglobin A1c and LDL-C measurement rates, and maximum hemoglobin A1c, SBP, DBP, and LDL-C values (where appropriate). To more clearly present the findings as a direct effect of encounter interval on time to normalization, we reanalyzed the data using Weibull regression models. We confirmed the equivalence of the Weibull regression models and the marginal Cox proportional hazards regression models by comparing Cox-Snell residual plots between these models using paired t tests and graphically using Nelson-Aalen plots.

To rule out ascertainment bias stemming from increased hemoglobin A1c, BP, and LDL-C measurement opportunities for patients with more frequent encounters, a sensitivity analysis was conducted at the patient level to compare the probability of target achievement at the end of 2 years from the first elevated hemoglobin A1c, BP, or LDL-C measurement with the frequency of patient-provider encounters. The logistic regression model adjusted for demographic confounders; Charlson Comorbidity Index; treatment intensification rates; maximum hemoglobin A1c, BP, and/or LDL-C measures; rates of hemoglobin A1c and LDL-C measurements, where appropriate; and clustering within providers.

To determine the relationship between encounter interval and rate of hemoglobin A1c, BP, and LDL-C change, we constructed hierarchical multivariable mixed linear regression models with random intercepts to account for clustering within individual physicians and repeated measurements with compound symmetry structure within patients.24 The models also included patient age, sex, race/ethnicity, primary language, income, health insurance, treatment intensification rate during the uncontrolled period, and insulin use for the hyperglycemic and combined periods. P values were obtained using the type III test and were adjusted for multiple hypothesis testing using the Simes-Hochberg method.25,26 All the analyses were performed using commercially available statistical software (SAS, version 9.2; SAS Institute Inc, Cary, North Carolina).

We identified 32 482 adults with DM who were regularly seen by BWH or MGH primary care physicians and had experienced at least 1 hyperglycemic, hypertensive, or hyperlipidemic period (Figure 1). We excluded 5655 hyperglycemic, 5181 hypertensive, and 5406 hyperlipidemic patients who were treated by endocrinologists; had no medication records; had only transient elevations in hemoglobin A1c, BP, and LDL-C values; had suspected hemoglobin A1c or LDL-C measurement errors; had missing demographic information; or were not regularly seen by a primary care physician associated with BWH or MGH during the study. The remaining 14 293 hyperglycemic, 26 128 hypertensive, and 15 739 hyperlipidemic patients were included in the study.

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Figure 1. Counts of patients excluded from the analysis. BP indicates blood pressure; BWH, Brigham and Women's Hospital; DM, diabetes mellitus; LDL-C, low-density lipoprotein cholesterol; MGH, Massachusetts General Hospital; and PCP, primary care physician.

During the study, only median DBP was below the treatment target (75 mm Hg); median hemoglobin A1c was 7.4%, SBP 130 mm Hg, and LDL-C 106.7 mg/dL (Table 1). The mean number of uncontrolled periods per patient during the study ranged from 1.4 for hyperlipidemia to 3.4 for hypertension. Hyperglycemic patients had hemoglobin A1c values above target 46% of the time, hypertensive patients had uncontrolled BP 42.7% of the time, and hyperlipidemic patients had elevated LDL-C values 46.3% of the time. At least 1 of the study measurements was not under control 88.4% of the time.

Median time between encounters ranged from 1.1 months for hypertensive periods to 1.8 months for hyperlipidemic periods (Table 2). The mean rate of antihyperglycemic medication intensification was approximately once per year, antihypertensive medications once every 4 months, and antihyperlipidemic medications once every 17 months. Overall, patients with at least 1 measurement above target had their treatment intensified on average once every 2.8 months.

Table Graphic Jump LocationTable 2. Uncontrolled Period Characteristics
ENCOUNTER INTERVAL AND TIME TO TREATMENT TARGET ACHIEVEMENT

In all the treatment categories, time to treatment target rose progressively as the interval between encounters increased (Figure 2). Compared with patients with a mean encounter interval of 1 to 2 weeks, median time to hemoglobin A1c target for patients whose mean encounter interval was 3 to 6 months was 4.4 vs 24.9 months (those not receiving insulin) and 10.1 vs 52.8 months (those receiving insulin), time to BP target was 1.3 vs 13.9 months, and time to LDL-C target was 5.1 vs 32.8 months. For all treatment targets combined, median time to target was 1.5 vs 36.9 months for a mean encounter interval of 1 to 2 weeks vs 3 to 6 months.

Place holder to copy figure label and caption
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Figure 2. Kaplan-Meier curves for time to treatment target from first elevated hemoglobin A1c, blood pressure (BP), or low-density lipoprotein cholesterol (LDL-C) values are plotted for different mean encounter intervals. Distinct uncontrolled periods (from the first elevated to the first normal measurement) for the same patient were analyzed separately. A, Encounter frequency and time to hemoglobin A1c level target for patients not receiving insulin. B, Encounter frequency and time to hemoglobin A1c target for patients receiving insulin. C, Encounter frequency and time to BP target. D, Encounter frequency and time to low-density lipoprotein cholesterol (LDL-C) target. (To convert LDL-C to millimoles per liter, multiply by 0.0259.) E, Encounter frequency and time to combined target. DBP, diastolic BP; and SBP, systolic BP.

As encounter intervals increased, the proportion of patients who never reached treatment targets also rose steadily. Comparing patients with a mean encounter interval of 1 to 2 weeks with those with an interval of more than 6 months, the fraction of uncontrolled periods that never reached treatment target was 35.4% vs 55.6% for hyperglycemic patients treated with insulin and 5.4% vs 15.9% for hypertensive patients. For hyperglycemic patients not receiving insulin and hyperlipidemic patients, the lowest proportion of uncontrolled periods that did not achieve treatment target was for encounter intervals of 1 to 2 weeks: 14.8% and 16.8% compared with 36.8% and 31.9% for encounter intervals longer than 6 months. For all treatment targets combined, the proportion of uncontrolled periods that never achieved all targets was 11.0% for encounter intervals of 1 week or less vs 43.4% for encounter intervals greater than 6 months.

In the multivariable Weibull regression model (Table 3) adjusted for demographic characteristics; Charlson Comorbidity Index; insulin administration (in hyperglycemic and combined uncontrolled periods); maximum hemoglobin A1c, SBP, DBP, and LDL-C (where relevant); hemoglobin A1c and LDL-C testing rates (where relevant); and treatment intensification, doubling the time between physician encounters resulted in a 35% (those not receiving insulin) and 17% (those receiving insulin) increase in median time to hemoglobin A1c normalization, an 87% increase in median time to BP normalization, and a 27% increase in median time to LDL-C normalization (P < .001 for all). Higher rates of treatment intensification; lower hemoglobin A1c, BP, and LDL-C; and not being treated with insulin (for hyperglycemic patients) were also associated with shorter periods (P < .001 for all). In a Weibull regression model of combined uncontrolled periods, doubling the time between physician encounters led to an 84% increase in the time to achievement of all treatment targets (P < .001). When treatment intensification was excluded from the model, doubling the time between physician encounters translated into 38%, 20%, 90%, 32%, and 88% increases in time to hemoglobin A1c when not receiving and receiving insulin, BP, LDL-C, and combined control, respectively (P < .001 for all). In a post hoc multivariable sensitivity analysis including periods for patients treated by endocrinologists, encounter frequency had similar effects on time to hemoglobin A1c, BP, and LDL-C normalization (results not shown).

Table Graphic Jump LocationTable 3. Effects of Patient and Treatment Characteristics on Time to Treatment Target

Multivariable sequential comparison of time to treatment target for encounter interval categories adjusted for patient demographics; highest hemoglobin A1c, BP, and LDL-C (where relevant) during the uncontrolled period; rate of treatment intensification; and insulin treatment (for hyperglycemic patients) showed that differences between most consequent encounter interval categories were highly significant (P < .001). Exceptions included encounter intervals of 1 week or less vs 1 to 2 weeks for hyperglycemic patients not treated with insulin (P = .006) and hyperlipidemic patients (P = .90) and encounter intervals of 1 to 2 weeks vs 2 to 3 weeks (P = .13) and 2 to 3 weeks vs longer than 3 months (P = .68) for hyperglycemic patients treated with insulin.

ENCOUNTER INTERVAL AND RATES OF OUTCOME MEASURE CHANGE

In multivariable analysis adjusted for demographic characteristics; Charlson Comorbidity Index; insulin treatment (in hyperglycemic patients); highest hemoglobin A1c, BP, and LDL-C (where relevant) values during the uncontrolled period; rate of treatment intensification and hemoglobin A1c and LDL-C measurement (where relevant); and clustering within individual physicians and repeated measurements within patients, for every additional month between encounters, rate of hemoglobin A1c declined an additional 0.014% per month, rate of SBP decreased by 2.5 mm Hg per month, rate of DBP decreased by 1.0 mm Hg per month, and rate of LDL-C decreased by 0.28 mg/dL per month (P < .001 for all). More frequent treatment intensification led to faster rates of decrease for all diabetes measures (P < .001 for all).

In this large retrospective study, we found a strong association between encounter frequency and hemoglobin A1c, BP, and LDL-C control in patients with DM. This relationship was confirmed in individual and combined analyses of time to normalization, rate of measure decrease, and rate of target achievement. A strong dose-response relationship between encounter frequency and the outcomes was evident in all the associations we analyzed.

Current guidelines provide little guidance for how frequently patients with DM should be seen by their physicians, apart from the recommendation for hemoglobin A1c measurement every 3 months.14 The present findings provide evidence that for many patients with elevated hemoglobin A1c, BP, or LDL-C, more frequent patient-provider encounters were associated with a shorter time to treatment target, and control was fastest at 2-week intervals. Encounters every 2 weeks may, therefore, be appropriate for the most severely uncontrolled patients or under a different treatment care model.

More frequent opportunities for medication intensification are likely an important mediator of the encounter frequency effect. This explanation is corroborated by a decrease in the encounter frequency effect when treatment intensification rate is included in the model. Many textbooks27,28 recommend a lower limit of 4 to 6 weeks on the medication intensification frequency out of concern for a stacking effect and overdose. However, time to maximum effect for most medications is shorter than commonly believed. The majority of antihyperglycemic agents achieve most of their effect within 2 weeks,2932 and others in less than 4 weeks3336; antihypertensive agents (except thiazides) in less than 2 weeks3742; and statins within 2 weeks.43 These results are consistent with the present findings that biweekly encounters are associated with fastest achievement of serum glucose, BP, and LDL control.

Although median time between patient-physician encounters was only 1.4 months for hyperglycemic patients, treatment intensification occurred just once per year. The target hemoglobin A1c is commonly reached much more slowly than recommended by guidelines; the incongruity between encounter frequency and rates of treatment intensification suggests that there are many opportunities for physicians to alter medications that may lead to faster hemoglobin A1c control during encounters.

Treatment intensification may not be the sole factor responsible for the association between encounter frequency and patient outcomes, as illustrated by the strong residual association between encounter frequency and time to normalization when controlling for treatment intensification. Other studies44,45 have shown that more frequent encounters are also associated with better medication adherence. During encounters, physicians may also be providing lifestyle coaching or other education that leads to better DM control.

There is evidence that faster control of intermediate end points (hemoglobin A1c level, BP, and LDL-C) that could be achieved by more frequent provider encounters translates into improvement in clinical outcomes. Early intensive insulin therapy in patients with newly diagnosed type 2 DM leads to more durable control and improvement in β-cell function.46 The VALUE (Valsartan Antihypertensive Long-term Use Evaluation) randomised trial found that lower BP in the first 3 months decreased rates of stroke and myocardial infarction.47 Several studies4852 have shown that statin therapy lowered rates of cardiovascular events in high-risk patients within 3 to 6 months of initiation.

Because more frequent encounters could increase demand on health care resources, straining an already taxed53 and dwindling primary care environment,54,55 increased encounter frequency implementation may require innovative approaches to patient care delivery. Medical homes may help coordinate care of patients, and some interactions could be accomplished through group visits, telephone, fax, e-mail, or Internet communications.56 Studies5660 have shown that midlevel providers can alleviate physician workload without any negative effect on patient outcomes.

Once a patient achieves DM control, the frequency of the encounters may be decreased to alleviate the strain on health care resources and possibly to also reward the patient.61 It has been shown that in patients with controlled hypertension, patient-provider encounters can be 6 months apart without adverse effects.62

The present study has several strengths. With access to EMRs from 2 large hospital systems, we were able to analyze more than 26 000 patients with uncontrolled DM from diverse backgrounds and health insurance coverage plans. We focused on the primary care setting, where most patients with DM are treated. Importantly, the present results were consistent with pharmacodynamic data, providing a physiologic basis for the findings.

This study also has several limitations. It was conducted in clinics affiliated with 2 academic medical centers in eastern Massachusetts and, thus, may not be generalizable to all settings. These clinics do not include many midlevel providers, primarily limiting these conclusions to primary care physicians. Uncontrolled periods were censored at the beginning of the study; however, unless encounter frequency was systematically uneven over the duration of the study, this should not have biased the results. We were unable to distinguish between routine scheduled encounters and last-minute appointments with physicians; the focus of care (routine vs urgent) probably differs between these 2 visit types. Hemoglobin A1c, BP, and LDL-C values were measured only during the course of routine care, possibly leading to an ascertainment bias because patients with shorter encounter intervals had more frequent opportunities to have measurements below target. However, a separate analysis showed that higher encounter frequency was linked to higher probability of hemoglobin A1c, BP, and LDL-C target achievement at 2 years after the first abnormal level was measured (data not shown). This finding supports our interpretation in a manner not subject to bias by the missing measurement data. The retrospective nature of these data does not allow us to assess the availability or motivation of patients to see their physicians, which may be another indicator of adherence. We were also unable to consider how individual patient-provider goals may have differed from published guidelines or which physicians may practice in clinics that institute DM management protocols; however, we did correct for clustering within providers and repeated measures within patients, which helps mitigate this confounder. There were several potential confounders we could not measure, including type of DM, face-to-face vs remote encounters, focus of treatment at an encounter, patient motivation, and medication adherence. We were also unable to measure potential costs and risks associated with higher encounter frequency, making a full risk-benefit analysis impossible. Although some clinical trials found evidence that faster attainment of intermediate measures can result in improved clinical outcomes, this study is limited to intermediate outcomes, and we do not have evidence that the association between higher encounter frequency and faster hemoglobin A1c, BP, and LDL-C control reported herein leads to improved clinical outcomes in this study population. The retrospective nature of this study prevents us from establishing a causal relationship between encounter frequency and patient outcomes. A randomized interventional study is, therefore, needed to definitively establish optimal encounter frequency for patients with DM.

Correspondence: Alexander Turchin, MD, MS, Division of Endocrinology, Brigham and Women's Hospital, 221 Longwood Ave, Boston, MA 02115 (aturchin@partners.org).

Accepted for Publication: May 23, 2011.

Author Contributions:Study concept and design: Shubina and Turchin. Acquisition of data: Turchin. Analysis and interpretation of data: Morrison, Shubina, and Turchin. Drafting of the manuscript: Morrison. Critical revision of the manuscript for important intellectual content: Shubina and Turchin. Statistical analysis: Shubina. Obtained funding: Turchin. Administrative, technical, and material support: Morrison. Study supervision: Turchin.

Financial Disclosure: None reported.

Funding/Support: This study was supported in part by grants 5R18HS017030 from the Agency for Healthcare Research and Quality (Drs Shubina and Turchin) and 5RC1LM010460 from the National Library of Medicine (Ms Morrison and Drs Shubina and Turchin), and the Diabetes Action Research and Education Foundation (Dr Turchin).

Role of the Sponsor: The funding sources had no direct impact on the design and conduct of the study; the collection, management, analysis, and interpretation of the data; and the preparation, review, or approval of the manuscript.

Previous Presentation: This study was presented in part at the 71st Scientific Sessions of the American Diabetes Association; June 26, 2011; San Diego, California.

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Goodman LS, Brunton LL, Chabner B, Knollmann BC. Goodman & Gilman's Pharmacological Basis of Therapeutics. 12th ed. New York, NY: McGraw-Hill Professional; 2011
McPhee S, Papadakis M, Rabow MW. Current Medical Diagnosis & Treatment. New York, NY: McGraw-Hill Medical; 2011
Simonson DC, Kourides IA, Feinglos M, Shamoon H, Fischette CT.The Glipizide Gastrointestinal Therapeutic System Study Group.  Efficacy, safety, and dose-response characteristics of glipizide gastrointestinal therapeutic system on glycemic control and insulin secretion in NIDDM: results of two multicenter, randomized, placebo-controlled clinical trials.  Diabetes Care. 1997;20(4):597-606
PubMed   |  Link to Article
Rosenstock J, Hassman DR, Madder RD,  et al; Repaglinide Versus Nateglinide Comparison Study Group.  Repaglinide versus nateglinide monotherapy: a randomized, multicenter study.  Diabetes Care. 2004;27(6):1265-1270
PubMed   |  Link to Article
Marre M, Shaw J, Brändle M,  et al; LEAD-1 SU study group.  Liraglutide, a once-daily human GLP-1 analogue, added to a sulphonylurea over 26 weeks produces greater improvements in glycaemic and weight control compared with adding rosiglitazone or placebo in subjects with type 2 diabetes (LEAD-1 SU).  Diabet Med. 2009;26(3):268-278
PubMed   |  Link to Article
Russell-Jones D, Vaag A, Schmitz O,  et al; Liraglutide Effect and Action in Diabetes 5 (LEAD-5) met+SU Study Group.  Liraglutide vs insulin glargine and placebo in combination with metformin and sulfonylurea therapy in type 2 diabetes mellitus (LEAD-5 met+SU): a randomised controlled trial.  Diabetologia. 2009;52(10):2046-2055
PubMed   |  Link to Article
Aschner P, Kipnes MS, Lunceford JK, Sanchez M, Mickel C, Williams-Herman DE.Sitagliptin Study 021 Group.  Effect of the dipeptidyl peptidase-4 inhibitor sitagliptin as monotherapy on glycemic control in patients with type 2 diabetes.  Diabetes Care. 2006;29(12):2632-2637
PubMed   |  Link to Article
Chacra AR, Tan GH, Apanovitch A, Ravichandran S, List J, Chen R.CV181-040 Investigators.  Saxagliptin added to a submaximal dose of sulphonylurea improves glycaemic control compared with uptitration of sulphonylurea in patients with type 2 diabetes: a randomised controlled trial.  Int J Clin Pract. 2009;63(9):1395-1406
PubMed   |  Link to Article
Kipnes MS, Krosnick A, Rendell MS, Egan JW, Mathisen AL, Schneider RL. Pioglitazone hydrochloride in combination with sulfonylurea therapy improves glycemic control in patients with type 2 diabetes mellitus: a randomized, placebo-controlled study.  Am J Med. 2001;111(1):10-17
PubMed   |  Link to Article
Fonseca V, Rosenstock J, Patwardhan R, Salzman A. Effect of metformin and rosiglitazone combination therapy in patients with type 2 diabetes mellitus: a randomized controlled trial.  JAMA. 2000;283(13):1695-1702
PubMed   |  Link to Article
Donnelly R, Elliott HL, Meredith PA, Kelman AW, Reid JL. Nifedipine: individual responses and concentration-effect relationships.  Hypertension. 1988;12(4):443-449
PubMed
Donnelly R, Elliott HL, Meredith PA, Reid JL. Concentration-effect relationships and individual responses to doxazosin in essential hypertension.  Br J Clin Pharmacol. 1989;28(5):517-526
PubMed
Donnelly R, Meredith PA, Elliott HL, Reid JL. Kinetic-dynamic relations and individual responses to enalapril.  Hypertension. 1990;15(3):301-309
PubMed
Michelson EL, Frishman WH, Lewis JE,  et al.  Multicenter clinical evaluation of long-term efficacy and safety of labetalol in treatment of hypertension.  Am J Med. 1983;75(4A):68-80
PubMed   |  Link to Article
Pool JL, Guthrie RM, Littlejohn TW III,  et al.  Dose-related antihypertensive effects of irbesartan in patients with mild-to-moderate hypertension.  Am J Hypertens. 1998;11(4, pt 1):462-470
PubMed   |  Link to Article
van Brummelen P, Man in 't Veld AJ, Schalekamp MA. Hemodynamic changes during long-term thiazide treatment of essential hypertension in responders and nonresponders.  Clin Pharmacol Ther. 1980;27(3):328-336
PubMed   |  Link to Article
Bakker-Arkema RG, Davidson MH, Goldstein RJ,  et al.  Efficacy and safety of a new HMG-CoA reductase inhibitor, atorvastatin, in patients with hypertriglyceridemia.  JAMA. 1996;275(2):128-133
PubMed   |  Link to Article
Patel NC, Crismon ML, Miller AL, Johnsrud MT. Drug adherence: effects of decreased visit frequency on adherence to clozapine therapy.  Pharmacotherapy. 2005;25(9):1242-1247
PubMed   |  Link to Article
Wannamaker BB, Morton WA Jr, Gross AJ, Saunders S. Improvement in antiepileptic drug levels following reduction of intervals between clinic visits.  Epilepsia. 1980;21(2):155-162
PubMed   |  Link to Article
Weng J, Li Y, Xu W,  et al.  Effect of intensive insulin therapy on β-cell function and glycaemic control in patients with newly diagnosed type 2 diabetes: a multicentre randomised parallel-group trial.  Lancet. 2008;371(9626):1753-1760
PubMed   |  Link to Article
Julius S, Kjeldsen SE, Weber M,  et al; VALUE trial group.  Outcomes in hypertensive patients at high cardiovascular risk treated with regimens based on valsartan or amlodipine: the VALUE randomised trial.  Lancet. 2004;363(9426):2022-2031
PubMed   |  Link to Article
Cannon CP, Braunwald E, McCabe CH,  et al; Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis in Myocardial Infarction 22 Investigators.  Intensive versus moderate lipid lowering with statins after acute coronary syndromes.  N Engl J Med. 2004;350(15):1495-1504
PubMed   |  Link to Article
Colhoun HM, Betteridge DJ, Durrington PN,  et al; CARDS Investigators.  Rapid emergence of effect of atorvastatin on cardiovascular outcomes in the Collaborative Atorvastatin Diabetes Study (CARDS).  Diabetologia. 2005;48(12):2482-2485
PubMed   |  Link to Article
Colhoun HM, Betteridge DJ, Durrington PN,  et al; CARDS investigators.  Primary prevention of cardiovascular disease with atorvastatin in type 2 diabetes in the Collaborative Atorvastatin Diabetes Study (CARDS): multicentre randomised placebo-controlled trial.  Lancet. 2004;364(9435):685-696
PubMed   |  Link to Article
Downs JR, Clearfield M, Weis S,  et al.  Primary prevention of acute coronary events with lovastatin in men and women with average cholesterol levels: results of AFCAPS/TexCAPS. Air Force/Texas Coronary Atherosclerosis Prevention Study.  JAMA. 1998;279(20):1615-1622
PubMed   |  Link to Article
Shepherd J, Cobbe SM, Ford I,  et al; West of Scotland Coronary Prevention Study Group.  Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia.  N Engl J Med. 1995;333(20):1301-1307
PubMed   |  Link to Article
Østbye T, Yarnall KS, Krause KM, Pollak KI, Gradison M, Michener JL. Is there time for management of patients with chronic diseases in primary care?  Ann Fam Med. 2005;3(3):209-214
PubMed   |  Link to Article
Bodenheimer T. Primary care—will it survive?  N Engl J Med. 2006;355(9):861-864
PubMed   |  Link to Article
Hauer KE, Durning SJ, Kernan WN,  et al.  Factors associated with medical students' career choices regarding internal medicine.  JAMA. 2008;300(10):1154-1164
PubMed   |  Link to Article
Lee TH, Bodenheimer T, Goroll AH, Starfield B, Treadway K. Perspective roundtable: redesigning primary care.  N Engl J Med. 2008;359(20):e24
PubMed  |  Link to Article   |  Link to Article
Denver EA, Barnard M, Woolfson RG, Earle KA. Management of uncontrolled hypertension in a nurse-led clinic compared with conventional care for patients with type 2 diabetes.  Diabetes Care. 2003;26(8):2256-2260
PubMed   |  Link to Article
New JP, Mason JM, Freemantle N,  et al.  Specialist nurse-led intervention to treat and control hypertension and hyperlipidemia in diabetes (SPLINT): a randomized controlled trial.  Diabetes Care. 2003;26(8):2250-2255
PubMed   |  Link to Article
Taylor CB, Miller NH, Reilly KR,  et al.  Evaluation of a nurse-care management system to improve outcomes in patients with complicated diabetes.  Diabetes Care. 2003;26(4):1058-1063
PubMed   |  Link to Article
Vivian EM. Improving blood pressure control in a pharmacist-managed hypertension clinic.  Pharmacotherapy. 2002;22(12):1533-1540
PubMed   |  Link to Article
Wick A, Koller MT. Views of patients and physicians on follow-up visits: results from a cross-sectional study in Swiss primary care.  Swiss Med Wkly. 2005;135(9-10):139-144
PubMed
Birtwhistle RV, Godwin MS, Delva MD,  et al.  Randomised equivalence trial comparing three month and six month follow up of patients with hypertension by family practitioners.  BMJ. 2004;328(7433):204-209
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Graphic Jump Location

Figure 1. Counts of patients excluded from the analysis. BP indicates blood pressure; BWH, Brigham and Women's Hospital; DM, diabetes mellitus; LDL-C, low-density lipoprotein cholesterol; MGH, Massachusetts General Hospital; and PCP, primary care physician.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 2. Kaplan-Meier curves for time to treatment target from first elevated hemoglobin A1c, blood pressure (BP), or low-density lipoprotein cholesterol (LDL-C) values are plotted for different mean encounter intervals. Distinct uncontrolled periods (from the first elevated to the first normal measurement) for the same patient were analyzed separately. A, Encounter frequency and time to hemoglobin A1c level target for patients not receiving insulin. B, Encounter frequency and time to hemoglobin A1c target for patients receiving insulin. C, Encounter frequency and time to BP target. D, Encounter frequency and time to low-density lipoprotein cholesterol (LDL-C) target. (To convert LDL-C to millimoles per liter, multiply by 0.0259.) E, Encounter frequency and time to combined target. DBP, diastolic BP; and SBP, systolic BP.

Tables

Table Graphic Jump LocationTable 2. Uncontrolled Period Characteristics
Table Graphic Jump LocationTable 3. Effects of Patient and Treatment Characteristics on Time to Treatment Target

References

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Turchin A, Goldberg SI, Shubina M, Einbinder JS, Conlin PR. Encounter frequency and blood pressure in hypertensive patients with diabetes mellitus.  Hypertension. 2010;56(1):68-74
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Turchin A, Shubina M, Chodos AH, Einbinder JS, Pendergrass ML. Effect of board certification on antihypertensive treatment intensification in patients with diabetes mellitus.  Circulation. 2008;117(5):623-628
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Turchin A, Kolatkar NS, Grant RW, Makhni EC, Pendergrass ML, Einbinder JS. Using regular expressions to abstract blood pressure and treatment intensification information from the text of physician notes.  J Am Med Inform Assoc. 2006;13(6):691-695
PubMed   |  Link to Article
Turchin A, Shubina M, Breydo E, Pendergrass ML, Einbinder JS. Comparison of information content of structured and narrative text data sources on the example of medication intensification.  J Am Med Inform Assoc. 2009;16(3):362-370
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Link to Article
Goodman LS, Brunton LL, Chabner B, Knollmann BC. Goodman & Gilman's Pharmacological Basis of Therapeutics. 12th ed. New York, NY: McGraw-Hill Professional; 2011
McPhee S, Papadakis M, Rabow MW. Current Medical Diagnosis & Treatment. New York, NY: McGraw-Hill Medical; 2011
Simonson DC, Kourides IA, Feinglos M, Shamoon H, Fischette CT.The Glipizide Gastrointestinal Therapeutic System Study Group.  Efficacy, safety, and dose-response characteristics of glipizide gastrointestinal therapeutic system on glycemic control and insulin secretion in NIDDM: results of two multicenter, randomized, placebo-controlled clinical trials.  Diabetes Care. 1997;20(4):597-606
PubMed   |  Link to Article
Rosenstock J, Hassman DR, Madder RD,  et al; Repaglinide Versus Nateglinide Comparison Study Group.  Repaglinide versus nateglinide monotherapy: a randomized, multicenter study.  Diabetes Care. 2004;27(6):1265-1270
PubMed   |  Link to Article
Marre M, Shaw J, Brändle M,  et al; LEAD-1 SU study group.  Liraglutide, a once-daily human GLP-1 analogue, added to a sulphonylurea over 26 weeks produces greater improvements in glycaemic and weight control compared with adding rosiglitazone or placebo in subjects with type 2 diabetes (LEAD-1 SU).  Diabet Med. 2009;26(3):268-278
PubMed   |  Link to Article
Russell-Jones D, Vaag A, Schmitz O,  et al; Liraglutide Effect and Action in Diabetes 5 (LEAD-5) met+SU Study Group.  Liraglutide vs insulin glargine and placebo in combination with metformin and sulfonylurea therapy in type 2 diabetes mellitus (LEAD-5 met+SU): a randomised controlled trial.  Diabetologia. 2009;52(10):2046-2055
PubMed   |  Link to Article
Aschner P, Kipnes MS, Lunceford JK, Sanchez M, Mickel C, Williams-Herman DE.Sitagliptin Study 021 Group.  Effect of the dipeptidyl peptidase-4 inhibitor sitagliptin as monotherapy on glycemic control in patients with type 2 diabetes.  Diabetes Care. 2006;29(12):2632-2637
PubMed   |  Link to Article
Chacra AR, Tan GH, Apanovitch A, Ravichandran S, List J, Chen R.CV181-040 Investigators.  Saxagliptin added to a submaximal dose of sulphonylurea improves glycaemic control compared with uptitration of sulphonylurea in patients with type 2 diabetes: a randomised controlled trial.  Int J Clin Pract. 2009;63(9):1395-1406
PubMed   |  Link to Article
Kipnes MS, Krosnick A, Rendell MS, Egan JW, Mathisen AL, Schneider RL. Pioglitazone hydrochloride in combination with sulfonylurea therapy improves glycemic control in patients with type 2 diabetes mellitus: a randomized, placebo-controlled study.  Am J Med. 2001;111(1):10-17
PubMed   |  Link to Article
Fonseca V, Rosenstock J, Patwardhan R, Salzman A. Effect of metformin and rosiglitazone combination therapy in patients with type 2 diabetes mellitus: a randomized controlled trial.  JAMA. 2000;283(13):1695-1702
PubMed   |  Link to Article
Donnelly R, Elliott HL, Meredith PA, Kelman AW, Reid JL. Nifedipine: individual responses and concentration-effect relationships.  Hypertension. 1988;12(4):443-449
PubMed
Donnelly R, Elliott HL, Meredith PA, Reid JL. Concentration-effect relationships and individual responses to doxazosin in essential hypertension.  Br J Clin Pharmacol. 1989;28(5):517-526
PubMed
Donnelly R, Meredith PA, Elliott HL, Reid JL. Kinetic-dynamic relations and individual responses to enalapril.  Hypertension. 1990;15(3):301-309
PubMed
Michelson EL, Frishman WH, Lewis JE,  et al.  Multicenter clinical evaluation of long-term efficacy and safety of labetalol in treatment of hypertension.  Am J Med. 1983;75(4A):68-80
PubMed   |  Link to Article
Pool JL, Guthrie RM, Littlejohn TW III,  et al.  Dose-related antihypertensive effects of irbesartan in patients with mild-to-moderate hypertension.  Am J Hypertens. 1998;11(4, pt 1):462-470
PubMed   |  Link to Article
van Brummelen P, Man in 't Veld AJ, Schalekamp MA. Hemodynamic changes during long-term thiazide treatment of essential hypertension in responders and nonresponders.  Clin Pharmacol Ther. 1980;27(3):328-336
PubMed   |  Link to Article
Bakker-Arkema RG, Davidson MH, Goldstein RJ,  et al.  Efficacy and safety of a new HMG-CoA reductase inhibitor, atorvastatin, in patients with hypertriglyceridemia.  JAMA. 1996;275(2):128-133
PubMed   |  Link to Article
Patel NC, Crismon ML, Miller AL, Johnsrud MT. Drug adherence: effects of decreased visit frequency on adherence to clozapine therapy.  Pharmacotherapy. 2005;25(9):1242-1247
PubMed   |  Link to Article
Wannamaker BB, Morton WA Jr, Gross AJ, Saunders S. Improvement in antiepileptic drug levels following reduction of intervals between clinic visits.  Epilepsia. 1980;21(2):155-162
PubMed   |  Link to Article
Weng J, Li Y, Xu W,  et al.  Effect of intensive insulin therapy on β-cell function and glycaemic control in patients with newly diagnosed type 2 diabetes: a multicentre randomised parallel-group trial.  Lancet. 2008;371(9626):1753-1760
PubMed   |  Link to Article
Julius S, Kjeldsen SE, Weber M,  et al; VALUE trial group.  Outcomes in hypertensive patients at high cardiovascular risk treated with regimens based on valsartan or amlodipine: the VALUE randomised trial.  Lancet. 2004;363(9426):2022-2031
PubMed   |  Link to Article
Cannon CP, Braunwald E, McCabe CH,  et al; Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis in Myocardial Infarction 22 Investigators.  Intensive versus moderate lipid lowering with statins after acute coronary syndromes.  N Engl J Med. 2004;350(15):1495-1504
PubMed   |  Link to Article
Colhoun HM, Betteridge DJ, Durrington PN,  et al; CARDS Investigators.  Rapid emergence of effect of atorvastatin on cardiovascular outcomes in the Collaborative Atorvastatin Diabetes Study (CARDS).  Diabetologia. 2005;48(12):2482-2485
PubMed   |  Link to Article
Colhoun HM, Betteridge DJ, Durrington PN,  et al; CARDS investigators.  Primary prevention of cardiovascular disease with atorvastatin in type 2 diabetes in the Collaborative Atorvastatin Diabetes Study (CARDS): multicentre randomised placebo-controlled trial.  Lancet. 2004;364(9435):685-696
PubMed   |  Link to Article
Downs JR, Clearfield M, Weis S,  et al.  Primary prevention of acute coronary events with lovastatin in men and women with average cholesterol levels: results of AFCAPS/TexCAPS. Air Force/Texas Coronary Atherosclerosis Prevention Study.  JAMA. 1998;279(20):1615-1622
PubMed   |  Link to Article
Shepherd J, Cobbe SM, Ford I,  et al; West of Scotland Coronary Prevention Study Group.  Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia.  N Engl J Med. 1995;333(20):1301-1307
PubMed   |  Link to Article
Østbye T, Yarnall KS, Krause KM, Pollak KI, Gradison M, Michener JL. Is there time for management of patients with chronic diseases in primary care?  Ann Fam Med. 2005;3(3):209-214
PubMed   |  Link to Article
Bodenheimer T. Primary care—will it survive?  N Engl J Med. 2006;355(9):861-864
PubMed   |  Link to Article
Hauer KE, Durning SJ, Kernan WN,  et al.  Factors associated with medical students' career choices regarding internal medicine.  JAMA. 2008;300(10):1154-1164
PubMed   |  Link to Article
Lee TH, Bodenheimer T, Goroll AH, Starfield B, Treadway K. Perspective roundtable: redesigning primary care.  N Engl J Med. 2008;359(20):e24
PubMed  |  Link to Article   |  Link to Article
Denver EA, Barnard M, Woolfson RG, Earle KA. Management of uncontrolled hypertension in a nurse-led clinic compared with conventional care for patients with type 2 diabetes.  Diabetes Care. 2003;26(8):2256-2260
PubMed   |  Link to Article
New JP, Mason JM, Freemantle N,  et al.  Specialist nurse-led intervention to treat and control hypertension and hyperlipidemia in diabetes (SPLINT): a randomized controlled trial.  Diabetes Care. 2003;26(8):2250-2255
PubMed   |  Link to Article
Taylor CB, Miller NH, Reilly KR,  et al.  Evaluation of a nurse-care management system to improve outcomes in patients with complicated diabetes.  Diabetes Care. 2003;26(4):1058-1063
PubMed   |  Link to Article
Vivian EM. Improving blood pressure control in a pharmacist-managed hypertension clinic.  Pharmacotherapy. 2002;22(12):1533-1540
PubMed   |  Link to Article
Wick A, Koller MT. Views of patients and physicians on follow-up visits: results from a cross-sectional study in Swiss primary care.  Swiss Med Wkly. 2005;135(9-10):139-144
PubMed
Birtwhistle RV, Godwin MS, Delva MD,  et al.  Randomised equivalence trial comparing three month and six month follow up of patients with hypertension by family practitioners.  BMJ. 2004;328(7433):204-209
PubMed   |  Link to Article

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The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
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For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
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