Poor treatment fidelity, also known as noncompliance or nonadherence, is responsible for significant waste in healthcare resources and poor outcomes among patients with multiple chronic conditions (MCC).1,2 Minimally disruptive medicine seeks to address the fundamental causes of poor patient adherence to therapies by mitigating the burden that prescribed treatments place on patients’ lives.3 This requires an individualized approach that takes into account the patient’s comorbidities, socio-personal context, and personal preferences. A key step toward minimally disruptive medicine is acknowledging that healthcare for patients with MCC involves work that patients have to do, which sometimes exceeds their capacity and overwhelms them, leading to poor treatment fidelity.4–6
Over one quarter of Americans are labeled as having MCC, and one of the most common chronic conditions among patients with MCC is type 2 diabetes mellitus.7 Diabetes causes premature loss of quality and duration of life around the world.8 Clinical practice guidelines seek to promote optimal evidence-based care for people with diabetes. However, quality gaps in the healthcare of patients with diabetes emerge when clinicians fail to follow guideline recommendations or when the guidelines do not provide adequate guidance to clinicians. Guidelines are often used to measure performance and quality of care; however, the performance measures typically do not consider the role of other chronic conditions.7 Moreover, guideline recommendations are not effective if patients cannot or will not implement guideline-based recommendations in their lives.9
Current diabetes management guidelines are complex and multifaceted. Implementing their recommendations may require patients to substantially adapt and change the way they and their caregivers live.10 The complexity of recommendations is compounded for patients with MCC who are managing competing tasks with additive burden of treatment.6,11 When multiple management priorities arise and conflict, clinicians may deviate from guidelines to manage these patients according to different priorities, manage them less aggressively, or focus on one condition and postpone attention to others. Clinicians doing the latter may be labeled as showing “clinical inertia” with respect to the conditions they deprioritized; patients might do the same, consequently facing the stigma of being labeled as “noncompliant.”12
Although there is a paucity of research on improving health outcomes in patients with MCC,13 it is clear that patient-centered care that includes consideration of personal context is important to patients,14 and there is support that patient-centered decision making favorably impacts patient outcomes, including diabetes self-care.15,16 Despite limited evidence to support this approach on the basis of health-related outcomes alone, we consider patient-centered care as a core feature of high quality healthcare.17
For this reason, guidelines should be developed with a patient-centered—as opposed to disease-centered—focus.18 In response to the heavy burden guideline-recommended care places on patients with MCC, useful guidelines should consider patients’ values and preferences as well as their clinical and socio-personal contexts. This requirement is consistent with the second principle of evidence-based medicine (ie, research evidence alone is never enough to make treatment recommendations).19–22 The inclusion of the point of view of multiple stakeholders, such as patients with MCC and their caregivers, should enable guideline panels to make pertinent recommendations for these patients and improve their usefulness. Consequently, this and other markers of high-quality practice guidelines should relate to the extent to which guidelines offer pertinent recommendations for patients with MCC.
In lieu of guidelines for patients with MCC, we systematically reviewed guidelines for the care of patients with type 2 diabetes, a common condition among patients with MCC, to note their quality and assess the extent to which these guidelines took into account comorbidities, socio-personal context, and personal preferences in formulating their recommendations.
Two of the investigators (L.M.S. and V.M.M.) developed an analytic framework that included a rubric to capture elements of recommendations for the management of adult patients with type 2 diabetes mellitus. Six recommendations typically included in type 2 diabetes mellitus guidelines were determined a priori for inclusion in the rubric based on expert opinion to ensure comparability between guidelines. To aid in interpretation and graphical comparison, we classified 3 of the recommendations as pertaining to treatment burden (ie, blood glucose self-monitoring, healthcare visit frequency, taking aspirin) and the other 3 as pertaining to treatment goals (ie, blood pressure, glycemic control, low-density lipoprotein [LDL]-cholesterol). The recommendations pertaining to treatment burden were chosen because blood glucose monitoring, attending to healthcare visits, and taking additional medicines (including aspirin) all contribute to the day-to-day work that is required of patients with type 2 diabetes mellitus and are representative of challenges patients with diabetes face. Work that patients must do to comply with treatment not only matters to patients,14 but perceptions about this work also reliably predict adherence.5 However, we acknowledge the challenge in identifying the most burdensome aspects of diabetes care for individual patients, especially given that burden is contextual (eg, the burden of picking up a prescription from the pharmacy will be greater for a patient without reliable transportation than for another receiving medicines by mail).
The 3 patient contexts determined a priori for inclusion in the rubric were comorbidities, socio-personal context, and patient preferences. We chose these contexts as a minimum set to characterize the effort guideline panels made to consider the patient’s context. Comorbidities referred to any other medical conditions—including chronic medical conditions—the patient had to manage in addition to diabetes. We sought to capture any consideration of conditions that could affect the efficacy, safety, or feasibility of treatments or self-care (eg, coronary disease, heart failure, renal impairment, depression, chronic pain, or disability). Socio-personal context emphasized a patient’s living conditions, which in turn reflect aspects of the means patients have to carry out the treatment recommendation, including factors such as financial means, social capital, and caregiver support, which may hinder or promote adoption of the recommended action. Personal preferences included incorporation of the patient’s personal goals of treatment, lifestyle choices, preferred treatment intensity, and values and preferences regarding risks and benefits of treatment options, including side effects. Recognizing the latter 2 contexts are rather broad terms and wanting to be as generous as possible in rewarding guidelines, a point was given for socio-personal context any time consideration was given for a patient’s means to carry out the recommendation, and similarly, a point was given for personal preferences when any indication was given that the patient’s personal wishes and desires should be taken into account.
Figure 1 describes the rubric. A guideline received 1 point for each of the 3 patient contexts (ie, comorbidities, socio-personal context, and patient preferences) that it included as a reason to modify each of the 6 recommendations (ie, blood glucose self-monitoring, healthcare visit frequency, taking aspirin, blood pressure goal, glycemic control goal, and LDL-cholesterol goal). Only the contexts and recommendations included in the rubric were considered. The maximum possible raw score was 18 (6 recommendations×3 patient contexts). If a guideline did not make a recommendation included in the rubric, it received no points for that recommendation. The final context score resulted from dividing the raw score by the number of possible points (ie, the number of recommendations included in the guideline×3 patient contexts) to arrive at a percentage so that only recommendations included in each guideline were considered. This percentage thus quantifies the extent to which the guideline took into account patient context when formulating recommendations included in the rubric, when such recommendations were made in the guideline.
Data Sources and Search Strategies
We conducted a comprehensive search of Ovid Medline In-Process & Other Non-Indexed Citations, Ovid MEDLINE, Ovid EMBASE, Scopus, EBSCO CINAHL, and the National Guideline Clearinghouse from January 2006 to September 2012. Given that incorporation of patient context in the context of evidence-based medicine is a growing trend, the search strategy was limited to articles published in the last 6 years in order to report on the current state of modern diabetes mellitus type 2 guidelines (ie, those currently being implemented in clinical practice). The search strategy, which an experienced research librarian designed and conducted, is included in Supplemental Digital Content 1, https://links.lww.com/MLR/A558. We did not search for gray literature (ie, guidelines published behind institutional firewalls) as we thought private guidelines would have limited reach, and we had no reason to believe they would be more or less patient-centered than publicly available ones.
Selection and Data Extraction
Eligible guidelines reported treatment recommendations for adult patients with diabetes mellitus type 2 in English. These criteria were established a priori. Two reviewers reviewed the titles and abstracts the search strategy yielded for full text retrieval. Full reports were evaluated in a similar manner for eligibility with disagreements resolved by consensus. Data extraction was calibrated with a subset of 10% of included guidelines. Reviewers extracted data about contextualization of recommendations from each of the eligible guidelines and also judged the general quality of each of these guidelines using the AGREE II instrument.23 We also evaluated guidelines for mention of 2 other important features that might increase the likelihood of patient-centered guidelines: inclusion of a methodologist and a patient representative on the guideline panel. Clinicians trained in clinical epidemiology and experts in the application of state-of-the-art guideline formulation approaches, such as GRADE,19 may assist guideline panels in considering the role of context in adjusting their confidence in estimates and the role of values and preferences in determining confidence in their recommendations. Patient representatives might increase the likelihood that panels will consider aspects relevant and important to patients when formulating recommendations, as highlighted by the Institute of Medicine and others.19,20,24
We use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standard in reporting this systematic review.25
We identified 902 potentially eligible guidelines, of which 28 satisfied inclusion criteria (Table 1). Reasons for exclusion included outdated versions of included guidelines (1 article), duplicates of already included guidelines that escaped electronic duplicate detection (2 articles), or executive summaries of guidelines but not the complete guideline, published between 2006 and 2012 (Fig. 2). During this process, we achieved substantial chance-adjusted interrater agreement (k=0.74).
The overall methodological quality of the guidelines was low (using the AGREE II instrument, with mean overall score of 56%, SD=23%) (Supplemental Digital Content 2, https://links.lww.com/MLR/A559 for item and subscale scores). Thirteen (46%) guidelines did not report on the process used to generate recommendations. Patients or methodologists were not explicitly included in the guideline development process in 20 (71%) and 24 (86%) guidelines, respectively.
Guidelines most frequently offered recommendations about treatment goals: about glycemic control targets in 27 (96%) and about LDL-cholesterol targets in 20 (71%) guidelines. Fewer guidelines made recommendations taking into context the overall burden of treatment; for instance, 16 (57%) made recommendations about healthcare visit frequency (Table 1).
Contextualization of Guidelines
Tables 2 and 3 show the recommendations made in guidelines, contexts considered in recommendations, overall context score (ie, the extent to which the guideline took into account patient context among included recommendations), and overall AGREE II scores (a measure of guideline quality). There was complete absence of incorporation of social-personal context, patient preferences, and comorbidities in 11 (39%), 16 (57%), and 8 (29%) guidelines, respectively. Figure 3 depicts the distribution of patient context domains by type of clinical recommendations.
Most diabetes guidelines are lacking in the extent to which they explicitly take into account the context of patients with MCC. When patient context was considered in guidelines, it was often in the form of “blanket statements” in the Introduction section, instructing clinicians to apply the guidelines with consideration of individual patient context but offering no specific guidance on how to prioritize tasks that compete for patients’ time, effort, and attention. Although incorporation of patient context was poor overall, guidelines tended to take into account medical comorbidities to a greater extent than socio-personal context or personal preference. When they did this, however, they considered these comorbidities biologically (ie, as a source of physiological interactions) rather than in terms of cumulative complexity or target patient-centered outcomes. When recommendations were categorized on the basis of whether they represented treatment goals or treatment burden, neither category of recommendation appeared to address patient context more than the other.
Limitations and Strengths of Our Analysis
The main limitations of this work are that we used a rubric with only face validity to ascertain context and that we did not contact the guideline authors to uncover implicit considerations of context. The main strengths of our work include the reproducibility of our guideline inclusion, assessment of guideline quality and contextualization, use of a reproducible rubric, and the selection of contemporary guidelines in one of the chronic conditions receiving most quality-of-care attention. The rubric used here might be adaptable to other chronic conditions by substituting the condition-specific recommendations with ones pertinent to other conditions at hand (in terms of treatment goals and treatment burden) and scoring guidelines according to whether their recommendations take into account patient context (ie, comorbidities, socio-personal context, and patient preferences).
How Our Findings Compare With Other Guideline Assessments
To our knowledge, this is among the first studies to systematically evaluate the extent to which diabetes management guidelines take into account patient context and consider how MCC might affect recommendations for patients with a common comorbidity. Many have commented, however, about the need to contextualize recommendations among patients with MCC.54–58 A recent review of Canadian clinical practice guidelines for high-prevalence conditions, including diabetes, hypertension, and dyslipidemia, found that comorbidities, barriers to implementation, and patient context such as life expectancy were given adequate consideration by only a minority of guidelines. Consistent with our findings, when recommendations were made in the guidelines, they were vague and nonspecific.54
Implications for Guideline Development and Research
One proposed explanation for the paucity of consideration given to patient context in guideline recommendations is that there might be an insufficient body of evidence to inform modification of single-disease recommendations when considering patients with complex contexts, such as patients with MCC. Clinical trials often exclude or underrepresent patients with certain comorbid conditions, and subgroup analyses are rarely conducted against socio-personal features. The role of personal preferences—particularly when competing priorities exist—also remains poorly studied. This might be limiting the ability of guideline developers to reach evidence-based conclusions that address these aspects of care.56,58 Tinetti et al6 have proposed a focus on patient-important outcomes as a way of harmonizing recommendations for patients with MCC; however, the most common recommendations in guidelines we reviewed have poor connection with such outcomes (ie, lowering HbA1c is not uniformly associated with improvements in functional capacity or symptom burden). Weak or tentative guideline recommendations take place when the trade-offs are unclear or when the pros and cons of alternative courses of action are closely matched. In these instances it is optimal to engage patients in the decision-making process. When guideline panels fail to detect these situations, they might instead frame them as technical “just do it” dictums that are often used to inform quality-of-care parameters and leave little room for patient involvement.56,58 This naturally leads to a tendency to “overtreat” or “treat to numbers,” which might cause more harm than good.56,58 A recent editorial has provided an extended example of how recommendations to achieve “tight” glycemic control might need to be modified to account for comorbidities, socio-personal context, and patient preferences.59
The GRADE approach emphasizes the need to devote more effort to shared decision making when recommendations are weak, in order to ensure that the choice made reflects the patient’s values and preferences.60 However, even in the context of strong recommendations, GRADE highlights a need to frame recommendations in the context of different values and preferences, which may lead to opposite courses of action based on the same evidence when various outcomes are weighed differently.60 In this vein, it may be helpful to include in specific recommendations an explicit statement of the preferred outcome judgments that the recommendation was based on.60 Another way this can be achieved in the framework of current guidelines is to make recommendations along with reasons why a patient may choose to deviate from the recommended course.60 It is clear, however, on the basis of our review, that these principles from the GRADE approach have not fully penetrated the realm of diabetes guidelines.
Other specific approaches to improve clinical practice guidelines by incorporating patient context and comorbidities have been proposed. For example, van Weel and Schellevis57 propose categorizing comorbidities as causal (diseases sharing a common pathophysiology), complicating (those that are disease specific), intercurrent (acute, interacting illnesses), and concurrent (no specific relation) in order to identify focus areas and separate comorbidities by the approach required to address them. Piette and Kerr61 offer a similar classification of comorbidities for people with diabetes as being dominant, concordant, discordant, symptomatic, and asymptomatic. Dominant comorbidities are those that command so much attention that they overshadow diabetes (eg, cancer, cognitive impairment). Concordant comorbidities (similar to those classified by van Weel and Schellevis as “causal”) share the same pathophysiology as diabetes and fit in the management plan for diabetes (eg, hypertension, peripheral vascular disease). In contrast, discordant comorbidities (similar to those referred to as “concurrent” by van Weel and Schellevis) are unrelated to diabetes in their pathophysiology or management (eg, chronic back pain, asthma). With symptomatic comorbidities (eg, depression, gastroesophageal reflux disease), the main focus is on symptom management and quality of life, although limited attention may be given to prevention of long-term complications. In contrast, the focus on asymptomatic comorbidities (eg, hypertension, hyperlipidemia) is solely on preventing long-term complications.61
Calculating and reporting a “payoff time” for guideline recommendations, over which a patient must comply with the guideline so as to achieve the proposed benefit, has also been proposed in order to help patients weigh guideline compliance with their comorbidities and personal context.55 As an example, a patient with limited life expectancy having difficulty maintaining tight glycemic control on oral antihyperglycemic pharmacotherapy should balance the payoff time for tight glycemic control with insulin to prevent long-term complications of diabetes with the burden and cost of regular blood glucose monitoring, risk of hypoglycemia, and the cost of the insulin regimen required. If the payoff time is greater than the patient’s life expectancy, a discussion in the context of shared decision making about foregoing insulin therapy may lead to a decreased burden of treatment with a corresponding increase in quality of life, improved cost-benefit, and more patient-centered care.
Although some have suggested the development of guidelines focused on specific population subsets (eg, patients with a disease plus specific comorbidities), it is unrealistic to develop guidelines that cover every possible permutation of patient circumstances, especially in the case of multimorbidity and preference-sensitive decisions.57 Instead, clinical practice guidelines must take a holistic approach, which provides practical guidance clinicians can use to individualize care while focusing on patient-important rather than disease-centered outcomes.6,57 Individualization of care to incorporate patient context and preferences necessitates patient participation in decision making. Guidelines should offer tentative recommendations when these might apply to patients with MCC, opening the space for conversations with patients and shared decision making.62,63 In the absence of these enlightened approaches, high-fidelity adherence to current guidelines results in an overwhelming number of clinical actions and an absurd accumulation of work and complexity to which clinicians and patients can only respond with noncompliance.
Although algorithmic guidelines are relatively simple to implement, individualized care is less straightforward, as there is little guidance to help clinicians individualize care.64 Although there is limited evidence in the literature on ways to improve outcomes for patients with complex contexts, including MCC,13 we urge those developing guidelines for chronic conditions to consider patient context in every recommendation they make and to offer specific modifications (in action, timing, or intensity) based on comorbidities, socio-personal context, and patient preferences.
Extant clinical practice guidelines for one chronic disease sometimes consider the context of the patient with that disease but do so narrowly and infrequently. Guideline panels must remove their contextual blinders if they want to practically guide the care of patients with MCC.
The authors thank Larry Prokop at the Mayo Clinic Libraries for assistance in conducting the literature search. The authors also acknowledge Hannah Fields for her contribution to the screening process.
1. Herman WH, Hoerger TJ, Brandle M, et al..The cost-effectiveness of lifestyle modification or metformin in preventing type 2 diabetes in adults with impaired glucose tolerance.Ann Intern Med.2005;142:323–332.
2. .National Diabetes Fact Sheet. 2007. Available at: http://www.cdc.gov/diabetes/pubs/estimates07.htm
. Accessed March 29, 2010.
3. May C, Montori VM, Mair FS.We need minimally disruptive medicine.BMJ.2009;339:b2803.
4. Shippee ND, Shah ND, May CR, et al..Cumulative complexity: a functional, patient-centered model of patient complexity can improve research and practice.J Clin Epidemiol.2012;65:1041–1051.
5. Vijan S, Hayward RA, Ronis DL, et al..Brief report: the burden of diabetes therapy: implications for the design of effective patient-centered treatment regimens.J Gen Intern Med.2005;20:479–482.
6. Tinetti ME, Bogardus ST Jr, Agostini JV.Potential pitfalls of disease-specific guidelines for patients with multiple conditions.N Engl J Med.2004;351:2870–2874.
7. .Multiple chronic conditions measurement framework. 2012. Available at: http://www.qualityforum.org/Publications/2012/05/MCC_Measurement_Framework_Final_Report.aspx
. Accessed March 23, 2013.
8. .Diabetes fact sheet. Sheet number 312. November 2009. Available at: http://www.who.int/mediacentre/factsheets/fs312/en/
. Accessed March 29, 2010.
9. Huang ES, Brown SE, Ewigman BG, et al..Patient perceptions of quality of life with diabetes-related complications and treatments.Diabetes Care.2007;30:2478–2483.
10. Fried TR, McGraw S, Agostini JV, et al..Views of older persons with multiple morbidities on competing outcomes and clinical decision-making.J Am Geriatr Soc.2008;56:1839–1844.
11. Struijs JN, Baan CA, Schellevis FG, et al..Comorbidity in patients with diabetes mellitus: impact on medical health care utilization.BMC Health Serv Res.2006;6:84.
12. Phillips LS, Branch WT, Cook CB, et al..Clinical inertia.Ann Intern Med.2001;135:825–834.
13. Smith SM, Soubhi H, Fortin M, et al..Interventions for improving outcomes in patients with multimorbidity in primary care and community settings.Cochrane Database Syst Rev.2012;4:CD006560.
14. Eton DT, Ramalho de Oliveira D, Egginton JS, et al..Building a measurement framework of burden of treatment in complex patients with chronic conditions: a qualitative study.Patient Relat Outcome Meas.2012;3:39–49.
15. Heisler M, Bouknight RR, Hayward RA, et al..The relative importance of physician communication, participatory decision making, and patient understanding in diabetes self-management.J Gen Intern Med.2002;17:243–252.
16. Weiner SJ, Schwartz A, Sharma G, et al..Patient-centered decision making and health care outcomes: an observational study.Ann Intern Med.2013;158:573–579.
17. .Crossing the Quality Chasm: A New Health System for the 21st Century.Washington, DC: The National Academies Press; 2001.
18. Tinetti ME, Fried TR, Boyd CM.Designing health care for the most common chronic condition—multimorbidity.JAMA.2012;307:2493–2494.
19. Andrews J, Guyatt G, Oxman AD, et al..GRADE guidelines: 15. Going from evidence to recommendations: the significance and presentation of recommendations.J Clin Epidemiol.2013;66:719–725.
20. Graham R, Mancher M, Wolman DM, Greenfield S, Steinberg E.Current Best Practices and Proposed Standards for Development of Trustworthy CPG's: Part 1, Getting Started.Clinical Practice Guidelines We Can Trust.2011:Chapter 4.Washington, DC:The National Academies Press;84–86. http://www.iom.edu/Reports/2011/Clinical-Practice-Guidelines-We-Can-Trust.aspx
21. Guyatt GH, Haynes RB, Jaeschke RZ, et al..Users’ Guides to the medical literature: XXV. Evidence-based medicine: principles for applying the Users’ Guides to patient care. Evidence-Based Medicine Working Group.JAMA.2000;284:1290–1296.
22. Murad MH, Montori VM, Guyatt GH.Incorporating patient preferences in evidence-based medicine.JAMA.2008;300:2483author reply 2483-2484.
23. .Appraisal of Guidelines Research & Evaluation. September 2001. Available at: http://www.agreecollaboration.org/pdf/agreeinstrumentfinal.pdf
. Accessed March 30, 2010.
24. Garces JPD, Lopez GJP, Wang Z, et al..Eliciting patient perspective in patient-centered outcomes research: a meta narrative systematic review. Patient-Centered Outcomes Research Institute, 2012. Available at: http://www.pcori.org/assets/Eliciting-Patient-Perspective-in-Patient-Centered-Outcomes-Research-A-Meta-Narrative-Systematic-Review.pdf
. Accessed March 23, 2013.
25. Moher D, Liberati A, Tetzlaff J, et al..Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.PLoS Med.2009;6:e1000097.
26. Alsafadi H, Morrissey J, Patel V.The updated Alphabet Strategy: facilitating the implementation of NICE guidelines.Diabetes Prim Care.2009;11:148–160.
27. .Standards of medical care in diabetes—2012.Diabetes Care.2012;35suppl 1S11–S63.
28. .Diabetes management in correctional institutions.Diabetes Care.2010;33suppl 1S75–S81.
29. .Clinical Practice Guideline for the Management of Diabetes Mellitus.2010.Washington, DC:Department of Veteran Affairs, Department of Defensehttp://www.healthquality.va.gov/diabetes/DM2010_FUL-v4e.pdf
30. Bantle JP, Wylie-Rosett J, Albright AL, et al..Nutrition recommendations and interventions for diabetes: a position statement of the American Diabetes Association.Diabetes Care.2008;31suppl 1S61–S78.
31. Bruno G, De Micheli A, Frontoni S, et al..Highlights from “Italian Standards of care for Diabetes Mellitus 2009-2010”.Nutr Metab Cardiovasc Dis.2011;21:302–314.
32. Handelsman Y, Mechanick JI, Blonde L, et al..American Association of Clinical Endocrinologists Medical Guidelines for Clinical Practice for developing a diabetes mellitus comprehensive care plan.Endocr Pract.2011;17suppl 21–53.
33. .Global guideline for type 2 diabetes: recommendations for standard, comprehensive, and minimal care.Diabet Med.2006;23:579–593.
34. Jellinger PS, Davidson JA, Blonde L, et al..Road maps to achieve glycemic control in type 2 diabetes mellitus: ACE/AACE Diabetes Road Map Task Force.Endocr Pract.2007;13:260–268.
35. Guzman JR, Lyra R, Aguilar-Salinas CA, et al..Treatment of type 2 diabetes in Latin America: a consensus statement by the medical associations of 17 Latin American countries. Latin American Diabetes Association.Rev Panam Salud Publica.2010;28:463–471.
36. Ko SH, Kim SR, Kim DJ, et al..2011 clinical practice guidelines for type 2 diabetes in Korea.Diabetes Metab J.2011;35:431–436.
37. Leszczyszyn-Pynka M, Pynka S.Management of the blood glucose abnormalities in HIV-infected Patients.HIV AIDS Rev.2006;5:25–27.
38. Amod A, Ascott-Evans B, Berg G, et al..The 2012 SEMDSA guideline for the management of type 2 diabetes.J Endocrinol Metab Diabetes S Afr.2012;17:S1–S95.
39. Matthaei S, Bierwirth R, Fritsche A, et al..Medical antihyperglycaemic treatment of type 2 diabetes mellitus: update of the evidence-based guideline of the German Diabetes Association.Exp Clin Endocrinol Diabetes.2009;117:522–557.
40. Maynard G, Wesorick DH, O’Malley C, et al..Subcutaneous insulin order sets and protocols: effective design and implementation strategies.J Hosp Med.2008;3suppl29–41.
41. .Management of Diabetes Mellitus, 2010. Available at: http://www.med.umich.edu/1info/fhp/practiceguides/diabetes/mqic.diabetes.pdf
. Accessed June 4, 2011.
42. .Wisconsin Diabetes Mellitus Essential Care Guidelines.2012.Madison, WI:Department of Health Serviceshttp://www.dhs.wisconsin.gov/publications/P4/P49356.pdf
43. .Guideline for the care of the older adult with diabetes. 2007. Available at: http://www.joslin.org/docs/Guideline_For_Care_Of_Older_Adults_with_Diabetes.pdf
. Accessed June 4, 2011.
44. Nathan DM, Buse JB, Davidson MB, et al..Management of hyperglycemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy: a consensus statement from the American Diabetes Association and the European Association for the Study of Diabetes.Diabetes Care.2006;29:1963–1972.
45. .Type 2 diabetes: the management of type 2 diabetes. NICE clinical guidelines. 2009. Available at: http://publications.nice.org.uk/type-2-diabetes-cg87
. Accessed October 5, 2012.
46. Qaseem A, Humphrey LL, Sweet DE, et al..Oral pharmacologic treatment of type 2 diabetes mellitus: a clinical practice guideline from the American College of Physicians.Ann Intern Med.2012;156:218–231.
47. Riethof M, Flavin P, Lindvall B, et al..Diagnosis and Management of Type 2 Diabetes Mellitus in Adults.2012.Bloomington, MN:Institute for Clinical Systems Improvement (ICSI)https://www.icsi.org/_asset/3rrm36/Diabetes-Interactive0412.pdf
48. Rodbard HW, Jellinger PS, Davidson JA, et al..Statement by an American Association of Clinical Endocrinologists/American College of Endocrinology consensus panel on type 2 diabetes mellitus: an algorithm for glycemic control.Endocr Pract.2009;15:540–559.
49. Rydén L, Standl E, Bartnik M, et al..Guidelines on diabetes, pre-diabetes, and cardiovascular diseases: full text.Eur Heart J Suppl.2007;9suppl CC3–C74.
50. .Management of diabetes. A national clinical guideline. 2010. Available at: http://guideline.gov/content.aspx?id=16394
. Accessed October 5, 2012.
51. Sigal RJ, Kenny GP, Wasserman DH, et al..Physical activity/exercise and type 2 diabetes: a consensus statement from the American Diabetes Association.Diabetes Care.2006;29:1433–1438.
52. Menendez Torre E, Lafita Tejedor J, Artola Menendez S, et al..Recommendations for the pharmacologic treatment of hyperglycemia in type 2 diabetes. Consensus document.Nefrologia.2011;31:17–26.
53. Vijan S, Ci Choe H, Funnell MM, et al..University of Michigan Health System Type 2 Diabetes Guideline Update. 2009. Available at: http://cme.med.umich.edu/pdf/guideline/dm08.pdf
54. Mutasingwa DR, Ge H, Upshur RE.How applicable are clinical practice guidelines to elderly patients with comorbidities
?Can Fam Physician.2011;57:e253–e262.
55. Braithwaite RS, Concato J, Chang CC, et al..A framework for tailoring clinical guidelines to comorbidity at the point of care.Arch Intern Med.2007;167:2361–2365.
56. Fitzgerald SP, Bean NG.An analysis of the interactions between individual comorbidities
and their treatments—implications for guidelines and polypharmacy.J Am Med Dir Assoc.2010;11:475–484.
57. van Weel C, Schellevis FG.Comorbidity and guidelines: conflicting interests.Lancet.2006;367:550–551.
58. .Patient-centered care for older adults with multiple chronic conditions: a stepwise approach from the American Geriatrics Society.J Am Geriatr Soc.2012;60:1957–1968.
59. Lipska KJ, Montori VM.Glucose control in older adults with diabetes mellitus-more harm than good?: comment on “The association between hypoglycemia and dementia in a biracial cohort of older adults with diabetes mellitus”.JAMA Intern Med.2013;10:1–2.
60. Andrews J, Guyatt G, Oxman AD, et al..GRADE guidelines: 14. Going from evidence to recommendations: the significance and presentation of recommendations.J Clin Epidemiol.2013;66:719–725.
61. Piette JD, Kerr EA.The impact of comorbid chronic conditions on diabetes care.Diabetes Care.2006;29:725–731.
62. Jaeschke R, Guyatt GH, Dellinger P, et al..Use of GRADE grid to reach decisions on clinical practice guidelines when consensus is elusive.BMJ.2008;337:a744.
63. Stiggelbout AM, Van der Weijden T, De Wit MP, et al..Shared decision making: really putting patients at the centre of healthcare.BMJ.2012;344:e256.
64. Weiner SJ, Schwartz A, Weaver F, et al..Contextual errors and failures in individualizing patient care: a multicenter study.Ann Intern Med.2010;153:69–75.