Abstract
The simultaneous presence of multiple conditions in one patient (multi-morbidity) is a key challenge facing healthcare systems globally. It potentially threatens the coordination, continuity and safety of care. In this paper, we report the results of a scoping review examining the impact of multi-morbidity on the quality of healthcare. We used its results as a basis for a discussion of the challenges that research in this area is currently facing. In addition, we discuss its implications for health policy and clinical practice. The review identified 37 studies focussing on multi-morbidity but using conceptually different approaches. Studies focusing on ‘comorbidity’ (i.e. the ‘index disease’ approach) suggested that quality may be enhanced in the presence of synergistic conditions, and impaired by antagonistic or neutral conditions. Studies on ‘multi-morbidity’ (i.e. multiplicity of problems) and ‘morbidity burden’ (i.e. the total severity of conditions) suggested that increasing number of conditions and severity may be associated with better quality of healthcare when measured by process or intermediate outcome indicators, but with worse quality when patient-centred measures are used. However, issues related to the conceptualization and measurement of multi-morbidity (inconsistent across studies) and of healthcare quality (restricted to evaluations for each separate condition without incorporating considerations about multi-morbidity itself and its implications for management) compromised the generalizability of these observations. Until these issues are addressed and robust evidence becomes available, clinicians should apply minimally invasive and patient-centred medicine when delivering care for clinically complex patients. Health systems should focus on enhancing primary care centred coordination and continuity of care.
Patients with multi-morbidity might be at a higher risk of receiving poor healthcare, but strong empirical evidence is lacking.
Clinicians should apply minimally invasive and patient-centred medicine when delivering care for clinically complex patients.
Health systems should enhance primary care centred coordination and continuity of care.
INTRODUCTION
The increasing prevalence of long-term conditions is the main challenge facing healthcare systems globally (Citation1). Patients with multiple health conditions, known as multi-morbidity (Citation2), constitute a significant proportion of patients in primary care (Citation3). Multi-morbidity presents an increasing tension between desired healthcare models that are truly centred on the patient and current health services, which are usually organized around the diagnosis and management of individual health conditions (Citation4). This tension has the potential to be particularly detrimental to patients with higher degrees of multi-morbidity, who may receive poor quality of healthcare. People suffering from multiple health conditions are more likely to require an increased number of healthcare processes, which will also trigger the involvement of an increased number of health professionals (Citation5). This increased complexity in the delivery of healthcare may threaten coordination, continuity and safety, thereby decreasing the likelihood of receiving care that meets high standards for quality (Citation6,Citation7). The high prevalence of polypharmacy with aging may lead to an increased risk of inappropriate drug use, under-use of effective treatments, medication errors, poor adherence, drug–drug and drug–disease interactions and, most importantly, adverse drug reactions (Citation8).
Alternatively, it may be also argued that the increased interaction with the health services might result in increased opportunities for receiving effective care (Citation9). The presence of synergistic morbidities (i.e., those representing parts of the same overall pathophysiologic risk profile and therefore more likely to be the focus of the same disease and self-management plan) may also provide increased incentives for both patients and professionals for adhering to guidelines for recommended care (Citation10). It is possible, however, that the described threats and benefits operate simultaneously. Therefore, in order to increase our understanding in this area, evidence from empirical studies is much needed. However, research in this complex area is facing a number of important challenges that limits its progression.
In this article, we present the results of a scoping review to ‘map’ existing empirical evidence on the impact of multi-morbidity on quality in primary care. Subsequently, we use that information to discuss the limitations and challenges that research in this field is currently facing. Finally, we discuss its implications for health policy, research and clinical practice.
METHODS
A detailed description of the methodology used for the scoping literature review is available in Box 1. Scoping reviews have been defined as ‘a form of knowledge synthesis that addresses an exploratory research question aimed at mapping key concepts, types of evidence, and gaps in research related to a defined area or field by systematically searching, selecting, and synthesizing existing knowledge’ (Citation11). We selected a scoping (rather than a systematic) literature review approach because (a) the impact of multi-morbidity on quality of healthcare constitutes an emerging research field, and (b) scoping reviews have been identified as a more suitable method to inform practice, policymaking, and research (Citation11).
To identify relevant studies, one reviewer searched Medline for studies of any design published from inception to February 2015 (search strategy available in the online supplementary Appendix Table 1 to be found online at http://informahealthcare.com/doi/abs/10.3109/13814788.2015.1046046).
The bibliographic search also included a manual search (using free key words) in Google Scholar and the examination of the references included in relevant studies that were identified a priori.
To be eligible for inclusion, studies had to include empirical research examining the quality of healthcare provided to patients with multi-morbidity in the context of primary care.
Four separate multi-morbidity constructs were taken into account:
Multi-morbidity: the presence of more than one distinct condition in an individual.
Co-morbidity: any distinct additional entity that has existed or may occur during the clinical course of a patient who has the index disease under study.
Morbidity burden: overall impact of the different diseases in an individual taking into account their severity.
Clinical complexity: the overall impact of the different diseases in an individual taking into account their severity and other health-related attributes.
Quality of healthcare was conceptualized according to the definition proposed by Campbell et al.: ‘whether individuals can access the health structures and processes of care which they need and whether the care received is effective’ (Citation15).
All studies falling into these conceptualizations were included, regardless of the methodology used to measure quality and multi-morbidity.
We did not exclude studies based on language, country, or date of publication.
Initially, references’ titles and abstracts were screened for relevance. Subsequently, identified articles’ full-text was read.
Findings were extracted using a structured template.
We searched Medline for studies published from inception to February 2015 (search strategy available in the online supplementary Appendix Table 1 to be found online at http://informahealthcare.com/doi/abs/10.3109/13814788.2015.1046046). We included studies containing empirical research examining the quality of healthcare provided to patients with multi-morbidity in the context of primary care.
In accordance to the framework proposed by Valderas et al. (Citation2), four separate multi-morbidity constructs were taken into account: multi-morbidity (‘the presence of more than one distinct condition in an individual’), comorbidity (‘any distinct additional entity that has existed or may occur during the clinical course of a patient who has the index disease under study’), morbidity burden (‘overall impact of the different diseases in an individual taking into account their severity’), and clinical complexity (‘the overall impact of the different diseases in an individual taking into account their severity and other health-related attributes’) (Citation2,Citation12–14).
Quality of healthcare was conceptualized according to the definition proposed by Campbell et al., ‘whether individuals can access the health structures and processes of care which they need and whether the care received is effective’ (Citation15).
RESULTS
Results of the literature review are outlined in Box 2. All 37 empirical studies identified (Citation16–52) were published during the previous decade, and had been mostly conducted in the United States. The studies included measures of multi-morbidity, comorbidity and/or morbidity burden, but none measured patient complexity. The vast majority of the studies measured quality of healthcare based on either condition-specific indicators of healthcare processes (e.g. percentage of patients with diabetes with a record of retinal screening during the last 12 months; percentage of patients with heart failure that were offered anticoagulation therapy, etc.) and/or intermediate outcomes (e.g. percentage of patients with diabetes whose last measure of glycated haemoglobin was ≤ 7.5%; percentage of patients with hypertension whose last blood pressure reading was ≤ 140/80 mm Hg, etc.), or on patient-reported information on patient-centred care (e.g. patients’ ratings of patient–provider communication; patient experiences of relational and management continuity, etc.).
The bibliographic search retrieved 1622 unique references. After abstract and full text screening, 37 relevant empirical studies examining the association between multi-morbidity and quality of healthcare were identified (Citation16–52).
All the studies published during the last decade, mostly in the United States.
The studies included measures of multi-morbidity (absolute number of health conditions), co-morbidity (health conditions present in addition to an index disease) or morbidity burden (using metrics that take into account both the number and severity of conditions), but none of them measured patient complexity (which additionally considers socio-demographic characteristics of the individuals).
Quality of healthcare was measured based on condition specific indicators of processes of care and/or intermediate outcomes, or on patient reported information of patient centred care.
Studies on multi-morbidity and morbidity burden suggested that increased severity and number of conditions may be associated with better quality of healthcare as measured by condition specific indicators of processes and intermediate outcomes, but with worse quality of healthcare when it is measured using a patient-centred approach, such as patient-reported impact.
Studies analysing the impact of co-morbidity suggested that quality of healthcare measured by condition specific indicators may be enhanced in the presence of synergistic combinations of conditions (i.e. conditions that share a patho-physiological pathway), and possibly impaired by the presence of antagonistic or neutral conditions.
Multi-morbidity
In the 10 studies specifically examining the impact of multi-morbidity on quality of healthcare (), the approach used to measure multi-morbidity varied substantially both in terms of the type of long-term conditions examined and the methods used to group patients according to number of conditions (Citation23,Citation24,Citation27,Citation29,Citation30, Citation33,Citation41,Citation43–45).
Table 1. Evidence for the impact of multi-morbidity on quality and safety of healthcare.
Studies consistently observed that multi-morbidity had an impact on the quality of healthcare, but the nature of the impact (positive or negative association) seemed to be dependent on the methodology used to measure the quality of healthcare. All six studies that focused on process or outcomes indicators observed a positive association between multi-morbidity and quality and safety (i.e., patients with multi-morbidity received higher quality and safety of healthcare than patients with no or only one condition), whereas all four studies using patient-reported information of quality of healthcare observed a negative association (Citation23,Citation24,Citation27,Citation29,Citation30, Citation33,Citation41,Citation43–45).
Morbidity burden
Out of the four studies identified examining the impact of morbidity burden on quality of healthcare) (), just one study focused on patient-reported experiences, observing worst quality of healthcare among patients with higher levels of morbidity burden (Citation18,Citation25,Citation40,Citation41). All of the remaining three studies used quality indicators of processes of care and/or intermediate outcomes and observed a positive association between morbidity burden and quality of healthcare, except for one study (Citation25,Citation40,Citation41).
Table 2. Evidence for the impact of morbidity burden on quality and safety of healthcare.
Comorbidity
The vast majority of studies (n = 24; 65%) actually focused on the additional impact that comorbid conditions had on the healthcare for an index condition () (Citation16,Citation17,Citation19–22,Citation26, Citation28,Citation31,Citation32,Citation34–39,Citation42,Citation46–52). The index condition most frequently examined was diabetes (nine studies); followed by hypertension and depression (three studies each). Ten of the studies restricted their analysis to the number of comorbidities or the degree of burden, whereas the rest of them examined the specific impact of each comorbidity or group of comorbidities (synergistic and antagonistic) on quality of healthcare.
Table 3. Evidence for the impact of co-morbidity on quality and safety of healthcare.
In general, the results suggested that quality of healthcare measured by condition-specific indicators might be enhanced in the presence of synergistic combinations of conditions, and possibly impaired by the presence of antagonistic conditions (i.e. those not directly related in either their pathogenesis or management). This pattern was especially apparent for those studies examining quality of healthcare provided to patients with diabetes; a fact that supports the framework proposed by Piet et al., on the impact of comorbidity for diabetes care, but that would be in principle applicable to many other index conditions (Citation53).
DISCUSSION
Current challenges in research on quality of healthcare for patients with multi-morbidity
Although some patterns seem to emerge from our review, a word of caution is needed before embracing the available evidence, as there are important issues related to the measurement of both multi-morbidity and quality of healthcare that compromise the generalization of these studies.
Definition and measurement of multi-morbidity. First, there is a lack of consistency not only in the selection of the construct for characterizing clinical complexity (multi-morbidity, comorbidity, and morbidity burden), but also in the very definition of each of them, impairing our ability to pool results across studies (Citation54). There are very good reasons why researchers and policymakers may want to focus specifically on selected groups of patients with multi-morbidity, such as those with chronic conditions, those with conditions considered unrelated, or those with a particularly high number of concurrent conditions (three or more, sometimes four or more conditions). It makes little sense, however, to redefine multi-morbidity constantly so that it incorporates specifications such as those listed above, which should be used to further characterize multi-morbidity, instead of used to define its boundaries. The very same is applicable to comorbidity as a specification of multi-morbidity.
Defining the populations of interest is therefore one of the key challenges for advancing research and improving care for patient with multi-morbidity and there is little doubt that a focus on the most prevalent chronic conditions, and on the different combinations (clusters) that underlay the emergence of multi-morbidity, is clearly a priority (Citation55).
Definition and measurement of quality healthcare for multi-morbidity. Second, but also crucial to progress in our understanding of this research area, is establishing what constitutes quality healthcare for patients with multi-morbidity. There is no doubt that quality for patients with multi-morbidity must take into account the evidence for the management of each individual condition. High quality healthcare for a patient with hypertension, osteoarthritis and chronic obstructive pulmonary disease must be informed by best practice guidelines for each of these three conditions. However, it is also essential to incorporate considerations about multi-morbidity itself and its implications for management. We can hardly speak of high quality of healthcare for patients with multi-morbidity if the potentially antagonistic goals are not adequately addressed, interactions between the corresponding medications are not carefully examined, and adequate coordination does not ensure smooth follow-up and monitoring of each of the conditions, while at the same time avoiding overexposing the patient to unnecessary healthcare. And yet all these issues have been grossly overlooked, restricting evaluations to the specifics of care for each separate condition and considering the evaluation of care as a whole the same as the sum of discrete evaluations of care for each condition.
We still lack thoroughly validated and well-established indicators that are fit for this purpose, as it is still unclear what constitutes good or poor healthcare when we think in terms of patients with multi-morbidity. Quality of healthcare is defined in relation to standards, and the key issue here is that we lack clear standards for patients with multi-morbidity. The applicability of current evidence-based guidelines to multi-morbid patients is limited, and can be problematic (Citation56,Citation57). Not providing guideline-consistent care for people with multi-morbidity cannot necessarily be equated with poor quality of care (an assumption made in all previous studies), as this may actually reflect care that is sensitive to the particular needs of these patients. Most guidelines do not provide explicit guidance on treatment of patients with comorbidity. Guidelines should be more explicit about the applicability of their recommendations to patients with comorbidity (Citation58). However, this is not helped by the lack of clinical trials that include patients with multi-morbidity (Citation59).
A recent systematic review shed some light on what type of primary care based interventions might be effective to improve health outcomes of patients with multi-morbidity (Citation60). That review identified 10 studies and their results suggested that organizational interventions which either targeted specific risk factor management, or focused on areas where patients have more difficulties (such as medicines management), were more likely to be effective. However, other organizational interventions with a broader focus (notably case management or changes in care delivery) or patient-oriented interventions that are not linked to healthcare delivery appeared to be less effective. These findings provide some evidence for what can be considered to constitute high quality of healthcare for patients with multi-morbidity. However, more research is needed to confirm the results.
Implications
Health policy. Although far from conclusive, the evidence suggests that the quality of care for specific conditions is enhanced in the presence of concordant conditions and possibly also impaired in the presence of discordant conditions. Efforts are needed to ensure that continuity and coordination of care for these patients is ensured, as the evidence suggests that patients with multi-morbidity recognize the potential for improvement in these areas (Citation61). Interestingly, the evidence suggests that complex models of care (such as case management) do not necessarily pay off and when it does, it may not be scalable to the wider majority of patients with multi-morbidity, making the use of already available alternatives, such as the enhancement of primary care services, a valid and potentially more efficient response (Citation60,Citation62). Importantly, until we have a better understanding of the implications of multi-morbidity for quality, not to mention the availability of multi-morbidity specific indicators, incentives systems that reward quality of healthcare should be more cautious in their definitions of eligible populations, allowing for the exclusion of selected patients from the incentives system based on clinical criteria (this is already the case for the quality and outcomes framework, the primary care pay for performance system in the UK) (Citation63).
Research. There is no doubt that we need more and better designed epidemiological research on the impact of multi-morbidity on quality and safety (Citation3). In that sense, so far the vast majority of the studies on this area have been conducted in the US, and there is very limited information from European countries—where well-developed primary care systems are more frequent. We cannot simply expect that the results from the studies in the US are transferable to European countries. In order to increase our understanding of the magnitude and nature of the impact of multi-morbidity on quality of healthcare in the European context, health system-specific research is very much needed. We also need research that helps us understand how to make best use of the available tools; e.g. how best to integrate evidence systematically from different clinical practice guidelines for providing care for these complex patients (Citation64). There is also a substantial lack of evidence on what is the impact of multi-morbidity at the population level (the mix of conditions in the population served by a primary health care provider) on the organization and delivery of healthcare. Moreover, a greater emphasis in the incorporation of patient-reported information in multi-morbidity studies is needed in order to account for patients’ perception of those problems that interfere more in their everyday lives.
Clinical practice. What now for busy clinicians for whom multi-morbidity is the bread and butter of their daily practice? Clinicians should approach the management of patients with multi-morbidity much as they would approach the management of any given group of patients: carefully weighing up the evidence supporting any recommendations for that particular group and tailoring to each individual's needs. Given the current state of the evidence, if there ever was a dichotomy between art and science in medicine, this is clearly an area where clinical practice is closer to the former than to the latter. The principles of minimally invasive medicine and patient-centred medicine might provide helpful guidance for decision making in everyday practice for patients with multi-morbidity (Citation65,Citation66).
Conclusion
Although patients with multi-morbidity are in theory at higher risk of receiving poor quality of healthcare, the evidence is inconsistent and suggests that there may also be potential benefits of current arrangements for the delivery of care. Indicators of the quality of healthcare that are based on available evidence are very much needed before progress can be made in this field. In the absence of evidence for the benefits and harm of available management options clinicians should be thoughtful when delivering care for these patients, using minimally invasive medicine and patient-centred medicine as guidance for everyday practice. Health systems should focus on enhancing primary care centred coordination and continuity of care and designing incentives systems that reward appropriate care for these patients.
Supplementary material available online
Supplementary Appendix Table 1 to be found online at http://informahealthcare.com/doi/abs/10.3109/13814788.2015.1046046.
igen_a_1046046_sm8027.docx
Download MS Word (13.9 KB)Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.
REFERENCES
- Alwan A. Global status report on noncommunicable diseases 2010. Geneva: World Health Organization; 2011. Available at: http://www.who.int/nmh/publications/ncd_report2010/en/ (accessed 7 December 2014).
- Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: Implications for understanding health and health services. Ann Fam Med. 2009;7:357–63.
- Violan C, Foguet-Boreu Q, Flores-Mateo G, Salisbury C, Blom J, Freitag M, et al. Prevalence, determinants and patterns of multimorbidity in primary care: A systematic review of observational studies. PloS one 2014;9:e102149.
- Starfield B. Threads and yarns: Weaving the tapestry of comorbidity. Ann Fam Med. 2006;4:101–3.
- Payne RA, Abel GA, Guthrie B, Mercer SW. The effect of physical multimorbidity, mental health conditions and socioeconomic deprivation on unplanned admissions to hospital: A retrospective cohort study. CMAJ 2013;185:E221–28.
- Cresswell KM, Fernando B, McKinstry B, Sheikh A. Adverse drug events in the elderly. Br Med Bull. 2007;83:259–74.
- Wehling M. Multimorbidity and polypharmacy: How to reduce the harmful drug load and yet add needed drugs in the elderly? Proposal of a new drug classification: Fit for the aged. J Am Geriatr Soc. 2009;57:560–1.
- Nobili A, Garattini S, Mannucci PM. Multiple diseases and polypharmacy in the elderly: Challenges for the internist of the third millennium. J Comorbidity 2011;1:28–44.
- Valderas JM, Ricci-Cabello I, Violan-Fors C. The impact of multi-morbidity on quality and safety of healthcare in theory and in practice: A primary care perspective. In: Salisbury C, Fortin M, Mercer S, editors. ABC of multimorbidity. 1st ed. Chichester: John Wiley & Sons; 2014. pp. 38–41.
- National Health Service. Quality and outcomes framework United Kingdom: NHS; 2012. Available at: http://www.qof.ic.nhs.uk/ (accessed 7 December 2014).
- Colquhoun HL, Levac D, O’Brien KK, Straus S, Tricco AC, Perrier L, et al. Scoping reviews: Time for clarity in definition, methods, and reporting. J Clin Epidemiol. 2014;67:1291–4.
- Feinstein AR. The pre-therapeutic classification of co-morbidity in chronic disease. J Chron Dis. 1970;23:455–68.
- Ritchie C. Health care quality and multimorbidity: The jury is still out. Med Care 2007;45:477–9.
- Safford MM, Allison JJ, Kiefe CI. Patient complexity: More than comorbidity. the vector model of complexity. J Gen Intern Med. 2007;3:382–90.
- Campbell SM, Roland MO, Buetow SA. Defining quality of care. Soc Sci Med. 2000;51:1611–25.
- Ahern MM, Hendryx M. Avoidable hospitalizations for diabetes: Comorbidity risks. Dis Manage 2007;10:347–55.
- Ani C, Bazargan M, Hindman D, Bell D, Rodriguez M, Baker RS. Comorbid chronic illness and the diagnosis and treatment of depression in safety net primary care settings. J Am Board Fam Med. 2009;22:123–35.
- Burgers JS, Voerman GE, Grol R, Faber MJ, Schneider EC. Quality and coordination of care for patients with multiple conditions: Results from an international survey of patient experience. Eval Health Prof. 2010;33:343–64.
- Chaudhry SI, Berlowitz DR, Concato J. Do age and comorbidity affect intensity of pharmacological therapy for poorly controlled diabetes mellitus? J Am Geriatr Soc. 2005;53:1214–6.
- Desai MM, Rosenheck RA, Druss BG, Perlin JB. Mental disorders and quality of diabetes care in the veterans health administration. Am J Psychiatry 2002;159:1584–90.
- Druss BG, Zhao L, Cummings JR, Shim RS, Rust GS, Marcus SC. Mental comorbidity and quality of diabetes care under Medicaid: A 50-state analysis. Med Care 2012;50:428–33.
- Fisher DA, Galanko J, Dudley TK, Shaheen NJ. Impact of comorbidity on colorectal cancer screening in the veterans healthcare system. Clin Gastroenterol Hepatol 2007;5:991–6.
- Fung CH, Setodji CM, Kung F-Y, Keesey J, Asch SM, Adams J, et al. The relationship between multimorbidity and patients’ ratings of communication. J Gen Intern Med. 2008;23:788–93.
- Gulliford M, Cowie L, Morgan M. Relational and management continuity survey in patients with multiple long-term conditions. J Health Serv Res Policy 2011;16:67–74.
- Halanych JH, Safford MM, Keys WC, Person SD, Shikany JM, Kim YI, et al. Burden of comorbid medical conditions and quality of diabetes care. Diabetes Care 2007;30:2999–3004.
- Harman JS, Edlund MJ, Fortney JC, Kallas H. The influence of comorbid chronic medical conditions on the adequacy of depression care for older Americans. J Am Geriatr Soc. 2005;53:2178–83.
- Higashi T, Wenger NS, Adams JL, Fung C, Roland M, McGlynn EA, et al. Relationship between number of medical conditions and quality of care. N Engl J Med. 2007;356:2496–504.
- Lagu T, Weiner MG, Hollenbeak CS, Eachus S, Roberts CS, Schwartz JS, et al. The impact of concordant and discordant conditions on the quality of care for hyperlipidemia. J Gen Intern Med. 2008;23:1208–13.
- Min LC, Wenger NS, Fung C, Chang JT, Ganz DA, Higashi T, et al. Multimorbidity is associated with better quality of care among vulnerable elders. Med care 2007;45:480–8.
- Parchman ML, Noel PH, Lee S. Primary care attributes, health care system hassles, and chronic illness. Med Care 2005;43: 1123–9.
- Pentakota SR, Rajan M, Fincke BG, Tseng C-L, Miller DR, Christiansen CL, et al. Does diabetes care differ by type of chronic comorbidity?: An evaluation of the Piette and Kerr framework. Diabetes care 2012;35:1285–92.
- Petersen LA, Woodard LD, Henderson LM, Urech TH, Pietz K. Will hypertension performance measures used for pay-for- performance programs penalize those who care for medically complex patients? Circulation 2009;119:2978–85.
- Schnitzer S, Kuhlmey A, Adolph H, Holzhausen J, Schenk L. Complaints as indicators of health care shortcomings: Which groups of patients are affected? Int J Qual Health Care 2012; 24:476–82.
- Singh JA, Hodges JS, Asch SM. Opportunities for improving medication use and monitoring in gout. Ann Rheum Dis. 2009; 68:1265–70.
- Teh CF, Reynolds CF 3rd, Cleary PD. Quality of depression care for people with coincident chronic medical conditions. Gen Hosp Psychiatry 2008;30:528–35.
- Turner BJ, Hollenbeak CS, Weiner M, Ten Have T, Tang SS. Effect of unrelated comorbid conditions on hypertension management. Ann Intern Med. 2008;148:578–86.
- Virani SS, Woodard LD, Chitwood SS, Landrum CR, Urech TH, Wang D, et al. Frequency and correlates of treatment intensification for elevated cholesterol levels in patients with cardiovascular disease. Am Heart J. 2011;162:725–32e1.
- Vitry AI, Roughead EE, Preiss AK, Ryan P, Ramsay EN, Gilbert AL, et al. Influence of comorbidities on therapeutic progression of diabetes treatment in Australian veterans: A cohort study. PloS One 2010;5:e14024.
- Voorham J, Haaijer-Ruskamp FM, Wolffenbuttel BH, de Zeeuw D, Stolk RP, Denig P. Differential effects of comorbidity on antihypertensive and glucose-regulating treatment in diabetes mellitus—a cohort study. PloS One 2012;7:e38707.
- Werner RM, Chang VW. The relationship between measured performance and satisfaction with care among clinically complex patients. J Gen Intern Med. 2008;23:1729–35.
- Woodard LD, Landrum CR, Urech TH, Wang D, Virani SS, Petersen LA. Impact of clinical complexity on the quality of diabetes care. Am J Manag Care 2012;18:508–14.
- Woodard LD, Urech T, Landrum CR, Wang D, Petersen LA. Impact of comorbidity type on measures of quality for diabetes care. Med Care 2011;49:605–10.
- Mand P, Roth K, Biertz F, Kersting M, Kruschinski C, Schmiemann G, et al. Drug-disease interaction in elderly patients in family practice. Int J Clin Pharmacol Ther. 2014;52:337–45.
- Min L, Kerr EA, Blaum CS, Reuben D, Cigolle C, Wenger N. Contrasting effects of geriatric versus general medical multimorbidity on quality of ambulatory care. J Am Geriatr Soc. 2014; 62:1714–21.
- Tsang C, Bottle A, Majeed A, Aylin P. Adverse events recorded in English primary care: observational study using the general practice research database. Br J Gen Pract. 2013;63:e534–42.
- Buja A, Gini R, Visca M, Damiani G, Federico B, Donato D, et al. Need and disparities in primary care management of patients with diabetes. BMC Endocr Disord. 2014;14:56.
- Doubova SV, Lamadrid-Figueroa H, Perez-Cuevas R. Use of electronic health records to evaluate the quality of care for hypertensive patients in Mexican family medicine clinics. J Hypertens. 2013;31:1714–23.
- Wirtz HS, Boudreau DM, Gralow JR, Barlow WE, Gray S, Bowles EJ, et al. Factors associated with long-term adherence to annual surveillance mammography among breast cancer survivors. Breast Cancer Res Treat. 2014;143:541–50.
- Cancian M, Battaggia A, Celebrano M, Del Zotti F, Novelletto BF, Michieli R, et al. The care for chronic heart failure by general practitioners. Results from a clinical audit in Italy. Eur J Gen Pract. 2013;19:3–10.
- Frigola-Capell E, Verdu-Rotellar JM, Comin-Colet J, Davins-Miralles J, Hermosilla E, Wensing M, et al. Prescription in patients with chronic heart failure and multimorbidity attended in primary care. Qual Prim Care 2013;21:211–9.
- Werner-Busse A, Kostev K, Heine G, Worm M. Impact of comorbidities on the treatment of atopic dermatitis in clinical practice. Int J Clin Pharmacol Ther. 2014;52:726–31.
- Sharif R, Cuevas CR, Wang Y, Arora M, Sharma G. Guideline adherence in management of stable chronic obstructive pulmonary disease. Respir Med. 2013;107:1046–52.
- Piette JD, Kerr EA. The impact of comorbid chronic conditions on diabetes care. Diabetes Care 2006 29:725–31.
- Huntley AL, Johnson R, Purdy S, Valderas JM, Salisbury C. Measures of multimorbidity and morbidity burden for use in primary care and community settings: A systematic review and guide. Ann Fam Med. 2012;10:134–41.
- Islam MM, Valderas JM, Yen L, Dawda P, Jowsey T, McRae IS. Multimorbidity and comorbidity of chronic diseases among the senior Australians: Prevalence and patterns. PloS one 2014; 9:e83783.
- Lugtenberg M, Burgers JS, Clancy C, Westert GP, Schneider EC. Current guidelines have limited applicability to patients with comorbid conditions: A systematic analysis of evidence-based guidelines. PloS One 2011;6:e25987.
- Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: Implications for pay for performance. J Am Med Assoc. 2005;294:716–24.
- Boyd CM, Leff B, Wolff JL, Yu Q, Zhou J, Rand C, et al. Informing clinical practice guideline development and implementation: Prevalence of coexisting conditions among adults with coronary heart disease. J Am Geriatr Soc. 2011;59:797–805.
- Fortin M, Stewart M, Poitras ME, Almirall J, Maddocks H. A systematic review of prevalence studies on multimorbidity: Toward a more uniform methodology. Ann Fam Med. 2012;10: 142–51.
- Smith SM, Soubhi H, Fortin M, Hudon C, O’Dowd T. Interventions for improving outcomes in patients with multimorbidity in primary care and community settings. Cochrane Database Syst Rev. 2012;4:CD006560.
- Roland M, Paddison C. Better management of patients with multimorbidity. Br Med J. 2013;346:f2510.
- Starfield B, Shi L, Macinko J. Contribution of primary care to health systems and health. Milbank Q. 2005;83:457–502.
- BMA. QOF guidance 2012–2013 (fifth revision). Available at: http://bma.org.uk/practical-support-at-work/contracts/independent-contractors/qof-guidance (accessed 7 December 2014).
- Muth C, Beyer M, Fortin M, Rochon J, Oswald F, Valderas JM, et al. Multimorbidity's research challenges and priorities from a clinical perspective: The case of ‘Mr Curran’. Eur J Gen Pract. 2014;20:139–47.
- May C, Montori VM, Mair FS. We need minimally disruptive medicine. Br Med J. 2009;339:b2803.
- Lin GA, Dudley RA. Patient-centered care: What is the best measuring stick? Arch Intern Med. 2009;169:1551–3.