Impact of multi-morbidity on quality of healthcare and its implications for health policy, research and clinical practice. A scoping review

Figures & data

Table 1. Evidence for the impact of multi-morbidity on quality and safety of healthcare.

Study (Ref.)	Measurement of multi-morbidity	Measurement of quality of healthcare	Observed association^a
Mand, 2014 (43)	Number of conditions (Beers list)	Number of potential drug– disease interactions	Direct association
Min, 2014 (44)	Number of general medical (atrial fibrillation, coronary artery disease, congestive heart failure, cerebrovascular disease, diabetes mellitus, hypertension) and geriatric (hearing impairment, dementia, falls, urinary incontinence, malnutrition, and osteoporosis) conditions.	65 ambulatory-care quality indicators related to care processes.	Direct association for general medical multi-morbidity (indirect association for geriatric multi- morbidity).
Tsang, 2013 (45)	Number of conditions (expanded diagnostic clusters in ACG system).	Incidence of recorded iatrogenic harm in general practice.	Direct association.
Schnitzer, 2012 (33)	Patients with at least three diseases or explicitly self-reporting to have multi-morbidity.	Patient complaints.	Inverse association
Woodard, 2012 (41)	Number of the following conditions (in addition to diabetes): hypertension, ischaemic heart disease, hyperlipidaemia, depression, arthritis, and chronic obstructive pulmonary disease. Patients were classified as having 0, 1, 2, or 3 of these comorbidities.	Quality of diabetes care (intermediate outcomes).	Direct association.
Gulliford, 2011 (24)	Number of patient reported long-term conditions. Patients were classified as having 0, 1, 2, 3, or 4 long-term conditions.	Patient-reported experiences of healthcare (relational and management continuity).	Inverse association for management continuity. No association for relational continuity.
Fung, 2008 (23)	Two approaches were used: 1. Count of individual conditions: the number of chronic conditions co-occurring in each participant was summed, without considering any concordance among the conditions. 2. Count of condition groups: concordant conditions were grouped together and the number of condition groups co-occurring in each participant was counted. Patients were subsequently allocated to the following groups: 0 condition groups, 1–2 conditions groups, and 3 or more condition groups.	Composite measure of patients’ ratings of patient– physician communication.	Inverse association
Higashi, 2007 (27)	Total number of chronic conditions affecting each patient.	Quality indicators related to care processes covering 30 clinical conditions and preventive care.	Direct association.
Min, 2007 (29)	Coexisting combinations of 8 conditions (hypertension, coronary artery disease, chronic obstructive pulmonary disease, osteoarthritis, diabetes mellitus, depression, osteoporosis, and atrial fibrillation).	Quality indicators related to care processes covering 15 clinical conditions and preventive care.	Direct association.
Parchman, 2005 (30)	Patients with single chronic illness compared to those with multiple chronic illnesses.	Patient-reported experiences of healthcare,	Inverse association.

^aA direct association is one in which an increase in the number of conditions is associated with an increase in quality and safety of healthcare; and indirect association is one in which an increase in the number of conditions is associated with a decrease in quality and safety of healthcare.

Table 2. Evidence for the impact of morbidity burden on quality and safety of healthcare.

Study (Ref.)	Measurement of morbidity burden	Measurement of quality of healthcare	Observed association^a
Woodard, 2012 (41)	Morbidity burden was measured with the ‘Diagnostic cost group relative risk scores’ (consisting in a ratio of the patient's predicted cost to the average actual cost of the patient population).	Quality of diabetes care (intermediate outcomes)	Direct association
Burgers, 2010 (18)	‘Morbidity score’, consisting in a combination between the number of conditions and patient-reported health status.	Patient-reported experiences of healthcare.	Inverse association
Werner, 2008 (40)	Diagnostic cost groups–hierarchical condition categories (DCG) model, which uses age, sex, and diagnoses to summarize a patient's medical conditions.	Quality indicators covering clinical conditions and preventive care, and patient- reported satisfaction with care.	Direct association (all quality indicators and satisfaction with care)
Halanych, 2007 (25)	Charlson Comorbidity Index, which includes 17 specific illnesses and weights them according to severity.	Quality indicators covering use of common services for diabetic patients (A1C testing, lipid testing, dilated eye exam, and urinary micro-albumin testing)	No association.

^aA direct association is one in which an increase in the morbidity burden is associated with an increase in quality and safety of healthcare; and indirect association is one in which an increase in the morbidity burden is associated with a decrease in quality and safety of healthcare.

Table 3. Evidence for the impact of co-morbidity on quality and safety of healthcare.

Study (Ref.)	Index condition	Measurement of comorbidity	Measurement of quality of healthcare	Observed associationa
Buja, 2014 (46)	Diabetes mellitus	Charlson comorbidity index	Quality of diabetes care (guideline consistent processes).	Mixed associations for the different quality indicators. Impact by type of comorbidity was not examined.
Druss, 2012 (21)	Diabetes mellitus	Having or not one or more mental conditions in addition to diabetes mellitus.	Quality of diabetes care (intermediate outcomes and hospital admissions).	Indirect association (antagonist).
Pentakota, 2012 (31)	Diabetes mellitus	Patients were classified into five chronic comorbid illness groups: none, concordant only, discordant only, both concordant and discordant, and dominant.	Quality of diabetes care (guideline consistent processes and intermediate outcomes).	Direct association (synergistic conditions); inverse association (neutral/antagonistic conditions).
Voorham, 2012 (39)	Diabetes mellitus	Comorbidity was measured taking into account two dimensions: 1. concordance to diabetes (related versus unrelated conditions), and 2. degree of priority (considering as high priority those conditions that are life-interfering, incident or requiring new medication treatment).	Quality of diabetes care(intensification of pharmacological therapy)	Direct association (synergistic conditions); no association otherwise
Woodard, 2011 (42)	Diabetes mellitus	Patients were assigned to one of four condition groups: diabetes-concordant (hypertension, ischaemic heart disease, hyperlipidaemia), and/or discordant (arthritis, depression, chronic obstructive pulmonary disease) conditions, or neither.	Quality of diabetes care (intermediate outcomes).	Direct association (synergistic and antagonist conditions).
Vitry, 2010 (38)	Diabetes mellitus	Comorbid conditions unrelated to diabetes were identified by using prescription-dispensed data. Potential impact of related to diabetes comorbid conditions was not examined.	Quality of diabetes care (time to therapeutic progression of pharmacological therapy).	Inverse association (neutral and antagonistic conditions).
Ahern, 2007 (16)	Diabetes mellitus	Charlson comorbidity index.	Quality of diabetes care (avoidable hospitalizations due to short-term complications and uncontrolled diabetes).	Direct association (synergistic conditions); inverse association (antagonistic conditions).
Chaudhry, 2005 (19)	Diabetes mellitus	Charlson comorbidity index.	Quality of diabetes care(intensification of pharmacological therapy)	No association. Impact by type of comorbidity was not examined.
Desai, 2002 (20)	Diabetes mellitus	Only mental comorbidities were examined. Patients were categorized into one of four exclusive diagnostic groups: no mental comorbidity; psychiatric comorbidity only; substance (alcohol or drug) use comorbidity only; or dual diagnosis (psychiatric and substance use disorders).	Quality of diabetes care (processes of care and intermediate outcomes).	Indirect association (antagonists).
Doubova, 2013 (47)	Hypertension	Comorbidity was calculated based on the presence of diabetes mellitus and/or chronic kidney disease.	Quality of healthcare for hypertension(intermediate outcomes).	Indirect association.
Petersen, 2009 (32)	Hypertension	Patients were classified into four condition groups: those with hypertension concordant (diabetes mellitus, ischaemic heart disease, dyslipidaemia) and/or discordant (arthritis, depression, chronic obstructive pulmonary disease) conditions or neither.	Quality of healthcare for hypertension (guideline consistent processes and intermediate outcomes, and satisfaction with care).	Direct association (all synergistic, neutral, and antagonistic conditions).
Turner, 2008 (36)	Hypertension	Patients were classified according to the number of unrelated (antagonist) comorbid conditions(0, 1, 2, 3, 4, 5, 6, and 7 or more unrelated conditions), and related(synergistic) comorbid conditions (single vascular disease, multiple vascular diseases, chronic renal insufficiency, and diabetes).	Quality of healthcare for hypertension(intensification of pharmacological therapy).	Indirect association (antagonistic conditions).
Ani, 2009 (17)	Depression	Comorbidities were calculated based on the Charlson comorbidity index. Patients were classified in three groups: 1. no comorbidity and depression alone; 2. with a comorbidity index of 1 to 2 and depression; and 3. with a comorbidity index of 3 or greater and depression.	Quality of healthcare for depression(diagnosis, guideline-concordant treatment, and follow-up care)	No association. Impact by type of comorbidity was not examined.
Teh, 2008 (35)	Depression	Comorbidity calculated based on the presence of one or more comorbid condition(s) (yes/no), and patient-reported health status.	Patient-reported depression care quality.	Direct association for diagnosis of depression and antidepressant prescription. No association with receiving minimally adequate depression care or patient satisfaction. Impact by type of comorbidity was not explored.
Harman, 2005 (26)	Depression	Comorbid diabetes mellitus, hypertension, heart disease, and arthritis in older persons with depression were identified from patient self-report.	Depression treatment.	Direct association with hypertension and diabetes. No association for heart disease and arthritis.
Wirtz, 2014 (48)	Cancer (breast)	Charlson comorbidity index	Annual receipt of surveillance mammography.	Indirect association Impact by type of comorbidity was not explored.
Fisher, 2007 (22)	Cancer (colorectal)	Comorbidity measured with an adaptation of the Charlson comorbidity index.	Colorectal cancer screening,	No association. Impact by type of comorbidity was not explored.
Virani, 2011 (37)	Cardiovascular disease	Comorbidity measured as patients with history of diabetes mellitus (yes/no) and hypertension (yes/no).	Quality of healthcare for hyperlipidaemia (intensification of pharmacological therapy).	Direct association (synergistic conditions).
Lagu, 2008 (28)	Cardiovascular risk factors(including hypertension and hyperlipidaemia).	Concordant comorbidity was calculated as the sum of the following conditions: diabetes, coronary artery disease, coronary artery disease equivalent and renal insufficiency. Discordant comorbidity burden was calculated from an adapted version of Elixhauser's comorbidity measure (which uses ICD-9-CM-codes to identify 29 specified conditions associated with inpatient resource use and mortality).	Quality of healthcare for hyperlipidaemia (guideline consistent processes and intermediate outcomes).	Direct association (synergistic conditions); inverse association(antagonistic/neutral conditions).
Cancian, 2013 (49)	Chronic heart failure	Presence of another cardiovascular condition(ischaemic heart disease, atrial fibrillation), or other conditions (chronic obstructive pulmonary disease, renal failure, dementia).	Pharmacotherapy (adherence to evidence-based recommendations) and chronic heart failure related hospitalizations.	Pharmacotherapy: direct association for ischaemic heart disease, and indirect for chronic obstructive pulmonary disease and dementia. Hospitalizations: direct association for coronary disease aetiology, atrial fibrillation, kidney failure and chronic obstructive pulmonary disease.
Frigola-Capell, 2013 (50)	Chronic heart failure	Number of comorbidities, including; hypercholesterolaemia, hypertension, diabetes mellitus, ischaemic heart disease, chronic obstructive pulmonary disease and chronic kidney disease.	Pharmacotherapy (prescription of angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, and beta-blockers).	Direct association between the number of comorbidities and the prescription of recommended treatments. Impact by type of comorbidity was not explored.
Werner-Busse, 2014 (51)	Atopic dermatitis	One or more atopic conditions (allergic asthma, urticaria, allergic rhinitis and food allergy).	Adherence to evidence-based treatment recommendations.	Direct association. Impact by type of comorbidity was not explored.
Sharif, 2013 (52)	Chronic obstructive pulmonary disease	Number of conditions, including: hypertension or other cardiovascular disease (coronary artery disease, chronic heart failure, ischaemic or non-ischaemic cardiomyopathy), diabetes mellitus, anxiety or depression, osteoporosis, and lung cancer.	Providers’ adherence to the 2007 Global initiative for chronic obstructive lung disease (GOLD) guidelines for the pharmacotherapeutic management of patients with stable chronic obstructive pulmonary disease.	No association. Impact by type of comorbidity was not explored.
Singh, 2009 (34)	Gout	Charlson comorbidity index.	Adherence to evidence-based recommendations.	Indirect association. Impact by type of comorbidity was not explored.

^aSynergistic conditions are those that represent parts of the same overall pathophysiologic risk profile and are more likely to be the focus of the same disease and self-management plan. Antagonistic conditions are those not directly related in either their pathogenesis or management. A direct association is one in which an increase in number of comorbid conditions is associated with an increase in quality and safety of healthcare; and indirect association is one in which an increase in the number of comorbid conditions is associated with a decrease in quality and safety of healthcare.

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