The expansion of primary care and community-based service delivery systems is intended to meet emerging needs, reduce the costs of hospital-based ambulatory care and prevent avoidable hospital use by the provision of more appropriate care. Great emphasis has been placed on the role of self-management in the complex process of care of patient with long-term conditions. Several studies have determined that nurses, among the health professionals, are more recommended to promote health and deliver preventive programs within the primary care context. The aim of this systematic review and meta-analysis is to assess the efficacy of the nurse-led self-management support versus usual care evaluating patient outcomes in chronic care community programs. Systematic review was carried out in MEDLINE, CINAHL, Scopus and Web of Science including RCTs of nurse-led self-management support interventions performed to improve observer reported outcomes (OROs) and patients reported outcomes (PROs), with any method of communication exchange or education in a community setting on patients >18 years of age with a diagnosis of chronic diseases or multi-morbidity. Of the 7,279 papers initially retrieved, 29 met the inclusion criteria. Meta-analyses on systolic (SBP) and diastolic (DBP) blood pressure reduction (10 studies—3,881 patients) and HbA1c reduction (7 studies—2,669 patients) were carried-out. The pooled MD were: SBP -3.04 (95% CI -5.01—-1.06), DBP -1.42 (95% CI -1.42—-0.49) and HbA1c -0.15 (95% CI -0.32–0.01) in favor of the experimental groups. Meta-analyses of subgroups showed, among others, a statistically significant effect if the interventions were delivered to patients with diabetes (SBP) or CVD (DBP), if the nurses were specifically trained, if the studies had a sample size higher than 200 patients and if the allocation concealment was not clearly defined. Effects on other OROs and PROs as well as quality of life remain inconclusive.
Citation: Massimi A, De Vito C, Brufola I, Corsaro A, Marzuillo C, Migliara G, et al. (2017) Are community-based nurse-led self-management support interventions effective in chronic patients? Results of a systematic review and meta-analysis. PLoS ONE 12(3): e0173617. https://doi.org/10.1371/journal.pone.0173617
Editor: Sari Helena Räisänen, Helsingin Yliopisto, FINLAND
Received: November 27, 2016; Accepted: February 23, 2017; Published: March 10, 2017
Copyright: © 2017 Massimi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests: The authors have declared that no competing interests exist.
The global burden of non-communicable diseases (NCDs) is increasing rapidly and is expected to reach a prevalence of 57% in 2020, when such chronic conditions will outnumber acute conditions  and are likely to kill 38 million people each year . In addition, over the next 20 years, NCDs are projected to cost more than US$ 30 trillion to the health systems, with a dramatic impact on productivity and quality of life . The growing prevalence of NCDs, the aging population, rising patient expectations and the pressing need to contain costs lead to an increasing demand for primary care services, long term care services and reforms that move care from hospitals to the community, providing both first contact care and continuing care of individuals [4,5]. According to the Medical Home Model, the Institute for Healthcare Improvement (IHI) Model and the Chronic Care Model, only a productive interaction between an informed, activated patient and a prepared, proactive practice team can lead to improved outcomes . The caregiver team must be patient-centered, coordinated, multidisciplinary, multi-professional and skilled in self-management support [7,8].
In this health care context, the transfer of tasks from medical doctors to appropriately trained nurses (so-called ‘task shifting’) can reduce both the workload of physicians and the direct cost of care, while achieving the same high quality of care, good health outcomes and, eventually, higher levels of patient satisfaction [4, 9, 10]. The effectiveness of task shifting in primary care, together with changing the skill mix, has been well reported in the literature [11–13] and is gaining growing acceptance among policy-makers . Thus, the WHO has recommended that “continuous monitoring and evaluation must therefore be established as an integral component of the implementation process for task shifting […] and operational research should be developed alongside this implementation process” . Moreover, nurses are already recognized as playing increasingly important roles in primary health care, especially in long-term care programs and in discharge planning programs for in-patients with chronic diseases [16–18].
Primary care must regain its central role in the frontline management of chronic diseases, because poor control at this level leads inexorably to hospital overcrowding due to the need to treat complications [19, 20]. To achieve this, great emphasis has been placed on the role of patient self-management, underlining its importance in primary care  and in the complex process of the care of patients with long-term conditions [21, 22]. Nurses, because of their traditional holistic perspective, are well versed in self-care support and must play a leading role in the administration of these systematic educational interventions focused on preserving or enhancing health and self-management goal achievement of a patient previously clinically assessed with a chronic disease. Self-monitoring (of symptoms or of physiologic processes) and decision making (managing the disease treatment or exacerbation or its impact through self-monitoring) are the aims of the interventions . There are several primary studies that compare the impact of nurse-led interventions to support patient self-management with the more usual care-in-the-community programs for chronic patients [24–26]. However, to our knowledge, no systematic reviews on this specific topic are available in the literature; we therefore aim to provide such a systematic review in this study, and we also try to identify specific characteristics that might make interventions more effective.
Materials and methods
Selection criteria and search strategy
We carried out a systematic review of randomized control trials (RCTs) of nurse-led self-management support interventions performed with any method of communication exchange or education in a community setting on patients >18 years old with a diagnosis of chronic disease or multiple morbidity (see Table 1 for definitions). For this purpose, we drafted a protocol based on the population, intervention, comparison and outcome (PICO) approach  and the recommended guidelines for the reporting of systematic reviews and meta-analyses .
Studies aimed to evaluate the efficacy of a nurse-led self-management support intervention, compared to the usual care, to improve observer-reported outcomes (OROs) [29, 30]–particularly clinical outcomes–and patient-reported outcomes (PROs) [30, 31]as primary outcomes. We excluded studies that evaluated interventions in which nurses were only involved in medical assessment or therapy optimization and studies that enrolled patients with mental disorders. To ensure maximum retrieval, two reviewers with different skills in bibliographic search methodology and in nursing chronic disease management, searched together for RCTs in MEDLINE (to July 2016) using the strategy reported in S1 File. Additional searches in CINAHL, Scopus and Web of Science were carried out using similar syntax; experts were consulted and bibliographies of relevant articles were reviewed. Bibliographic search was restricted to studies reported in English. Each citation found in the databases was reviewed independently by two authors via a titles-first approach to obtain records for the abstract screening.
Study selection and quality assessment
Two reviewers independently reviewed the abstracts obtained in the search and retrieved the full text article of those that met the inclusion criteria. In cases of disagreement, full text article for review was retrieved. The methodological quality of the RCTs was assessed independently by two reviewers using the risk of bias approach described in the Cochrane Handbook . Random sequence generation, allocation concealment, blinding, incomplete outcome data, selective outcome reporting and other potential sources of bias were described and assessed. Any disagreements about methodological quality were resolved by discussion and, if necessary, a third reviewer was involved.
Two reviewers performed data extraction and data entry independently, in duplicate. Differences in data extraction were discussed and if necessary resolved by a third reviewer. A standardized form was used to abstract the following data: bibliographic details; population demographics; interventions; patient condition (diabetes, cardiovascular diseases (CVD), multichronic conditions); type of nurses employed in the study (RN: registered nurse; APN: advanced practice nurse); availability of specific training for the nurses that provide the intervention; type of intervention (face-to-face; telephone/telemedicine; mixed); duration of the intervention; study sample size; outcome data (continuous or binary).
A rating system, based on the methodological quality of the studies and on the consistency of the findings [33, 34], was used to assess the strength of the evidence for OROs and PROs. The results were synthesized and assigned one of the following three levels of scientific evidence:
- strong evidence: provided by generally consistent findings, supporting the hypotheses, in multiple high-quality studies;
- moderate evidence: provided by generally consistent findings, supporting the hypotheses, in one high quality study and one or more moderate quality studies, or in multiple moderate quality studies;
- insufficient evidence: only one study available or inconsistent findings in multiple studies.
To summarize continuous data, the pooled mean difference (MD) and 95% confidence interval (CI) were calculated . A random effect approach was chosen for all analyses to account for between-study variance . The fixed-effects model  was also used to check the level of agreement with random effects conclusions. The I2 metric, which describes the percentage of total variation across studies that was due to heterogeneity rather than sample error (chance) , was used to test for heterogeneity. If I2 was ≥60%, a sensitivity analysis was performed by removing the studies contributing to the heterogeneity. Results of studies reported in multiple articles were included once in each meta-analysis. Presence of publication bias was assessed through funnel plot graph.
Given the highly diverse nature of the studies analysed, several stratified meta-analyses were carried out to explore the efficacy in subgroups; meta-analyses were also carried out in the absence of statistical heterogeneity. In particular, we analyzed the effect of the following stratification factors: patient condition (diabetes, cardiovascular diseases (CVD), multichronic conditions); type of nurses employed in the study (RN: registered nurse; APN: advanced practice nurse); availability of specific training for the nurses that provide the intervention; type of intervention (face-to-face; telephone/telemedicine; mixed); duration of the intervention (≤6 months; >6 months); study sample size (≤200; >200); attrition rate (<20%; ≥20%); allocation concealment (clearly stated; undefined/absent).
All meta-analyses were performed using RevMan software, version 5.2 (Cochrane Collaboration, Oxford, UK, 2012). Reporting was made following the PRISMA Statement guidelines (see S2 File for the Checklist).
Main characteristics of the included studies
Of the 7,279 papers initially retrieved (Fig 1) 29, that describe the results of 23 studies, met our inclusion criteria (see S1 Table for a summary of the main characteristics and an overall quality score of the studies included in the review). A summary of the type of intervention and primary outcomes measured in each study is reported in Table 2.
From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(7): e1000097. doi: 10.1371/journal.pmed1000097.
The studies were published from 2000 to 2013, mainly in the USA (15), the UK (5) and the Netherlands (4). Overall, 10,162 patients were enrolled in the 23 studies (range: 51–1665), seven of which enrolled fewer than 200 patients. Six papers [39–44] reported analyses of previous studies [45–49], which extended the follow-up and/or took into account different outcomes; these were included in the meta-analyses as appropriate. Patients’ mean age was reported in all studies, ranging from 55.5  to 77.2  for the experimental group and from 54.8  to 78.1  for the control group. The majority of the papers assessed the efficacy of the interventions among patients affected by cardiovascular diseases (11), diabetes (9) or multichronic conditions (7). Only two papers took into account patients with COPD. Interventions were mainly carried out at patients’ homes (10 studies) and in general practices (five studies) by APNs (13 studies) and RNs (10 studies); the nurses were specially trained in 15 studies. It is interesting to note that self-management skills were appropriately assessed in patients by validated tools in only five studies.
The methodological quality was high in nine studies and moderate in another nine (S2 Table). Only one paper fulfilled all the criteria for reducing risk of bias. Eight studies failed to report only one of the criteria. Nine papers out of 29 did not report on the methods used to randomly allocate patients to groups and in 20 and 11 cases the allocation concealment and the blinding, respectively, were not sufficiently detailed or were clearly absent. Five studies were at high risk of bias for attrition.
Blood pressure levels.
Overall, 12 studies [24, 25, 39, 43, 44, 48, 50, 51–55] evaluated the levels of systolic blood pressure (SBP) as a primary outcome–on a total of 5,671 patients–showing strong evidence. Seven studies [24, 43, 48, 50, 52, 53, 55] out of 12 found that SBP levels were significantly lower in the experimental groups than in the control groups (Table 3); in particular, all studies with shorter interventions [24, 50, 52, 53] showed significant results.
The majority of effective interventions were carried out by advanced nurses/case managers [43, 48, 52, 53, 55]. A variety of intervention techniques were used: four out of the seven effective studies used face-to-face studies [24, 50, 55] or face-to-face/telephone  nurse visits; these were delivered at the patient’s home [50, 53], in nurse-led clinics , at local community activity centres  or in primary care clinics .
A meta-analysis on SBP reduction was carried out on 10 studies [24, 39, 44, 48, 50–55], involving a total of 3,881 patients. The pooled MD was -3.04 (95% CI -5.01 to -1.06) in favour of the interventions, with significant heterogeneity between studies (I2 = 55%, p = 0.02) (Fig 2).
Meta-analyses of subgroups showed a statistically significant effect if the interventions were delivered to diabetic patients (MD -2.56, 95% CI -4.82 to -0.31), if an APN was employed (MD -3.57, 95% CI -6.36 to -0.78), if the nurses were specially trained (MD -2.81, 95% CI -4.30 to -1.32), if the studies had a sample size greater than 200 patients (MD -0.13, 95% CI -0.25 to -0.01) and if the allocation concealment was not clearly defined (MD -2.54, 95% CI -5.04 to -0.56). Stratification by type of intervention failed to show a significant effect of any specific intervention. Neither length of intervention nor attrition rate influenced the results, which remained significant in favour of intervention (Table 4).
The same 12 studies [24, 25, 39, 43, 44, 48, 50–55] explored the effect on diastolic blood pressure (DBP) levels in a total of 5,671 patients with strong evidence (Table 3). Ten studies with 3,881 patients in total were included in the meta-analysis on the reduction in DBP [24, 39, 44, 48, 50–55]. A statistically significant reduction in DBP was found for the whole group (MD -1.42, 95% CI -1.42 to -0.49) with no statistically significant heterogeneity between studies (I2 = 34%, p = 0.14) (Fig 2). The analysis of the funnel plot showed a lack of studies with large sample size and high effect measures.
An attempt was made to identify possible influencing factors using stratified meta-analyses. A statistically significant effect was shown for interventions on patients with CVD (MD -2.09, 95% CI -4.11 to -0.07), specific training of nurses (MD -1.56, 95% CI 2.63–0.48), face-to-face interventions (MD -2.41, 95% -3.54 to -1.28), attrition rate lower than 20% (MD -1.68, 95% CI -2.93 to -0.43) and unclear presence of allocation concealment (-1.71, 95% CI -2.86 to -0.56). Stratification by type of nurse employed, by sample size and by duration of intervention did not influence the results, which remained significant in all subgroups (Table 4).
Of the 29 included studies, 11 [25, 39, 43, 48, 51, 54–59] investigated HbA1c levels as a primary outcome in diabetic patients, resulting in strong evidence of the efficacy of intervention. Overall, these studies included 4,207 patients. The levels of HbA1c were significantly lower in the experimental groups than in the control groups in four studies [25, 43, 48, 58] (Table 3). The two studies with statistically significant results and high methodological quality were based on one-to-one sessions with patients led by a skilled diabetes RN  and on telemedicine and videoconferencing carried out by specially trained nurses .
The results of seven studies [48, 51, 54–56, 58, 59], involving 2,669 patients, were useful for pooling data. The MD showed a reduction in HbA1c of 0.15 in favour of the experimental group (95% CI -0.32 to 0.01) with a heterogeneity of I2 = 28, p = 0.21 (Fig 2). The funnel plot showed that the results were based mainly on small studies with low-effect measures.
After stratification, statistical significance was shown for specific training of nurses (MD -0.13, 95% CI -0.25 to -0.01), intervention by telephone/telemedicine (MD -0.14, 95% CI -0.27 to -0.01), intervention length >6 months (MD -0.13, 95% CI -0.25 to -0.01) and a sample size of >200 people (MD -0.13, 95% CI -0.25 to -0.01). Stratification by type of nurse employed, attrition rate and presence of allocation concealment failed to show significant differences between intervention and control (Table 5). Moderate or insufficient evidence was obtained for the reduction of total cholesterol, LDL cholesterol, triglycerides and fasting serum glucose (Table 3).
Three studies [45, 60, 61], with an overall sample size of 2,564 patients, evaluated total mortality. The study of Delaney et al.  used the same population and intervention as Murchie et al.  but considered the results from 10 years of follow-up. For all four studies the total number of deaths in the experimental groups was lower than in the control groups, reaching statistical significance in two studies [45, 60] (Table 3); these studies were based on interventions lasting 12 months  or longer  on patients with coronary heart disease or chronic heart failure led by RNs  or APNs [60, 61]. Educational interventions were based on face-to-face visits carried out at nurse-run clinics  or hospital  with telephone follow-up [60, 61].
Multiple clinical outcomes.
Only one study  evaluated as a primary outcome the simultaneous reaching of a threshold in BP levels, LDL serum levels and percentage of HbA1c, taking into account 556 patients. A significantly higher percentage of patients in the intervention group reached the goals compared to the control group. The intervention consisted of an initial personal meeting with a nurse case manager, followed by follow-up telephone calls.
Patient reported outcomes
Quality of life.
Three studies [40, 63, 64] included changes in quality of life–evaluated with SF-36 [40, 64] or other questionnaires related to the specific disease aim of the study [63, 64]–as a primary outcome, but there was insufficient evidence of a significant effect. The overall scores of the questionnaires were analyzed. For two studies [40, 64] the overall scores in the experimental groups were higher rather than the control groups, but this result was only significant for the study of Murchie et al.  (Table 3). Educational interventions were based on face-to-face visits [40, 63] or telephone health mentoring  led by RNs [40, 64] or APNs .
Discussion and conclusions
Primary care systems across the world are facing the challenge of an ageing population and an associated increase in the number of chronic patients [65, 66], leading to a growing demand for a kind of care  that meets emerging needs, reduces the costs of hospital-based ambulatory care and prevents avoidable hospital use by the provision of more appropriate care systems. In this context, the rational redistribution of tasks among health workforce teams–namely task shifting –as a means of addressing this public health issue represents a potentially winning strategy. More particularly, serious attention has been payed to the support of patient self-management, since it can improve patient self-efficacy [8, 68], disease-related behaviors and, finally, enhance patients’ functional and health status [8, 69, 70]. Among health professionals, nurses can play a pivotal role in the delivery of self-management support interventions, particularly in areas of medical workforce shortage. This policy development clearly brings with it the need to continually seek updated evidence about the roles that nurses can undertake, their clinical effectiveness and cost-effectiveness in these roles, as well as patient satisfaction.
According to our systematic review and meta-analysis, nurse-led self-management support interventions in chronic care community programs have a positive impact on some OROs, such as a reduction in the levels of HbA1c, DBP/SBP and, to a lesser extent, LDL, particularly in patients with diabetes and CVD. Effects on other outcomes such as serum levels of total cholesterol, fasting serum glucose levels and triglycerides, as well as quality of life and all-causes mortality, remain inconclusive.
Diabetes and CVD are among the diseases that can most benefit from patient self-management. Empowering patients to manage their own diseases and fostering patient-centered activities can effectively reduce complications or reactivation of diseases that can shorten length of life and reduce autonomy. Self-management training in type 2 diabetes has evolved since the didactic primarily interventions of the 1970s into the empowerment models of the 1990s [69, 71]. Such a transformation has led to better glycemic control . Our results confirm this and suggest also that trained nurses can effectively administer self-management support interventions to type 2 diabetes patients [25, 43, 48, 58]. A study published in 2004 showed that a nurse-led education intervention led to the improvement of glycemic control and a delay in the requirement for insulin therapy in patients treated with oral hypoglycemic therapy . Moreover, our results show that nurse-led telemedicine interventions can also have a positive effect by reducing HbA1C levels [43, 48]. The remote monitoring and transmission of physiological data facilitate contact with a health care professional via telephone or video, while disease-specific education guarantees the reinforcement of self-management behaviors . More difficulties were encountered in reducing serum levels of LDL [25, 39, 43, 48, 55] and triglycerides  in patients with diabetes. This is of particular interest since LDL oxidation does not decrease after improvement in metabolic control in type 2 diabetes . Together with hypertriglyceridemia, LDL oxidation is involved in the pathogenesis of the so-called metabolic syndrome, which is associated with increased risk of CVD and for which lifestyle modification is an important therapeutic strategy . Therefore, developers of educational interventions should focus on general knowledge of diabetes, adherence to medication, lifestyle changes and, if possible, self-monitoring of blood glucose .
With respect to CVD, the results of our meta-analysis also show that nurses can be more effective than the usual care-in-the-community systems in improving blood pressure control, eventually leading to reduced blood pressure levels. This positive effect is clearer when nurses are specially trained and is more significant among diabetes patients for SBP levels and among CVD patients for DBP levels. Face-to-face interventions seem to be more effective, at least for the reduction of DBP levels, even though nurses also significantly improve self-management behavior by telephone interventions .
Nurse-led intervention is less effective at improving clinical outcomes in multi-chronic patients [24–26, 39, 44, 46, 49] probably because of the subjective and objective barriers to good self-management associated with this condition. Indeed, comorbidity has been mentioned in previous studies as a limit to self-care [76, 77]. A semi-structured interview study concluded that major barriers to self-care for people with more than one chronic disease are mainly linked to the combined effects of multiple conditions or to a single dominant disease making the management of the other conditions difficult. Other barriers were identified as a lack of patient knowledge about their conditions, financial constraints, low self-efficacy, inadequate communication with providers, the need for or use of social support and finally various logistical issues . Another qualitative study, which used patient focus groups, placed much more emphasis on the role of physician communication and family support as barriers to the self-management of their chronic conditions . Clearly, self-care interventions for people with multiple chronic diseases must be tailored to patients’ real needs, since they are likely to be more effective if targeted at particular risk factors or specific functional difficulties .
The finding that the benefits of nurse-led intervention to support patient self-management disappear when nurses are not specially trained is one of the most important results of this meta-analysis. Ad hoc training seems to be more important than the role and general experience of the nurse. In fact, the results of the meta-analyses show that APNs are more effective than RNs only in reducing SBP levels. Provider training is recognized to be a key factor in the entire self-management support intervention process. Studies that evaluated the effectiveness of in-person training have reported generally positive results [81–83]. However, promising results also derive from web-based self-management training for health professionals: webinar-based training sessions can benefit participants’ self-beliefs and confidence .
Several studies have determined that, among health professionals, nurses are best placed to promote health and to deliver preventive programs within the primary care context [85, 86]. Their employment as providers of self-management support programs in primary care can further improve the health status of chronic patients, even if the task shifting from physicians to nurses in this particular area requires specific education and training. Further research on the efficacy of nurse-led self-management support programs must focus on long-term outcomes. Evidence on the effect of these programs on mortality and hospitalization rates is still insufficient or lacking. Moreover, the evaluation of patient self-efficacy in experimental studies that use reliable and valid instruments is urgently required.
Finally, the methodological quality of RCTs must be improved. In many cases, in the particular context of trials that evaluate the efficacy of nurse-led interventions vs. physician-led interventions, blind participation in the intervention is not always possible. This was often acknowledged in the included studies, but it was not always counterbalanced by appropriate allocation concealment that, in such cases, is universally recognized to reduce bias .
Our systematic review and meta-analysis have several weaknesses that must be taken into account. First of all, we included only publications in English and we did not search for grey literature. However, we made the literature search as widespread and inclusive as possible; primarily, we used electronic databases, but also screened the bibliographies of the retrieved articles for relevant publications. Second, one may argue that some clinical and physiological characteristics of the patients other than the educational interventions could influence the outcomes. To reduce this possibility to a minimum, we included only RCTs because of their lower risk of bias and we used restrictive inclusion and exclusion criteria to minimize heterogeneity among patient populations in terms of severity of disease, learning abilities and capacity to realize autonomously the activities of daily living. However, future research that includes non-randomised trials and/or observational studies are strongly recommended. Finally, we included different types of intervention. We decided to use this strategy because even though self-management support interventions differ in terms of target population, mode, format and content, it is clear that this variability in approach does not markedly affect outcomes . Moreover, we made stratified analyses to account for some characteristics of the interventions that might affect the results.
In conclusion, self-management is a key focus of health policies for chronic disease control in many countries. Nurse-led self-management support interventions can be included in routine primary care activities, since specially trained nurses appear to be more effective than physicians in educating patients with diabetes and CVD in self-management of blood pressure and Hb1Ac in community settings. Future research should evaluate the efficiency of task shifting from physicians to nurses in community settings. Furthermore, trials with higher methodological quality and larger patient populations are urgently needed to assess the efficacy of self-management programs, since current evidence is based on very few large studies of mixed methodological quality.
S1 File. Research strategy and study eligibility criteria.
S1 Table. Summary characteristics of participants and interventions of included studies.
We are sincerely grateful to Francesca Laurino for her support with search strategy and consensus of data.
- Conceptualization: AM CDV GD WR PV.
- Data curation: CDV IB MLR.
- Formal analysis: AM CDV GM.
- Investigation: AM IB CM GM MLR AC.
- Methodology: AM CDV CM GM GD.
- Project administration: AM CDV GD.
- Supervision: WR PV GD.
- Visualization: AM AC CDV CM MLR.
- Writing – original draft: AM CDV IB PV GD.
- Writing – review & editing: WR PV GD.
- 1. Ward BW, Schiller JS, Goodman RA. Multiple chronic conditions among US adults: a 2012 update. Prev Chronic Dis. 2014;11:E62. pmid:24742395
- 2. World Health Organization. Global status report on noncommunicable diseases 2014. WHO 2014. Available from: http://www.who.int/nmh/publications/ncd-status-report-2014/en/
- 3. Bloom DE, Cafiero ET, Jane-Llopis E, Abrahams-Gessel S, Bloom LR, Fathima S, et al. The global economic burden of non-communicable diseases: a report by the World Economic Forum and the Harvard School of Public Health. World Economic Forum 2011.
- 4. World Health Organization. Declaration of Alma-Ata: International Conference on Primary Health Care, Alma-Ata, USSR, 6–12 September 1978. Retrieved February. 1978;14:2006.
- 5. Laurant M, Reeves D, Hermens R, Braspenning J, Grol R, Sibbald B. Substitution of doctors by nurses in primary care. Cochrane Database Syst Rev. 2005;(2):CD001271. pmid:15846614
- 6. Kilo CM, Wasson JH. Practice redesign and the patient-centered medical home: history, promises, and challenges. Health Aff (Millwood). 2010 May;29(5):773–8.
- 7. Wagner EH, Austin BT, Davis C, Hindmarsh M, Schaefer J, Bonomi A. Improving chronic illness care: translating evidence into action. Health Aff (Millwood). 2001 Dec;20(6):64–78.
- 8. Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness. JAMA. 2002 Oct 9;288(14):1775–9. pmid:12365965
- 9. Buchan J, Calman L. Skill-Mix and policy change in the health workforce. 2005, OECD Health Working Papers, No. 17, OECD Publishing.
- 10. Martínez-González NA, Djalali S, Tandjung R, Huber-Geismann F, Markun S, Wensing M, et al. Substitution of physicians by nurses in primary care: a systematic review and meta-analysis. BMC Health Serv Res. 2014;14:214. pmid:24884763
- 11. Dennis S, May J, Perkins D, Zwar N, Sibbald B, Hasan I. What evidence is there to support skill mix changes between GPs, pharmacists and practice nurses in the care of elderly people living in the community? Aust New Zealand Health Policy. 2009;6:23. pmid:19744350
- 12. Dubois C-A, Singh D. From staff-mix to skill-mix and beyond: towards a systemic approach to health workforce management. Hum Resour Health. 2009;7:87. pmid:20021682
- 13. Martínez-González NA, Rosemann T, Djalali S, Huber-Geismann F, Tandjung R. Task-Shifting From Physicians to Nurses in Primary Care and its Impact on Resource Utilization: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Med Care Res Rev. 2015 Aug;72(4):395–418. pmid:25972383
- 14. Chopra M, Munro S, Lavis JN, Vist G, Bennett S. Effects of policy options for human resources for health: an analysis of systematic reviews. Lancet. 2008 Feb 23; 371 (9613): 668–74. pmid:18295024
- 15. World Health Organization. Task shifting: rational redistribution of tasks among health workforce teams: global recommendations and guidelines. 2007; Available from: http://apps.who.int/iris/handle/10665/43821
- 16. Rich MW, Beckham V, Wittenberg C, Leven CL, Freedland KE, Carney RM. A multidisciplinary intervention to prevent the readmission of elderly patients with congestive heart failure. N Engl J Med. 1995 Nov 2;333(18):1190–5. pmid:7565975
- 17. Keleher H, Parker R, Abdulwadud O, Francis K. Systematic review of the effectiveness of primary care nursing. Int J Nurs Pract. 2009 Feb;15(1):16–24. pmid:19187165
- 18. Zhu Q-M, Liu J, Hu H-Y, Wang S. Effectiveness of nurse-led early discharge planning programmes for hospital inpatients with chronic disease or rehabilitation needs: a systematic review and meta-analysis. J Clin Nurs. 2015 Oct;24(19–20):2993–3005. pmid:26095175
- 19. Tian Y. Data briefing: emergency hospital admissions for ambulatory care-sensitive conditions. Kings fund report. 3 April 2012. Available from: http://www.kingsfund.org.uk/publications/data-briefing-emergency-hospital-admissions-ambulatory-care-sensitive-conditions.
- 20. Huntley A, Lasserson D, Wye L, Morris R, Checkland K, England H, et al. Which features of primary care affect unscheduled secondary care use? A systematic review. BMJ Open. 2014 May 23;4(5):e004746. pmid:24860000
- 21. Franek J. Self-management support interventions for persons with chronic disease: an evidence-based analysis. Ont Health Technol Assess Ser. 2013;13(9):1–60. pmid:24194800
- 22. Galdas P, Fell J, Bower P, Kidd L, Blickem C, McPherson K, et al. The effectiveness of self-management support interventions for men with long-term conditions: a systematic review and meta-analysis. BMJ Open. 2015;5(3):e006620. pmid:25795688
- 23. Institute of Medicine (US). Committee on the Robert Wood Johnson Foundation Initiative on the Future of Nursing. The future of nursing: Leading change, advancing health. 2011, Washington, DC: National Academies Press.
- 24. 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 Aug;26(8):2256–60. pmid:12882845
- 25. Taylor CB, Miller NH, Reilly KR, Greenwald G, Cunning D, Deeter A, et al. Evaluation of a nurse-care management system to improve outcomes in patients with complicated diabetes. Diabetes Care. 2003 Apr;26(4):1058–63. pmid:12663573
- 26. Boyd CM, Reider L, Frey K, Scharfstein D, Leff B, Wolff J, et al. The effects of guided care on the perceived quality of health care for multi-morbid older persons: 18-month outcomes from a cluster-randomized controlled trial. J Gen Intern Med. 2010 Mar;25(3):235–42. pmid:20033622
- 27. Egger M, Smith GD, Altman DG. Principles of and procedures for systematic reviews. In: Systematic reviews in health care. Hoboken: BMJ Publishing Group; 2008;23–42.
- 28. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009 Jul 21;6(7):e1000100. pmid:19621070
- 29. Chin R, Lee BY. Economics and patient reported outcomes, Principles and practice of clinical trial medicine. Elsevier Inc; 2008;145–66.
- 30. Deshpande PR, Rajan S, Sudeepthi BL, Abdul Nazir CP. Patient-reported outcomes: A new era in clinical research. Perspect Clin Res. 2011 Oct;2(4):137–44. pmid:22145124
- 31. U.S. Department of Health and Human Services FDA Center for Drug Evaluation and Research, U.S. Department of Health and Human Services FDA Center for Biologics Evaluation and Research, U.S. Department of Health and Human Services FDA Center for Devices and Radiological Health. Guidance for industry: patient-reported outcome measures: use in medical product development to support labeling claims: draft guidance. Health Qual Life Outcomes. 2006;4:79. pmid:17034633
- 32. Higgins JP, Altman DG. Chapter 8: Assessing risk of bias in included studies. In: Higgins JP, Green S. (editors), 2008. Cochrane handbook for systematic reviews of interventions. Version 5.0.1 [updated September 2008]. Wiley Online Library. Available from www.cochrane-handbook.org.
- 33. Hoogendoorn WE, van Poppel MN, Bongers PM, Koes BW, Bouter LM. Systematic review of psychosocial factors at work and private life as risk factors for back pain. Spine. 2000 Aug 15;25(16):2114–25. pmid:10954644
- 34. Damiani G, Silvestrini G, Federico B, Cosentino M, Marvulli M, Tirabassi F, et al. A systematic review on the effectiveness of group versus single-handed practice. Health Policy. 2013 Nov;113(1–2):180–7. pmid:23910731
- 35. Deeks JJ, Higgins J, Altman DG. Chapter 9: Analysing data and undertaking meta-analyses. In: Higgins JP, Green S. (editors), 2008. Cochrane handbook for systematic reviews of interventions Version 5.1.0 (updated March 2011). Wiley Online Library. Available from www.cochrane-handbook.org.
- 36. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986 Sep;7(3):177–88. pmid:3802833
- 37. Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst. 1959 Apr;22(4):719–48. pmid:13655060
- 38. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003 Sep 6;327(7414):557–60. pmid:12958120
- 39. Woollard J, Burke V, Beilin LJ. Effects of general practice-based nurse-counselling on ambulatory blood pressure and antihypertensive drug prescription in patients at increased risk of cardiovascular disease. J Hum Hypertens. 2003 Oct;17(10):689–95. pmid:14504627
- 40. Murchie P, Campbell NC, Ritchie LD, Deans HG, Thain J. Effects of secondary prevention clinics on health status in patients with coronary heart disease: 4 year follow-up of a randomized trial in primary care. Fam Pract. 2004 Oct;21(5):567–74. pmid:15367480
- 41. Delaney EK, Murchie P, Lee AJ, Ritchie LD, Campbell NC. Secondary prevention clinics for coronary heart disease: a 10-year follow-up of a randomised controlled trial in primary care. Heart. 2008 Nov;94(11):1419–23. pmid:18198203
- 42. Bosworth HB, Olsen MK, Grubber JM, Neary AM, Orr MM, Powers BJ, et al. Two self-management interventions to improve hypertension control: a randomized trial. Ann Intern Med. 2009 Nov 17;151(10):687–95. pmid:19920269
- 43. Shea S, Weinstock RS, Teresi JA, Palmas W, Starren J, Cimino JJ, et al. A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus: 5 year results of the IDEATel study. J Am Med Inform Assoc. 2009 Aug;16(4):446–56. pmid:19390093
- 44. ter Bogt NCW, Bemelmans WJE, Beltman FW, Broer J, Smit AJ, van der Meer K. Preventing weight gain by lifestyle intervention in a general practice setting: three-year results of a randomized controlled trial. Arch Intern Med. 2011 Feb 28;171(4):306–13. pmid:21357805
- 45. Murchie P, Campbell NC, Ritchie LD, Simpson JA, Thain J. Secondary prevention clinics for coronary heart disease: four year follow up of a randomised controlled trial in primary care. BMJ. 2003 Jan 11;326(7380):84. pmid:12521974
- 46. Woollard J, Burke V, Beilin LJ, Verheijden M, Bulsara MK. Effects of a general practice-based intervention on diet, body mass index and blood lipids in patients at cardiovascular risk. J Cardiovasc Risk. 2003 Feb;10(1):31–40. pmid:12569235
- 47. Bosworth HB, Olsen MK, Gentry P, Orr M, Dudley T, McCant F, et al. Nurse administered telephone intervention for blood pressure control: a patient-tailored multifactorial intervention. Patient Educ Couns. 2005 Apr;57(1):5–14. pmid:15797147
- 48. Shea S, Weinstock RS, Starren J, Teresi J, Palmas W, Field L, et al. A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus. J Am Med Inform Assoc. 2006 Feb;13(1):40–51. pmid:16221935
- 49. ter Bogt NCW, Bemelmans WJE, Beltman FW, Broer J, Smit AJ, van der Meer K. Preventing weight gain: one-year results of a randomized lifestyle intervention. Am J Prev Med. 2009 Oct;37(4):270–7. pmid:19765497
- 50. Garcia-Peña C, Thorogood M, Armstrong B, Reyes-Frausto S, Muñoz O. Pragmatic randomized trial of home visits by a nurse to elderly people with hypertension in Mexico. Int J Epidemiol. 2001 Dec;30(6):1485–91. pmid:11821367
- 51. Krein SL, Klamerus ML, Vijan S, Lee JL, Fitzgerald JT, Pawlow A, et al. Case management for patients with poorly controlled diabetes: a randomized trial. Am J Med. 2004 Jun 1;116(11):732–9. pmid:15144909
- 52. Rudd P, Miller NH, Kaufman J, Kraemer HC, Bandura A, Greenwald G, et al. Nurse management for hypertension. A systems approach. Am J Hypertens. 2004 Oct;17(10):921–7. pmid:15485755
- 53. Lee L-L, Arthur A, Avis M. Evaluating a community-based walking intervention for hypertensive older people in Taiwan: a randomized controlled trial. Prev Med. 2007 Feb;44(2):160–6. pmid:17055561
- 54. Tonstad S, Alm CS, Sandvik E. Effect of nurse counselling on metabolic risk factors in patients with mild hypertension: a randomised controlled trial. Eur J Cardiovasc Nurs. 2007 Jun;6(2):160–4. pmid:16914379
- 55. Gabbay RA, Añel-Tiangco RM, Dellasega C, Mauger DT, Adelman A, Van Horn DHA. Diabetes nurse case management and motivational interviewing for change (DYNAMIC): results of a 2-year randomized controlled pragmatic trial. J Diabetes. 2013 Sep;5(3):349–57. pmid:23368423
- 56. Piette JD, Weinberger M, McPhee SJ, Mah CA, Kraemer FB, Crapo LM. Do automated calls with nurse follow-up improve self-care and glycemic control among vulnerable patients with diabetes? Am J Med. 2000 Jan;108(1):20–7. pmid:11059437
- 57. Gary TL, Bone LR, Hill MN, Levine DM, McGuire M, Saudek C, et al. Randomized controlled trial of the effects of nurse case manager and community health worker interventions on risk factors for diabetes-related complications in urban African Americans. Prev Med. 2003 Jul;37(1):23–32. pmid:12799126
- 58. Goudswaard AN, Stolk RP, Zuithoff NPA, de Valk HW, Rutten GEHM. Long-term effects of self-management education for patients with Type 2 diabetes taking maximal oral hypoglycaemic therapy: a randomized trial in primary care. Diabet Med. 2004 May;21(5):491–6. pmid:15089797
- 59. Cooper H, Booth K, Gill G. A trial of empowerment-based education in type 2 diabetes—global rather than glycaemic benefits. Diabetes Res Clin Pract. 2008 Nov;82(2):165–71. pmid:18804887
- 60. Galbreath AD, Krasuski RA, Smith B, Stajduhar KC, Kwan MD, Ellis R, et al. Long-term healthcare and cost outcomes of disease management in a large, randomized, community-based population with heart failure. Circulation. 2004 Dec 7;110(23):3518–26. pmid:15531765
- 61. Sisk JE, Hebert PL, Horowitz CR, McLaughlin MA, Wang JJ, Chassin MR. Effects of nurse management on the quality of heart failure care in minority communities: a randomized trial. Ann Intern Med. 2006 Aug 15;145(4):273–83. pmid:16908918
- 62. Ishani A, Greer N, Taylor BC, Kubes L, Cole P, Atwood M, et al. Effect of nurse case management compared with usual care on controlling cardiovascular risk factors in patients with diabetes: a randomized controlled trial. Diabetes Care. 2011 Aug;34(8):1689–94. pmid:21636796
- 63. Bischoff EWMA, Akkermans R, Bourbeau J, van Weel C, Vercoulen JH, Schermer TRJ. Comprehensive self management and routine monitoring in chronic obstructive pulmonary disease patients in general practice: randomised controlled trial. BMJ. 2012;345:e7642. pmid:23190905
- 64. Walters J, Cameron-Tucker H, Wills K, Schüz N, Scott J, Robinson A, et al. Effects of telephone health mentoring in community-recruited chronic obstructive pulmonary disease on self-management capacity, quality of life and psychological morbidity: a randomised controlled trial. BMJ Open. 2013;3(9):e003097. pmid:24014482
- 65. Hofer AN, Abraham JM, Moscovice I. Expansion of coverage under the Patient Protection and Affordable Care Act and primary care utilization. Milbank Q. 2011 Mar;89(1):69–89. pmid:21418313
- 66. Petterson SM, Liaw WR, Phillips RL, Rabin DL, Meyers DS, Bazemore AW. Projecting US primary care physician workforce needs: 2010–2025. Ann Fam Med. 2012 Dec;10(6):503–9. pmid:23149526
- 67. Tinetti ME, Fried TR, Boyd CM. Designing health care for the most common chronic condition—multimorbidity. JAMA. 2012 Jun 20;307(23):2493–4. pmid:22797447
- 68. Coleman MT, Newton KS. Supporting self-management in patients with chronic illness. Am Fam Physician. 2005 Oct 15;72(8):1503–10. pmid:16273817
- 69. Norris SL, Engelgau MM, Narayan KM. Effectiveness of self-management training in type 2 diabetes: a systematic review of randomized controlled trials. Diabetes Care. 2001 Mar;24(3):561–87. pmid:11289485
- 70. Norris SL, Lau J, Smith SJ, Schmid CH, Engelgau MM. Self-management education for adults with type 2 diabetes: a meta-analysis of the effect on glycemic control. Diabetes Care. 2002 Jul;25(7):1159–71. pmid:12087014
- 71. Glasgow RE, Anderson RM. In diabetes care, moving from compliance to adherence is not enough. Something entirely different is needed. Diabetes Care. 1999 Dec;22(12):2090–2. pmid:10587854
- 72. Oldenburg B, Taylor CB, O’Neil A, Cocker F, Cameron LD. Using new technologies to improve the prevention and management of chronic conditions in populations. Annu Rev Public Health. 2015 Mar 18;36:483–505. pmid:25581147
- 73. Oranje WA, Rondas-Colbers GJ, Swennen GN, Jansen H, Wolffenbuttel BH. Lack of effect on LDL oxidation and antioxidant status after improvement of metabolic control in type 2 diabetes. Diabetes Care. 1999 Dec;22(12):2083–4. pmid:10587847
- 74. Subramanian S, Chait A. Hypertriglyceridemia secondary to obesity and diabetes. Biochim Biophys Acta. 2012 May;1821(5):819–25. pmid:22005032
- 75. Piette JD, Glasgow RE. Education and home glucose monitoring. Evidence based diabetes care Hamilton, Ontario: BC Decker. 2001;207–51.
- 76. Lansbury G. Chronic pain management: a qualitative study of elderly people’s preferred coping strategies and barriers to management. Disabil Rehabil. 2000 Jan 10;22(1–2):2–14. pmid:10661753
- 77. Riegel B, Carlson B. Facilitators and barriers to heart failure self-care. Patient Educ Couns. 2002 Apr;46(4):287–95. pmid:11932128
- 78. Bayliss EA, Steiner JF, Fernald DH, Crane LA, Main DS. Descriptions of barriers to self-care by persons with comorbid chronic diseases. Ann Fam Med. 2003 Jun;1(1):15–21. pmid:15043175
- 79. Jerant AF, von Friederichs-Fitzwater MM, Moore M. Patients’ perceived barriers to active self-management of chronic conditions. Patient Educ Couns. 2005 Jun;57(3):300–7. pmid:15893212
- 80. Smith SM, Soubhi H, Fortin M, Hudon C, O’Dowd T. Managing patients with multimorbidity: systematic review of interventions in primary care and community settings. BMJ. 2012;345:e5205. pmid:22945950
- 81. MacGregor K, Handley M, Wong S, Sharifi C, Gjeltema K, Schillinger D, et al. Behavior-change action plans in primary care: a feasibility study of clinicians. J Am Board Fam Med. 2006 Jun;19(3):215–23. pmid:16672674
- 82. Johnson JK, Woods DM, Stevens DP, Bowen JL, Provost LP, Sixta CS, et al. Joy and challenges in improving chronic illness care: capturing daily experiences of academic primary care teams. J Gen Intern Med. 2010 Sep;25 Suppl 4:S581–585.
- 83. Newton JM, Falkingham L, Clearihan L. Better knowledge, better health: piloting an education intervention in chronic condition self-management support. Aust J Prim Health. 2011;17(1):4–9. pmid:21616017
- 84. Yank V, Laurent D, Plant K, Lorig K. Web-based self-management support training for health professionals: a pilot study. Patient Educ Couns. 2013 Jan;90(1):29–37. pmid:23031610
- 85. Kemppainen V, Tossavainen K, Turunen H. Nurses’ roles in health promotion practice: an integrative review. Health Promot Int. 2013 Dec;28(4):490–501. pmid:22888155
- 86. Maijala V, Tossavainen K, Turunen H. Health promotion practices delivered by primary health care nurses: Elements for success in Finland. Appl Nurs Res. 2016 May;30:45–51. pmid:27091252
- 87. Schulz KF, Grimes DA. Blinding in randomised trials: hiding who got what. Lancet. 2002 Feb 23;359(9307):696–700. pmid:11879884
- 88. Barlow J, Wright C, Sheasby J, Turner A, Hainsworth J. Self-management approaches for people with chronic conditions: a review. Patient Educ Couns. 2002 Nov;48(2):177–87. pmid:12401421