Background: Information and communications technologies (ICTs) are recognized as critical enablers of integrated primary care to support patients with multiple chronic conditions. Although ICT-enabled integrated primary care holds promise in supporting patients with complex care needs through team-based and continued care, critical implementation factors regarding what ICTs are available and how they enable this model are yet to be mapped in the literature.
Objective: This scoping review addressed the current knowledge gap by answering the following research question: What ICTs are used in delivering integrated primary care to patients with complex care needs?
Methods: The Arksey and O’Malley method enhanced by the work by Levac et al was used to guide this scoping review. In total, 4 electronic medical databases were accessed—MEDLINE, Embase, CINAHL, and PsycINFO—collecting studies published between January 2000 and December 2021. Identified peer-reviewed articles were screened. Relevant studies were charted, collated, and analyzed using the Rainbow Model of Integrated Care and the eHealth Enhanced Chronic Care Model.
Results: A total of 52,216 articles were identified, of which 31 (0.06%) met the review’s eligibility criteria. In the current literature, ICTs are used to serve the following functions in the integrated primary care setting: information sharing, self-management support, clinical decision-making, and remote service delivery. Integration efforts are supported by ICTs by promoting teamwork and coordinating clinical services across teams and organizations. Patient, provider, organizational, and technological implementation factors are considered important for ICT-based interventions in the integrated primary care setting.
Conclusions: ICTs play a critical role in enabling clinical and professional integration in the primary care setting to meet the health system–related needs of patients with complex care needs. Future research is needed to explore how to integrate technologies at an organizational and system level to create a health system that is well prepared to optimize technologies to support patients with complex care needs.
There is a growing number of patients living with 2 or more chronic conditions in Canada and worldwide [, ]. These individuals not only manage multiple chronic conditions [ ] but also experience additional biopsychosocial challenges [ , ]. Living with multiple chronic conditions can introduce additional complexity into this patient population’s care management experience, such as high symptom and treatment burden [ , ]. In addition, this patient population can have complicated and contradictory treatments or medication regimens [ ] that require care from multiple health professionals and services spanning various health and social care settings [ ]. Owing to the multitude of challenges this patient population faces in the current disease-specific care model [ ], this patient population is often referred to as patients with complex care needs or complex patients. Navigating a fragmented care system can leave patients with complex care needs feeling overwhelmed and dissatisfied with their care [ , ]. An agile and coordinated care system can better address this population’s challenges.
Integrated care models that involve primary care are well positioned to support people living with chronic conditions as most chronic disease–related care is delivered in this setting . The definition of integrated care is a coordinated, collaborative, multidisciplinary, and person-centered care delivery system [ ]. In recent years, integrated care approaches have been shown to support improved care coordination within primary care [ , ]. However, implementing integrated primary care models is an ongoing challenge within health systems.
The Rainbow Model of Integrated Care (RMIC) offers a conceptual way of understanding integrated care, suggesting that integration can occur at different levels (clinical, professional, organizational, and system) and is enabled through functional and normative mechanisms . This validated model is helpful in understanding the different types and degrees of integration that a care model or intervention aims to achieve [ , ]. Each level of integration (clinical, professional, organizational, and system) may require different strategies, tools, and mechanisms to support integration efforts, such as care coordination across health professionals for effective care continuity and coordination of services [ ]. Information and communications technologies (ICTs) can enable these types of integration efforts regarding care continuity or shared decision-making by offering their functionalities, such as sharing patient data across professionals and organizations [ , ]. In the health care setting, ICT is used as an umbrella term that includes different types of health technologies [ ]. Therefore, to operationalize this term for this study, we have used the World Health Organization ICT definition in the context of health systems, which is as follows: health services and information delivered through the combined use of the internet and other electronic communication technologies [ , ]. ICT-enabled integrated care can be helpful for patients with complex care needs in terms of care coordination and as a decision support tool as this patient population may require multiple support services from multiple health professionals and organizations [ ].
shows the RMIC levels and how ICTs can support each component.
The Rainbow Model of Integrated Care levels and examples of information and communications technologies (ICTs) that can support integration activities in the primary care model.
- Refers to the coordination of person-centered patient care across multiple conditions, care teams, settings, and time to provide efficient care
- Example of ICTs: patient portal to access information across services [ ] and telehealth to deliver coordinated services remotely [ ]
- A means to promote teamwork and collaboration among multidisciplinary teams
- Example of ICTs: videoconferencing among providers [ ] and access to patient data across providers [ ]
- Interorganizational care coordination, including common administrative mechanisms to deliver comprehensive services to a defined population
- Example of ICTs: shared patient electronic medical records among primary care and community services [ ]
- An alignment of rules, regulations, and policies within a system
- Example of ICTs: telehealth reimbursement policies for primary care providers [ ]
- Key functions to support care integration
- Example of ICTs: the care model being situated in an integrated network where financial, information, and management systems are coordinated [ ]
- Having a common frame of reference, shared values, and goals for service delivery between organizations, stakeholders, and providers
- Example of ICTs: a shared goal of accelerating internet-based care adoption during COVID-19 [ ]
Another way to conceptualize how technology can support patients with chronic conditions is the eHealth Enhanced Chronic Care Model (eCCM). This model builds on the foundational Chronic Care Model introduced by Wagner  that has been used to guide chronic disease management for patients with complex care needs in primary care and other settings [ ]. The eCCM version offers a salient way to identify how ICTs and ICT-generated information can aid in improving patients’ health outcomes by increasing patients’ and providers’ knowledge of chronic disease management [ ]. shows the key components of the eCCM.
Key elements of the eHealth Enhanced Chronic Care Model.
- Refers to developing strategies that link with community organizations and virtual health-related communities
- Example of information and communications technologies (ICTs): health-related social networks and web-based communities that facilitate care connections
Health system enhancements
- Refers to the strategies in place to support patient engagement and self-management support
- Example of ICTs: web-based health platforms and mobile health that support quality improvement
Delivery system design enhancements
- Refers to technologies that facilitate teamwork practice to deliver care efficiently
- Example of ICTs: electronic health records (EHRs) and web-based health platforms that facilitate information sharing
Self-management support enhancements
- Refers to the patient’s active role in managing their care through using technology
- Example of ICTs: health apps and web-based resources that support patients’ self-management skills
Clinical decision support enhancements
- A means for providers and patients to have access to evidence-based clinical guidelines, protocols, care standards, and self-management resources to make an informed decision
- Example of ICTs: web-based platforms and EHRs to access protocols and guidelines on the internet
Clinical information system enhancements
- Management of information systems (ie, patient databases and patient portals or personal health records) to facilitate efficient care
- Example of ICTs: mobile health apps and web-based platforms to coordinate care and monitor patients’ health status
Taken together, the RMIC and eCCM offer useful suggestions on how ICT may be of use to enable integrated primary care delivery for patients with complex care needs. Although these frameworks and emerging literature in the field of digital health and care integration provide some evidence of how technology may be of service to patients with complex care needs, there has not been a comprehensive systematic review of the literature focused on how ICT supports integrated primary care models to identify current trends or gaps in research. Therefore, the purpose of this knowledge synthesis was to scope the current literature on the types of ICTs that are being used to support patients with complex conditions in integrated primary care settings while also identifying potential areas for continued research.
A scoping review approach was used to systematically map and identify relevant literature at the crossroads of integrated primary care models, ICTs, and patients with complex conditions. Scoping reviews capture a breadth of literature, which can effectively identify emerging literature as well as evidence gaps on a topic of interest . Given that ICT-based integrated primary care is comparatively a newer model of care, a scoping review is an ideal approach for this study. To conduct a rigorous review, we followed the six stages of the scoping review framework by Arksey and O’Malley [ ] enhanced by the work by Levac et al [ ]: (1) identifying the research question; (2) identifying relevant literature; (3) selecting the studies; (4) charting the data; (5) collating, summarizing, and reporting the articles; and (6) disseminating knowledge. Each of these 6 stages is described in detail in the following sections. For further details, the study protocol has been published elsewhere [ ].
Stage 1: Identifying the Research Question
The guiding research question for this scoping review was as follows: What ICTs are used in the delivery of integrated primary care to patients with complex care needs? The subquestions were as follows: (1) Which technologies are being used for this patient population? What are the functionalities and characteristics of these technologies? (2) How are these technologies being used in the integrated primary care model in terms of care integration? (3) What implementation factors are being reported in the selected studies that describe ICT-enabled integrated primary care models?
These questions were selected as there has been no systematic documentation in the current literature of what sort of ICTs are available to support an integrated primary care model or how ICTs are enabling the process of care integration in primary care settings. In addition, the third subquestion was posed given the importance of implementation strategies in the successful use of ICT-based interventions in the integrated primary care model . Given the interconnectedness of the primary research questions and the 3 subquestions, a single search strategy and review were determined to be sufficient, and addressing all 3 questions in a single study was expected to lead to a richer and more meaningful analysis and findings.
Stage 2: Identifying Relevant Literature
To operationalize the research questions, we identified and defined 4 major concepts to inform our search strategy. The 4 concepts and their key definitions are outlined in. shows the keywords associated with each concept for each category.
Relevant studies were identified by searching the following electronic databases of published literature: Ovid MEDLINE, Ovid Embase, EBSCO CINAHL, and Ovid PsycINFO. The MEDLINE search strategy was developed first and peer reviewed using the Peer Review of Electronic Search Strategies tool. This search strategy was then translated to the remaining 3 databases. The searches were limited to articles published between January 2000 and December 2021. Articles published before 2000 were excluded as a preliminary search showed that there were very few articles published on ICTs during this time. The MEDLINE search strategy was included in the published protocol . In addition, the search strategy for PsycINFO can be found in . The initial search of all databases was completed in the summer of 2019 and then updated in December 2020 and again in December 2021.
Information and communications technologies (ICTs) [, ]
- Health care–related services and information are delivered through the combined use of the internet and other electronic ICTs. In this study, the eHealth Enhanced Chronic Care Model is used to categorize ICTs based on the primary functions of a technology (ie, decision support).
Integrated care model 
- This refers to a coordinated collaborative, multidisciplinary, and person-centered care delivery system.
Patients with complex care needs 
- Individuals with multiple chronic conditions often encounter additional psychosocial challenges. The complexity of their conditions affects treatment, health outcomes, and quality of life.
Primary health care 
- This refers to the first point of contact to health care that provides comprehensive community-based service. Primary health care is most often delivered by general practitioners or family physicians.
Stage 3: Study Selection
The search results were imported into the knowledge synthesis software Covidence. The inclusion and exclusion criteria were imported into the software as well. The inclusion and exclusion criteria were decided a priori and were used for screening citations first, for the title and abstract review, and then again for the full-text review. Both levels of review were conducted in duplicate by 2 reviewers.
To be included in the review, articles were required to report on an intervention that (1) had an ICT-enabled health care model, (2) was based on an integrated health care model or team-based care, (3) included adult patients with complex care needs, and (4) took place in a model that included primary care. If the intervention had a target population of (1) individuals aged <18 years (given the focus of this review on adults with complex care needs) or individuals with (2) cancer or (3) mental disorders, it was excluded as cancer care and mental health provision have unique care pathways that may not be translatable into integrated primary care settings [, ]. Any published article, including quantitative studies, qualitative studies, mixed or multimethods research, both comparative (eg, randomized, controlled, cohort, or quasi-experimental) and noncomparative (eg, survey and narrative audit) methods, educational materials, and reports, could be included in the review if it met the aforementioned inclusion criteria. These inclusion and exclusion criteria were published in the study protocol [ ].
To ensure consistency between reviewers, a series of training exercises and discussions were held before commencing title and abstract screening. At first, all 6 members of the research team screened a random sample of 30 articles to assess interrater agreement. Interrater agreement for study inclusion was calculated using percentage of agreement; when it reached >70% across the team, we proceeded to the next stage. If a lower agreement was observed, the team had a discussion about eligibility criteria, and another pilot test was conducted. In total, 6 rounds of pilot tests were required for the title and abstract screening of a random sample of a total of 110 citations. After the initial agreement between the 6 screeners was established, they were divided into groups of 2 for an efficient screening process. The pairs worked together to screen titles and abstracts for inclusion. Any disagreements within pairs were resolved through weekly group discussions.
For the full-text screening stage, 3 rounds of pilot tests were conducted on a random sample of 30 articles. All 6 team members participated in the pilot-testing round. In each round, interrater agreement was calculated using percentage of agreement. In the third round, we reached >70% consensus across the team. Subsequently, the 6 team members were divided into 3 groups consisting of 2 group members each. All 3 pairs screened the full texts of potentially relevant articles to determine inclusion using the inclusion and exclusion criteria. All discrepancies were resolved through weekly group discussions.
Stage 4: Data Extraction
All the included studies were reviewed and charted independently by 6 team members. To ensure consistency between team members regarding data extraction, the entire team pilot-tested the data abstraction form on 3 articles that were randomly selected. Full data abstraction began only after full agreement was reached. The full agreement was decided based on percentage of agreement, and it reached >90% agreement in the first round of pilot-testing. After reaching a full team agreement, each team member extracted the study data independently. The data extraction form can be found in the published protocol paper . Subsequently, the studies were divided among the team to be abstracted by a single team member and verified by a second reviewer (FT and AA) to ensure data accuracy. Consistent with a scoping review approach, the methodological quality of the included articles was not appraised [ ].
Stage 5: Data Summary and Synthesis of Findings
The charted data were summarized to gain a descriptive understanding of the data collected. In addition, to answer the 3 subquestions, we used the qualitative content analysis method ().
Qualitative content analysis method.
- The technologies described in the identified studies were categorized using the eHealth Enhanced Chronic Care Model (eCCM) [ ] to assess the types of functions and technological components supporting chronic disease management for patients with complex care needs in integrated primary care settings. We used a deductive content analysis method [ ] to categorize the identified information and communications technologies according to the eCCM domains. The key definitions of the eCCM that we used in the analysis are described in .
- To understand how technologies supported integrated care-related activities, the included studies were thematically mapped onto the Rainbow Model of Integrated Care (RMIC) [ ]. A deductive content analysis [ ] was conducted to analyze the study data and was linked to the 6 dimensions of integrated care included in . In addition, we extracted the measured outcomes of each study as the RMIC suggested that integrated care should lead to outcomes aligned with the triple aim, which are lower cost, improved health, and improved care [ ].
- To explore the implementation factors reported in the identified studies, we used an inductive content analysis method [ ].
Stage 6: Knowledge Dissemination
The study findings have been disseminated in academic conferences  and a webinar [ ]. A wide variety of stakeholders, such as clinicians, researchers, policy makers, and patients, some of whom provided feedback and reflections on the findings, participated in both academic conferences and the webinar. This manuscript marks another key knowledge dissemination tool for this study.
A total of 52,286 articles were identified. After removing duplicates, 69.76% (36,474/52,286) of the articles underwent title and abstract screening. A total of 293 articles underwent a full-text review, resulting in 31 (10.6%) that met the eligibility criteria and were included in the final analysis.shows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram for this review.
shows the full description of each study. The included articles spanned nearly 16 years (2003-2020), with 68% (21/31) published after 2014 ( ). Of the 31 included studies, 15 (48%) were from the United States, with the remaining 52% (16/31) being from Canada, the United Kingdom, Spain, Israel, Taiwan, and India. Of the 31 selected studies, 15 (48%) were quantitative, whereas 5 (16%) used qualitative methods, and 3 (10%) used mixed methods research designs.
|Study, year||Method||Country||Targeted chronic condition||ICTa component of the intervention||Type of provider involved||Nature of technologyb||Type of primary care||Type of patient||Outcomes|
|Alkema et al , 2003||Case study||United States||N/Ac||Telephone||SWd and medical case management staff||2-way||Acute care; long-term; community-based; social services; PCPe||Frail older adults enrolled in the Medicare program||N/A|
|Alkema et al , 2007||Quantitative; RCTf||United States||Cancer, COPDg and pneumonia, diabetes, fractures, heart disease, hypertension, kidney disease, osteoarthritis, prostate cancer, and stroke||Telephone||Care advocates, PCPs, specialists, and home and community care service providers||2-way||Acute care; long-term; community-based; social services; PCP||Frail older adults enrolled in the Medicare program||Quality of life, mortality, and fewer hospitalizations|
|Allen et al , 2011||Quantitative; RCT||United States||COPD, diabetes, hypertension, chronic HFh, osteoporosis, and osteoarthritis||Telephone||Geriatrician, nurse care manager, advanced practice nurse, SW, and geriatrics-certified pharmacist; extended team experts included a psychologist, cardiologist, pulmonologist, endocrinologist, and occupational therapist||2-way||Hospital; social services; primary care||Older adults who were eligible for Medicare and Medicaid||Quality of life, physical condition, self-efficacy, behavior change, caregiver strain, empowerment, quality effectiveness, fewer hospitalizations, other use, access to care, and satisfaction|
|Allen et al , 2012||Quantitative; pilot RCT study||United States||N/A||Electric protocol template, telephone, and fax||Care managers, a physician (PCP), a palliative care physician and specialist, a geriatrician, a SW, a spiritual advisor, and a pharmacist; extended team included physical and occupational therapists, a dietitian, a geriatric advance practice nurse, and a psychologist||2-way||Acute hospital care with community service; PCP||Older adults who were eligible for Medicaid, had a life-limiting illness and 2 deficits in activities of daily life, and were aged >60 years||Quality of life, symptom management, patient-provider relationships, and anxiety and depression|
|Alyousef et al , 2017||Quantitative survey; cross-sectional study||United States||N/A||Case management software, EHRsi, and HIEj||Care managers and other health care providers||1-way||Outpatient clinics and a transition-of-care center but works with primary care case management software||Patients with chronic conditions||Workload, burnout, and intention to use|
|Bendixen et al , 2007||Case report||United States||Arthritis, diabetes, hypertension, and pulmonary disease||Basic computer and cell phone with internet capability and in-home messaging device||Occupational therapists, an IT specialist, and a program support assistant||2-way||PCP; rehabilitation center||Patients at high risk with complex chronic conditions||Quadruple aim, cost-efficiency, usability, and acceptability|
|Berry et al , 2013||Institutional case study||United States||N/A||EMRk||Care coordinators, nurses, SWs, and specialized nurses||1-way||Primary and specialty care||Older adults with multiple conditions||Quality effectiveness and less hospitalizations|
|Darkins et al , 2008||Case report||United States||Diabetes mellitus, chronic HF, hypertension, PTSDl, COPD, and depression||Telehealth, which included SMS text messages and biometric devices||Nurses or SWs||2-way||Primary ambulatory care||Older adults with chronic disabling conditions||Patient satisfaction and hospital admissions|
|Gagnon et al , 2019||Mixed methods; cluster randomized trial||Canada||At least 2 of the following: diabetes, hypertension, and dyslipidemia||Personalized eHealth platform named CONCERTO+||PCP||Unclear||Primary care||Patients with chronic conditions||Patient activation measure and technology acceptance|
|Gutteridge et al , 2014||Quantitative; descriptive study||United States||N/A||Clinical event notification||Geriatric EDm physicians, transitional care NPsn, PCPs, SWs, geriatric ED pharmacists, physical therapists, and CAREo volunteers||1-way||ED; PCP integration||Older adults who were triaged to a bed in the geriatric ED||Use of the technology|
|Hans et al , 2018||Qualitative; descriptive study||Canada||N/A||Goal management app||PCPs, nurses, and allied health professionals||1-way||Primary care||Individuals living with chronic illness or disability or living with multimorbidity||N/A|
|Hernandez et al , 2015||Comparative case study||Multiple countries: Spain, Norway, and Greece||COPD and respiratory symptoms||Remote diagnosis of spirometry testing (not described fully)||N/A||Unclear||ED||Patients who visited primary care for respiratory symptoms||Accessibility to testing|
|Jindal et al , 2018||Developmental pilot study||India||Cardiovascular disease and diabetes||mHealthp app||Nurse, PCP, and pharmacist||2-way||Primary health care||Patients with cardiovascular disease and diabetes||N/A|
|Marek et al , 2013||RCT||United States||N/A||Medication dispensing system with reminders||Advanced practice nurses, RNsq, multiple physicians, pharmacies, social service agencies, and others||1-way||N/A||Patients with complex medication regimens for chronic illnesses||N/A|
|Martín-Lesende et al , 2013||Quantitative; RCT||Spain||HF or chronic lung disease||Telemonitoring of patients’ clinical parameters and PDA platform||Health professionals, nurses, and GPsr||1-way||Primary care||HF or chronic lung disease||The number and length of hospital admissions|
|Martín-Lesende et al , 2011||Quantitative; RCT||Spain||HF or chronic lung disease||Telemonitoring of self-measured clinical parameters that were measured using Bluetooth wireless sensors||Primary care nurses, GPs, and hospital providers||1-way||Primary care||HF or chronic lung disease||The number and length of hospital admissions|
|Martín-Lesende et al , 2017||Quantitative; uncontrolled before-and-after study||Spain||HF and CLDs (mainly COPD and a few with asthma)||Telecare||GP and nurse||1-way||Primary care||N/A||Rate of hospital use|
|May et al , 2011||Qualitative; comparative study||England||Asthma, coronary heart disease, COPD, and diabetes||Telecare system||PCPs and SWs||N/A||Primary care||Patients with multiple chronic conditions||N/A|
|Metting et al , 2018||Qualitative; exploratory study||The Netherlands||Asthma and COPD||Patient web portal||N/A||1-way||Primary care||Patients with asthma and COPD from low socioeconomic areas||N/A|
|Noel et al , 2018||Quantitative; superior RCT with parallel group||United States||N/A||Smartphone device and Bluetooth-enabled clinical parameter measurement||Senior resident physician (“teledoc”) and family medicine PCPs||1-way||Primary and social care||Multi-comorbid conditions||30-day hospital readmissions|
|Porath et al , 2017||Quasi-experimental; observational study||Israel||Diabetes, hypertension, transient ischemic attack, HF, COPD, and dementia||Web-based clinical protocols||MTCt personal nurse, PCP, other physician consultants (cardiologists, pulmonary specialists, endocrinologists, and psychogeriatricians), clinical pharmacists, SWs, nutritionists, and an administrative team||1-way||Inpatient and ambulatory care||Frail older adults with chronic conditions||Hospital use and hospitalization cost|
|Portz et al , 2018||Qualitative descriptive||United States||Multiple chronic conditions||Patient portal||PCP||1-way||Primary health care||Patients with multiple chronic conditions||N/A|
|Price-Haywood et al , 2017||Quantitative; retrospective observational study||United States||Diabetes and hypertension||Shared web-based portal||PCP||Unclear||Primary care||Older adults with diabetes or hypertension||N/A|
|Ryan et al , 2003||Quantitative; evaluative pilot study||United States||Diabetes, hypertension, schizophrenia, and depression||An in-home messaging device, the Health Buddy; a disease management app; Instamatic cameras for diabetic wound care management; and personal computers with internet connectivity for supervised chat rooms||Care coordinators and other unspecified providers||2-way||Community-based primary care clinics; hospitals; outpatient clinics||Patients with multimorbidity||Patient and provider satisfaction, compliance, and quality of life|
|Sorocco et al , 2013||Quantitative; pilot study||United States||COPD, spinal cord injury, diabetes, hypertension, syncope, depression, dementia, anxiety, and PTSD||Video telehealth (mental health and occupational therapy) and remote monitoring of vitals using a digital scale||Physician assistant, nurse or NP, pharmacist, nutritionist, occupational therapist, SW, and mental health practitioner||2-way||Primary care||Veterans with complex medical conditions||Satisfaction and mental health conditions|
|Steele Gray et al , 2019||Multimethods; exploratory trial||Canada||N/A||ePROu tool, a goal-supporting mHealth app||Physician, NP, nurse, SW, and dietitian||1-way||Primary care||Patients aged ≥60 years living with 2 or more chronic conditions and provider referred||Quality of life, cost-effectiveness, experience of care, and attainment of goals|
|Steele Gray et al , 2016||Qualitative; descriptive interpretive study||Canada||N/A||ePRO tool, a goal-supporting mHealth app||PCPs, NPs, RNs, SWs, and dietitians||1-way||Primary care||Patients aged ≥60 years living with 2 or more chronic conditions and provider referred||N/A|
|Steele Gray et al , 2016||Mixed methods; RCT, cost-effectiveness analysis, and research protocol||Canada||N/A||ePRO tool, a goal-supporting mHealth app||PCPs, NPs, RNs, SWs, and dietitians||1-way||Primary care||Patients aged ≥60 years living with 2 or more chronic conditions and provider referred||Quality of life, cost-effectiveness, experience of care, and attainment of goals|
|Uei et al , 2017||Quantitative; cross-sectional study||Taiwan||Diabetes or hypertension||Telephone and patient health record||N/A||2-way||Primary care||Individuals with multiple chronic conditions||Telecare use intention|
|Valdivieso et al , 2018||Quantitative; RCT||Spain||N/A||Tablet with Bluetooth connection that receives information from digital health scales, EHR, and patient portal||Primary care team and hospital case manager nurses||2-way||Primary care||Older adult patients at high risk||Quality of life, mortality, and health care use|
|Varey et al , 2020||Qualitative||England||General chronic conditions||Tablet||NP, clinical care coordinator, primary care assistant, and nonclinical team leader||1-way||Primary care||Older adults with chronic conditions||N/A|
aICT: information and communications technology.
b1-way versus 2-way: ICTs that support 1-way communication typically transmit biomarkers, vital signs, health information, and educational messages [, ]. In contrast, ICTs that support 2-way communication facilitate conversations between patients and clinicians via telephone and SMS text messaging [ , ].
cN/A: not applicable.
dSW: social worker.
ePCP: primary care physician.
fRCT: randomized controlled trial.
gCOPD: chronic obstructive pulmonary disease.
hHF: heart failure.
iEHR: electronic health record.
jHIE: health information exchange.
kEMR: electronic medical record.
lPTSD: posttraumatic stress disorder.
mED: emergency department.
nNP: nurse practitioner.
oCARE: Care and Respect for Elders.
pmHealth: mobile health.
qRN: registered nurse.
rGP: general practitioner.
sCLD: chronic liver disease.
tMTC: Maccabi Telecare Center.
uePRO: electronic patient-reported outcomes.
|Publication year||Articles, n (%)|
Most of the interventions (15/31, 48%) [, , , , - , , - , , ] only took place in a primary health care setting. However, 39% (12/31) of the studies linked primary care to acute care [ , - , , , , , ], social services [ - , ], or rehabilitation centers [ ].
Health Care Providers
Of the 31 identified studies, 17 (55%) described the involvement of primary care physicians [, , - , - , - , , , , ]. A total of 52% (16/31) of the studies described the involvement of registered and specialized nurses, such as geriatric nurses [ , , , , , , , , , , , , , , , ]. In addition, 23% (7/31) of the studies described the involvement of nonclinical members such as care coordinators and care managers [ , , - , ].
Types of ICTs
The most prominent type of technology discussed across the identified studies (21/31, 68%) were ICTs that support patients’ health status monitoring by providers, which are also known as telemonitoring devices [, - , - , , , ]. Telemonitoring devices include mobile health (mHealth) apps where patients can either actively input their health status or automated biometric (eg, blood pressure) devices connected to a smartphone, tablet, or web-based application can receive that information [ , , , , , , , , ]. This sort of telemonitoring device served dual purposes: (1) enabling physicians to continuously monitor patients and (2) facilitating patient self-management, meaning that patients can track their own symptoms and disease progression. Electronic health records (EHRs) were described in 23% (7/31) of the studies to share patient data across multiple professionals or organizations (eg, acute care hospitals and primary care) [ , , , , , , ]. Telephone-supported interventions were discussed in 16% (5/31) of the studies to facilitate patient follow-up remotely [ - ].
ICTs Aligned With the eCCM
shows the ICTs categorized into the eCCM and RMIC models. Of the 31 studies, 24 (77%) described ICTs that supported the clinical information management aspect of the eCCM to provide relevant patient data to one or more health care providers [ , - , - , - , - , , , - , ]. The types of ICTs for clinical information management were wide-ranging: smartphone apps, telemonitoring devices, patient health records (PHRs), and telephones. To support clinical information management, these ICTs relied on patient self-reporting of symptoms and health status and on providers to monitor patient data remotely. The clinical information management functions of ICTs were important as shared patient information supported other key functions of the Chronic Care Model such as self-management and delivery system design.
Remote patient monitoring data enabled the delivery system design aspect of the eCCM as health professionals followed up with patients to provide additional support or consultation based on patient data [, - , - , , , , - , ]. In total, 65% (20/31) of the studies described ICTs that enhanced delivery system design in the integrated primary care model by sharing data across team members, communicating about patients’ health status, and facilitating regular team meetings [ , - , - , , , , - , ]. Telephones, EHRs, mHealth apps, and case management software were used to enhance the delivery system [ , - , - , , , , - , ].
A total of 61% (19/31) of the studies described ICTs that supported the patient self-management aspect of the eCCM by engaging patients in symptom monitoring and tracking. mHealth apps or web-based platforms, medication reminders through medication adherence devices, and providing patients with their health data and appointments through PHRs were used to support patient self-management [, , , , , , - , , , , , , ]. In all 61% (19/31) of the studies, the primary care team had access to patients’ self-management–related data.
A total of 16% (5/31) of the studies described ICTs such as case management software, EHRs, and mHealth that facilitate evidence-based and data-driven clinical decision-making aspects of the eCCM [, , , , ]. The ICTs enabled the clinical decision-making aspect of the eCCM by being a platform for clinical algorithms that alert or remind health professionals to follow up with patients [ , , , ]. The clinical algorithms were developed based on evidence-based clinical guidelines for providers to make decisions about how to support patients with chronic conditions remotely [ , , , ]. None of the studies explicitly described ICTs that support the eCommunity resource aspect of the eCCM.
The eCCM emphasizes the importance of productive interactions between patients and providers to ensure mutual partnership and communication. According to Pols , health-related ICTs can be divided into 2 broad categories: ICTs supporting 1-way versus 2-way communication [ ]. ICTs that support 1-way communication typically transmit biomarkers, vital signs, health information, and educational messages [ , ]. In contrast, ICTs that support 2-way communication facilitate conventional conversations between patients and clinicians via telephone and SMS text messaging [ , ]. In this review, 35% (11/31) of the studies described an ICT that enabled 2-way communication between patients and providers [ - , , , , , , , ]. This 2-way communication was supported by ICTs such as telephones, internet-enabled computers, smartphones, and fax. In contrast, ICTs such as telemonitoring devices, electronic medical records (EMRs), patient portals, and mHealth apps supported 1-way communication features in 48% (15/31) of the studies, allowing providers to receive patient information remotely through ICTs [ , , , , - , , , , ] and patients to receive automated algorithm-generated reminders about medications or lifestyle advice related to chronic conditions [ , , , ].
|Study, year||Type of technology||Delivery system design||Self-management support enhancements||Clinical decision support enhancements||Clinical information system enhancements||eHealth education||Clinical||Professional||Organizational|
|Alkema et al , 2003||Telephone||✓||✓||✓|
|Alkema et al , 2007||Telephone||✓||✓||✓|
|Allen et al , 2011||Telephone||✓||✓||✓||✓||✓||✓||✓|
|Allen et al , 2012||Electric protocol template, telephone, and fax||✓||✓||✓||✓||✓||✓||✓|
|Alyousef et al , 2017||Case management software, EHRa, and HIEb||✓||✓||✓||✓|
|Bendixen et al , 2007||Basic computer and cell phone with internet capability and in-home messaging device||✓||✓||✓||✓|
|Berry , 2003||EMRc||✓||✓||✓||✓|
|Darkins et al , 2008||Telehealth, including SMS text messages and biometric devices||✓||✓||✓||✓||✓||✓|
|Gagnon et al , 2019||Personalized eHealth named CONCERTO+||✓||✓||✓|
|Gutteridge et al , 2014||Clinical event notification||✓||✓||✓||✓|
|Hans et al , 2018||Goal management app||✓||✓||✓||✓||✓|
|Hernandez et al , 2015||Remote diagnosis of spirometry testing (not described fully)||✓||✓|
|Jindal et al , 2018||mHealthd app||✓||✓||✓||✓||✓||✓|
|Marek et al , 2013||Medication dispensing system with reminders||✓||✓||✓||✓|
|Martín-Lesende et al , 2013||Telemonitoring of patients’ clinical parameters and PDA platform||✓||✓||✓||✓|
|Martín-Lesende et al , 2011||Telemonitoring of self-measured clinical parameters||✓||✓||✓||✓|
|Martín-Lesende et al , 2017||Telecare||✓||✓||✓||✓|
|May et al , 2011||Telecare system||✓||✓||✓|
|Metting et al , 2018||Patient web portal||✓||✓|
|Noel et al , 2018||Smartphone device and Bluetooth-enabled clinical parameter measurement||✓||✓||✓|
|Porath et al , 2017||Remote consultation using telecare||✓||✓||✓||✓||✓|
|Portz et al , 2020||Patient portal||✓||✓||✓|
|Price-Haywood et al , 2017||Shared web-based portal||✓||✓|
|Ryan et al , 2003||An in-home messaging device, the Health Buddy; a disease management app; Instamatic cameras for diabetic wound care management; and personal computers with internet connectivity for supervised chat rooms||✓||✓||✓||✓|
|Sorocco et al , 2013||Video telehealth and remote monitoring of vitals using a digital scale||✓||✓||✓||✓|
|Steele Gray et al , 2019||ePROe tool, a goal-supporting mHealth app||✓||✓||✓||✓||✓|
|Steele Gray et al , 2016||ePRO tool, a goal-supporting mHealth app||✓||✓||✓||✓||✓|
|Steele Gray et al , 2016||ePRO tool, a goal-supporting mHealth app||✓||✓||✓||✓|
|Uei et al , 2017||Telephone and patient health record||✓||✓||✓||✓|
|Valdivieso et al , 2018||Tablet with Bluetooth connection that receives information from digital health scales, EHR, and patient portal||✓||✓||✓||✓||✓|
|Varey et al , 2019||Tablet||✓||✓||✓|
aEHR: electronic health record.
bHIE: health information exchange.
cEMR: electronic medical record.
dmHealth: mobile health.
eePRO: electronic patient-reported outcomes.
ICTs Aligned With the RMIC
A total of 77% (24/31) of the studies described ICTs that enabled clinical or service integration by coordinating clinical services across multiple professionals, organizations, and sectors (ie, long-term care or acute care services with primary care services) [, - , , - , - , , , , , , ]. mHealth apps, web-based platforms, disease-specific self-measurement devices (eg, glucose monitoring devices), case management software, EMRs, and PHRs were used to ensure care continuity across multiple disciplines. These wide-ranging ICTs supported collaborative goal setting between patients and providers through the use of mHealth apps [ , , , ]; coordination of patient information and clinical guidelines through EHRs, software, or case management platforms [ , - , ]; connecting patients with multiple services by using telephone consultation [ , ]; and supporting patient self-management by using mHealth and telephones [ , ].
In total, 61% (19/31) of the studies described ICT-enabled professional integration among multidisciplinary teams within the same organization or professionals across multiple organizations [, - , , , , , - , , , - , ]. ICTs such as case management platforms, telemonitoring devices, and EHRs or patient portals were used for clinical information sharing across team members [ , - , ]. This shared information was considered important for service coordination and delivery to patients. In addition, mHealth devices such as smartphones and tablets were used to transmit patient data to multiple providers simultaneously [ , , ]. In 19% (6/31) of the studies, an assigned team member (nurse, social worker, or general practitioner) followed up with patients for a routine checkup or to provide health education [ - , , , ].
A total of 26% (8/31) of the studies described organizational integration, achieved through the data-sharing feature of ICTs [- , , , , ]. In total, 16% (5/31) of the studies pursued organizational integration through a shared EHR or case management platform, and patient information was shared across multiple organizations [ , , , , ]. A total of 10% (3/31) of the studies supported organizational integration by creating connections between primary care teams and community services [ - ]. We did not find any studies that pursued system-level integration.
The “formative aspect” of integration is described as the extent to which key functions in a health care model are coordinated across time, services, and settings . The reviewed articles in this study describe multiple key functions achieved through ICTs in integrated primary care settings. The articles emphasized how the coordination of care and information sharing between professionals and between organizations are achieved through ICTs. Similarly, the reviewed articles identified the role that ICTs play in the self-management of chronic conditions supporting patients with complex care needs. In contrast, as the normative aspect of integrated care is achieved through functional, organizational, and service integration, typically, the normative aspect of integration is not considered as a stand-alone objective of an intervention [ , ]. Rather, normative integration is considered as a process or mechanism of integration [ ]. Hence, in this study, we did not identify any examples of how technologies influenced the values, attitudes, and beliefs of actors, organizations, and systems, which are some components of normative integration.
The Types of ICTs and Their Role in Supporting Functions of eCCM and Enabling RMIC
shows how different types of ICTs support different functions of the eCCM and enable different levels of the RMIC. Telemonitoring devices supported self-management and clinical information system components of the eCCM in 48% (15/31) of the studies [ , , , , - , , , , , - ]. The telemonitoring devices often included the daily or weekly reception of patient data shared across teams and organizations and routine follow-up by providers [ , , , , - , , , - ]. This shared patient information enabled clinical, professional, and organizational integration. In addition, by engaging patients in tracking and monitoring their own conditions, these telemonitoring devices enabled self-management support among patients. In 10% (3/31) of the studies, EHRs or EMRs enabled sharing of patient data across multidisciplinary teams [ , ] and organizations [ ], which enabled professional- and organizational-level integration, respectively. In addition, in 10% (3/31) of the studies, patient health portals were described as a tool for patients to access their own health records or appointments and contact health professionals via email [ , , ]. These patient portals enabled clinic- or service-level integration through clinical information management [ , , ]. mHealth apps supported patient self-management to track or monitor patients’ health, social goals, and symptoms as well as share patient information across multidisciplinary teams to tailor clinical services to patients based on their clinical information [ , , , , ]. Finally, 10% (3/31) of the studies described the use of telephones to provide patient education and follow-up and link patients with community resources [ , , ].
|Study, year||Type of technology and its function||Delivery system design||Self-management support enhancements||Clinical decision support enhancements||Clinical information system enhancements||eHealth education||Clinical||Professional||Organizational|
|Alkema et al , 2003||To receive social care management from social workers||✓||✓||✓|
|Alkema et al , 2007||To link patients with source and for monitoring and follow-up by social workers||✓||✓||✓|
|Allen et al , 2011||Patient education and monitoring by nurses||✓||✓||✓||✓||✓||✓||✓|
|EHRa, EMRb, and PHRc|
|Allen et al , 2012||Electric protocol template, telephone, and fax for patient monitoring and evidence-based guidelines||✓||✓||✓||✓||✓||✓||✓|
|Alyousef et al , 2017||Case management software, EHR, and HIEd to facilitate patient information across professionals and organizations||✓||✓||✓||✓|
|Berry et al , 2003||EMR for coordinating multiple services provided to patients||✓||✓||✓||✓|
|Metting et al , 2018||Patient web portal: a place for patients to access their information||✓||✓|
|Portz et al , 2020||Patient portal: a place for patients to access their information||✓||✓|
|Price-Haywood et al , 2017||Shared web-based portal: a place for patients to access their information||✓||✓|
|Bendixen et al , 2007||Basic computer and cell phone with internet capability and in-home messaging device for daily patient monitoring and communication between patient and provider||✓||✓||✓||✓|
|Darkins et al , 2008||Telehealth, including SMS text messages and biometric devices, to monitor patients’ vital signs remotely and coordinate care accordingly||✓||✓||✓||✓||✓||✓|
|Gagnon et al , 2019||Personalized eHealth named CONCERTO+ for sharing patient self-reported data with multiple providers and organizations||✓||✓||✓|
|Hernandez et al , 2015||Remote diagnosis of spirometry testing (not described fully)||✓||✓|
|Martín-Lesende et al , 2013||Telemonitoring of patients’ reported clinical parameters, PDA platform, and routine follow-up via phone||✓||✓||✓||✓|
|Martín-Lesende et al , 2011||Telemonitoring of self-measured clinical parameters and routine follow-up via phone||✓||✓||✓||✓|
|Martín-Lesende et al , 2017||Telemonitoring of self-measured clinical parameters and routine follow-up via phone||✓||✓||✓||✓|
|May et al , 2011||Telecare system: general patient perception of any telehealth-related services||✓||✓||✓|
|Noel et al , 2018||Telehealth: smartphone device, Bluetooth-enabled clinical parameter measurement by patients daily, and weekly follow-up by providers||✓||✓||✓|
|Porath et al , 2017||Telemonitoring system for patient monitoring, patient education, and coordination of multiple services||✓||✓||✓||✓||✓|
|Ryan et al , 2003||Several technologies: (1) an in-home messaging device, the Health Buddy; (2) a disease management app; (3) Instamatic cameras for diabetic wound care management; and (4) personal computers with internet connectivity for remote consultation and supervised chat rooms||✓||✓||✓||✓|
|Sorocco et al , 2013||Telehealth: remote monitoring of daily vitals using a digital scale and provision of services remotely via video||✓||✓||✓||✓|
|Uei et al , 2017||Telehealth (telephone and PHR) for monitoring patient health status and providing health education||✓||✓||✓||✓|
|Valdivieso et al , 2018||Telehealth: tablet with Bluetooth connection that receives information from digital health scales that is connected to EHR and patient portal||✓||✓||✓||✓||✓|
|Varey et al , 2019||Motiva clinical system: a tablet or television where patients can report their vital signs and providers can give educational content, messages, and reminders||✓||✓||✓||✓|
|Clinical event notifications (for providers)|
|Gutteridge et al , 2014||Clinical event notification to inform multiple health professionals about patients’ discharge and schedules to coordinate care across organizations and providers||✓||✓||✓||✓|
|Medication reminder for patients|
|Marek et al , 2013||Medication dispensing system with reminders||✓||✓||✓||✓|
|Hans et al , 2018||Goal management app||✓||✓||✓||✓||✓|
|Jindal et al , 2018||mHealth app||✓||✓||✓||✓||✓||✓|
|Steele Gray et al , 2019||ePROf tool, a goal-supporting mHealth app||✓||✓||✓||✓||✓|
|Steele Gray et al , 2016||ePRO tool, a goal-supporting mHealth app||✓||✓||✓||✓||✓|
|Steele Gray et al , 2016||ePRO tool, a goal-supporting mHealth app||✓||✓||✓||✓|
aEHR: electronic health record.
bEMR: electronic medical record.
cPHR: patient health record.
dHIE: health information exchange.
emHealth: mobile health.
fePRO: electronic patient-reported outcomes.
Outcomes and Process Measures Reported in the Studies
Aligning with the RMIC goal of improving the patient experience by pursuing the triple aim of health care, the studies reported outcomes related to the triple aim, such as quality of life (improved health), cost-effectiveness (lower cost), and acceptability of the care delivery system (improved care). Outcome measures included patients’ health outcomes (eg, mental and physical conditions), patient and provider perceived outcomes (eg, satisfaction), and cost-effectiveness. Patient experience measures included satisfaction, perceived empowerment, caregiver strain, loneliness, self-efficacy, acceptability, and usability of the technology [, , - , - , , ]. Cost-effectiveness included costs associated with hospital use and cost-efficiency [ , , , , , - , , , , ]. We did not observe any pattern in the type of outcome or technology.
In total, 68% (21/31) of the studies evaluated outcomes. A total of 45% (14/31) measured selected clinical outcomes such as quality of life (6/31, 19%) [- , , , , ], mental or physical conditions [ , ], and hospital use (10/31, 32%) [ , , , , , , , , ]. Among the nonclinical outcomes, provider workload [ ], patient-provider relationship [ ], patient satisfaction [ , , , ], cost-effectiveness [ , , ], and attitude toward technologies [ , , ] were studied. In contrast, patients’ self-efficacy (3/31, 10%) [ , , ] and acceptability of the technologies (4/31, 13%) [ , , , ] were explored mostly in mixed methods and qualitative studies. The cost-effectiveness (4/31, 13%) [ , , ] of the implemented technologies was evaluated quantitatively and through mixed methods research.
Implementation Factors Reported in the Identified Studies
The implementation of technology has been identified in the digital health literature as a key issue that requires further exploration . Thus, we extracted the factors associated with the successful implementation of technology in the models of care described in the studies. Inductive analysis of the studies revealed implementation factors of technologies that were categorized into the patient, provider, technology, and organizational level. shows the implementation factors discussed in each study.
Patient characteristics that were described as important implementation factors in the selected studies included age, gender, type of chronic conditions [, ], patients’ interest in buying into the technology [ ], digital literacy [ , ], and perceived ease of use and usefulness [ ]. At the provider level, their willingness to adopt digital technology in their practice [ , , , ], collaboration and communication among providers [ , ], and providers’ level of ICT training [ ] contributed to the implementation of ICT-enabled integrated primary care. Barriers to implementation arose when technology disrupted provider workflow [ , , ] and increased their workload [ ].
Some implementation factors spanned more than one category. Notably, the patient-provider relationship emerged as an important factor [, ]. For example, Berry et al [ ] signaled that technology-enabled care works better when there is a long-established trusting relationship between the patient and the provider.
In addition, technology- and organizational-related implementation factors emerged. Technology-related factors such as system errors [, , , ], lack of interoperability with existing technologies (such as EMRs) [ , , ], and technologies’ lack of responsiveness to the patient and providers’ needs and tasks were found to deter implementation in 16% (5/31) of the studies [ , , , , ]. At the organizational level, funding support [ ] and organizations’ willingness to adopt a new technology [ ] were reported as important organizational-level implementation factors. Moreover, having a coordinator to support IT-related issues [ ], having a team structure that involves nurses [ ], and having additional care coordination [ ] were also reported as important implementation factors for ICT-based integrated primary care.
|Alkema et al , 2003||✓|
|Alkema et al , 2007||✓||✓|
|Allen et al , 2011||✓||✓||✓|
|Allen et al , 2012||✓||✓|
|Alyousef et al , 2017||✓|
|Bendixen et al , 2007||✓||✓||✓||✓|
|Berry et al , 2013||✓||✓||✓|
|Darkins et al , 2008||✓|
|Gagnon et al , 2019||✓||✓|
|Gutteridge et al , 2014||✓|
|Hans et al , 2018||✓||✓|
|Hernandez et al , 2015||✓||✓|
|Jindal et al , 2018|
|Marek et al , 2013||✓||✓||✓||✓|
|Martín-Lesende et al , 2013|
|Martín-Lesende et al , 2011||✓||✓|
|Martín-Lesende et al , 2017||✓||✓||✓||✓|
|May et al , 2011||✓||✓|
|Metting et al , 2018||✓||✓||✓||✓|
|Noel et al , 2018||✓||✓|
|Porath et al , 2017||✓||✓||✓|
|Portz et al , 2018||✓|
|Price-Haywood et al , 2017||✓||✓|
|Ryan et al , 2003||✓||✓|
|Sorocco et al , 2013||✓||✓|
|Steele Gray et al , 2019||✓||✓||✓||✓|
|Steele Gray et al , 2016||✓||✓||✓||✓|
|Steele Gray et al , 2016||✓||✓||✓||✓|
|Uei et al , 2017||✓|
|Valdivieso et al , 2018||✓|
|Varey et al , 2020||✓||✓||✓|
The primary objective of this scoping review was to provide a comprehensive overview of the types of ICTs that are being used to support patients with complex care needs in the integrated primary care model. The findings show that, in the current ICT-based integrated primary care models, wide-ranging technologies such as telemonitoring devices, mHealth apps, EHRs, and telephones are being used to support patients with complex care needs. These technologies enable information sharing among multiple professionals within and across organizations and between patients and providers. These technologies support care integration at the service or clinical, professional, and organizational levels. However, system-level integration was absent in this study. The findings also show that patient-, provider-, technology-, and organizational-level factors contribute to the implementation of ICTs in the integrated primary care model.
Among the identified studies, we observed a number of ICTs that enabled clinical information management across teams in the integrated primary care models. These ICTs promoted teamwork across professionals by providing access to critical patient information across the teams. This shared patient information system is considered a critical tenet of an integrated primary care model [, ]. Moreover, ICTs that supported patient self-management were also frequently observed. This finding is unsurprising as a previous study identified that, given the nature of chronic conditions, self-measurement of the body is frequently used to track symptoms [ ]. This self-management approach to chronic conditions can empower patients by engaging them with their care plan, which in turn can improve patients’ health outcomes [ ]. In contrast, too many self-management responsibilities can overwhelm patients, especially if the patient has a low capacity (ie, financial resources) to shoulder the responsibilities [ ]. For example, a number of ICT-based interventions in this review required daily reporting of patients’ vital signs and symptoms [ , - , , ]. For patients with complex care needs, this daily reporting of vital signs may be overwhelming because of the number of conditions and complexity related to each condition. Therefore, it is critical to examine how to effectively use and design ICTs to minimize the self-management–related workload for patients.
The findings of this study show that a number of ICTs transmit patient data to providers for remote disease monitoring. However, most of these ICTs lack a 2-way communication loop. As a result, providers may receive an overwhelming amount of patient data, but engaging in a productive interaction may be difficult for both the patient and provider without a 2-way communication loop. This is problematic as the quality of the eCCM relies strongly on productive interaction and communication between providers and patients . Therefore, an increased effort to promote meaningful and productive interaction between patients and providers can improve the effectiveness of ICT-based interventions designed for patients with complex care needs [ ].
Identified Research Gap and Recommendation for Future Research
This scoping review revealed several gaps in the current literature. System-level integration and the normative aspect of integration were absent in the sample of studies in this review. Undertaking an ICT-enabled system integration can be challenging because of interoperability issues, provider unwillingness, lack of coalition among stakeholders, lack of data privacy, and security issues [, ]. For future researchers, it would be important to explore the broader system-level changes that are required for the successful adoption and implementation of ICTs in the integrated primary care model.
In addition, normative aspects of integration, such as culture, shared vision, and regulatory factors, need to be studied further for the long-term sustainability of ICT-based integrated primary care. Evaluation frameworks used in implementation science , such as the Consolidated Framework for Implementation Research [ ] and the nonadoption, abandonment, scale-up, spread, and sustainability framework by Greenhalgh et al [ ], can be useful to explore the normative factors that can contribute to the implementation of ICT-based interventions in the integrated primary care setting.
Furthermore, organizational integration was also minimally described in the studies. Organizational-level integration may be difficult because of a lack of shared vision in terms of policy, regulations, and culture across organizations . This lack of organizational integration may negatively affect patients with complex care needs as they may have to report similar information to multiple providers. For example, although ICTs can be helpful in creating an eCommunity that enables access to patient data for community staff and social service organizations, this aspect of the eCCM is currently underused. However, creating an eCommunity where patients’ clinical data are readily available to formal or informal caregivers can reduce the patients’ need to repeat information to multiple providers, thereby reducing the burden on patients and caregivers [ ]. We also identified that the definitions of the components of the eCCM are broad, which made the categorization of the ICTs difficult and interpretive. This criticism of the eCCM has been identified in previous work [ ].
In terms of measured outcomes, 45% (14/31) of the studies evaluated the impact of ICTs at the patient level through a clinical lens, such as quality of life. Going beyond clinical outcomes, such as health status or symptoms, and considering the impact of ICTs on patients’ relational factors, such as patient-provider relationships  or potential disruption of technology in patients’ lives [ ], may be important factors to consider for future researchers.
To categorize the study data, we used 2 established conceptual frameworks, the eCCM and RMIC, which helped identify literature gaps. For example, by categorizing the role of ICTs in the RMIC, we identified that there is little information available about ICT-enabled system-level and normative integration. In addition, the use of these established frameworks will be helpful for future researchers from multiple contexts and jurisdictions to interpret and apply the findings to their own contexts. The use of the scoping review method also allowed us to provide a comprehensive overview of the literature on the topic regardless of methodology, quality of the publications, and measured outcomes . This will be helpful for researchers to gain an understanding of the current landscape of ICTs supporting patients with complex care needs in integrated primary care settings.
This scoping review has a few notable limitations. Owing to time and resource constraints, we were unable to conduct a review of gray literature, potentially missing relevant publications. However, the peer-reviewed sample was extracted from a very large pool of potential articles, which adds to our confidence that the peer-reviewed literature was thoroughly covered. Second, we have observed that the term “complex patient” is defined in various ways in the current literature. We may have missed unexpected characterizations of a patient with complex care needs that are not captured in the current literature. In addition, we did not involve patients or the public during the conceptualization of the research question. However, we tackled this issue by disseminating our research findings among different audiences (conferences and webinars) that were accessible to the public.
This scoping review identified that multiple types of ICTs play important functional roles in supporting patients with complex care needs in integrated primary care settings. ICTs play a critical role in coordinating multiple clinical services across multidisciplinary teams and supporting the self-management of patients with complex care needs remotely. However, to use the full potential of ICTs, further studies are required to understand how to achieve organizational- and system-level integration.
Primary funding for this research was through a research endowment fund from the Lunenfeld-Tanenbaum Research Institute in Sinai Health to support the development of the senior author's (CSG) program of work. In addition, this research was undertaken in part thanks to funding from the Canada Research Chairs Program.
Conflicts of Interest
Key search domains and associated search terms.DOCX File , 15 KB
Search strategy for PsycINFO.DOCX File , 18 KB
- Sakib MN, Shooshtari S, St John P, Menec V. The prevalence of multimorbidity and associations with lifestyle factors among middle-aged Canadians: an analysis of Canadian Longitudinal Study on Aging data. BMC Public Health 2019 Feb 28;19(1):243 [FREE Full text] [CrossRef] [Medline]
- Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 2012 Jul 07;380(9836):37-43 [FREE Full text] [CrossRef] [Medline]
- Harrison C, Britt H, Miller G, Henderson J. Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice. BMJ Open 2014 Jul 11;4(7):e004694 [FREE Full text] [CrossRef] [Medline]
- Morris RL, Sanders C, Kennedy AP, Rogers A. Shifting priorities in multimorbidity: a longitudinal qualitative study of patient's prioritization of multiple conditions. Chronic Illn 2011 Jun;7(2):147-161. [CrossRef] [Medline]
- Shippee N, Shah N, May C, Mair F, Montori V. Cumulative complexity: a functional, patient-centered model of patient complexity can improve research and practice. J Clin Epidemiol 2012 Oct;65(10):1041-1051 [FREE Full text] [CrossRef] [Medline]
- Coventry PA, Small N, Panagioti M, Adeyemi I, Bee P. Living with complexity; marshalling resources: a systematic review and qualitative meta-synthesis of lived experience of mental and physical multimorbidity. BMC Fam Pract 2015 Nov 24;16:171 [FREE Full text] [CrossRef] [Medline]
- Zulman DM, Asch SM, Martins SB, Kerr EA, Hoffman BB, Goldstein MK. Quality of care for patients with multiple chronic conditions: the role of comorbidity interrelatedness. J Gen Intern Med 2014 Mar;29(3):529-537 [FREE Full text] [CrossRef] [Medline]
- 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 Sep;33(3):343-364. [CrossRef] [Medline]
- Schaink AK, Kuluski K, Lyons RF, Fortin M, Jadad AR, Upshur R, et al. A scoping review and thematic classification of patient complexity: offering a unifying framework. J Comorb 2012;2:1-9 [FREE Full text] [CrossRef] [Medline]
- May CR, Eton DT, Boehmer K, Gallacher K, Hunt K, MacDonald S, et al. Rethinking the patient: using Burden of Treatment Theory to understand the changing dynamics of illness. BMC Health Serv Res 2014 Jun 26;14:281 [FREE Full text] [CrossRef] [Medline]
- Leppin A, Montori V, Gionfriddo M. Minimally disruptive medicine: a pragmatically comprehensive model for delivering care to patients with multiple chronic conditions. Healthcare (Basel) 2015 Jan 29;3(1):50-63 [FREE Full text] [CrossRef] [Medline]
- Starfield B. Primary care: an increasingly important contributor to effectiveness, equity, and efficiency of health services. SESPAS report 2012. Gac Sanit 2012 Mar;26 Suppl 1:20-26 [FREE Full text] [CrossRef] [Medline]
- Valentijn PP, Schepman SM, Opheij W, Bruijnzeels MA. Understanding integrated care: a comprehensive conceptual framework based on the integrative functions of primary care. Int J Integr Care 2013;13:e010 [FREE Full text] [CrossRef] [Medline]
- Steele Gray C, Barnsley J, Gagnon D, Belzile L, Kenealy T, Shaw J, et al. Using information communication technology in models of integrated community-based primary health care: learning from the iCOACH case studies. Implement Sci 2018 Jun 26;13(1):87 [FREE Full text] [CrossRef] [Medline]
- Anderson G, Wodchis W. Providing integrated care for older people with complex needs: lessons from seven international case studies. The King's Fund. 2014 Jan 30. URL: https://www.kingsfund.org.uk/publications/providing-integrated-care-older-people-complex-needs [accessed 2022-01-14]
- Valentijn PP, Pereira F, Sterner CW, Vrijhoef HJ, Ruwaard D, Hegbrant J, et al. validation of the rainbow model of integrated care measurement tools (RMIC-MTs) in renal care for patient and care providers. PLoS One 2019 Sep 19;14(9):e0222593 [FREE Full text] [CrossRef] [Medline]
- Boesveld IC, Valentijn PP, Hitzert M, Hermus MA, Franx A, de Vries RG, et al. An approach to measuring integrated care within a maternity care system: experiences from the maternity care network study and the Dutch Birth Centre study. Int J Integr Care 2017 Jun 20;17(2):6 [FREE Full text] [CrossRef] [Medline]
- van der Klauw D, Molema H, Grooten L, Vrijhoef H. Identification of mechanisms enabling integrated care for patients with chronic diseases: a literature review. Int J Integr Care 2014 Jul;14:e024 [FREE Full text] [CrossRef] [Medline]
- Gray C, Gagnon D, Guldemond N, Kenealy T. Digital health enabling integrated care. In: How to Deliver Integrated Care (European Health Management in Transition). Bingley, United Kingdom: Emerald Publishing Limited; 2021.
- Steele Gray C. Integrated care's new protagonist: the expanding role of digital health. Int J Integr Care 2021;21(4):1 [FREE Full text] [CrossRef] [Medline]
- Gee PM, Greenwood DA, Paterniti DA, Ward D, Miller LM. The eHealth Enhanced Chronic Care Model: a theory derivation approach. J Med Internet Res 2015 Apr 01;17(4):e86 [FREE Full text] [CrossRef] [Medline]
- WHO Global Observatory for eHealth. Telemedicine: Opportunities and Developments in Member States: Report on the Second Global Survey on eHealth. Geneva: World Health Organization; 2010.
- Eysenbach G. What is e-health? J Med Internet Res 2001;3(2):E20 [FREE Full text] [CrossRef] [Medline]
- Feger H, Crump B, Scott P. UK learning about digital health and COVID-19. BMJ Health Care Inform 2021 May;28(1):e100376 [FREE Full text] [CrossRef] [Medline]
- Falconer E, Kho D, Docherty JP. Use of technology for care coordination initiatives for patients with mental health issues: a systematic literature review. Neuropsychiatr Dis Treat 2018;14:2337-2349 [FREE Full text] [CrossRef] [Medline]
- Sinsky CA, Jerzak JT, Hopkins KD. Telemedicine and team-based care: the perils and the promise. Mayo Clin Proc 2021 Feb;96(2):429-437 [FREE Full text] [CrossRef] [Medline]
- Ramirez M, Wu S, Ryan G, Towfighi A, Vickrey BG. Using beta-version mHealth technology for team-based care management to support stroke prevention: an assessment of utility and challenges. JMIR Res Protoc 2017 May 23;6(5):e94 [FREE Full text] [CrossRef] [Medline]
- Lydon C. Five NHS trusts roll out Allocate’s eCommunity to help free up staff time. Digital Health. 2021 Aug 18. URL: https://www.digitalhealth.net/2021/08/five-nhs-trusts-adopt-allocate-ecommunity/ [accessed 2022-05-05]
- Daniel H, Sulmasy LS, HealthPublic Policy Committee of the American College of Physicians. Policy recommendations to guide the use of telemedicine in primary care settings: an American College of Physicians position paper. Ann Intern Med 2015 Nov 17;163(10):787-789 [FREE Full text] [CrossRef] [Medline]
- Darkins A, Ryan P, Kobb R, Foster L, Edmonson E, Wakefield B, et al. Care Coordination/Home Telehealth: the systematic implementation of health informatics, home telehealth, and disease management to support the care of veteran patients with chronic conditions. Telemed J E Health 2008 Dec;14(10):1118-1126. [CrossRef] [Medline]
- Kouroubali A, Kondylakis H, Katehakis DG. Integrated care in the era of COVID-19: turning vision into reality with digital health. Front Digit Health 2021;3:647938 [FREE Full text] [CrossRef] [Medline]
- Wagner EH. Chronic disease management: what will it take to improve care for chronic illness? Eff Clin Pract 1998;1(1):2-4. [Medline]
- Aryani FM, Lee SW, Chua SS, Kok LC, Efendie B, Paraidathathu T. Chronic care model in primary care: can it improve health-related quality of life? Integr Pharm Res Pract 2016;5:11-17 [FREE Full text] [CrossRef] [Medline]
- Arksey H, O'Malley L. Scoping studies: towards a methodological framework. Int J Social Res Methodol 2005 Feb;8(1):19-32. [CrossRef]
- Levac D, Colquhoun H, O'Brien KK. Scoping studies: advancing the methodology. Implement Sci 2010 Sep 20;5:69 [FREE Full text] [CrossRef] [Medline]
- Tahsin F, Armas A, Kirakalaprathapan A, Cunningham H, Kadu M, Sritharan J, et al. Information and Communication Technologies (ICTs) enabling integrated primary care for complex patients: a protocol for a scoping review. Syst Rev 2022 Sep 07;11(1):193 [FREE Full text] [CrossRef] [Medline]
- Looman W, Struckmann V, Köppen J, Baltaxe E, Czypionka T, Huic M, SELFIE consortium. Drivers of successful implementation of integrated care for multi-morbidity: mechanisms identified in 17 case studies from 8 European countries. Soc Sci Med 2021 May;277:113728 [FREE Full text] [CrossRef] [Medline]
- Shaw T, McGregor D, Brunner M, Keep M, Janssen A, Barnet S. What is eHealth (6)? Development of a conceptual model for eHealth: qualitative study with key informants. J Med Internet Res 2017 Oct 24;19(10):e324 [FREE Full text] [CrossRef] [Medline]
- Thielke S, Vannoy S, Unützer J. Integrating mental health and primary care. Prim Care 2007 Sep;34(3):571-92, vii. [CrossRef] [Medline]
- Nutting PA, Gallagher KM, Riley K, White S, Dietrich AJ, Dickinson WP. Implementing a depression improvement intervention in five health care organizations: experience from the RESPECT-Depression trial. Adm Policy Ment Health 2007 Mar;34(2):127-137. [CrossRef] [Medline]
- Peters MD, Marnie C, Tricco AC, Pollock D, Munn Z, Alexander L, et al. Updated methodological guidance for the conduct of scoping reviews. JBI Evid Implement 2021 Mar;19(1):3-10. [CrossRef] [Medline]
- Hsieh H, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res 2005 Nov;15(9):1277-1288. [CrossRef] [Medline]
- Branca Vergano L, Monesi M, Vicenti G, Bizzoca D, Solarino G, Moretti B. Posterior approaches in malleolar fracture: when, why and how. J Biol Regul Homeost Agents 2020;34(3 Suppl. 2):89-95. [Medline]
- Digital health enabling integrated care webinar series. International Foundation for Integrated Care. URL: https://integratedcarefoundation.org/events/digital-health-enabling-integrated-care-webinar-series-2 [accessed 2021-12-22]
- Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021 Mar 29;372:n71 [FREE Full text] [CrossRef] [Medline]
- Alkema GE, Shannon GR, Wilber KH. Using interagency collaboration to serve older adults with chronic care needs: the Care Advocate Program. Fam Community Health 2003;26(3):221-229. [CrossRef] [Medline]
- Alkema GE, Wilber KH, Shannon GR, Allen D. Reduced mortality: the unexpected impact of a telephone-based care management intervention for older adults in managed care. Health Serv Res 2007 Aug;42(4):1632-1650 [FREE Full text] [CrossRef] [Medline]
- Allen KR, Hazelett SE, Jarjoura D, Wright K, Fosnight SM, Kropp DJ, et al. The after discharge care management of low income frail elderly (AD-LIFE) randomized trial: theoretical framework and study design. Popul Health Manag 2011 Jun;14(3):137-142 [FREE Full text] [CrossRef] [Medline]
- Allen KR, Hazelett SE, Radwany S, Ertle D, Fosnight SM, Moore PS. The Promoting Effective Advance Care for Elders (PEACE) randomized pilot study: theoretical framework and study design. Popul Health Manag 2012 Apr;15(2):71-77. [CrossRef] [Medline]
- Alyousef B, Carayon P, Hoonakker P, Hundt AS, Salek D, Tomcavage J. Obstacles experienced by care managers in managing information for the care of chronically ill patients. Int J Hum Comput Interact 2017 Dec 12;33(4):313-321 [FREE Full text] [CrossRef] [Medline]
- Bendixen RM, Horn K, Levy C. Using telerehabilitation to support elders with chronic illness in their homes. Topics Geriatric Rehabil 2007;23(1):47-51. [CrossRef]
- Berry LL, Rock BL, Smith Houskamp B, Brueggeman J, Tucker L. Care coordination for patients with complex health profiles in inpatient and outpatient settings. Mayo Clin Proc 2013 Feb;88(2):184-194. [CrossRef] [Medline]
- Gagnon M, Ndiaye MA, Larouche A, Chabot G, Chabot C, Buyl R, et al. Optimising patient active role with a user-centred eHealth platform (CONCERTO+) in chronic diseases management: a study protocol for a pilot cluster randomised controlled trial. BMJ Open 2019 Apr 02;9(4):e028554 [FREE Full text] [CrossRef] [Medline]
- Gutteridge DL, Genes N, Hwang U, Kaplan B, GEDI WISE Investigators, Shapiro JS. Enhancing a geriatric emergency department care coordination intervention using automated health information exchange-based clinical event notifications. EGEMS (Wash DC) 2014;2(3):1095 [FREE Full text] [CrossRef] [Medline]
- Hans PK, Gray CS, Gill A, Tiessen J. The provider perspective: investigating the effect of the Electronic Patient-Reported Outcome (ePRO) mobile application and portal on primary care provider workflow. Prim Health Care Res Dev 2018 Mar;19(2):151-164 [FREE Full text] [CrossRef] [Medline]
- Hernández C, Alonso A, Garcia-Aymerich J, Grimsmo A, Vontetsianos T, García Cuyàs F, et al. Integrated care services: lessons learned from the deployment of the NEXES project. Int J Integr Care 2015;15:e006 [FREE Full text] [CrossRef] [Medline]
- Jindal D, Gupta P, Jha D, Ajay VS, Goenka S, Jacob P, et al. Development of mWellcare: an mHealth intervention for integrated management of hypertension and diabetes in low-resource settings. Glob Health Action 2018;11(1):1517930 [FREE Full text] [CrossRef] [Medline]
- Marek KD, Stetzer F, Ryan PA, Bub LD, Adams SJ, Schlidt A, et al. Nurse care coordination and technology effects on health status of frail older adults via enhanced self-management of medication: randomized clinical trial to test efficacy. Nurs Res 2013;62(4):269-278 [FREE Full text] [CrossRef] [Medline]
- Martín-Lesende I, Orruño E, Bilbao A, Vergara I, Cairo MC, Bayón JC, et al. Impact of telemonitoring home care patients with heart failure or chronic lung disease from primary care on healthcare resource use (the TELBIL study randomised controlled trial). BMC Health Serv Res 2013 Mar 28;13:118 [FREE Full text] [CrossRef] [Medline]
- Martín-Lesende I, Orruño E, Cairo C, Bilbao A, Asua J, Romo MI, et al. Assessment of a primary care-based telemonitoring intervention for home care patients with heart failure and chronic lung disease. The TELBIL study. BMC Health Serv Res 2011 Mar 08;11:56 [FREE Full text] [CrossRef] [Medline]
- Martín-Lesende I, Orruño E, Mateos M, Recalde E, Asua J, Reviriego E, et al. Telemonitoring in-home complex chronic patients from primary care in routine clinical practice: impact on healthcare resources use. Eur J Gen Pract 2017 Dec;23(1):135-142 [FREE Full text] [CrossRef] [Medline]
- May CR, Finch TL, Cornford J, Exley C, Gately C, Kirk S, et al. Integrating telecare for chronic disease management in the community: what needs to be done? BMC Health Serv Res 2011 May 27;11:131 [FREE Full text] [CrossRef] [Medline]
- Metting E, Schrage AJ, Kocks JW, Sanderman R, van der Molen T. Assessing the needs and perspectives of patients with asthma and chronic obstructive pulmonary disease on patient web portals: focus group study. JMIR Form Res 2018 Nov 22;2(2):e22 [FREE Full text] [CrossRef] [Medline]
- Noel K, Yagudayev S, Messina C, Schoenfeld E, Hou W, Kelly G. Tele-transitions of care. A 12-month, parallel-group, superiority randomized controlled trial protocol, evaluating the use of telehealth versus standard transitions of care in the prevention of avoidable hospital readmissions. Contemp Clin Trials Commun 2018 Dec;12:9-16 [FREE Full text] [CrossRef] [Medline]
- Porath A, Irony A, Borobick AS, Nasser S, Malachi A, Fund N, et al. Maccabi proactive Telecare Center for chronic conditions - the care of frail elderly patients. Isr J Health Policy Res 2017 Dec 11;6(1):68 [FREE Full text] [CrossRef] [Medline]
- Portz JD, Bayliss EA, Bull S, Boxer RS, Bekelman DB, Gleason K, et al. Using the technology acceptance model to explore user experience, intent to use, and use behavior of a patient portal among older adults with multiple chronic conditions: descriptive qualitative study. J Med Internet Res 2019 Apr 08;21(4):e11604 [FREE Full text] [CrossRef] [Medline]
- Price-Haywood EG, Harden-Barrios J, Ulep R, Luo Q. Ehealth literacy: patient engagement in identifying strategies to encourage use of patient portals among older adults. Popul Health Manag 2017 Dec;20(6):486-494. [CrossRef] [Medline]
- Ryan P, Kobb R, Hilsen P. Making the right connection: matching patients to technology. Telemed J E Health 2003;9(1):81-88. [CrossRef] [Medline]
- Sorocco KH, Bratkovich KL, Wingo R, Qureshi SM, Mason PJ. Integrating care coordination home telehealth and home based primary care in rural Oklahoma: a pilot study. Psychol Serv 2013 Aug;10(3):350-352. [CrossRef] [Medline]
- Steele Gray C, Gill A, Khan AI, Hans PK, Kuluski K, Cott C. The electronic patient reported outcome tool: testing usability and feasibility of a mobile app and portal to support care for patients with complex chronic disease and disability in primary care settings. JMIR Mhealth Uhealth 2016 Jun 02;4(2):e58 [FREE Full text] [CrossRef] [Medline]
- Steele Gray C, Khan AI, Kuluski K, McKillop I, Sharpe S, Bierman AS, et al. Improving patient experience and primary care quality for patients with complex chronic disease using the electronic patient-reported outcomes tool: adopting qualitative methods into a user-centered design approach. JMIR Res Protoc 2016 Feb 18;5(1):e28 [FREE Full text] [CrossRef] [Medline]
- Uei S, Kuo Y, Tsai C, Kuo Y. An exploration of intent to use telehealth at home for patients with chronic diseases. Int J Environ Res Public Health 2017 Dec 09;14(12):1544 [FREE Full text] [CrossRef] [Medline]
- Valdivieso B, García-Sempere A, Sanfélix-Gimeno G, Faubel R, Librero J, Soriano E, GeChronic Group. The effect of telehealth, telephone support or usual care on quality of life, mortality and healthcare utilization in elderly high-risk patients with multiple chronic conditions. A prospective study. Med Clin (Barc) 2018 Oct 23;151(8):308-314. [CrossRef] [Medline]
- Varey S, Dixon M, Hernández A, Mateus C, Palmer T, Milligan C. The role of combinatorial health technologies in supporting older people with long-term conditions: responsibilisation or co-management of healthcare? Soc Sci Med 2021 Jan;269:113545. [CrossRef] [Medline]
- Pols J. Front matter. In: Care at a Distance: On the Closeness of Technology. Amsterdam, Netherlands: Amsterdam University Press; 2012.
- Greenhalgh T, Wherton J, Papoutsi C, Lynch J, Hughes G, A'Court C, et al. Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. J Med Internet Res 2017 Nov 01;19(11):e367 [FREE Full text] [CrossRef] [Medline]
- Price-Haywood E, Burton J, Harden-Barrios J, Bazzano A, Lefante J, Shi L, et al. Depression, anxiety, pain and chronic opioid management in primary care: type II effectiveness-implementation hybrid stepped wedge cluster randomized trial. Contemp Clin Trials 2021 Feb;101:106250 [FREE Full text] [CrossRef] [Medline]
- Steele Gray C, Gravesande J, Hans PK, Nie JX, Sharpe S, Loganathan M, et al. Using exploratory trials to identify relevant contexts and mechanisms in complex electronic health interventions: evaluating the electronic patient-reported outcome tool. JMIR Form Res 2019 Feb 27;3(1):e11950 [FREE Full text] [CrossRef] [Medline]
- Kodner D. All together now: a conceptual exploration of integrated care. Healthc Q 2009 Oct 16;13 Spec No(sp):6-15. [CrossRef] [Medline]
- Ryan A, Wallace E, O'Hara P, Smith SM. Multimorbidity and functional decline in community-dwelling adults: a systematic review. Health Qual Life Outcomes 2015 Oct 15;13(1):168 [FREE Full text] [CrossRef] [Medline]
- Buis L. Implementation: the next giant hurdle to clinical transformation with digital health. J Med Internet Res 2019 Nov 20;21(11):e16259 [FREE Full text] [CrossRef] [Medline]
- Wildevuur SE, Simonse LW. Information and communication technology-enabled person-centered care for the "big five" chronic conditions: scoping review. J Med Internet Res 2015 Mar 27;17(3):e77 [FREE Full text] [CrossRef] [Medline]
- Bartlett SJ, Lambert SD, McCusker J, Yaffe M, de Raad M, Belzile E, et al. Self-management across chronic diseases: targeting education and support needs. Patient Educ Couns 2020 Feb;103(2):398-404. [CrossRef] [Medline]
- Maruthappu M, Hasan A, Zeltner T. Enablers and barriers in implementing integrated care. Health Syst Reform 2015 May 19;1(4):250-256. [CrossRef] [Medline]
- Oksavik JD, Kirchhoff R, Sogstad MK, Solbjør M. Sharing responsibility: municipal health professionals' approaches to goal setting with older patients with multi-morbidity - a grounded theory study. BMC Health Serv Res 2020 Feb 24;20(1):141 [FREE Full text] [CrossRef] [Medline]
- Nilsen P. Making sense of implementation theories, models and frameworks. Implement Sci 2015 Apr 21;10:53 [FREE Full text] [CrossRef] [Medline]
- Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci 2009 Aug 07;4:50 [FREE Full text] [CrossRef] [Medline]
- Kinch V. Identification & Visualization of Patient Information Elements to Support Chronic Illness Care: a Scoping Review and Pilot Study. Victoria, Canada: University of Victoria; 2017.
- Weiner M, Biondich P. The influence of information technology on patient-physician relationships. J Gen Intern Med 2006 Jan;21 Suppl 1(Suppl 1):S35-S39 [FREE Full text] [CrossRef] [Medline]
|eCCM: eHealth Enhanced Chronic Care Model|
|EHR: electronic health record|
|EMR: electronic medical record|
|ICT: information and communications technology|
|mHealth: mobile health|
|PHR: patient health record|
|PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses|
|RMIC: Rainbow Model of Integrated Care|
Edited by A Mavragani; submitted 04.11.22; peer-reviewed by M Gottumukkala, H Pilabré; comments to author 21.01.23; revised version received 02.02.23; accepted 10.03.23; published 19.04.23Copyright
©Farah Tahsin, Alana Armas, Apery Kirakalaprathapan, Mudathira Kadu, Jasvinei Sritharan, Carolyn Steele Gray. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.04.2023.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.