Design, effectiveness, and economic outcomes of contemporary chronic disease clinical decision support systems: a systematic review and meta-analysis

Integrated patient-centred care for type 2 diabetes in Singapore Primary Care Networks: a mixed-methods study

OBJECTIVE

Patients with type 2 diabetes require patient-centred care as guided by the Chronic Care Model (CCM). Many diabetes patients in Singapore are managed by the Primary Care Networks (PCNs) which organised healthcare professionals (HCPs) comprising general practitioners, nurses and care coordinators into teams to provide diabetes care. Little is known about how the PCNs deliver care to people with type 2 diabetes. This study evaluated the consistency of diabetes care delivery in the PCNs with the CCM.

DESIGN

This was a mixed-method study. The Assessment of Chronic Illness Care (ACIC version 3.5) survey was self-administered by the HCPs in the quantitative study (ACIC scores range 0-11, the latter indicating care delivery most consistent with CCM). Descriptive statistics were obtained, and linear mixed-effects regression model was used to test for association between independent variables and ACIC total scores. The qualitative study comprised semi-structured focus group discussions and used thematic analysis.

SETTING

The study was conducted on virtual platforms involving the PCNs.

PARTICIPANTS

179 HCPs for quantitative study and 65 HCPs for qualitative study.

RESULTS

Integrated analysis of quantitative and qualitative results found that there was support for diabetes care consistent with the CCM in the PCNs. The mean ACIC total score was 5.62 (SD 1.93). The mean element scores ranged from 6.69 (SD 2.18) (Health System Organisation) to 4.91 (SD 2.37) (Community Linkages). The qualitative themes described how the PCNs provided much needed diabetes services, their characteristics such as continuity of care, patient-centred care; collaborating with community partners, financial aspects of care, enablers for and challenges in performing care, and areas for enhancement.

CONCLUSION

This mixed-methods study informs that diabetes care delivery in the Singapore PCNs is consistent with the CCM. Future research should consider using independent observers in the quantitative study and collecting objective data such as patient outcomes.

Developing an integrated clinical decision support system for the early identification and management of kidney disease-building cross-sectoral partnerships

BACKGROUND

The burden of chronic conditions is growing in Australia with people in remote areas experiencing high rates of disease, especially kidney disease. Health care in remote areas of the Northern Territory (NT) is complicated by a mobile population, high staff turnover, poor communication between health services and complex comorbid health conditions requiring multidisciplinary care.

AIM

This paper aims to describe the collaborative process between research, government and non-government health services to develop an integrated clinical decision support system to improve patient care.

METHODS

Building on established partnerships in the government and Aboriginal Community-Controlled Health Service (ACCHS) sectors, we developed a novel digital clinical decision support system for people at risk of developing kidney disease (due to hypertension, diabetes, cardiovascular disease) or with kidney disease. A cross-organisational and multidisciplinary Steering Committee has overseen the design, development and implementation stages. Further, the system's design and functionality were strongly informed by experts (Clinical Reference Group and Technical Working Group), health service providers, and end-user feedback through a formative evaluation.

RESULTS

We established data sharing agreements with 11 ACCHS to link patient level data with 56 government primary health services and six hospitals. Electronic Health Record (EHR) data, based on agreed criteria, is automatically and securely transferred from 15 existing EHR platforms. Through clinician-determined algorithms, the system assists clinicians to diagnose, monitor and provide guideline-based care for individuals, as well as service-level risk stratification and alerts for clinically significant events.

CONCLUSION

Disconnected health services and separate EHRs result in information gaps and a health and safety risk, particularly for patients who access multiple health services. However, barriers to clinical data sharing between health services still exist. In this first phase, we report how robust partnerships and effective governance processes can overcome these barriers to support clinical decision making and contribute to holistic care.

Acceptance and use of a clinical decision support system in musculoskeletal pain disorders - the SupportPrim project

BACKGROUND

We have developed a clinical decision support system (CDSS) based on methods from artificial intelligence to support physiotherapists and patients in the decision-making process of managing musculoskeletal (MSK) pain disorders in primary care. The CDSS finds the most similar successful patients from the past to give treatment recommendations for a new patient. Using previous similar patients with successful outcomes to advise treatment moves management of MSK pain patients from one-size fits all recommendations to more individually tailored treatment. This study aimed to summarise the development and explore the acceptance and use of the CDSS for MSK pain patients.

METHODS

This qualitative study was carried out in the Norwegian physiotherapy primary healthcare sector between October and November 2020, ahead of a randomised controlled trial. We included four physiotherapists and three of their patients, in total 12 patients, with musculoskeletal pain in the neck, shoulder, back, hip, knee or complex pain. We conducted semi-structured telephone interviews with all participants. The interviews were analysed using the Framework Method.

RESULTS

Overall, both the physiotherapists and patients found the system acceptable and usable. Important findings from the analysis of the interviews were that the CDSS was valued as a preparatory and exploratory tool, facilitating the therapeutic relationship. However, the physiotherapists used the system mainly to support their previous and current practice rather than involving patients to a greater extent in decisions and learning from previous successful patients.

CONCLUSIONS

The CDSS was acceptable and usable to both the patients and physiotherapists. However, the system appeared not to considerably influence the physiotherapists' clinical reasoning and choice of treatment based on information from most similar successful patients. This could be due to a smaller than optimal number of previous patients in the CDSS or insufficient clinical implementation. Extensive training of physiotherapists should not be underestimated to build understanding and trust in CDSSs.

The effectiveness of a noninterruptive alert to increase prescription of take-home naloxone in emergency departments

OBJECTIVE

Opioid-related overdose (OD) deaths continue to increase. Take-home naloxone (THN), after treatment for an OD in an emergency department (ED), is a recommended but under-utilized practice. To promote THN prescription, we developed a noninterruptive decision support intervention that combined a detailed OD documentation template with a reminder to use the template that is automatically inserted into a provider's note by decision rules. We studied the impact of the combined intervention on THN prescribing in a longitudinal observational study.

METHODS

ED encounters involving an OD were reviewed before and after implementation of the reminder embedded in the physicians' note to use an advanced OD documentation template for changes in: (1) use of the template and (2) prescription of THN. Chi square tests and interrupted time series analyses were used to assess the impact. Usability and satisfaction were measured using the System Usability Scale (SUS) and the Net Promoter Score.

RESULTS

In 736 OD cases defined by International Classification of Disease version 10 diagnosis codes (247 prereminder and 489 postreminder), the documentation template was used in 0.0% and 21.3%, respectively (P < .0001). The sensitivity and specificity of the reminder for OD cases were 95.9% and 99.8%, respectively. Use of the documentation template led to twice the rate of prescribing of THN (25.7% vs 50.0%, P < .001). Of 19 providers responding to the survey, 74% of SUS responses were in the good-to-excellent range and 53% of providers were Net Promoters.

CONCLUSIONS

A noninterruptive decision support intervention was associated with higher THN prescribing in a pre-post study across a multiinstitution health system.