APPENDIX E:
Guidance on Technological Interventions
EHRs were primarily designed to manage individual patients rather than groups of patients. However, over time, EHRs have increasingly added functionality for population-level quality reporting and management, and for some degree of care planning and care coordination, especially to support value-based care tracking and reporting. Practices should evaluate your EHR capabilities against specifically designed population management applications. While these applications require interface with the EHR, they generally offer additional functionality. While EHR solutions are integrated with EHR data, they still usually require import of data from outside sources to be optimally useful. Managed care organizations may provide care coordination and population management applications, usually only for their own enrolled patients. EHR-based solutions may also pose challenges where groups of practices using different EHR solutions are collaborating in value-based care contracts.
In value-based care arrangements, practices are responsible for attributed patients who may have never been seen. Since these patients do not have records in the EHR, practices need to consider how they can manage these patients to engage them into care at the practice in the absence, at least initially, of the patients having records within the EHR. If your practice is using freestanding applications for this, it needs the capacity to handle these attributed patients who have not been registered as patients.
Figure 25 below includes the technical functionalities required to support population management for adults with chronic conditions. These requirements can guide the evaluation of existing solutions or guide the development of requirements in evaluating potential new applications. The figure also indicates the data sources required to enable the functionality.
FIGURE 25: CORE POPULATION HEALTH MANAGEMENT FUNCTIONALITY REQUIREMENT
Functionality |
Population Health Management Requirement Description |
Data Acquisition Dependency |
---|---|---|
Care guidelines |
Identify care gaps for all adults with chronic conditions against care protocol. Care guidelines may be presentable to the clinical provider/support team at the point of care through the EHR, in the visit workflow as pre-visit prep/team huddle, through registries as above, and aspirationally as prompts to patients/caregivers. |
Commercial EHR-embedded guidelines provided by vendor or customized by practice. External source guidelines (clinical guidelines). Reference sites made available electronically. |
Registries |
Identify care gaps for all adults with chronic conditions against care protocol. Care guidelines may be presentable to the clinical provider/support team at the point of care through the EHR, in the visit workflow as pre-visit prep/team huddle, through registries as above, and aspirationally as prompts to patients/caregivers. Ability to produce registries (list/cohort of patients) organized to facilitate population management: Adults in age ranges relevant to measures and/or clinical standards. Adults sharing designated high-risk criteria (medical, behavioral, social needs) impacting their ability to achieve guidelines. These registries should consider the inclusion of functionality to trigger automated, predefined action(s) and/or human-initiated action(s) for all or a defined subset of patients comprising the registry. Suggested HIT assets that can be leveraged to achieve this function include: EHR – generates a list of patients who meet the criteria for inclusion in the population of focus. Track using an external database. Consider merging patients from an external data source, such as a payor, to have a complete roster. Population health management tool – specialized chronic disease management applications (some of which include patient-facing components). |
EHR:
External data sources, such as: reference labs, specialty care, immunization registries, social service clinicians’ data. Data from home devices such a glucometers and home blood pressure monitoring devices.
|
Clinical decision support (CDS) |
Care gaps should be displayed based on what is due, with insight into previous results, to support clinicians’ ability to make decisions at the point of care (POC) for the provider and care team members supporting non-POC management. Care guidelines may be presentable as clinical decision support to the clinical provider/support team at the point of care, in the visit workflow as pre-visit prep/team huddle, through registries as above, and aspirationally as prompts to patients/caregivers. While EHR-based prompts are usually thought of as ideal, team-based care presents an opportunity for clinical decision support to be presented to other members of the care team through other channels. The Five Rights Framework Clinical Decision Support: More Than Just ‘Alerts’ Tipsheet is a useful guidance to help health centers to support decision-making across a wider range of the care delivery life cycle, broader teams and technology other than the EHR to look beyond office visits and providers. This is especially important to avoid “alert fatigue” and burnout. |
Internal EHR data. External source clinical data. Claims data (clinical lag should be noted). Electronic guideline specifications. Patient-contributed data. |
Care dashboards and reports |
Adults with chronic conditions dashboard: population view by eligible study with sorting/filtering capability based on characteristics to be defined by the practice, with ability for care team/case managers to document the actions completed; ability to see care gaps at a patient level and population level according to health center-prioritized care guidelines. Note that to automate these reports, it is necessary to apply standardized data collection strategies against electronically specified protocols. |
Same as above (EHR data and external data sources. Data from other sources of care). Claims data. |
Quality reports |
Same as above by quality measures, as opposed to care guidelines; ability to track HEDIS as well as customized measures and UDS. |
Quality measure specifications. Same as above (EHR data and external data sources). Data from other sources of care. Claims data. |
Risk stratification |
Ability to categorize risk for patients and develop lists according to risk classification (tie to registry). Can be imported as externally generated risk score or calculated internally according to proprietary or customized risk algorithm. |
Data acquisition platform ingestion: already curated high-risk list ingested and utilized downstream in the journey and/or additional internal and external data sources to populate defined risk model. |
Outreach and engagement |
Allow for outreach to support previsit planning or post-visit care needs, such as assessments. Technology channels include population registry outputs; patient-facing applications, such as patient portals; freestanding text messaging; and self-assessment/self-management applications.
|
Same as above (clinical/EHR/etc.) Claims.
|
Care management |
Allow for management of specific and unique care needs for high-risk patients. Care management requires the ability for multiple members of the care team to contribute to and rack elements of the plan. Challenges with freestanding care management applications include access to data from other sources of care, including the ability to track referrals, and workflow burden of staff utilizing multiple applications. Ability of the care management application to draw from and “write back” to the EHR is desirable but difficult to achieve.
|
Care management protocols. Appointment data: internal/external. Clinical data from external service providers.
|
FIGURE 26: USE OF TECHNOLOGY FOR RECOMMENDED SCREENING FOR FOUNDATIONAL KEY ACTIVITIES
This figure identifies strategies for using digital tools to complete appropriate screeners as recommended by clinical guidelines. Using technology to facilitate screening may streamline the workflow and preserve patient confidentiality where necessary.
ID |
Focus Area |
Completion of Digital Screeners |
Data Acquisition Dependency |
---|---|---|---|
1 |
Depression screening |
In-office tablet-based screening and/ or remote patient-facing application-based self-completed screening.
|
Population health and EHR integration of screener responses or, at minimum, scores. |
2 |
Anxiety screening |
In-office tablet-based screening and/ or remote patient-facing application-based self-completed screening.
|
Population health and EHR integration of screener responses or, at minimum, scores. |
3 |
Unhealthy substance use screening |
In-office tablet-based screening and/ or remote patient-facing application-based self-completed screening.
|
Population health and EHR integration of screener responses or, at minimum, scores. |
4 |
Social needs screening |
In-office tablet-based screening and/ or remote patient-facing application-based self-completed screening.
|
Population health and EHR integration of screener responses or, at minimum, scores. |
FIGURE 27: USE OF TECHNOLOGY FOR PATIENT OUTREACH AND PVP FOR FOUNDATIONAL KEY ACTIVITIES
This figure outlines the use of technology to facilitate specific activities and potential technology solutions that can optimize the uptake and efficiency of in-office visits.
ID |
Technology Focus |
Patient Outreach and Pre-Visit Planning |
Data Acquisition Dependency |
---|---|---|---|
1 |
Portal-based communication |
|
EHR interface and integration. |
2 |
AI-enabled chatbots |
Identifying issues that need to be addressed before an office visit can be converted to telehealth visits. |
Population health and EHR incorporation of screening scores and responses. |
3 |
Text messaging |
Appointment reminders. |
EHR interface and integration. |
FIGURE 28: USE OF TECHNOLOGY FOR ENHANCED PATIENT ENGAGEMENT AND VIRTUAL CARE FOR GOING DEEPER ACTIVITIES
The figure identifies technology solutions to engage patients asynchronously from office visits for a variety of use cases to enhance care and patient experience.
ID |
Focus Area |
Patient Engagement and Mobile Technology |
Data Acquisition Dependency |
---|---|---|---|
1 |
AI-enabled chatbots |
|
EHR integration. |
2 |
|
EHR and population health integration. |
FIGURE 29: USE OF TECHNOLOGY FOR INNOVATIONS IN CARE DELIVERY FOR ON THE HORIZON ACTIVITIES
The figure describes technology strategies that can enhance care delivery by using artificial intelligence and advanced technology tools.
ID |
Focus Area |
Artificial Intelligence and Innovation |
Data Acquisition Dependency |
---|---|---|---|
1 |
Predictive analytics |
|
EHR integration, population health, and patient engagement application integration. |
2 |
Artificial intelligence (AI)- enabled diagnostics |
|
EHR integration and population health integration. |