Described as ‘a set of processes and technology that enable
organizations to analyze and manage populations, engage patients in
their care, coordinate benefits and services, and ultimately,
improve the health of a defined group,’ PHM aims to improve the
health of an entire population through better management of
population data to improve clinical care, improve the quality of
life and prevent illness. It seeks to achieve the quadruple aim:
improved patient care (better healthcare); improved population
health (higher quality of life and better health); and lowered costs
of caring for patients and whole populations. Through analyzing
complex datasets from multiple sources, including EHR and patient
survey data, combined with social determinants of health such as
economic status, education, and social environment, PHM seeks to
identify at-risk populations, implement preventative measures, and
tailor treatments accordingly. In modern healthcare, PHM is critical
in advancing proactive, personalized care and moving away from
reactive care. It helps address the deficiency of treating only the
immediate illness while enabling healthcare practitioners to address
the wider determinants of health to benefit patients.
Custom
software solutions can be tailored to fit individual and
organizational needs and requirements exactly. This adaptability,
which off-the-shelf software does not offer, grants the flexibility
to have software that integrates into existing systems, currently
stores data the way that fits the organization’s data management
needs, and performs the specific functionalities that a company
needs for its work, including analytics and care-coordination
purposes. As a technology, the use of custom solutions is
particularly relevant to PHM because it allows developers to create
forward-looking software designed to face the challenges of the
industry – challenges such as interoperability, efficient management
of workflows, and the ability to tailor patient engagement to each
individual. A software system developed to closely match the
requirements of PHM provides healthcare professionals with the tools
to manage population health better to achieve optimal outcomes.
PHM encompasses four key components that enhance health outcomes for
populations: data collection and analysis, risk stratification and
segmentation, care coordination, and patient engagement. Data
collection and analysis involves collecting and analyzing various
sources of information for health risk identification and population
health trends – including EHRs, patient surveys, and public health
data. Risk stratification and segmentation help providers and payers
categorize individuals according to their health risks and needs –
for example, stratifying a population by the risk of developing
chronic disease, assessing health literacy and necessary support to
manage the disease, as well as identifying high-need, high-cost
patients for whom targeted interventions could reduce costs. Care
coordination involves optimizing care across different services and
providers within one healthcare system. Patient engagement entails
involving patients in their own care and providing them with
education, self-management tools, and communication channels that
can facilitate better adherence to treatment plans and health
behaviors.
While PHM can be highly beneficial, it has many
challenges on the horizon. One big hurdle is data – data
integration, or the combination and interoperability of information
from inside and outside the healthcare ecosystem, and data
integration, or unifying gathered data in one interoperable system –
remain enormous technical challenges. Another big challenge is that
social determinants of health, which are socioeconomic conditions
and environmental factors that impact health, must also be included
in the optimal care equation. Patient compliance and engagement is
another notable challenge: if patients don’t have good access to
healthcare if they’re not health literate (i.e., they can’t
understand medical information), or if they don’t want to be, this
can complicate and perhaps impede the process and goals of PHM.
These challenges will need to be addressed through solid strategies,
such as using the best technologies to make and analyze the data,
building bridges amongst the various sectors in healthcare (i.e.,
‘upstream’ communities, academic or research groups, and government
institutions and organizations), and developing targeted
interventions integrating medical and social need.
Custom software is well-suited for population health management (PHM) because it allows for highly tailored solutions for specific care-delivery environments, including hospitals, clinics, and public health agencies. Each environment has specific operational requirements and patient care goals that mandate a high degree of customization in the software. Whereas in a hospital, we might need advanced integration capabilities (with a large number of services and data sources), high-speed data analysis capabilities (to analyze and follow patients in real-time), and readmission modeling tools to effectively manage patient care after discharge, we might need something more suited to the preventive needs of a clinic (such as a multi-functional patient management tool) or the data needs of a public health agency (risk factors assessments and reporting dashboards that can best track and evaluate large population’s health)—using data visualization tools for real-time monitoring of multiple metrics to meet the needs of different stakeholders in the clinic.
Secondly, custom software enables better data management and analytics in PHM by providing enhanced ability to handle the large volume of health data, especially those requiring advanced processing capabilities, and to derive actionable insights from it. This can be done through advanced data analytics solutions, which allow healthcare providers more sophisticated risk stratification solutions, for instance, by finding high-risk populations and even predicting health outcomes based on historical and real-time data. Data integration with other sources such as Electronic Health Records (EHRs) can also provide a more holistic view of patient health than relying on symptoms alone, aiding healthcare providers in making better clinical decisions and developing more personalised care plans. Custom software can also assist in streamlining data integration processes between other systems and can help ensure that data flows seamlessly among systems, reducing the risk of data fragmentation. Overall, better data management from custom software will likely facilitate more accurate health assessments and health outcomes, where appropriate interventions can be targeted for specific high-risk populations.
Promoting these actions is a crucial factor for successful PHM, and custom software can be a useful tool for improving care coordination. For example, shared patient records, secure messaging systems between care providers, and collaborative care planning platforms allow care teams to communicate seamlessly and coordinate their efforts more cohesively. In more general terms, customizing workflow management and task automation tools in software solutions could enable integrating those features. This digital solution can help healthcare practitioners effectively and efficiently address the administrative demands of care coordination by reducing manual workloads and error rates. In other words, by automating simple administrative requests, custom software enables practitioners to directly tackle the main goal of care coordination, which is patient care rather than administrative tasks.
Starting from a set of high-level requirements, the development of custom software for PHM is a process that iteratively delineates more and more specific requirements, requirements, and then more requirements until the development team has incorporated and documented as much functionality as is feasible. This process requires first identifying the overarching problems and potential for improved performance in an organization’s population health management approach. Engaging with human resources staff, physicians, mental health and physical health personnel, administrators, and IT staff allows these stakeholders to help define the requirements and consider the needs of each group in terms of how the solution will function. Defining specific goals and success metrics is central to building custom software. These metrics will serve as the ‘benchmarks’ (baselines) for how and when the software is applied once in active use – the non-hypothetical clinical setting. Aligning those goals with the organization’s strategic aims and immediate operational needs will provide meaning to the custom-developed solution.
With these requirements identified, design and implementation can commence with an approach that favors agile development – that is, where a software system is built in piecemeal form and iterated upon as new features are added and tested based on feedback from humans using the system until it provides sufficient functionality to be deployed and garner further feedback. Adaptability during such development is key, giving way to changes in the requirements identified, which in a healthcare context can be unpredictable and difficult to identify at the outset (with ‘bootstrap’ or limited resources). Overall, scalability and flexible functionality are important design aspects because PHM solutions must account for future scale and expansion in healthcare needs, requiring the software to accommodate new data capture technologies and handle increased data volumes over time.
It is crucial to test custom PHM software to make sure that it meets certain standards of performance and reliability, such that when feedback or findings are reported – and actions directed – they are complete and accurate and not due to any technical issues. This is important for user testing and user feedback. However, good medical decision-making also requires that physicians and other frontline medical personnel who use and interpret these findings be well-trained to manage their use of the findings to be of the greatest benefit to their patients and their patient’s families. In this sense, the utilization of good custom PHM software is a public good and very important to the improved function of our society. However, if the PHM software is poor or flawed, this can lead to poor quality of care, skyrocketing costs, and an impaired population of citizens and citizens’ families. It is also the responsibility of users to give timely and adequate feedback so that additional quality assurance efforts can continue for the duration of the software’s lifecycle. Security and compliance considerations are also important; after all, we are dealing with health information or, in a nutshell, medical information.
PHM software of the future is going to be changed by emerging technologies and innovation; Artificial Intelligence (AI) with machine learning allows for more accurate predictions in risk assessments, optimizing health outcomes by analyzing massive data sets and identifying clusters of risk that might not otherwise be uncovered manually. Connecting wearable technology or remote monitoring devices to patients’ homes allows for continuous patient health monitoring while people still go about their day, providing more real-time data. Combining this with telemedicine, nurses or doctors can proactively call patients and check in to see how they are doing. PHM is moving towards more prevention-oriented care where providers can react quickly to patient health changes over days and weeks.
The rise of emerging infectious diseases, along with the aging of populations and the explosion in both the numbers of and care that is needed for people with chronic conditions, will present opportunities for the pursuit, differentiation, and novel approaches by health-related companies and new adaptations by health systems and patients. PHM software will likewise be subject to evolution. It should incorporate new data sources and functions as they evolve and become relevant. It should also anticipate and adapt to changes in regulatory and other policies that are likely to emerge. PHM software that includes ‘flexible, forward-looking features’ will be critical to keeping ahead of the curve. In doing so, PHM software can be instrumental in ensuring that the same companies drive innovation, that the same organizations differentiate, and that the same patients transition into new care ecosystems where they can receive effective, high-quality care.
To conclude, Population Health Management (PHM) can be significantly boosted by custom software solutions that prioritize individual private needs, organization requirements, systems, user access, and specific areas for improvement. A strategic approach toward developing such software components should also be made with clear requirements, adjustable solutions, and technologies that can support functionality using relevant data, dynamic information, and mobile capabilities. This way, healthcare facilities can move into a more evolved and complex environment that challenges today’s society and the healthcare domain as a whole by innovating and adapting to the developments of patient needs, data access, and care provision. Custom solutions in PHM software thus become an important area of assisting healthcare in handling their tasks and needs by managing patient groups or populations to reach their objectives and provide the best possible care in real-time and across various healthcare settings.