Population health analytics is a great boon to healthcare suppliers and distributors with the potential of driving their businesses forward.
The collection of patient data from different demographics improve the services provided to hospitals and distributors. Healthcare supply analytics benefits significantly from the data furnished by population health. It helps identify areas where specific products have great demand.
As a medical supplier, you need to forecast the healthcare demands on the horizon. Analysis of this data can help make the supply chain more efficient, reducing overhead expenses from stocking up on supplies that medical providers don’t need.
Global market size for healthcare analytics, which includes population health, will grow to around $40 billion by 2025. This developing demand in the healthcare industry makes it more crucial to increase your awareness about population health.
What Health Suppliers Should Know About Population Healthcare Supply Analytics
Value-based care is at the core of population health analytics. The benefits of correctly matching a patient to a health provider can be extended to medical suppliers – matching suppliers’ capabilities with the providers’ needs.
These five things can help you understand the impact of population health analytics on your business and the health industry:
1. What is Population Health Analytics?
Population health covers a broad area that’s not always well-defined. However, management and analysis of its data have a clear goal. It improves the health of the communities and specific groups of people, addressing medical problems on a large scale.
The information gained by providers from this type of health analytics can give medical suppliers an insight on how to match their customers’ needs.
Population health investigates the following fields:
- Health outcomes and distribution in a population
- Patterns of health determinants
- Policies and interventions at both individual and social levels
Widespread health problems such as heart disease and diabetes require population health data to help create effective health solutions.
Population health analytics seeks to bridge the gap between financial and clinical aspects of the health industry. Medical errors pose health risks to patients and have severe implications in other areas, such as psychological issues for healthcare professionals and financial losses for the health institutions. Data collected from various disciplines, including those gathered outside the health sector, goes through population health analysis.
As a result, analytics will help standardize clinical approaches, identify the right healthcare products to combat community-wide illnesses, and reduce cases of medical errors.
2. Analysis of Claims Data
Population health includes claims data, which are readily available and have a structured and standardized format. However, the data is retrospective consisting of a month or year-old information. Even so, it still helps providers to study patients based on their claims history.
Claims data help providers understand their patients better with information such as:
- Patient demographics
- Dates of service
- Diagnosis codes
- Cost of services
Analysis of claims data helps healthcare professionals learn any major health issues their patients face and how they usually pay for their treatments.
While not complete in and of itself, claims data provides an excellent starting point for healthcare analytics.
3. Importance of Electronic Health Record Data
Electronic Health Record data, also known as EHR, fills the gap that claims data cannot provide. A vast majority of hospitals focus on implementing EHR in their infrastructure. It allows for a better understanding of patient-oriented information such as vital signs, medications, allergies, lab data and imaging, and immunization dates.
EHRs can go deeper into detail, giving information such as provider impressions of their patients, records of patients’ concerns about misdiagnoses, and care processes patients received.
The availability of EHR datasets can help healthcare providers learn specific population health information, including:
- Patients with high blood pressure readings that are at high-risk levels
- Number of patients taking multiple medications which could have contraindications
- Number of pediatric patients who did not receive the recommended dosages because of missed immunization appointments
However, the plethora of data that EHRs provide is also the source of its downside. Analysis requires additional workflows to make the data structured. Some of its fields contain static PDF files, imaging reports, and lab results. These data need further processing before going through analysis.
Since data entry can be overly complex, some users end up taking shortcuts. They could leave default values in place or copy old data and paste them for each new visit.
Fortunately, EHR continues to undergo optimization. A large segment of the healthcare industry is redesigning EHR to accommodate current global challenges as well.
4. Value of Socioeconomic Data
Socioeconomic status can impact a patient’s experience on the healthcare they receive, such as the waiting time and quality of doctor care. Population health analytics can help in addressing every patient’s holistic needs using socioeconomic data. Environmental, community, and social data are vital in telling the whole story behind a patient’s condition.
Further analysis of specific groupings organized by location, ethnicity, and age are possible using socioeconomic datasets, such as:
- Local healthy food choices
- Average income
- English proficiency
- Transportation access
- Education levels
Health management programs immensely benefit from socioeconomic data, giving them information on addressing specific groups’ health needs.
5. Challenges Addressed by Population Health Analytics
Population health analytics aids healthcare professionals in taking proactive measures when providing treatment. For instance, the results of data analysis can give a prediction on the possibility of acute kidney failure in hospitalized patients.
Some of the challenges that population health analytics address are:
- Increased healthcare costs
- Inaccurate patient data
- Inability to recognize developing health threats
The analysis can also identify what types of medication are in high demand for a specific group. It can help point out ineffective prescriptions that are soon to be obsolete.
Information such as these is crucial to medical suppliers, allowing you to focus more on providing healthcare solutions that your customers currently need. You can also have a better forecast as to which products will be in high demand in the future.
Population Health Analytics Improves Healthcare Supply Business
These five lessons from population health analytics can help you improve specific business processes. You can strategically tailor your approach, significantly reducing risks from investing in products that won’t sell.
Share Moving Media provides webinars and training to help healthcare manufacturers and distributors address their clients’ needs. Contact us for more strategies on how to boost your business effectively.