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By capturing the morbidity burden of populations, the Johns Hopkins ACG System helps explain and predict how health care resources are delivered and consumed. Some common applications include:
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
WHITE PAPER: Can populations be risk stratified using only EHR data?
CASE STUDY: Data visualization and patient identification in a military setting.
CASE STUDY: Population health management through care coordination and interventions.
Once targeted programs are identified and implemented, the ACG System can help determine their success—including patient characteristics associated with successful programs’ outcomes, changes needed, program continuation or termination. These analyses also quantify improvements related to specific interventions, which demonstrates program value to external parties.
With the ACG System you can identify up to 25% more individuals for care management before they become high utilizers. Optimize your case management and disease management programs by targeting individuals, assessing patient risk, and identifying those who would benefit the most.
CASE STUDY: Use an adapted taxonomy, combined with ACG System output, to expand care management programs for high-risk Medicare patients.
CASE STUDY: Identify high-risk patients for care management program and reduce lengths of stay and readmissions.
CASE STUDY: Improve health care resource allocation and better describe the disease profile of a population.
Coordination exerts an important impact on both the efficiency and effectiveness of care. Patients most in need of highly coordinated care include those with multiple chronic medical conditions, concurrent care from several health professionals or many medications, and patients undergoing extensive diagnostic workups or transitions from one setting of care to another.
The ACG System Utilization Profile Report includes many concepts to evaluate population health, including concurrent and prospective risk, risk factors, utilization, disease prevalence, pharmacy adherence, and care coordination risk.
CASE STUDY: Identify high-risk patients for care management program and reduce lengths of stay and readmissions.
CASE STUDY: Population health management through care coordination and interventions.
The ACG System performance analysis takes into account the health of the particular population served by a specific clinician or set of clinicians, addressing important differences in case mix and the often stated concern that “my patients are sicker.” Because a disease-based focus may miss important implications of related co-morbidities, we provide a holistic view of the patient rather than the management of specific diseases or episodes.
The ACG System helps several health plans tackle various issues by understanding their population. Patricia M. Brown, Esq., President, Johns Hopkins Healthcare, highlights this application in a video captured at the ACG System 2016 AcademyHealth Health Services Research (HSR) Award celebration.
CASE STUDY: Case Mix Adjustment to Analyze Practice Characteristics.
CASE STUDY: Provider Profiling and Engagement.
The ACG System is widely used by health plans and health systems for risk adjustment, setting capitation rates, insurance premiums and for appropriately distributing health care resources within large health systems. The ACG System helps health care providers, payers, and governments worldwide ensure that resources appropriately target populations in greatest need.
CASE STUDY: Customize the ACG System to support risk ajusted resource allocation in primary care.
Prescription drug claims are processed at the point of service and prescribing events often occur with more frequency than physician events, providing more timely and frequent information. Three months of pharmacy claims can often be available immediately at the end of this period whereas medical claims from this same three-month-period may not be available for another three months.
The ACG System is the most widely used population-based case mix system in the world. Currently used in close to 30 countries, the System incorporates local cost structures, coding systems, practice behavior, languages and local markers for socio-economic, functionality, living arrangement, or other dimensions. Some international application examples are available by clicking on a specific country.
Chad Abrams, Director of U.S. Operations, describes common challenges around the world such as language differences, data quality, turning data into impact, and misconceptions of local population health, and the ACG System’s ability to turn them into successes.
The ACG System is unique in its ability to account for differences in local cost data, practice behavior, additional available data inputs (i.e. socio-economic status, functionality, or living arrangement measures) and other variables that distinguish a given population. In addition, all menus and labels within the program can be easily translated to other languages.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
Diagnosis Codes
The ACG System is the only case mix system in the world which accepts and integrates International Classification of Primary Care (ICPC) diagnostic codes as an input stream. No mapping of ICPC to ICD codes is needed. In addition, the ACG System works with ICD and Read codes.
Pharmaceutical Codes
The ACG System includes a case mix algorithm which relies solely on pharmaceutical codes to group patients into morbidity categories. Pharmacy information using U.S. National Drug Code (NDC), WHO Anatomical Therapeutic Chemical (ATC) as well as Read codes or from the British National Formulary (BNF) has proven beneficial in situations where diagnosis codes are untimely, of questionable quality or incomplete. Using pharmaceutical information is also helpful to identify potential gaps in data, as well as identify clinicians who may be over prescribing. Click here to read about ACG Rx Gaps.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
All pharmacy codes (NDC, ATC or other national codes) can be classified according to these clinical criteria. An active ingredient count is also made available.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
For a handful of carefully selected chronic conditions where administration of medications is warranted, and where specific medications that should be taken continuously can be identified, the ACG System provides indicators if a patient is receiving treatment and calculates potential gaps in availability of needed medications.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
Identifying Patients for Disease Management and Wellness Programs
The ACG System can help identify patients for disease management programs and for wellness programs. The ACG System Expanded Diagnosis Clusters (EDCs) methodology assigns diagnosis codes found in electronic claims or encounter data to one of 286 categories, which enables you to select a specific disease or condition to focus on.
Evaluating Disease Management and Wellness Programs
The ACG System can also be used to evaluate the effectiveness of disease management or wellness programs.The ACG System can segment the population by level of multi-morbidity, enabling you to examine the results of your disease management programs and wellness programs while accounting for co-occurring diseases.
Disease Management Program Enrollment Goal
In the population represented in Figure 1, the health plan has a goal to enroll 2,000 members in their asthma disease management program each year.
Measure of Program Success and Health Improvement
One of the key indicators for the population is an improvement in the rate of members dispensed a preferred asthma therapy (a higher overall rate is the desired result.)
Over time, the dispensing rate for these therapies is decreasing and is leading management to wrongly conclude that the disease management program is not achieving its goal. However, the results are different if you look at the results by multi-morbidity level.
Modify Program to Exclude Highly Co-morbid Members
Suppose the health plan changed the criteria for acceptance into the asthma disease management program so that highly co-morbid members are excluded. These are patients with, on average, 6 or more chronic conditions.
When you analyze the results by co-morbidity level as in Figure 2, you see that there were modest improvements for each morbidity group in year 2 except in the very high morbidity group where there were no members enrolled in year 2.
Members with lower co-morbidity showed an increase in using the preferred asthma therapy. This demonstrated that the asthma disease management program achieved greater success with individuals with lower co-morbidity. Case mix control using the ACG System is a critical component of evaluating program effectiveness and ROI.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
The ACG System helps you target those individuals who might benefit from case management programs. You can perform a quick assessment of an entire health care population or sub-group to identify patients at risk who may not already be identified through other programs. Then you can drill down to patient-specific information to understand an individual patient’s risk factors and resource needs.
NOTE: Patients who would typically already be in a case management program due to their diagnosis, such as cancer patients, are excluded from the report.
While this patient’s current utilization pattern and medical costs may not indicate a need for case management, the significant potential increase in cost indicate that case management interventions may be a cost-effective way to improve care.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
The ACG System helps you allocate health resources in a way that adjusts for morbidity and considers more than age, gender and geography. By incorporating patient clinical characteristics the ACG System improves health care resource allocation by accounting for individuals’ expected medical needs. This ensures an equitable distribution of limited health care resources directing them to those populations who need them most.
The complexity (case mix) of people in different populations varies. This information can be used to allocate resources in an equitable way based on the overall morbidity burden of people in a population. The ACG System will automatically assign a six-level (“low” to “very high”) simplified morbidity category termed a Resource Utilization Band, or RUB. The RUBs are formed by collapsing the ACG mutually exclusive cells that measure overall morbidity burden into six distinct groups.
The following graph illustrates the variation in case mix that occurs across GP Practices (primary care provider organizations) in a UK city, with the practices on the right having up to twice as many patients in the “high” and “very high” RUBs as those on the left:
In this second example, the analysis only includes patients who have diabetes and illustrates that the case mix variation is even greater. The funding organization has used this information to allocate diabetes resources based on the percentage of patients in the “high” and “very high” RUBs rather than the historical approach of dividing the resource equally across all practices:
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
CASE STUDY: Identify factors driving costs in a patient population and implement complex case management service.
CASE STUDY: Improve health care resource allocation and better describe the disease profile of population.
The ACG System risk adjustment methodology is simple and straightforward and provides a relative population risk index that can be used to adjust capitation rates. It has long been a standard actuarial method for capitation and rate setting. ACG actuarial cells, classify individuals by expected use of health care resources. Covered populations are sorted into these 102 ACG actuarial cells and either national weights or localized weights are applied.
For more than a decade, the ACG System has been used to facilitate the exchange of many billions of dollars within numerous private and public health plans in the United States, Canada and Sweden.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
The ACG System’s rating methodology for setting health care premiums goes beyond demographics and considers individual health. You can set premiums at a fair level that provides more accurate and credible predictions of health care utilization. With more competitive renewal rates you will achieve improved customer retention.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
Health Care Finance Reform
In 2009, a sweeping overhaul of health care financing implemented a morbidity-based risk adjustment method for transferring funds within the German health care system. This brought to the forefront the need for health care organizations, academic institutions, and government decision makers to understand the variation in disease burden amongst their population.
Subsequently, two German sickness funds licensed the ACG System to aid with population comparisons, cost projections, identification of potential high-cost members, and cost controlling. Cost controlling is achieved by establishing profiles of member groups, tracking changes in costs over time, and controlling budgets.
The sickness funds are also applying the ACG System in innovative ways to manage patients with psychosocial disease clusters in order to avoid expensive inpatient care. They are also exploring a similar approach for other disease clusters such as diabetes and hypertension.
Custom Code Sets for Germany
To better meet the needs of the sickness funds, the ACG System Team created new code sets based on the German adaptation of ICD-10 codes, as well as two new Risk Assessment Variable Sets (RAVS) that are based on the sickness fund’s own data.
The ACG System provided a more comprehensive assessment of morbidity and resource use at the patient level.
Read more about our Collaborator in Germany Lohman & Birkner
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
For almost a decade the ACG System Team has collaborated with Israel’s largest health fund to better understand its members’ needs and characteristics. This not-for-profit government-mandated insurer and health care provider (of primary, secondary and tertiary care) has more than 4 million enrollees and covers 53% of the population.
Examining Differences in Health Care Utilization
The ACG System was instrumental in proving that age and gender adjustments yield an inaccurate positive association between low socioeconomic class and diagnostic tests as well as specialty care use. Moreover, the results demonstrated the superiority of the ACG System in comparison with the Charlson Index in measuring this correlation. The study was part of this health fund’s all-encompassing disparity reduction program and helped direct policy decisions regarding resource use.
Identifying Opportunities for Quality Improvement
Another study conducted as part of this research collaboration examined the association between co-morbidity, as measured by the ACG System, and quality of care. The study showed that, process measures rather than outcome measures were associated with morbidity level and provided a valuable tool for identifying patient groups for which quality of care could be improved.
Identifying High-Risk Users
The ACG System has also been used in Israel to identify high-risk users who could benefit from targeted care management interventions. This method was more accurate than locally developed data-mining tools. The ACG System Team is working with this same health fund to examine the incorporation of information from this health fund’s extensive database (including a comprehensive chronic disease registry, full EMR coverage in all community clinics, and data on social support and functional status); to improve the predictive capabilities of high-risk case identification tools; and test the use of continuity of care tools.
To read a case study of the ACG System’s use in a comprehensive complex care management program for an integrated delivery system in Israel, click here.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
Veneto, a northern Italian region, uses the ACG System to perform detailed assessments of its population’s morbidity burden and identify future health care needs based on patient data. During the first year of the project Local Health Units including the Italian cities of Verona and Padua participated. The following year, the project expanded to four additional Local Health Units: Feltre, Alto Vicentino, Vicenza and Treviso. In its third year, the project involves all Local Health Units across the Veneto Region.
The Veneto Region project demonstrates the ACG System’s underlying principle that diseases and their distribution are the main determinants of the population’s health care needs.
Insights from Inpatient and Outpatient Data
The ACG System detects disease patterns in patients by not solely utilizing inpatient data, but also by focusing on patients who receive most of their care outside the hospital setting. The ACG System’s first application in Italy validates the Veneto Regional Health Service’s focus on innovation, quality and sustainable methods to ensure the best care is provided to its citizens.
Geographic Disease Concentration
Utilizing existing data from the Local Health Units, the ACG System examines the population’s morbidity burden in order to improve health outcomes, provide more appropriate care, and more equitably allocate health care resources based on need. At its core, the ACG System identifies greater and lower disease concentration levels in different geographical areas. A map will show the “safe areas” and the “hot areas” (those with higher risk patients). Each group is measured by their illness level—single or multiple—and because their health needs and risks have been properly identified, patients can receive better, more targeted health services.
Identifying Patients for Case Management Programs
After identifying patients with complex care needs, the ACG System identifies individuals who would benefit from specialized case management programs, such as Guided Care®, an innovative patient-centered care model that integrates the general practitioner, local nurses, and the patient’s family to improve care coordination and health outcomes.
Learn more about this project at the Veneto Region website.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
“We believe the ACG System provides us with a valid, relevant and meaningful measure of the population’s health status. With its assistance we can ensure equitable funding and distribution of health resources, accurate evaluations of the quality of care patients receive and fair assessments of the professionals who serve them.”
Gabriel Mª Inclán Iribar
Minister of Health; Basque Region
Provider Performance Assessment
Together with our local collaborator, Iasist, the ACG System Team has been working with several regional governments in Spain since 2005 to provide the tools necessary to assess primary care doctors’ performance. The ACG® System allows primary care managers to compare performance results from one primary care setting to another, and use this information to determine where practice improvements are needed.
Meeting the Needs of Integrated Care
The ACG System has already been adopted as the primary care case mix tool by three regional governments in Spain, while several other regional authorities are currently piloting the system. In the face of the growing interest for integrated care in Spain, there is increased need for other ACG System applications, such as the assessment of the morbidity risk of individual patients to determine resource allocation to different areas and help with risk-stratifying strategies. The ACG System’s predictive models are also being considered for their ability to identify individuals that could benefit from case management strategies.
Read more about our Collaborator in Spain lasist
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
Historically in Sweden, allocation of funds for health care resources was based on diagnostic codes at the hospital level, and on age and gender at the primary care level. After Sweden passed legislation allowing patients to choose their primary care provider, the Freedom of Choice Act, a model that accounted for the variance in morbidity was needed.
Risk-Adjusted Resource Allocation
When Sweden tested the ACG System for risk-adjusted resource allocation, it was able to explain over 60% of the variance in concurrent patient costs. The ACG System is now used for over 95% of the Swedish population and has been customized to the Swedish health care system. The ACG system has been adapted to recognize Swedish ICD10 codes and incorporates standard Swedish weights. County councils are currently running the Swedish ACG System model based on the latest patient data and 15 months of historical diagnosis data.
Incorporating Pharmacy Data
In addition, the ACG System furthered its success in Sweden by partnering with a health care government agency. With access to its national drug register database, the ACG System Team was able to test the pharmacy based predictive model’s (Rx-PM) validity as a risk adjustment tool in the Swedish context. The year-long study, conducted on a database capturing the entire Swedish population, showed that the Rx-PM model not only works very well for Swedish pharmaceutical data, but it could potentially be applied to assess performance.
Read more about our Collaborator in Sweden Ensolution.
CASE STUDY: Customize the ACG System to support risk ajusted resource allocation in primary care.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
Performance Assessment
At the beginning of the 21st century, the government of a western Canadian province started holding physicians accountable for their overall billing patterns, with the annual reporting of each physician’s practice profile. This allowed physicians to compare their practice patterns with others, but it also provided the government with a guide to detect outliers suspected of fraud and abuse. In addition, it increased the need to use risk adjustment tools to ensure that physicians were being evaluated fairly.
Detecting Fraud, Waste and Abuse
Prior to the introduction of the ACG System, audit results showed that, in 3 out of 4 cases, high health care expenses were justified by a sicker patient pool. After the ACG System was extensively evaluated in this particular Canadian province, it became accepted as the gold standard case mix adjustment method for physician profiling. Subsequent audit results enabling more targeted evaluation then showed that unjustified health care expenses were actually confirmed in 3 out of 4 cases identified. The ACG System continues to be successfully used for physician profiling and the detection of fraud and abuse in this province.
The ACG System has been widely adopted in Canada and is currently being used in hundreds of projects across the country.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
Amy Salls, Director of Population Health Strategy at DST Health Solutions, provides a summary on the applications of the ACG System in the United States.
WHITE PAPER: Can populations be risk stratified using only EHR data?
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
US Medicaid
In the United States the ACG System is used by various Medicaid health plans and state governments to improve health outcomes for underserved populations. The ACG System provides insight into health care utilization and health care resources allocation.
East Baltimore: Managing High Risk Populations. Linda Dunbar, Vice President of Population Health Care
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
On February 20th, 2015, the Centers for Medicare & Medicaid Services (CMS) announced the use of the ACG System Pharmacy Defined Morbidity Groups™ (Rx-MGs™) methodology as a means to assess coding intensity. For detailed information read the entire CMS 2016 Draft Call Letter: February 20, 2015.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
It is recommended that consultants knowledgeable in the use and application of the ACG System assist with proper software implementation.
Amy Salls, 866-287-9243, is DST Health Solution’s contact regarding ACG-HIE and can answer questions about the software and obtaining a license.
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The ACG System provides a measure of patient sharing, termed “Care Density Score” based on this research. This patient-level measure indicates how much of the care of that patient is shared among clinicians.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
Patients with poorly coordinated care have worse clinical outcomes and higher medical expenses than those with coordinated care. The ACG System developed Coordination Markers to identify populations at risk for poorly coordinated care.
A coordination risk measure combines these markers to determine whether a person has a “likely,” “possible,” or “unlikely” coordination issue. A care density ratio quantifies patient sharing based on outpatient face-to-face visits with eligible physicians.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
Sollis has been delivering business intelligence and health care analytics solutions to the UK National Health Service (NHS) for 20 years.
We have a long and established relationship with the Johns Hopkins University where we have successfully integrated the ACG® System into our health care business intelligence software – Clarity Patients.
We believe that our collaboration with the world renowned Johns Hopkins University has resulted in one of the most advanced clinically based commissioning decision support systems available to the UK health care system.
Sollis Clarity Patients is the largest implementation of the Johns Hopkins ACG System in the UK.
It currently supports 29 Clinical Commissioning Groups (CCGs) and 868 GP Practices.
In 2013, Sollis collaborated with the ACG International Team and NHS Central Southern CSU to recalibrate the predictive models in Version 10i of the ACG System to better reflect the NHS context. This enables the ACG System to more accurately capture the morbidity patterns within the NHS as well as the factors that contribute to increased risk within the local population. Central Southern CSU and Sollis agreed to make this enhancement available free of charge to other non-Sollis NHS implementations.
We continue to further develop Clarity Patients while integrating the ACG System to support service transformation and outcomes based commissioning for the UK NHS.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
The example below demonstrates how the ACG System controls for case mix differences and also risk-adjusts the population enrolled in a program.
Focusing on high-risk patients, results show that those enrolled in the intervention program experienced reductions in cost that far exceeded the high-risk, no intervention group.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
With a total disease burden perspective, the ACG System focuses on commonly occurring patterns of morbidity and assesses all types of medical need to achieve significant administrative efficiencies in the care management process, patient risk assessment and in patient targeting. This comprehensive approach has repeatedly proven superior to other case mix adjustment methodologies, especially those using complex data-mining or artificial intelligence algorithms where no two patients are categorized in the same manner.
The ACG System uses both pharmacy and electronic medical record data sources to select individuals based upon program-specific criteria, allowing care managers to spend more time with patients and less time on analysis. The clinical markers produced automatically eliminate the need to review records manually. The care manager is then able to understand a patient’s disease and morbidity profile; and select only the patients that truly warrant a detailed chart review.
The ACG System Predictive Models can identify up to 25% more individuals in need of care management intervention before they become high utilizers, compared to traditional methods based on prior utilization such as hospital concurrent review and emergency department utilization reports. By emphasizing developing patterns of morbidity, the ACG System helps identify individuals with a high disease burden—those seeing multiple clinicians and taking multiple prescriptions, as they may benefit from improved coordination of care.
Greater insight about the convergence of risk, medical utilization and prescribing patterns can be captured by combining risk defined by diagnoses with risk defined by retail pharmacy claims.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.
Patient adherence with therapy represents a major impediment to assessing clinical performance and contributes substantively to patient care costs and outcomes. The ACG RxGaps methodology was developed to capture patients with adherence issues and thereby improve their care management. Pharmacy benefits managers have made available refill patterns of patients to help identify potentially non-adhering patients who may warrant interventions by care managers. Unfortunately, the signal to noise ratio of these warnings is not high; there are many instances where gaps in adherence are expected, especially when medications are used acutely or as needed.
RxGaps employs innovative methods that increase the ability to detect genuine adherence problems by careful selection of conditions where chronic administration of medications is warranted, by the careful identification of specific medications that should be taken continuously, by capturing prescribing patterns that introduce potential noise, and by identifying medications that may be validly substituted without introducing gaps in adherence. Generally, measurement strategies have targeted specific possession events (i.e., gaps) or average possession of time expressed as a ratio (supply over prescribing period). The RxGaps employs markers using both of these strategies as they address different dimensions of adherence. Gaps capture acute occurrences and may represent a therapeutically significant event that could be overlooked if only averages are considered. Averages represent how well medication is supplied over a span of time (i.e, one year) and are a good summary indicator of possession in assessing the overall status of a patient but may be less amenable to direct clinical action.
To see the ACG System in action and speak to a Team member about your specific needs, request a demo today.