This detailed report utilizes the Johns Hopkins Adjusted Clinical Groups (ACG) including the Expanded Diagnosis Clusters (EDCs) to stratify the population by clinical morbidity. The EDCs are very useful for identifying patients for inclusion in a targeted disease management program. Selecting the EDCs allows the user access to the members within each classification which describes actual and anticipated costs for the next 12 months. This report uses a decision tree-filtering format where each panel of the report leads to a deeper analysis of the population in the subsequent panels.
Target Audience for this Report
Chief Medical Officer, Compliance & Regulatory Department, Finance Department and CFO, Leadership Team, Medical management/Care Management Department, Pharmacy & Therapeutics Committee, Physician Relations, Quality Management, and Utilization Management.
Business Processes Impacted by this Report
Population health and medical management functions will rely on this report for identification, stratification, and assessment of the members. The EDCs are a tool for easily identifying people with specific diseases or symptoms and the health plan does not have to create their own tools to manage this data with this report available.
The leadership/administration of the health plan will be informed by this report and will find by increasing the understanding of the membership, cost drivers, provider performance, and disease prevalence, the strategies developed can be focused and effective. Provider relations and the CMO/Medical Director have actionable data derived from this report. The ability to understand provider behavior is critical to developing ways to support providers in their care delivery at a population health level. Education of providers can be specific and outcome based rather than anecdotal and infrequent. EDCs help to remove differences in coding behavior between practitioners and create a better method of analysis. Medical Management will focus their member interactions as well as their interface with the providers/facilities. Targeted care management and member outreach is informed by this report. Medical Management including utilization management will find this report extremely helpful to both understand current utilization and to predict future utilization.
Detail and Definitions
ACG Groups – (Adjusted Clinical Groups) Classification system based on administrative diagnosis data and developed by The Johns Hopkins Bloomberg School of Public Health to measure morbidity and predict the utilization of medical resources. Used for risk stratification of the population.
The ACG method groups every medical diagnosis code, assigned to a patient, and is based on the following five clinical and expected utilization criteria:
1. Duration of the condition (acute, recurrent, or chronic)
2. Severity of the condition (e.g., minor and stable versus major and unstable)
3. Diagnostic certainty (symptoms focusing on diagnostic evaluation versus documented disease focusing on treatment services)
4. Etiology of the condition (infectious, injury, or other)
5. Specialty care involvement (medical, surgical, obstetric, hematology, etc.)
Non-users are individuals that used services for a shorter period of time than the full year period. These eligible members could have entered the plan near the end of the analysis period and may lack sufficient contact with the provider to allow accurate overall ACG assignment. With no valid diagnosis assigned to an ADG there is no EDC grouping in the report.
ADG - Aggregated Diagnosis Groups (ADG) as designed by expert clinicians, the ACG system categorizes ICD-9 / ICD-10 diagnosis codes into one of 32 groups called Aggregated Diagnosis Groups™ (ADGs®).
If, over a defined interval (usually one year) an individual has at least one of the diagnoses in an Aggregated Diagnosis Group, they are assigned that ADG. A patient can be assigned as few as none and as many as 32 ADGs. The system further classifies ADGs as "major" or "minor".
EDC - To provide a comprehensive clinical context, the ACG® System also includes Expanded Diagnosis Clusters (EDCs). EDCs are groupings of diagnostic codes that describe the same or related condition. For example, the many diagnostic codes that describe different forms of congestive heart failure are all clustered into a single EDC. EDCs are useful for examining the epidemiology of disease within a population. They can also be used as a disease/condition marker for various applications, such as identifying patients for inclusion in a targeted disease management program.
For more information on ACGs and EDCs- https://www.hopkinsacg.org/document/acg-system-version-11-1-technical-reference-guide/
Patient RX-MG; Rx Defined Morbidity Groups (Rx-MGs) represent the building blocks of a pharmacy-based predictive model. Each generic drug/route of administration combination is assigned to a single Rx-MG. Generic drug/route of administration combinations within therapeutic classes were sometimes logically assigned to different Rx-MGs, which further reinforced the need to make assignments at the individual drug level. The Rx-MGs were created using a clinical framework that makes sense to health professionals and medical managers. Pharmacy derived morbidity markers add a great deal of clinical context and improved statistical performance when applied to predictive modeling applications.
- ACG Groups
- EDC Clusters
- Members EDC
- 1 EDC
- 2-3 EDC
- 4-6 EDC
- 7-10 EDC
- 11-15 EDC
- 16+ EDC
Population Stratification (Graph) - The graph displays the ACGs - comorbidity combinations – Complex, Commonly Occurring, Single, Pregnant, Infant, and Non-Users. These combinations are defined and listed in detail in the adjacent table “Each member is assigned to ONE ACG….”
The comorbidity combinations are described in 3 columns –
- Patient Count
- Total Cost
The colored bar graphs offer the user a quick reference to understanding the volume and costs of each combination. When the bar graph is clicked in the Population Decision Tree the adjacent table “Each member is assigned to ONE ACG….”is sorted to place that combination at the top of the list.
Members by Aggregated Diagnosis Groups
The ACGs comorbidity combinations listed in the Population Decision Tree graph are further defined in this table. Each combination type contains a detailed description of the ACG with the patient volume, risk and cost.
- ADG Classification1 - The ACG descriptions are segmented as Complex, Commonly Occurring, Single, Pregnant, Infant, and Non-Users which corresponds to the Population Decision Tree graph.
- Avg Risk
- Risk Score Prospective
Members by Expanded Diagnosis Culusters
- (Impact) Icon – Yellow indicates medium impact, and red is high.
- Member Number
- Member Name
- Predicted Costs
Patient Medical Markers (EDC)
Patient Pharmacy Markers (RX-MG)
- Pharmacy Marker
- Impact Type