Chronic Disease Management Efficiency: Outcome Analytics Is The Key

By Natallia Babrovich, Business Analyst at ScienceSoft

As chronic diseases account for 86 percent of the U.S. healthcare costs, caregivers are concerned with accurate evaluation of their chronic condition management activities. Accordingly, there is much discussions and research on how to improve health outcomes for chronic patients. However, there is not much written on what precedes actual improvement — that is, medical data analytics where caregivers define, measure, and analyze these outcomes in order to base their progress with clinical processes on real-world data.

Only when this chain of defining, measuring, analyzing, and improving stays uninterrupted can providers reach a number of crucial milestones in the value-based care environment such as:

• improving care delivery by recognizing dependencies between medications, procedures, and lifestyle factors
• finding gaps in clinical processes and fixing them
• enhancing patient engagement to positively influence chronic patients’ health outcomes
• reporting to CMS and complying with the value-based care model
• analyzing their facilities, doctors, and nurses to both adopt best practices and fix the gaps in performance

But before the chain kicks off, caregivers may face certain challenges, including these three that chronic diseases bring into health outcomes analytics.

• A patient still stays ill: There is no way caregivers can use any outcome related to a complete recovery. Even with cancer, there can only be remission but this period can end anytime.
• Differences in initial health statuses: It is harder to evaluate health outcomes when patients’ initial general states differ a lot. One patient’s regular health condition can be life-threatening for another (for example, individual normal values of blood glucose vary among diabetes patients).
• Slow treatment progress: When speaking of clinical process improvements via outcome analysis specifically for long-term conditions, it is useless to analyze short-time outcome data (apart from complications and exacerbations), such as monthly measurements. This lag between an instance of care and the following health status improvement makes outcome data analytics even more challenging.

Defining Appropriate Measures For Chronic Health Outcomes With CMS

In the first place, caregivers are most likely to go for CMS quality measures of chronic health outcomes, which potentially allows both to report to CMS appropriately and acquire a set of measures for internal performance evaluation. De facto, CMS-provided metrics on health outcomes work for general reporting only. Here’s why.

The CMS quality measures were created on a consensual basis with the participation of multiple committees, agencies, and health systems, including AHRQ, PCPI, ASCO, and NCQA. This collaborative work resulted in sets of core quality measures related to seven clinical areas:

• Accountable Care Organizations (ACOs), Patient Centered Medical Homes (PCMH), and Primary Care
• Cardiology
• Gastroenterology
• HIV and Hepatitis C
• Medical Oncology
• Obstetrics and Gynecology
• Orthopedics

It’s important to keep in mind that, with these sets, CMS doesn’t pursue the goal to provide caregivers with top-to-down coverage of every disease and condition within each department. CMS itself states the core quality measures are best to be considered as “a framework upon which future efforts can be based,” not as hands-on instructions.

The sets feature few outcomes-focused measures for chronic diseases. Here are the long-term conditions covered with at least one outcome measure:

• Hypertension two alternative measures on blood pressure
• Diabetes one measure on negative HbA1c level trend
• Depression remission at 12 months and depression response at 12 months — progress towards remission
• Heart failure readmission rate, mortality rate
• Ischemic heart disease/coronary heart disease although the condition is chronic, the following measures cover only the acute form of therapy — surgery: two alternative measures on mortality rate following coronary artery bypass graft surgery, two alternative measures on readmission rate for CABG surgery

Hopefully, more outcomes-bound criteria are to come, as each of the seven documents includes a list of future areas for measure development. We have summed up those that are useful for chronic conditions:

ACOs, PCMH, And Primary Care

• health-related quality of life
• patient-reported outcomes (PROs)
• pain management measures
• pros for asthma exacerbations

Cardiology

• outpatient – symptom control or change in symptoms
• renal function measures for hypertension
• rehabilitation measures
• symptom management measures

Oncology

• pain control
• functional status or quality of life
• disease-free survival for x number of years
• patient experience/pros for the level of pain experienced by a patient

Conclusion: Caregivers can adopt the CMS quality measures for internal reporting only, and use the provided information as a starting point in defining the relevant chronic health outcomes measures for internal data analytics.

Beyond CMS: AMA, NQF, AHRQ review

The American Medical Association gives caregivers and researchers access to a wide array of clinical quality measures related to the following chronic diseases: asthma, COPD, stable coronary artery disease, diabetes, hypertension and heart failure. However, not all conditions are supported by outcomes-focused measures, as most of criteria target clinical processes. Currently, the covered diseases and conditions are the following:

• Stable Coronary Artery Disease
  • percentage of members with coronary artery disease who have optimally managed modifiable cardiovascular risk factors (LDL cholesterol, blood pressure control, daily aspirin use, documented non-tobacco use)
  • percentage of patients with coronary artery disease who have a lipid profile determination at target (less than 100) and measured within the last year
  • percentage of patients discharged with AMI, CABG, PTCA (inpatient or outpatient), or with ischemic vascular disease who have had a full lipid panel in the past year and LDL-C less than 100 on the most recent test in the past year
• Heart Failure (with most of measures addressing acute forms)
  • congestive heart failure mortality rate
  • heart failure 30-day mortality rate
  • congestive heart failure admission rate
  • heart failure 30-day risk-standardized heart failure readmission rate
  • risk-adjusted average length of inpatient hospital stay
• Hypertension
  • percentage of members 18 to 85 years of age diagnosed with hypertension whose blood pressure (bp) was adequately controlled (bp less than or equal to 140/90 mmhg) during the measurement year
  • percentage of eligible patients with an active diagnosis of hypertension whose most recent blood pressure recording was less than 140/90 mmhg
  • blood pressure control: percentage of patients aged 18 years and older with a diagnosis of hypertension seen within a 12 month period with a blood pressure <140/90 mm hg, or patients with a blood pressure ≥140/90 mm hg and prescribed 2 or more anti-hypertensive medications during the most recent office visit

Conclusion: While AMA doesn’t cover all the chronic conditions above with the quality measures related to patient outcomes, providers can embrace their experience and refer to AMA’s expertise when defining their own measure sets.

The National Quality Forum’s website is home to 290 outcome-focused measures that can be filtered by a clinical condition/topic area. Regarding chronic diseases, providers can explore the measures in such areas as cancer, cardiovascular, endocrine, neurology, pulmonary/critical care and renal.

Each area includes a list of particular conditions and diseases to pick. Sadly, there are few measures unrelated to admission, readmission and mortality. For example, from six outcome-related measures for asthma, one half applies to admission and the other to readmission.

Still, there is a chance to find valuable measures for some conditions. Diabetes is wrapped into 15 outcomes-allied measures, with particular criteria on patient treatment progress and self-management. To name a few:

• Hypoglycemia: Total number of hypoglycemic events (<40 mg/dl) that were preceded by administration of rapid/short-acting insulin within 12 hours or an anti-diabetic agent other than short-acting insulin within 24 hours, were not followed by another glucose value greater than 80 mg/dl within five minutes, and were at least 20 hours apart.
• Hyperglycemia: Total number of admissions with a diagnosis of diabetes mellitus, at least one administration of insulin or any anti-diabetic medication except metformin, or at least one elevated blood glucose value (>200 mg/dl [11.1 mmol/l]) at any time during the entire hospital stay.
• HbA1c control (<8.0 percent): The percentage of patients 18-75 years of age with diabetes (type 1 and type 2) whose most recent HbA1c level is <8.0 percent during the measurement year.
• HbA1c poor control (>9.0 percent): The percentage of patients 18-75 years of age with diabetes (type 1 and type 2) whose most recent HbA1c level during the measurement year was greater than 9.0 percent (poor control) or was missing a result, or if an HbA1c test was not done during the measurement year.
• Controlling high blood pressure: The percentage of patients 18-75 years of age with diabetes (type 1 and type 2) whose most recent blood pressure level taken during the measurement year is <140/90 mm Hg.

Conclusion: NQF’s materials can be used only for the selected diseases, and there is no possibility to apply all the criteria as they are. However, providers can come across a few valuable measures to enrich their internal CDM analytics.

Currently, there are 246 different outcome-focused measures on AHRQ’s National Quality Measures Clearinghouse (NQMC) web resource. Each measure is supported with a rationale, data collection guidelines, measure computation, and other attributes. However, there seems to be a gap between more or less covered and disregarded conditions.

Say, the search for ‘asthma’ returns three outcome-focused measures:

• average number of lost workdays and/or school days in the past 30 days
• percentage of pediatric and adult patients who have asthma and meet specified targets to control their asthma
• average number of symptom-free days in the previous two weeks

On the other hand, diabetes is wrapped with 15 measures. Most of them bring value for both reporting and internal medical analytics, to name a few:

• percentage of patients with diabetes with a documented HbA1c of less than 7.0 percent or meeting the patient’s individualized HbA1c goal
• percentage of patients with a blood pressure reading less than 130/80 in the last 12 months
• percentage of patients from 18 to 75 years with type 1 or type 2 diabetes whose most recent hemoglobin A1c (HbA1c) level is greater than 9.0 percent (poorly controlled)
• percentage of patients whose most recent LDL was less than 100 in the last 12 months

Conclusion: NQMC provides access to some chronic disease-specific outcome measures that can be useful in internal performance evaluation and care quality improvement. Unlike one can do on NQF’s website, caregivers can’t just pick a required disease from a list, so filtering is available only via typing relevant keywords, e.g. asthma or diabetes. Still, as a little more research uncovers valuable insights, providers shouldn’t disregard this source just because of some inconveniences.

International Practice For CDM Outcomes Measures: UK

The UK National Institute for Health and Care Excellence (NICE) provides caregivers with healthcare improvement guidance on a national level by developing care quality standards, measures, and indicators. Additionally, providers can access guidelines on diagnosis and management, interventional procedure guidance and technology appraisal guidance.

When it comes to chronic diseases, the following conditions are covered: chronic heart failure, hypertension, diabetes in adults and children separately, chronic kidney disease, chronic liver disease, depression in adults and children separately, asthma, and COPD.

The quality standards part is where the measures belong. Here, providers can find the sets of certain quality statements, where each statement is a separate measure. Even while not every measure relates to health outcomes, some examples are pretty impressive.

Let’s take COPD as one of them. From seven statements available, six focus on multiple outcomes:

• inhaler technique: target outcomes: exacerbation rates, hospital admission
• assessment for long‑term oxygen therapy: target outcomes: hospital admission for acute exacerbation, quality of life
• pulmonary rehabilitation for stable COPD and exercise limitation: target outcomes: hospital admission for acute exacerbation, quality of life, exercise capacity, GP attendances
• pulmonary rehabilitation after an acute exacerbation: target outcomes: hospital admission for acute exacerbation, quality of life, exercise capacity
• emergency oxygen during an exacerbation: target outcomes: frequency of non‑invasive ventilation due to oxygen toxicity, morbidity rates
• non‑invasive ventilation: target outcomes: mortality rates

Conclusion: NICE shows an example of a systematic approach to chronic diseases, their management and improvement of care quality. Most of long-term conditions are covered extensively. The organization clearly looks after both patients and providers with all the useful information in one place, ready to be taken and applied in a clinical environment. NICE also explains the reasons behind certain statements, their practical and research value, as well as solid connection to patient health outcomes.

Getting To Work With Chronic Outcomes-Focused Measures

Bad news is there is no ready-made set with complete measures to implement right away and enjoy chronic condition management data analytics running smoothly. But let’s look at this from the positive side.

As a range of respectable sources with frameworks, guidelines and good examples is available, there is no need to start from scratch. Providers can use available metrics from several sources, assemble or rework them, research in the field of future measures defined by CMS, or embrace the experience of fellow healthcare organizations worldwide.

This will allow caregivers to fully grasp CDM performance evaluation and systematically approach the question of improving chronic patients’ health outcomes, namely by:

• improving patients’ self-management for better blood glucose control, blood pressure control, weight control, dyspnea management and more
• enhancing patients’ life quality
• improving patients’ activity level
• reducing complications and exacerbations
• reducing morbidity, mortality, admission and readmission
• lessening hospital stay and time to work
• reducing redundant tests and procedures and more

While defining appropriate outcome-focused measures for chronic conditions will take some time and effort, the potential results outlined here are rewarding.