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Incomplete Population Health Data Exacerbates Care Disparities

Most health plans are missing key socioeconomic data required to develop meaningful population health management programs for vulnerable patients.

Population health and socioeconomic data

Source: Thinkstock

By Jennifer Bresnick

- Managed care policymakers do not have access to enough clean, complete, and accurate socioeconomic and population health data on the millions of patients depending on public insurance programs for care, according to a new article in Health Affairs.

“To reduce disparities, it is critical to first know where they exist,” said the research team from CMS and NCQA.  “Improving documentation of race, ethnicity, and language needs in managed care plan reporting, regardless of data collection method, and clarifying how high-performing health plans achieve their results, will be important.”

Plans collect this data, among other information, through the Healthcare Effectiveness Data and Information Set (HEDIS).  Yet the majority of insurers are missing critical data on huge swathes of the patient population.

Health plans are particularly deficient in collecting information on race, ethnicity, and patient language needs, with commercial entities being among the worst offenders. 

Between 2012 and 2015, more than 80 percent of commercial plans were missing at least half of their HEDIS data about ethnicity, primary spoken language, and primary written language for their beneficiaries.

READ MORE: Identifying Care Disparities for Population Health Management

Medicaid plan providers were also caught short on ethnicity data, with approximately 70 percent of plans holding incomplete information on more than half of their patients.

Gaps in socioeconomic data collection by managed care plans

Source: Health Affairs

“Fewer than half of commercial, Medicaid, and Medicare plans reported complete or partially complete data on spoken language, and even fewer reported complete or partially complete written language or other language needs data,” said the researchers.

“Medicare plans reported more complete or partially complete language needs data than did Medicaid plans, while commercial plans reported the least complete or partially complete language needs data.”

Racial and ethnic disparities in care delivery and patient outcomes can be fueled by language barriers that prevent clear patient-provider communication.

READ MORE: How to Get Started with a Population Health Management Program

Beneficiaries with limited English skills are less likely to have positive interactions with the healthcare system, said a recent survey by Oliver Wyman and the Altarum Institute.

Just under half of Spanish-speaking patients participating in the survey said they experience difficulties communicating with providers and reading printed forms. 

They are significantly less likely to trust professionals who do not speak Spanish, and 40 percent left the encounter feeling disrespected.  These patients later exhibited lower adherence to recommended treatment.

When providers successfully engage non-English speaking patients in their native languages, however, the results can be extremely positive. 

A pilot medication adherence project at San Francisco General Hospital in 2015 found that delivering tailored educational materials in the patient’s native language helped to decrease readmissions among high-risk patients by 70 percent.

READ MORE: Smart Big Data is Key to Population Health, Value-Based Care

Simple explanations, visual calendars, and information in the patient’s preferred language helped patients develop greater confidence in their home care routines and help them form better habits, said

“When it comes to high risk patients…you have to grab onto any chance you can to make an impact with the individual,” said David Smith, PharmD, at the time.

“And you have to make sure that it’s done in their native language.  You can sit there with Google Translate or a human translator by the bedside, but if you give them a ream of papers in English to take home, they’re not going to remember anything you said, and they won’t necessarily be able to read those instructions.”

But without accurate data that can help providers apportion translation services and develop language-specific plans to serve local communities, health plans and clinical organizations will be flying blind.

Similar deficiencies in racial and ethnic data may prevent providers from conducting meaningful risk stratification for chronic diseases or acute conditions more prevalent in certain groups.

While Medicare, Medicaid, and commercial plans were more likely to collect racial and ethnic information than language-related data, they still have room for improvement.

Racial and ethnic data collection rates

Source: Health Affairs

“In 2015, one-third of commercial plans, half of Medicaid plans, and nearly three-quarters of Medicare plans reported complete and partially complete data on race,” the study explained.

“Plans fared worse on ethnicity data reporting, with fewer than half of all plan types reporting complete or partially complete data.”

Race and ethnicity also have a significant impact on the patient experience.  CMS data from 2014 shows that black, Asian, Hispanic, and American Indian/Alaskan Native patients all generally fared worse on patient experience metrics than white patients. 

These metrics include access to care, customer service, and patient-provider communication.

Patient experience disparities among ethnic groups

Source: CMS

Non-white patients also tend to have higher rates of certain chronic diseases and often experience more social and community barriers to healthy lifestyle choices.  Hospitalization rates for conditions such as hypertension vary widely between ethnic groups, with black and Hispanic patients experiencing admissions at much higher rates than whites.

Incomplete data makes it more difficult for providers to create meaningful population health management plans that address the specific needs of their communities.

“The ability to stratify reporting of health quality measures, to target disparities, and to understand effective interventions or strategies for addressing disparities depends on the ability to collect this information consistently,” the Health Affairs team stated.

“Policy requirements or other incentives may be needed to improve data availability for stratified reporting of health quality measures and disparity reduction efforts in commercial plans.”


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