Blog banner

The Truven Health Blog


The latest healthcare topics from a trusted, proven, and unbiased source.


The Effects of Telecommuting Intensity on Employee Health

Chosen as AJHP Editor’s Pick for 2016


By Truven Staff/Friday, March 10, 2017

 

The number of employees who take advantage of telecommuting has increased substantially in recent years - especially with the improvements in technology and the increasing demand for more flexible work schedules. The Effects of Telecommuting Intensity on Employee Health, recently chosen as Editor’s Pick for 2016 by the American Journal of Health Promotion (AJHP), highlights how the employees at Prudential Financial, a company with a long history in promoting work flexibility are affected by telecommuting - specifically in relation to their overall health.

Over a two-year period, Prudential Financial, in partnership with Truven Health Analytics®, IBM Watson Health™ analyzed the amount of time employees spent telecommuting and what potential health risks arose because of it, including depression, stress, poor nutrition, physical inactivity, tobacco use, alcohol abuse, and obesity.

The research suggested that telecommuters had a lower risk of developing many medical ailments, including obesity, alcohol abuse, physical inactivity, and tobacco use. The study also found evidence that employees who engage in a small number of telecommuting hours were less likely to develop depression. While the study provided some evidence to suggest that flexibility with telecommuting has health benefits, maintaining some level of in-office work may help to strengthen spiritual and social health.

 Download the full study here.

 


Workplace programs, policies and environmental supports to prevent cardiovascular disease


By Truven Staff/Tuesday, February 7, 2017

Ninety-nine percent of the U.S. population has at least one of seven cardiovascular health risks: high blood pressure, high total cholesterol, high blood glucose, unhealthy body mass index (BMI), tobacco use, physical inactivity, or poor diet.[1] The combined contribution of these risk factors increases employer medical spending by 213 percent per person per year.[2]

“Organizations need to assess their heart health programs, policies and environmental supports to reduce health risk factors for cardiovascular disease, lower the prevalence of the illness, and reduce medical expenditures,” said Ron Z. Goetzel, Ph.D., vice president of consulting and applied research at Truven Health Analytics, an IBM Company.

The American Heart Association (AHA) offers the Workplace Health Achievement Index (WHAI) to help organizations perform these assessments. Last year we connected organizational WHAI measures to individual employee medical, drug and health risk data housed in the Truven Health MarketScan® multi-employer database, and together we analyzed the data.

Results from the study

Twenty large employers participated in this study to assess the association between organizational health and measures of cardiovascular health risks, disease prevalence and medical costs. Some results of the study included:

  • One fifth of employees have cardiovascular disease, with an average per member per year spending of $329 for the disease
  • The most common health risk for these workers was unhealthy weight (72% prevalence), followed by poor diet (71%) and high blood pressure (66%)
  • The least common health risk was tobacco use (5.5%), which was substantially lower than that for the U.S. adult population (16.8%)
  • A higher WHAI score was associated with lower prevalence of four modifiable health risk factors: high blood pressure, high cholesterol, tobacco use, and physical inactivity
  • WHAI scores were not correlated with high blood glucose and unhealthy weight, but were positively correlated with poor diet
  • A higher WHAI score was associated with lower cardiovascular disease prevalence but higher cardiovascular disease spending, a result meriting further study

Though there is no clear pattern as to which organizational health factors are associated with better outcomes, we encourage employers to participate in the next wave of multi-employer studies that aims to look at trends in organizational programs, policies and environment, and how these support a healthy lifestyle among workers[SE1] [GRZ2] .

What can employers do with these results?

  • Employers can act now! There is no need to wait for more research before implementing evidence-based health promotion programs proven to positively influence employee health and well-being.
  • When implementing a program, remember to always measure and evaluate.  This can be done by designing “dashboards” that track key program structure, process and outcome measures for the organization.
  • Finally, employers can experiment with different health promotion strategies at different business units/locations and track the effectiveness of alternative models.

Dr. Goetzel presented the study findings at a briefing event sponsored by Health Affairs on Tuesday, February 7, 2017 at the National Press Club in Washington, DC.  For more information, click here.

 

[1] Ford ES, Greenlund KJ, Hong Y. Ideal cardiovascular health and mortality from all causes and diseases of the circulatory system among adults in the United States. Circulation. 2012;125:987-995.

[2] Goetzel RZ, Pei X, Tabrizi MJ, Henke RM, Kowlessar N, Nelson CF, et al. Ten modifiable health risk factors are linked to more than one-fifth of employer-employee health care spending. Health Aff (Millwood). 2012;31(11):2474-84

 

 

 


Evidence That Telecommuting May Improve Employee Health


By Rachel Mosher Henke/Friday, December 16, 2016

 More people than ever work from home one or more days a week. The practice of telecommuting has taken the business world by storm.  Improvements in technology, the demand for more flexible work schedules and cost reduction strategies have contributed to this trend which has seen a dramatic increase over the last several years. Even people who live close to their place of work may take advantage of working remotely to eliminate commute time and provide flexibility to take care of midday appointments or family needs.  

Most of the attention on telecommuting has focused on how it impacts work productivity and opportunities for promotion.  But an important factor has been largely overlooked and absent from consideration – employee health.  Employers and employees can both benefit from learning how telecommuting affects health. 

Prudential Financial, a company with a long history in promoting work flexibility, in partnership with Truven Health endeavored to fill this gap and understand what affects telecommuting has on their overall employee health.  The research study looked at amount of time telecommuting and potential health risks including depression, stress, poor nutrition, physical inactivity, tobacco use, alcohol abuse, and obesity.

Studying a time period of two years, our research suggests that telecommuters had lower risk for obesity, alcohol abuse, physical inactivity, and tobacco use.  We found evidence that employees who engage in a small amount of telecommuting hours are likely to benefit positively from the activity including reducing their risk for depression.

The connection we found between telecommuting and lower health risks further strengthens the business case for support of flexibility and the connection between work-life and health.  However, it is important to note that while our study provides some evidence to suggest that flexibility has health benefits, maintaining some level of in-office work may help to strengthen spiritual and social health. In the case of 100% remote workers, managers may want to ensure extra effort is made to stay connected to those workers and create inclusive opportunities with the rest of the team.

The study timeframe was only two years, so more research is needed to understand the longer term impact of working from home on health. The results from our study of the Prudential program are specific to their employee programs.  And though not generalizable employers and health plans may be curious to see whether these health benefits translate to health care savings for their organizations. 

Truven Health Analytics is encouraged and eager to help organizations examine the relationship between telecommuting intensity and health outcomes. 

You can read more about our findings by downloading the full research brief, The Effects of Telecommuting Intensity on Employee Health.

Rachel Henke
Senior Director Behavioral Health and Quality Research

 


Risk of Hospitalization


By Therese Gorski/Tuesday, December 13, 2016

As Anne Fischer wrote in her last blog How a Data Scientist Thinks about Risk Stratification, in order to predict risk, we need to first determine what “risk” is being measured. One important risk is that of being hospitalized.  Risk of hospitalization or admission models have become more targeted, more personal and seemingly more prevalent. Further, they are very much in line with the goals of population health and the “quadruple aim” (improving patient care, reducing costs, improving the health of populations and improving the provider’s experience). If a person has proper ambulatory or outpatient care for a chronic disease, acute inpatient admissions related to that disease should be rare.

At Truven Health, we have been developing and maintaining risk models for decades. Many risk models, such as risk of cost, risk of mortality and risk of complications, are best used in aggregate within a population subset. This evaluation is typically done at a service line or patient group level, for example, all cardiovascular patients or all patients with a specific MS-DRG.

In today’s world of increasing interest in care management and targeted outreach, individual level risk models hold much promise.  These models evaluate and interpret risk for each individual patient. Several years ago, we started a journey to develop new targeted risk models – including risk of hospitalization – to meet this increasing business need. We focused on specific diseases with the intent to have high predictive accuracy overall but particularly at the “tails”, meaning we must perform well at identifying those who have a high likelihood of being admitted in the near future. Or, in data science terms, model performance was measured by its sensitivity, specificity and positive predictive value for all patients above a specific risk threshold, with an emphasis on high sensitivity (that is, reducing false negatives).

To start, we chose to focus on diabetes, congestive heart failure (CHF), asthma, and more recently chronic obstructive pulmonary disease (COPD). These conditions run the gamut for both prevalence and admission risk, with asthma being most prevalent and least likely to result in admission versus CHF, which is least common but most likely to result in admission. These are also chronic conditions that are typically managed, at some level, which also fit our criteria.

In addition to specific diseases, we also focused on identifying risk at one-, three- and six-month intervals so that a care manager can better understand the risk at hand and be able to prioritize accordingly. Further, we report risk across several categories including “all-cause admissions”, “potentially avoidable admissions” (largely defined by AHRQ) and risk of “related admissions” which represents conditions that are considered to be related to the main condition as defined by Truven Health. Finally, along with each model’s risk score, we provide the patient attributes that are driving the risk score, whether it be a recent hospitalization, level of disease severity or even age. We believe that this additional insight gives the care manager a bit more background on the patient, helping to explain why the patient may have an increased risk value.

These models have been notably successful in terms of their predictive accuracy and our work will continue as we expand the number of diseases and work with our clients to help make the information actionable. The general trend toward person specific risk versus risk in aggregate will only grow and will become more refined as we, and the industry in general, are able to obtain and incorporate more personalized information about people.

Therese Gorski
Senior Director, Advanced Analytics


Truven Health Risk Model Ranks High in Actuarial Evaluation


By John Azzolini/Monday, November 28, 2016

 

Healthcare payers today are facing the complexities of reform, increased competition, and budget constraints — all while dealing with pressures to reduce costs and improve member health. Managing health risk has become a necessity. But to manage risk, payers must first understand their population. To do this well, they need reliable, robust risk and cost of care models.

 

Last month, the Society of Actuaries (SOA) released a study showing that Truven Health Analytics’ cost of care model outperformed other risk models in 18 out of 22 measures. SOA’s Accuracy of Claims-Based Risk Scoring Models compared health risk-scoring models, building on their previous studies with similar objectives (the most recent was in 2007). In the medical claims category (predictions based only on medical claims data), the current study showed that, in 21 of the 22 measures, the Truven Health model was ranked either first or second. No other model came close to matching this performance. (See Table 1 for a summary of how Truven Health’s model ranked relative to the competition).

 

How the SOA Evaluates Risk Models

The SOA evaluated Truven Health Analytics’ cost of care model against six others:

 

  • ACG® System
  • Chronic Illness & Disability Payment System and MedicaidRx
  • DxCG Intelligence
  • HHS-HCC
  • Milliman Advanced Risk Adjusters
  • Wakely Risk Assessment Model

 

The SOA assessed all models on their ability to predict costs using the Truven Health Marketscan® commercial claims dataset of 1 million members, and used three methodologies to evaluate their precision: R-Squared, the mean absolute error statistics, and predictive ratios. All three methodologies measure the statistical difference between the prediction and the actual results. All models produced both a concurrent and prospective cost prediction and were evaluated using both a capped data set (where patient costs were capped at $250,000) and a non-capped data set.

 

The SOA evaluated the models’ predictive ability using a number of scenarios (total medical costs, simulated random groups, condition-specific predictions, patient cost). In the simulated random group scenario, the SOA created groups of 1,000 and 10,000 patients to simulate the application of the model to subgroups of the population.

 

Table 1: How the Truven Health Cost of Care Model Performed

The Truven Health model ranked first or second for its ability to predict costs in 21 of the 22 measures studied.

 

Scenario

Truven Health Model Ranking*

R-Squared

Mean Absolute Error

Non-Capped

Capped**

Non-Capped

Capped**

Total Medical Costs, Concurrent

2

1

2

1

Total Medical Costs, Prospective

1

1

1

1

Simulated Random Groups, Concurrent

2

3

1

1

Simulated Random Groups, Prospective

1

1

1

1

 

 

Predictive Ratios

 

 

Overall Condition Specific Prediction, Concurrent

 

1

 

 

Overall Condition Specific Prediction, Prospective

 

1

 

 

Very Low Cost Patients, Concurrent

 

1

 

 

Very Low Cost Patients, Prospective

 

1

 

 

Very High Cost Patients, Concurrent

 

1

 

 

Very High Cost Patients, Prospective

 

1

 

 

     * Compared with six other models.

** Capped at $250,000

 

Why Risk Models Are Important to Payers

Risk modeling is a very helpful tool for health plans and employers. It can provide valuable insights into member utilization patterns and risk– vital for benefit planning, disease management and wellness program management, and member communications. It can provide deep insights into provider performance, and aid in determining ideal reimbursement and premium rates. Such models are an integral part of a number of Truven Health databases and analytical tools. The SOA evaluation speaks to the high quality and reliability of the Truven Health solutions.

John Azzolini
Senior Consulting Scientist

RSS