Thursday, August 24, 2017

What is the impact on utilization and outcomes for adults with obstructive airway disease?

Contributions of COPD, asthma, and ten comorbid conditions to health care utilization and patient-centered outcomes among US adults with obstructive airway disease.

Background: Among persons with obstructive airway disease, the relative contributions of chronic obstructive pulmonary disease (COPD), asthma, and common comorbid conditions to health care utilization and patient-centered outcomes (PCOs) have not been previously reported.

Methods: We followed a total of 3,486 persons aged ≥40 years with COPD, asthma, or both at baseline, from the Medical Expenditure Panel Survey (MEPS) cohorts enrolled annually from 2008 through 2012 for 1 year. MEPS is a prospective observational study of US households recording self-reported COPD, asthma, and ten medical conditions: angina, arthritis, cancer, coronary heart disease, cognitive impairment, diabetes, hypertension, lung cancer, myocardial infarction, and stroke/transient ischemic attack. We studied the separate contributions of these conditions to health care utilization (all-cause and respiratory disease hospitalization, any emergency department [ED] visit, and six or more outpatient visits) and PCOs (seven or more days spent in bed due to illness, incident loss of mobility, and incident decline in self-perceived health).

Results: COPD made the largest contributions to all-cause and respiratory disease hospitalization and ED visits, while arthritis made the largest contribution to outpatient health care. Arthritis and COPD, respectively, made the greatest contributions to the PCOs.

Conclusion: COPD made the largest and second largest contributions to health care utilization and PCOs among US adults with obstructive airway disease. The twelve medical conditions collectively accounted for between 52% and 61% of the health care utilization outcomes and between 53% and 68% of the PCOs. Cognitive impairment, diabetes, hypertension, and stroke also made significant contributions.

Authors Murphy TE, McAvay GJ, Allore HG, Stamm JA, Simonelli PF
Received 19 April 2017
Accepted for publication 1 July 2017
Published 23 August 2017 Volume 2017:12 Pages 2515—2522

Read More

Humana banks on big data to boost patient health — and profits

From fewer heart attacks to stronger bones and longer functioning brains, insurer Humana hopes that a data analysis partnership with a California biotech company will help improve people’s health, lower the cost of care and increase profits.

Humana’s collaboration with Amgen will focus on the enormous amounts of health claims data that Humana collects on its roughly 9 million customers. While details about the research are still being finalized, the insurer hopes to analyze the data to detect health problems earlier and intervene before they become more serious — and costly to the patient, the hospital and the insurer.

“We believe that you lower costs by improving patient outcomes,” said Laura Happe, the company’s chief pharmacy officer.

The companies also plan to combine real-world evidence with data from wearable tech and apps or even Bluetooth-enabled drug delivery devices to target serious conditions such as cardiovascular disease, osteoporosis, neurologic disorders, inflammatory diseases and cancer.

While Humana and Amgen have worked together before, the new partnership marks the first research collaboration.

“Overall, there is a trend towards using data and learning from data to optimize care,” Happe said.
Businesses and governments hope the ability to analyze big sets of health care data will allow them to improve care and reduce waste, fraud and costs — but the sheer amount of data that is available and being collected also presents significant challenges.

In a recent report by Stanford Medicine, Dr. Lloyd Minor, dean of the Stanford School of Medicine, said the health care industry’s increasing connectivity and complexity “poses both an opportunity and a challenge.”

“By leveraging big data, we can create a vision of health care that is more preventive, predictive and precise,” he said.

California-based data analytics company MapR recently said that data analysis can help health care providers with early detection of serious health conditions, such as congestive heart failure.
CHF “accounts for the most health care spending. The earlier it is diagnosed, the better it can be treated, avoiding expensive complications, but early manifestations can be easily missed by physicians,” the company said. “A machine learning example from Georgia Tech demonstrated that machine learning algorithms could look at many more factors in patients’ charts than doctors, and by adding additional features, there was a substantial increase in the ability of the model to distinguish people who have CHF from people who don’t.”

Happe said that when CHF is undetected or uncontrolled, patients can end up with fluid retention, which can become life-threatening.

Humana and Amgen will sift through data to figure out how to detect the condition earlier and prevent bad outcomes. Healthier patients will mean fewer doctor and hospital visits, which will mean lower costs to health care providers and payers, including the patient and Humana.

Amgen, based in Thousand Oaks, Calif., conducts research and develops therapies for illnesses, primarily in six areas: cardiovascular disease, oncology, bone health, neuroscience, nephrology and inflammation. Its products include Enbrel, which treats arthritis; Neulasta, which stimulates white blood cell growth and is used often for chemotherapy patients; and Sensipar, which prevents bone disease. The company employs about 20,000 in 100 countries and last year generated revenue of about $23 billion.

Read More