A Nurse Care Manager’s Experience With a Consumer’s Medication Adherence
Joe, a 39-year-old consumer, is being treated in Maryland at a community behavioral health center focused on integrated care. Joe has a schizophrenia diagnosis, a poor diet and diabetes. During visits with a nurse care manager, he self-reported that he was taking his medications as prescribed, but his symptoms suggested otherwise. Joe’s blood sugar was high, and he was internalizing, not engaging with others and talking to himself.
To get a 360-degree view of what might be going on with Joe, the nurse care manager reviewed the data using their data analytics tool from Relias, which provided information to get a clearer picture on Joe’s medication adherence.
Joe was not filling all his medications on a regular basis.
This changed the conversation that the nurse care manager had with Joe. Instead of asking, “Are you taking your medicine?” she changed her approach to, “Tell me about when you take your medicine,” and “How do you get to the pharmacy?”
It turned out that Joe was taking his prescription medications, but he was taking them every other day because of side effects that he wasn’t comfortable talking about.
You can do more for consumers like Joe when you know more and have more pieces of the puzzle. Behavioral and physical health data analytics, pharmacy data and the information you gather from self-reporting give the clinical insight to genuinely improve outcomes for a person facing many challenges.
A client may not be able to provide a perfectly accurate medical history, but a healthcare data analytics solution like Relias Population Health is a way to get supplemental information beyond what clients tell you. All humans are flawed, but data is not.
A Health Home Care Manager’s Experience With Self-Reporting a Hospitalization From an Individual With an SMI Diagnosis
Carl is a 42-year-old patient who is being treated by a PCP at a community health center in Missouri that serves as his health home. Carl has a schizophrenia diagnosis, a poor diet and substance use disorders. Carl missed two regular visits and had not been seen in five months. During a visit with a nurse care manager, he self-reported that he was taking his medications as prescribed, but his symptoms suggested otherwise. Carl’s blood sugar was high, he said he was having severe headaches and it was evident that he was likely having auditory hallucinations, as he was talking to himself.
The nurse care manager reviewed the paid claims data via their population health tool and saw that Carl was hospitalized five weeks prior in another city, but he didn’t tell her that during the visit when he was asked about changes in his health.
Armed with this knowledge, the care manager could have asked Carl leading questions to get details about his hospitalization. If she had chosen to, the care manager could decide not to ask additional questions if she thought it might provoke or otherwise compromise Carl’s care, but she knew about it and it helped inform Carl’s treatment plan.
You can do more for clients and patients when you know more and have more pieces of the puzzle, like this full picture of Carl’s recent medical history. Behavioral and physical health data analytics, combined with the information you gather from self-reporting, give the clinical insight to genuinely improve outcomes for a person facing many challenges who may not be able to provide a perfectly accurate medical history.
A Care Coordinator’s Experience With a Client’s Medication Adherence and Social Determinants
Karen, a 31-year-old client, is being treated at a behavioral health center in North Carolina. Karen has an SMI diagnosis as well as diabetes. She self-reported that she was taking her medications as prescribed, but her blood sugar levels and manic symptoms were worsening.
To get a fuller picture of why Karen’s symptoms were no longer being controlled by her medications, the care coordinator reviewed the data using their data analytics tool, which provided the insight into Karen’s medication adherence.
The pharmacy data showed that Karen was sporadically filling her prescriptions.
Knowing this changed the conversation the care coordinator had with Karen. Instead of asking, “Do you take your medicine?” she changed her approach to, “How do you get to the pharmacy?” and “When do you take your medicine?”
The care coordinator learned that Karen was not able to afford all her medicines, so she was taking half doses to make them “stretch” longer. Armed with this new piece of information, the coordinator expanded her focus and got Karen assistance with the cost of her medicine, and she remains adherent to this day.
You can do more for clients like Karen when you know more. The combination of self-reported information plus behavioral health and pharmacy data gives the clinical insight to target your treatment plans to improve outcomes for a person facing many challenges, including the social determinants of their health and well-being.
A healthcare data analytics solution like Relias Population Health is a way to get supplemental information beyond what clients and patients tell you.