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He had also been abused as a puppy and had severe anxiety. Moose had epilepsy and had required surgery on both his hind legs. Both were the kind of dog she preferred to adopt: older rescues with significant medical problems that other prospective owners might avoid. And eventually she came upon an explanation that helped her understand what might have gone wrong: She had sick pets.ДЄt the time of her hospitalization, Kathryn owned two flat-coated retrievers, Bear and Moose. But could that really have been enough to get her kicked out of a medical practice?ДЄs Kathryn continued her research online, she found that there was a whole world of chronic pain patients on Twitter and other forums comparing notes on how theyвЂ™d run afoul of NarxCare or other screening tools. She did have a prescription for a benzodiazepine to treat post-traumatic stress disorder, and combining such drugs with opioids is a known risk factor for overdose. And doctors have authorities looking over their shoulders as they weigh their own responses to those scores.Д®ventually she came upon an explanation that helped her understand where sheвЂ™d gone wrong: She had sick pets.Д®ven after Kathryn had read up on NarxCare, however, she was still left with a basic question: Why had she been flagged with such a high score? She wasnвЂ™t вЂњdoctor shopping.вЂќ The only other physician she saw was her psychiatrist. In essence, Kathryn found, nearly all Americans have the equivalent of a secret credit score that rates the risk of prescribing controlled substances to them. In some states, police and federal law enforcement officers can also access this highly sensitive medical information-in many cases without a warrant-to prosecute both doctors and patients.

SHAPE COLLAGE PRO CRACK SOFTWARE

Nearly every state now uses Appriss software to manage its prescription drug monitoring programs, and most legally require physicians and pharmacists to consult them when prescribing controlled substances, on penalty of losing their license. But physicians ignore these numbers at their peril. Only Appriss knows exactly how this score is derived, but according to the companyвЂ™s promotional material, its predictive model not only draws from state drug registry data, but вЂњmay include medical claims data, electronic health records, EMS data, and criminal justice data.вЂќ At least eight states, including Texas, Florida, Ohio, and Michigan-where Kathryn lives-have signed up to incorporate this algorithm into their monitoring programs.ДЇor all the seeming complexity of these inputs, what doctors see on their screen when they call up a patientвЂ™s NarxCare report is very simple: a bunch of data visualizations that describe the personвЂ™s prescription history, topped by a handful of three-digit scores that neatly purport to sum up the patientвЂ™s risk.ДЄppriss is adamant that a NarxCare score is not meant to supplant a doctorвЂ™s diagnosis. NarxCare also offers states access to a complex machine-learning product that automatically assigns each patient a unique, comprehensive Overdose Risk Score. On the most basic level, when a doctor queries NarxCare about someone like Kathryn, the software mines state registries for red flags indicating that she has engaged in вЂњdrug shoppingвЂќ behavior: It notes the number of pharmacies a patient has visited, the distances sheвЂ™s traveled to receive health care, and the combinations of prescriptions she receives.Д«eyond that, things get a little mysterious.

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