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DTSTART;VALUE=DATE:20260706
DTEND;VALUE=DATE:20261201
DTSTAMP:20261021T083612
CREATED:20260706T205554Z
LAST-MODIFIED:20260707T181446Z
UID:173481-1783296000-1796083199@www.parker.edu
SUMMARY:Alumni Awards Nominations
DESCRIPTION:Quick Answer\n			\n						AI is already drafting clinical notes\, flagging patients at risk of decline\, and suggesting billing codes. The career story in 2026 isn't that AI is doing the work. It's that someone has to verify it. States are writing that verification into law\, major health systems are hiring executives to own it\, and the American Medical Association just released a framework built around one question: who is accountable when AI gets it wrong? Health information management professionals and healthcare administrators are the people most often holding that responsibility.\n			\n						\n									×\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Is AI actually being used in hospitals right now? 				\n				\n					\n				\n		\n					\n				\n				\n									Yes\, and well past the pilot stage at many organizations. In a recent survey of 250 U.S. healthcare leaders reported by Healthcare Dive\, about 28% said their organization had already deployed agentic AI tools\, which can complete multi-step tasks without a person approving each step. Another 44% were running pilots.  One of the clearest examples landed in September. The electronic health record company Epic received FDA clearance for Version 2 of its Deterioration Index\, a tool built into the patient record that scores hospitalized adults from 0 to 100 based on their risk of needing escalated care within a day or dying within three days. It pulls from 195 data points in the record\, including vital signs\, lab results\, nursing assessments and medications.  What makes this story useful for anyone considering a healthcare career is the detail underneath the headline. Hospitals had been using earlier versions of the tool for years before the FDA reviewed it. A 2024 study across seven Yale New Haven Health hospitals ranked the earlier index near the bottom of six early warning scores. A separate study published this summer linked its use at RWJBarnabas Health to an 18% drop in the risk-adjusted odds of in-hospital death among high-risk patients. And in Epic’s own testing data\, the tool caught deterioration less reliably in Black and Hispanic patients than in white patients at its medium-risk threshold\, though that gap narrowed when results were analyzed site by site.  The same tool helped in one setting\, underperformed in another and showed uneven accuracy across patient groups. That isn’t a reason to avoid AI. It’s the reason healthcare needs people trained to ask whether a tool is working\, for whom\, and how anyone would know.  								\n				\n				\n				\n					What are states requiring when healthcare uses AI? 				\n				\n					\n				\n		\n					\n				\n				\n									More than most people realize. According to a Manatt Health analysis cited by Becker’s Hospital Review\, lawmakers in 47 states introduced more than 250 bills on healthcare AI in 2025\, and 33 became law across 21 states. A few patterns stand out:  Patients have to be told. Texas’s Responsible Artificial Intelligence Governance Act\, in effect since Jan. 1\, 2026\, requires providers to disclose AI use in a patient’s care. An earlier Texas law\, SB 1188\, also requires practitioners who use AI for diagnosis or treatment recommendations to review AI-generated records. AI-written documentation has to be checked. Rhode Island now requires providers to tell patients when AI is used to document a visit\, and to review that documentation for accuracy. AI can’t have the final word. Iowa allows AI in initial prior authorization reviews\, but it can’t be the sole basis for denying or downgrading a request on medical necessity. California’s AB 1979 protects licensed providers’ professional judgment when AI tools are part of care. Bias has to be monitored. California’s SB 503 requires organizations that deploy clinical decision support tools to monitor them regularly and address biased outcomes. Notice where many of these obligations land: in the patient record\, in documentation review\, in compliance processes. Laws don’t verify AI output. People do.  								\n				\n				\n				\n					Who is responsible when AI makes a mistake? 				\n				\n					\n				\n		\n					\n				\n				\n									That question is now formally on the table. On Oct. 15\, Healthcare Dive reported that the AMA had released a governance framework for AI agents performing clinical functions. It asks four questions of any clinical AI agent:  What clinical function is it performing?What evidence shows it can do that\, and what happens if it fails? What should it be allowed to do\, and under what conditions? Who is responsible for the risks and outcomes? The framework arrives while federal regulation trails the technology\, leaving professional organizations and individual health systems to set guardrails on their own. The same healthcare leader survey found that 72% say agentic AI tools are sometimes put into use without IT approval\, and more than half named compliance violations and unauthorized access to protected health information as major concerns.  That fourth AMA question is the one to sit with if you’re weighing a career in this field. Someone has to own the answer.  								\n				\n				\n				\n					Is AI creating new healthcare jobs? 				\n				\n					\n				\n		\n					\n				\n				\n									At the top of the org chart\, clearly yes. Becker’s Hospital Review now tracks more than 20 health systems that have appointed a chief AI officer or an equivalent executive\, including Cleveland Clinic\, Cedars-Sinai\, Mayo Clinic and\, here in Dallas\, UT Southwestern Medical Center\, which named its first chief AI officer. Becker’s ties the trend to the industry’s recognition that AI carries real risk to patient safety\, professional liability and regulatory compliance.  Look at the titles\, though: chief data and AI officer\, chief analytics and AI officer\, chief medical informatics and AI officer. AI leadership is growing directly out of data governance and informatics. And for every executive setting AI policy\, there are teams doing the daily work of applying it: auditing records\, validating codes\, monitoring workflows\, vetting vendors and keeping the organization compliant. That’s where most healthcare careers touched by AI will actually live.  								\n				\n				\n				\n					What does AI mean for a health information management career? 				\n				\n					\n				\n		\n					\n				\n				\n									Health information management has always been about whether the health record is accurate\, complete and trustworthy. What’s changed is that a growing share of that record may now be drafted\, summarized or coded with help from AI. Rhode Island’s scribe law and Texas’s record review requirements are\, in practical terms\, HIM work.  Parker University’s online Bachelor of Science in Health Information Management has built that reality into its coursework. Dr. Joe Lintz\, Program Director of Health Information Management\, describes the shift this way:  “From an HIM education perspective\, one of the most important shifts is moving from teaching students simply to manage health information to teaching them to critically evaluate information generated by AI.”  In Parker’s Healthcare Data Analytics course\, students receive an AI-generated summary of a patient encounter alongside the original simulated clinical transcript. They cross-reference the summary against the source\, then flag AI hallucinations\, omitted chronic conditions and potentially incorrect billing codes. They also examine how AI coding recommendations could lead to undercoding or upcoding\, and what that means for reimbursement\, billing accuracy and regulatory compliance.  In a clinical course\, students review an AI-generated summary that suggests a diagnosis the physician’s documentation doesn’t support. Their job is to verify it against the record\, identify what’s unsupported and decide on the right next steps. The lesson is simple and non-negotiable: AI-generated information gets validated before it goes into clinical documentation.  “By auditing AI-generated summaries\, validating coding recommendations\, and identifying unsupported diagnoses\, students develop practical AI governance skills. They learn to question AI outputs\, verify supporting evidence\, protect data integrity\, and recognize the limitations of automation.”- Dr. Joe Lintz Dr. Lintz notes these priorities align with the professional competencies emphasized by the Commission on Accreditation for Health Informatics and Information Management Education (CAHIIM)\, which accredits Parker’s HIM program.  								\n				\n				\n				\n					What does AI mean for healthcare administrators? 				\n				\n					\n				\n		\n					\n				\n				\n									If HIM professionals verify what AI produces\, healthcare administrators decide how AI gets used in the first place: which tools are purchased\, who signs off before deployment\, how performance is monitored and who answers when something goes wrong. That 72% figure on tools going live without IT approval is a leadership problem\, not a technical one.  Parker’s online Master of Business Administration is preparing students for exactly that. Dr. Gery Hochanadel II\, Program Director of the MBA\, explains:  “Parker University’s MBA program is not only updating current curriculum with AI content that will help students to balance technical AI skills with critical ethical\, clinical\, and data privacy [considerations] as future leaders\, but also\, we are in the early development of an AI Health Care Management related concentration. This will allow students to become more successful healthcare administrators ready to drive safe innovation.”  								\n				\n					\n				\n		\n					\n				\n				\n							\n			\n						\n		\n						\n				\n				\n				\n					Questions People Are Asking 				\n				\n					\n				\n		\n					\n				\n				\n									Will AI replace health information management jobs? The direction of this year’s laws and frameworks points toward more human review\, not less. Rhode Island\, Texas and other states now require people to review AI-generated documentation\, and the AMA’s framework centers on human accountability. The emphasis in HIM work is shifting from managing records toward validating what AI puts into them.  What is agentic AI in healthcare? Agentic AI refers to tools that can complete multi-step tasks on their own\, such as documenting a visit or monitoring a patient\, without a person approving each step. Because an error can carry forward before a clinician steps in\, groups like the AMA are focused on defining what these tools are allowed to do and who is responsible for them.  Does Texas regulate AI in healthcare? Yes. Since Jan. 1\, 2026\, Texas law has required healthcare providers to disclose to patients when an AI system is used in their care. A separate Texas law in effect since Sept. 1\, 2025\, requires practitioners who use AI for diagnosis or treatment recommendations to disclose that use and review AI-generated records.  Do I need a technology background to work in healthcare AI oversight? Not necessarily. The skills showing up in these new laws and frameworks are verification\, documentation integrity\, compliance and judgment: knowing what a correct record looks like and recognizing when an AI output doesn’t match it. Those are core to health information management and healthcare administration training.  Which Parker University programs prepare students for AI in healthcare? Parker’s online Bachelor of Science in Health Information Management teaches students to audit AI-generated summaries\, validate coding recommendations and identify unsupported diagnoses. Parker’s online MBA is integrating AI content into its curriculum\, with an AI-focused healthcare management concentration in early development.  								\n				\n				\n				\n					Build the skills healthcare AI depends on 				\n				\n					\n				\n		\n					\n				\n				\n									Explore Parker’s online Bachelor of Science in Health Information Management or Master of Business Administration\, or request information to talk with admissions about which path fits your goals. 
URL:https://www.parker.edu/event/alumni-awards-nominations/
ATTACH;FMTTYPE=image/png:https://www.parker.edu/wp-content/uploads/2026/07/ChatGPT-Image-Jul-6-2026-02_44_35-PM.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260706
DTEND;VALUE=DATE:20261102
DTSTAMP:20261021T083612
CREATED:20260706T205823Z
LAST-MODIFIED:20260707T181634Z
UID:173485-1783296000-1793577599@www.parker.edu
SUMMARY:Alumni Board Applications
DESCRIPTION:Quick Answer\n			\n						AI is already drafting clinical notes\, flagging patients at risk of decline\, and suggesting billing codes. The career story in 2026 isn't that AI is doing the work. It's that someone has to verify it. States are writing that verification into law\, major health systems are hiring executives to own it\, and the American Medical Association just released a framework built around one question: who is accountable when AI gets it wrong? Health information management professionals and healthcare administrators are the people most often holding that responsibility.\n			\n						\n									×\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Is AI actually being used in hospitals right now? 				\n				\n					\n				\n		\n					\n				\n				\n									Yes\, and well past the pilot stage at many organizations. In a recent survey of 250 U.S. healthcare leaders reported by Healthcare Dive\, about 28% said their organization had already deployed agentic AI tools\, which can complete multi-step tasks without a person approving each step. Another 44% were running pilots.  One of the clearest examples landed in September. The electronic health record company Epic received FDA clearance for Version 2 of its Deterioration Index\, a tool built into the patient record that scores hospitalized adults from 0 to 100 based on their risk of needing escalated care within a day or dying within three days. It pulls from 195 data points in the record\, including vital signs\, lab results\, nursing assessments and medications.  What makes this story useful for anyone considering a healthcare career is the detail underneath the headline. Hospitals had been using earlier versions of the tool for years before the FDA reviewed it. A 2024 study across seven Yale New Haven Health hospitals ranked the earlier index near the bottom of six early warning scores. A separate study published this summer linked its use at RWJBarnabas Health to an 18% drop in the risk-adjusted odds of in-hospital death among high-risk patients. And in Epic’s own testing data\, the tool caught deterioration less reliably in Black and Hispanic patients than in white patients at its medium-risk threshold\, though that gap narrowed when results were analyzed site by site.  The same tool helped in one setting\, underperformed in another and showed uneven accuracy across patient groups. That isn’t a reason to avoid AI. It’s the reason healthcare needs people trained to ask whether a tool is working\, for whom\, and how anyone would know.  								\n				\n				\n				\n					What are states requiring when healthcare uses AI? 				\n				\n					\n				\n		\n					\n				\n				\n									More than most people realize. According to a Manatt Health analysis cited by Becker’s Hospital Review\, lawmakers in 47 states introduced more than 250 bills on healthcare AI in 2025\, and 33 became law across 21 states. A few patterns stand out:  Patients have to be told. Texas’s Responsible Artificial Intelligence Governance Act\, in effect since Jan. 1\, 2026\, requires providers to disclose AI use in a patient’s care. An earlier Texas law\, SB 1188\, also requires practitioners who use AI for diagnosis or treatment recommendations to review AI-generated records. AI-written documentation has to be checked. Rhode Island now requires providers to tell patients when AI is used to document a visit\, and to review that documentation for accuracy. AI can’t have the final word. Iowa allows AI in initial prior authorization reviews\, but it can’t be the sole basis for denying or downgrading a request on medical necessity. California’s AB 1979 protects licensed providers’ professional judgment when AI tools are part of care. Bias has to be monitored. California’s SB 503 requires organizations that deploy clinical decision support tools to monitor them regularly and address biased outcomes. Notice where many of these obligations land: in the patient record\, in documentation review\, in compliance processes. Laws don’t verify AI output. People do.  								\n				\n				\n				\n					Who is responsible when AI makes a mistake? 				\n				\n					\n				\n		\n					\n				\n				\n									That question is now formally on the table. On Oct. 15\, Healthcare Dive reported that the AMA had released a governance framework for AI agents performing clinical functions. It asks four questions of any clinical AI agent:  What clinical function is it performing?What evidence shows it can do that\, and what happens if it fails? What should it be allowed to do\, and under what conditions? Who is responsible for the risks and outcomes? The framework arrives while federal regulation trails the technology\, leaving professional organizations and individual health systems to set guardrails on their own. The same healthcare leader survey found that 72% say agentic AI tools are sometimes put into use without IT approval\, and more than half named compliance violations and unauthorized access to protected health information as major concerns.  That fourth AMA question is the one to sit with if you’re weighing a career in this field. Someone has to own the answer.  								\n				\n				\n				\n					Is AI creating new healthcare jobs? 				\n				\n					\n				\n		\n					\n				\n				\n									At the top of the org chart\, clearly yes. Becker’s Hospital Review now tracks more than 20 health systems that have appointed a chief AI officer or an equivalent executive\, including Cleveland Clinic\, Cedars-Sinai\, Mayo Clinic and\, here in Dallas\, UT Southwestern Medical Center\, which named its first chief AI officer. Becker’s ties the trend to the industry’s recognition that AI carries real risk to patient safety\, professional liability and regulatory compliance.  Look at the titles\, though: chief data and AI officer\, chief analytics and AI officer\, chief medical informatics and AI officer. AI leadership is growing directly out of data governance and informatics. And for every executive setting AI policy\, there are teams doing the daily work of applying it: auditing records\, validating codes\, monitoring workflows\, vetting vendors and keeping the organization compliant. That’s where most healthcare careers touched by AI will actually live.  								\n				\n				\n				\n					What does AI mean for a health information management career? 				\n				\n					\n				\n		\n					\n				\n				\n									Health information management has always been about whether the health record is accurate\, complete and trustworthy. What’s changed is that a growing share of that record may now be drafted\, summarized or coded with help from AI. Rhode Island’s scribe law and Texas’s record review requirements are\, in practical terms\, HIM work.  Parker University’s online Bachelor of Science in Health Information Management has built that reality into its coursework. Dr. Joe Lintz\, Program Director of Health Information Management\, describes the shift this way:  “From an HIM education perspective\, one of the most important shifts is moving from teaching students simply to manage health information to teaching them to critically evaluate information generated by AI.”  In Parker’s Healthcare Data Analytics course\, students receive an AI-generated summary of a patient encounter alongside the original simulated clinical transcript. They cross-reference the summary against the source\, then flag AI hallucinations\, omitted chronic conditions and potentially incorrect billing codes. They also examine how AI coding recommendations could lead to undercoding or upcoding\, and what that means for reimbursement\, billing accuracy and regulatory compliance.  In a clinical course\, students review an AI-generated summary that suggests a diagnosis the physician’s documentation doesn’t support. Their job is to verify it against the record\, identify what’s unsupported and decide on the right next steps. The lesson is simple and non-negotiable: AI-generated information gets validated before it goes into clinical documentation.  “By auditing AI-generated summaries\, validating coding recommendations\, and identifying unsupported diagnoses\, students develop practical AI governance skills. They learn to question AI outputs\, verify supporting evidence\, protect data integrity\, and recognize the limitations of automation.”- Dr. Joe Lintz Dr. Lintz notes these priorities align with the professional competencies emphasized by the Commission on Accreditation for Health Informatics and Information Management Education (CAHIIM)\, which accredits Parker’s HIM program.  								\n				\n				\n				\n					What does AI mean for healthcare administrators? 				\n				\n					\n				\n		\n					\n				\n				\n									If HIM professionals verify what AI produces\, healthcare administrators decide how AI gets used in the first place: which tools are purchased\, who signs off before deployment\, how performance is monitored and who answers when something goes wrong. That 72% figure on tools going live without IT approval is a leadership problem\, not a technical one.  Parker’s online Master of Business Administration is preparing students for exactly that. Dr. Gery Hochanadel II\, Program Director of the MBA\, explains:  “Parker University’s MBA program is not only updating current curriculum with AI content that will help students to balance technical AI skills with critical ethical\, clinical\, and data privacy [considerations] as future leaders\, but also\, we are in the early development of an AI Health Care Management related concentration. This will allow students to become more successful healthcare administrators ready to drive safe innovation.”  								\n				\n					\n				\n		\n					\n				\n				\n							\n			\n						\n		\n						\n				\n				\n				\n					Questions People Are Asking 				\n				\n					\n				\n		\n					\n				\n				\n									Will AI replace health information management jobs? The direction of this year’s laws and frameworks points toward more human review\, not less. Rhode Island\, Texas and other states now require people to review AI-generated documentation\, and the AMA’s framework centers on human accountability. The emphasis in HIM work is shifting from managing records toward validating what AI puts into them.  What is agentic AI in healthcare? Agentic AI refers to tools that can complete multi-step tasks on their own\, such as documenting a visit or monitoring a patient\, without a person approving each step. Because an error can carry forward before a clinician steps in\, groups like the AMA are focused on defining what these tools are allowed to do and who is responsible for them.  Does Texas regulate AI in healthcare? Yes. Since Jan. 1\, 2026\, Texas law has required healthcare providers to disclose to patients when an AI system is used in their care. A separate Texas law in effect since Sept. 1\, 2025\, requires practitioners who use AI for diagnosis or treatment recommendations to disclose that use and review AI-generated records.  Do I need a technology background to work in healthcare AI oversight? Not necessarily. The skills showing up in these new laws and frameworks are verification\, documentation integrity\, compliance and judgment: knowing what a correct record looks like and recognizing when an AI output doesn’t match it. Those are core to health information management and healthcare administration training.  Which Parker University programs prepare students for AI in healthcare? Parker’s online Bachelor of Science in Health Information Management teaches students to audit AI-generated summaries\, validate coding recommendations and identify unsupported diagnoses. Parker’s online MBA is integrating AI content into its curriculum\, with an AI-focused healthcare management concentration in early development.  								\n				\n				\n				\n					Build the skills healthcare AI depends on 				\n				\n					\n				\n		\n					\n				\n				\n									Explore Parker’s online Bachelor of Science in Health Information Management or Master of Business Administration\, or request information to talk with admissions about which path fits your goals. 
URL:https://www.parker.edu/event/alumni-board-applications/
ATTACH;FMTTYPE=image/png:https://www.parker.edu/wp-content/uploads/2026/07/ChatGPT-Image-Jul-6-2026-02_50_36-PM.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20261022T070000
DTEND;TZID=America/Chicago:20261022T130000
DTSTAMP:20261021T083612
CREATED:20260706T212907Z
LAST-MODIFIED:20261013T171424Z
UID:173494-1792652400-1792674000@www.parker.edu
SUMMARY:Homecoming Golf Tournament
DESCRIPTION:Quick Answer\n			\n						AI is already drafting clinical notes\, flagging patients at risk of decline\, and suggesting billing codes. The career story in 2026 isn't that AI is doing the work. It's that someone has to verify it. States are writing that verification into law\, major health systems are hiring executives to own it\, and the American Medical Association just released a framework built around one question: who is accountable when AI gets it wrong? Health information management professionals and healthcare administrators are the people most often holding that responsibility.\n			\n						\n									×\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Is AI actually being used in hospitals right now? 				\n				\n					\n				\n		\n					\n				\n				\n									Yes\, and well past the pilot stage at many organizations. In a recent survey of 250 U.S. healthcare leaders reported by Healthcare Dive\, about 28% said their organization had already deployed agentic AI tools\, which can complete multi-step tasks without a person approving each step. Another 44% were running pilots.  One of the clearest examples landed in September. The electronic health record company Epic received FDA clearance for Version 2 of its Deterioration Index\, a tool built into the patient record that scores hospitalized adults from 0 to 100 based on their risk of needing escalated care within a day or dying within three days. It pulls from 195 data points in the record\, including vital signs\, lab results\, nursing assessments and medications.  What makes this story useful for anyone considering a healthcare career is the detail underneath the headline. Hospitals had been using earlier versions of the tool for years before the FDA reviewed it. A 2024 study across seven Yale New Haven Health hospitals ranked the earlier index near the bottom of six early warning scores. A separate study published this summer linked its use at RWJBarnabas Health to an 18% drop in the risk-adjusted odds of in-hospital death among high-risk patients. And in Epic’s own testing data\, the tool caught deterioration less reliably in Black and Hispanic patients than in white patients at its medium-risk threshold\, though that gap narrowed when results were analyzed site by site.  The same tool helped in one setting\, underperformed in another and showed uneven accuracy across patient groups. That isn’t a reason to avoid AI. It’s the reason healthcare needs people trained to ask whether a tool is working\, for whom\, and how anyone would know.  								\n				\n				\n				\n					What are states requiring when healthcare uses AI? 				\n				\n					\n				\n		\n					\n				\n				\n									More than most people realize. According to a Manatt Health analysis cited by Becker’s Hospital Review\, lawmakers in 47 states introduced more than 250 bills on healthcare AI in 2025\, and 33 became law across 21 states. A few patterns stand out:  Patients have to be told. Texas’s Responsible Artificial Intelligence Governance Act\, in effect since Jan. 1\, 2026\, requires providers to disclose AI use in a patient’s care. An earlier Texas law\, SB 1188\, also requires practitioners who use AI for diagnosis or treatment recommendations to review AI-generated records. AI-written documentation has to be checked. Rhode Island now requires providers to tell patients when AI is used to document a visit\, and to review that documentation for accuracy. AI can’t have the final word. Iowa allows AI in initial prior authorization reviews\, but it can’t be the sole basis for denying or downgrading a request on medical necessity. California’s AB 1979 protects licensed providers’ professional judgment when AI tools are part of care. Bias has to be monitored. California’s SB 503 requires organizations that deploy clinical decision support tools to monitor them regularly and address biased outcomes. Notice where many of these obligations land: in the patient record\, in documentation review\, in compliance processes. Laws don’t verify AI output. People do.  								\n				\n				\n				\n					Who is responsible when AI makes a mistake? 				\n				\n					\n				\n		\n					\n				\n				\n									That question is now formally on the table. On Oct. 15\, Healthcare Dive reported that the AMA had released a governance framework for AI agents performing clinical functions. It asks four questions of any clinical AI agent:  What clinical function is it performing?What evidence shows it can do that\, and what happens if it fails? What should it be allowed to do\, and under what conditions? Who is responsible for the risks and outcomes? The framework arrives while federal regulation trails the technology\, leaving professional organizations and individual health systems to set guardrails on their own. The same healthcare leader survey found that 72% say agentic AI tools are sometimes put into use without IT approval\, and more than half named compliance violations and unauthorized access to protected health information as major concerns.  That fourth AMA question is the one to sit with if you’re weighing a career in this field. Someone has to own the answer.  								\n				\n				\n				\n					Is AI creating new healthcare jobs? 				\n				\n					\n				\n		\n					\n				\n				\n									At the top of the org chart\, clearly yes. Becker’s Hospital Review now tracks more than 20 health systems that have appointed a chief AI officer or an equivalent executive\, including Cleveland Clinic\, Cedars-Sinai\, Mayo Clinic and\, here in Dallas\, UT Southwestern Medical Center\, which named its first chief AI officer. Becker’s ties the trend to the industry’s recognition that AI carries real risk to patient safety\, professional liability and regulatory compliance.  Look at the titles\, though: chief data and AI officer\, chief analytics and AI officer\, chief medical informatics and AI officer. AI leadership is growing directly out of data governance and informatics. And for every executive setting AI policy\, there are teams doing the daily work of applying it: auditing records\, validating codes\, monitoring workflows\, vetting vendors and keeping the organization compliant. That’s where most healthcare careers touched by AI will actually live.  								\n				\n				\n				\n					What does AI mean for a health information management career? 				\n				\n					\n				\n		\n					\n				\n				\n									Health information management has always been about whether the health record is accurate\, complete and trustworthy. What’s changed is that a growing share of that record may now be drafted\, summarized or coded with help from AI. Rhode Island’s scribe law and Texas’s record review requirements are\, in practical terms\, HIM work.  Parker University’s online Bachelor of Science in Health Information Management has built that reality into its coursework. Dr. Joe Lintz\, Program Director of Health Information Management\, describes the shift this way:  “From an HIM education perspective\, one of the most important shifts is moving from teaching students simply to manage health information to teaching them to critically evaluate information generated by AI.”  In Parker’s Healthcare Data Analytics course\, students receive an AI-generated summary of a patient encounter alongside the original simulated clinical transcript. They cross-reference the summary against the source\, then flag AI hallucinations\, omitted chronic conditions and potentially incorrect billing codes. They also examine how AI coding recommendations could lead to undercoding or upcoding\, and what that means for reimbursement\, billing accuracy and regulatory compliance.  In a clinical course\, students review an AI-generated summary that suggests a diagnosis the physician’s documentation doesn’t support. Their job is to verify it against the record\, identify what’s unsupported and decide on the right next steps. The lesson is simple and non-negotiable: AI-generated information gets validated before it goes into clinical documentation.  “By auditing AI-generated summaries\, validating coding recommendations\, and identifying unsupported diagnoses\, students develop practical AI governance skills. They learn to question AI outputs\, verify supporting evidence\, protect data integrity\, and recognize the limitations of automation.”- Dr. Joe Lintz Dr. Lintz notes these priorities align with the professional competencies emphasized by the Commission on Accreditation for Health Informatics and Information Management Education (CAHIIM)\, which accredits Parker’s HIM program.  								\n				\n				\n				\n					What does AI mean for healthcare administrators? 				\n				\n					\n				\n		\n					\n				\n				\n									If HIM professionals verify what AI produces\, healthcare administrators decide how AI gets used in the first place: which tools are purchased\, who signs off before deployment\, how performance is monitored and who answers when something goes wrong. That 72% figure on tools going live without IT approval is a leadership problem\, not a technical one.  Parker’s online Master of Business Administration is preparing students for exactly that. Dr. Gery Hochanadel II\, Program Director of the MBA\, explains:  “Parker University’s MBA program is not only updating current curriculum with AI content that will help students to balance technical AI skills with critical ethical\, clinical\, and data privacy [considerations] as future leaders\, but also\, we are in the early development of an AI Health Care Management related concentration. This will allow students to become more successful healthcare administrators ready to drive safe innovation.”  								\n				\n					\n				\n		\n					\n				\n				\n							\n			\n						\n		\n						\n				\n				\n				\n					Questions People Are Asking 				\n				\n					\n				\n		\n					\n				\n				\n									Will AI replace health information management jobs? The direction of this year’s laws and frameworks points toward more human review\, not less. Rhode Island\, Texas and other states now require people to review AI-generated documentation\, and the AMA’s framework centers on human accountability. The emphasis in HIM work is shifting from managing records toward validating what AI puts into them.  What is agentic AI in healthcare? Agentic AI refers to tools that can complete multi-step tasks on their own\, such as documenting a visit or monitoring a patient\, without a person approving each step. Because an error can carry forward before a clinician steps in\, groups like the AMA are focused on defining what these tools are allowed to do and who is responsible for them.  Does Texas regulate AI in healthcare? Yes. Since Jan. 1\, 2026\, Texas law has required healthcare providers to disclose to patients when an AI system is used in their care. A separate Texas law in effect since Sept. 1\, 2025\, requires practitioners who use AI for diagnosis or treatment recommendations to disclose that use and review AI-generated records.  Do I need a technology background to work in healthcare AI oversight? Not necessarily. The skills showing up in these new laws and frameworks are verification\, documentation integrity\, compliance and judgment: knowing what a correct record looks like and recognizing when an AI output doesn’t match it. Those are core to health information management and healthcare administration training.  Which Parker University programs prepare students for AI in healthcare? Parker’s online Bachelor of Science in Health Information Management teaches students to audit AI-generated summaries\, validate coding recommendations and identify unsupported diagnoses. Parker’s online MBA is integrating AI content into its curriculum\, with an AI-focused healthcare management concentration in early development.  								\n				\n				\n				\n					Build the skills healthcare AI depends on 				\n				\n					\n				\n		\n					\n				\n				\n									Explore Parker’s online Bachelor of Science in Health Information Management or Master of Business Administration\, or request information to talk with admissions about which path fits your goals. 
URL:https://www.parker.edu/event/homecoming-golf-tournament/
LOCATION:The Creeks Course at Indian Creek Golf Club\, 1650 W Frankford Rd\, Carrollton\, TX\, United States
ATTACH;FMTTYPE=image/jpeg:https://www.parker.edu/wp-content/uploads/2026/07/Parker-Seminars-Dallas-100225-1578-ZL.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20261029T180000
DTEND;TZID=America/Chicago:20261029T200000
DTSTAMP:20261021T083612
CREATED:20261008T160720Z
LAST-MODIFIED:20261008T163535Z
UID:181129-1793296800-1793304000@www.parker.edu
SUMMARY:Halloween Pickleball Mentoring Mixer
DESCRIPTION:Quick Answer\n			\n						AI is already drafting clinical notes\, flagging patients at risk of decline\, and suggesting billing codes. The career story in 2026 isn't that AI is doing the work. It's that someone has to verify it. States are writing that verification into law\, major health systems are hiring executives to own it\, and the American Medical Association just released a framework built around one question: who is accountable when AI gets it wrong? Health information management professionals and healthcare administrators are the people most often holding that responsibility.\n			\n						\n									×\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Is AI actually being used in hospitals right now? 				\n				\n					\n				\n		\n					\n				\n				\n									Yes\, and well past the pilot stage at many organizations. In a recent survey of 250 U.S. healthcare leaders reported by Healthcare Dive\, about 28% said their organization had already deployed agentic AI tools\, which can complete multi-step tasks without a person approving each step. Another 44% were running pilots.  One of the clearest examples landed in September. The electronic health record company Epic received FDA clearance for Version 2 of its Deterioration Index\, a tool built into the patient record that scores hospitalized adults from 0 to 100 based on their risk of needing escalated care within a day or dying within three days. It pulls from 195 data points in the record\, including vital signs\, lab results\, nursing assessments and medications.  What makes this story useful for anyone considering a healthcare career is the detail underneath the headline. Hospitals had been using earlier versions of the tool for years before the FDA reviewed it. A 2024 study across seven Yale New Haven Health hospitals ranked the earlier index near the bottom of six early warning scores. A separate study published this summer linked its use at RWJBarnabas Health to an 18% drop in the risk-adjusted odds of in-hospital death among high-risk patients. And in Epic’s own testing data\, the tool caught deterioration less reliably in Black and Hispanic patients than in white patients at its medium-risk threshold\, though that gap narrowed when results were analyzed site by site.  The same tool helped in one setting\, underperformed in another and showed uneven accuracy across patient groups. That isn’t a reason to avoid AI. It’s the reason healthcare needs people trained to ask whether a tool is working\, for whom\, and how anyone would know.  								\n				\n				\n				\n					What are states requiring when healthcare uses AI? 				\n				\n					\n				\n		\n					\n				\n				\n									More than most people realize. According to a Manatt Health analysis cited by Becker’s Hospital Review\, lawmakers in 47 states introduced more than 250 bills on healthcare AI in 2025\, and 33 became law across 21 states. A few patterns stand out:  Patients have to be told. Texas’s Responsible Artificial Intelligence Governance Act\, in effect since Jan. 1\, 2026\, requires providers to disclose AI use in a patient’s care. An earlier Texas law\, SB 1188\, also requires practitioners who use AI for diagnosis or treatment recommendations to review AI-generated records. AI-written documentation has to be checked. Rhode Island now requires providers to tell patients when AI is used to document a visit\, and to review that documentation for accuracy. AI can’t have the final word. Iowa allows AI in initial prior authorization reviews\, but it can’t be the sole basis for denying or downgrading a request on medical necessity. California’s AB 1979 protects licensed providers’ professional judgment when AI tools are part of care. Bias has to be monitored. California’s SB 503 requires organizations that deploy clinical decision support tools to monitor them regularly and address biased outcomes. Notice where many of these obligations land: in the patient record\, in documentation review\, in compliance processes. Laws don’t verify AI output. People do.  								\n				\n				\n				\n					Who is responsible when AI makes a mistake? 				\n				\n					\n				\n		\n					\n				\n				\n									That question is now formally on the table. On Oct. 15\, Healthcare Dive reported that the AMA had released a governance framework for AI agents performing clinical functions. It asks four questions of any clinical AI agent:  What clinical function is it performing?What evidence shows it can do that\, and what happens if it fails? What should it be allowed to do\, and under what conditions? Who is responsible for the risks and outcomes? The framework arrives while federal regulation trails the technology\, leaving professional organizations and individual health systems to set guardrails on their own. The same healthcare leader survey found that 72% say agentic AI tools are sometimes put into use without IT approval\, and more than half named compliance violations and unauthorized access to protected health information as major concerns.  That fourth AMA question is the one to sit with if you’re weighing a career in this field. Someone has to own the answer.  								\n				\n				\n				\n					Is AI creating new healthcare jobs? 				\n				\n					\n				\n		\n					\n				\n				\n									At the top of the org chart\, clearly yes. Becker’s Hospital Review now tracks more than 20 health systems that have appointed a chief AI officer or an equivalent executive\, including Cleveland Clinic\, Cedars-Sinai\, Mayo Clinic and\, here in Dallas\, UT Southwestern Medical Center\, which named its first chief AI officer. Becker’s ties the trend to the industry’s recognition that AI carries real risk to patient safety\, professional liability and regulatory compliance.  Look at the titles\, though: chief data and AI officer\, chief analytics and AI officer\, chief medical informatics and AI officer. AI leadership is growing directly out of data governance and informatics. And for every executive setting AI policy\, there are teams doing the daily work of applying it: auditing records\, validating codes\, monitoring workflows\, vetting vendors and keeping the organization compliant. That’s where most healthcare careers touched by AI will actually live.  								\n				\n				\n				\n					What does AI mean for a health information management career? 				\n				\n					\n				\n		\n					\n				\n				\n									Health information management has always been about whether the health record is accurate\, complete and trustworthy. What’s changed is that a growing share of that record may now be drafted\, summarized or coded with help from AI. Rhode Island’s scribe law and Texas’s record review requirements are\, in practical terms\, HIM work.  Parker University’s online Bachelor of Science in Health Information Management has built that reality into its coursework. Dr. Joe Lintz\, Program Director of Health Information Management\, describes the shift this way:  “From an HIM education perspective\, one of the most important shifts is moving from teaching students simply to manage health information to teaching them to critically evaluate information generated by AI.”  In Parker’s Healthcare Data Analytics course\, students receive an AI-generated summary of a patient encounter alongside the original simulated clinical transcript. They cross-reference the summary against the source\, then flag AI hallucinations\, omitted chronic conditions and potentially incorrect billing codes. They also examine how AI coding recommendations could lead to undercoding or upcoding\, and what that means for reimbursement\, billing accuracy and regulatory compliance.  In a clinical course\, students review an AI-generated summary that suggests a diagnosis the physician’s documentation doesn’t support. Their job is to verify it against the record\, identify what’s unsupported and decide on the right next steps. The lesson is simple and non-negotiable: AI-generated information gets validated before it goes into clinical documentation.  “By auditing AI-generated summaries\, validating coding recommendations\, and identifying unsupported diagnoses\, students develop practical AI governance skills. They learn to question AI outputs\, verify supporting evidence\, protect data integrity\, and recognize the limitations of automation.”- Dr. Joe Lintz Dr. Lintz notes these priorities align with the professional competencies emphasized by the Commission on Accreditation for Health Informatics and Information Management Education (CAHIIM)\, which accredits Parker’s HIM program.  								\n				\n				\n				\n					What does AI mean for healthcare administrators? 				\n				\n					\n				\n		\n					\n				\n				\n									If HIM professionals verify what AI produces\, healthcare administrators decide how AI gets used in the first place: which tools are purchased\, who signs off before deployment\, how performance is monitored and who answers when something goes wrong. That 72% figure on tools going live without IT approval is a leadership problem\, not a technical one.  Parker’s online Master of Business Administration is preparing students for exactly that. Dr. Gery Hochanadel II\, Program Director of the MBA\, explains:  “Parker University’s MBA program is not only updating current curriculum with AI content that will help students to balance technical AI skills with critical ethical\, clinical\, and data privacy [considerations] as future leaders\, but also\, we are in the early development of an AI Health Care Management related concentration. This will allow students to become more successful healthcare administrators ready to drive safe innovation.”  								\n				\n					\n				\n		\n					\n				\n				\n							\n			\n						\n		\n						\n				\n				\n				\n					Questions People Are Asking 				\n				\n					\n				\n		\n					\n				\n				\n									Will AI replace health information management jobs? The direction of this year’s laws and frameworks points toward more human review\, not less. Rhode Island\, Texas and other states now require people to review AI-generated documentation\, and the AMA’s framework centers on human accountability. The emphasis in HIM work is shifting from managing records toward validating what AI puts into them.  What is agentic AI in healthcare? Agentic AI refers to tools that can complete multi-step tasks on their own\, such as documenting a visit or monitoring a patient\, without a person approving each step. Because an error can carry forward before a clinician steps in\, groups like the AMA are focused on defining what these tools are allowed to do and who is responsible for them.  Does Texas regulate AI in healthcare? Yes. Since Jan. 1\, 2026\, Texas law has required healthcare providers to disclose to patients when an AI system is used in their care. A separate Texas law in effect since Sept. 1\, 2025\, requires practitioners who use AI for diagnosis or treatment recommendations to disclose that use and review AI-generated records.  Do I need a technology background to work in healthcare AI oversight? Not necessarily. The skills showing up in these new laws and frameworks are verification\, documentation integrity\, compliance and judgment: knowing what a correct record looks like and recognizing when an AI output doesn’t match it. Those are core to health information management and healthcare administration training.  Which Parker University programs prepare students for AI in healthcare? Parker’s online Bachelor of Science in Health Information Management teaches students to audit AI-generated summaries\, validate coding recommendations and identify unsupported diagnoses. Parker’s online MBA is integrating AI content into its curriculum\, with an AI-focused healthcare management concentration in early development.  								\n				\n				\n				\n					Build the skills healthcare AI depends on 				\n				\n					\n				\n		\n					\n				\n				\n									Explore Parker’s online Bachelor of Science in Health Information Management or Master of Business Administration\, or request information to talk with admissions about which path fits your goals. 
URL:https://www.parker.edu/event/halloween-pickleball-mentoring-mixer/
LOCATION:Westside Pickleball Club\, 9203 Denton Dr.\, Dallas\, TX\, 75235\, United States
ATTACH;FMTTYPE=image/jpeg:https://www.parker.edu/wp-content/uploads/2026/10/10.29-Pickleball-Social-Media-Flyer-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20261110T110000
DTEND;TZID=America/Chicago:20261110T130000
DTSTAMP:20261021T083612
CREATED:20261006T143538Z
LAST-MODIFIED:20261006T144805Z
UID:181074-1794308400-1794315600@www.parker.edu
SUMMARY:Fall 2026 Career and Resource Fair
DESCRIPTION:Quick Answer\n			\n						AI is already drafting clinical notes\, flagging patients at risk of decline\, and suggesting billing codes. The career story in 2026 isn't that AI is doing the work. It's that someone has to verify it. States are writing that verification into law\, major health systems are hiring executives to own it\, and the American Medical Association just released a framework built around one question: who is accountable when AI gets it wrong? Health information management professionals and healthcare administrators are the people most often holding that responsibility.\n			\n						\n									×\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Is AI actually being used in hospitals right now? 				\n				\n					\n				\n		\n					\n				\n				\n									Yes\, and well past the pilot stage at many organizations. In a recent survey of 250 U.S. healthcare leaders reported by Healthcare Dive\, about 28% said their organization had already deployed agentic AI tools\, which can complete multi-step tasks without a person approving each step. Another 44% were running pilots.  One of the clearest examples landed in September. The electronic health record company Epic received FDA clearance for Version 2 of its Deterioration Index\, a tool built into the patient record that scores hospitalized adults from 0 to 100 based on their risk of needing escalated care within a day or dying within three days. It pulls from 195 data points in the record\, including vital signs\, lab results\, nursing assessments and medications.  What makes this story useful for anyone considering a healthcare career is the detail underneath the headline. Hospitals had been using earlier versions of the tool for years before the FDA reviewed it. A 2024 study across seven Yale New Haven Health hospitals ranked the earlier index near the bottom of six early warning scores. A separate study published this summer linked its use at RWJBarnabas Health to an 18% drop in the risk-adjusted odds of in-hospital death among high-risk patients. And in Epic’s own testing data\, the tool caught deterioration less reliably in Black and Hispanic patients than in white patients at its medium-risk threshold\, though that gap narrowed when results were analyzed site by site.  The same tool helped in one setting\, underperformed in another and showed uneven accuracy across patient groups. That isn’t a reason to avoid AI. It’s the reason healthcare needs people trained to ask whether a tool is working\, for whom\, and how anyone would know.  								\n				\n				\n				\n					What are states requiring when healthcare uses AI? 				\n				\n					\n				\n		\n					\n				\n				\n									More than most people realize. According to a Manatt Health analysis cited by Becker’s Hospital Review\, lawmakers in 47 states introduced more than 250 bills on healthcare AI in 2025\, and 33 became law across 21 states. A few patterns stand out:  Patients have to be told. Texas’s Responsible Artificial Intelligence Governance Act\, in effect since Jan. 1\, 2026\, requires providers to disclose AI use in a patient’s care. An earlier Texas law\, SB 1188\, also requires practitioners who use AI for diagnosis or treatment recommendations to review AI-generated records. AI-written documentation has to be checked. Rhode Island now requires providers to tell patients when AI is used to document a visit\, and to review that documentation for accuracy. AI can’t have the final word. Iowa allows AI in initial prior authorization reviews\, but it can’t be the sole basis for denying or downgrading a request on medical necessity. California’s AB 1979 protects licensed providers’ professional judgment when AI tools are part of care. Bias has to be monitored. California’s SB 503 requires organizations that deploy clinical decision support tools to monitor them regularly and address biased outcomes. Notice where many of these obligations land: in the patient record\, in documentation review\, in compliance processes. Laws don’t verify AI output. People do.  								\n				\n				\n				\n					Who is responsible when AI makes a mistake? 				\n				\n					\n				\n		\n					\n				\n				\n									That question is now formally on the table. On Oct. 15\, Healthcare Dive reported that the AMA had released a governance framework for AI agents performing clinical functions. It asks four questions of any clinical AI agent:  What clinical function is it performing?What evidence shows it can do that\, and what happens if it fails? What should it be allowed to do\, and under what conditions? Who is responsible for the risks and outcomes? The framework arrives while federal regulation trails the technology\, leaving professional organizations and individual health systems to set guardrails on their own. The same healthcare leader survey found that 72% say agentic AI tools are sometimes put into use without IT approval\, and more than half named compliance violations and unauthorized access to protected health information as major concerns.  That fourth AMA question is the one to sit with if you’re weighing a career in this field. Someone has to own the answer.  								\n				\n				\n				\n					Is AI creating new healthcare jobs? 				\n				\n					\n				\n		\n					\n				\n				\n									At the top of the org chart\, clearly yes. Becker’s Hospital Review now tracks more than 20 health systems that have appointed a chief AI officer or an equivalent executive\, including Cleveland Clinic\, Cedars-Sinai\, Mayo Clinic and\, here in Dallas\, UT Southwestern Medical Center\, which named its first chief AI officer. Becker’s ties the trend to the industry’s recognition that AI carries real risk to patient safety\, professional liability and regulatory compliance.  Look at the titles\, though: chief data and AI officer\, chief analytics and AI officer\, chief medical informatics and AI officer. AI leadership is growing directly out of data governance and informatics. And for every executive setting AI policy\, there are teams doing the daily work of applying it: auditing records\, validating codes\, monitoring workflows\, vetting vendors and keeping the organization compliant. That’s where most healthcare careers touched by AI will actually live.  								\n				\n				\n				\n					What does AI mean for a health information management career? 				\n				\n					\n				\n		\n					\n				\n				\n									Health information management has always been about whether the health record is accurate\, complete and trustworthy. What’s changed is that a growing share of that record may now be drafted\, summarized or coded with help from AI. Rhode Island’s scribe law and Texas’s record review requirements are\, in practical terms\, HIM work.  Parker University’s online Bachelor of Science in Health Information Management has built that reality into its coursework. Dr. Joe Lintz\, Program Director of Health Information Management\, describes the shift this way:  “From an HIM education perspective\, one of the most important shifts is moving from teaching students simply to manage health information to teaching them to critically evaluate information generated by AI.”  In Parker’s Healthcare Data Analytics course\, students receive an AI-generated summary of a patient encounter alongside the original simulated clinical transcript. They cross-reference the summary against the source\, then flag AI hallucinations\, omitted chronic conditions and potentially incorrect billing codes. They also examine how AI coding recommendations could lead to undercoding or upcoding\, and what that means for reimbursement\, billing accuracy and regulatory compliance.  In a clinical course\, students review an AI-generated summary that suggests a diagnosis the physician’s documentation doesn’t support. Their job is to verify it against the record\, identify what’s unsupported and decide on the right next steps. The lesson is simple and non-negotiable: AI-generated information gets validated before it goes into clinical documentation.  “By auditing AI-generated summaries\, validating coding recommendations\, and identifying unsupported diagnoses\, students develop practical AI governance skills. They learn to question AI outputs\, verify supporting evidence\, protect data integrity\, and recognize the limitations of automation.”- Dr. Joe Lintz Dr. Lintz notes these priorities align with the professional competencies emphasized by the Commission on Accreditation for Health Informatics and Information Management Education (CAHIIM)\, which accredits Parker’s HIM program.  								\n				\n				\n				\n					What does AI mean for healthcare administrators? 				\n				\n					\n				\n		\n					\n				\n				\n									If HIM professionals verify what AI produces\, healthcare administrators decide how AI gets used in the first place: which tools are purchased\, who signs off before deployment\, how performance is monitored and who answers when something goes wrong. That 72% figure on tools going live without IT approval is a leadership problem\, not a technical one.  Parker’s online Master of Business Administration is preparing students for exactly that. Dr. Gery Hochanadel II\, Program Director of the MBA\, explains:  “Parker University’s MBA program is not only updating current curriculum with AI content that will help students to balance technical AI skills with critical ethical\, clinical\, and data privacy [considerations] as future leaders\, but also\, we are in the early development of an AI Health Care Management related concentration. This will allow students to become more successful healthcare administrators ready to drive safe innovation.”  								\n				\n					\n				\n		\n					\n				\n				\n							\n			\n						\n		\n						\n				\n				\n				\n					Questions People Are Asking 				\n				\n					\n				\n		\n					\n				\n				\n									Will AI replace health information management jobs? The direction of this year’s laws and frameworks points toward more human review\, not less. Rhode Island\, Texas and other states now require people to review AI-generated documentation\, and the AMA’s framework centers on human accountability. The emphasis in HIM work is shifting from managing records toward validating what AI puts into them.  What is agentic AI in healthcare? Agentic AI refers to tools that can complete multi-step tasks on their own\, such as documenting a visit or monitoring a patient\, without a person approving each step. Because an error can carry forward before a clinician steps in\, groups like the AMA are focused on defining what these tools are allowed to do and who is responsible for them.  Does Texas regulate AI in healthcare? Yes. Since Jan. 1\, 2026\, Texas law has required healthcare providers to disclose to patients when an AI system is used in their care. A separate Texas law in effect since Sept. 1\, 2025\, requires practitioners who use AI for diagnosis or treatment recommendations to disclose that use and review AI-generated records.  Do I need a technology background to work in healthcare AI oversight? Not necessarily. The skills showing up in these new laws and frameworks are verification\, documentation integrity\, compliance and judgment: knowing what a correct record looks like and recognizing when an AI output doesn’t match it. Those are core to health information management and healthcare administration training.  Which Parker University programs prepare students for AI in healthcare? Parker’s online Bachelor of Science in Health Information Management teaches students to audit AI-generated summaries\, validate coding recommendations and identify unsupported diagnoses. Parker’s online MBA is integrating AI content into its curriculum\, with an AI-focused healthcare management concentration in early development.  								\n				\n				\n				\n					Build the skills healthcare AI depends on 				\n				\n					\n				\n		\n					\n				\n				\n									Explore Parker’s online Bachelor of Science in Health Information Management or Master of Business Administration\, or request information to talk with admissions about which path fits your goals. 
URL:https://www.parker.edu/event/fall-2026-career-and-resource-fair/
LOCATION:Standard Process Student Activity Center
ATTACH;FMTTYPE=image/png:https://www.parker.edu/wp-content/uploads/2026/10/Career-Fair-Instagram-Post.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20261111T113000
DTEND;TZID=America/Chicago:20261111T130000
DTSTAMP:20261021T083612
CREATED:20261014T193717Z
LAST-MODIFIED:20261014T193717Z
UID:181211-1794396600-1794402000@www.parker.edu
SUMMARY:Veteran's Day Luncheon
DESCRIPTION:Quick Answer\n			\n						AI is already drafting clinical notes\, flagging patients at risk of decline\, and suggesting billing codes. The career story in 2026 isn't that AI is doing the work. It's that someone has to verify it. States are writing that verification into law\, major health systems are hiring executives to own it\, and the American Medical Association just released a framework built around one question: who is accountable when AI gets it wrong? Health information management professionals and healthcare administrators are the people most often holding that responsibility.\n			\n						\n									×\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Is AI actually being used in hospitals right now? 				\n				\n					\n				\n		\n					\n				\n				\n									Yes\, and well past the pilot stage at many organizations. In a recent survey of 250 U.S. healthcare leaders reported by Healthcare Dive\, about 28% said their organization had already deployed agentic AI tools\, which can complete multi-step tasks without a person approving each step. Another 44% were running pilots.  One of the clearest examples landed in September. The electronic health record company Epic received FDA clearance for Version 2 of its Deterioration Index\, a tool built into the patient record that scores hospitalized adults from 0 to 100 based on their risk of needing escalated care within a day or dying within three days. It pulls from 195 data points in the record\, including vital signs\, lab results\, nursing assessments and medications.  What makes this story useful for anyone considering a healthcare career is the detail underneath the headline. Hospitals had been using earlier versions of the tool for years before the FDA reviewed it. A 2024 study across seven Yale New Haven Health hospitals ranked the earlier index near the bottom of six early warning scores. A separate study published this summer linked its use at RWJBarnabas Health to an 18% drop in the risk-adjusted odds of in-hospital death among high-risk patients. And in Epic’s own testing data\, the tool caught deterioration less reliably in Black and Hispanic patients than in white patients at its medium-risk threshold\, though that gap narrowed when results were analyzed site by site.  The same tool helped in one setting\, underperformed in another and showed uneven accuracy across patient groups. That isn’t a reason to avoid AI. It’s the reason healthcare needs people trained to ask whether a tool is working\, for whom\, and how anyone would know.  								\n				\n				\n				\n					What are states requiring when healthcare uses AI? 				\n				\n					\n				\n		\n					\n				\n				\n									More than most people realize. According to a Manatt Health analysis cited by Becker’s Hospital Review\, lawmakers in 47 states introduced more than 250 bills on healthcare AI in 2025\, and 33 became law across 21 states. A few patterns stand out:  Patients have to be told. Texas’s Responsible Artificial Intelligence Governance Act\, in effect since Jan. 1\, 2026\, requires providers to disclose AI use in a patient’s care. An earlier Texas law\, SB 1188\, also requires practitioners who use AI for diagnosis or treatment recommendations to review AI-generated records. AI-written documentation has to be checked. Rhode Island now requires providers to tell patients when AI is used to document a visit\, and to review that documentation for accuracy. AI can’t have the final word. Iowa allows AI in initial prior authorization reviews\, but it can’t be the sole basis for denying or downgrading a request on medical necessity. California’s AB 1979 protects licensed providers’ professional judgment when AI tools are part of care. Bias has to be monitored. California’s SB 503 requires organizations that deploy clinical decision support tools to monitor them regularly and address biased outcomes. Notice where many of these obligations land: in the patient record\, in documentation review\, in compliance processes. Laws don’t verify AI output. People do.  								\n				\n				\n				\n					Who is responsible when AI makes a mistake? 				\n				\n					\n				\n		\n					\n				\n				\n									That question is now formally on the table. On Oct. 15\, Healthcare Dive reported that the AMA had released a governance framework for AI agents performing clinical functions. It asks four questions of any clinical AI agent:  What clinical function is it performing?What evidence shows it can do that\, and what happens if it fails? What should it be allowed to do\, and under what conditions? Who is responsible for the risks and outcomes? The framework arrives while federal regulation trails the technology\, leaving professional organizations and individual health systems to set guardrails on their own. The same healthcare leader survey found that 72% say agentic AI tools are sometimes put into use without IT approval\, and more than half named compliance violations and unauthorized access to protected health information as major concerns.  That fourth AMA question is the one to sit with if you’re weighing a career in this field. Someone has to own the answer.  								\n				\n				\n				\n					Is AI creating new healthcare jobs? 				\n				\n					\n				\n		\n					\n				\n				\n									At the top of the org chart\, clearly yes. Becker’s Hospital Review now tracks more than 20 health systems that have appointed a chief AI officer or an equivalent executive\, including Cleveland Clinic\, Cedars-Sinai\, Mayo Clinic and\, here in Dallas\, UT Southwestern Medical Center\, which named its first chief AI officer. Becker’s ties the trend to the industry’s recognition that AI carries real risk to patient safety\, professional liability and regulatory compliance.  Look at the titles\, though: chief data and AI officer\, chief analytics and AI officer\, chief medical informatics and AI officer. AI leadership is growing directly out of data governance and informatics. And for every executive setting AI policy\, there are teams doing the daily work of applying it: auditing records\, validating codes\, monitoring workflows\, vetting vendors and keeping the organization compliant. That’s where most healthcare careers touched by AI will actually live.  								\n				\n				\n				\n					What does AI mean for a health information management career? 				\n				\n					\n				\n		\n					\n				\n				\n									Health information management has always been about whether the health record is accurate\, complete and trustworthy. What’s changed is that a growing share of that record may now be drafted\, summarized or coded with help from AI. Rhode Island’s scribe law and Texas’s record review requirements are\, in practical terms\, HIM work.  Parker University’s online Bachelor of Science in Health Information Management has built that reality into its coursework. Dr. Joe Lintz\, Program Director of Health Information Management\, describes the shift this way:  “From an HIM education perspective\, one of the most important shifts is moving from teaching students simply to manage health information to teaching them to critically evaluate information generated by AI.”  In Parker’s Healthcare Data Analytics course\, students receive an AI-generated summary of a patient encounter alongside the original simulated clinical transcript. They cross-reference the summary against the source\, then flag AI hallucinations\, omitted chronic conditions and potentially incorrect billing codes. They also examine how AI coding recommendations could lead to undercoding or upcoding\, and what that means for reimbursement\, billing accuracy and regulatory compliance.  In a clinical course\, students review an AI-generated summary that suggests a diagnosis the physician’s documentation doesn’t support. Their job is to verify it against the record\, identify what’s unsupported and decide on the right next steps. The lesson is simple and non-negotiable: AI-generated information gets validated before it goes into clinical documentation.  “By auditing AI-generated summaries\, validating coding recommendations\, and identifying unsupported diagnoses\, students develop practical AI governance skills. They learn to question AI outputs\, verify supporting evidence\, protect data integrity\, and recognize the limitations of automation.”- Dr. Joe Lintz Dr. Lintz notes these priorities align with the professional competencies emphasized by the Commission on Accreditation for Health Informatics and Information Management Education (CAHIIM)\, which accredits Parker’s HIM program.  								\n				\n				\n				\n					What does AI mean for healthcare administrators? 				\n				\n					\n				\n		\n					\n				\n				\n									If HIM professionals verify what AI produces\, healthcare administrators decide how AI gets used in the first place: which tools are purchased\, who signs off before deployment\, how performance is monitored and who answers when something goes wrong. That 72% figure on tools going live without IT approval is a leadership problem\, not a technical one.  Parker’s online Master of Business Administration is preparing students for exactly that. Dr. Gery Hochanadel II\, Program Director of the MBA\, explains:  “Parker University’s MBA program is not only updating current curriculum with AI content that will help students to balance technical AI skills with critical ethical\, clinical\, and data privacy [considerations] as future leaders\, but also\, we are in the early development of an AI Health Care Management related concentration. This will allow students to become more successful healthcare administrators ready to drive safe innovation.”  								\n				\n					\n				\n		\n					\n				\n				\n							\n			\n						\n		\n						\n				\n				\n				\n					Questions People Are Asking 				\n				\n					\n				\n		\n					\n				\n				\n									Will AI replace health information management jobs? The direction of this year’s laws and frameworks points toward more human review\, not less. Rhode Island\, Texas and other states now require people to review AI-generated documentation\, and the AMA’s framework centers on human accountability. The emphasis in HIM work is shifting from managing records toward validating what AI puts into them.  What is agentic AI in healthcare? Agentic AI refers to tools that can complete multi-step tasks on their own\, such as documenting a visit or monitoring a patient\, without a person approving each step. Because an error can carry forward before a clinician steps in\, groups like the AMA are focused on defining what these tools are allowed to do and who is responsible for them.  Does Texas regulate AI in healthcare? Yes. Since Jan. 1\, 2026\, Texas law has required healthcare providers to disclose to patients when an AI system is used in their care. A separate Texas law in effect since Sept. 1\, 2025\, requires practitioners who use AI for diagnosis or treatment recommendations to disclose that use and review AI-generated records.  Do I need a technology background to work in healthcare AI oversight? Not necessarily. The skills showing up in these new laws and frameworks are verification\, documentation integrity\, compliance and judgment: knowing what a correct record looks like and recognizing when an AI output doesn’t match it. Those are core to health information management and healthcare administration training.  Which Parker University programs prepare students for AI in healthcare? Parker’s online Bachelor of Science in Health Information Management teaches students to audit AI-generated summaries\, validate coding recommendations and identify unsupported diagnoses. Parker’s online MBA is integrating AI content into its curriculum\, with an AI-focused healthcare management concentration in early development.  								\n				\n				\n				\n					Build the skills healthcare AI depends on 				\n				\n					\n				\n		\n					\n				\n				\n									Explore Parker’s online Bachelor of Science in Health Information Management or Master of Business Administration\, or request information to talk with admissions about which path fits your goals. 
URL:https://www.parker.edu/event/veterans-day-luncheon/
LOCATION:South 234
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