Articles liés à AI for Healthcare Scheduling & Patient Access:...
AI for Healthcare Scheduling & Patient Access: A Practical Guide to Predictive No-Shows, Intelligent Optimization, and the Future of How Patients Connect with Care - Couverture souple
Livre 1 sur 2: Healthcare AI Playbook Series
Synopsis
Your scheduling system is losing you money. A lot of it.
The average primary care practice loses $150,000–$400,000 per year to no-shows and underutilized capacity. And that's before counting the patients who never get scheduled because they can't get through your phone system, the providers burning out from chaotic schedules, or the competitors building frictionless access while you're still running a manual call center.
AI changes the equation, not with hype, but with prediction, optimization, and automation that healthcare operations leaders can implement starting now.
AI for Healthcare Scheduling & Patient Access is the definitive operational guide for healthcare leaders who want to fix their scheduling systems using artificial intelligence. Written by the Healthcare AI Institute — founded by a physician-executive with two decades of operations leadership across three health systems internationally — this book delivers what most healthcare AI resources don't: specific tools, named vendors, implementation timelines, and frameworks you can use Monday morning.
Inside this book, you'll find:
- How to build the access metrics dashboard that 90% of healthcare organizations are missing, and why no-show rate alone tells you almost nothing useful
- The complete framework for predictive no-show modeling: how it works, which vendors lead the market (Qventus, LeanTaaS, Notable Health, and more), and the four-tier intervention protocol that turns predictions into recovered revenue
- AI-powered schedule optimization that moves beyond "first available" to genuinely optimal appointment matching, with documented 10–20% fill rate improvements
- Patient self-scheduling that actually works: symptom-to-appointment matching, intelligent provider routing, and the design principles that determine whether patients use your digital tools or abandon them
- Strategic overbooking: the math, the guardrails, the provider communication strategy, and why leaving 20% of your capacity empty is a choice, not an inevitability
- Conversational AI for phone and chat scheduling, how voice agents are handling 60–70% of scheduling calls at leading health systems
- A vendor evaluation framework with seven weighted dimensions and the specific questions to ask during demos
- A complete implementation playbook from contract to go-live, including the change management approach that prevents the 60–70% technology implementation failure rate
Whether you run a 5-provider primary care group or a 500-provider health system, this book gives you the knowledge and tools to transform patient access. No data science degree required.
Part of the Healthcare AI Playbook Series, practical AI guides for every healthcare operational domain.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Résultats de recherche pour AI for Healthcare Scheduling & Patient Access:...
Image d'archives
AI for Healthcare Scheduling & Patient Access (Paperback)
impression à la demandeVendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : new. Paperback. Third-next-available has not moved in two years. The template was set by a committee that has since dissolved; half the slots are held by rules nobody can trace to a decision, and the call center is measured on abandonment while the clinic is measured on utilization, so the two of them optimize against each other every single day.Scheduling is where AI is easiest to buy and hardest to bank. A no-show model is only worth what your overbooking policy lets you do with it. An optimizer is only worth what your template governance permits it to change. Buy the model without fixing the policy underneath, and you get a more accurate prediction feeding a schedule that cannot act on it, which is an expensive way to be right.This book works the other order. It starts with the metrics that actually move and the ones that only look like they do, sets the template governance a model needs to be useful, and only then evaluates the tool. It says plainly where the category is thin and which claims to make a vendor demonstrate on your data instead of theirs.What this book will not do. It will not promise you an access improvement, because the size of one depends on your template, your payer mix, and your no-show pattern, none of which a book can see. It does not rank named products. It gives you the measurement and the evaluation method, and leaves the conclusion where it belongs, which is with you and the people who run your schedule.What you will be able to doInstrument access with a metric set that survives a board question, and retire the ones that measure the schedule rather than the patient.Separate demand you can predict from demand you cannot, and stop trying to optimize the second.Set the overbooking and release policy before the no-show model arrives, so the prediction has somewhere to land.Score a scheduling vendor across seven dimensions with weights you set in advance and can defend afterwards.Design a pilot with a baseline, a stop rule and an owner, so it ends in a decision rather than an extension.Say what the tool must show on your own historical data before you sign.The frameworks this book buildsThe access metrics dashboard: the small number of measures that move together, with the definition written down so it cannot drift.The seven-dimension vendor evaluation: capability, integration, workflow fit, evidence, security, service and exit, weighted before you see a demo.The companion instruments. Every framework here is published as a working file in the AI-Powered Scheduling Optimization Toolkit: 6 workbooks and documents in Excel and Word, licensed to a single organization, available separately from the Institute. Data validation on the cells you fill, IFERROR on every division, formula cells protected and your cells left open. The book gives you enough to build these yourself. The toolkit exists so that you do not have to.Written from the operator's chair. Neel Chauhan, MD MBA is a physician-executive whose career spans three national healthcare systems. Quantitative claims carry a named, dated source in the same sentence, or the sentence says where the evidence stops. Composites are labeled as composites. The Healthcare AI Institute accepts no vendor sponsorship, holds no vendor equity and takes no referral fees, which is the only reason a chapter is free to say that a category is not ready. Who this is forAccess leaders, ambulatory COOs and the operations teams who own the schedule. Written for the person who will have to make the template change, not the person who signs the purchase order. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798252683638
Acheter neuf
EUR 24,82
Livraison gratuite
Expédition nationale : Etats-Unis
Expédition nationale : Etats-Unis
Quantité disponible : 1 disponible(s)
Image d'archives
AI for Healthcare Scheduling & Patient Access: A Practical Guide to Predictive No-Shows, Intelligent Optimization, and the Future of How Patients Connect with Care (Healthcare AI Playbook Series)
impression à la demandeVendeur : California Books, Miami, FL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Print on Demand. N° de réf. du vendeur I-9798252683638
Acheter neuf
EUR 24,83
Livraison gratuite
Expédition nationale : Etats-Unis
Expédition nationale : Etats-Unis
Quantité disponible : Plus de 20 disponibles
Image d'archives
AI for Healthcare Scheduling & Patient Access : A Practical Guide to Predictive No-Shows, Intelligent Optimization, and the Future of How Patients Connect with Care
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware. N° de réf. du vendeur 9798252683638
Acheter neuf
EUR 30,87
Expédition à EUR 30,50
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 2 disponible(s)
Image d'archives
AI for Healthcare Scheduling & Patient Access (Paperback)
impression à la demandeVendeur : CitiRetail, Stevenage, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : new. Paperback. Third-next-available has not moved in two years. The template was set by a committee that has since dissolved; half the slots are held by rules nobody can trace to a decision, and the call center is measured on abandonment while the clinic is measured on utilization, so the two of them optimize against each other every single day.Scheduling is where AI is easiest to buy and hardest to bank. A no-show model is only worth what your overbooking policy lets you do with it. An optimizer is only worth what your template governance permits it to change. Buy the model without fixing the policy underneath, and you get a more accurate prediction feeding a schedule that cannot act on it, which is an expensive way to be right.This book works the other order. It starts with the metrics that actually move and the ones that only look like they do, sets the template governance a model needs to be useful, and only then evaluates the tool. It says plainly where the category is thin and which claims to make a vendor demonstrate on your data instead of theirs.What this book will not do. It will not promise you an access improvement, because the size of one depends on your template, your payer mix, and your no-show pattern, none of which a book can see. It does not rank named products. It gives you the measurement and the evaluation method, and leaves the conclusion where it belongs, which is with you and the people who run your schedule.What you will be able to doInstrument access with a metric set that survives a board question, and retire the ones that measure the schedule rather than the patient.Separate demand you can predict from demand you cannot, and stop trying to optimize the second.Set the overbooking and release policy before the no-show model arrives, so the prediction has somewhere to land.Score a scheduling vendor across seven dimensions with weights you set in advance and can defend afterwards.Design a pilot with a baseline, a stop rule and an owner, so it ends in a decision rather than an extension.Say what the tool must show on your own historical data before you sign.The frameworks this book buildsThe access metrics dashboard: the small number of measures that move together, with the definition written down so it cannot drift.The seven-dimension vendor evaluation: capability, integration, workflow fit, evidence, security, service and exit, weighted before you see a demo.The companion instruments. Every framework here is published as a working file in the AI-Powered Scheduling Optimization Toolkit: 6 workbooks and documents in Excel and Word, licensed to a single organization, available separately from the Institute. Data validation on the cells you fill, IFERROR on every division, formula cells protected and your cells left open. The book gives you enough to build these yourself. The toolkit exists so that you do not have to.Written from the operator's chair. Neel Chauhan, MD MBA is a physician-executive whose career spans three national healthcare systems. Quantitative claims carry a named, dated source in the same sentence, or the sentence says where the evidence stops. Composites are labeled as composites. The Healthcare AI Institute accepts no vendor sponsorship, holds no vendor equity and takes no referral fees, which is the only reason a chapter is free to say that a category is not ready. Who this is forAccess leaders, ambulatory COOs and the operations teams who own the schedule. Written for the person who will have to make the template change, not the person who signs the purchase order. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798252683638
Acheter neuf
EUR 32,35
Expédition à EUR 43,06
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
Quantité disponible : 1 disponible(s)