New application areas for speech recognition in the EMR and their effects on patient safety

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New application areas for speech recognition in the EMR and their effects on patient safety

Mert Öz, Product Manager Innovations, Nuance Healthcare

Mert.oez@nuance.com

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Agenda

• EMRs: A bird’s-eye view

• The silver bullet: EMR promise and reality

• Facilitating EMR adoption with speech recognition

• “Not your father’s speech recognition”

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Complex Eco-system of IT Entities

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EMR / EPR / EHR / PHR …

• Many names, many meanings

• Hailed as the key to sustainable healthcare

• US stimulus plan calls for vast government subsidies for EMR adoption

• European Commission: “EMRs should be interoperable by 2015 to ensure cross-border healthcare.”

• Big players increase their activities: Google, Microsoft, IBM, SAP…

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The Cost Promise

• prevent unnecessary costs (labs, images, medications, etc.)

• through improved disease management

• optimize patient management

• help in anti-fraud measures

• reduce malpractice costs

• generate data for developing more cost effective care

• better regulatory compliance (less fines, accurate and timely reimbursement etc)

• …

Efficient hospital: 91% of spendings related to medical care.

Source: Blue Cross Blue Shield of Michigan.

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The Care Promise

• reduce diagnostic & medication errors

• improve treatment through e.g. EBM

• avoid unnecessary procedures & medications

• indulge in preventive care

• raise quality of life through disease management

• educate patients on their condition / treatment plan

• …

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The Reality

• Adoption rate 10-12% in US

• Systems not always used to their full potential or don’t deliver to the promise

• Simply converting paper to electronic forms is not enough

• Adoption barriers and resistance among physicians

EMR adoption: Making physicians happy. Always?

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Adoption challenges

USABILITY

• Costs of implementation / transition / operation

• Interoperability / standards

• Security & privacy concerns

• Costs / benefits alignment

• …

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Speech Recognition in Healthcare today: An Update

Backend– MTSOs– In-house / on-premise with own /

outsourced transcriptionists / editors

Front-end– Mostly radiology– Limited usage in EMRs, but growing

• At specific control points in workflow (e.g. discharge summary)

• “Dictate Anywhere” paradigm: Dragon Medical

Healthcare documentation: Every time has its methods

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Speech Recognition in Healthcare today: Workflow dimension

The classical documentation workflow enhanced with speech recognition.

Raw data

Text

Text attached

EMRReport

Billing

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Speech Recognition in Healthcare today: Workflow dimension

SpeechMagic / Discharge SummarySpeechMagic / Discharge Summary

Status bar Status divider

The patient is a 58 year old male complaining of chest pain and shortness of breath.The Patient has been suffering from hypertension and high cholesterol. The patient is currently on Lipitor and Lisinopril.His father died of an MI in his 60s.The patient smokes one half pack per day. Denies alcohol.]

Physical ExaminationPatient’s vital signs are within normal limits. The patient appears to be in moderate distress. Skin is diaphoretic. Pupils are equal and react to light.

File Tools

SpeechMagic InterActive / Patient Encounter NoteSpeechMagic InterActive / Patient Encounter Note

Status bar Status divider

Chief Complaint[The patient is a 58 year old male complaining of chest pain and shortness of breath.]

Past Medical History[Hypertension and high cholesterol. The patient is currently on Lipitor and Lisinopril.]

Family History[Father died of an MI in his 60s.]

Social History[The patient smokes one half pack per day. Denies alcohol.]

Physical Examination[Patient’s vital signs are within normal limits. The patient appears to be in moderate distress. Skin is diaphoretic. Pupils are equal and react to light. ]

File Tools

Report

Billing

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EMRxIS

Structured, Complex, Multidiciplinary – and Many Actors Usability in the backburner

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Contrast: Dictated Report vs EMR documentation

SpeechMagic InterActive / Patient Encounter NoteSpeechMagic InterActive / Patient Encounter Note

Status bar Status divider

Chief Complaint[The patient is a 58 year old male complaining of chest pain and shortness of breath.]

Past Medical History[Hypertension and high cholesterol. The patient is currently on Lipitor and Lisinopril.]

Family History[Father died of an MI in his 60s.]

Social History[The patient smokes one half pack per day. Denies alcohol.]

Physical Examination[Patient’s vital signs are within normal limits. The patient appears to be in moderate distress. Skin is diaphoretic. Pupils are equal and react to light. ]

File Tools

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Speech Recognition in Healthcare: Workflow dimension

The classical documentation workflow enhanced with speech recognition.

Raw data

Text

Text attached

EMRReport

Billing

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• Parsing• Tagging

Interpretation

Speech Recognition in Healthcare: The Future

Information capturing and processing with advanced speech tools.

Point & Click /

Direct voice entry of

structured info

Actions

Medication check

Reference Lookup

CDSS

Coding

Structured reports

Clinical pathways

Raw data

Text

Actionable information

Clinical Data

Repository

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Evolution of Speech Recognition in Healthcare

SpeechMagic / Discharge SummarySpeechMagic / Discharge Summary

Status bar Status divider

The patient is a 58 year old male complaining of chest pain and shortness of breath.The Patient has been suffering from hypertension and high cholesterol. The patient is currently on Lipitor and Lisinopril.His father died of an MI in his 60s.The patient smokes one half pack per day. Denies alcohol.]

Physical ExaminationPatient’s vital signs are within normal limits. The patient appears to be in moderate distress. Skin is diaphoretic. Pupils are equal and react to light.

File Tools

SpeechMagic InterActive / Patient Encounter NoteSpeechMagic InterActive / Patient Encounter Note

Status bar Status divider

Chief Complaint[The patient is a 58 year old male complaining of chest pain and shortness of breath.]

Past Medical History[Hypertension and high cholesterol. The patient is currently on Lipitor and Lisinopril.]

Family History[Father died of an MI in his 60s.]

Social History[The patient smokes one half pack per day. Denies alcohol.]

Physical Examination[Patient’s vital signs are within normal limits. The patient appears to be in moderate distress. Skin is diaphoretic. Pupils are equal and react to light. ]

File Tools

SpeechMagic InterOp

Status bar

Status divider

Chief Complaint[The patient is a 58 year old male complaining of chest pain and shortness of breath.]

Past Medical History[Hypertension and high cholesterol. The patient is currently on Lipitor and Lisinopril.]

Family History[Father died of an MI in his 60s.]

Social History[The patient smokes one half pack per day. Denies alcohol.]

Physical Examination[Patient’s vital signs are within normal limits. The patient appears to be in moderate distress. Skin is diaphoretic. Pupils are equal and react to light. ]

File Tools

High cholesterol

Shortness of breath

Chest pain

Concepts Medications Map of MedicineICD-10

EMR using Nuance / SpeechMagic with Structured Data

Status bar Status divider

Patient Name:John Doe Allergies:NoneMedications: Lipitor, Lisinopril DoB: 15.5.1951

Chief Complaint

Pyhsical Exam General

Narrative:The patient is a 58 year old male complaining of chest pain and shortness of breath.The Patient has been suffering from hypertension and high cholesterol. The patient is currently on Lipitor and Lisinopril.His father died of an MI in his 60s.The patient smokes one half pack per day. Denies alcohol.

File Tools

High cholesterol

Shortness of breath

Chest pain

Problem List Medications Map of MedicineICD-10

Sinus pain Sore throat SoB Head ache Feeling down ...

Congestion Cough Cough Runny nose Chest pain ...

WNL underweight Moderate distress Severe Distress

asleep awake alert oriented

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Interactive Clinical Documentation

• Demonstration by

– By David Lareau, COO Medicomp

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Booth 1448

Nuance @ HIMSS2009

Integration Partners

Thank you

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A Difficult Fit: EMR and “Classical” Speech Recognition

Not too many places to dictate

SpeechMagic InterActive / Patient Encounter NoteSpeechMagic InterActive / Patient Encounter Note

Status bar Status divider

Chief Complaint[The patient is a 58 year old male complaining of chest pain and shortness of breath.]

Past Medical History[Hypertension and high cholesterol. The patient is currently on Lipitor and Lisinopril.]

Family History[Father died of an MI in his 60s.]

Social History[The patient smokes one half pack per day. Denies alcohol.]

Physical Examination[Patient’s vital signs are within normal limits. The patient appears to be in moderate distress. Skin is diaphoretic. Pupils are equal and react to light. ]

File Tools

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Electronic Medical Record: The Promise -3-

• Ohio State example– Medication turn-around times dropped fully 64 percent.– Radiology order entry turnaround times fell from seven

hours, 37 minutes, to four hours, 21 minutes.– Medical transcription errors were eliminated where the

system was in use. Where it was not yet implemented, errors reached as high as 26 percent.

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Electronic Medical Record: The Promise -4-

• Small Practice example– Dr. Peter Masucci, a pediatrician with his own office in Everett, Mass., embraced electronic

health records to “try to get our practice into the 21st century.” He could not afford conventional software, and chose a Web-based service from Athenahealth, a company supplying online financial and electronic health record services to doctors’ offices. Dr. Masucci was already using Athenahealth’s outsourced financial service, and less than two years ago adopted the online medical record. Today, Dr. Masucci is an enthusiast, talking about the wealth of patient

information, drug interaction warnings and guidelines for care, all in the Web-based records. “Do I see more patients because of this technology? Probably no,” Dr. Masucci said. “But I am doing a better job with the patients I am seeing. It almost forces you to be a better doctor.”

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Electronic Medical Record: The flip side -2-

Cedars-Sinai Medical Center in Los Angeles– … $34 million Computerized Physician Order Entry

system, but only included the input of a few physicians before launching it hospital-wide in late 2002 without thorough training (Connolly, 2005). Physicians who were used to scribbling a few notes by hand were now required to go through nearly a dozen screens and respond to numerous alerts for even common orders. Such usability issues with the “clunky and slow” interface caused more than 400 doctors to demand its removal within three months of its launch (Ornstein, 2003).

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Electronic Medical Record: The flip side -3-

VA Example:– ... display that did not clearly indicate stop orders for treatment,

leading to reported cases of unnecessary drug doses. The Associated Press (2009) reported that “patients at VA health centers were given incorrect doses of drugs, had needed treatments delayed and may have been exposed to other medical errors due to the glitches that showed faulty displays of their electronic health records.” This prompted the chairman of the House Veterans Affairs Committee, Rep. Bob Filner (D-California) to state that "… confidence must be inherent in any electronic medical records system."

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Barriers to implementing EHR

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Barriers to implementing EHR

When inspecting this table, some interesting observations emerge. Certainly, well-known factors like security and cost are cited as key factors, but another theme – usability – floats near the top. Usability is rarely mentioned by name as a barrier to EHR adoption by respondents at these group practices; yet, two of the top five barriers to implementation are related to the usability of EHRs (items 3 and 4). And while implementation costs are important barriers to practitioners, some of the other popularly cited reasons for lack of adoption – security, privacy, and systems integration – are outranked by usability and productivity concerns. Usability issues are also a factor in why EHR implementations fail. In a survey conducted by Linder et al., (Linder, Schnipper, Tsurikova, Melnikas, Volk, & Middleton, 2006), primary care physicians were asked to list reasons they did not use the EHRs available to them. Thirty-five percent of those physicians listed specific EHR usability issues, the most common of which were: problems with screen navigation, no access to secondary functions, and concerns that data will be lost. Anecdotal support for usability and EHR failure comes from Cedars-Sinai Medical Center in Los Angeles.

developed a $34 million Computerized Physician Order Entry system, but only included the input of a few physicians before launching it hospital-wide in late 2002 without thorough training (Connolly, 2005). Physicians who were used to scribbling a few notes by hand were now required to go through nearly a dozen screens and respond to numerous alerts for even common orders. Such usability issues with the “clunky and slow” interface caused more than 400 doctors to demand its removal within three months of its launch (Ornstein, 2003). Poor usability can also endanger patient health. One example of a usability failure was a display that did not clearly indicate stop orders for treatment, leading to reported cases of unnecessary drug doses. The Associated Press (2009) reported that “patients at VA health centers were given incorrect doses of drugs, had needed treatments delayed and may have been exposed to other medical errors due to the glitches that showed faulty displays of their electronic health records.” This prompted the chairman of the House Veterans Affairs Committee, Rep. Bob Filner (D-California) to that "… confidence must be inherent in any electronic medical records system.“ Clearly, there is a dissociation between the importance of usability and its lack of inclusion in the procurement process. On one hand, we have usability being a main barrier to entry and a significant reason for lack of acceptance, and on the other, we have seen that usability is largely ignored during the procurement process.

Defining usability: usability goals must be set by specifying target values for effectiveness, efficiency, and satisfaction. For each product, these attributes should be measured in order to compare products to each other and to the usability goals.

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Other Countries' Experience : examples of EHR adoption

Source: How to Select an Electronic Health Record System that Healthcare Professionals can Use   

User Centric, Inc.

February 2009