INDEX
Please note that page numbers are not accurate for the e-book edition.
abdominal pain, differential diagnosis of, 40–42
ACE inhibitors, 62
acute myeloid leukemia (AML), 24–25
acute promyelocytic leukemia (APML), 27
acute respiratory distress syndrome (ARDS), 73, 201–2
Adcock, Jack (child with Down’s syndrome), 111–16, 124, 128, 132–33, 143, 181, 197
adrenal insufficiency, diagnosis of, 65–67
adverse events: appropriate responses to, 228–29; Bagian on, 241; definition of, in Harvard Medical Practice Study, 5; internal reviews of, 172; reporting of, 235, 244; as result of handoffs, 120–23. See also medical error
Affordable Care Act (2010), 161–62
Agency for Healthcare Research and Quality (AHRQ), 239–40
(AI) artificial intelligence, 57–59, 128, 237–39
AIDS, harm reduction strategies and, 221
airway protection, in burn treatment, 167
alarms, from medical monitoring devices, prevalence of, 90–92
alerts, EMRs and alert fatigue, 87–92, 101
altruism, in professions, 145
alveoli (air sacs), 73
American Association for Justice (Association of Trial Lawyers of America), 161–62
American Burn Society, transfer criteria for burn victims, 170
American Medical Association, formation of, 136
Amir, Dr. (heme-onc fellow), 30, 51, 71–72, 73, 201–2
AML (acute myeloid leukemia), 24–25
amyloidosis, 62
anemia, diagnosis of, 35–36, 37–38
anesthesia, 176–77, 195, 231
Annals of Internal Medicine, Schimmel article in, 4
APML (acute promyelocytic leukemia), 27
ARDS (acute respiratory distress syndrome), 73
artificial intelligence (AI), 57–59, 128, 237–39
Association of Trial Lawyers of America (American Association for Justice), 161–62
asthma, 62
atelectasis, 75
attending physicians: impact of work rules changes on, 124; July effect and, 126; in digoxin overdose case, 154; responsibilities of, 54, 116; senior doctors as, 111; simulations and, 194; in Zion case, 115. See also McAuliffe, Vincent; Mueller, Dr.
autologous bone marrow transplants, 25
autopsies, decline in numbers of, 40
aviation industry, 8–9, 64–65, 220
Bactrim (antibiotic), 85–87
Bagian, Jim, 240, 241
Bawa-Garba, Hadiza (pediatrics ward registrar), 111–16, 124, 132–33, 143, 181
Bell Commission, 116
Bellevue Hospital: attending physicians, scheduling of, 124; Ebola preparations at, 94; MERS response test, 96–97; work schedule changes at, 119–21. See also Ofri, Danielle
Benadryl (diphenhydramine), 236
bias. See racial bias
BiPAP (breathing mask), 75–76
blame, 134, 241
blood clots in lungs, 62, 207
blood draws, proper procedures for, 198
blood vessels, impact of burns on, 167, 175–76
BMTUs (bone marrow transplant units), 30, 51, 147–49, 202–4, 209
bone marrow biopsies, 22–24
bone marrow transplants, 25, 149
bone marrow transplant units (BMTUs), 30, 51, 147–49, 202–4, 209
Boston Globe, on alarm fatigue deaths, 91
brain: brain-friendly EMR, 185–86; brain-friendly technology, 195; brain-friendly training, 188, 192; information processing by, 187–88; limited bandwidth of, 44, 185–86, 187, 238. See also training on medical error
Bramhall, Simon (transplant surgeon), 132–33, 181
British Medical Journal (BMJ): article on preventable medical error, 1–2, 242–43; cover of patient safety issue, 155–56
bronchitis, 62
B-17 “Flying Fortress” bombers, 8–9
buprenorphine, 221
burns and burn patients, 164–83; ARDS and, 111; assessments of, 167; Communication and Resolution Programs and, 180–83; fluids for, 175–76; Glenn, accident of, 164–66; Glenn, family’s efforts to obtain
treatment information for, 171–73; Glenn, family’s learning of medical errors during treatment of, 175–78; Glenn, family’s notification of errors in treatment of, 169–70; Glenn, outcome of family’s search for
information, 178–83; Glenn, treatment and death, 167–69
camels, MERS virus and, 96
cancer and cancer patients: race and, 130. See also Jay (patient with leukemia)
Car Talk (radio show), 68–69
catheter-related infections, 9–10
causality, problem of determining, 169
CBCs (complete blood counts), 38–40
C. diff (Clostridium difficile bacteria), 232, 235–36
central lines, 9–10, 11
cerebral palsy, 160
certified nurse assistants (CNAs), 216–17
change, as social problem, 13
Charles, Sara, 143–44
checklists: in aviation, 9, 217, 220; for diagnosis, 63–65, 67, 70; early uses of, 10–11, 12; Leape on, 13; limitations of, 11, 13, 15, 198, 231; Nightingale, comparison with, 19; tuning out of, 184
chemotherapy, induction chemotherapy, 26, 27–28
chest X-rays, meaning of negative, 56–57
chief complaints, 84
childbed fever (puerperal fever), 16
childbirth, malpractice cases regarding, 160
Chowdury, Dr. (heme-onc fellow), 30, 54, 148
clinical histories, fevers and, 206. See also history of present illness (HPI)
clinical judicial syndrome, 144
clinical styles, 200
clinics, error reduction and architecture of, 232
Clostridium difficile bacteria (C. diff), 232, 235–36
CNAs (certified nurse assistants), 216–17
Code of Hammurabi, 136
codes (cardiac or pulmonary arrest), 79–82, 83
cognition, 43, 185–86, 188. See also brain; training on medical error
collaboration, 19–20
communication: checklists and, 11; doctornurse, importance of, 95; doctor-patient, importance of, 70, 101; as source of errors, 190, 191
Communication and Resolution Programs (CRPs), 163, 180–83
complete blood counts (CBCs), 38–40
computerized diagnostic systems, 58–60. See also artificial intelligence (AI)
computerized sign-out systems, 121
congestive heart failure, 62
Constance (nurse manager), 76–77, 80–81, 148, 216
contamination in positive blood cultures, 199
content checklists, 63
copper, antimicrobial properties, 232
Core IM (podcast), 66
corporatization of medicine, rise of, 118
cough, as symptoms, differential diagnosis and, 62–63
cowboy medicine, 201
Crimean War, military hospitals during, 18–19
Croskerry, Pat, 63, 64
CRPs (Communication and Resolution Programs), 163, 180–83
CT imaging, increased availability of, 118
culture: cultural shifts, patient safety and, 234–37; culture change, difficulty of, 184–85; of hospitals, 178; importance of, 11, 17; just culture, 181; on medical error, changes to, 179; of medical training, changes to, 123
cyclic neutropenia, 22
Danish Society for Patient Safety, 157
data: data collection issues on patient safety, 241–44; influence on diagnosis, 208
death certificates, data collection from, 243–44
death(s): from alarm fatigue, 91; identifying cause of, 242–43; time of, 82, 83
decubitus ulcers (pressure ulcers), 159
Deep Medicine (Topol), 237
defensive medicine, 142–43, 145
Denmark: handling of medical error, 152–54, 182; Patient Safety Act, 157–58, 239;
patient safety report and follow-up actions, 156–59
diabetes: diabetic ketoacidosis, 190; diabetic retinopathy, 237; race and, 130 diagnosis: checklists for, 63–65, 67, 70; diagnostic systems, 58–60; diagnostic tests, 43, 46–47, 48; diagnostic timeout, 64; differential
diagnosis, 33–35, 40–42, 44, 45–46, 62–63; feedback on, 68–69; as moving target, 40, 41. See also artificial intelligence (AI); diagnostic thinking; names of specific tests
diagnosis, errors in, 33–48; contexts for, 45–48;
diagnostic versus procedural errors, 40; differential diagnoses and, 33–35; EMRs as basis for research on, 47; minimization of, 222–23; Ofri’s missed diagnoses, 35–37, 40, 240–41; in outpatient, primary care setting, 42–45; reporting of, 70; universal antidote to, 62; work schedules and, 118–19 diagnostic thinking, 56–70; cultural shift necessary for improving, 67–69; introduction to, 56–60; IOM report on diagnostic error, 69–70; Ofri’s experiences with, 65–67; question of possible improvements to, 60–65
DIC (disseminated intravascular coagulation), 216
differential diagnosis, 33–35, 40–42, 44, 45–46, 62–63
The Digital Doctor (Wachter), 85
digoxin, 154–55
diphenhydramine (Benadryl), 236
“Diseases of Medical Progress” (Moser), 3
disseminated intravascular coagulation (DIC), 216
diversity, impact on healthcare, 131
doctors: clinical styles of, 200; diagnostic accuracy, 34–35; doctor-patient interactions, 43, 101; identity of, 123, 218; responses to malpractice system, 143–45. See also attending physicians; Everett, Dr.; Mueller, Dr.; Ofri, Danielle; Peterson, Dr.
Dror, Itiel, 184–85, 187–92, 195
drugs. See medications
Duncan, Thomas Eric (Ebola patient), 93–95
DXplain (diagnostic software), 58
dyspnea, 58–59
earthen dams, 164–65
Ebola, 93–95
edema (swelling), in Jay, 53, 71, 76, 78
Ekene (medical student), 129–34
electronic medical records (EMRs), 83–101; alert fatigue and, 87–92; as basis for research on diagnostic errors, 47; brain-friendliness of, 185–86; conclusions on, 100–101; cut-and-paste in, 93, 101, 121, 181; drawbacks of, 98–100; impact of unannounced changes to, 13–15; impact on medical care, 84, 85–88, 92–93, 233–34; in-baskets, 97–98; infection control and, 235–36; introduction to, 83–85; MERS response test, 96–97; rise of, 118; systems-related errors in, 92–93, 95; Texas Ebola cases and, 93–95; time management and, 63, 66; trends in, 39
Ely, John, 63, 64
emergency rooms (ERs), doctors’ rotation coverage of, 166–67
emotions: learning and, 189–90; malpractice cases and, 138; power of, over intellect, 36
emphysema, 62
empyemas, 193
EMRs. See electronic medical records (EMRs)
enalapril (blood pressure medication), 112, 114
endocarditis, 206
endoscopies, 41–42
environmental irritants, 62
Epstein-Barr virus, 63
errors. See medical error
Everett, Dr. (oncologist), 25–26, 29–31, 49–51, 148, 214–15
explicit bias, implicit bias versus, 130–31
extent, of burns, 167
family finances, impact of healthcare decisions on, 25–26
family members, doctors’ and nurses’ relationships with, 210–12
fever, 199, 205–7. See also infections
filgrastim (bone marrow stimulant), 22, 24
finances. See family finances
First Night on Call exercise, 193–94
Florida: birth-related neurological injuries, compensation funds for, 160; obstetricians’ insurance in, 160
fluids, for burn patients, 175–76
“Flying Fortress” (B-17) bombers, 8–9
foreign bodies, removal of, with fever, 199
foreign countries, handling of medical error by, 152–63; Danish system, question of adoption in US, 159–62; Denmark, 152–54; Denmark, Patient Safety Act, 157–58; Denmark, patient safety report and follow-up actions, 156–59; Digoxin overdose case, 154–55; US system, possibilities of improvements to, 162–63
Gallagher, Tom, 171, 179, 180–81, 182
Garcia, Pablo (UCSF Children’s Hospital patient), 85–87, 155
Gawande, Atul, 10
genetic sequencing, advances in, 118
getting help, as method for improving diagnostic
accuracy, 44, 45
Glenn (patient with burns), 164–73; accident of, 164–66; family’s search for information, outcome of, 178–83; family’s search for treatment information on, 171–73; treatment and death, 168–69; treatment errors, complexity and, 197; treatment errors, family’s learning of, 175–78; treatment errors, family’s notification about, 169–70; treatment errors, family’s response to learning of, 178–80. See also Melissa (Glenn’s daughter); Nancy (Glenn’s wife)
Global Trigger Tool, 236–37
Graber, Mark: on diagnostic accuracy, possible improvements to, 44; on diagnostic errors, 70; on diagnostic thinking, 61–62; on differential diagnosis, 44; on getting help, 45; on malpractice cases, EMR-related errors in, 92–93; on overconfidence, 67–68, 69, 212; process checklists, creation of, 63–64
granulomatosis with polyangiitis, 62
Hall, Judith, 134
hallucinations, sedatives and, 72
Hammurabi, King, 136
handoffs, increased, as cause of adverse events, 120–23
hand sanitizers, 232
hand washing, importance of, 10–12, 16–19, 188–89, 223, 228, 232
harm. See patient harms
Harvard Medical Practice Study, 5, 7
“The Hazards of Hospitalization” (Schimmel), 4
healthcare, as human endeavor, 219–20
health courts, 161–62
health insurance, impact on healthcare decisions, 25–26
heart disease, race and, 130
hematocrits, 37–38
heparin, 231–32
hepatitis C, 118, 221
hierarchy(ies): as cause of patient deaths, 12;
patient care and, 178
Hippocrates, 244
history of present illness (HPI), 84
HIV treatments, advances in, 118
hospitalist model, 215
hospitalized patients, as subjects of medical error studies, 7
hospitals: administrators’ concern with financial liability, 110, 138; architecture of, error reduction and, 232; cultures of, 178, 216; difficulty of obtaining information from, 170; responses to Medicare’s fining of, 145; risk management offices, 228; rural hospitals, 166–67. See also Bellevue Hospital
The House of God (Shem), 133
HPI (history of present illness), 84
Hula-Hoop (Wii Fit game), 21
human-factors engineering, patient safety and, 231–32
human factors research, description of, 6
hydration, 167–68, 209
hypotension, training session on, 191
hypovolemic shock, 176
hypoxia, 73
iatrogenic illness, 4
ICUs: central line infections and, 10; in Glenn’s case, 166–68, 172, 176–78, 183; Jay’s failure to be transferred to, 73, 74, 75, 77–80, 139, 147, 149, 197, 200–204, 210, 212; sepsis treatment in, 210; work schedules in, 118–19
immunotherapy, advances in, 118
implementation, importance of, 13–15, 17, 18
implicit (unconscious) bias, 130–31
incentive spirometers, 53
individualism, in US, 184
induction chemotherapy, 26, 27–28
indwelling catheters, 29, 52, 199–200
infections: in central lines, 10; in chemotherapy patients, 31; human-factors engineering for control of, 232; Jay’s, treatment of, 49–55; prevention of, 168, 223; risks of, 30; white count and, 22
influenza, 62
inpatient settings, focus on, in medical error research, 42
in’s and out’s (I’s and O’s), 53
Institute for Healthcare Improvement, Global Trigger Tool, 236–37
Institute of Medicine (IOM, later National Academy of Medicine): report on diagnostic error, 69; report on medical error deaths, 2; report on resident work hours, 117; To Err Is Human, 6–7, 8, 156, 242, 244;
insurance, for hospitals, possibilities of government subsidies for, 162–63
intellect, power of emotions over, 36
intelligence, cognitive shortcuts as basis of, 188
intensivists, 208
intubation, 77, 208, 210, 212–13
IOM. See Institute of Medicine I-PASS (handoff mnemonic), 122
ISABEL (diagnostic software), 58
Jalloh, Hassan (diabetes patient), 99–100
Jay (patient with leukemia): death of, impact on family, 102–10; diagnosis and initial treatments of, 21–32; final illness and death of, 71–82; impact of poor communication on, 101; infection in, treatment of, 49–55. See also Tara Jay (patient with leukemia), analysis of errors in treatment of, 197–218; the big picture, lack of, 208–10; clinical abilities, overconfidence in, 212–13; clinical situation, lack of ownership of, 213–16; ICU, transfer to, 200–204; indwelling catheter, 199–200; introduction to, 197–98; poor clinical evaluation of, 205–8; significant others, not listening to, 210–12; summary of, 216–18; Vacutainer, 198–99
JCAHO (Joint Commission, Joint Commission on Accreditation of Healthcare Organizations), 228–29
Johns Hopkins Hospital, central line infections, 10
Johnsongrass (weed), 165
Joint Commission (Joint Commission on Accreditation of Healthcare Organizations, JCAHO), 228–29
July effect, 126–27
jumbo jet, as metaphor for medical error deaths, 6, 8, 9, 10, 156, 242
juries, health courts versus, 162
Kachalia, Allen, 162
Kalet, Adina, 193–94
Kansas: law on medical malpractice lawsuits, 174; state politics, 179
Kansas Board of Healing Arts, 173
Kansas Foundation for Medical Care, 173, 177
knowledge, increasing, as method for improving diagnostic accuracy, 44–45
lactate, elevated, 111
lawyers, trial lawyers as obstacle to health courts, 161–62
Leape, Lucian, 5–6, 13, 114, 156, 162
legal redress. See malpractice systems and legal redress legal system, impact of money on, 138
Leriche, René, 241
Lilja, Beth, 154–55, 156
litigious environment for healthcare, EMR-related errors and, 92–93
lung cancer, 62
machine learning, reading X-rays and, 57–58. See also artificial intelligence (AI)
Magliozzi, Tom and Ray, 68
Makary, Martin, 10, 242–43
malpractice systems and legal redress, 136–51; in Denmark, 152–54; deposition process, 137; doctors’ responses to malpractice system, 143–45; inefficiencies of, 145; introduction to, 136–37; lawsuits, from Zion and Adcock deaths, 116; lawsuits, public perceptions of, 110; litigation, adversarial nature of, 145; malpractice law, inconsistencies in, 142; malpractice lawyers, selectivity of, 137; proofs of malpractice, 136–37; question of impact on patient safety, 143–47; research on, 5; settlements, 141–42; Tara’s efforts at improved patient safety, 147–51; Tara’s participation in legal case preparation, 138–41; Tara’s possible lawsuit, trauma of, 137–38, 141
Martinez, Jose (baby with heart defect), 154–55
Massachusetts General Hospital, 91
maternal mortality, race and, 130
McAuliffe, Vincent, 206, 214
mechanical ventilation, for septic patients, 210
medical error: burn victims and, 164–83;
complexities of, 230; diagnosis, errors in, 33–48; diagnostic thinking, 56–70;
electronic medical records and, 83–101;
foreign countries’ handling of, 152–63;
inevitability of, 187–88; introduction to, 1–20; Jay (patient with leukemia, analysis of errors in treatment of, 197–218; Jay, final illness and death of, 71–82; Jay, impact of death on family of, 102–10; Jay, infection in, treatment of, 49–55; Jay, initial story of, 21–32; legal redress for, 136–51; patient harm reduction, 219–29; patient safety improvements, 230–44; racial bias and, 129–35; recognition of and recovery from, 188–89; system failures and, 111–28; training on, 184–96. See also adverse events
medical histories, 43, 70, 222
medical information, EMR-forced changes in healthcare professionals’ processing of, 84–85. See also electronic medical records (EMRs)
Medicare, 145, 234
medications: brain-friendly naming of, 195–96;
comparison of patients’ and doctors’ lists of, 222; drug reactions, ARDS and, 111;
medication safe zones, 233–34. See also names of specific medications
medicine (general): brief history of, 2–3; checklists in, 9–12; defensive medicine, 142–43, 145; medical field, humanity of, 135; medical knowledge, vastness of, 45; medical practice, impact of medical records on, 84; medical tests, trending in, 39; medical textbooks, on differential diagnosis, 34; medical training, changes to culture of, 123. See also attending physicians; doctors; nurses; working conditions
Melissa (Glenn’s daughter): CRP training and, 182; efforts to obtain information from hospital, 171–73; father, relationship with, 164; father’s treatment, need for understanding errors in, 170; father’s treatment, response to learning of errors in, 178–80;
malpractice lawsuit, decision to file, 174–75; medical errors, training on, 173–74
Mello, Michelle, 161–62, 163, 182
MERS (Middle East respiratory syndrome), 96–97
methadone, 221
methicillin-resistant staph aureus (MRSA), 53, 56, 71, 198, 200
Middle East respiratory syndrome (MERS), 96–97
military hospitals, during Crimean War, 18–19
minimally invasive surgery, 118
Ministry of Health (Ontario), use of surgical checklists, 11, 13
mold, illnesses caused by, 59
morbidity and mortality conferences (M&Ms), 3, 69, 197
morphine, 75
mortality rates: nurse-to-patient ratios and, 125; of sepsis, 210; weekend effect and, 127
Moser, Robert, 3–4
MRI imaging, increased availability of, 118
MRSA (methicillin-resistant staph aureus), 53, 56, 71, 198, 200
Mueller, Dr. (hematology attending): as director of care for Jay, 215; on elective intubations, 212–13; Jay, first evaluation of, 54; Jay, treatment of, 76–79; possible explanations for actions of, 200–201; possible overconfidence of, 212; Tara and, 74, 80, 138, 148, 211
Mullenix, Peter, 143, 145, 146
multiple myeloma, 36
naloxone kits, 221
Nancy (Glenn’s wife): concern at husband’s non-transference to burn center, 203; CRP training and, 182–83; efforts to obtain information from hospital, 171–73; husband, relationship with, 164–65; with husband in ICU and at burn center, 168–69; husband’s accident, response to, 165–66; husband’s treatment, need for understanding errors in, 170; husband’s treatment, response to learning of errors in, 178–80; malpractice lawsuit, decision to file, 174–75
National Academy of Medicine. See Institute of Medicine National Incident Reporting System (Denmark), 158
National Patient Safety Foundation, 229
National Vaccine Injury Compensation Program, 160–61
natural language processing technology, 237
near misses, 240–41
neutropenia, 22, 197, 199
New England Journal of Medicine, Moser article in, 3
New York Hospital, patient death at, 115
New York State, Bell Commission, 116
New York Times, Pronovost interview in, 12
Nightingale, Florence, vii, 18–19, 61
no-fault compensation system for medical errors, 152–54, 155, 161–62
Notes on Hospitals (Nightingale), 18
nurses: alert fatigue and, 91; in burn units, 168; case ownership by, 216; clinical styles of, 200; depositions in Tara’s legal case, 139–40; drug errors and, 87; empowerment of, through checklists, 12, 19; importance of input of, 20; Jay’s treatment, participation in, 49–50, 52–53, 54–55, 72–73, 76, 78–81;
need for educating, 150; nurse-to-patient ratios, patient mortality rates and, 125;
nursing stations, noise and confusion at, 233; on patient transfers to ICUs, 201; Tara on supposed professionalism of, 218; working conditions as cause of medical error, 125–26. See also Constance; Tara
observation units, 235
obstetricians, costs of insuring, 160
Ofri, Danielle: baby son of, surgery on, 113–14; bone marrow biopsies, experiences with, 23–24; daughter’s illness as teaching moment, 223–28; diabetes patients, confusion over, 99–100; diagnostic thinking of, 64, 65–67; EMR alerts, experiences with, 88–89; EMRs, experience of unannounced changes to, 13–15; medical error deaths, perceptions of, 1–2; medical hierarchy, experiences of, 12–13; medical information processing, EMR-forced changes in, 84–85; missed diagnoses by, 35–37, 40, 240–41; work schedule changes, experiences with, 120–21, 124. See also Bellevue Hospital
Of the Epidemics (Hippocrates), 244
operating rooms, checklists for, 10
ophthalmology, AI diagnosis in, 237
opioid epidemic, 221
organizations, patient safety organizations, 239–41
outpatient, primary care settings, diagnosis in, 42–45
overconfidence, as problem in diagnostic thinking, 67–68
over-testing, under-diagnosis versus, 46–47
pain management, 167–68, 176–77
pancreatitis, ARDS and, 111
parvovirus B19 infections, 63
passwords, 185
patient advocates, 228
Patient Compensation System (Denmark), 153, 155, 158, 182
patient harms, 219–29; from defensive medicine, 142–43; errors and adverse events, appropriate responses to, 228–29; Ofri’s daughter’s illness and harms reduction, 223–28; strategies for harms reduction, 219–23. See also patient safety
patient safety, 230–44; artificial intelligence and, 237–39; collaboration, role in patient safety improvements, 19–20; conclusions on, 244; cultural shifts and, 234–37; data collection issues on, 241–44; human-factors engineering and, 231–32; introduction to, 229–31; medication safe zones, 233–34; nonreporting of errors, reasons for, 240–41;
patient-safety advocates, 146–47; patient safety movement, start of, 8; patient safety organizations, 239–40; staff working conditions and, 115; systems approach to, 241; Tara’s efforts for improvements in, 147–51; Vienna General Hospital, interventions in, 16–17. See also patient harms Patient Safety Act (Denmark, 2003), 157–58, 239
Patient Safety Act (US, 2005), 239
Patient Safety Network, 239–40
Patient Safety Organizations (PSOs), 239
Patient Safety Reporting System (VA), 240
patient turnover, impact on mortality rates, 125
pattern recognition, accuracy in, 57–58
PEA (pulseless electrical activity), 80
penicillin allergies, 157–58
personal experience, simulation programs versus, 190–91, 192
pertussis (whooping cough), 62
Peterson, Dr. (pulmonologist): deposition by, 139; Jay’s case, actions during, 74–76; Jay’s case, lack of ownership of, 215–16; lack of attendance at meeting with Tara, 148; Ofri’s analysis of actions of, 207–8; overconfidence of, 147; possible explanation for actions of, 200–201; Tara’s intentions toward, 138
PET imaging, increased availability of, 118
physical exams: as contributing factor to medical error, 43; fevers and, 206
“The Physician as Pathogen” (Schimmel), 4
pleural effusions, 74, 75
pneumonia, 62, 111, 206
Portero, Emile (diabetes patient), 98–100
post-nasal drip, 62
post-traumatic stress disorder (PTSD), 110
pressors (vasopressors, medication to increase blood pressure), 168, 176, 209–10
pressure ulcers (decubitus ulcers), 159
preventable medical errors, 7–8
prevention of medical error, challenges of, 198
primary care settings, diagnosis in, 42–45
procedural errors, 40, 118
process checklists, 63
Pronovost, Peter, 9–10, 11, 12, 18, 19, 61
PSOs (Patient Safety Organizations), 239
psychogenic cough, 62
PTSD (post-traumatic stress disorder), 110
puerperal fever (childbed fever), 16
pulmonary Langerhans cell histiocytosis, 62
pulseless electrical activity (PEA), 80
Rabøl, Louise, 156–57, 158–59
racial bias, 129–35
radiology units, privatization of, 202–3
rapid response teams, 79–80
relapsing polychondritis, 62
residents (medical), required work hours for, 117–18
risk management offices, 228
Romero, Ms. (patient with cancer), 35–40, 241
root cause analysis, 197
Roter, Debra, 134
rule of nines (in assessing burn extent), 167
rural hospitals, 166–67
sabotage techniques (in training sessions), 191
Samir, Dr., 148
sarcoidosis, 62
Schimmel, Elihu, 3–4
schmutz, on chest X-rays, 57
scope of care, 201
second opinions, 45
sedatives, hallucinations and, 72
Selwin, Dr. (hematologist), 22, 24, 26
Semmelweis, Ignaz, 15–18, 61
sepsis: ARDS and, 111; awareness of, in BMTUs, 209; elevated lactate and, 111, 114; Jay’s, mistreatment of, 149, 205; mortality rates, 210; septic shock, steroids and, 176; Tara’s desire for training on, in Jay’s hospital, 147; training on, 191; treatment of, 209–10. See also Jay (patient with leukemia)
September 11, 2001 terrorist attacks, 156
severity, of burns, 167
shame, error reporting and, 240–41
Shem, Samuel, 133
shortness of breath, 56
sign-out systems, 121
simulation programs, 190–94
Singh, Hardeep: on diagnostic errors, 40, 70; diagnostic error study, 42–44; on diagnostic thinking, 61, 62, 67; on getting help, 45; mentioned, 46; on Ofri’s possible misdiagnosis, 41; process checklists, creation of, 63–64
sinusitis, 62
skin rashes, AI diagnosis of, 237
social safety net, in Denmark, 153
standards of care, 136–37, 146, 153, 176, 227
The Starry Night (van Gogh), 154
state boards, 229
steroids, hypovolemic shock and, 176
supportive care, 209
surgery, minimally invasive, increased availability of, 118
syncope, Jay’s experiences of, 30–32
syngamosis, 62
system failures, 111–28; Adcock death and, 111–15, 116; conclusions on, 128; handoffs, increases in, 121–23; July effect, 126–27; medical error as, 6; nurses’ working conditions, 125–26; as traps, 181; weekend effect, 127; work schedule changes, 116–25; Zion death and, 115–16
tachycardia, 58–59
Tara (ER nurse, wife of Jay, patient with leukemia): after Jay’s diagnosis, 24–26; as Clinician Nurse Educator, 110, 138; efforts at improving patient safety, 147–51; husband’s breathing, concern with, 54–55, 71–73; husband’s chemotherapy and, 28–32; husband’s death, reactions to, 102–10; husband’s diagnosis and, 21–22, 24; husband’s illness, reaction to, 49–50; husband’s infection and, 51–55; and husband’s non-transference from BMTU to ICU, 202–4; husband’s treatment, disappointment in, 216–17; husband’s treatment and death, impact of experiences with, 216–18; on husband’s venous access, 199; husband’s worsening condition, response to, 73–82; legal case preparation, participation in, 137–41; medical team’s lack of regard for, 135, 211–12; physicians’ reactions to, 77–78; possible lawsuit, trauma of, 137–38, 141; on source of husband’s infection, 198; on staff, dealings with, 210–11; as subject of Ofri’s investigation, 217–18. See also Jay (patient with leukemia)
technology: brain-friendly technology, 195; changes to (1996-2016), 117–18; computerized diagnostic systems, 58–60; computerized sign-out systems, 121; natural language processing technology, 237. See also artificial intelligence (AI); electronic medical records (EMRs)
television, popularity of medical shows, 55
Terror of Error technique, 189, 190
testicular torsion, 21–22
test results, in EMR in-baskets, 97–98
Texas Health Presbyterian Hospital, Ebola case, 93–95
thinking processes: cognition, 43, 185–86, 188; fragmentation of, EMRs and, 85, 233–34; sharpening, as method for improving diagnostic accuracy, 45–46. See also diagnostic thinking
thoracentesis, 193
time, importance for diagnosis, 65–67
time of death, arbitrary nature of, 83
To Err Is Human (Institute of Medicine), 6–7, 8, 156, 242, 244
Topol, Eric, 237, 238–39
Toradol, 226
tracheobronchopathia osteochondroplastica, 62
training, for improving diagnosis and treatments, 44–45
training on medical error, 184–96; cognitive consistency, issue of, 185–86; culture change, difficulty of, 184–85; emotions and learning, 189–90; group training, importance of, 190–91; medical errors and, 181; recognition of and recovery from medical error, 188–89, 192; simulation training, 192–94; technology design and, 195; toxic work environments, 186–87; unexpected learning, 191–92
trending, in medical tests, 39
trial lawyers, as obstacle to health courts, 161–62
triggers, in Global Trigger Tool, 236–37
trisomy 11 (AML mutation), 29
tuberculosis, 62
tympanostomy tubes, implantation of, in Ofri’s young son, 113–14
uncertainty: in diagnoses, 61; in medicine, 47
unconscious (implicit) bias, 130–31
under-diagnosis, over-testing versus, 46–47
United States: Danish system of handling medical error, question of adoption in, 159–62; deaths in, causes of, 1; Ebola cases in, 94; first malpractice case, 136; healthcare spending, 159; healthcare system, 25–26, 69–70; individualism in, 184; possible improvements to litigious malpractice system, 162–63; residency programs, workweek standards for interns, 117
upper respiratory infection (URI), 62, 63
usability, 93, 101, 185
vaccines, National Vaccine Injury Compensation Program, 160–61
Vacutainers, errors with, in Jay’s case, 198–99
van Gogh, Vincent, 154
vasopressors (pressors, medication to increase blood pressure), 168, 176, 209–10
Veterans Administration (VA) medical system, Patient Safety Reporting System, 240
Victoria, Queen, 18
Vienna General Hospital, 15–16
Virginia, compensation funds for birth-related neurological injuries, 160
VisualDx (diagnostic software), 58
visual pattern recognition, 57–58
Wachter, Robert: on alert fatigue, 90–91, 92; on EMR alerts, 88; on machines, 101; on medical technology, 85, 86; overdose case and, 155; on smart alarms, 92; on using tools, 100
warfarin, 89–90
Washington Advocates for Patient Safety, 146
weekend effect, 127
white blood cells, 22
whooping cough (pertussis), 62
working conditions: Adcock case and, 111–15, 116; changing regulations, doctors’ responses to, 123; mandated changes to work hours, 116–19, 122; unintended consequences of changing, 123–24; Zion case and, 115, 116
X-rays, non-objectivity of, 57
Yale-New Haven Hospital, medical error study at, 3–4
Zabar, Sondra, 193–94
Zion, Libby (college freshman), 115–16, 124, 128
Zion, Sidney, 116–17