Читать книгу Transforming Healthcare Analytics - Michael N. Lewis - Страница 2
ОглавлениеTable of Contents
1 Cover
5 CHAPTER 1: Introduction PURPOSE OF THIS BOOK HEALTH DATA DEFINED HEALTHCARE CHALLENGES AND FOCUS AREAS AUDIENCE FOR THIS BOOK HOW TO READ THIS BOOK STATE OF HEALTHCARE HEALTH TECHNOLOGY HEALTH RESEARCH MEDICAL PROCEDURES GROWTH IN HEALTHCARE HEALTHCARE DATA MULTIFACETED AND SILOED DATA UNSTRUCTURED DATA STRICT REGULATIONS VALUE OF ANALYTICS NOTES
6 CHAPTER 2: People THE ABILITY TO PRODUCE RESULTS WHAT TYPES OF ROLES? WHAT JOB ROLES DO YOU NEED? ORGANIZATIONAL STRUCTURES FOR YOUR COMPANY ROLES TO EXECUTE YOUR DATA AND ANALYTICS STRATEGY CHALLENGES TO GETTING THE RIGHT PEOPLE THE ABILITY TO CONSUME RESULTS THE “REAL ANALYTICAL EMPLOYEE COST” TO AN ORGANIZATION BUILDING A RESOURCE LIBRARY CONCLUSION NOTES
7 CHAPTER 3: Process WHAT IS CULTURE? WHAT IS DESIGN THINKING? WHAT IS LEAN? WHAT IS AGILE? DESIGN THINKING, LEAN, AND AGILE DEFINITIONS CREATING A DATA MANAGEMENT AND ANALYTICS PROCESS FRAMEWORK CHANGING THE ANALYTICS JOURNEY WHAT IS THE CURRENT PROCESS? NOTES
8 CHAPTER 4: Technology STATUS QUO IN-DATABASE PROCESSING IN-MEMORY PROCESSING OPEN SOURCE TECHNOLOGY HADOOP SPARK PYTHON R OPEN SOURCE BEST PRACTICES NOTES
9 CHAPTER 5: Unifying People, Process, and Technology PEOPLE USE CASE – DELIVERING PRIMARY CARE PREDICTIVE RISK MODEL PROCESS USE CASE – RATE REALIZATION MODEL TECHNOLOGY USE CASE – POPULATION HEALTH MANAGEMENT APPLICATION INTEGRATING PEOPLE, PROCESS, AND TECHNOLOGY – ENHANCING CLEVELAND CLINIC WEEKLY OPERATIONAL MEETINGS/CORPORATE STATISTICS DASHBOARDS CASE STUDY TAKEAWAYS CONCLUSION
10 CHAPTER 6: The Future in Healthcare CLOUD SECURITY INTERNET OF THINGS AI – ARTIFICIAL (AND AUGMENTED) INTELLIGENCE VIRTUAL REALITY – TEACHING, EDUCATION, LAB NOTES
11 CHAPTER 7: Final Thoughts FINAL THOUGHTS INDUSTRY TRANSFORMATION JOURNEY TO VALUE-BASED CARE INVESTMENT VS. RETURNS ON TECHNOLOGY AND INNOVATION APPLYING AUGMENTED INTELLIGENCE TO SUPPORT CLINICAL, OPERATIONAL, AND FINANCIAL OUTCOMES ENGAGEMENT ON THE HEALTHCARE DELIVERY MODEL TO UNDERSTAND EXPERIENCES AND VIEWPOINTS TO CREATE TRUST BETWEEN PROVIDERS AND PATIENTS CONCLUSION KEY TAKEAWAYS
12 Index
List of Tables
1 Chapter 2Table 2.1 Assets Within an OrganizationTable 2.2 Traditional Quantitative Business Analytics TechniquesTable 2.3 Machine Learning AlgorithmsTable 2.4 Typical Storytelling SkillsTable 2.5 General Business SkillsTable 2.6 Sample of Healthcare Business Acumen Questions
2 Chapter 4Table 4.1 Data Sources
3 Chapter 5Table 5.1 Surgical and E and M Forecast Model Performance
4 Chapter 6Table 6.1 IoT in Industries
List of Illustrations
1 Chapter 1Figure 1.1 Storage of Your Medical RecordsFigure 1.2 Sources of Health Data: From Paper to DigitalFigure 1.3 Major Advancements in HealthcareFigure 1.4 Uniqueness of Healthcare Data
2 Chapter 2Figure 2.1 What Is an Analyst?Figure 2.2 The Analytics Maturity CurveFigure 2.3 Four Capability Pillars to Support Your Analytics StrategyFigure 2.4 A3 Title: What Are You Talking About?Figure 2.5 Skills MapFigure 2.6 Basic Organizational Models
3 Chapter 3Figure 3.1 Process FrameworkFigure 3.2 Getting-Ready-for-Work ProcessFigure 3.3 Traditional Process WorkflowFigure 3.4 The Analytics Maturity CurveFigure 3.5 Evolving Process Workflow
4 Chapter 4Figure 4.1 Traditional Approach to Data and AnalyticsFigure 4.2 In-Database Processing ApproachFigure 4.3 In-Memory Processing ApproachFigure 4.4 Hadoop ArchitectureFigure 4.5 Data Analysis with Python and R
5 Chapter 5Figure 5.1 Traditional Work SilosFigure 5.2 The Work Is Converging
Pages
1 ii
2 iii
3 iv
4 v
5 vi
6 vii
7 xi
8 xii
9 xiii
10 xiv
11 xv
12 xvii
13 xviii
14 xix
15 1
16 2
17 3
18 4
19 5
20 6
21 7
22 8
23 9
24 10
25 11
26 12
27 13
28 14
29 15
30 16
31 17
32 18
33 19
34 20
35 21
36 22
37 23
38 24
39 25
40 26
41 27
42 28
43 29
44 30
45 31
46 33
47 34
48 35
49 36
50 37
51 38
52 39
53 40
54 41
55 42
56 43
57 44
58 45
59 46
60 47
61 48
62 49
63 50
64 51
65 52
66 53
67 54
68 55
69 56
70 57
71 58
72 59
73 60
74 61
75 62
76 63
77 64
78 65
79 66
80 67
81 68
82 69
83 70
84 71
85 72
86 73
87 74
88 75
89 76
90 77
91 78
92 79
93 80
94 81
95 82
96 83
97 84
98 85
99 86
100 87
101 88
102 89
103 90
104 91
105 92
106 93
107 94
108 95
109 96
110 97
111 98
112 99
113 100
114 101
115 102
116 103
117 104
118 105
119 106
120 107
121 108
122 109
123 110
124 111
125 112
126 113
127 114
128 115
129 116
130 117
131 118
132 119
133 120
134 121
135 122
136 123
137 125
138 126
139 127
140 128
141 129
142 130
143 131
144 132
145 133
146 134
147 135
148 136
149 137
150 138
151 139
152 140
153 141
154 142
155 143
156 144
157 145
158 146
159 147
160 148
161 149
162 150
163 151
164 152
165 153
166 154
167 155
168 156
169 157
170 158
171 159
172 160
173 161
174 162
175 163
176 164
177 165
178 166
179 167
180 168
181 169
182 170
183 171
184 172
185 173
186 174
187 175
188 176
189 177
190 178
191 179
192 180
193 181
194 182
195 183
196 184
197 185
198 186
199 187
200 188
201 189
202 190
203 191
204 192
205 193
206 194
207 195
208 196
209 197
210 198
211 199
212 200
213 201
214 202
215 203
216 204
217 205
218 206
219 207
220 208
221 209
222 210
223 211
224 212
225 213
226 214
227 215
228 216
229 217
230 218
231 219
232 220
233 221
234 222
235 223
236 224
237 225
238 226
239 227
240 228
241 229
242 230
243 231
244 232
245 233
246 234
247 235
248 236
249 237
250 238
251 239
252 240
253 241
254 242
255 243
256 244
257 245
258 246
259 247
260 248
261 249
262 250
263 251
264 252
265 253
266 254
267 255
268 256
269 257
270 258
271 259
272 260
273 261
274 262
275 263
276 264
277 265
278 266
279 267
280 268
281 269
